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Parental influence on physical activity in Hispanic and non-Hispanic white children

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Parental influence on physical activity in Hispanic and non-Hispanic white children
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Barry, Mary J
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Denver, CO
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University of Colorado Denver
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English
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xiv, 164 leaves : ; 28 cm

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Exercise ( lcsh )
Parental influences ( lcsh )
Hispanic American children ( lcsh )
Children, White -- United States ( lcsh )
Children, White ( fast )
Exercise ( fast )
Hispanic American children ( fast )
Parental influences ( fast )
United States ( fast )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Includes bibliographical references (leaves 154-164).
Thesis:
Health and behavioral sciences
General Note:
Department of Health and Behavioral Sciences
Statement of Responsibility:
by Mary J. Barry.

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ocm47058263
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Full Text
PARENTAL INFLUENCE ON PHYSICAL ACTIVITY
IN HISPANIC AND NON-HISPANIC
WHITE CHILDREN
by
Mary J. Barry
B.S.N., University of Colorado Health Sciences Center 1979
M.S., Chapman University, 1988
A thesis submitted to the
University of Colorado at Denver
in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Health and Behavioral Sciences
2000


This thesis for Doctor of Philosophy
degree by
Mary J. Barry
has been approved
by
Date
j 2.OOP


Barry, Mary J. (Ph.D., Health and Behavioral Sciences)
Parental Influence on Physical Activity in Hispanic and Non-Hispanic White
Children
Thesis directed by Associate Professor Stacy Zamudio
ABSTRACT
The purpose of this study was to identify social, psychological and
environmental determinants of 3-5th grade Hispanic and non-Hispanic white
(NHW), and high and low socioeconomic status (SES) children's physical
activity.
To predict children's physical activity level we measured: (1) children's
perceived athletic competence, (2) parent prioritization of activity for
themselves, (3) parent ranking of the importance of physical activity, (4)
parent perceived family activity/recreation environment; and (5) parent total
physical activity. Physical activity was measured using uniaxial
accelerometers in parents (51 non-Hispanic white, 48 Hispanic, 48 high
SES and 51 low SES families) and their children over 7 days. Each
predictor variable was explored to assess for possible interaction between
ethnicity and SES.
Socioeconomic status had a greater influence on childrens physical
activity than ethnicity in this sample. Non-Hispanic white and high SES
mothers scored higher on their perceived importance of family
activity/recreation, prioritization of physical activity for themselves, and were
more physically active than Hispanic and low SES mothers. High SES
mothers had greater ranking of the importance of physical activity than low
SES mothers. There was an interaction between SES and ethnicity across
all mothers such that low SES Hispanic and high SES NHW mothers had
greater prioritization of physical activity for themselves and total physical
activity than high SES Hispanic and low SES NHW mothers. High SES
mothers valuation of physical activity was greater than low SES mothers.
There were no differences in physical activity levels between Hispanic vs.
NHW and high and low vs. high SES children, yet Hispanic and low SES
children's BMIs were higher than NHW and high SES children's BMIs.


There are no differences between Hispanic vs. NHW fathers' predictor
variables nor did any of fathers' data relate to children's physical activity
levels or perceived competence. High SES fathers had greater perceived
family activity/recreation environment than low SES fathers. For all groups,
children's physical activity was best predicted by children's perceived
athletic competence. A re-specified model was developed and tested
resulting in mothers' physical activity and prioritization affecting familys
activity/recreation and thus, children's perceived athletic competence and
physical activity.
This abstract accurately represents the content of the candidates thesis. I
recommend its publication.
IV


DEDICATION
I dedicate this thesis to all those who have supported, encouraged,
whined, tolerated and loved me through the process. To my running
buddies who never acted bored and even pretended to listen; to my sisters
who have always inspired me and certainly have been my biggest fans,
especially to my sissy, Janny, who helped me with Cro-Magnon analyses,
bragged to her friends unnecessarily, and never once told me I was crazy,
even though she thought I was; of course to my mom and dad who DID tell
me I was crazy but nonetheless, set the foundation for all my successes in
life. To my friends (Mickey and Gene, Mary Jo, Gina, Mary H. and John,
Cecilia, Marcia, Mary D. and Jim, Lauren) who must have wanted to check
me off their lists, but never failed to include me in get-togethers and routine
phone calls to check-in; to my classmates, especially to my pal Meredith,
who REALLY understood the hoops of academia and who permitted many
whining sessions; to my committee chair, Stacy Zamudio, who never quit
pushing the standards for excellence, never lost her patience, and most
importantly never stopped believing in me. Stacys commitment and
dedication to her students is extraordinary. Finally and most importantly, I
dedicate this thesis to my ultimate supporters, Frank, Colleen, and Megan,
who lived through the process day in and day out. They never
complained about my tuning out, late nights at school, data collection
panics, too many fast food burrito dinners, missed soccer, school, and
social events. It is inconceivable the tolerance and loving support they
sustained over these past few years. It took more than a village. Thank
you.


ACKNOWLEDGEMENT
My most sincere thanks go to my committee members, Stacy
Zamudio, Susan Johnson, David Tracer, and Nancy Hester. Stacy, who
was my consistent support and stabilizing force; Susan, who persevered
the process from the very beginning when I was truly green and taught me
everything I needed to know about the infamous process; David, who
shared in my tribulations during data collection but always shared in the
peaks and valleys; Nancy who amidst her changing life, made time when
there was none; Carol Vojir, who at the end threw in life saving statistical
advice; and Ed Melanson, who provided expert guidance with physical
activity data. No words can express my gratitude for your hours of
dedication. Thank you all.


CONTENTS
Figures.....................,...........................xii
Tables ................................................. xiii
CHAPTER
1. INTRODUCTION.........................................1
Background ....................................1
Determinants of Physical Activity in Hispanic and
non-Hispanic White Children ...................4
The Energy Equation and Definition of BMI ... 4
Physical Activity and Its Health Related
Effects On Children......................6
Factors Influencing Childrens Physical
Activity.................................9
2. THEORETICAL ISSUES AND MODELS ......................24
Social Cognitive Theory ....................26
Parent Cognition .......................36
3. RESEARCH QUESTION AND PRELIMINARY DATA .... 39
Research Question.............................39
Hypotheses .............................40
Preliminary Data..............................41
VII


Questionnaire Development ..............41
Physical Activity Prioritization Survey
Questions.................................42
Pilot Questionnaire Results...............45
4. RESEARCH DESIGN AND METHODS ..........................47
Overview .......................................47
Subjects..................................49
Subject Payment...........................51
Measurements..............................51
5. DATA ANALYSES AND RESULTS :...........................60
Data Analyses ..................................60
Results.........................................64
Descriptive Data and Ethnicity............64
Parent and Child Data by Sex and Ethnicity......65
Differences in Mothers Variables by Ethnicity.65
Differences in Fathers Variables by Ethnicity .67
Childrens Results for Ethnicity................68
Socioeconomic Status ...........................71
Parent and Child Data by Sex and
Socioeconomic Status......................72
Differences in Mothers Variables by
Socioeconomic Status......................72
Status ...................................72
VIII


Differences in Fathers Variables by
Socioeconomic Status.......................74
Differences in Childrens Variables by
Socioeconomic Status.......................74
Interaction Between Socioeconomic Status
And Ethnicity ....................................77
Correlation Analyses.......................79
Mothers Correlation Data .................79
Fathers Correlation Data..................81
Multiple Regression Analyses .................... 85
Mothers ...................................85
Fathers....................................86
Model Restructure ................................86
Hypotheses .......................................87
Mothers....................................90
Fathers....................................92
Summary of Theorized Hypotheses............93
Qualitative Data .................................94
6. DISCUSSION AND CONCLUSION .............................98
Discussion .......................................98
Main Findings Compared with Past Studies.......100
Childrens Athletic Competence and
Childrens Physical Activity .............100
ix


SES and Childrens Physical Activity
101
Ethnicity, Childrens Physical Activity,
and BMI .................................103
Mothers vs. Fathers Influence on
Childrens Physical Activity ............105
Organized Sports and Childrens Physical
Activity.................................106
Parent and Child Physical Activity
Relationship.............................107
Summary of Relationship Between SCT and
Childrens Physical Activity...................108
Weaknesses and Strengths of Study..............110
Future Research Questions......................114
Conclusion ....................................116
APPENDIX
A. EVIDENCE TABLES OF CRITICAL STUDIES
RELATED TO PHYSICAL ACTIVITY IN CHILDREN .... 118
B. SURVEY INSTRUMENTS.....................................134
Socioeconomic Status Questionnaire.............135
Family Environment Scale ......................136
Harter Scale...................................140
Prioritization Questionnaire ..................143
C..........................................................145
Introductory Letter to Parents.................146
x


Guidelines for Prioritization Questionnaire..147
Information for Accelerometers ................148
7 Day Monitoring Record .......................149
D..........................................................150
Parent Consent ................................151
Children Assent ...............................153
REFERENCES.......................................................154
XI


FIGURES
Figure
2.1 Banduras Triadic Model .......................................26
2.2 Social Cognitive Model of Parental Influence ................. 28
2.3 Role Modeling/Observation Learning.............................32
2.4 Environment/Situation .........................................34
2.5 Self-Efficacy..................................................36
2.6 Parent Cognition ..............................................38
5.1 Model........................................................ 63
5.2 Theorized Model to Be Tested...................................87
5.3 Re-specified Model Related to Mothers Variables ..............91
5.4 Re-specified Model Related to Fathers Variables..............92
XII


TABLES
Table
1. Percentiles for BMI in U.S. Children 8-10 Years .................7
2.1 Theories and Models.............................................25
4.1 Total Daily Energy Expenditures (kcal/kg/day) ..................47
4.2 Summary of Parent and Child Measurements........................59
5.1 Mothers and Fathers Variables for Ethnicity ....................66
5.2 Childrens Variables for Ethnicity..............................69
5.3 Mothers and Fathers Variables for SES ..........................73
5.4 Childrens Variables for SES................................... 76
5.5 Hispanic Mothers Correlation ..................................79
5.6 Non-Hispanic White Mothers Correlation Matrix..................80
5.7 High SES Mothers Correlation Matrix............................80
5.8 Low SES Mothers Correlation Matrix ............................81
5.9 Fathers Correlation Data.......................................82
5.10 Non-Hispanic White FathersCorrelation atrix ...................83
5.11 High SES FathersCorrelation Matrix ............................83
5.12 Low SES Fathers Correlation Matrix.............................84
XIII


5.13 Hypotheses Summary.....................................93
5.14 Responses From PAPS....................................95
XIV


CHAPTER 1
INTRODUCTION
Background
Our technologically advanced environment permits less energy
expenditure in day to day life and promotes increased sedentary lifestyles.
Twenty percent of United States children participate in two or fewer bouts
of vigorous activity per week, and girls are especially likely not to exercise
vigorously (26% versus 17% in boys (NHANES III). Further, 26% of
children watch four or more hours of television daily. Boys and girls who
watch four or more hours/day of television have higher body fat (e_< .001)
and body mass index (BMI) (g < .001) than children who watch less than 2
hours/day of television (Anderson et al., 1998). Despite the health benefits
of regular physical activity (protection from cardiovascular disease,
hypertension, obesity and poor self-image) (Baranowski et al., 1992),
children are not meeting national health objectives of daily light to moderate
physical activity for 30 minutes/day (USDHHS, 1990, Kann et al., 1996).
Energy expended through physical activity helps to maintain the
balance between calories consumed (energy input) and calories burned
(energy expenditure). When energy intake exceeds the sum of energy
1


expenditure and basal metabolic rate (BMR), weight gain results. Physical
activity has been shown to diminish the prevalence of obesity,
cardiovascular disease, and diabetes in adults (Bouchard, et al., 1994).
Obesity has increased nationwide with obesity rates over 14% in four states
in 1991 to thirty-seven states by 1998 (www.cdc.qov. 2000). The
increasing prevalence of obesity in US children (25%) with 40% having at
least one cardiovascular risk factor related to being overweight (Troiano et
al., 1998) suggests that children are less active now than they have been in
the past (Baranowski et al, 1987) and thus are at increased risk for
cardiovascular disease and diabetes. Obesity and the diseases linked to it
are more common in women than men, more prevalent in lower
socioeconomic status (SES) groups, those with less education, and
minorities (USDHHS, 1996). Minority groups, especially Latinos and
Hispanics, are more likely to be inactive and consistently have larger body
mass indices (BMI)than Euro-Americans (NHANES III, Robinson, 1995).
Exercise habits formed early in life impact upon later behavior. Less
active children remain less active into adolescence and adulthood (Pate et
al., 1996). Obesity in childhood after the age of 6 years increases the
probability of obesity in young adulthood (21-29 years of age) by 50%.
Non-obese children, in comparison, have a 10% probability of obesity in
adulthood. Moreover, obese children with at least one obese parent have a
2


79% higher risk of remaining obese into adulthood than children without an
obese parent (Whitaker et al., 1997).
Developing and maintaining healthy activity levels in youth (30
minutes of daily light-moderate physical activity) appears to be an effective
way to prevent childhood obesity (USDHHS, 1996). In a society where
high fat foods are readily available and aggressively promoted, regular
exercise can prevent obesity and health-related diseases throughout
childhood, adolescence, and ultimately adulthood (Stefanick, 1993).
Physical activity in youth is a modifiable behavior that correlates with
diverse environmental, psychological and sociocultural influences.
Presently, there is limited understanding of factors that influence
childrens physical activity, particularly in minority children. Understanding
the determinants of physical activity in minority children is crucial in
preventing the onset of obesity, particularly in Hispanics who represent the
fastest growing segment of the United Stafes^population (Rauh et al.,
1992). Although several recent studies have examined psychosocial and
environmental determinants of physical activity in African-American and
Caucasian children (Trost et al., 1999, Lindquist et al., 1999), Hispanic
populations have been under-investigated with respect to physical activity.
3


Determinants of Physical Activity in Hispanic and
non-Hispanic White Children
This section begins by describing important measurements used to
characterize weight: first, the energy equation and second, the definition of
body mass index. Next, physical activity and its health related effects in
children are described. Then the factors that influence childrens physical
activity are explored. Finally, intervention strategies are summarized.
The Energy Equation and Definition of BMI
Energy balance and weight stability depend on the relationship
between calories consumed (energy input) and calories burned (energy
expenditure). Total energy expenditure is determined by the cumulative
effects of resting metabolic rate (RMR), the thermic effect of food (TEF),
and physical activity, which increases metabolic rate and therefore
increases energy expenditure (DeLany & Lovejoy, 1996).
Stored energy reserves develops when energy intake exceeds
energy expenditure. All else being equal, physical activity, the most
variable and modifiable component of an individuals energy balance
(DeLany & Lovejoy, 1996), has been shown to prevent weight gain and
protect against the onset of obesity in adults (Grilo, 1995; Stefanick, 1993)
but there is no direct evidence of this influence in children. Prospective
4


investigations have shown men and women who reported higher physical
activity at baseline and follow-up (over 10 years) gained less weight than
those who reported less activity (Kahn et al., 1997, Williamson et al., 1993).
These findings support the widely held belief that more physically active
adults have a lowered incidence of obesity and gain less weight over time.
Accordingly, increasing levels of obesity in US children, concurrent with the
fact physical activity levels decline with age (Sallis, 1993), suggest that
similar trends also apply to children. While it is clear that physical activity
declines with age, there is accumulating evidence that physical activity,
fitness and endurance among youth has declined over the past several
decades (Luepker, 1999).
Body mass index (BMI; weight in kilograms/height in meters2) is a
reliable measure of overweight and obesity status in children and
adolescents (Rosner et al, 1998). Dual photon absorptiometry (DXA), a
gold standard measure of body composition, has demonstrated that body
fat is correlated (r = .79-.83) with BMI, supporting the use of BMI as a valid
measure of body composition in children and adolescents (Pietrobelli et al,
1998).
Adults are overweight when their BMI is between 25.0 and 29.9.
Adults are obese when their BMI exceeds 30.0 kilograms/meter2. These
definitions of what comprises overweight versus obese are based on the
5


National Health and Nutrition Examination Survey (NHANES I) (Must et al.,
1991). The Expert Committee on Clinical Guidelines for Overweight in
Adolescent Preventive Services defined overweight as BMI equal to or in
excess of the 95th percentile for age and gender or greater than 30 kg/m2,
whichever is smaller (Rosner et al., 1998). Table 1.1 shows the percentile
ranking of BMI for children aged 8, 9, and 10 years. Both sex and ethic
differences are included and serve as a screening tool to identify those
children at risk for overweight and obesity.
Physical Activity and Its Health Related
Effects in Children
The specific health effects of physical activity have primarily been
studied in adults and adolescents; data are limited in younger children
(Rigotti et al., 1984, Tipton et al., 1983, Surgeon General Report, 1996).
There is little evidence that exercise in the growing years directly improves
the health of children; yet exercise in adolescence contributes to favorable
health status into adulthood. Results from the Harvard alumni study show
that young adults who were active as children and became sedentary in
their adult years had a higher risk of coronary artery disease when
compared to those individuals who continued to be active (Paffenbarger et
al., 1986). These data suggest that continuous participation in daily activity
6


starting in young adulthood provide long-term health benefits. For the most
part, we can infer that children who are physically active throughout
childhood and adolescence may be more likely to continue being active as
adults (Blair et al.,1989). Thus, increasing physical activity (the amount of
movement performed on a daily basis) in childhood may be one approach
to the prevention of disease later in life.
Table 1.1 Percentiles for BMI in U.S. Children 8-10 Years
Age Percentile GIRLS BOYS
Hispanic White Hispanic White
8 years 5% 14.0 13.5 14.2 14.1
15% 14.9 14.3 15.1 14.9
50% 16.3 15.7 16.6 16.2
75% 18.8 17.4 18.3 17.5
85% 20.2 18.6 19.5 18.6
95% 22.9 21.2 22.7 21.4
9 years 5% 14.1 13.6 14.4 14.3
15% 15.1 14.5 15.4 15.1
50% 16.9 16.2 17 16.6
75% 19.7 18.3 19.1 18.3
85% 21.4 19.7 20.7 19.7
95% 24.3 22.6 24.4 23.0
10 years 5% 14.4 13.9 14.7 14.6
15% 15.5 14.9 15.6 15.4
50% 17.6 16.9 17.6 17.1
75% 20.8 19.3 20.0 19.2
85% 22.7 21.0 21.9 20.9
95% 25.8 24.1 25.9 24.5
Note: Adapted from Rosner et al., 1997.
7


Few studies have focused on the health effects of physical activity in
young children. Research has focused primarily on children aged 11-21
years (preadolescence through young adulthood) and shows that; 1)
physical fitness is minimally correlated (r = .17) with physical activity
(Morrow & Freedson, 1994); 2) physical activity is positively associated with
self-esteem, self-concept, or self-efficacy (Calfas & Taylor, 1994); and 3)
the amount of energy expenditure and the degree of adiposity found in
adolescents is not necessarily correlated, with various studies unable to
find a relationship (Bar-Or& Baranowski, 1994).
Studies examining physical activity relative to the degree of adiposity
in children are inconsistent. One study found total energy expenditure,
measured by doubly labeled water and room calorimetry, between obese
and lean prepubertal children to be similar (Treuth et al., 1998). However,
there was a 14kg weight difference between the heaviest and the leanest
children, but no difference in their fat-free mass (underlying lean tissue
mass was similar). When the lack of difference in fat-free mass between
the lean and obese children was accounted for, obese children were found
to have reduced activity levels (DeLany et al., 1995 and Treuth et al.,
1998). Cross-sectional studies of body composition show that greater
physical activity is correlated with less fat mass in children (DeLany, 1998).
However, longitudinal studies examining exercise in relationship to the
8


changes in body composition that occur in preadolescents, show no
relationship between fat mass and energy expenditure (Goran et al., 1998).
The developmental changes seen in children as they approach
adolescence, in combination with the physiological differences between
sexes, may contribute to the inconsistent findings in the research relating to
the role of physical activity and its impact on obesity (Goran et al., 1999).
Furthermore, the difficulty associated with accurate measurement of
physical activity may explain the disparity seen in the aforementioned
studies between energy expenditure and adiposity in young children.
Because physical activity is essential to the regulation of energy
balance, numerous studies have investigated an alternative mechanism,
physical inactivity, to help explain the etiology of childhood obesity.
Physical inactivity has been examined for the purpose of exploring
behaviors that may replace time spent being physically active.
Factors Influencing Childrens Physical Activity
Many factors influence childrens patterns of physical activity,
including access to sedentary play, their parents beliefs and attitudes, their
parents level of activity, and the childrens ethnicity. These are further
described, below.
9


Access to Sedentary Plav. Television viewing, video game playing,
and personal computing have been studied as potential contributors to
childhood inactivity and subsequent obesity (Dietz & Gortmaker, 1985,
Gortmaker et al., 1996, Bouchard, 1997, Robinson & Killen, 1995). One
study of 1,912 ethnically diverse ninth graders (34.7% Latino/Hispanic,
27.9% Asian/Pacific Islander, 22% white, 6.8% African American, 1.7%
Native American/Alaskan Native, 2.0% other, and 4.8% belonged to more
than one ethnic groups) examined the relationship between television
viewing and obesity. Statistically significant positive correlations (r= 0.19 to
0.25) were found between hours of television viewing and intake of high fat
foods. No statistically significant correlation was found directly between
hours of television viewing and BMI. This finding suggests that BMI may be
mediated by the effects of consuming excess dietary fat while watching
television (average 41.8 hours per week for the entire sample) (Robinson &
Killen, 1995). Kleges (1994) found a lowered metabolic rate (-211 kcal/day
caloric expenditure at rest) in both obese (n = 15) and normal-weight (n =
16) children while watching television. These two studies illustrate the
complexity of the interplay between variables: Television watching both
lowers BMR and stimulates an increased fat intake, both of which influence
childrens BMI.
10


A more direct relationship between television viewing and body fat
was reported by the NHANES III Survey. Children (n= 4,063 aged 8
through 16) who watched 4 or more hours of TV per day had significantly
greater body fat (q_< .001) and greater BMIs (p_< .001) than those who
watched 2 hours per day (Andersen et al., 1998). A recent study sought to
determine whether limiting sedentary activities (television viewing, video
game playing) would decrease BMI. Those in the intervention group
(limited television viewing, video game playing) showed a significant
decrease in BMI from their pre-intervention BMI when compared with
control children (no TV or video limits) (p_< .002). This change occurred
despite similarity between the intervention and control groups for changes
in moderate-to-vigorous physical activity, high-fat food intake or
cardiorespiratory fitness (Robinson, R., 1999). It is important to note that
physical activity was measured using recall method, which should be
interpreted with caution because the ability of young children to accurately
recall events is questionable (Sallis, 1991, Sallis et al., 1996). However,
taken together, the data support that the current rate of childhood obesity
might be ameliorated by limiting the time children spend watching television
or in other forms of sedentary play.
Limited community resources that provide safe places for children to
congregate and budget constraints in schools that restrict programs and
11


equipment, contribute to decreased participation in physical activity (Bar-Or
et al., 1998). Parents may limit their childrens outdoor playtime, and may
even drive them to and from nearby schools due to concerns over
neighborhood safety. Furthermore, access to organized sports may be
limited by parents financial resources which may further decrease
childrens opportunities to participate in physical activity (Sallis et al., 1997).
Those factors that supplant physical activity in children as well as barriers
to participation in physical activity contribute to childrens inactivity.
Parental Attitudes/Beliefs. Because it is likely that childrens habits
are developed early in childhood, parental influences, attitudes and values
related to physical activity may be important determinants of childrens
exercise habits (Moore, 1991). Within families, parents are strong and
credible models for young children (Sallis, 1992). Attitudes and behaviors
relating to physical activity, exercise, games and sports are learned and
Teinforced by parents in the home environmenr(Bfustad, 1993). As
children reach adolescence, different factors play a part in influencing
levels of physical activity such as peers, school, coaches and media
(Raudsepp & Viira, 2000).
Parents and childrens attitudes and beliefs about childrens physical
activity are under investigated in terms of how they influence childrens
participation in physical activity. One study examining the relationship
12


between childrens and parents beliefs regarding physical activity showed
a number of important findings (Kimiecik et al., 1996). Childrens beliefs
(degree to which they value participation) about physical activity were
significantly related (g < .001) to their parents beliefs about physical
activity. Further, childrens perceptions of their parents belief about their
childs physical activity and fitness and their own belief about moderate-
vigorous activity were significantly related (£ < .001). These findings
confirm that parental beliefs and attitudes are one source of influence upon
childrens activity levels and may serve to significantly influence childrens
behavior (Kimiecik et al., 1996). Furthermore, Kimiecik and Horn (1998)
found that parents positive beliefs about their childs physical competence
and goal orientations for their child contributed significantly (26.9% of the
variance, £ < .009) to their childs engaging in moderate to vigorous
physical activity. Therefore, when parents have positive beliefs and
attitudes towards~physical"activity7theirchi1drens'physicar activity
increases.
When parents value and prioritize physical activity, they will more
likely be active themselves and thereby influence their childs opportunity to
participate in physical activity. This specific construct, referred to here as
prioritization, has not yet been studied and is a primary focus of this
project. I hypothesized that prioritization and valuation of physical activity
13


would relate to childrens activity levels. If true, interventions may be
developed to change health behaviors when parents consider it important
and are ready to make a behavioral change. Conversely, if parents do not
prioritize or value physical activity for themselves or their children,
intervention strategies may focus on changing health beliefs prior to
changing behavior.
Parental Activity. One of the most influential determinants of
childrens physical activity is parents degree of physical activity habits.
Parents serving as role models is one possible reason for this association
(Moore et al., 1991); however, there is variation in the extent to which
studies have found that parent role modeling influences their childrens
exercise habits. Moore et al. (1991), using an objective measure of energy
expenditure (accelerometers), obtained physical activity levels over M. =
8.6, SD =1.8 days for 100 children, M = 8.3, SD = 2.1 for their mothers (n =
99), and M = 7.7, SD = 2.3 for their fathers (n = 92). Children (4-7 years
old) of active mothers (average Caltrac accelerometer counts per hour
greater than the median) were two times as likely to be active as those of
inactive mothers. When both parents were active, children were 5.8 times
as likely to be active. These results contrast with those of another study
where childrens activity levels were correlated (r = 0.45) with that of their
mothers, but not with that of their fathers (Sallis et al., 1988). However, as
14


opposed to direct measurement of physical activity, the 7 day physical
activity recall (PAR-7), an interviewer-administered subjective method of
data collection for physical activity, was used in the latter study. Self-reports
of childrens physical activity are limited in accuracy and recall of habitual
exercise and therefore challenge the validity and reliability of self-reported
physical activity. In contrast to these two studies, McMurray et al. (1993)
reported that parents exercise practices did not influence their childrens
activity levels (Rf = .006). Again, however, this study used self-reported
activity (SRA) to measure physical activity in 3rd and 4th grade children and
their parents. Lastly, in a study involving both Mexican American and Anglo
families, Sallis et al. (1988) found a moderate degree (r = 0.45- 0.55) of
family aggregation of physical activity with mother-child correlation higher
than father-child correlation. Mexican American families had higher
intrafamily corrrelations than the Anglo families suggesting that the differing
Intensity of fa mi lyTnfl u e n ce arnonglMexicmATnehcan families may be
related to an increased reliance or cohesion among family members that
influences physical activity.
Differences among the studies described above may be due to the
different direct versus indirect methods for measuring physical activity.
Because physical activity is a complex behavior, measurement is also
complex. The disparate associations between parents physical activity
15


and that of their children might be clarified by using more precise
measurement of physical activity (accelerometers) versus the more
common subjective measures (mothers answering questions pertaining to
childs activity, children self-reporting).
The review above should make clear that determinants of childrens
physical activity patterns are multifactorial. Therefore, studies must
examine multiple domains in an effort to identify those factors that
contribute substantially to the development of good versus poor physical
activity habits. In addition, precise and consistent measures of childrens
activity are needed to resolve conflicts within the relevant literature.
Ethnicity. In a review of approximately 300 studies investigating
determinants of physical activity in adults, Dishman and Sallis (1994)
summarized nine modifiable variables most consistently associated with
overall physical activity: social support, self-efficacy, perceived barriers,
perceived benefits; enjoyment of physicai activity7 processes of change,
intention to exercise, lower intensity of exercise, and eating habits. Few of
these studies included diverse ethnic and socioeconomic samples. For
Hispanic adults, the predictive variables related to physical activity indicate
that self-efficacy, friends support, childhood physical activity and eating a
heart healthy diet are important (Hovell et al., 1991). The determinants of
physical activity related to Hispanic children are not understood and further
16


investigation is needed to identify the variables that influence physical
activity in this subgroup.
Examining socio-cultural contributors to exercise behavior and their
association with body size in adults and children may further our
understanding of belief systems regarding physical activity and body size
that contribute to inactivity and increased body fatness. Hispanic men and
women reported higher desired body weights than non-Hispanic white men
and women, suggesting that cultural factors may contribute to ethnic
differences in body weight (overweight NHW desired more substantial
weight loss than overweight Hispanic). For example, Hispanic men and
women had significantly higher BMIs (0.9-2.9 BMI units) than non-Hispanic
white pairs when matched for education, city of residence, age, gender,
language spoken and time of survey (Winkleby et al., 1996). A culturally
mediated preference for higher body weight may contribute to the incidence
of higher "B Ml in HispanicTad u Its and childrenrThefefofe, the culturally
accepted view of body weight may influence the choicesfamilies make
concerning physical activity participation if the behavior has an impact on
loss of body weight. The present concept of overweight within the general
U.S. populace may be devised around white middle class societys
acceptance of an ideal standard for beauty and attractiveness. The extent
to which parents ethnicity influences their childrens participation in physical
17


activity, impact on body size, and the health consequences of being
overweight and obese, is less understood.
The value of and attitudes towards participation in regular physical
activity may also contribute to the differences found in minority adults and
childrens level of physical activity and BMI. In a study querying 40 Mexican
American, 40 African American, and 40 European American women
regarding how they became overweight, most of the Mexican American
women discussed the strong family influence of mothers cooking and social
traditions surrounding food, but the Mexican American womens families did
not discuss physical activity (Allan, 1998). Because many ethnic groups
maintain their cultural norms and values from generation to generation,
Hispanic women may not have learned that physical activity has important
general health benefits as well as contributing to weight control. Alternately,
Hispanic women may be aware of current health promotion practices such
as exercise and healthy eating but take better care of their families than
themselves (Higgins & Learn, 1999). Although a large proportion of
minorities are poor and have limited access and resources to exercise,
Winkleby et al. (1998) reported that highly educated Mexican American
women were still more likely to report no physical activity compared to non-
Hispanic white women of similar educational levels. It would appear that
18


culturally diverse parents values and attitudes concerning physical .activity
may contribute to childrens physical activity independent of SES.
There are differences in the pattern of developmental change in body
mass within social classes that may contribute to long term differences
measured in childrens weight. Children from upper socioeconomic families
display excess adiposity in childhood and change to a more lean body type
as they grow older, while children of lower socioeconomic families are
thinner in their youth but gain more fat mass later in life (Bray, 1979,
Cockington, 1980 and Stunkard et al, 1972). Again, these disparities within
social classes, similar to the differences within ethnic groups, occur within a
social and cultural context that is not fully understood.
In general, Hispanic children are at higher risk for cardiovascular
disease and obesity, which is not surprising considering that Hispanic
American children have lower activity levels (NHANES III), and a higher
incidence of overweight parents than their Anglo counterparts (McKenzie et
al., 1992). Television viewing (sedentary habits) may relate to ethnic
disparities in physical inactivity, obesity and ill health. For example,
Hispanic children are less active both at school and home when compared
to Anglo children (McKenzie, 1992) and African-American boys and girls
had the highest rate (43%) of watching television (more than four hours per
day) as compared to Latino/Hispanic boys (33.3%) and girls (28.3%). Non-
19


Hispanic white boys and girls had the lowest rate (24.3% boys and 15.6%
girls) of watching television more than four hours per day (Anderson et al.,
1998).
The determinants of ethnic differences in time spent watching
television and associated inactivity, dietary fat intake, and gender
differences are unclear (Gortmaker, 1996). One possible factor is that
families in low socioeconomic neighborhoods (disproportionately inhabited
by minorities) may use television as a means of providing inexpensive safe
child-care, thus inadvertently decreasing physical activity and increasing the
risk of obesity and associated health problems. Another explanation may
be that families do not prioritize an active lifestyle because of competing
demands on their time and available resources as well as having an unclear
understanding of the benefits of being physically active. Finally, family life is
another important aspect of the Hispanic culture that may positively or
negativelylnfluence physicaTactiVity patterns. Familism,considered to be a
defining feature of Hispanic populations, refers to the concept of family as
being the strongest area of life (Padilla, 1994). Conducting a family-focused
investigation of values, attitudes and participation in physical activity is
necessary especially when considering parental influence in differing ethnic
groups in which there may be unrecognized differences.
20


In summary, it is likely that socioeconomic status contributes to
differences between Hispanic and NHW ethnic groups in the physical
activity of children. Because of this potentially confounding influence, my
study includes high and low socioeconomic status Hispanic and Non-
Hispanic white (NHW) families.
Intervention. Programs designed to increase childrens physical
activity levels and prevent childhood obesity should be aimed, in part, at
promoting the development of healthy exercise patterns as early as possible
in childhood. Identifying factors that influence childrens physical activity
may provide data that can be used to design interventions aimed at
assisting parents and other important adults in encouraging children to
develop a long-term commitment to physical activity.
When families are included in programs designed to prevent and
treat inactivity and obesity, children lose more weight and maintain lower
weight over a longer period'dnime (bpst^h^t al7; i 994). ln one study,
treating childhood obesity involved randomization of families into groups
that chose increased activity, groups that decreased sedentary behavior, or
a combined group to test the influence of reinforcing children to be more
active or less sedentary (Epstein et al., 1995). After one year of treatment,
the group that was reinforced for decreasing sedentary behavior had
greater decrease in percentage overweight than the combined and the
21


exercise groups (-18.7 vs. -10.3 and -8.7), lost significantly more body fat
than the other groups (-4.7% vs. -1.3%), improved their liking for high-
intensity activities, and reported lower caloric intake (Epstein et al., 1995).
The intensity of exercise and/or extent of dietary intervention needed to
effectively treat childhood obesity are still unknown.
Physical activity interventions promoting physical activity in healthy
families have shown very limited success. Nader et al (1989) developed an
educational program to improve physical activity and nutrition in healthy
Mexican American and European American families with children in the 5th
or 6th grades. No significant changes were found in either the parents or
childrens physical activity levels after a 2-year period. Changes in diet,
blood pressure, and lipids were found, but only in the adults (Nader et al.,
1989). In another study, Baranowski et al (1990) developed a 14-week
program focusing on increasing physical activity and promoting dietary
changes in African American families (5th-7th grades). Again, there were no
significant differences between the intervention group and the control group.
Both of the aforementioned studies had low compliance (40%, Nader study,
and 20% Baranowski study) and therefore, the results should not be
considered definitive. These studies bring to light the difficulties in
promoting family based physical activity interventions that require time and
22


commitment from families and suggest that other creative approaches
should be sought.
The increasing prevalence of cardiovascular disease and diabetes
among younger Hispanic American adults and children is alarming. This
trend lends urgency to the idea that preventing obesity and sedentary
lifestyle, beginning in childhood, is one way to slow down or even reverse
the trend towards increasing ill health at an earlier age in this population
(Rauh et al. 1992).
In summary, the generalized health benefits of exercise warrants
establishing generalized public health recommendations to increase
physical activity nationwide. In this study, psychological, social,
environmental and behavioral variables that are associated with childrens
physical activity were investigated to further understand what may predict
physical activity levels in non-Hispanic white and Hispanic youth.
Specifically, the variables: (a) parents physical activity; (b) parents
prioritization and value of physical activity; (c) parents perception of activity
and recreation within the family; and (d) childrens perceived athletic
competence were included and expected to positively correlate with
childrens physical activity. Interventions may thus be tailored to changing
health behaviors and/or health beliefs, depending on parents perceptions
and beliefs concerning physical activity for themselves and their children.
23


CHAPTER 2
THEORETICAL ISSUES AND MODELS
A plethora of theories have been applied to physical activity and
health behaviors. The most common theories and models include: Health
Belief Model, Theory of Planned Behavior, Transtheoretical Model,
Ecological Models and Social Cognitive Theory. They are summarized in
Table 2.1.
Childrens physical activity behavior is highly variable and dependent
on a wide variety of factors in the childrens family environment (Dishman et
al., 1985, Moore et al., 1991,). As such, a theoretical perspective that
examines multiple determinants (athletic competence, prioritization and
value, family social environment, physical activity, and ethnicity) and their
interactions are required for understanding childrens choices regarding
exercise behavior
24


Table 2.1: Theories and Models
Physical
Theory/Model Intrapersonal Variables Social Variables Environmental Variables
Health Belief Perceived
Model susceptibility, severity
(Becker, M., benefits, barriers; cues
1974) to action; self-efficacy
Theory of Behavioral intention: Subjective norms:
Planned attitude toward the perception of beliefs
Behavior behavior; perceived of others and
(Ajzen, I., behavioral control motivation to comply
1991)
Trans- Stages of change; Some processes of Some processes
Theoretical processes of change; change; some of change; some
Model decision balance; decision balance decision balance
(Prochaska, J.O., self-efficacy variables (benefits variables
1984) and costs of changing)
Ecological Multiple levels of Interpersonal factors; Community
Model influence, including institutional factors factors; public
(McLeroy et.al, intrapersonal policy factors;
1988) health promotive
environments
Social Cognitive Multiple levels of Observational Reinforcement
Theory influence, including learning; reinforcement
(Bandura, 1986) intrapersonal
Source: Adpated from Sallis and Owen (1999; Table 7.1, page 112).
25


Social Cognitive Theory
Banduras social cognitive theory states that behavior, cognition,
environment and other personal factors (attitudes, values, beliefs) interact
to influence behavior (Bandura, 1986). Social cognitive theory is widely
applied in physical activity research because it allows for the interactions
between intrapersonal, social, environmental and behavioral influences that
affect ones behavior (Sallis, 1999). Therefore, social cognitive theory
proposes that the aforementioned factors operate as interacting
determinants of each other and provide a dynamic and interactive
framework from which to study human behavior. Banduras triadic model
(Figure 2.1) refers to the relationships of the three classes of determinants
for an individuals physical activity.
Figure 2.1: Banduras Triadic Model
Behavior (intensity, duration, frequency, mode)
(cognitions, cognitive styles, body, (spouse support, facilities
composition, age) access, stimulus control)
Source: Bandura, 1986.
26


For example, a childs degree of television viewing, defined as
behavior, may be associated with his or her age, body composition, and
cognition, defined as person. Stimulus control, parent support, and access
to facilities are associated with environment. These interacting
determinants help to explain the behavior outcome, television viewing, by
examining the interaction between intrapersonal, social, and environmental
influences. The research reported here has been informed primarily by
social cognitive theory (SCT).
Taylor et al (1994) modified Banduras model (Figure 2.1) to include
two or more persons with reciprocal interactions among the home
environment, parent behavior and cognition, and child behavior and
cognition. My application of social cognitive theory towards the conceptual
model diagrammed in Figure 2.2 is intended to help explain and understand
the determinants of childrens physical activity (Sallis et al., 1992).
27


Figure 2.2:Social Cognitive Model of Parental Influence
Environment (Family Environment Scale)
i
Parent behavior (PA by accelerometer) + Child behavior (PA by
accelerometer)
+'
Parent Cognition (prioritization and value of PA) Child Cognition (perceived
athletic competence)
(proposed study measures)
(Adapted from Taylor, Baranowski, Sallis, 1994)
The model above shows the independent and dependent variables
and the means by which they are measured in this research project. The
model suggests that behavior, cognition, competencies, attitudes,
preferences and environmental influences interact as determinants of each
other as well as the outcome variable, childrens physical activity (Dishman,
1994). For example, parents may affect a childs behavior by changing the
environment in a direct or indirect manner. Parent cognition (prioritization
and value) may affect a childs behavior when mediated by parent behavior
(participation in physical activity). A childs cognition (perceived athletic
28


competence) may influence his or her physical activity behavior when
mediated by parents physical activity behavior and parents cognition. For
example, parents may prioritize, value, and participate in physical activity in
their day-to-day lives which in turn affects childrens participation in physical
activity and their sense of athletic competence. Thus, parent behavior,
cognition, and perceived family participation in physical activity interact as
determinants of each other and influence childrens behavior. The specific
predictor variables, parent valuation, parent prioritization, perceived family
activity/recreation, parent physical activity and childrens athletic
competency were selected because of their contribution to psychological,
social, and physical environment factors that have been shown to be closely
related to physical activity (Lindquist et al., 1999, Sallis et al., 1997)
The current literature supports that self-efficacy in physical activity,
enjoyment, parental influences, attitudes, or beliefs related to physical
activity, and access to sport equipment and programs are significantly
correlated with physical activity (Reynolds et al., 1990, Stuckey-Ropp &
DiLorenzo, 1993, Moore et al., 1991, Trost et al., 1997). The strength of
these associations range between 5-25% of the variance in childrens
physical activity (Trost et al., 1997). The studies above examined children
of different ages, hence the disparate correlations may be due to the known
age-associated^variation in physical activity as children progress through
29


childhood and adolescence (Rowland, 1991). This study will use known
correlates of physical activity (parent behavior and beliefs, self-efficacy) and
adopt new variables (parent prioritization and valuation), guided by social
cognitive theory, to further expand and explore the determinants of
childrens physical activity (Sallis and Owen, 1999). The rationale for
evaluating prioritization is obvious. If parents set aside time for themselves
and their children to engage in physical activity, they are prioritizing physical
activity. If parents do not prioritize or value physical activity, then perhaps
intervention and social marketing strategies should be altered to support
prioritization of physical activity for parents and their children.
The family oriented research, informed by SCT, examines how
parents of different ethnic groups influence childrens physical activity
behavior through role modeling (parents physical activity levels-behavior),
parents perceived social environment (environmental), childrens self-
efficacy, and parents prioritization and value (cognition). Understanding
and identifying family determinants that affect and positively contribute to
childrens levels of physical activity are critical to the process of improving
child health through prevention of sedentary lifestyle and childhood obesity.
The independent variables investigated in relation to variation in
childhood physical activity are described in detail below.
30


1. Role modeling, or observational learning, is one of the major
concepts in social cognitive theory applicable in this research project.
Observational learning refers to behavioral acquisition that occurs by
watching the actions and outcomes of others behavior (Baranowski, et al.,
1997). For example, parents who set aside time for regular exercise
demonstrate to their children that exercise is prioritized as well as important
in their day to day activity. As a result, their children are more physically
active than the children of parents who do not engage in regular exercise
(Moore et al., 1991). When the child observes parents engaging in a
behavior (e.g. physical activity), he or she also observes the rewards,
successes, and punishments related to the behavior. The child thus
becomes more likely to internalize those behaviors that are accepted and
rewarded rather than punished into their own behavioral repertoire. This
process includes not only participation and immediate reinforcement, but
involves observing parent behaviors in which learning (through observation)
occurs (Bandura, 1986). This research reported herein explored the
importance of parents functioning as role models for their childrens physical
activity behavior and will expand the model to include psychosocial aspects
(prioritization, valuation, perceived athletic competence and recreational
environment) of parental influence towards childrens physical activity.
31


Figure 2.3 depicts where role modeling/observation learning (italicized) fits
into the theoretical model.
Figure 2.3: Role Modeling/Observation Learning
Environment (Family Environment Scale)
J
*Parent behavior (PA by accelerometer) + ^ *Child behavior (PA by
accelerometer)
athletic competence)
2. Environments and situations within social cognitive theory refer
to the physical and social environments and the individuals and/or groups
perception of these environments. In social cognitive theory, environment
and situations refer to different representations of the environment. The
term "environment refers to an objective notion of all the factors that can
affect a persons behavior but are physically external to that person
(Baranowski, et al., 1997). Social environment may include family, friends,
or peers, whereas physical environment refers to facilities, weather, or
neighborhood. The term situation pertains to the cognitive or mental
32


representation of the environment that may affect a persons behavior
(Baranowski et al., 1997). This study explores how parents perceive their
family social activity/recreation environment (situation) and how these
perceptions promote or inhibit childrens physical activity. Physical
environment may affect behavior by visible and clear examples such as
exercise equipment in the home or membership in a health club. Less
obvious social and situational environments may include cues provided by
parents concerning engaging in outdoor activities, viewing a childs play or
practice, discussing physical activity with the child, or establishing rules and
environmental conditions that encourage the child to be active instead of
sedentary (such as limiting TV or structuring leisure time with organized
sports). Therefore, the physical environment as well as the social and
situational representation (parents perception) of the environment may
positively or negatively affect behavior and thus modulate how family
rrfembel^behave(Baranowski et a I. ,1997)^Figufe~2.4d epictswhe resocia I
and situational environment (italicized) fits into the theoretical model.
33


Figure 2.4: Environment/Situation
*Environment (Family Environment Scale)
1
Parent behavior (PA by accelerometer)
I.
Child behavior (PA by
accelerometer)
I.
Parent Cognition (prioritization and value of PA)
Child Cognition (perceived
athletic competence)
3. Self-efficacy is defined as an individuals sense of competence
and confidence in executing a particular behavior and in overcoming
barriers to performing a particular behavior (Bandura, 1986). Self-efficacy
has shown to be a strong primary predictor of intention to engage in physical
activity in adolescent girls and boys (Reynolds et al., 1990). In
preadolescent boys and girls, self-efficacy in physical activity was the
strongest predictors of daily participation in moderate and vigorous exercise
(boys r = 0.27, girls r = 0.33, jd < 0.05) when examining the influence often
psychosocial and environmental determinants (Trost et al., 1999). The
construct, self-efficacy (measured using questionnaires related to ones
sense of perceived confidence) is determined by how individuals process
34


and integrate information about their abilities and beliefs from various
sources (peers, parents, siblings) and ultimately acquire perceptions and
expectations regarding their own individual abilities. These perceptions,
beliefs and expectations then determine, in part, the individuals choice of
goals, the degree of effort they expend to achieve those goals, and their
degree of confidence in being able to overcome barriers in pursuit of goals
(Maddux, 1993). Self-efficacy is an essential condition/concept within social
cognitive theory because of its fundamental contribution to behavioral
change. Self-efficacy influences the adoption of healthy behaviors, arrests
unhealthy behaviors, and aids in maintenance of positive behavioral change
when such change is threatened by barriers and obstacles (Maddux, 1993).
Figure 2.5 depicts where self-efficacy (italicized) fits into the theoretical
model.
35


Figure 2.5: Self-Efficacy
Environment (Family Environment Scale)
J
Parent behavior (PA by accelerometer) + ------- *Child behavior (PA by
accelerometer)
+
Parent Cognition (prioritization and value of PA) *Child Cognition (perceived
athletic competence)
Parent Cognition
Social cognitive theory (SCT) posits that intrapersonal factors such
as values and attitudes influence particular behaviors. Within the parents
belief system, particular behaviors are initiated or avoided, thus influencing
childrens behaviors (Dishman et al., 1985). In application of SCT,
children's physical activity levels are influenced by parental cognitive
processes (prioritization and value of physical activity), childrens cognitive
processes, (self-efficacy and perceived athletic competence), parental
perceived social environmental (activity and recreation) and behavior
(physical activity participation).
This study will introduce new predictor variables, parental
prioritization for themselves and valuation of physical activity, for the
36


purpose of examining parents attitudes, values and beliefs concerning
physical activity. Valuation is operationalized here as a rating according to
relative worth, importance and/or desirability. Individuals would be expected
to engage in a behavior which they believed was of value and importance
and avoid those behaviors that are perceived to increase risk of illness or
injury (Strecher & Rosenstock, 1997). I hypothesize that the degree to
which parents prioritize and value physical activity in their everyday lives is
an important influence on childrens physical activity levels. Figure 2.6
depicts where parent cognition (italicized) fits into the theoretical model and
the predicted correlation between parents values and child behavior.
37


Figure 2.6: Parent Cognition
'Environment (Family Environment Scale)
+
i
'Parent behavior (PA by accelerometer) + ^ *Child behavior (PA by
accelerometer)
t
t.
*Parent Cognition (prioritization and value of PA ) 'Child Cognition (perceived
athletic competence)
38


CHAPTER 3
RESEARCH QUESTION AND PRELIMINARY DATA
Research Question
The specific research question to be addressed is: To what extent
do mothers and fathers perceived family activity/recreation environment,
parent physical activity, parent prioritization and valuation of physical
activity, and childs (boys and girls) athletic competence predict childs
physical activity?
The proposed study will assess environmental, sociocultural, and
psychological and behavioral variables in order to understand determinants
that contribute to Hispanic and non-Hispanic white, and low and high
socioeconomic status, childrens physical activity. The constructs evaluated
in this project have not previously been investigated collectively. No prior
study has examined the extent to which ethnicity may influence parent
prioritization and valuation of exercise for their children, and certainly no
study has examined how Hispanic girls, who are reportedly the least active
among ail children, may be influenced by their families into a pattern of low
daily physical activity levels (McKenzie, 1997).
39


Hypotheses
Childrens (boys and girls) energy expenditure will be positively
correlated with:
Parental (mothers and fathers) prioritization of physical activity for
themselves measured by Physical Activity Prioritization Survey
(PAPS).
Parent (mothers and fathers) ranking of the value of physical activity
measured by a 7-item lifestyle-ranking instrument.
Parental (mothers and fathers) participation in physical activity
objectively measured by accelerometers.
Parental (mothers and fathers) perceived family social environment
measured by Family Environment Scale.
Childrens (boys and girls) perceived athletic competence measured
by Self-perception Profile for Children
In essence, the hypotheses posit that when parents (mothers and
fathers) prioritize and value physical activity and participate in physical
activity themselves, their children (girls and boys) will perceive higher
athletic competence and be more physically active. Ethnic and
socioeconomic differences in childrens energy expenditure will be mediated
by differing parental perceptions of physical activity for themselves and their
families and childrens self-efficacy related to athletic competence.
40


Preliminary Data
Questionnaire Development
A pilot study of parents' opinions about attitudes towards and
prioritization and valuation of physical activity was conducted using
questions adapted from The Healthy Families Project (Gomel & Tinsley,
1999 personal communication), survey questions from Dr. Susan Johnsons
Family Systems Approach to Childhood Obesity project, and informal expert
discussions. The results of this pilot study were then used to develop the
PAPS (Physical Activity Prioritization Survey) which I used to measure
prioritization and value ranking of physical activity.
The PAPS questions were developed from an expert panel of judges
in the area of physical activity and questionnaire development, tested in the
field, edited and re-tested with continued expert advice and direction.
Expert contribution included the following individuals who were solicited for
their varying expertise: Dr. Kim Reynolds, a social psychologist who
conducts research in sociocultural determinants of physical activity in
children; Dr. John Brett, an anthropologist with expertise in ethnographic
methodology investigating physical activity and dietary patterns in Hispanic
and non-Hispanic white families; Dr. Kitty Corbett, an anthropologist with a
masters degree in public health who has extensively worked with
questionnaire and semi-structured interviews; Dr. Lori Crane, who is
41


involved in the area of preventive medicine and biometrics, and was
selected for her expertise in questionnaire and survey development; Dr.
Stacy Zamudio, who teaches research design and methodology in the
health and behavioral sciences, Dr. David Tracer, director of Health and
Behavioral Sciences department at the University of Colorado at Denver,
was solicited for his experience with questionnaire and semi-structured
interviews; as was Dr. Susan Johnson, a nutrition scientist, researching
eating behaviors in Hispanic and non-Hispanic white families in the
proposed Denver schools.
Topics to be included in the questionnaire were decided in an initial
draft and revised per the advice of the expert panelists. The final PAPS
questionnaire includes a total of nine questions. Only questions 7-9 were
used to measure parental prioritization and parent value ranking.
Questions 1-6 were collected as adjunct data in order to describe possible
differences between the ethnic groups perceptions of frequency, duration,
type and time set aside for physical activity.
Physical Activity Prioritization Survey Questions
1. Can you tell me what physical activity means to you?
2. As part of your daily/weekly routine, what kinds of physical
activity do you do?
42


3. Do you think physical activity is important for you? For your
children?
WHY is it important for you (parent)?
WHY is it important for your children
4. Compared to other adults of your same age and sex, how
physically active are you?
A lot more/A little more/A little less/A lot less/Average/NA
5. How many times during the past week did you engage in an
activity that made your heart beat fast, made you breathe hard, and maybe
caused you to sweat? How long did that activity last?
6. Do you set aside time, in your normal routine, to engage in
physical activity for yourself? In other words, do you forego other tasks or
activities to make time for physical activity?
If parent answers yes Can you tell me how you do that?
If parent answers no^Can you telllneTnore about why not?
Now, think about your child_____________. Can you tell me if time is
set aside for him/her to participate in physical activity?
If parent answers yes Can you tell me how that happens?
If parent answers no Can you tell me more about why that may
not happen for____________?
43


7. Please rank these items according to how important they are
to you: (Scale 1-7 with 1 being the most important and 7 the least)
_______being financially successful
_______being healthy/not being sick
_______doing well at work
_______enjoying leisure time
_______having a good family life
_______having a good spiritual life
_______having good friendships
8. Where does being physically active fit into this list?
9. Consider your responsibilities and tasks in a typical day. Now
think to yourself about those responsibilities/tasks that you consider your
highest priority in a given day and think to yourself about those
responsibilities/tasks that are your lowest priority. REALISTICALLY, where
Tnigbrphysical^ctivity^fitlnto^this scalefor you irra'typical day?
For (parent):
Lowest priority Highest priority
For (child):
Lowest priority Highest priority
44


Question #1 was originally developed to evaluate how subjects
define physical activity. On the advice of the ethnographer, we changed
the question to an open-ended format to allow participants to define
physical activity from their own perspective and avoid stereotyping. The
ranking questions (#7 and #8) were developed by Gomel and Tinsley
(1999) in The Healthy Families Project in California and used in studies of
health and nutritional values in Latino families. The parent prioritization (#9)
was developed and refined utilizing the aforementioned expert panelists
familiar with questionnaire/survey methods. The language of the
questionnaire and visual analog scale (VAS) used in question #9 was
piloted for vague or misleading questions and re-tested in two differing
ethnic cohorts with minimal revisions. For example: In a typical week, how
many days do you get physical activity? was modified to How many times
during the past week did you engage in an activity that made your heart
beat fast, made you breathe hard;and maybe causedyouto sweat?
Pilot Questionnaire Results
Parents from two Denver schools were asked questions during
parent night, track and field day, and by telephone interview. Ten Hispanic
and 10 non-Hispanic white parents were initially asked questions from the
first draft of the PAPS questionnaire to trial question design, order, and
45


content. Twenty-two Hispanic parents and 19 non-Hispanic white parents
were then used for the second phase of pilot testing of the questionnaire.
The pilot data revealed that both Hispanic families and non-Hispanic
families consider physical activity primarily as movement of the body in
differing degrees of intensity. The biggest differences were that Hispanic
families included day-to-day activities such as going to the store and
cleaning the house (movement for a purpose) as well as sports in their
conceptualization of physical activity whereas the non-Hispanic white
families more often thought of physical activity as being solely related to
sports activities.
46


CHAPTER 4
RESEARCH DESIGN AND METHODS
Overview
Data were collected from families with children enrolled in 3rd-5fh
grades. The reason for examining this age range is because children
become less physically active as they grow older as shown in Table 4.1
(Rowland, 1991).
Table 4.1: Total Daily Energy Expenditures (kcal/kg/day)
6 Years 8 Years 10 Years 12 Years 14 Years
Boys 82 74 75 58 50
Girls 76 70 58 53 45
Source: Adapted from Rowland (1991; Figure 3.1, p.35)
Participation in all forms of physical activity decreases considerably
during adolescence for both boys and girls (Surgeon General Report,
1996). Furthermore, Hispanic-American children and those of low
47


socioeconomic status are at greater risk for being sedentary and overweight
(McKenzie, 1992). For these reasons, I selected children in 3rd -5th grades
(8-10 years of age) in order to capture activity levels prior to the age-
associated decrease in activity with the intention of ultimately developing an
intervention that interrupts the decline.
A cross-sectional design was used to identify sociocultural,
environmental, behavioral and psychological determinants of physical
activity in non-Hispanic white (high and low SES) and Hispanic (high and
low SES) families. The design allows for examination of the relationships
between family social activity/recreation environments, parental
prioritization and value of physical activity, physical activity participation,
and children's athletic perceptions and the outcome variable, physical
activity. The design further evaluates the extent to which these
relationships differ between high and low SES Hispanic and non-Hispanic
white families. Hispanic families from whom I collected data were primarily
of low socioeconomic status, whereas the non-Hispanic families were of
high socioeconomic status. Recognizing that this was a skewed sample,
the research design was modified to include high SES Hispanic families and
low SES non-Hispanic white families.
The sample included 99 families recruited from four schools. A
family is defined as two or more individuals who reside in the same
48


household and who have some common emotional bond (Baranowski &
Nader, 1984). This definition included biological parents in both single
parent and two-parent families. Both mothers and fathers were included
when feasible. Data collection began September 1999, two to three weeks
after school had resumed from summer break. During this initial phase
families were recruited by mail, phone, and school bulletin messages sent
home with the children. Consent forms were completed for parents, and
assent forms for children, who agreed to participate during the home visit
prior to data collection. The consent forms and protocols were approved by
the University of Colorado at Denver Institutional Review Board.
Subjects
Participants were recruited from the target populations, Colorado
Springs School (CSS) in Colorado Springs, Lincoln Elementary School
(LES) in Colorado Springs, Corpus Christi Catholic School (CCC) in
Colorado Springs and Columbian Elementary School (CES) in Denver.
Colorado Springs School, a private institution, is comprised of primarily high
SES non-Hispanic white families. Lincoln Elementary School serves
primarily low income non-Hispanic white families. Columbian Elementary
School is serves primarily low SES Hispanic families. Corpus Christi
Catholic School is a private institution with sufficient numbers of high SES
49


Hispanic families for recruitment. The staff at these schools provided
current enrollment lists of parents and phone numbers so that we could
identify those parents and children who were potential participants. Parents
were solicited by mail in the form of a letter describing the purpose of the
study and information concerning payment for participation. Follow-up
phone contact was used to recruit families for participation. Parents and
children from CSS, CCC, LES and CES 3rd through 5th grades were asked
to provide consent for participation, but were counseled that the child or
parent could terminate their involvement in the study at any time. All
participants were assured of confidentiality.
Excluded from the study were students and the parents of children
who had any physical disabilities that may have prohibited them from being
physically active. Families that were unable to read, write and/or speak
English were excluded due to limited financial resources for the hiring of an
interpreter. LastlyV bothT)ai^tslVhb did not ideh'tify themselves as
Hispanic or Caucasian were excluded from the analyses.
Following the familys agreement to participate in the proposed
study, we set up a convenient time and place to meet in order to obtain
consent and assent. Both parents (if possible) and child interviews were
completed prior to placement of the activity monitors.
50


Subject Payment
Parents were paid $20.00 each for participating in: 1) a semi-
structured interview asking their opinions and values concerning physical
activity for themselves and their children; and 2) wearing an accelerometer
for 7 days. Children received a choice of 5 prizes or $20.00 after wearing
an accelerometer for 7 days. Prizes were valued at approximately $20.00
and included sports-related items such as soccer balls, foursquare balls,
and baseball bats.
Measurements
Parent and child physical activity levels were objectively measured
using activity monitors. Child cognition was measured by children's
perceived athletic competence using a sub-scale of the Self-perception
Profile for Children (Harter, 1985). The Self-perception Profile for Children
measures self-perception for the purpose of assessing childrens
perceptions within a specific domain. Parent cognition was assessed with
the Physical Activity Prioritization Survey (PAPS) in an interviewer
administered semi-structured interview focusing on prioritization and value
ranking of physical activity. The family environment was assessed using
the recreation/activity factor of the Family Environment Scale (Moos &
51


Moos, 1994) which measures parents perception and rating of their current
family activity/recreation environment.
Physical Activity Levels. To avoid the problems associated with self-
reported physical activity I used physical activity monitors, (Accelerometers,
model 7164, Computer Science Applications (CSA), Shalimar, FL.) to
objectively measure physical activity in children and parents (Montoye et al,
1996 and Sallis, 1991). The CSA activity monitor utilizes a vertical plane
accelerometer to quantify movement. The accelerometer is firmly secured
to a belt and is worn positioned over the right hip. The accelerometer
measures acceleration due to the displacement of the center of mass of the
body but filters out high frequency movements such as vibrations. The
accelerometer signal is digitized, converted to numerical counts and
summed over one-minute intervals. Thus, the more steps or the more
intense the movement, the greater number of counts will be accumulated in
^one^Tninute period:_For example, each step creates- an acceleration of
the center of mass (COM) upward and downward. The magnitude of this
acceleration depends upon the speed at which the individual is moving.
Running, for example, will create greater accelerations of the COM than
walking. The CSA data are stored in memory, and downloaded to a
personal computer for subsequent retrieval and analysis. This study
determined physical activity levels based on the average number of
52


accelerometer counts per day. Janz (1994) maintains that CSA activity
counts correlate (r=.50 .74) with heart rate elevation in activities of
different physical intensity, supporting the notion that CSA data
corresponds to exercise intensity (Janz, 1994).
The physical activity monitoring was done over seven consecutive
days and considered representative of a typical week and habitual activity
patterns. The primary outcome was the mean of the 6 days of activity.
Monitoring was done during normal weeks (i.e. not during school breaks
or holiday weeks). While the assumption of normalcy in any given week
could be questioned, most children and their parents have fairly stable
schedules from week to week during the school year.
Two levels of analyses were employed to assess the validity of the
accelerometer data. First, printouts of the activity monitor data were
obtained for each subject across the seven days of monitoring. In this
graph, minute-by-minute values of activity countsare plotted across the
seven days (144 hours) of monitoring. If the subject wore the monitor for
the full seven days, we were able to obtain a characteristic profiles, i.e.,
seven distinct clusters of elevated counts separated by spaces. The
clusters represent the activity counts recorded during the day, and the
spaces represent the sleeping periods when the monitor was not worn. The
53


clusters corresponded to daytime values, and this was verified by having
the subject record what time the monitor was put on and taken off each day.
Second, a mean daily activity value was calculated in adults and
children. For any given day, if the total counts were more than two
standard deviations above the mean, I examined the daily profile and then
followed up with the subject in order to ascertain whether the counts were
truly due to activity or were an artifact. Data on days that were determined
to be invalid were excluded from the calculation of weekly means. Although
these procedures are somewhat subjective, I am not aware of any
published study that has described more objective criteria for quality control
of activity monitor data.
To avoid the novelty effect associated with monitors worn by children
(e.g. children may shake the monitors or take them off to play with them or
show them to their friends etc.) the first day of measurement was
consideredlTleafning period and was not includeTTih the analyses. The
first day of monitoring was not always the same day of the week for each
child and parent(s). Because of logistical constraints, children and
parent(s) often received the monitors on different days of the week.
Records were maintained of the precise day and time that the monitor was
placed on the children and their parents.
54


Careful instructions were provided to both the children and their
parents on how to properly wear and secure the monitor. A chart was
provided that illustrated this as well. Carefully explaining the procedures
enhanced compliance, but as with any other study using activity monitors in
field settings, I could not independently guarantee how compliant subjects
were in vigilant wearing of the monitors (other than the analyses listed
above).
Childrens Perceived Athletic Competence. Self-efficacy is a strong
mediator of behavior change and an important predictor of childrens
physical activity (Bandura, 1982). I considered that my other independent
variables (prioritization, valuation, parental physical activity and family
activity/recreation environment) might relate to self-efficacy and might
therefore enhance our understanding of what variables contribute to self-
efficacy. The Self-Perception Profile for Children (Harter, 1985) was used
to measure"childrens self-perceptions of six separate domains. They
include: scholastic competence, social acceptance, physical appearance,
behavior conduct, global self-worth and athletic competence (Harter,
1985). Examination of the differing profiles, measured by six separate
subscales, reflects an accurate depiction of childrens self-concept and self-
adequacy. While all 6 subscales were collected, this study focused on
perceived athletic competency. The subscale, athletic competence,
55


contains items that probe childrens perception of sport and outdoor games
and their perceived proficiency and adequacy in athletic endeavors. The
arrangement of the question strives to elicit self-perceptions rather than
socially acceptable answers. Each item is scored 1 through 4 with 1
indicating low perceived competency and 4 indicating the highest perceived
competency. Three items are counter-balanced such that 4 indicates low
perceived competence and 1 indicates high competence. Athletic
competence is moderately (R=0.50 and above) correlated in grades 3rd and
4th with physical appearance, self-worth, social acceptance and scholastic
competence (Harter, 1985). Internal consistency was assessed using
Chronbachs Alpha. Internal consistency reliabilities for each subscale
using four different samples ranged from .71 to .86. Behavioral conduct
was the lowest at .71, and athletic competence was the highest at .86
(Harter, 1985).
ParentaTPrioritizatiorrand Rankin~a~of~PhvsicarActivitv. Parental
prioritization of physical activity was assessed using a semi-structured
questionnaire (PAPS) that had been pilot-tested during summer of 1999.
This questionnaire elicited parental opinions about their values, attitudes,
and prioritization of physical activity for themselves as well as their children.
It also asked parents to rank physical activity with respect to 6 other
personal life values (Gomel and Tinsley, 1999, Rokeach, 1973). No study
56


to date has included these specific variables in analyses to predict
childrens physical activity levels. These new data (prioritization and value
ranking), associated with data derived from the social cognitive theoretical
perspective (parent cognition) will contribute to my long-term goal of
devising ways to encourage families and children to develop life-long
healthy exercise habits.
Scoring of prioritization data used a continuous 10cm analog scale
where parents indicated the extent to which they prioritize physical activity
on a daily basis for themselves and their children by marking the scale
lowest priority (0) to highest priority (10). The purpose of these data was
to measure parents ranking of the importance of physical activity in relation
to other life values and how the degree of importance and value is then
associated with their measure of prioritization of physical activity. Finally,
these data were examined to compare how prioritization and value ranking
may beTeflected in the total physical activity measured in both parents and
children.
Family Environment Scale. The Family Environment Scale (FES)
was developed to measure the social-environmental characteristics of
families (Moos & Moos, 1994). The FES specifically assesses 10 areas of
family life. All 10 sub-scales were collected but only one subscale was
incorporated into the data analyses. The activity-recreational subscale,
57


(perceived degree of participation in social and recreational activities within
families), was obtained by asking parents questions about their familys
participation, interest, and importance of activity and recreation (Moos &
Moos, p.1). This subscale was chosen because parents perception of their
familys social environment related to activity and recreation, within social
cognitive theory, may relate to childrens actual participation in physical
activity. According to the social cognitive theoretical model, this
measurement is taken to represent environment. The familys perception
of activity/recreation provides additional data related to parental attitudes
towards physical activity and extends those attitudes to include how parents
perceive physical activity behavior within the family. In addition to parent
modeling physical activity for their children, this broader family variable may
affect habits related to childrens physical activity and may support
childrens physical activity in a more indirect way.
The FES instru^mwit has beeTrused extensively'with good test-retest
reliability (.68-.86) and construct validity. Activity-recreation environment
norms and standard deviations were obtained for minority families (Latino
and African American) with mean scores of 5.01 1.96 and non minority
families with mean scores of 5.33 1.96 (Moos & Moos, 1994). When
scoring the FES, a template is used that divides the difference subscales.
58


The raw score for each subscale in our sample was converted to standard
scores for analyses (Table 4.2).
Table 4.2: Summary of Parent and Child Measurements
Domain ProDosed Measures Parent or Child Measurement
Outcome Child Behavior Childrens physical activity Child measurement
Predictors Parent Behavior Parent physical activity Parent measurement
Parent Cognition Parent prioritization Parent value ranking Parent measurement Parent measurement
Environment Family social environment Parent measurement
Child Cognition Perceived athletic competence Child measurement
Ethnicity Hispanic or non-Hispanic white Parent measurement
59


CHAPTER 5
DATA ANALYSES AND RESULTS
Data Analyses
The study hypothesis is that parents (mothers and fathers) who hold
greater value and priority for physical activity, who positively perceive their
familys social environment related to activity/recreation, who participate in
physical activity themselves, and children with greater perceived athletic
competence will positively correlate with childrens levels of physical
activity. Ethnic and socioeconomic differences in childrens energy
expenditure are postulated to be influenced by differing parental valuation,
prioritization of physical activity for themselves, perceived family
environment of physical activity, parental participation in physical activity,
and, in turn, differences in childrens perceived athletic competence. The
research question stemming from these hypotheses is: To what extent do
mothers and fathers perceived family activity/recreation environment,
parent physical activity, parent prioritization and valuation of physical
activity, and childs (boys and girls) perceived athletic competence predict a
childs physical activity?
60


The data analyses were conducted sequentially, beginning with
descriptive statistics of all outcome and predictor variables by SES and
ethnicity, followed by a series of analyses of variance to assess SES and
ethnic differences in mothers, fathers, and childrens variables. Two-factor
analyses of variance were used to evaluate whether there was an
interaction between SES and ethnicity for each predictor variable using the
outcome variable, childrens physical activity. Next, bivariate correlation
analyses were explored, which in turn, informed the development of
multiple regression analyses to examine the relative contributions and
strength of the predictor variables on the outcome variable. Next,
development and testing of a newly structured model was created to assess
possible alternative paths of influence on childrens physical activity.
Finally, responses to questions from the PAPS that were qualitative in
nature were summarized using percentages.
The independent variables used in these analyses were ethnicity
(Hispanic vs. non-Hispanic white), parental sex (mothers vs. fathers), child
sex (boys vs. girls) and socioeconomic status (high vs. low). The
dependent (outcome) variable is childrens physical activity. The following
variables were investigated as predictor variables that might have
influenced the outcome variable; (1) parental prioritization of physical
activity (2) parental valuation of physical activity (3) parents perceived
61


family social activity/recreation environment (4) parental participation in
physical activity and (5) childrens perceived athletic competence. We
extended previous reports by examining parental prioritization and valuation
of physical activity which might reasonably be expected to influence the
outcome variable.
Statistical power analyses were based on the assumption that the
final model would be a multiple regression containing 5-7 independent
variables. The alpha was set at .05, with a power of .80. Under these
assumptions, a sample of 99 children and 99 parents is sufficient to detect
a cumulative R2 value of 20% (e.g. 20% of the variance in the dependent
outcome measure by 7 variables) (Hair et al., 1998). Using the sample size
employed in this study (99 children and 99 parents), a regression model
that employs seven independent variables to predict childrens physical
activity with an alpha .05 will detect R2 values of 17% and above (Hair et al.,
1998). For complex questions employing both psychological and social
parameters, Cohen (1988) defines an R2> 15% as being of moderate
predictive power and significance value. Significance for all analyses was
set at p <.05. All statistical analyses were performed using SPSS version
10 (SPSS, Chicago, IL, 1999).
Descriptive statistics for each predictor variable and the outcome
variable (children's physical activity) included means, ranges, standard
62


deviations, skewness, kurtosis, test for normality and boxplots/histograms
with normal curve to identify whether variables were normally distributed
and if outliers were present. Parent and child data were analyzed
separately by SES and ethnicity to investigate possible differences in the
effects of the independent variables.
Intrascale reliability (Family Environment Scale and the Harter Scale)
was assessed using Cronbach's alpha; the coefficient was set at .60 to .70
(Hair et al., 1998). The perceived athletic competence scale demonstrated
adequate internal consistency (.76) as did The Family Environment Scale
for perceived family activity/recreation (.72 mothers and .60 fathers) (Figure
5.1).
Figure 5.1: Model
Ethnicity
Socioeconomic status
Parent Valuation of Physical Activity
Family Environment Scale ^
Childrens Physical Activity
Parent Physical Activity
Parent Prioritization of Physical Activity
Childrens Perceived Athletic Competency
Parent variables are analyzed separately for mothers and fathers
Childrens variables are analyzed separately for boys and girls
63


Results
To examine the differing effects of ethnicity and SES upon the
independent variables and the dependent variable the descriptive data are
presented by ethnicity (Hispanic and non-Hispanic white), followed by SES
(high and low). Furthermore, mothers and fathers were examined
separately and not aggregated into families because a greater number of
mothers provided information, a low number of fathers agreed to
participate, and previous research has identified that mothers and fathers
impact upon child physical activity differs (Sallis, 1988).
Descriptive Data and Ethnicity
T tests were used to answer the questions: (1) Do Hispanic and non-
Hispanic white NHW mothers and fathers differ significantly in BMI, parental
prioritization, parental valuation, parents perceived family social
activity/recreation, and^^ntal^articip^tiorrin physical activity? (2) Do
Hispanic and NHW boys and girls differ significantly in perceived athletic
competency, BMI and total physical activity? All descriptive data was
analyzed for the purpose of examining patterns and relationships between
and among variables in both Hispanic and NHW and low and high SES
families.
64


Parent and Child Data bv Sex and Ethnicity
Table 5.1 shows overall differences in mothers and fathers
variables by ethnicity
Differences in Mothers Variables bv Ethnicity
1. Education: NHW mothers have completed more years of
education than Hispanic mothers.
2. BMI: Hispanic mothers had higher BMIs than NHW mothers
and on average were obese.
3. Perceived family activity and recreation: NHW mothers
perception of their familys activity/recreation environment was higher than
that of Hispanic mothers. Note: In this sample, Hispanic mothers mean
value was slightly higher than normative mean value (sample M = 5.7 2.2,
norm M = 5.01 2.3). NHW mothers mean value was slightly higher than
"normative mean value (sampTe M ^6:8 1:9, norm M = 6.31 1.9)
4. Value ranking of physical activity: There were no differences
found between NHW and Hispanic mothers value ranking of physical
activity.
5. Prioritization of physical activity: NHW mothers prioritization
of physical activity for themselves was greater than the Hispanic mothers.
65


Table 5.1: Mothers and Fathers Variables for Ethnicity
03
03
Mother Father
Variable (n = 95) Hispanic (n=45) M SD Non-Hispanic (n=50) M SD t Hispanic (n=28) M SD (n=67) Non-Hispanic (n=39) M SD t
Education 12.3 2.3 15.7 2.8 6.3* 12.1 3.8 17.9 4.1 5.8*
BMI 34.4 8.7 24.9 6.9 -5.7* 28.2 4.0 25.0 2.7 -3.8*
FES 5.7 2.2 6.8 1.9 2.4* 5.8 1.9 6.2 1.7 .1
Value 3.8 1.7 3.5 1.6 -.6 3.1 1.6 3.3 1.6 .6
Ranking
Prioritization 3.9 2.3 5.0 2.9 1.9* 4.7 2.5 5.0 2.8 .4
Total Parent PA
260992.9 88178.3 310046.6 110042.7 *2.4 320933.9 152270.1 322888.2 114109.4 .1
*e < .05


6. Total physical activity: Non-Hispanic white mothers total
physical activity counts were higher than those of Hispanic mothers.
Differences in Fathers Variables bv Ethnicity
1. Education: The NHW fathers had more years of education
than Hispanic fathers.
2. BMI: Hispanic fathers BMI were higher than NHW fathers
and on average were overweight.
3. Perceived family activity and recreation: There were no
difference between NHW and Hispanic fathers perceptions of their
perceived family activity/recreation environment. Note: In this sample,
Hispanic fathers mean value was slightly higher than normative mean
value (sample M = 5.8 1.9, norm M = 5.01 2.33). NHW fathers mean
value was slightly lower than normative mean value (sample M = 6.2 + 1.7,
normMr=6:3T ~T.Q). "
4. Value ranking of physical activity: There were no differences
between NHW and Hispanic fathers.
5. Prioritization of physical activity: There were no differences
between NHW and Hispanic fathers prioritization of physical activity.
6. Total physical activity: There were no differences between
NHW and Hispanic fathers total physical activity counts.
67


Table 5.2 shows the childrens variables for ethnicity.
Childrens Results for Ethnicity
1. BMI: Hispanic children had greater BMIs than NHW children.
This was true for both Hispanic boys and girls compared with their NHW
counterparts. In this sample, there were no differences between girls and
boys BMIs within ethnicity. Note: There are developmental changes in
BMI with age. In this sample of 8-10 year olds, there were no significant
correlation between age of child and BMI. Specifically, when examining
age related BMIs in this sample, mean for age, sex, and ethnicity
associated BMI resulted in no boys or girls falling into the 85 percentile or
above. Therefore, BMI was not age-adjusted because there was no age-
associated variation in this sample.
2. Perceived athletic competency: There were no differences in
athletic competency between NHW and Hispanic children nor between boys
and girls within each ethnicity. Note: When comparing age-related athletic
competence norms to this sample, NHW and Hispanic mean scores were
the same or higher for both girls (NHW M = 3.1, Hispanic M = 3.0 vs. norm
M = 2.7) and boys (NHW M = 3.3 and Hispanic M = 3.1 vs. norm M = 3.1).
It is important to note that these normative values are drawn from primarily
68


Table 5.2: Childrens Variables for Ethnicity
Total
(n=99)
Hispanic Non-Hispanic
(n=48) (n=51)
Variable M SD M SD t
Girls
(n = 45)
Hispanic Non-Hispanic
(n=23) (n=22)
M SD M SD t
Boys
(n=54)
Hispanic Non-Hispanic
(n=25) (n=29)
M SD M SD t
BMI 18.6 4.4 16.9 2.4 -2.6* 17.9 3.7 16.0 2.4 -2.0* 19.3 4.9 17.1 2.4 -1.9*
Athletic 3.0 .7 3.2 .6 1.3 3.0 .7 3.1 .8 .6 3.1 .7 3.3 .5 1.3
competence
Total PA
§ 495988.0 (157132.2) 513300.7 (153271.1) t = .55
Girls
458884.2 (163241.1)494665.2 (141997.5) t = .78
Boys
530123.4 (146260.7) 527437.9 (162319.8) t = -.06
p < .05


lower middle class to upper middle class Caucasian neighborhoods (Harter,
1985).
3. Total physical activity: There were no differences in total
physical activity counts between Hispanic and NHW children nor between
boys and girls within each ethnicity.
In summary, NHW mothers, when compared with Hispanic mothers,
had more years of education, perceived a more positive family social
environment relative to activity/recreation, had higher prioritization of
physical activity for themselves, had higher physical activity counts and
lower BMIs. NHW and Hispanic mothers were equivalent in their value
ranking of physical activity. NHW fathers differed from Hispanic fathers
only in having greater education and lower BMI.
The children did not differ in total physical activity and perceived
athletic competency by either ethnicity or sex. Despite these similarities in
physical activity, Hispanic children had significantly higher BMIs than NHW
children, with the relationship holding within each sex.
These data suggest that the main differences, with respect to
physical activity between Hispanic and NHW families, is in the mothers
predictor variables. Specifically, NHW mothers have greater prioritization,
higher perceived family activity/recreation environment and total physical
activity than Hispanic mothers.
70


Socioeconomic Status
In this study, educational level served as a proxy for determining
SES. Years of education were significantly correlated with the Hollingshead
social class index score (1-5) (_r = .85, jd < .01) and thus, there appeared
to be justification for using education as a proxy for SES. The Hollingshead
index is a two factor index (education and occupation) of social position that
is calculated by multiplying a scale score for occupation and education by a
factor weight. The index of social position score is then classified into 5
score groups with social class 1 being the highest level of social class and 5
being the lowest (Hollingshead, 1965). Hence, by definition, lower SES
parents were less educated than high SES parents. The majority (78%) of
mothers and fathers from lower SES families finished high school but had
no college whereas the majority (84%) of mothers and fathers from high
SES families had completed 4 or more years of college.
T tests were used to answer the questions: (1) Do low and high SES
imothers and fathers differ significantly in BMI, parental prioritization,
parental valuation, parents perceived family social activity/recreation, and
parental participation in physical activity, and (2) Do low and high SES boys
and girls differ significantly in perceived athletic competency, BMI and total
physical activity?
71


Parent and Child Data bv Sex and
Socioeconomic Status
Overall differences and mothers and fathers variables by
socioeconomic status (Table 5.3).
Differences in Mothers Variables bv
Socioeconomic Status
1. BMI: Low SES mothers had higher BMIs compared to high
SES mothers.
2. Perceived family activity/recreation environment: High SES
mothers perception of their familys activity/recreation environment was
greater than that of low SES mothers.
3. Value ranking of physical activity: High SES mothers value
ranking of physical activity is higher than that of low SES mothers.
4. Prioritization of physical activity: High SES mothers
prioritizatiotTof"physical'activityforthemselvesis^higlTertharrlow SES
mothers.
5. Total physical activity: High SES mothers total physical
activity was higher than low SES mothers.
72


w
Table 5.3:
Mothers and Fath
srs Variables for SES
Mother
Father
(n= 95) (n=67)
Variable High SES (n=47) M SD Low SES (n=48) M SD High SES (n=42) t M SD Low SES (n=25) M SD t
Education 16.4 2.3 11.7 2.3 18.4 3.4 10.6 2.9
BMI 23.3 5.2 35.6 8.0 -8.4* 25.7 3.5 27.3 3.7 -1.7
FES 7.2 1.5 5.3 2.2 4.7* 6.6 1.5 5.2 2.1 3.3*
Value 3.2 1.3 4.2 1.8 -3.0* 3.3 1.6 3.0 1.6 .6
Ranking
Prioritization
5.0 2.8 3.9 2.4 2.0* 4.7 2.8 5.2 2.6 -.7
Total Parent PA
320468.6 101541.4 93717.5 13526.9 3.2* 311767.3 109767.0 339382.6 160069.5 -.8
* fi < .05


Differences in Fathers Variables bv
Socioeconomic Status
1. BMI: There were no differences in BMI between low SES and
high SES fathers.
2. Perceived family activity/recreation environment: High SES
fathers perception of their familys activity/recreation environment was
higher than low SES fathers.
3. Value ranking: There was no difference between high SES
and low SES fathers value ranking of physical activity.
4. Prioritization of physical activity: There was no difference
between high SES and low SES fathers prioritization of physical activity.
5. Physical activity: There was no difference between high SES
and low SES fathers total physical activity counts.
Differences in Childrens Variables bv
Socioeconomic Status
1. BMI: Low SES children have significantly higher BMIs than
high SES children and this relationship held within each sex.
2. Perceived athletic competency: Low SES children have lower
perceived athletic competency than high SES children. High and low SES
girls had similar athletic competency scores, but high SES boys scores
exceeded those of low SES boys.
74


3. Total physical activity: There were no differences between low
SES children and high SES children in total physical activity counts nor
between high SES vs. low SES girls or high SES vs. low SES boys.
In summary, the descriptive data examining socioeconomic status
(SES) and sex differences between mothers and fathers predictor
variables indicate (by study design) that low SES mothers and fathers have
lower educational levels. High SES mothers value ranking of physical
activity, prioritization of physical activity, and rating of their perceived family
activity/recreation was greater than that of low SES mothers. High SES
mothers engaged in more physical activity and had lower BMIs than low
SES mothers. High vs. low SES fathers differed on only one variable: their
perception of their familys activity/recreation environment is more positive
than that of low SES fathers
Childrens descriptive data suggests no differences by SES or sex in
total physical activity. However, BMIs were greater in all low SES children
compared to high SES children, and the relationship held true for both girls
and boys. Perceived athletic competency was higher in the high SES
children versus the low SES children overall, but within each sex the
differences reached significance only for boys (Table 5.4).
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Table 5.4: Childrens Variables for SES
Total
(n=99)
High SES Low SES
(n=48) (n=51)
Variable M SD M SD t
Girls
(n = 45)
High SES Low SES
(n=23) (n=22)
M SD M SD t
Boys
(n=54)
High SES Low SES
(n=25) (n=29)
M SD M SD t
BMI 16.3 2.3 18.8 4.2 -3.5* 15.8 2.1 18.2 3.8 -2.5* 16.8 2.4 19.3 4.6 -2.5*
Athletic 3.4 .6 3.0 .7 3.1* 3.2 .7 2.8 .7 1.7 3.4 .5 3.0 .7 3.0*
Competence
Total PA
05 320468.6(101541.4) 93717.5 (13526.9) t = .6
Girls
502084.6 (146555.6) 449501.1 (157427.9) t= 1.2
Boys
525628.3 (151988.2) 531313.0 (157706.9) t =-.1
*e < .05


These data suggest that the primary differences between high and
low SES families reside in the mothers predictor variables. High SES
mothers tend to prioritize, value rank, perceive their familys activity and
recreational environment, and participate in physical activity to a greater
degree than low SES mothers. Although children do not differ in their levels
of physical activity by SES, the low SES children have greater BMIs and
lower perceived athletic competency. Surprisingly, the girls sense of
athletic competency does not differ by SES.
Interaction Between Socioeconomic
Status and Ethnicity
Two factor analyses of variance was employed to assess whether
there was an interaction between ethnicity and SES with respect to
predictor variables or the outcome, childrens total physical activity. The
results showed significant interaction only in mothers prioritization of
physical activity, F (1,94) = 5.74, jd < .02 and mothers total physical
activity, F (1,94) = 13.9, q. = -00. High SES Hispanic mothers and low SES
NHW mothers had lower scores for prioritization of physical activity and
lower total physical activity. Otherwise, there was no interaction between
SES and ethnicity in any of the predictor or outcome variables for all
parents, fathers, all children, boys or girls.
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The inequity in samples sizes impacted data analysis in that the low
SES group included a larger percentage of Hispanic subjects vs. NHW
subjects (76% vs. 23%, respectively) and the high SES group included a
larger percentage of NHW vs. Hispanic subjects (81% vs. 18%,
respectively). Data were collected from 99 families and included n = 39 low
SES Hispanic families, n = 9 high SES Hispanic families, n = 39 high SES
non-Hispanic white families, and n = 12 low SES non-Hispanic white
families. There is an increased chance of committing a type II error
(concluding that there is no significant difference or relationship when there
is) because power (probability of detecting a true difference) was decreased
by separating the sample into differing SES groups within each ethnic
group. Based on the current data, sample sizes of high SES Hispanic and
low SES NHW subjects would need to be increased to demonstrate a
significant affect of SES and ethnicity interaction. With alpha set at .05,
desired power of .80, 3 degrees of freedom (four groups), and an effect size
of .30 (Cohen, 1987, defines a moderate effects size as .25), the sample of
9 high SES Hispanic families and 12 low SES NHW families would need to
be increased to 27 subjects in each group. Because there are 4 groups, a
total of 108 families would be needed to address the problematic sampling
issue defined above.
78


Correlation Analyses
Following evaluation for potential interaction between SES and
ethnicity, Pearson correlations between childrens total physical activity and
the hypothesized predictor variables were examined. These analyses were
conducted to explore the relationships between predictor and outcome
variables, not for the purpose of testing the study hypotheses. Mothers
and fathers data were analyzed separately by ethnicity and SES. Mothers
are shown in Tables 5.5 to 5. 8 and fathers in Tables 5.9 to 5.12.
Mothers Correlation Data
Table 5.5: Hispanic Mothers Correlation Matrix (n=45)
Variables Act/Rec Value Rank Prioritization Mothers PA Athl Como. ChildPA
Act/Rec .004 .057 .089 .502* .205
Value Rank -.367* .167 .121 .105
Prioritization -.018 -.389** -.317*
Mothers PA .070 .153
Athl. Comp. .371**
Child PA
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**£. < .01, two tailed
*p < .05, two tailed
79


Table 5.6: Non-Hispanic White Mothers Correlation Matrix (n=50)
Variables Act/Rec Value Rank Prioritization Mothers PA Athl Como. ChildPA
Act/Rec .328* * .336* .447* .165 -.020
Value Rank -.484** -.258 .121 .228
Prioritization .235 .288* .110
Mothers PA -.082 -.063
Athl. Comp. .216
Child PA
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**P_ < .01, two tailed
*p < .05, two tailed
Table 5.7: High SES Mothers Correlation Matrix (n=47)
Variables
Act/Rec Value Rank Prioritization
Mothers PA Athl Comp. ChildPA
Act/Rec
Value Rank
Prioritization
Mothers PA
Athl. Comp.
Child PA
.093 .271 .299*
-.327* .192
.275
.126 .115
.127 .100
.001 .021
.277 -.077
.237
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**E_ < .01, two tailed
*p < .05, two tailed
80


Table 5.8: Low SES Mothers Correlation Matrix (n=48)
Variables Act/Rec Value Rank Prioritization Mothers PA Athl Como. ChildPA
Act/Rec -.106 .113 .159 .338* .069
Value Rank -.476** .184 -.010 .262
Prioritization -.054 -.081 -.426**
Mothers PA -.056 .117
Athl. Comp. .339*
Child PA
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**£_ < .01, two tailed *p < .05, two tailed
Similarities between Hispanic and NHW mothers variables include
the positive association between prioritization and value ranking (the
negative correlation coefficient is an artifact of the scales used). The main
difference was a negative association between Hispanic mothers
prioritization and childrens athletic competence and mothers prioritization,
whereas NHW mothers show a positive relationship between their
prioritization of physical activity for themselves and their childrens athletic
competence.
Similarities between low and high SES mothers variables include the
positive relationship between prioritization and value ranking of physical
activity. Low SES mothers prioritization of physical activity was negatively
81


associated with childrens total physical activity. High SES mothers
favorable perception of the family activity/recreation environment is
positively associated with their own physical activity, but not that of their
children. Low SES children had a positive relationship between perceived
athletic competence and physical activity, whereas a similar relationship in
high SES was not significant (jd = .05)
Fathers Correlation Data
Table 5.9: Hispanic Fathers Correlation Matrix (n=28)
Variables Act/Rec Value Rank Prioritization Fathers PA Athl ComD. ChildPA
Act/Rec -.284 -.049 .364 .150* -.085
Value Rank -.180 -.335 -.015 .182
Prioritization Fathers PA Athl. Comp. Child PA .331 -.003 -.025 -.203 -.207 .371**
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**g < .01, two tailed
*p < .05, two tailed
82


Table 5.10: Non-Hispanic White Fathers Correlation Matrix (n=39)
Variables Act/Rec Value Rank Prioritization Fathers PA Athl ComD. ChildPA
Act/Rec -.036 -.061 .284 .119 .208
Value Rank -.735** -.178 -.017 -.133
Prioritization .347* -184 -.031
Fathers PA .109 .342*
Athl. Comp. .216
Child PA
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**p < .01, two tailed
*p < .05, two tailed
Table 5.11 : High SES Fathers Correlation Matrix (n=42)
Variables Act/Rec Value Rank Prioritization Fathers PA Athl ComD. Chile
Act/Rec -.285 .230 .545** .215 .248
Value Rank -.654** -.159 -.055 -.107
Prioritization Fathers PA Athl. Comp. Child PA .309* -.120 -.111 -.100 .222 .237
Note: For value ranking a negative coefficient represent a positive relationship
between variables.
**p < .01, two tailed
*E < .05, two tailed
83


Table 5.12: Low SES Fathers Correlation Matrix (n=25)
Variables Act/Rec Value Rank Prioritization Fathers PA Athl ComD. ChildPA
Act/Rec -.035 -.391 .288 -.107 -.188
Value Rank -.237 -.353 .006 .182
Prioritization .388 -035 .121
Fathers PA -.155 -.088
Athl. Comp. .339*
Child PA
Note: For value ranking a negative coefficient represent a positive relationship between
variables.
**g < .01, two tailed
< .05, two tailed
There are no similarities between the correlation matrices of the
Hispanic and NHW fathers. There is a positive association between NHW
fathers physical activity and childrens physical activity, whereas, a non-
significant negative correlation is observed in Hispanic fathers. NHW
fathers value ranking of physical activity and their prioritization of physical
activity for themselves are strongly related. NHW fathers prioritization is
also related to their own physical activity. Hispanic childrens physical
activity is positively associated with their athletic competence, but a similar
relationship in NHW children is not significant. Low vs. high SES fathers
also show different patterns of correlation. Athletic competence is positively
associated with childrens physical activity in the low SES group, but not in
the high SES group. A strong positive association is present between high
84


SES fathers prioritization of physical activity, perceived family
activity/recreation environment and their own participation in physical
activity.
Multiple Regression Analyses
Standard multiple regression analyses were performed between
childrens total physical activity counts as the dependent variable and
ethnicity, socioeconomic status, perceived family activity/recreation, value
ranking of physical activity, prioritization of physical activity, parents total
physical activity and childrens athletic competence as independent
variables. Socioeconomic status and ethnicity interacted only in the
mothers model, therefore, SES and ethnicity were not included in the
fathers multiple regression analyses.
Mothers
The full equation was not significant (g= .154). The hypothesized
relationships between mothers predictor variables and childrens physical
activity are not evident. Subsequent analyses will examine possible
intervening variables related to childrens physical activity.
<
85


Fathers
The full multiple regression equation was not significant (jd = .152).
The hypothesized relationships between fathers predictor variables and
childrens physical activity were not supported.
Model Restructure
To achieve a more comprehensive description of childrens total
physical activity, the original model was restructured and examined further.
Development and testing of this newly structured model provides
information concerning possible alternative paths of influence of the
independent variables related to childrens physical activity. The theorized
model includes a series of seven hypotheses based on extant literature
pertaining to the present study. Socioeconomic status and ethnicity are
antecedent (demographic) variables that cannot be influenced by
psychosocial variables. Therefore, proposed model presented in Figure 5.2
begins with SES and ethnicity. Mothers and fathers were explored
separately.
86


Full Text

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PARENTAL INFLUENCE ON PHYSICAL ACTIVITY IN HISPANIC AND NON-HISPANIC WHITE CHILDREN by Mary J. Barry B.S.N., University of Colorado Health Sciences Center 1979 M.S., Chapman University, 1988 A thesis submitted to the University of Colorado at Denver in partial fulfillment of the requirements for the degree of Doctor of Philosophy Health and Behavioral Sciences 2000

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This thesis for Doctor of Philosophy degree by Mary J. Barry has been approved by

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I I I i i I l I i I I I I Barry, Mary J. (Ph.D., Health and Behavioral Sciences) Parental Influence on Physical Activity in Hispanic and Non-Hispanic White Children Thesis directed by Associate Professor Stacy Zamudio ABSTRACT The purpose of this study was to identify social, psychological and environmental determinants of 3-5th grade Hispanic and non-Hispanic white (NHW), and high and low socioeconomic status (SES) children's physical activity. To predict children's physical activity level we measured: (1) children's perceived athletic competence, (2) parent prioritization of activity for themselves, (3) parent ranking of the importance of physical activity, (4) parent perceived family activity/recreation environment; and (5) parent total physical activity. Physical activity was measured using uniaxial accelerometers in parents (51 non-Hispanic white, 48 Hispanic, 48 high SES and 51 low SES families) and their children over 7 days. Each predictor variable was explored to assess for possible interaction between ethnicity and SES. Socioeconomic status had a greater influence on children's physical activity than ethnicity in this sample. Non-Hispanic white and high SES mothers scored higher on their perceived importance of family activity/recreation, prioritization of physical activity for themselves, and were more physically active than Hispanic and low SES mothers. High SES mothers had greater ranking of the importance of physical activity than low SES mothers. There was an interaction between SES and ethnicity across all mothers such that low SES Hispanic and high SES NHW mothers had greater prioritization of physical activity for themselves and total physical activity than high SES Hispanic and low SES NHW mothers. High SES mothers' valuation of physical activity was greater than low SES mothers. There were no differences in physical activity levels between Hispanic vs. NHW and high and low vs. high SES children, yet Hispanic and low SES children's BMis were higher than NHW and high SES children's BMis. iii

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,... ......... ,... ................. -J ___ :.a.L. ---There are no differences between Hispanic vs. NHW fathers' predictor variables nor did any of fathers' data relate to children's physical activity levels or perceived competence. High SES fathers had greater perceived family activity/recreation environment than low SES fathers. For all groups, children's physical activity was best predicted by children's perceived athletic competence. A re-specified model was developed and tested resulting in mothers' physical activity and prioritization affecting family's activity/recreation and thus, children's perceived athletic competence and physical activity . This abstract accurately represents the content of the candidate's thesis. recommend its publication. iv

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DEDICATION I dedicate this thesis to all those who have supported, encouraged, whined, tolerated and loved me through "the process." To my running buddies who never acted bored and even pretended to listen; to my sisters who have always inspired me and certainly have been my "biggest fans," especially to my sissy, Janny, who helped me with Cro-Magnon analyses, bragged to her friends unnecessarily, and never once told me I was crazy, even though she thought I was; of course to my mom and dad who DID tell me I was crazy but nonetheless, set the foundation for all my successes in life. To my friends (Mickey and Gene, Mary Jo, Gina, Mary H. and John, Cecilia, Marcia, Mary D. and Jim, Lauren) who must have wanted to check me off their lists, but never failed to include me in get-togethers and routine phone calls to check-in; to my classmates, especially to my pal Meredith, who REALLY understood the hoops of academia and who permitted many whining sessions; to my committee chair, Stacy Zamudio, who never quit pushing the standards for excellence, never lost her patience, and most importantly never stopped believing in me. Stacy's commitment and dedication to her students is extraordinary. Finally and most importantly, I dedicate this thesis to my ultimate supporters, Frank, Colleen, and Megan, who lived through "the process" day in and day out. They never complained about my "tuning out," late nights at school, data collection panics, too many fast food burrito dinners, missed soccer, school, and social events. It is inconceivable the tolerance and loving support they sustained over these past few years. It took more than a village. Thank you.

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ACKNOWLEDGEMENT My most sincere thanks go to my committee members, Stacy Zamudio, Susan Johnson, David Tracer, and Nancy Hester. Stacy, who was my consistent support and stabilizing force; Susan, who persevered the process from the very beginning when I was truly "green" and taught me everything I needed to know about the infamous "process;" David, who shared in my tribulations during data collection but always shared in the peaks and valleys; Nancy who amidst her changing life, made time when there was none; Carol Vojir, who at the end threw in life saving statistical advice; and Ed Melanson, who provided expert guidance with physical activity data. No words can express my gratitude for your hours of dedication. Thank you all.

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CONTENTS Figures . . . . . . . . . . . . . . . . . . . . . . xii Tables . . . . . . . . . . . . . . . . . . . . . . xiii CHAPTER 1. INTRODUCTION .................................. 1 Background ................................ 1 Determinants of Physical Activity in Hispanic and non-Hispanic White Children ................... 4 The Energy Equation and Definition of BMI ... 4 Physical Activity and Its Health Related Effects On Children ..................... 6 Factors Influencing Children's Physical Activity . . . . . . . . . . . . . . 9 2. THEORETICAL ISSUES AND MODELS .............. 24 Social Cognitive Theory ...................... 26 ParnntCognffion ...................... 36 3. RESEARCH QUESTION AND PRELIMINARY DATA .... 39 Research Question .......................... 39 Hypotheses .......................... 40 Preliminary Data .......................... 41 vii

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Questionnaire Development ............. 41 Physical Activity Prioritization Survey Questions ............................ 42 Pilot Questionnaire Results .............. 45 4. RESEARCH DESIGN AND METHODS ............... 4 7 Overview ................................. 4 7 Subjects ............................. 49 Subject Payment ...................... 51 Measurements ........................ 51 5. DATA ANALYSES AND RESULTS ................... 60 Data Analyses ............................. 60 Results ................................... 64 Descriptive Data and Ethnicity ............ 64 Parent and Child Data by Sex and Ethnicity ....... 65 Differences in Mothers' Variables by Ethnicity ..... 65 Differences in Fathers' Variables by Ethnicity ..... 67 Children's Results for Ethnicity ................. 68 Socioeconomic Status ....................... 71 Parent and Child Data by Sex and Socioeconomic Status . . .............. 72 Differences in Mothers' Variables by Socioeconomic Status .................. 72 Status .............................. 72 viii

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Differences in Fathers' Variables by Socioeconomic Status .................. 7 4 Differences in Childrens' Variables by Socioeconomic Status .................. 7 4 Interaction Between Socioeconomic Status And Ethnicity .............................. 77 Correlation Analyses ................... 79 Mothers' Correlation Data ............... 79 Fathers' Correlation Data ................ 81 Multiple Regression Analyses ................. 85 Mothers ............................. 85 Fathers .............................. 86 Model Restructure .......................... 86 Hypotheses ............................... 87 Mothers ............................. 90 Fathers .............................. 92 Summary of Theorized Hypotheses ........ 93 Qualitative Data ............................ 94 6. DISCUSSION AND CONCLUSION .................. 98 Discussion ................................ 98 Main Findings Compared with Past Studies ...... 1 00 Children's Athletic Competence and Children's Physical Activity ............. 1 00 ix

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II I I i I I i I I I APPENDIX SES and Children's Physical Activity ...... 101 Ethnicity, Children's Physical Activity, and BMI ........................... 103 Mothers' vs. Fathers' Influence on Children's Physical Activity ............. 105 Organized Sports and Children's Physical Activity . . . . . . . . . . . . . . 1 06 Parent and Child Physical Activity Relationship ......................... 107 Summary of Relationship Between SCT and Children's Physical Activity ................... 108 Weaknesses and Strengths of Study ........... 11 0 Future Research Questions .................. 114 Conclusion ............................... 116 A. EVIDENCE TABLES OF CRITICAL STUDIES RELATED TO PHYSICAL ACTIVITY IN CHILDREN .... 118 B. SURVEY INSTRUMENTS ......................... 134 Socioeconomic Status Questionnaire ........... 135 Family Environment Scale ................... 136 Harter Scale .............................. 140 Prioritization Questionnaire .................. 143 c .................................................. 145 Introductory Letter to Parents ................. 146 X

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Guidelines for Prioritization Questionnaire ...... 147 Information for Accelerometers ............... 148 7 Day Monitoring Record .................... 149 D. ............................................ 150 Parent Consent ........................... 151 Children Assent ........................... 1 53 REFERENCES ............................................ 154 xi

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FIGURES Figure 2.1 Bandura's Triadic Model ................................ 26 2.2 Social Cognitive Model of Parental Influence ................ 28 2.3 Role Modeling/Observation Learning ....................... 32 2.4 Environment/Situation .................................. 34 2.5 Self-Efficacy .......................................... 36 2.6 Parent Cognition ...................................... 38 5.1 Model ............................................... 63 5.2 Theorized Model to Be Tested ............................ 87 5.3 Re-specified Model Related to Mothers' Variables ............ 91 5.4 Re-specified Model Related to Fathers' Variables ............. 92 xii

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TABLES Table 1. Percentiles for BMI in U.S. Children 8-10 Years ............... 7 2. 1 Theories and Models ................................... 25 4.1 Total Daily Energy Expenditures (kcal/kg/day) ............... 47 4.2 Summary of Parent and Child Measurements ................ 59 5.1 Mothers and Fathers Variables for Ethnicity ................. 66 5.2 Children's Variables for Ethnicity .......................... 69 5.3 Mothers and Fathers Variables for SES .................... 73 5.4 Children's Variables for SES ............................. 76 5.5 Hispanic Mothers' Correlation ............................ 79 5.6 Non-Hispanic White Mothers' Correlation Matrix .............. 80 5. 7 High SES Mothers' Correlation Matrix ...................... 80 5.8 Low SES Mothers' Correlation Matrix ...................... 81 5.9 Fathers' Correlation Data ................................ 82 5.1 0 Non-Hispanic White Fathers' Correlation atrix ............... 83 5.11 High SES Fathers' Correlation Matrix ...................... 83 5.12 Low SES Fathers' Correlation Matrix ....................... 84 xiii

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5.13 Hypotheses Summary .................................. 93 5.14 Responses From PAPS ................................. 95 xiv

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CHAPTER 1 INTRODUCTION Background Our technologically advanced environment permits less energy expenditure in day to day life and promotes increased sedentary lifestyles. Twenty percent of United States children participate in two or fewer bouts of vigorous activity per week, and girls are especially likely not to exercise vigorously (26% versus 17% in boys (NHANES Ill). Further, 26% of children watch four or more hours of television daily. Boys and girls who watch four or more hours/day of television have higher body fat (JL < .001) and body mass index (BMI) (Q < .001) than children who watch less than 2 hours/day of television (Anderson et al., 1998). Despite the health benefits of regular physical activity (protection from cardiovascular disease, hypertension, obesity and poor self-image) (Baranowski et al., 1992), children are not meeting national health objectives of daily light to moderate physical activity for 30 minutes/day (USDHHS, 1990, Kann et al., 1996). Energy expended through physical activity helps to maintain the balance between calories consumed (energy input) and calories burned (energy expenditure). When energy intake exceeds the sum of energy 1

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expenditure and basal metabolic rate (BMR), weight gain results. Physical activity has been shown to diminish the prevalence of obesity, cardiovascular disease, and diabetes in adults (Bouchard, et al., 1994). Obesity has increased nationwide with obesity rates over 14% in four states in 1991 to thirty-seven states by 1998 (www.cdc.gov,2000). The increasing prevalence of obesity in US children (25%) with 40% having at least one cardiovascular risk factor related to being overweight (Troiano et al., 1998) suggests that children are less active now than they have been in the past (Baranowski et al, 1987) and thus are at increased risk for cardiovascular disease and diabetes. Obesity and the diseases linked to it are more common in women than men, more prevalent in lower socioeconomic status (SES) groups, those with less education, and minorities (USDHHS, 1996). Minority groups, especially Latinos and Hispanics, are more likely to be inactive and consistently have larger body mass indices (BMI) than Euro-Americans (NHANES Ill, Robinson, 1995). Exercise habits formed early in life impact upon later behavior. Less active children remain less active into adolescence and adulthood (Pate et al., 1996). Obesity in childhood after the age of 6 years increases the probability of obesity in young adulthood (21-29 years of age) by 50%. Non-obese children, in comparison, have a 10% probability of obesity in adulthood. Moreover, obese children with at least one obese parent have a 2

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79% higher risk of remaining obese into adulthood than children without an obese parent (Whitaker et al., 1997). Developing and maintaining healthy activity levels in youth (30 minutes of daily light-moderate physical activity) appears to be an effective way to prevent childhood obesity (USDHHS, 1996). In a society where high fat foods are readily available and aggressively promoted, regular exercise can prevent obesity and health-related diseases throughout childhood, adolescence, and ultimately adulthood (Stefanick, 1993). Physical activity in youth is a modifiable behavior that correlates with diverse environmental, psychological and sociocultural influences. Presently, there is limited understanding of factors that influence children's physical activity, particularly in minority children. Understanding the determinants of physical activity in minority children is crucial in preventing the onset of obesity, particularly in Hispanics who represent the fastest growing segment of the United States population (Rauh et al., 1992). Although several recent studies have examined psychosocial and environmental determinants of physical activity in African-American and Caucasian children (Trost et al., 1999, Lindquist et al., 1999), Hispanic populations have been under-investigated with respect to physical activity. 3

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Determinants of Physical Activity in Hispanic and non-Hispanic White Children This section begins by describing important measurements used to characterize weight: first, the energy equation and second, the definition of body mass index. Next, physical activity and its health related effects in children are described. Then the factors that influence children's physical activity are explored. Finally, intervention strategies are summarized. The Energy Equation and Definition of BMI Energy balance and weight stability depend on the relationship between calories consumed (energy input) and calories burned (energy expenditure). Total energy expenditure is determined by the cumulative effects of resting metabolic rate (RMR), the thermic effect of food (TEF), and physical activity, which increases metabolic rate and therefore increases energy expenditure (DeLany & Lovejoy, 1996). Stored energy reserves develops when energy intake exceeds energy expenditure. All else being equal, physical activity, the most variable and modifiable component of an individual's energy balance (DeLany & Lovejoy, 1996), has been shown to prevent weight gain and protect against the onset of obesity in adults (Grilo, 1995; Stefanick, 1993) but there is no direct evidence of this influence in children. Prospective 4

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I I I I I I i I I i I I I I I i I I I I i I i i i investigations have shown men and women who reported higher physical activity at baseline and follow-up (over 10 years) gained less weight than those who reported less activity (Kahn et al., 1997, Williamson et al., 1993). These findings support the widely held belief that more physically active adults have a lowered incidence of obesity and gain less weight over time. Accordingly, increasing levels of obesity in US children, concurrent with the fact physical activity levels decline with age (Sallis, 1993 ), suggest that similar trends also apply to children. While it is clear that physical activity declines with age, there is accumulating evidence that physical activity, fitness and endurance among youth has declined over the past several decades (luepker, 1999). Body mass index (BMI; weight in kilograms/height in meters2 ) is a reliable measure of overweight and obesity status in children and adolescents (Rosner et al, 1998). Dual photon absorptiometry (DXA), a gold standard measure of body composition, has demonstrated that body fat is correlated (r = .79-.83) with BMI, supporting the use of BMI as a valid measure of body composition in children and adolescents (Pietrobelli et al, 1998). Adults are overweight when their BMI is between 25.0 and 29.9. Adults are obese when their BMI exceeds 30.0 kilograms/meter2. These definitions of what comprises "overweighe versus "obese" are based on the 5

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National Health and Nutrition Examination Survey (NHANES I) (Must et al., 1991 ). The Expert Committee on Clinical Guidelines for Overweight in Adolescent Preventive Services defined overweight as BMI equal to or in excess of the 95th percentile for age and gender or greater than 30 kg/m2 whichever is smaller (Rosner et al., 1998). Table 1.1 shows the percentile ranking of BMI for children aged 8, 9, and 10 years. Both sex and ethic differences are included and serve as a screening tool to identify those children at risk for overweight and obesity. Physical Activity and Its Health Related Effects in Children The specific health effects of physical activity have primarily been studied in adults and adolescents; data are limited in younger children (Rigotti et al., 1984, Tipton et al., 1983, Surgeon General Report, 1996). There is little evidence that exercise in the growing years directly improves the health of children; yet exercise in adolescence contributes to favorable health status into adulthood. Results from the Harvard alumni study show that young adults who were active as children and became sedentary in their adult years had a higher risk of coronary artery disease when compared to those individuals who continued to be active (Paffenbarger et al., 1986). These data suggest that continuous participation in daily activity 6

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starting in young adulthood provide long-term health benefits. For the most part, we can infer that children who are physically active throughout childhood and adolescence may be more likely to continue being active as adults (Blair et al., 1 989). Thus, increasing physical activity (the amount of movement performed on a daily basis) in childhood may be one approach to the prevention of disease later in life. Table 1.1 Percentiles for BMI in U.S. Children 8-10 Years GIRLS BOYS Age Percentile Hispanic White Hispanic White 8 years 5% 14.0 13.5 14.2 14.1 15% 14.9 14.3 15.1 14.9 50% 16.3 15.7 16.6 16.2 75% 18.8 17.4 18.3 17.5 85% 20.2 18.6 19.5 18.6 95% 22.9 21.2 22.7 21.4 9 years 5% 14.1 13.6 14.4 14.3 15% 15.1 14.5 15.4 15.1 50% 16.9 16.2 17 16.6 75% 19.7 18.3 19.1 18.3 ------------------------85% 21.4 19.7 20.7 19.7 95% 24.3 22.6 24.4 23.0 10 years 5% 14.4 13.9 14.7 14.6 15% 15.5 14.9 15.6 15.4 50% 17.6 16.9 17.6 17.1 75% 20.8 19.3 20.0 19.2 85% 22.7 21.0 21.9 20.9 95% 25.8 24.1 25.9 24.5 Note: Adapted from Rosner et al., 1997. 7

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Few studies have focused on the health effects of physical activity in young children. Research has focused primarily on children aged 11-21 years (preadolescence through young adulthood) and shows that; 1) physical fitness is minimally correlated (r = .17) with physical activity (Morrow & Freedson, 1994); 2) physical activity is positively associated with self-esteem, self-concept, or self-efficacy (Calfas & Taylor, 1994); and 3) the amount of energy expenditure and the degree of adiposity found in adolescents is not necessarily correlated, with various studies unable to find a relationship (Bar-Or & Baranowski, 1994 ). Studies examining physical activity relative to the degree of adiposity in children are inconsistent. One study found total energy expenditure, measured by doubly labeled water and room calorimetry, between obese and lean prepubertal children to be similar (Treuth et al., 1998). However, there was a 14kg weight difference between the heaviest and the leanest children, but no difference in their fat-free mass (underlying lean tissue mass was similar). When the lack of difference in fat-free mass between the lean and obese children was accounted for, obese children were found to have reduced activity levels (Delany et al., 1995 and Treuth et al., 1998). Cross-sectional studies of body composition show that greater physical activity is correlated with less fat mass in children (Delany, 1998). However, longitudinal studies examining exercise in relationship to the 8

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changes in body composition that occur in preadolescents. show no relationship between fat mass and energy expenditure (Goran et al., 1998). The developmental changes seen in children as they approach adolescence, in combination with the physiological differences between sexes, may contribute to the inconsistent findings in the research relating to the role of physical activity and its impact on obesity (Goran et al., 1999). Furthermore, the difficulty associated with accurate measurement of physical activity may explain the disparity seen in the aforementioned studies between energy expenditure and adiposity in young children. Because physical activity is essential to the regulation of energy balance, numerous studies have investigated an alternative mechanism, physical inactivity, to help explain the etiology of childhood obesity. Physical inactivity has been examined for the purpose of exploring behaviors that may replace time spent being physically active. Factors Influencing Children's Physical Activity Many factors influence children's patterns of physical activity, including access to sedentary play, their parents' beliefs and attitudes, their parents' level of activity, and the children's ethnicity. These are further described, below. 9

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Access to Sedentary Play. Television viewing, video game playing, and personal computing have been studied as potential contributors to childhood inactivity and subsequent obesity (Dietz & Gortmaker, 1985, Gortmaker et al., 1996, Bouchard, 1997, Robinson & Killen, 1995). One study of 1 ,912 ethnically diverse ninth graders (34. 7% Latina/Hispanic, 27.9% Asian/Pacific Islander, 22% white, 6.8% African American, 1.7% Native American/Alaskan Native, 2.0% other, and 4.8% belonged to more than one ethnic groups) examined the relationship between television viewing and obesity. Statistically significant positive correlations (r= 0.19 to 0.25) were found between hours of television viewing and intake of high fat foods. No statistically significant correlation was found directly between hours of television viewing and BMI. This finding suggests that BMI may be mediated by the effects of consuming excess dietary fat while watching television (average 41.8 hours per week for the entire sample) (Robinson & Killen, 1995). Kleges (1994) found a lowered metabolic rate (-211 kcal/day caloric expenditure at rest) in both obese (n = 15) and normal-weight (n = 16) children while watching television. These two studies illustrate the complexity of the interplay between variables: Television watching both lowers BMR and stimulates an increased fat intake, both of which influence children's BMI. 10

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A more direct relationship between television viewing and body fat was reported by the NHANES Ill Survey. Children (n= 4,063 aged 8 through 16) who watched 4 or more hours of TV per day had significantly greater body fat (JL < .001) and greater BMis (Q... < .001) than those who watched 2 hours per day (Andersen et al., 1998). A recent study sought to determine whether limiting sedentary activities (television viewing, video game playing) would decrease BMI. Those in the intervention group (limited television viewing, video game playing) showed a significant decrease in BMI from their pre-intervention BMI when compared with control children (no TV or video limits) (Q... < .002). This change occurred despite similarity between the intervention and control groups for changes in moderate-to-vigorous physical activity, high-fat food intake or cardiorespiratory fitness (Robinson, R., 1999). It is important to note that physical activity was measured using recall method, which should be interpreted with caution because the ability of young children to accurately recall events is questionable (Sallis, 1991, Sallis et al., 1996). However, taken together, the data support that the current rate of childhood obesity might be ameliorated by limiting the time children spend watching television or in other forms of sedentary play. Limited community resources that provide safe places for children to congregate and budget constraints in schools that restrict programs and 11

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equipment, contribute to decreased participation in physical activity (Bar-Or et al., 1998). Parents may limit their children's outdoor playtime, and may even drive them to and from nearby schools due to concerns over neighborhood safety. Furthermore, access to organized sports may be limited by parents' financial resources which may further decrease children's opportunities to participate in physical activity (Sallis et al., 1997). Those factors that supplant physical activity in children as well as barriers to participation in physical activity contribute to children's inactivity. Parental Attitudes/Beliefs. Because it is likely that children's habits are developed early in childhood, parental influences, attitudes and values related to physical activity may be important determinants of children's exercise habits (Moore, 1991 ). Within families, parents are strong and credible models for young children (Sallis, 1992). Attitudes and behaviors relating to physical activity, exercise, games and sports are learned and -reinforced by -parents-in-the-home -environment (Brustad, 1993). As children reach adolescence, different factors play a part in influencing levels of physical activity such as peers, school, coaches and media (Raudsepp & Viira, 2000). Parents' and children's attitudes and beliefs about children's physical activity are under investigated in terms of how they influence children's participation in physical activity. One study examining the relationship 12

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between children's and parents' beliefs regarding physical activity showed a number of important findings (Kimiecik et al., 1996). Children's beliefs (degree to which they value participation) about physical activity were significantly related (Q < .001) to their parents' beliefs about physical activity. Further, children's perceptions of their parents' belief about their child's physical activity and fitness and their own belief about moderatevigorous activity were significantly related (Q < .001 ). These findings confirm that parental beliefs and attitudes are one source of influence upon children's activity levels and may serve to significantly influence children's behavior (Kimiecik et al., 1996). Furthermore, Kimiecik and Hom (1998) found that parents' positive beliefs about their child's physical competence and goal orientations for their child contributed significantly (26.9% of the variance, R < .009) to their child's engaging in moderate to vigorous physical activity. Therefore, when parents have positive beliefs and --attitudes towards physical activity,their children's physical activity increases. When parents value and prioritize physical activity, they will more likely be active themselves and thereby influence their child's opportunity to participate in physical activity. This specific construct, referred to here as "prioritization", has not yet been studied and is a primary focus of this project. I hypothesized that prioritization and valuation of physical activity 13

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would relate to children's activity levels. If true, interventions may be developed to change health behaviors when parents consider it important and are ready to make a behavioral change. Conversely, if parents do not prioritize or value physical activity for themselves or their children, intervention strategies may focus on changing health beliefs prior to changing behavior. Parental Activity. One of the most influential determinants of children's physical activity is parents' degree of physical activity habits. Parents serving as role models is one possible reason for this association (Moore et al., 1991 ); however, there is variation in the extent to which studies have found that parent role modeling influences their children's exercise habits. Moore et al. (1991 ), using an objective measure of energy expenditure (accelerometers), obtained physical activity levels over M = 8.6, SO =1.8 days for 100 children, M = 8.3, SO = 2.1 for their mothers (n = 99), and M = 7.7, SD = 2.3 for their fathers (n = 92). Children (4-7 years old) of active mothers (average Caltrac accelerometer counts per hour greater than the median) were two times as likely to be active as those of inactive mothers. When both parents were active, children were 5.8 times as likely to be active. These results contrast with those of another study where children's activity levels were correlated (r = 0.45) with that of their mothers, but not with that of their fathers (Sallis et al., 1988). However, as 14

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opposed to direct measurement of physical activity, the 7 day physical activity recall (PAR-7), an interviewer-administered subjective method of data collection for physical activity, was used in the latter study. Self-reports of children's physical activity are limited in accuracy and recall of habitual exercise and therefore challenge the validity and reliability of self-reported physical activity. In contrast to these two studies, McMurray et al. (1993) reported that parents' exercise practices did not influence their children's activity levels (R2 = .006). Again, however, this study used self-reported activity (SRA) to measure physical activity in 3rd and 4th grade children and their parents. Lastly, in a study involving both Mexican American and Anglo families, Sallis et al. (1988) found a moderate degree (I= 0.450.55) of family aggregation of physical activity with mother-child correlation higher than father-child correlation. Mexican American families had higher intrafamily corrrelations than the Anglo families suggesting that the differing -Intensity of fatnily-rnfiOehCef American families may be related to an increased reliance or cohesion among family members that influences physical activity. Differences among the studies described above may be due to the different direct versus indirect methods for measuring physical activity. Because physical activity is a complex behavior, measurement is also complex. The disparate associations between parents' physical activity 15

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and that of their children might be clarified by using more precise measurement of physical activity (accelerometers) versus the more common subjective measures (mothers answering questions pertaining to child's activity, children self-reporting). The review above should make clear that determinants of children's physical activity patterns are multifactorial. Therefore, studies must examine multiple domains in an effort to identify those factors that contribute substantially to the development of good versus poor physical activity habits. In addition, precise and consistent measures of children's activity are needed to resolve conflicts within the relevant literature. Ethnicity. In a review of approximately 300 studies investigating determinants of physical activity in adults, Dishman and Sallis (1994) summarized nine modifiable variables most consistently associated with overall physical activity: social support, self-efficacy, perceived barriers, perceived benefits, enjoyment of-physical activity, processes of change, intention to exercise, lower intensity of exercise, and eating habits. Few of these studies included diverse ethnic and socioeconomic samples. For Hispanic adults, the predictive variables related to physical activity indicate that self-efficacy, friends' support, childhood physical activity and eating a heart healthy diet are important (Hovell et al., 1991 ). The determinants of physical activity related to Hispanic children are not understood and further 16

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investigation is needed to identify the variables that influence physical activity in this subgroup. Examining socio-cultural contributors to exercise behavior and their association with body size in adults and children may further our understanding of belief systems regarding physical activity and body size that contribute to inactivity and increased body fatness. Hispanic men and women reported higher desired body weights than non-Hispanic white men and women, suggesting that cultural factors may contribute to ethnic differences in body weight (overweight NHW desired more substantial weight loss than overweight Hispanic). For example, Hispanic men and women had significantly higher BMis (0.9-2.9 BMI units) than non-Hispanic white pairs when matched for education, city of residence, age, gender, language spoken and time of survey (Winkleby et al., 1996). A culturally mediated preference for higher body weight may contribute to the incidence --of higher BMI in Hispanic adults ana children. Therefore, the culturally accepted view of body weight may influence the choices families make concerning physical activity participation if the behavior has an impact on loss of body weight. The present concept of overweight within the general U.S. populace may be devised around white middle class society's acceptance of an ideal standard for beauty and attractiveness. The extent to which parents' ethnicity influences their children's participation in physical 17

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activity, impact on body size, and the health consequences of being overweight and obese, is less understood. The value of and attitudes towards participation in regular physical activity may also contribute to the differences found in minority adults' and children's level of physical activity and BMI. In a study querying 40 Mexican American, 40 African American, and 40 European American women regarding how they became overweight, most of the Mexican American women discussed the strong family influence of mothers' cooking and social traditions surrounding food, but the Mexican American women's families did not discuss physical activity (Allan, 1998). Because many ethnic groups maintain their cultural norms and values from generation to generation, Hispanic women may not have learned that physical activity has important general health benefrts as well as contributing to weight control. Alternately, Hispanic women may be aware of current health promotion practices such as exercise and healthy eating but take better care of their families than themselves (Higgins & Learn, 1999). Although a large proportion of minorities are poor and have limited access and resources to exercise, Winkleby et al. (1998) reported that highly educated Mexican American women were still more likely to report no physical activity compared to non Hispanic white women of similar educational levels. It would appear that 18

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culturally diverse parents' values and attitudes concerning physical,activity may contribute to children's physical activity independent of SES. There are differences in the pattern of developmental change in body mass within social classes that may contribute to long term differences measured in children's weight. Children from upper socioeconomic families display excess adiposity in childhood and change to a more lean body type as they grow older, while children of lower socioeconomic families are thinner in their youth but gain more fat mass later in life (Bray, 1979, Cockington, 1980 and Stunkard et al, 1972). Again, these disparities within social classes, similar to the differences within ethnic groups, occur within a social and cultural context that is not fully understood. In general, Hispanic children are at higher risk for cardiovascular disease and obesity, which is not surprising considering that Hispanic American children have lower activity levels (NHANES Ill), and a higher incidence of overweight parents than their Anglo counterparts (McKenzie et al., 1992). Television viewing (sedentary habits) may relate to ethnic disparities in physical inactivity, obesity and ill health. For example, Hispanic children are less active both at school and home when compared to Anglo children (McKenzie, 1992) and African-American boys and girls had the highest rate (43%) of watching television (more than four hours per day) as compared to Latina/Hispanic boys (33.3%) and girls (28.3%). Non-19

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Hispanic white boys and gins had the lowest rate (24.3% boys and 15.6% gins) of watching television more than four hours per day (Anderson et al., 1998). The determinants of ethnic differences in time spent watching television and associated inactivity, dietary fat intake, and gender differences are unclear (Gortmaker, 1996). One possible factor is that families in low socioeconomic neighborhoods (disproportionately inhabited by minorities) may use television as a means of providing inexpensive safe child-care, thus inadvertently decreasing physical activity and increasing the risk of obesity and associated health problems. Another explanation may be that families do not prioritize an active lifestyle because of competing demands on their time and available resources as well as having an unclear understanding of the benefits of being physically active. Finally, family life is another important aspect of the Hispanic culture that may positively or negatively-influence--physical activity pattems.--Familism, considered to be a defining feature of Hispanic populations, refers to the concept of family as being the strongest area of life (Padilla, 1994 ). Conducting a family-focused investigation of values, attitudes and participation in physical activity is necessary especially when considering parental influence in differing ethnic groups in which there may be unrecognized differences. 20

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In summary, it is likely that socioeconomic status contributes to differences between Hispanic and NHW ethnic groups in the physical activity of children. Because of this potentially confounding influence, my study includes high and low socioeconomic status Hispanic and Non Hispanic white (NHW) families. Intervention. Programs designed to increase children's physical activity levels and prevent childhood obesity should be aimed, in part, at promoting the development of healthy exercise patterns as early as possible in childhood. Identifying factors that influence children's physical activity may provide data that can be used to design interventions aimed at assisting parents and other important adults in encouraging children to develop a long-term commitment to physical activity. When families are included in programs designed to prevent and treat inactivity and obesity, children lose more weight and maintain lower ---we1ghtovera longer 1994).lrfone study, treating childhood obesity involved randomization of families into groups that chose increased activity, groups that decreased sedentary behavior, or a combined group to test the influence of reinforcing children to be more active or less sedentary (Epstein et al., 1995). After one year of treatment, the group that was reinforced for decreasing sedentary behavior had greater decrease in percentage overweight than the combined and the 21

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exercise groups (-18.7 vs. -10.3 and -8.7), lost significantly more body fat than the other groups (-4.7% vs. -1.3%), improved their liking for high intensity activities, and reported lower caloric intake (Epstein et al., 1995). The intensity of exercise and/or extent of dietary intervention needed to effectively treat childhood obesity are still unknown. Physical activity interventions promoting physical activity in healthy families have shown very limited success. Nader et al (1989) developed an educational program to improve physical activity and nutrition in healthy Mexican American and European American families with children in the 51 h or 6th grades. No significant changes were found in either the parents or children's physical activity levels after a 2-year period. Changes in diet, blood pressure, and lipids were found, but only in the adults (Nader et al., 1989). In another study, Baranowski et al (1990) developed a 14-week program focusing on increasing physical activity and promoting dietary --changes in African American-families (5th-7th grades). Again, there were no significant differences between the intervention group and the control group. Both of the aforementioned studies had low compliance (40%, Nader study, and 20% Baranowski study) and therefore, the results should not be considered definitive. These studies bring to light the difficulties in promoting family based physical activity interventions that require time and 22

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commitment from families and suggest that other creative approaches should be sought. The increasing prevalence of cardiovascular disease and diabetes among younger Hispanic American adults and children is alarming. This trend lends urgency to the idea that preventing obesity and sedentary lifestyle, beginning in childhood, is one way to slow down or even reverse the trend towards increasing ill health at an earlier age in this population (Rauh et al. 1992). In summary, the generalized health benefits of exercise warrants establishing generalized public health recommendations to increase physical activity nationwide. In this study, psychological, social, environmental and behavioral variables that are associated with children's physical activity were investigated to further understand what may predict physical activity levels in non-Hispanic white and Hispanic youth. Specifically, the variables: (a) parent's physical activity; (b) parent's prioritization and value of physical activity; (c) parent's perception of activity and recreation within the family; and (d) children's perceived athletic competence were included and expected to positively correlate with children's physical activity. Interventions may thus be tailored to changing health behaviors and/or health beliefs, depending on parents' perceptions and beliefs concerning physical activity for themselves and their children. 23

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CHAPTER2 THEORETICAL ISSUES AND MODELS A plethora of theories have been applied to physical activity and health behaviors. The most common theories and models include: Health Belief Model, Theory of Planned Behavior, Transtheoretical Model, Ecological Models and Social Cognitive Theory. They are summarized in Table 2.1. Children's physical activity behavior is highly variable and dependent on a wide variety of factors in the children's family environment (Dishman et al., 1985, Moore et al., 1991 ,). As such, a theoretical perspective that examines multiple determinants (athletic competence, prioritization and value, family social environment, physical activity, and ethnicity) and their --------interactions are required for understanding children's choices regarding exercise behavior 24

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Table 2.1: Theories and Models Theory/Model Health Belief Model (Becker, M., 1974) Theory of Planned Behavior (Ajzen, I., 1991) Trans Theoretical Model (Prochaska, J.O., 1984) Ecological Model (Mcleroy et.al, 1988) Social Cognitive Theory (Bandura, 1986) lntrapersonal Variables Perceived susceptibility, severity benefits, barriers; cues to action; self-efficacy Behavioral intention: attitude toward the behavior, perceived behavioral control Stages of change; processes of change; decision balance; self-efficacy Social Variables Subjective norms: perception of beliefs of others and motivation to comply Some processes of change; some decision balance variables (benefits and costs of changing) Multiple levels of Interpersonal factors; influence, including institutional factors intrapersonal Multiple levels of Observational influence, including learning; reinforcement intrapersonal Source: Adpated from Sallis and Owen (1999; Table 7.1, page 112). 25 Physical Environmental Variables Some processes of change; some decision balance variables Community factors; public policy factors; health promotive environments Reinforcement

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Social Cognitive Theory Bandura's social cognitive theory states that behavior, cognition, environment and other personal factors (attitudes, values, beliefs) interact to influence behavior (Bandura, 1986). Social cognitive theory is widely applied in physical activity research because it allows for the interactions between intrapersonal, social, environmental and behavioral influences that affect one's behavior (Sallis, 1999). Therefore, social cognitive theory proposes that the aforementioned factors operate as interacting determinants of each other and provide a dynamic and interactive framework from which to study human behavior. Bandura's triadic model (Figure 2.1) refers to the relationships of the three classes of determinants for an individual's physical activity. Figure 2.1 : Bandura's Triadic Model Behavior {intensity, duration, frequency, mode) Person (cognitions, cognitive styles, body, composition, age) Source: Bandura, 1986. 26 Environment (spouse support, facilities access, stimulus control)

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For example, a child's degree of television viewing, defined as behavior, may be associated with his or her age, body composition, and cognition, defined as person. Stimulus control, parent support, and access to facilities are associated with environment. These interacting determinants help to explain the behavior outcome, television viewing, by examining the interaction between intrapersonal, social, and environmental influences. The research reported here has been informed primarily by social cognitive theory (SCT). Taylor et al (1994) modified Bandura's model (Figure 2.1) to include two or more persons with reciprocal interactions among the home environment, parent behavior and cognition, and child behavior and cognition. My application of social cognitive theory towards the conceptual model diagrammed in Figure 2.2 is intended to help explain and understand the determinants of children's physical activity (Sallis et al., 1992). 27

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Figure 2.2: Social Cognitive Model of Parental Influence *Environment (Family Environment Scale) + *Parent behavior (PA by accelerometer) + behavior (PA by accelerometer) + *Parent Cognition (prioritization and value of PA ) *(proposed study measures) (Adapted from Taylor, Baranowski, Sallis, 1994) *Child Cognition (perceived athletic competence) The model above shows the independent and dependent variables and the means by which they are measured in this research project. The model suggests that behavior, cognition, competencies, attitudes, preferences and environmental influences interact as determinants of each other as well as the outcome variable, children's physical activity (Dishman, 1994). For example, parents may affect a child's behavior by changing the environment in a direct or indirect manner. Parent cognition (prioritization and value) may affect a child's behavior when mediated by parent behavior (participation in physical activity). A child's cognition (perceived athletic 28

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competence) may influence his or her physical activity behavior when mediated by parents' physical activity behavior and parents' cognition. For example, parents may prioritize, value, and participate in physical activity in their day-to-day lives which in tum affects children's participation in physical activity and their sense of athletic competence. Thus, parent behavior, cognition, and perceived family participation in physical activity interact as determinants of each other and influence children's behavior. The specific predictor variables, parent valuation, parent prioritization, perceived family activity/recreation, parent physical activity and children's athletic competency were selected because of their contribution to psychological, social, and physical environment factors that have been shown to be closely related to physical activity (Lindquist et al., 1999, Sallis et al., 1997) The current literature supports that self-efficacy in physical activity, enjoyment, parental influences, attitudes, or beliefs related to physical activity, and access to sport equipment and programs are significantly correlated with physical activity (Reynolds et al., 1990, Stuckey-Ropp & DiLorenzo, 1993, Moore et al., 1991, Trost et al., 1997). The strength of these associations range between 5-25% of the variance in children's physical activity (Trost et al., 1997). The studies above examined children of different ages, hence the disparate correlations may be due to the known age-associated variation in physical activity as children progress through 29

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childhood and adolescence (Rowland, 1991 ). This study will use known correlates of physical activity (parent behavior and beliefs, self-efficacy) and adopt new variables (parent prioritization and valuation), guided by social cognitive theory, to further expand and explore the determinants of children's physical activity (Sallis and Owen, 1999). The rationale for evaluating prioritization is obvious. If parents set aside time for themselves and their children to engage in physical activity, they are prioritizing physical activity. If parents do not prioritize or value physical activity, then perhaps intervention and social marketing strategies should be altered to support prioritization of physical activity for parents and their children. The family oriented research, informed by SCT, examines how parents of different ethnic groups influence children's physical activity behavior through role modeling (parents' physical activity levels-behavior), parents' perceived social environment (environmental), children's self efficacy, and parents' prioritization and value (cognition). Understanding and identifying family determinants that affect and positively contribute to children's levels of physical activity are critical to the process of improving child health through prevention of sedentary lifestyle and childhood obesity. The independent variables investigated in relation to variation in childhood physical activity are described in detail below. 30

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1. Role modeling, or observational learning, is one of the major concepts in social cognitive theory applicable in this research project. Observational learning refers to "behavioral acquisition that occurs by watching the actions and outcomes of others' behavior" (Baranowski, et al., 1997). For example, parents who set aside time for regular exercise demonstrate to their children that exercise is prioritized as well as important in their day to day activity. As a result, their children are more physically active than the children of parents who do not engage in regular exercise (Moore et al., 1991 ). When the child observes parents engaging in a behavior (e.g. physical activity), he or she also observes the rewards, successes, and punishments related to the behavior. The child thus becomes more likely to internalize those behaviors that are accepted and rewarded rather than punished into their own behavioral repertoire. This process includes not only participation and immediate reinforcement, but involves observing parent behaviors in which learning (through observation) occurs (Bandura, 1986). This research reported herein explored the importance of parents functioning as role models for their children's physical activity behavior and will expand the model to include psychosocial aspects (prioritization, valuation, perceived athletic competence and recreational environment) of parental influence towards children's physical activity. 31

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Figure 2.3 depicts where role modeling/observation learning (italicized) fits into the theoretical model. Figure 2.3: Role Modeling/Observation Learning *Environment (Family Environment Scale) + *Parent behavior (PA by accelerometer) + __ *Child behavior (PA by accelerometer) + *Parent Cognition (prioritization and value of PA ) *Child Cognition (perceived athletic competence) 2. Environments and situations within social cognitive theory refer to the physical and social environments and the individual's and/or group's perception of these environments. In social cognitive theory, environment and situations refer to different representations of the environment. The term "environment" refers to an "objective notion of all the factors that can affect a person's behavior but are physically external to that person" (Baranowski, et al., 1997). Social environment may include family, friends, or peers, whereas physical environment refers to facilities, weather, or neighborhood. The term usituation" pertains to "the cognitive or mental 32

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representation of the environment that may affect a person's behavior" (Baranowski et al., 1997}. This study explores how parents perceive their family social activity/recreation environment (situation} and how these perceptions promote or inhibit children's physical activity. Physical environment may affect behavior by visible and clear examples such as exercise equipment in the home or membership in a health club. Less obvious social and situational environments may include cues provided by parents concerning engaging in outdoor activities, viewing a child's play or practice, discussing physical activity with the child, or establishing rules and environmental conditions that encourage the child to be active instead of sedentary (such as limiting TV or structuring leisure time with organized sports}. Therefore, the physical environment as well as the social and situational representation (parents' perception) of the environment may positively or negatively affect behavior and thus modulate how family --members behave et al., -1997}:Figure 2.4 depicts where social and situational environment (italicized) fits into the theoretical model. 33

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I i i I i I J ' i : i I i l I I I I i I I I l I i I l l I I I i Figure 2.4: Environment/Situation *Environment (Family Environment Scale) + *Parent behavior (PA by accelerometer)+ *Child behavior (PA by accelerometer) + *Parent Cognition (prioritization and value of PA) *Child Cognition (perceived athletic competence) 3. Self-efficacy is defined as an individual's sense of competence and confidence in executing a particular behavior and in overcoming barriers to performing a particular behavior (Bandura. 1986). Self-efficacy has shown to be a strong primary predictor of intention to engage in physical activity in adolescent girts and boys (Reynolds et al., 1990). In preadolescent boys and girts, self-efficacy in physical activity was the strongest predictors of daily participation in moderate and vigorous exercise (boys r = 0.27. girts r = 0.33, R < 0.05) when examining the influence of ten psychosocial and environmental determinants (Trost et al., 1999). The construct, "self-efficacyn (measured using questionnaires related to one's sense of perceived confidence) is determined by how individuals process 34

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and integrate information about their abilities and beliefs from various sources (peers, parents, siblings) and ultimately acquire perceptions and expectations regarding their own individual abilities. These perceptions, beliefs and expectations then determine, in part, the individuals' choice of goals, the degree of effort they expend to achieve those goals, and their degree of confidence in being able to overcome barriers in pursuit of goals (Maddux, 1993). Self-efficacy is an essential condition/concept within social cognitive theory because of its fundamental contribution to behavioral change. Self-efficacy influences the adoption of healthy behaviors, arrests unhealthy behaviors, and aids in maintenance of positive behavioral change when such change is threatened by barriers and obstacles (Maddux, 1993). Figure 2.5 depicts where self-efficacy (italicized) fits into the theoretical model. 35

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Figure 2.5: Self-Efficacy *Environment (Family Environment Scale) + *Parent behavior (PA by accelerometer) + + *Parent Cognition (prioritization and vafue of PA ) Parent Cognition Ill-*Child behavior (PA by accelerometer) child Cognition (perceived athletic competence) Social cognitive theory (SCT) posits that intrapersonal factors such as values and attitudes influence particular behaviors. Within the parents' belief system, particular behaviors are initiated or avoided, thus influencing children's behaviors (Dishman et al., 1985). In application of SCT, children's physical activity levels are influenced by parental cognitive processes (prioritization and value of physical activity), children's cognitive processes, (self-efficacy and perceived athletic competence), parental perceived social environmental (activity and recreation) and behavior (physical activity participation). This study will introduce new predictor variables, parental prioritization for themselves and valuation of physical activity, for the 36

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purpose of examining parents' attitudes, values and beliefs concerning physical activity. Valuation is operationalized here as a rating according to relative worth, importance and/or desirability. Individuals would be expected to engage in a behavior which they believed was of value and importance and avoid those behaviors that are perceived to increase risk of illness or injury (Strecher & Rosenstock, 1997). I hypothesize that the degree to which parents prioritize and value physical activity in their everyday lives is an important influence on children's physical activity levels. Figure 2.6 depicts where parent cognition (italicized) fits into the theoretical model and the predicted correlation between parents' values and child behavior. 37

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Figure 2.6: Parent Cognition *Environment (Family Environment Scale) *Parent behavior (PA by accelerometer) + *Child behavior (PA by accelerometer) + *Parent Cognition (prioritization and value of PA ) 38 *Child Cognition (perceived athletic competence)

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CHAPTER3 RESEARCH QUESTION AND PRELIMINARY DATA Research Question The specific research question to be addressed is: To what extent do mothers' and fathers' perceived family activity/recreation environment, parent physical activity, parent prioritization and valuation of physical activity, and child's (boys and girls) athletic competence predict child's physical activity? The proposed study will assess environmental, sociocultural, and psychological and behavioral variables in order to understand determinants that contribute to Hispanic and non-Hispanic white, and low and high socioeconomic status, children's physical activity. The constructs evaluated in this project have not previously been investigated collectively. No prior study has examined the extent to which ethnicity may influence parent prioritization and valuation of exercise for their children, and certainly no study has examined how Hispanic girls, who are reportedly the least active among all children, may be influenced by their families into a pattern of low daily physical activity levels (McKenzie, 1997). 39

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Hypotheses Children's (boys and girls) energy expenditure will be positively correlated with: Parental (mothers and fathers) prioritization of physical activity for themselves measured by Physical Activity Prioritization Survey (PAPS). Parent (mothers and fathers) ranking of the value of physical activity measured by a 7 -item lifestyle-ranking instrument. Parental (mothers and fathers) participation in physical activity objectively measured by accelerometers. Parental (mothers and fathers) perceived family social environment measured by Family Environment Scale. Children's (boys and girls) perceived athletic competence measured by Self-perception Profile for Children In essence, the hypotheses posit that when parents (mothers and fathers) prioritize and value physical activity and participate in physical activity themselves, their children (girls and boys) will perceive higher athletic competence and be more physically active. Ethnic and socioeconomic differences in children's energy expenditure will be mediated by differing parental perceptions of physical activity for themselves and their families and children's self-efficacy related to athletic competence. 40

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Preliminary Data Questionnaire Development A pilot study of parents' opinions about attitudes towards and prioritization and valuation of physical activity was conducted using questions adapted from The Healthy Families Project (Gamel & Tinsley, 1999 personal communication), survey questions from Dr. Susan Johnson's Family Systems Approach to Childhood Obesity project, and informal expert discussions. The results of this pilot study were then used to develop the PAPS (Physical Activity Prioritization Survey) which I used to measure prioritization and value ranking of physical activity. The PAPS questions were developed from an expert panel of judges in the area of physical activity and questionnaire development, tested in the field, edited and re-tested with continued expert advice and direction. Expert contribution included the following individuals who were solicited for their varying expertise: Dr. Kim Reynolds, a social psychologist who conducts research in sociocultural determinants of physical activity in children; Dr. John Brett, an anthropologist with expertise in ethnographic methodology investigating physical activity and dietary patterns in Hispanic and non-Hispanic white families; Dr. Kitty Corbett, an anthropologist with a masters degree in public health who has extensively worked with questionnaire and semi-structured interviews; Dr. Lori Crane, who is 41

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involved in the area of preventive medicine and biometrics, and was selected for her expertise in questionnaire and survey development; Dr. Stacy Zamudio, who teaches research design and methodology in the health and behavioral sciences, Dr. David Tracer, director of Health and Behavioral Sciences department at the University of Colorado at Denver, was solicited for his experience with questionnaire and semi-structured interviews; as was Dr. Susan Johnson, a nutrition scientist, researching eating behaviors in Hispanic and non-Hispanic white families in the proposed Denver schools. Topics to be included in the questionnaire were decided in an initial draft and revised per the advice of the expert panelists. The final PAPS questionnaire includes a total of nine questions. Only questions 7-9 were used to measure parental prioritization and parent value ranking. Questions 1-6 were collected as adjunct data in order to describe possible differences between the ethnic group's perceptions of frequency, duration, type and time set aside for physical activity. Physical Activity Prioritization Survey Questions 1 Can you tell me what physical activity means to you? 2. As part of your daily/weekly routine, what kinds of physical activity do you do? 42

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3. Do you think physical activity is important for you? For your children? WHY is it important for you (parent)? WHY is it important for your children 4. Compared to other adults of your same age and sex, how physically active are you? A lot more/A little more/A little less/A lot less/Average/NA 5. How many times during the past week did you engage in an activity that made your heart beat fast, made you breathe hard, and maybe caused you to sweat? How long did that activity last? 6. Do you set aside time, in your normal routine, to engage in physical activity for yourself? In other words, do you forego other tasks or activities to make time for physical activity? If parent answers yes"Can you tell me how you do that? If pareriCanswe-rs-"h-o"=-=--Can-you about why not? Now, think about your child Can you tell me if time is set aside for him/her to participate in physical activity? If parent answers yes"Can you tell me how that happens? If parent answers "no"-Can you tell me more about why that may not happen for ____ ? 43

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i I i I I. i 7. Please rank these items according to how important they are to you: (Scale 1-7 with 1 being the most important and 7 the least) ___ being financially successful ___ being healthy/not being sick ___ doing well at work ___ enjoying leisure time ___ having a good family life ___ having a good spiritual life ___ having good friendships 8. Where does being physically active frt into this list? 9. Consider your responsibilities and tasks in a typical day. Now think to yourself about those responsibilities/tasks that you consider your highest priority in a given day and think to yourself about those responsibilities/tasks that are your lowest priority. REALISTICALLY, where For (parent): Lowest priority Highest priority For (child): Lowest priority Highest priority 44

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Question #1 was originally developed to evaluate how subjects' define "physical activity". On the advice of the ethnographer, we changed the question to an open-ended format to allow participants to define physical activity from their own perspective and avoid stereotyping. The ranking questions (#7 and #8) were developed by Gamel and Tinsley (1999) in The Healthy Families Project in California and used in studies of health and nutritional values in Latino families. The parent prioritization (#9) was developed and refined utilizing the aforementioned expert panelists familiar with questionnaire/survey methods. The language of the questionnaire and visual analog scale \VAS) used in question #9 was piloted for vague or misleading questions and re-tested in two differing ethnic cohorts with minimal revisions. For example: "In a typical week, how many days do you get physical activity?" was modified to "How many times during the past week did you engage in an activity that made your heart beat fast, mace y61Toreatlie ,ancfmaybe -causfed you to sweat? Pilot Questionnaire Results Parents from two Denver schools were asked questions during parent night, track and field day, and by telephone interview. Ten Hispanic and 10 non-Hispanic white parents were initially asked questions from the first draft of the PAPS questionnaire to trial question design, order, and 45

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content. Twenty-two Hispanic parents and 19 non-Hispanic white parents were then used for the second phase of pilot testing of the questionnaire. The pilot data revealed that both Hispanic families and non-Hispanic families consider physical activity primarily as movement of the body in differing degrees of intensity. The biggest differences were that Hispanic families included day-to-day activities such as going to the store and cleaning the house (movement for a purpose) as well as sports in their conceptualization of physical activity whereas the non-Hispanic white families more often thought of physical activity as being solely related to sports activities. I ------------i 46

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CHAPTER4 RESEARCH DESIGN AND METHODS Overview Data were collected from families with children enrolled in 3rd-5th grades. The reason for examining this age range is because children become less physically active as they grow older as shown in Table 4.1 (Rowland, 1991). Table 4.1: Total Daily Energy Expenditures (kcal/kg/day) 6 Years 8 Years Boys 82 74 ... ----------------Girls 76 70 10 Years 75 58 12 Years 58 53 Source: Adapted from Rowland (1991; Figure 3.1, p.35) 14 Years 50 45 Participation in all forms of physical activity decreases considerably during adolescence for both boys and girls (Surgeon General Report, 1996). Furthermore, Hispanic-American children and those of low 47

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socioeconomic status are at greater risk for being sedentary and overweight (McKenzie, 1992). For these reasons, I selected children in 3rd -5th grades (8-1 0 years of age) in order to capture activity levels prior to the age associated decrease in activity with the intention of ultimately developing an intervention that interrupts the decline. A cross-sectional design was used to identify sociocultural, environmental, behavioral and psychological determinants of physical activity in non-Hispanic white (high and low SES) and Hispanic (high and low SES) families. The design allows for examination of the relationships between family social activity/recreation environments, parental prioritization and value of physical activity, physical activity participation, and children's athletic perceptions and the outcome variable, physical activity. The design further evaluates the extent to which these relationships differ between high and low SES Hispanic and non-Hispanic white families. Hispanic families from whom I collected data were primarily of low socioeconomic status, whereas the non-Hispanic families were of high socioeconomic status. Recognizing that this was a skewed sample, the research design was modified to include high SES Hispanic families and low SES non-Hispanic white families. The sample included 99 families recruited from four schools. A family is defined as two or more individuals who reside in the same 48

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household and who have some common emotional bond (Baranowski & Nader, 1984 ). This definition included biological parents in both single parent and two-parent families. Both mothers and fathers were included when feasible. Data collection began September 1999, two to three weeks after school had resumed from summer break. During this initial phase families were recruited by mail, phone, and school bulletin messages sent home with the children. Consent forms were completed for parents, and assent forms for children, who agreed to participate during the home visit prior to data collection. The consent forms and protocols were approved by the University of Colorado at Denver Institutional Review Board. Subjects Participants were recruited from the target populations, Colorado Springs School (CSS) in Colorado Springs, Lincoln Elementary School (LES) in Colorado Springs, Corpus Christi Catholic School (CCC) in Colorado Springs and Columbian Elementary School (CES) in Denver. Colorado Springs School, a private institution, is comprised of primarily high SES non-Hispanic white families. Lincoln Elementary School serves primarily low income non-Hispanic white families. Columbian Elementary School is serves primarily low SES Hispanic families. Corpus Christi Catholic School is a private institution with sufficient numbers of high SES 49

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I i I I l I I I I I I i l I I I I I I I I i i i I Hispanic families for recruitment. The staff at these schools provided current enrollment lists of parents and phone numbers so that we could identify those parents and children who were potential participants. Parents were solicited by mail in the form of a letter describing the purpose of the study and information concerning payment for participation. Follow-up phone contact was used to recruit families for participation. Parents and children from CSS, CCC, LES and CES 3rtt through 51 h grades were asked to provide consent for participation, but were counseled that the child or parent could terminate their involvement in the study at any time. All participants were assured of confidentiality. Excluded from the study were students and the parents of children who had any physical disabilities that may have prohibited them from being physically active. Families that were unable to read, write and/or speak English were excluded due to limited financial resources for the hiring of an interpreter. Lastly, bath parents who did noridentify themselves as "Hispanic" or "Caucasian" were excluded from the analyses. Following the family's agreement to participate in the proposed study, we set up a convenient time and place to meet in order to obtain consent and assent. Both parents (if possible) and child interviews were completed prior to placement of the activity monitors. 50

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Subject Payment Parents were paid $20.00 each for participating in: 1) a semi structured interview asking their opinions and values concerning physical activity for themselves and their children; and 2) wearing an accelerometer for 7 days. Children received a choice of 5 prizes or $20.00 after wearing an accelerometer for 7 days. Prizes were valued at approximately $20.00 and included sports-related items such as soccer balls, foursquare balls, and baseball bats. Measurements Parent and child physical activity levels were objectively measured using activity monitors. Child cognition was measured by children's perceived athletic competence using a sub-scale of the Self-perception Profile for Children (Harter, 1985). The Self-perception Profile for Children measures self-perception for the purpose of assessing children's perceptions within a specific domain. Parent cognition was assessed with the Physical Activity Prioritization Survey (PAPS) in an interviewer administered semi-structured interview focusing on prioritization and value ranking of physical activity. The family environment was assessed using the recreation/activity factor of the Family Environment Scale (Moos & 51

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Moos, 1994) which measures parents' perception and rating of their current family activity/recreation environment. Physical Activity Levels. To avoid the problems associated with self reported physical activity I used physical activity monitors, (Accelerometers, model 7164, Computer Science Applications (CSA), Shalimar, FL.) to objectively measure physical activity in children and parents (Montoye et al, 1996 and Sallis, 1991 ). The CSA activity monitor utilizes a vertical plane accelerometer to quantify movement. The accelerometer is firmly secured to a belt and is worn positioned over the right hip. The accelerometer measures acceleration due to the displacement of the center of mass of the body but filters out high frequency movements such as vibrations. The accelerometer signal is digitized, converted to numerical counts and summed over one-minute intervals. Thus, the more steps or the more intense the movement, the greater number of counts will be accumulated in --a-one-minute period:For example, -each-step creates an acceleration of the center of mass (COM) upward and downward. The magnitude of this acceleration depends upon the speed at which the individual is moving. Running, for example, will create greater accelerations of the COM than walking. The CSA data are stored in memory, and downloaded to a personal computer for subsequent retrieval and analysis. This study determined physical activity levels based on the average number of 52

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accelerometer counts per day. Janz (1994) maintains that CSA activity counts correlate (r-.50 -. 7 4) with heart rate elevation in activities of different physical intensity, supporting the notion that CSA data corresponds to exercise intensity (Janz, 1994 ). The physical activity monitoring was done over seven consecutive days and considered representative of a typical week and habitual activity patterns. The primary outcome was the mean of the 6 days of activity. Monitoring was done during "normal" weeks (i.e. not during school breaks or holiday weeks). While the assumption of normalcy in any given week could be questioned, most children and their parents have fairly stable schedules from week to week during the school year. Two levels of analyses were employed to assess the validity of the accelerometer data. First, printouts of the activity monitor data were obtained for each subject across the seven days of monitoring. In this --counts-are plotted across the seven days (144 hours) of monitoring. If the subject wore the monitor for the full seven days, we were able to obtain a characteristic profiles, i.e., seven distinct clusters of elevated counts separated by spaces. The clusters represent the activity counts recorded during the day, and the spaces represent the sleeping periods when the monitor was not worn. The 53

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I I I I. I I I I I i I clusters corresponded to daytime values, and this was verified by having the subject record what time the monitor was put on and taken off each day. Second, a mean daily activity value was calculated in adults and children. For any given day, if the total counts were more than two standard deviations above the mean, I examined the daily profile and then followed up with the subject in order to ascertain whether the counts were truly due to activity or were an artifact. Data on days that were determined to be invalid were excluded from the calculation of weekly means. Although these procedures are somewhat subjective, I am not aware of any published study that has described more objective criteria for quality control of activity monitor data. To avoid the novelty effect associated with monitors worn by children (e.g. children may shake the monitors or take them off to play with them or show them to their friends etc.) the first day of measurement was considered a learning period and was not included in the analyses. The first day of monitoring was not always the same day of the week for each child and parent(s). Because of logistical constraints, children and parent(s) often received the monitors on different days of the week. Records were maintained of the precise day and time that the monitor was placed on the children and their parents. 54

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Careful instructions were provided to both the children and their parents on how to property wear and secure the monitor. A chart was provided that illustrated this as well. Carefully explaining the procedures enhanced compliance, but as with any other study using activity monitors in field settings, I could not independently guarantee how compliant subjects were in vigilant wearing of the monitors (other than the analyses listed above). Children's Perceived Athletic Competence. Self-efficacy is a strong mediator of behavior change and an important predictor of children's physical activity (Bandura, 1982). I considered that my other independent variables (prioritization, valuation, parental physical activity and family activity/recreation environment) might relate to self-efficacy and might therefore enhance our understanding of what variables contribute to self efficacy. The Self-Perception Profile for Children (Harter, 1985) was used to measure children's self-perceptions of six separate domains. They include: scholastic competence, social acceptance, physical appearance, behavior conduct, global self-worth and athletic competence (Harter, 1985). Examination of the differing profiles, measured by six separate subscales, reflects an accurate depiction of children's self-concept and self adequacy. While all 6 subscales were collected, this study focused on perceived athletic competency. The subscale, athletic competence, 55

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contains items that probe children's perception of sport and outdoor games and their perceived proficiency and adequacy in athletic endeavors. The arrangement of the question strives to elicit self-perceptions rather than socially acceptable answers. Each item is scored 1 through 4 with 1 indicating low perceived competency and 4 indicating the highest perceived competency. Three items are counter-balanced such that 4 indicates low perceived competence and 1 indicates high competence. Athletic competence is moderately (R=0.50 and above) correlated in grades 3rd and 4th with physical appearance, self-worth, social acceptance and scholastic competence (Harter, 1985). Internal consistency was assessed using Chronbach's Alpha. Internal consistency reliabilities for each subscale using four different samples ranged from 71 to .86. Behavioral conduct was the lowest at .71, and athletic competence was the highest at .86 (Harter, 1985). ---parental Prioritization and Ranking of Physical Activity. Parental prioritization of physical activity was assessed using a semi-structured questionnaire (PAPS) that had been pilot-tested during summer of 1999. This questionnaire elicited parental opinions about their values, attitudes, and prioritization of physical activity for themselves as well as their children. It also asked parents to rank physical activity with respect to 6 other personal life values (Gamel and Tinsley, 1999, Rokeach, 1973). No study 56

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to date has included these specific variables in analyses to predict children's physical activity levels. These new data (prioritization and value ranking), associated with data derived from the social cognitive theoretical perspective {parent cognition) will contribute to my long-term goal of devising ways to encourage families and children to develop life-long healthy exercise habits. Scoring of prioritization data used a continuous 1 Ocm analog scale where parents indicated the extent to which they prioritize physical activity on a daily basis for themselves and their children by marking the scale "lowest priority" (0) to "highest priority" (1 0). The purpose of these data was to measure parents' ranking of the importance of physical activity in relation to other life values and how the degree of importance and value is then associated with their measure of prioritization of physical activity. Finally, these data were examined to compare how prioritization and value ranking --may-o-ereflected in the total physical activity measured in both parents and children. Family Environment Scale. The Family Environment Scale (FES) was developed to measure the social-environmental characteristics of families (Moos & Moos, 1994 ). The FES specifically assesses 1 0 areas of family life. All 10 sub-scales were collected but only one subscale was incorporated into the data analyses. The activity-recreational subscale, 57

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(perceived degree of participation in social and recreational activities within families), was obtained by asking parents questions about their family's participation, interest, and importance of activity and recreation (Moos & Moos, p.1 ). This subscale was chosen because parent's perception of their family's social environment related to activity and recreation, within social cognitive theory, may relate to children's actual participation in physical activity. According to the social cognitive theoretical model, this measurement is taken to represent "environment". The family's perception of activity/recreation provides additional data related to parental attitudes towards physical activity and extends those attitudes to include how parents perceive physical activity behavior within the family. In addition to parent modeling physical activity for their children, this broader family variable may affect habits related to children's physical activity and may support children's physical activity in a more indirect way. ---rhe--FES-hstroment with good test-retest reliability (.68-.86) and construct validity. Activity-recreation environment norms and standard deviations were obtained for minority families (Latino and African American) with mean scores of 5.01 1.96 and non minority families with mean scores of 5.33 1.96 (Moos & Moos, 1994 ). When scoring the FES, a template is used that divides the difference subscales. 58

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The raw score for each subscale in our sample was converted to standard scores for analyses (Table 4.2). Table 4.2: Summary of Parent and Child Measurements Parent or Child Domain Proposed Measures Measurement Outcome Child Behavior Children's physical activity Child measurement Predictors Parent Behavior Parent physical activity Parent measurement Parent Cognition Parent prioritization Parent measurement Parent value ranking Parent measurement Environment Family social environment Parent measurement Child Cognition Perceived athletic Child measurement competence Ethnicity Hispanic or non-Hispanic Parent measurement white 59

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CHAPTER 5 DATA ANALYSES AND RESULTS Data Analyses The study hypothesis is that parents (mothers and fathers) who hold greater value and priority for physical activity, who positively perceive their family's social environment related to activity/recreation, who participate in physical activity themselves, and children with greater perceived athletic competence will positively correlate with children's levels of physical activity. Ethnic and socioeconomic differences in children's energy expenditure are postulated to be influenced by differing parental valuation, prioritization of physical activity for themselves, perceived family environment of physical activity, parental participation in physical activity, ------------------and, in tum, differences in children's perceived athletic competence. The research question stemming from these hypotheses is: To what extent do mothers' and fathers' perceived family activity/recreation environment, parent physical activity, parent prioritization and valuation of physical activity, and child's (boys and girls) perceived athletic competence predict a child's physical activity? 60

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The data analyses were conducted sequentially, beginning with descriptive statistics of all outcome and predictor variables by SES and ethnicity, followed by a series of analyses of variance to assess SES and ethnic differences in mothers', fathers', and children's variables. Two-factor analyses of variance were used to evaluate whether there was an interaction between SES and ethnicity for each predictor variable using the outcome variable, children's physical activity. Next, bivariate correlation analyses were explored, which in tum, informed the development of multiple regression analyses to examine the relative contributions and strength of the predictor variables on the outcome variable. Next, development and testing of a newly structured model was created to assess possible alternative paths of influence on children's physical activity. Finally, responses to questions from the PAPS that were qualitative in nature were summarized using percentages. The independent variables used in these analyses were ethnicity (Hispanic vs. non-Hispanic white), parental sex (mothers vs. fathers), child sex (boys vs. girls) and socioeconomic status (high vs. low). The dependent (outcome) variable is children's physical activity. The following variables were investigated as predictor variables that might have influenced the outcome variable; (1) parental prioritization of physical activity (2) parental valuation of physical activity (3) parents' perceived 61

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family social activity/recreation environment (4) parental participation in physical activity and (5) children's perceived athletic competence. We extended previous reports by examining parental prioritization and valuation of physical activity which might reasonably be expected to influence the outcome variable. Statistical power analyses were based on the assumption that the final model would be a multiple regression containing 5-7 independent variables. The alpha was set at .05, with a power of .80. Under these assumptions, a sample of 99 children and 99 parents is sufficient to detect a cumulative R2 value of 20% (e.g. 20% of the variance in the dependent outcome measure by 7 variables) (Hair et al., 1998). Using the sample size employed in this study (99 children and 99 parents), a regression model that employs seven independent variables to predict children's physical activity with an alpha .05 will detect R2 values of 17% and above (Hair et al., 1998). For complex questions employing both psychological and social parameters, Cohen (1988) defines an R2> 15% as being of moderate predictive power and significance value. Significance for all analyses was set at p <.05. All statistical analyses were performed using SPSS version 10 (SPSS, Chicago, IL, 1999). Descriptive statistics for each predictor variable and the outcome variable (children's physical activity) included means, ranges, standard 62

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deviations, skewness, kurtosis, test for normality and boxplots/histograms with normal curve to identify whether variables were normally distributed and if outliers were present. Parent and child data were analyzed separately by SES and ethnicity to investigate possible differences in the effects of the independent variables. lntrascale reliability (Family Environment Scale and the Harter Scale) was assessed using Cronbach's alpha; the coefficient was set at .60 to 70 (Hair et al., 1998). The perceived athletic competence scale demonstrated adequate internal consistency (.76) as did The Family Environment Scale for perceived family activity/recreation (.72 mothers and .60 fathers) (Figure 5.1 ). Figure 5.1: Model Ethnicity Socioeconomic status Parent Valuation of Physical Activity Family Environment Scale Children's Physical Activity Parent Physical Activity Parent Prioritization of Physical Activity Children's Perceived Athletic Competency *Parent variables are analyzed separately for mothers and fathers *Children's variables are analyzed separately for boys and girls 63

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Results To examine the differing effects of ethnicity and SES upon the independent variables and the dependent variable the descriptive data are presented by ethnicity (Hispanic and non-Hispanic white), followed by SES (high and low). Furthermore, mothers and fathers were examined separately and not aggregated into families because a greater number of mothers provided information, a low number of fathers agreed to participate, and previous research has identified that mother's and father's impact upon child physical activity differs (Sallis, 1988). Descriptive Data and Ethnicity T tests were used to answer the questions: (1) Do Hispanic and nonHispanic white NHW mothers and fathers differ significantly in BMI, parental prioritization, parental valuation, parents' perceived family social -activity/recreation, and -parentarparticipation in physical activity? (2) Do Hispanic and NHW boys and girls differ significantly in perceived athletic competency, BMI and total physical activity? All descriptive data was analyzed for the purpose of examining patterns and relationships between and among variables in both Hispanic and NHW and low and high SES families. 64

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Parent and Child Data by Sex and Ethnicity Table 5.1 shows overall differences in mothers' and fathers' variables by ethnicity Differences in Mothers' Variables by Ethnicity 1. Education: NHW mothers have completed more years of education than Hispanic mothers. 2. BMI: Hispanic mothers had higher BMis than NHW mothers' and on average were obese. 3. Perceived family activity and recreation: NHW mothers' perception of their family's activity/recreation environment was higher than that of Hispanic mothers. Note: In this sample, Hispanic mothers' mean value was slightly higher than normative mean value (sample M = 5.7 2.2, norm M = 5.01 2.3). NHW mothers' mean value was slightly higher than ---normative mean value-(sample M = 6.81.9, norm M = 6.31 1.9) 4. Value ranking of physical activity: There were no differences found between NHW and Hispanic mothers' value ranking of physical activity. 5. Prioritization of physical activity: NHW mothers' prioritization of physical activity for themselves was greater than the Hispanic mothers. 65

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---------------------------------------Table 5.1: Mothers and Fathers Variables for Ethnicity Mother Father (n = 95) (n=67) Hispanic Non-Hispanic Hispanic Non-Hispanic (n=45) (n=50) (n=28) (n=39) Variable M so M so t M so M so t Education 12.3 2.3 15.7 2.8 6.3* 12.1 3.8 17.9 4.1 5.8* BMI 34.4 8.7 24.9 6.9 -5.7* 28.2 4.0 25.0 2.7 -3.8* FES 5.7 2.2 6.8 1.9 2.4* 5.8 1.9 6.2 1.7 .1 Value 3.8 1.7 3.5 1.6 -.6 3.1 1.6 3.3 1.6 .6 0) Ranking 0) Prioritization 3.9 2.3 5.0 2.9 1.9* 4.7 2.5 5.0 2.8 .4 Total Parent PA 260992.9 88178.3 310046.6 110042.7 *2.4 320933.9152270.1 322888.2114109.4 .1 *Q < .05

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6. Total physical activity: Non-Hispanic white mothers' total physical activity counts were higher than those of Hispanic mothers'. Differences in Fathers' Variables by Ethnicity 1. Education: The NHW fathers had more years of education than Hispanic fathers. 2. BMI: Hispanic fathers' BMI were higher than NHW fathers and on average were overweight. 3. Perceived family activity and recreation: There were no difference between NHW and Hispanic fathers' perceptions of their perceived family activity/recreation environment. Note: In this sample, Hispanic fathers' mean value was slightly higher than normative mean value (sample M = 5.8 1.9, norm M = 5.01 2.33). NHW fathers' mean value was slightly lower than normative mean value (sample M = 6.2 1.7, --n-orm-M = 6.31 1 :9): 4. Value ranking of physical activity: There were no differences between NHW and Hispanic fathers. 5. Prioritization of physical activity: There were no differences between NHW and Hispanic fathers' prioritization of physical activity. 6. Total physical activity: There were no differences between NHW and Hispanic fathers' total physical activity counts. 67

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Table 5.2 shows the children's variables for ethnicity. Children's Results for Ethnicity 1. BMI: Hispanic children had greater BMis than NHW children. This was true for both Hispanic boys and girls compared with their NHW counterparts. In this sample, there were no differences between girls' and boys' BMis within ethnicity. Note: There are developmental changes in BMI with age. In this sample of 8-10 year olds, there were no significant correlation between age of child and BMI. Specifically, when examining age related BMis in this sample, mean for age, sex, and ethnicity associated BMI resulted in no boys or girls falling into the 85 percentile or above. Therefore, BMI was not age-adjusted because there was no age associated variation in this sample. 2. Perceived athletic competency: There were no differences in athletic competency between NHW and Hispanic children nor between boys and girls within each ethnicity. Note: When comparing age-related athletic competence norms to this sample, NHW and Hispanic mean scores were the same or higher for both girls (NHW M = 3.1, Hispanic M = 3.0 vs. norm M = 2. 7) and boys (NHW M = 3.3 and Hispanic M = 3.1 vs. norm M = 3.1 ). It is important to note that these normative values are drawn from primarily 68

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0> <0 Table 5.2: Children's Variables for Ethnicity Total (n=99) Hispanic Non-Hispanic (n=48) (n=51) Variable M SO M SO t Girls (n = 45) Hispanic Non-Hispanic (n=23) (n=22) M SO M SO t Boys (n=54) Hispanic Non-Hispanic (n=25) (n=29) M SO M SO t BMI 18.6 4.4 16.9 2.4 -2.6* 17.9 3.7 16.0 2.4 -2.0* 19.3 4.9 17.1 2.4 -1.9* Athletic 3.0 .7 3.2 .6 1.3 3.0 .7 3.1 .8 .6 3.1 .7 3.3 .5 1.3 competence Total PA 495988.0 (157132.2) 513300.7 (153271.1) t =.55 Girls 458884.2 (163241.1) 494665.2 (141997.5) t = .78 Boys 530123.4 (146260.7) 527437.9 (162319.8) t = -.06 Q. < .05

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lower middle class to upper middle class Caucasian neighborhoods (Harter, 1985). 3. Total physical activity: There were no differences in total physical activity counts between Hispanic and NHW children nor between boys and girls within each ethnicity. In summary, NHW mothers, when compared with Hispanic mothers, had more years of education, perceived a more positive family social environment relative to activity/recreation, had higher prioritization of physical activity for themselves, had higher physical activity counts and lower BMis. NHW and Hispanic mothers were equivalent in their value ranking of physical activity. NHW fathers differed from Hispanic fathers only in having greater education and lower BMI. The children did not differ in total physical activity and perceived athletic competency by either ethnicity or sex. Despite these similarities in physical activity, Hispanic children had significantly higher BMls than NHW children, with the relationship holding within each sex. These data suggest that the main differences, with respect to physical activity between Hispanic and NHW families, is in the mothers' predictor variables. Specifically, NHW mothers' have greater prioritization, higher perceived family activity/recreation environment and total physical activity than Hispanic mothers. 70

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Socioeconomic Status In this study, educational level served as a proxy for determining SES. Years of education were significantly correlated with the Hollingshead social class index score (1-5) lr =-.85, Q. < .01) and thus, there appeared to be justification for using education as a proxy for SES. The Hollingshead index is a two factor index (education and occupation) of social position that is calculated by multiplying a scale score for occupation and education by a factor weight. The index of social position score is then classified into 5 score groups with social class 1 being the highest level of social class and 5 being the lowest (Hollingshead, 1 965). Hence, by definition, lower SES parents were less educated than high SES parents. The majority (78%) of mothers and fathers from lower SES families finished high school but had no college whereas the majority (84%) of mothers and fathers from high SES families had completed 4 or more years of college. T tests were used to answer the questions: (1) Do low and high SES mothers and fathers differ significantly in BMI, parental prioritization, parental valuation, parents' perceived family social activity/recreation, and parental participation in physical activity, and (2) Do low and high SES boys and girls differ significantly in perceived athletic competency, BMI and total physical activity? 71

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Parent and Child Data by Sex and Socioeconomic Status Overall differences and mothers' and fathers' variables by socioeconomic status (Table 5.3). Differences in Mothers' Variables by Socioeconomic Status 1. BMI: Low SES mothers had higher BMis compared to high SES mothers. 2. Perceived family activity/recreation environment: High SES mothers' perception of their family's activity/recreation environment was greater than that of low SES mothers. 3. Value ranking of physical activity: High SES mothers' value ranking of physical activity is higher than that of low SES mothers. 4. Prioritization of physical activity: High SES mothers' -prfontizatfon-of pnysfcalactlvity-forthem1:relves is higher than low SES mothers. 5. Total physical activity: High SES mothers' total physical activity was higher than low SES mothers. 72

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Table 5.3: Mothers and Fathrrs Variables for SES I Mother Father (n= (n=67) High SES 1 LowSES High SES LowSES (n=47) (n=48) (n=42) (n=25) Variable M SD M SD t M SD M SD t I I Education 16.4 2.3 1.7 2.3 18.4 3.4 10.6 2.9 BMI 23.3 5.2 8.0 -8.4* 25.7 3.5 27.3 3.7 -1.7 """ FES 7.2 1.5 15.3 2.2 4.7* 6.6 1.5 5.2 2.1 3.3* w Value 3.2 1.3 )4.2 1.8 -3.0* 3.3 1.6 3.0 1.6 .6 Ranking Prioritization i 5.0 2.8 i 3.9 2.4 2.0* 4.7 2.8 5.2 2.6 -.7 Total Parent PA 937,7.5 '352o.9 3.211 3"787.3 'D9787.D 339382.8 '8DD89.5 -.8 Q < .05

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Differences in Fathers' Variables by Socioeconomic Status 1. BMI: There were no differences in BMI between low SES and high SES fathers. 2. Perceived family activity/recreation environment: High SES fathers' perception of their family's activity/recreation environment was higher than low SES fathers'. 3. Value ranking: There was no difference between high SES and low SES fathers' value ranking of physical activity. 4. Prioritization of physical activity: There was no difference between high SES and low SES fathers' prioritization of physical activity. 5. Physical activity: There was no difference between high SES and low SES fathers' total physical activity counts. Differences in Children's Variables by Socioeconomic Status 1. BMI: Low SES children have significantly higher BMis than high SES children and this relationship held within each sex. 2. Perceived athletic competency: Low SES children have lower perceived athletic competency than high SES children. High and low SES girls' had similar athletic competency scores, but high SES boys' scores exceeded those of low SES boys. 74

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3. Total physical activity: There were no differences between low SES children and high SES children in total physical activity counts nor between high SE:S vs. low SES girls or high SES vs. low SES boys. In sumrnary, the descriptive data examining socioeconomic status (SES) and sex differences between mothers' and fathers' predictor variables indicate (by study design) that low SES mothers and fathers have lower educational levels. High SES mothers' value ranking of physical activity, prioritization of physical activity, and rating of their perceived family activity/recreation was greater than that of low SES mothers. High SES mothers engaged in more physical activity and had lower BMis than low SES mothers. High vs. low SES fathers differed on only one variable: their perception of their family's activity/recreation environment is more positive than that of low SES fathers Children's descriptive data suggests no differences by SES or sex in total physical activity. However, BMis were greater in all low SES children compared to high SES children, and the relationship held true for both girls and boys. Perceived athletic competency was higher in the high SES children versus the low SES children overall, but within each sex the differences reached significance only for boys (Table 5.4). 75

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"""' (J) Table 5.4: Children's Variables for SES Total (n=99) High SES Low SES (n=48) (n=51) Variable M SD M SD t Girls (n = 45) High SES Low SES (n=23) (n=22) M SD M SD t Boys (n=54) High SES Low SES (n=25) (n=29) M SD M SD t BMI 16.3 2.3 18.8 4.2 -3.5* 15.8 2.1 18.2 3.8 -2.5* 16.8 2.4 19.3 4.6 -2.5* Athletic 3.4 .6 3.0 7 3.1* 3.2 7 2.8 7 1. 7 3.4 .5 3.0 7 3.0* Competence Total PA 320468.6 (101541.4) 93717.5 (13526.9) t = .6 Girls 502084.6 (146555.6) 449501.1 (157427.9) t = 1.2 Boys 525628.3 (151988.2) 531313.0 (157706.9) t =-.1 *Q < .05

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These data suggest that the primary differences between high and low SES families reside in the mothers' predictor variables. High SES mothers tend to prioritize, value rank, perceive their family's activity and recreational environment, and participate in physical activity to a greater degree than low SES mothers. Although children do not differ in their levels of physical activity by SES, the low SES children have greater BMis and lower perceived athletic competency. Surprisingly, the girls' sense of athletic competency does not differ by SES. Interaction Between Socioeconomic Status and Ethnicitv Two factor analyses of variance was employed to assess whether there was an interaction between ethnicity and SES with respect to predictor variables or the outcome, children's total physical activity. The results showed significant interaction only in mothers' prioritization of physical activity, F (1, 94) = 5.74, Q < .02 and mothers' total physical activity, F (1, 94) = 13.9, Q = .00. High SES Hispanic mothers and low SES NHW mothers had lower scores for prioritization of physical activity and lower total physical activity. Otherwise, there was no interaction between SES and ethnicity in any of the predictor or outcome variables for all parents, fathers, all children, boys or girls. 77

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The inequity in samples sizes impacted data analysis in that the low SES group included a larger percentage of Hispanic subjects vs. NHW subjects (76% vs. 23%, respectively) and the high SES group included a larger percentage of NHW vs. Hispanic subjects (81% vs. 18%, respectively). Data were collected from 99 families and included n = 39 low SES Hispanic families, n = 9 high SES Hispanic families, n = 39 high SES non-Hispanic white families, and n = 12 low SES non-Hispanic white families. There is an increased chance of committing a type II error (concluding that there is no significant difference or relationship when there is) because power (probability of detecting a true difference) was decreased by separating the sample into differing SES groups within each ethnic group. Based on the current data, sample sizes of high SES Hispanic and low SES NHW subjects would need to be increased to demonstrate a significant affect of SES and ethnicity interaction. With alpha set at .05, desired power of .80, 3 degrees of freedom (four groups), and an effect size of .30 (Cohen, 1987, defines a moderate effects size as .25), the sample of 9 high SES Hispanic families and 12 low SES NHW families would need to be increased to 27 subjects in each group. Because there are 4 groups, a total of 108 families would be needed to address the problematic sampling issue defined above. 78

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Correlation Analyses Following evaluation for potential interaction between SES and ethnicity, Pearson correlations between children's total physical activity and the hypothesized predictor variables were examined. These analyses were conducted to explore the relationships between predictor and outcome variables, not for the purpose of testing the study hypotheses. Mothers' and fathers' data were analyzed separately by ethnicity and SES. Mothers are shown in Tables 5.5 to 5. 8 and fathers in Tables 5.9 to 5.12. Mothers' Correlation Data Table 5.5: Hispanic Mothers' Correlation Matrix (n=45) Variables Act!Rec Value Rank Prioritization Mothers' PA Athl Comp. ChildPA Act!Rec Value Rank Prioritization Mothers' PA Athl. Camp. Child PA .004 .057 -.367* .089 .167 -.018 .502* .121 -.389** .070 .205 .105 -.317* .153 .371** Note: For value ranking a negative coefficient represent a positive relationship between variables. **Q... < .01, two tailed *Q < .05, two tailed 79

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Table 5.6: Non-Hispanic White Mothers' Correlation Matrix (n=50) Variables Act/Rec Value Rank Prioritization Mothers' PA Athl. Camp. Child PA Act/Rec Value Rank Prioritization 328* .336 -.484* Mothers' PA Athl Camp. ChildPA .447* -.258 .235 .165 .121 .288* -.082 -.020 .228 .110 -.063 .216 Note: For value ranking a negative coefficient represent a positive relationship between variables. **fL < .01, two tailed *Q. < .05, two tailed Table 5.7: High SES Mothers' Correlation Matrix (n=47) Variables Act/Rec Value Rank Prioritization Mothers' PA Athl. Camp. Child PA Act/Rec Value Rank Prioritization .093 .271 -.327* Mothers' PA Athl Camp. ChildPA .299* .192 .275 .126 .127 .001 -.277 .115 .100 .021 -.077 .237 Note: For value ranking a negative coefficient represent a positive relationship between variables. **fL < .01, two tailed *Q < .05, two tailed 80

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Table 5.8: Low SES Mothers' Correlation Matrix (n=48) Variables Act/Rec Value Rank Prioritization Mothers' PA Athl Camp. ChildPA Act/Rec Value Rank Prioritization Mothers' PA Athl. Comp. Child PA -.106 .113 -.476 .... .159 .184 -.054 .338* .010 .081 -.056 .069 .262 -.426 .... .117 .339'" Note: For value ranking a negative coefficient represent a positive relationship between variables. **Q.. < .01, two tailed *Q. < .05, two tailed Similarities between Hispanic and NHW mothers' variables include the positive association between prioritization and value ranking (the negative correlation coefficient is an artifact of the scales used). The main difference was a negative association between Hispanic mothers' prioritization and children's athletic competence and mother's prioritization, whereas NHW mothers show a positive relationship between their prioritization of physical activity for themselves and their children's athletic competence. Similarities between low and high SES mothers' variables include the positive relationship between prioritization and value ranking of physical activity. Low SES mothers' prioritization of physical activity was negatively 81

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associated with children's total physical activity. High SES mothers' favorable perception of the family activity/recreation environment is positively associated with their own physical activity, but not that of their children. Low SES children had a positive relationship between perceived athletic competence and physical activity, whereas a similar relationship in high SES was not significant (Q. = .05) Fathers' Correlation Data Table 5.9: Hispanic Fathers' Correlation Matrix (n=28) Variables Act/Rec Value Rank Prioritization Fathers' PA Athl. Camp. Child PA Act/Rec Value Rank Prioritization Fathers' PA -.284 -.049 -.180 .364 -.335 .331 Athl Camp. ChildPA .15()% -.015 -.003 -.203 -.085 .182 -.025 -.207 .371*"* Note: For value ranking a negative coefficient represent a positive relationship between variables. **Q. < .01, two tailed *Q. < .05, two tailed 82

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Table 5.10: Non-Hispanic White Fathers' Correlation Matrix (n=39) Variables Act/Rec Value Rank Prioritization Fathers' PA Athl. Camp. Child PA Act/Rec Value Rank Prioritization Fathers' PA -.036 -.061 -.735-.284 -.178 .347* Athl Camp. ChildPA .119 -.017 -184 .109 .208 -.133 -.031 .342* .216 Note: For value ranking a negative coefficient represent a positive relationship between variables. **Q < .01, two tailed *Q < .05, two tailed Table 5.11: High SES Fathers' Correlation Matrix (n=42) Variables Act/Rec Value Rank Prioritization Fathers' PA Athl. Camp. Child PA Act/Rec Value Rank Prioritization Fathers' PA -.285 .230 -.654-.545--.159 .309* Athl Camp. ChildPA .215 -.055 -.120 -.111 .248 -.107 -.100 .222 .237 Note: For value ranking a negative coefficient represent a positive relationship between variables. **Q < .01, two tailed *Q < .05, two tailed 83

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Table 5.12: Low SES Fathers' Correlation Matrix (n=25) Variables AcURec Value Rank Prioritization Fathers' PA Athl Comp. ChildPA AcURec Value Rank Prioritization Fathers' PA Athl. Comp. Child PA -.035 -.391 -.237 .288 -.353 .388 -.107 .006 -035 -.155 -.188 .182 .121 -.088 .339* Note: For value ranking a negative coefficient represent a positive relationship between variables. **g < .01, two tailed *g < .05, two tailed There are no similarities between the correlation matrices of the Hispanic and NHW fathers. There is a positive association between NHW fathers' physical activity and children's physical activity, whereas, a nonsignificant negative correlation is observed in Hispanic fathers. NHW fathers' value ranking of physical activity and their prioritization of physical activity for themselves are strongly related. NHW fathers' prioritization is also related to their own physical activity. Hispanic children's physical activity is positively associated with their athletic competence, but a similar relationship in NHW children is not significant. Low vs. high SES fathers also show different patterns of correlation. Athletic competence is positively associated with children's physical activity in the low SES group, but not in the high SES group. A strong positive association is present between high 84

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SES fathers' prioritization of physical activrty, perceived family activity/recreation environment and their own participation in physical activity. Multiple Regression Analyses Standard multiple regression analyses were performed between children's total physical activrty counts as the dependent variable and ethnicity, socioeconomic status, perceived family activity/recreation, value ranking of physical activity, prioritization of physical activity, parents' total physical activity and children's athletic competence as independent variables. Socioeconomic status and ethnicity interacted only in the mothers' model, therefore, SES and ethnicity were not included in the fathers' multiple regression analyses. Mothers The full equation was not significant (g= .154 ). The hypothesized relationships between mothers' predictor variables and children's physical activity are not evident. Subsequent analyses will examine possible intervening variables related to children's physical activity. 85

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Fathers The full multiple regression equation was not significant (Q = .152). The hypothesized relationships between fathers' predictor variables and children's physical activity were not supported. Model Restructure To achieve a more comprehensive description of children's total physical activity, the original model was restructured and examined further. Development and testing of this newly structured model provides information concerning possible alternative paths of influence of the independent variables related to children's physical activity. The theorized model includes a series of seven hypotheses based on extant literature pertaining to the present study. Socioeconomic status and ethnicity are antecedent (demographic) variables that cannot be influenced by psychosocial variables. Therefore, proposed model presented in Figure 5.2 begins with SES and ethnicity. Mothers and fathers were explored separately. 86

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Figure 5.2: Theorized Model to Be Tested l Etlmicity Hypotheses 1 An increase in parents' socioeconomic status will lead to an increase in valuation and prioritization of physical activity for themselves (Hypothesis 1 ) lsEs I 2. Parents' ethnicity will be positively related to an increase in prioritization of physical activity for themselves (Hypothesis 2). Ethnicity 87

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3. An increase in parents' value ranking of physical activity will lead to an increase in children's perceived athletic competency and children's physical activity (Hypothesis 3). !value -----.. 4. An increase in parents' prioritization of physical activity for themselves will lead to an increase in their physical activity, perceived family activity/recreation environment, children's perceived athletic competency and children's physical activity (Hypothesis 4 ). Prioritization ,.. cA_Ctivity/RecreatiQ!i:) ----88

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5. An increase in parents' participation in physical activity will lead to an increase in their perceived family activity/recreation environment, and children's physical activity (Hypothesis 5). ctivity/Recreation 6. Perception of their family's activity/recreation environment will lead to an increase in children's athletic competency (Hypothesis 6). 7. Children's perception of their athletic competency will lead to an increase in children's physical activity (Hypothesis 7). @ildren's Athletic These hypotheses were tested in a series of seven multiple regression equations, beginning with the main outcome, children's physical 89

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I i I i I I I I I I i I I II activity and progressing backwards through the hypothesis path outlined above (e.g. hypotheses 7 backwards to hypotheses 1 ). First, children's physical activity was regressed on athletic competence, prioritization, valuation, and parent physical activity. Second, children's athletic competence was regressed on family activity/recreation, prioritization and valuation of physical activity. Third, perceived activity/recreation was regressed on parent physical activity and prioritization. Fourth, parent physical activity was regressed on prioritization. Fifth, value ranking was regressed on children's perceived athletic competence and children's physical activity. Sixth, prioritization was regressed on ethnicity and SES. Finally, valuation was regressed on SES. The beta coefficients provided an estimate of the relative strength of the relations specified by each path between the predictor variables and the dependent variable. Model testing with a series of seven regression analyses relating to mothers' influences on children's physical activity resulted in elimination of three paths (3, 5, and 6) based on lack of significance (Q > .05). Athletic competence, in the first path, accounted for 13% of the variance in children's physical activity. Activity recreation, in the second path, accounted for 13% of the variance in children's athletic competence. The fourth path, parent physical activity and prioritization of physical activity, accounted for 14% of the variance in family's activity/recreation. And, 90

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finally, in the sixth path, SES accounted for 9% of the variance in value ranking. Model testing with a series of seven regression analyses relating to fathers' variables, resulted in retention of only the fourth path, fathers' physical activity, which accounted for 10% of the variance in fathers' perceived family-activity/recreation environment. Mothers Figure 5.3: Re-specified Model Relating to Mothers' Variables I Mother's PA I *.29 .............._ *.30 .......... *.36 *.28 I SESI I Value Rankind I Activity/Recreation I ___. Athletic I I Competence ___. Chidren's PA I Prioritization I This hypothesized causal model postulates mothers' SES influences her value ranking of physical activity. Mothers' physical activity and prioritization of physical activity for herself influences mothers' perception of the family's activity/recreation environment. It further posits that mothers' perception of the family's activity/recreation environment influences children's perceived athletic competence and thus, children's physical activity. 91

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Fathers Figure 5.4: Re-specified Model Relating to Fathers' Variables Fathers' Physical Activity *.33 Activity/ Recreation This hypothesized causal model (Figure 5.4) postulates fathers' physical activity influences his perception of the family's activity/recreation environment. There are no paths related to children's athletic competency or children's physical activity (Table 5.13). 92

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Summary of Seven Hypotheses and Results Table 5.13: Hypotheses Summary Hypothesis Mothers Fathers 1 Socioeconomic status affects SES affects Not supported valuation of physical activity and prioritization, not prioritization of physical activity for supported themselves. SES affects valuation supported 2 Ethnicity affects prioritization of Not supported Not supported physical activity for themselves. 3 Value ranking affects children's Not supported Not supported perceived athletic competence and children's PA. 4 Prioritization of physical activity for Prioritization Not supported themselves affects their physical affects parent activity, perceived family activity/ PA, athletic recreation environment, children's competence, and physical activity. child's PA, not supported Prioritization affects activity recreation, supported 5 Participation in physical activity will Parent PA Parent PA lead to an-iritrease in their perceived affects affects family activity/recreation environment, children's PA children's PA and children's physical activity. not supported not supported Parent PA Parent PA affects affects activity recreaactivity recreation, supported tion, supported 6 Perception of their family's activity/ Supported Not supported recreation environment affects children's athletic competency. 7 Children's perception of their Supported Not supported athletic competency affects children's physical activity. 93

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Qualitative Data To supplement the quantitative data, qualitative data were collected from mothers and fathers during home visits. Responses to questions were divided into ethnicity and socioeconomic status groups and summarized using percentages. Questions from the PAPS survey were used to further understand parents' perception of whether or not they think physical activity is important for themselves and their children, and subsequently, how they might act upon their beliefs and values?. If parents say something is important to them, do they act accordingly? Parents had the opportunity to provide more than one response to the open-ended questions from the PAPS survey. All responses were included in the analyses with some parents providing more than one response. Table 5.14 summarizes the responses from the PAPS. 94

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Table 5.14: Responses From PAPS Group SES/Ethnic High SES n=114 responses LowSES n=92 responses Hispanic n=94 responses Do you set aside time for PA for your child? If yes" how do you do that? "Yes"n=97 70% organized sports 8% self motivated 6% family activity 5% parents encourage 2% set aside time 2% after school time 1% limitlV 1 %just does it 1% child decides on own 40% organized sports 4% park 6% school 8% family activity 6% set time for child 6% daily sports/bike 6% chores 8% community ctr 4% limitlV 4% home equip 4% walk to school 2% just happens "Yes"= 66 responses 39% organized sport 21% on own/after school play/self motivated/just happens 1 0% school provides 6% participate with parents 4% chores 4%community organization 3% walk to and from school 3% limit 1V 3% encourage 2% home equipment 95 If "no", why not? 35% child decides on own 28% involved in organized sport 15% environment allows it 8% no time 8% discourage inactivity 8% still young 46% on own 13% no time 14% school 2% to and from school 2% cannot afford YMCA 2% outside and play 9% no set time 5% parks too far 5% dangerous neighborhood "No" = 28 responses 57% on own/just happens/after school play 7% after school activities 7% no time 4% organized sport 4%too hectic to enroll in organized sports 4% no sports in school 4% do not set time 4% dangerous environ. 4% park is too far 4% not in any program

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II I I I I I l i i I Table 5.14: (Cont.) Do you set aside time for PA for your Group SES/Ethnic child? If yes" how do you do that? lf"no", why not? Non-Hispanic white "Yes" n=86 n= 112 49% organized sport 13% just happens/self motivated/free play after school 6% encourage child 3% family participation 2% limit TV 1% get PA at school 1% parents set aside time/weekends 1% go to park "No"n=26 44% on own 26% PA in organized sports 7% live in area where daily PA is routine (out of city) 4% seldom see child 4% don't make time 4% have limited time 4% get PA at school 4% walk to and from school 4% encourage Description and summary from the differing socioeconomic (high and low) and ethnic (non-Hispanic white and Hispanic) groups are described below. All parents consider physical activity important for their children. High SES and NHW parents primarily enroll their children in organized sport in order to assure weekly physical activity, whereas, low SES and Hispanic parents believe that their children do it "on their own, participate in school activities, or (parents) have limited time" to provide opportunities for participation in physical activity for their child. Parents who do not set aside time for their children do not think there is a need to intervene in their children's daily activity. 96

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These qualitative data show that the percent difference of parents who enroll their children in organized sport in order to provide physical activity were less between ethnic groups (49% NHW and 39% Hispanic) than between SES groups {70% high SES and 40% low SES). This suggests family economic resources, as opposed to ethnic differences, may influence these differences in children's increased opportunities for structured physical activity involvement, such as organized sports versus unstructured physical activity that occurs in neighborhoods, parks, and school playgrounds. Moreover, parents' perception of their children's activity level as something that "just happensn {high SES 35% vs.low SES 46% and NHW 44% vs. Hispanic 57%) may affect parents' motivation to intervene in their child's day to day activity. These data support the findings in the quantitative data: parental influence upon children's physical activity is influenced by SES to a greater extent than by ethnicity in this sample. 97

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CHAPTER6 DISCUSSION AND CONCLUSION Discussion Determinants of children's physical activity are complex and related to a number of different personal, behavioral and environmental variables. The overall models hypothesizing that specific parent and child variables were predictive of children's physical activity were not supported. In addition, regardless of SES or ethnicity, there was no correlation between children's physical activity and BMI and all children had similar levels of physical activity. However, there were some additional findings from parent and children's variables that were of interest relating to children's physical activity. In all groups, children's athletic competence was the key predictor of children's physical activity. Examination of parental variables in relation to children's athletic competence and physical activity suggests that SES exerts a greater impact upon children's physical activity than ethnicity. The data further suggest that mothers exert a greater influence than fathers on their children's physical activity and that such effects are mediated by mothers' influences on children's perceived athletic competence. Among mothers, high SES was positively associated with prioritization of physical 98

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activity, higher levels of physical activity in the mother, a greater perceived family recreation/activity environment, and, in tum, a higher perceived athletic competence and physical activity in children. In contrast, high SES fathers' prioritization of physical activity impacted only upon their own physical activity and their perceived family/recreation environment. NHW fathers' physical activity was positively associated with their child's, whereas among low SES and Hispanic children, only the child's sense of athletic competence related to the child's physical activity. The qualitative data supported that all parents consider physical activity important for their children and that organized sports were considered the primary mode in which children participate in physical activity with SES influencing children's participation in organized sport to a greater extent than ethnicity. Quantitative comparison of these groups showed several similarities and contrasting relationships. These similarities and differences must, however, be viewed cautiously due to inequity in samples sizes between high and low SES and NHW and Hispanic families which may have influenced the study's results and increased the chance of type II errors. Because low SES Hispanic and high SES NHW families were over sampled relative to low SES NHW and high SES Hispanic families, some effects may have not been detected or may have been erroneously detected. Of particular interest is the fathers' data showing no difference 99

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between any of the predictor variables. A sample size of 27 in each ethnic and SES group would have been needed to have sufficient power to detect significant potential interaction/effects with respect to variables, parental prioritization and valuation, perceived family environment, parents' physical activity, and children's perceived athletic competence. Future work in this area should include an adequate sampling of these subgroups in order to discern the impact of ethnicity and SES relating to parental influence on children's physical activity. Main Findings Compared with Past Studies Children's Athletic Competence and Children's Physical Activity In this study, children, regardless of sex, ethnicity, age and SES, were found to be similarly active and had favorable perceptions of their athletic competence (there was no significant correlation between age of children and perceived athletic competence or physical activity counts). As expected, children's physical activity levels, in this sample of 3-5th graders, have not yet declined. Consistent with earlier findings, children's perceived athletic competency in this study is positively related to children's participation in physical activity, and was found to have a stronger correlation than previous studies (Reynolds et at., 1990, Trost et at., 1997). This study extends previous findings and provides additional support for the 100

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assertion that mothers have a greater influence on their child's sense of athletic competence and physical activity than fathers. Further, exploratory analyses suggest mothers' physical activity and prioritization positively affects perceived family activity and recreation environment and thus children's perceived athletic competence and physical activity. This is the first analysis of parent and child activity that identifies a specific causal pathway by which maternal variables positively affect their children. SES and Children's Physical Activity The finding that SES is a more important influence than ethnicity upon physical activity is supported by the data from the NHANES Ill indicating that inactivity is more common among women of lower social classes and among persons who are less educated (Crespo et al., 2000). Such data are congruent with the findings reported here regarding mothers. Low SES mothers in this sample have lower levels of physical activity than high SES mothers. There were no significant differences between high and low SES fathers' physical activity. This findings may be due to the small sample size of fathers or perhaps differences in energy expenditure related to occupation e.g. blue-collar jobs involve more physical labor and therefore have higher energy expenditure than white-collar jobs (Ainsworth, et al., 1993). 101

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One finding that is difficult to explain is the interaction between SES and ethnicity such that high SES and Hispanic mothers had greater prioritization of physical activity for themselves than low SES and NHW mothers. This is unexpected given that Hispanic mothers have greater BMis and lower physical activity than NHW mothers. This unusual finding may be explained by social desirability response bias by the Hispanic mothers. The Hispanic mothers' high prioritization response may not be the mothers' true feeling, but rather a response intended to meet the approval of the experimenter (Shaver, 1987). Hispanic mothers may be more apt to overestimate prioritization of physical activity for themselves in response to their higher BMis partly as a function to what they may intend to do, as opposed to their present physical activity behavior. They may not be ready to change their behavior from inactivity to activity and thus, positively respond to prioritization of physical activity for themselves but have not yet adopted increased daily physical activity. Furthermore, the fact that Hispanic mothers prioritize physical activity for themselves, and yet do not engage in as much physical activity as NHW mothers, suggests that Hispanic mothers' may perceive the relationship between physical activity and body weight differently than NHW mothers. Many people participate in physical activity to control weight and improve their fitness level. Although this may be true for NHW women, it may not be the case for Hispanic 102

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women. Hispanic women's positive body image for a given size is greater than NHW women's (Winkleby et al . 1996) and thus may influence the amount of physical activity they perceive necessary for weight control and positive health benefits. Therefore, their prioritization of physical activity for themselves is not reflected in the arnount of physical activity as compared to NHW women who prioritize physical activity and participate to a greater degree in physical activity which is reflected in their greater physical activity counts and lower BMis. Furthermore, Hispanic women may prioritize their family's needs to a greater degree than their own and thus, may replace their time to participate in physical activity with their family's needs (Higgins & Learn, 1999). Ethnicitv. Children's Physical and BMI The findings in this study show that children's physical activity did -not differ by ethnicity-or sex:Despite the similarities in physical activity, Hispanic children had higher BMis than NHW. These findings are supported by data from NHANES Ill that reported Hispanic American children have greater BMis for their age than Euro-American children. However, NHANES Ill reported Hispanic children to have lower activity levels than NHW children (NHANES Ill, 1994). While physical activity differences were not supported in this study, sampling biases (subjects not 103

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randomly selected), sample size, and children's age may have limited the likelihood of finding a difference between NHW and Hispanic children. Additional explanations for the greater BMis found in Hispanic children may be related to total dietary intake. Comparison of food consumption and of nutrient intake was not measured in this study and therefore the contribution of energy intake to the differences between Hispanic and NHW and low and high SES children's BMI in this sample are unknown. Genetic and metabolic factors also contribute to weight status. Heritability studies indicate that up to 50% of the variance in weight and body mass index is attributable to genetic influences, whereas environmental factors account for approximately 25% to 50% of the (Bouchard, 1994). Therefore, genetic and metabolic factors may contribute to the discrepancies found between Hispanic and NHW children's BMis. Data from this study does not support the relationship between --levels of physical activity and BMI in children. Therefore, based on this study, physical activity in youth (8-10 years) may not provide evidence that physical activity impacts upon BMI, but may provide a starting point for further study into the changes that occur within different ethnic and SES groups over time. The need for longitudinal observations is supported by current literature demonstrating that physical activity habits track from youth (adolescence) into adulthood (Malina, 1996). 104

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Mothers' vs. Fathers' Influence on Children's Physical Activity Although both mothers' and fathers' have positive beliefs concerning physical activity for themselves and their children, mothers' appear to influence children's physical activity to a greater extent than fathers' in this study. Data from other studies examining mothers' and fathers' role in influencing children's physical activity are comparable to the results of this study. For example, in Kimiecik and Horn's study (1998), both mothers and fathers positively endorsed physical health, but mothers' beliefs about children's physical competence, goal orientations, value of fitness participation, and reasons for participation, played a greater role in the amount of children's moderate-to-vigorous physical activity participation. Results from another study (Howard & Madrigal, 1990) found that in twoparent families, mothers were more involved than fathers in the shaping and organizing of the recreation participation patterns of their children. The finding that high SES fathers' variables bore no relationship to their children's physical activity suggests some interesting possibilities i.e. high SES fathers may engage in more work hours per week and thus have less time for their personal structured physical activity. Consequently, they may be less apt to be involved in organizing, planning, or participating in physical activity with their children. 105

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Organized Sports and Children's Physical Activity Most parents in this study consider physical activity for their children to be defined by participation in organized sports. The qualitative findings in this study regarding organized vs. non-organized sport are supported by data from the Amsterdam Longitudinal Growth and Health Study. Van Mechelen et al. (2000) found that physical activity declines during adolescence due to decreases in non-organized sport and vigorous activity. Conceivably, the physical activity levels measured in this study captured physical activity levels before the age-related decline because a majority of children in both SES and ethnic groups were enrolled in organized sports. The drop in physical activity shown among older children by authors elsewhere (Rowland, 1991, Adams et al., 1992, Kann et al., 1996) may be influenced by the lack of opportunity and access to organized sports, especially among children from low SES families. An additional contributor to the decline in physical activity as children approach adolescence may be due to social and peer acceptance of participation in organized sport. Girls, in may be limited in their choice of organized sports because many are male dominated e.g. baseball, football, lacrosse. 106

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Parent and Child Physical Activity Relationship The present study's findings demonstrate that parents' physical activity levels may not be the primary influence upon children's physical activity levels and that role modeling may only be one source of parental influence. Current studies suggest that physically active parents are more likely to have physically active children (Moore et al., 1991, Taylor et al., 1994) while other studies find no significant relationship between parents' and children's physical activity levels (Sallis et al., 1993). These inconsistencies in the literature highlight the need for more research to discover the possible direct and indirect influences upon children's physical activity. My data suggests that a combination of parents' beliefs, values, and particularly, children's perceived athletic competence, may contribute to children's participation in physical activity. Perhaps differing cultural values contribute to the way in which children perceive the message to engage in physical activity. For example, Hispanic mothers may prompt children verbally to participate in free-play activity whereas NHW mothers may engage in less verbal prompting but more modeling. Alternatively, children may internalize their parents' value, prioritization, and modeling of activity differently. Conceivably, children may utilize both direct and indirect parental behavior and/or messages in their decision-making process to be active or inactive. Again, the present study supports the 107

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I I I i I i I I I l I I I I I I I I I I i i notion that parents' physical activity may indirectly influence children's physical activity. The mothers' re-specified model in Figure 5.3 illustrates that the theoretically proposed different predictor variables may possibly indirectly influence children's athletic competence, and thus children's physical activity. A further of parents' influence on children's physical activity may be associated with parent's time spent in physical activity with their children that may contribute to children's enjoyment of physical activity. Children naturally welcome and pursue parent's attention, interaction, and contact. When parents engage in playful and enjoyable physical activity with their children, the children's subsequent attraction to physical activity may increase and impact children's formation of life-long exercise habits. Understanding the impact of parents' participation in physical activity with their children is a potentially beneficial area of -research thatneeds-furtherstudy: -Summary of Relationship Between SCT and Children's Physical Activity Overall, the social cognitive model of parental influence partially explained children's physical activity in this study. The present study tested the relationship between parent cognition (prioritization and valuation of physical activity), parent role modeling (physical activity 108

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behavior), child behavior (physical activity). and environment (parents perceived family activity/recreation environment). These variables have not previously been studied in aggregate youth and families. Previous studies have demonstrated that role modeling (parent exercise behavior) is associated with child behavior (Moore et al., 1991 and Taylor et al.. 1994). The present study supports this theoretical relationship, but only among NHW fathers. whose physical activity levels correlated positively with that of their children. The relationship between children's cognition (perceived athletic competence) and children's behavior (physical activity) is supported in this study and consistent with earlier findings of a positive correlation between children's perceived athletic competence and children's participation in physical activity (Reynolds et al., 1990. Trost et al.. 1997). However, there was no support for role modeling influencing children's behavior with all mothers or the subset of Hispanic fathers. ---There was-no supportforthetheoretical relationship between parent cognition (prioritization and valuation of physical activity) and child behavior in the entire sample or among sub-samples. The positive influence of environment on child cognition was only observed in Hispanic and low SES mothers. In summary, only limited support for the SCT interactive influences model of behavior was observed in this sample. 109

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Weaknesses and Strengths of Study The present study has several limitations. First, this study used cross-sectional data and does not provide causal evidence. For example, the relationship between children's physical activity and children's athletic competence may result partly from the developmental stage (pre pubescence) of the children from whom these data were collected. Despite the fact that previous research reports a strong relationship between children's self-efficacy and their activity levels (Reynolds et al., 1990), longitudinal research would provide further examination on the correlates of physical activity in Hispanic and NHW children as they develop into adolescents and young adults. Second, additional determinants of physical activity such as physical environmental variables, hours of television viewing, and exercise behavior of peers and siblings might further reveal factors that contribute to children's physical activity, and how they interact with parental variables. Third, an expanded sample of Hispanic families that include both less acculturated and higher economic status, as well as non-Hispanic white families of lower economic status, would provide a more thorough examination of the differences associated with ethnicity and SES. I defined acculturation for this sample as the ability to read, write and speak English which addresses only one segment of the Hispanic population and may have limited the ability to 110

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assess ethnic influence upon children's physical activity. A more formal measurement of acculturation is needed to further understand the impact of ethnicity on children's physical activity (Clark & Hofsess, 1998). Fourth, parents' total physical activity was measured by accelerometers whereby both planned activity and occupational activity were combined. Therefore, occupational physical activity or working conditions may affect parents' response to questions pertaining to prioritization and valuation related to physical activity. Fifth, it is also possible that the construct "prioritization" and the manner in which it was evaluated in the study (PAPS) may have been at odds with parents' interpretation of its meaning as it relates to physical activity. Additional questions that seek information regarding parents' prioritization of physical activity in comparison to other specific behaviors may improve and clarify the concept of "prioritization". In addition, both sampling error and small sample sizes may have contributed to-this problem and need to-be-evaluated-further and more carefully in future research. Sixth, energy balance and weight stability depend on the relationship between calories consumed (energy input) and calories burned (energy expenditure). Inclusion of dietary data would have provided the necessary information to realize the contribution of caloric intake in relation to energy expenditure and BMI status. Lastly, self-selection bias is a concern. Those that participated may be more positively biased in their 111

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beliefs and attitudes towards physical activity. Therefore, caution is warranted to generalizing these findings to other populations. Nevertheless, within the limitations of the study design, results from this study provide original and meaningful information about the determinants of physical activity in 3rd-5th grade Hispanic and NHW children of high and low SES. The most notable strengths of the study include objectively measured physical activity in both the children and their parentis using accelerometers, the inclusion of families of differing socioeconomic status families within both ethnic groups, and the quality of data collection (92% of all data collection was completed by the P.l.). In addition, the inclusion criteria specified that both parents must identify themselves as "Hispanic" or "Caucasian" in order to be considered for study. Therefore, all participating families were not racially mixed, which contributed to the strength of analyses when differentiating families into Hispanic or NHW. Two environmental factors potentially influencing parents and their children's physical activity are the seasonal changes in Colorado and the sense of safety within neighborhoods where families reside. Data were collected during the months of September through December in Denver and Colorado Springs. During the month of January, twenty additional families in Colorado Springs were included in order to expand the sample 112

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size of low SES NHW families and high SES Hispanic families. The fall and winter was considered "mild" with average temperatures in Colorado Springs ranging between 57.6 F, 50.8 F, 44.8 F, 33.6 F, 32.1 o F, September through January, respectively. Denver temperatures were similar ranging between 59.5 F, 51.7 F, 47.1 o F, 35.4 F, September through December, respectively. These seasonal temperature changes would not account for a large variability in physical activity levels in parents and children. Furthermore, data were collected only during the first two weeks of December (prior to the school holiday) when temperatures started to decline. During the month of January, no schools in Colorado Springs were delayed or had limited outdoor play due to inclement weather (personal communication from District 11 school administration). To assess a sense of safety within neighborhoods where families reside, neighborhood crime risk information was obtained using the zip --codes -A -risk rating-system provides a ranking of risk of violent crime in a specific geographic area. Ratings 1-3 are considered low risk, 4-6 moderate risk, 7-8 moderately high risk, 9 high risk, and 1 0 extremely high risk. A rating of 1 0 indicates the risk is 1 0 times the national average or more. The majority of families (low SES Hispanic n = 39 and high SES NHW n = 39) participating in this study lived in two zip codes, 80906 (Colorado Springs) and 80211 (Denver). The 113

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APB/Neighborhood CrimeCheck (www.apbnews.com) rating for both 80906 and 80211 were 6, designating a moderate crime risk. Neighborhoods where Hispanic, NHW, low SES, and high SES families reside share the same indices for risk of crime. Therefore, their participation in physical activity may be similarly facilitated or hindered when the association between neighborhood safety and physical activity is considered. Future Research Questions Longitudinal studies to examine determinants of children's perceived athletic competency and physical activity are needed to identify factors that influence children's participation in physical activity during different stages of development from childhood through adolescence. Because physical activity decreases from childhood to adolescence to adulthood, longitudinal studies would identify predictors of physical activity changes over the life span (Sallis et al., 2000). Identification of age-related predictors of physical inactivity in youth would help interrupt the decline in physical activity and support children to maintain healthy physical activity levels. In addition, a larger and more diverse SES sample with less acculturated Hispanic families would provide the data necessary to fully identify the impact of SES and ethnicity within and among these groups. 114

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Future research should examine the biological, social, and a psychological influence upon participation in organized sport during youth. Identification of subgroups (girls, minority groups, and adolescents) who are at the highest risk of maintaining sedentary habits should be focused upon in order to increase sports participation because of its possible foundation for activity habits in the future (Malina, 1996). The variable, parental prioritization of physical activity, needs to be studied in more detail so that the construct of prioritization can be used as a valid and reliable measure in future studies. More extensive examination is necessary before its influence upon children's physical can be adequately evaluated. Modifiable determinants of physical activity, particularly children's athletic competence, ought to be explored at greater depth because of the strong relationship between children's participation in physical activity and ----percelvea competence:Interventions that build athletic competence and self-efficacy through supportive and enjoyable physical activity for children will therefore be more effective. Innovative methods to encourage children to participate in physical activity beyond organized sports are needed to prompt individuals to adopt and maintain life long regular physical activity. Strategies are needed to assist children who may not be athletically inclined and/or children who 115

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have limited access to physical activity and skill-acquisition opportunities to enjoy and participate in activities that are enjoyable. Conclusions Socioeconomic status had a greater influence on children's physical activity than ethnicity in this sample. Non-Hispanic white and high SES mothers scored higher on their perceived importance of family activity/recreation environment, prioritization of physical activity for themselves, and were more physically active than Hispanic and low SES mothers. High SES mothers had greater ranking of the importance of physical activity than low SES mothers. There was an interaction between SES and ethnicity across all mothers such that high SES and Hispanic mothers had greater prioritization of physical activity for themselves than low SES and non-Hispanic white mothers. High SES mothers' valuation of --physical-activity was-greaterthan low SES mothers.-There were no differences in physical activity levels between Hispanic vs. non-Hispanic white and high vs. low SES children, yet Hispanic and low SES children's BMis were higher than non-Hispanic white and high SES children's BMls. There were no differences between Hispanic vs. non-Hispanic white nor low vs. high SES fathers' predictor variables, nor did any of fathers' data relate to children's physical activity levels or perceived athletic 116

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competence. For all groups, children's physical activfty was best predicted by children's perceived athletic competence. A re-specified model was developed and tested. The hypothesized causal model postulated that mothers' increased SES influenced her valuation of physical activity. Mothers' increased physical activity and prioritization influenced her perceived family activity/recreation environment and thus, an increase in children's perceived athletic competence and physical activity. These findings suggest that determinants of physical activity differ between Hispanic and non-Hispanic white families of differing socioeconomic status. To prevent pediatric obesity and inactivity, a coordinated nation wide commitment to improve and provide physical activity within public schools and community settings are needed. Intervention programs should be developed in a culturally appropriate manner for low income and minority groups who are at increased risk for negative health consequences related ---to-being inactive-and overweight: ln-addition,-improved family participation in physical activity intervention programs (although difficult), and understanding the present day family structure, is critical to improve a healthy overall lifestyle pattern of regular activity for families that all members enjoy and support. 117

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APPENDIX A EVIDENCE TABLES OF CRITICAL STUDIES RELATED TO PHYSICAL ACTIVITY IN CHILDREN 118

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----------------------------------------------... __ Author, liUe Sampling 1 N;age; Results Conclusion Problems; Joumal measurements strengths Calderon, Risk factors Normal ; n=18 pairs; Triceps Slgnlf. differences between TV viewing and Small sample. LL., for obesity In weight I sklnfold, obese and non-obese girls were consumption of Derived from same Journal of Mexicanmom/ Demographic, found In weight, BMI, mothers' excess energy may school and thus may American American daughter j anthropometric, diet BMI, daughters' triceps. Annual be an Important Interfere reliability of DleteUc girls: dietary pairs I (24 hour recall) and family Income did not differ predictors of obesity. survey responses. Assoclatlo factors, volunteer PA for daughter (3 between 2 groups. Dietary PA modified for 3 n, 1996. anthropomet day modification variables ... no sign dlfferencu. days. Dietary data ric factors from 7 day recall) PA ... dally minutes of PA no from girls may be and physical and hours of TV, sign differences. BMI not assoc. problematic. Mothers activity. computer or video. with PA minutes. But, sign -PA would have association between PA min and contributed to hours of TV (r=-.34, p=.04). explanation of BMI. Obese girls had 115 kcal/day> All similar Income, than nonobese girls. difficult to assess ...... I SES contribution to ...... (0 larger BMI, when no sign differences In PA and dietary assessment. I Bungum, Correlates 8publlc, 2/ n=520 primarily 9111 Males more active and lntenUon In males and females, Self report, not T. of PAin private graders (8111) to parUclpate. Females stronger self efficacy Is random, AA and Pediatric male and and 2 34o/o non white. attitudes about PA. Corr + males associated w/ PA, white only. Exercise female parochial 5 psychological and subject norms with enjoyment of PA Science, youth schools In: variables, PA lntenUons. Females subjective correlated with 2000 So. I measured by norms corr with VPA and lntenUon 1o be active. I Carolina previous day Intentions. Both = attitudes, Possibly attitudes activity recall. enjoyment, self-efficacy corr with towards PA In males MVPA and VPA and age= VPA maybe more and Intentions = MVPA and VPA. effecUve In promoting Regression -+males = attitudes PAIn males vs. re PA predicted enjoy and self-females. elf. predicted VPA. Females-+ Self efficacy predicted MVPA and self efficacy predicted VPA.

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...... 1\) 0 ------------Evidence Tables (Cont.) Author, TIUe Sampling N; age; Results Conclusion Problems; Joumal measurements strengths Sallls,JF, Medicine and Science In Sports and Exercise, 2000 A review of correlates of physical activity of chRdren and adolescents Dependent variable was measure ofoveran PA 108 studies evaluaHng 40 variables for chHdren and 48 for adolescents; ages 3-18 Children's PA: Of 102 studies, 54 were of chRdren. Cross-lldlonal design In 76% studln. 81% of compartsona (boyslglrta) boys were more ac:tlve. Body wtladlposlty 8l1d age had assoc. w/ PA & were Inconsistent SES not rlt to children's PA. Minorities PA = nonHispanlc white, Perceived baniers neg correlated and lntenUon to PA and preference for PA had+ associations. Indeterminate relations were self-eflk:acy, perceived competence and attitudes. TV was Indeterminate with healthy diet and previous PA + associations. Parent PA + associations with parent PA with chHd Indeterminate. Access to facilities and lime spent outdOOB + related to children's PA wllh nelghbortloocl safety and parents providing transportation to PA unrelated to PA. Very little over1ap In differing age groups-+boys, Intention to be active, previous PA, access to facllltlea and opportunities to exercise. Note: 1996 Surgeon General Report found 9 confirmed var1ables conslstenUy associated with PA of chHdren or adolescents = self elficacy, perceived physical competence, perceived benefits, perceived barriers, 60% of reported asaoclaUon with PA were slgnlf. Association with children PA c: male, parental averwelght status, PA preferences, Intention, perceived barriers, previous PA, health diet, access facllltla, time spent outdoors. Adolescents = male, elhnlclty (white) age, perceived act competence, Intentions, PA, community sports, sensation Heklng, sedentary after school and on weekends, parent support. SUpport from others, sibling PA. direct help from parents and opportunity to exercise. Adolescents use survey methods whereas chHdren used objective measure. No dissertation data, not true mete-analysis, sample, analysis strlt81lel, dlvnlty of variables.

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Evidence Tables (Cont.) Author, TiUe Sampling N; age; Results Conduslon Problems; joumal measurements strengths lntenUon,enjoyment, physical education attitudes, parents encouragement, direct help from parents, peer and sibling support, access to play spaces and equipment, end lime spent outdoors. Rosner, Percentiles 9 studies n=66,772 children Mean BMIIncreases with age and Is Tables to detennlne Data from muiU B., for body ofBP In ages 5-17; Height slightly higher for girls than boys. relative ranking of study sites In which The mass Index children and weight using Mean BMI for black and Hispanic BMI from large htlwt are not Joumal of In US varying methods. girts noticeably higher than for white study of health measured with Pediatrics chRdren 5 to "standardized glr1s. %iles of BMI higher than those chOdren and consistent methods. 1998 17 years of measurements" based on NHANESI especially for adolescents with %of ethnic ....... age 95"%ile. ProporUon of obese children gender and ethnic variability Is limiting 1\) compared with NHANES I standards differences, Large sample size ....... Is higher and Is highest for Hispanic boys and black and Hispanic girts. Sallis, JF, Parent Cross n=148 411 grade Glr1s= transporting to play sign. corr Parents reported Self report by AJOC, Behavior In sectional glr1s and 149 4" with reported activity and parent edu physical activity parents, sampling 1992 relaUon to survey of grade boys and was Inversely associated with Caltrac was not associated started large and physical students parents; PA by self activity score. Boys=playlng with with child activity or dwindled to those acUvlty and and report 1 day recall, child slgnlt. corr with reported act and fitness. Availability eligible, all finding fitness In 9 parents accelerometer, Inversely corr w/1 mile run. of transportation by weak, no diverse year old htlwt, fitness by 1 Children's reported activity, Caltrac parents to sport ethnic composition. children. mile run, parent act and 1 mile run time sign corr with and fitness survey for PA. edu parent variables. Transport child to activities was slgnlf. # of hours of work play was sign. contributor (p<.02) for (nearly so) Parents outside home, glr1s, but entire model was not slg. who play with parent support of Playing with child was slgnlf. children had more children's PA contributor for boys and sign model active boys with accounted tor 4% of variance. Parent verbal PA was r/t to children's PA. Ethnlclty encouragement to was not sign contributor to any model be active was not and BMI only related to boy's sign In any model Callrac. (boys or glr1s)

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.. -----------------------------------------------Evideoce Tables (CQnt.} Author, Title Sampling N;age; Results Conclusion Problems; measurements strengths Wolf AM, Activity, Children n=552 girls In Controlling for age, Asian and 36% of entire Ages too varied. American Inactivity, from grades 5-12; PA Hispanic reported 8.81 (p<.01) and sample met Healthy Self-report of htlwt. Journal of and obesity: Mass. measured by 12.61 (p<.0001) fewer activity units, People 2000 for Old find ethnic Public Racial, Schools. Godln-Shepard PA respectively than ref. groups. Most vigorous activity; differences. Puberty Health, ethnic, and Elem., Jr. survey, htlwt selr activity was mild eKerclse. 38.4% of less than 1/5 of confounds data 1993 age High and reported, obesity enUre sample and less than 50% or Hispanic, Asian because or vast differences High defined by age most ethnic groups met 2000 children met goal. range of ages. among school. and seK reference objective for strenuous activity. Elem. PA Inversely schoolgirls. data at 85111 school children were more active. associated with percentile, Mild activity lnaeased with age BMI. Obesity not sedentary where total activity and strenuous related to Inactivity. behavior or activity decreased with age. Inactivity assessed Inactivity: no grade level differences by ## of hour of lV In lV viewing. AA children had per day. highest o/o of hours of TV (>5 hrslday). Between >2 hr/day, white were highest at 53.8 followed by Hispanic children at 50.0 hrs/day. Obesity: Highest among AA and lowest among Asians. BMIInversely related to PA (p<.0001 ). No relationship between TV and obesity. Sallis, JF, Predictors of 7 suburn=370 girts and Psychological variables eKplalned Children's 82% white, 12% American change In ban 362 boys 4-5111 4% of variance In PA change, preference for PA Asian/pacific Journal of Children's schools grades parent variables eJCplalned 8% and and frequency Islander, 4o/o Pre-Physical SPARK Interactions with skin-folds explained parents Hispanic and 2% ventlve Activity Over program 3% (total 15%) .@!!:!!.-psychological transporting AA. Change In PA Medicine, 20 Months: variables explained 3% and parent children to activity and very 1999. Variation by variables 1.5% and Interactions with locations eKplalned comprehensive gender and skin-folds 1.5% (totalS%). Rate of slgnlf. proportion of psychometrlc level of decline over 20 months ranged from variance for girls characteristics adiposity. 3-6% for boys and 7-12% girts. and boys. Decline measured. Skin-In PA during folds triceps and childhood Is calf. parUally explained

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-----------------------------------------------... -------------------"""" 1\) 1\) Evidence_ Tables lCont.l Author, lille Sampling N; age; Results Conclusion Problems; Journal measurements strengths Sallls,J. Research Otly for Ex and Sport, 1997 Assessing perceiVed physical environment al variables that may lnftuence physical activity lnlro psych. students at participatIng University ChDd PA measures : One day recall, Caltrac accelerometer (one day), parent report of children PA PA change Index: Index combining all measures for habitual PA Predictors: skinfolds, child survey (psychol variables) and parent survey (PA and behaviors rft chDd PA) n=110 college students 20.6 yrs n=83 women, 27 men; Environmental characteristics: Home, neighborhood, convenient facRIIIes. PA measures: survey data strength, vigor, freq and duration taken from various surveys Test-retest retlabRitles were ,89 tor home equip scale, .68 for neighborhood, and .80 for convenient facilities scale. Home and convenient facilities scales were corr with self reported PA. In multiple regression only slgnlf. association was home equipment with strength exercise. psychological and social characteristic measurements In this study. Different factorslnftuence dedlne In girls' and boys' PA In youth. Further research needed to Identify other environmental characteristics that may lnftuence PA. This Is one tool that measures home, neighborhood and convenient facl. Others are needed. Sampling Is nonrepresentallve of larget' pop. Dlvene sample. Recall PA survey.

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Evidence Tables (Cont.} Author, TlUe Sampling N;age; Results Conclusion Problems; Journal measurements strengths Treuth, Energy Lab 24 healthy glr1s 7Overweight group had slg. higher Overweight glr1s do Small sample size, MS. Expenditure based 10 yr.; Room body weight, % fate, fat mass and nat have lower PA PA In lab setting Is lntemaand physical study respiration fat-free mass (p<.001). Overweight energy ex-not Indicative of Uonal fitness In calorimetry and glr1s had high BMR. sleeping mel pendltura or fitness typical tree play Joumal of over-weight doubly labeled rate, 24 hr sedentary energy expecl. levels than nonespecially within this Obesity vs. non-water= BMR, and total energy expe
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...... 1\) (.rJ --------------Evidence Tables CCont.l Author, Title Sampling N; age; Results Conclusion Problems; Loumal measurements strengths Lindquist, CH, Pre ventive Medicine, 1999 Sociocultural determinant s of physical activity among children longitudln al Ages 6.5 years (mean of 10 years). n=107; Tanner stage, Hollingshead, gender, age, single parent, pubertal development, social class, TV viewing, V02 max (lab), DEXA for fat mass and fat-rrae mass, PAby modlfted Kriska actlv. quesHonnalre, vlg actl by survey Interview quesUons, PE dass Ume, and sports team participation Weak correlaUons among various activity and fitness dimensions and multivariate analyses revealed distinct predictors for activity and ftlness outcomes dearfy support that PA Is muiUdlmenslonal construct. Physical fttness corr with few activity outcomes and represent distinct attributes predicted parUally by sociocultural factors but largely by physiological characteristics (eg body c:omposllfon). Few ethnic differences In childhood PA once characterfatlcs as social dus and single vs. dual parent tamny were controlled for Multivariate analyses found higher levels of TV and vlg among children from single parent homes, lower habitual PA among girls, less PE exercise among M and children from single homes, higher sports team among older yet phys Immature children and higher PA fitness among boys, Caucasian, physically mature children and children from single parent homes. Mulll-dlmenslonal nature of ch"dhood PA and lnftuence of soclo
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Evidence Tables (Co_ntJ Author, Tille Sampling N;age; Results Conclusion Problems; lou mal measurements strengths Dl Determinant Involved In n=111 families 1 Children enjoyment of PA was Socialization In Self selection/white Lorenzo, s of previous Caucasian (93%) consistent predictor of PA (511 and 611 family exerts and middle class TM, Exercise study 811 and 9" graders; grades). 8" and 9" graders-chUd's lnftuence on famHies. Dads who Preamong 54 glrfs and 57 exercise knowledge, mothers' PA exercise. Relative participated may be ventive children. II. boys mean age and child's and mother friend Importance differs more biases towards Medicine, Long14.0 ys. modeling/support predicted for glr1s. for glr1s and boys results. 1998 ltudlnal Measurements: For boys child's setf-efftcaey for PA, and patterns of Analysis. 1) home Interviews exercise knowledge, parental these determinants (physical activity modeling, and Interest In sports change over lime. Interview) with met media. Longitudinally, mother's self Glr1sselfetficacy levels calculated efficacy, barriers to exercise, for PA was only over 3 days. 2) enjoyment of PA and chHd's elf positive predictor. Children's PA elllcacy for PA were Important for questionnaire (8) glr1s. Only child's exercise knowledge ...... operant and social predicted boys' PA. Information from 1\) learning variables fathers nearly doubles explanatory 3) parent PA power of predictors for both genders. questionnaire (6) habits and social leamlng var. Sallls,JF, Correlates Nationally n=1504 children Demographic variables explain >2% Across all age Telephone survey. Health of Physical representa and parents; of variance. Child variables explain groups and sex PA by recall. Large PsyActivity In Uve Telephone 8-42% of variance In child PA. Use of subgroups diverse chology, National sample. Interviews; child's afternoon time was sign for all enjoyment of PE, representative 1999 Sample of PAIs 11-ltem PA subgroups. Enjoyment of PA was use of afternoon sample. Education Glr1s and Index, sign if. In 5 of 6 subsgroups. lime and family high with primarily Boys In demographic, child Perception of general barriers support are white and black. Grades4 psychological and contributed to model for glris 10-12 associated with Through 12. biological grades. Social variables slgnlf. In all children's PA. variables, social models except girls 7-9 grades. (family and peer) Social variables explained 1-17% of variables, and variance. Family supports was sign "hysical In all subgroups. Parents paying fees environmental for PA high partial carr. Boy 7-9 characteristics. grades and 10 grades. MR separate for 6 age-sex subgroups =

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-----------------..----.. ------------------. -----Evidence Tables (Cont.) Author, Title Sampling N; age; Results Conduslon Problems: Ioumal _ measurements % ot variance explain 18% tor boys In 4-6 and 59% for gk1s In 10.12. Positive assoc. = afternoon for sports and PA, enjoyment of PE, family support. Crespo, Race NHANES n=9488; adults 20 Between NHANES II and Ill there 22% of Amerlean No data on duration CJ, IEthnlclty, Ill years and older, was an Increase from 25% to 33% of conunue to be of PA. Survey Archives Social Class (between lyJM and overweight adults between 20.7 4 Inactive or formal of and Their 1988and frequency of years of ages. Note: BP and blood Irregularly active Comprehensive. In lema I RelaUon to 1991) physically active cholesterol levels decreased 27% to (34%) during their Home Interview. Medicine, Physical were hobbles, sports 20% and 39% to 24%, respectively. leisure time. Rates Limit to specific ....... 1998 Inactivity home and exercise. 22% reported no L TPA; rate was of lnac:tlvlty are questions possibly 1\) During Inter-higher In women (27%) ll'lan men greater for woman, not culturally 01 Leisure viewed ( 17% ). Mexican American men and older persons, appropriate. lime women reported highest prevalence blacks, and MA. of no L TPA. Mex. Am women had highest at 46%. N. age, decrease LTPA. CDC, Nelghbomo 1998 N=12,767 Those wlll'l more ll'lan high school Persons who Ethic dlft'erences MMWR, od safety BRFSSin QuesUonnalre r/t education, little difference In physical perceive their were "white and 1999 and Pre-Maryland, to PA and safety Inactivity who perceived neighborhood to be other". Numbers too valence of Montana, neighborhood unsafe and safe unsafe were more small (ethnic) for Physical Ohio, (24.5% and 23% respectively). likely to be meaningful analysis. Inactivity-Penn., Those older than 65 associated physically Inactive. Only 5 states, self Selected and lower levels of safety with activity report, and States, VIrginia. (more active if more safe). unmeasured 1996. BRFSS Prevalence of physical Inactivity confoundk\g factors telephone among men and women (women > (e.g., social and survey on men) differed across neighborhood demographic PA safety levels among person aged 18 factors). 84 but not among persons > 65. In conjunction with previous data, physical Inactivity highest among >65, woman, minorities, high school

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' I L I ----------------Evidence Tables (Cont.) Author, Tille Sampling N;age; Results Conclusion (oumal measurements education or less and Income <20,000. CDC, Monthly Population 18 years and older 29.4% of adults reported no leisure One third of adults In MMWR, Estimates of based were asked lime PA. Inactivity highest In Jan US report no leisure 1997 Leisurerandom : questions about (35.3%) and lowest In June (24.7%). time PA and rates of Time telephone Whether they Seasonal patterns consistent for both lnac:tiYity have been Physical survey of participated In sexes, all age, mlnotity status and higher In Jan than In Inactivity us exercise, region of residence. VIU'Ied by north June. Seasonal United populated raereaUon, or PA vs. south. Higher Inactivity during patterns In Slates, other than their winter and lower during summer. prevalence Of 1994. regular Job duties reported leisure time during past month. PA. Monthly rates of _.... Inactivity higher and 1\) 0') more stable among older persona, Hispanic' and residents of southern states Norman Parental and Cross-.,.. graders from Boys reported more PA than girls By serving as Ander peer sectional. Norway, aged 13.3 p.001. Gender dltf on reported models and ssen lnftuences +-.30 years n=904 activity of best friend, p.OS, direct supporter, slgnlf. Research on leisure(498 boys, 406 support for fitness-related IICerclse others have an Quarterly time girls); 90 minute from father .05 and direct support to Important Impact In for physical confidential exercise vlg from parents 05. All promoting PAIn Exercise activity In questionnaire >for boys vs. girls. Rs boys= direct young adolescents. Blld young administered In help from pamet In ex vlg, PA level of Sport, adolescents schools. All self best friend and support In ex vlg from 1992 reporting. parents. Girls= direct help In ex vlg Measurement r/lto and PA of beat friend. 3 of 4 lnftuences on adol predictors (direct help In ex vlg, PA of PA1) perceived sign others, direct support for PA leisure lime PA of from slgnif. others, not value of PA of parents and best sign others) explained 14% for boys friend, 2) and 18'Yo for girls. perceived direct Problems: strengths Confounded by social, demographic and climatic raetors. Cultural differences, self-f'eport data, student perception may not be accurate.

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0 3 l. ) ) l. ;: :r ---------------------------) ...... N ........ Evidence Tables (Cont.) Author, Title Sampling N; age; Results Conclusion Problems; journal measurements Freed son PS Research Quarterly for Exercise and Sport, Vol.62, no4, p.384-389 1991 Familial Aggreg ation In Physical Activity Parent and children volunteer. 1) Examine stability and con sistency of Caltrac accelero meter and activity record to assess physical activity In children and adults 2) detennlne Is there is relation ship between parents and their support for PA from parents and friends 3) direct help from parents In exercising vigorously 4) perceived value of PA of parents and friends. n=30 5-9 year-old children and biological parents; Caltrac wom for 3 consecutive days (one weekend day) with activity record completed by parents for both themselves and their children. Experiment 1: No differences between counts/per day and minutes of light activity and activity across day for any family member. Correlation between day for counts were+ for parents (r-.73 to .87 p<.001) and children (r-.38 to .79 p<.001) and min of light activity and acUvlty were .67 .91 p<.OS for parents and .36 to .72 p<.05 for children. Two methods of assessment sign. carr for both parents and children r-.30, -.47 and .39 (p. <.05) between counts and light act/act and counts and act .32, .50 and .. 35 p<.05 Children counts were 68% higher than parents but not as consistent across days as parents. Experiment 2:Counts between father and chOd occurred In 67% of sample which approached sign. Low activity fathers with high act. child was 13% and high father and low child was 20%. CAL REC (low act/act) occurred In 70% of father child sample and was sign. 28% of Largest proportion of Inactive children are In families where neither parents Is active and If both parents were In high act category (93%) of children were high act. Family aggregation In PA occurred In 67% of fathers and 73%of mothers when sorted by cal count compared to 70% of fathers and 66% of mother when sorted by CALREC. Low active parents are more likely to have low active children. Suggests more Influential modeling behavior r/t Inactivity versus activity. Influence of Activity record completed by parents required child to recall activity during school time (recess etc) Three days of PA measurement. No description of ethnic or SES status of famHfes which contributes to profile of families and Individuals. Caltrac may not pick up acllvlt/es performed In nonvertlcal plane as well as Intense activity. Small sample size. Mom AND dads Included.

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----------------------------------------.... ..... 1\) (X) Evidence Tables
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Tables (Cont.} Alllhor, Title Sampling N;age; Results Conclusion Problems; toumat measurements strengths Pate, RR, Tracking of Followed 47 children (22 Con'etatlon of yat 1D y .. PA Physical activity PA doesn't appear Medicine physical over3 males and 25 measures. Yurly r.tiles were tracks during early to change durfngthls Science ldlvlty In year females) 3-4 created and examk'lld for % chHdhood from 3-4 developmental Sport young period YDIT. Heart rate agreement and CGhtn's kappa. yam to 8-8 years. stage. 3-3 p.m. time Exercise, children by telemetry 2-4 Repeated miUUriS AHOVA to lllmitlng. Perhaps 1996 days per year examine lnlradlst can'llatlon across l'ull day monitoring during p.m. 3 ye111. Spunnln rank .57 to .86 and accounting for when heart rate (p<.OO). % agreement ranged from level and amount of was 50% or more 49% to 62%. lntrldns R far 3 ye111 PA. Check ethnic above RHR. was .81. and SES dlff..,ces, Time of y .. and rac:Nitment methods ...a. canfaundlng results I\) co Whitaker, Pradldlng HMO In n-854 Aged-21 (young adulthood) Obese children 94% were white New obesity In Washing Hllwt medical 79% far 10.14 yr. aids with at least under 3 yr. without 84%r.male England young ton rwcords one obese patW1t n 8% ror 1 obese parents .. 93% bam to manied Joumll of 8dulthood BMI year aids without obese parents. It low rtsk far adult mothers Medicine, from >8 5" % for age obesity but risk Ladt of precision of 1997 childhood and sex lnaeases with age measurement since of child. When oblakled from parents are obese medical records. both obese and non-abase kids are 2x risk of adult obesity. Rosner, % nes for 9 n:a68,772 BMI t with age and t glr1s vs. boys. Bays t:!lm!l& Sample of ethic TheJml BMIIn US epldamlol 5-17years groups Is small as of children 5-ogle 51% bays (8 yr.)17.5 +-2.9 compared to while Pediatrics 17years studies 28% black 16.8 +.2 (adequate) 1998 (NHANES 7.5%Hispanlc (9 yr.)18.2 +.8 % ites of ethnic and II, Ill and 2.5% Asian 17.5 2.7 age and sex Is others) 62%white (10 yr.)18.5 3.4 comprehensive 18.3 3.1 Helps to classify Glr1s degree of

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...... w 0 Evidence Tables (ContJ Author, Title Sampling N; age; Results Conclusion Problems; Joumal measurements strengths McMur-Parental 18 elem. n = 1253 families ray, lnftuences N Carolina 34111 graders Research on Involved in ht/submaxlhr/ Ortly for Childhood CHIC EBBS (parent Ex and Fitness and study attitude) /self Sport, activity report PA child 1993 patterns Parents exercise habits not associated with children's. Little associate of parents' attitudes of exercise and their children's V02 Mother's ex habits weakly assoc. with girls. (8 yr.)17.6 3.1 18.8 2.5 (9 yr.)18.1 3.5 17.3 2.9 (10 yr.)19.1 3.8 18.2 3.2 Parental exercise habits are not associated with children's activity habits or aerobic power. Mothers' sign + attitude and V02 of child and not fathers. Factors other than parental attitudes and exercise habits are more lnftuentlal In determining fitness and activity levels of children. overweight and obesity. Useful for relative ranking but not necessarily used to established new norms but rather to observe trends. 82% white, 14%AA and 4%other 70% mothers Only 1 parent was asked to respond to questionnaire EBBS measure attitude Children's PAwas self report Parent's PA was 6 month recall of partlc;ipatlonlastlng 20.30 minutes,

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------------Evidence Tables (Cont.} Author, Title Sampling N;age; Results Conclusion Problems; Journal measurements strengths Trost, Correlates 4So. n=198 mean age All75 min/day MPA Girls self etf as Comprehensive American of Carolina 11.4 years m"MPA slgnlf. predictor of range of Jrl objectively middle 55.1%AA No dlff. In VPA dally VPA, PA self psychosocial Preventlv measured schools CSA, determinants Boys sports teams efficacy, social determinants and 8 PAin = Boysself-eff mom's PA, comm. PA norms regarding environmental Medicine, preadol Psychosocial and org corr VPA .. MPA= social PA, beliefs about variables 1999 youth Environmental norms, percep of dad's actl, comm. PA outcomes and 7 day monitoring Demographic PAand org PA Involvement In with accelerometer Glrfs. Self-etf belief PA outcomes + community based AA and white, no corr VPA MPA =self-elf, beliefs re PA organization Hispanic outcome/access to sprt eq. + corr to were slgnif. Age may be more MPA correlated to adolescent than objectively preadol, No measured PAIn 6111 measurement of ....lo. grade students developmental w Findings consistent staging ....lo. with self-report PA. No SES Information of sample. Sallis, Aggregation San Diego n= 197 families Anglo= energy ex. + carr siblings and PA habits are Middle class families Journal of of Physical Family 95 Anglo, 58 dads mother-older child moderately (Hollingshead) Anglo Behavior Activity Health and 87 moms, 104 Hard leisure moms + corr both aggregated within middle-class and al Habits In Project kids (old/young) children. No father lnft. families, possibly Mex lower end of Medicine, Mex-Am and 102 Mex-Amer, 42 Max= lntrafamil carr higher higher In Max. distribution 1988 Anglo dads, 102 moms, Energy ex + fathers and older There are other Effects of single vs. families 143 kids children and moms both and sibling forces operating dual parents? 5111 and 6th graders BMI no Important effects In Mex or concurrently. Effects of multiple PA=7day PAR Anglo Parents affects children In family? BMI seen more In older No sex differences children measured Families Is an Ethnic differences Important due to SES? socializing agent Pausing subjective regarding PA. measure.

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--------------------------w 1\) Evidence Tables (Cont.) Author, Title Sampling N; age; Results Conclusion Problems; tournai measurements ___ _!_lrengths Reynolds Preventive Medicine, 1990 Robinson PsychoSocial Predictors of PAin Adolescents Ethnic and Journal of gender Health differences Ed,1995 In rll betweenlV viewing an obesity, PA and dietary fat Intake Stanford Adoles cent Heart Health program Calif. Schoof based si\Jdy Intervenetlon to decrease cvo n= 388 males, 355 females 10" Questionnaire from SAHHP Intention, self-eff, social ln-ftuence, stress, PA self. report n=1912 9" graders; Self report of lV, ethnlclty, 2 quesUons r/l PA, dietary fat modllled from NHANES II, BMI Females: setf-eff and lntenUon r/t PA at 16 mos. 28% of variance explained by baseRne ac:tlvlty, self efftcacy, Intention, slress, social lnftuence. Males: 24% of variance explained above variables "TV viewing and dietary tat Intake (r-.23 (p< .0001) B & G: Boys TV vs. girls, with M girts highest. Boys t PA and eaUng ftat foods Ethnic: M= 1' TV, t PA and t fat foods. Whites :ofowest TV and 2"' PA. Among boys M and Hlsp t BMI. Among girts His t than whites. B and G M and Hlsp greatest BMis. lV weakly assoc. with BMI and PA. Consistent associations, Intention and salt emcacywere assoc;lated with adolescent PA. TV viewing Is associated wtth Increased dietary fat Intake In both boys and girts and across enUre sam pie. Boys reported mora TV viewing among M girts. Boys reported more PA and eating high fat foods than girls. M and Hispanics greatest BMI. Weekly hours of TV weakly assoc. with BMI. White boys had slgnlt. Assoc. between lV and BMI. Gender and ethnic associations suggest cultural factors may lnftu ence risk of child ren and adol to effects of TV viewing. PA was list of 19 activities to be scales for frequency. All sports related. Part of larger si\Jdy. Measurements all self report Ninth graders pose differing barriers and patterns of behavior than children.

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------------------------.. .......... ----.. -------------------... ------------------------------------------Evidence Tables (Cont.) Author, Title Sampling N; age; Results Conclusion Problems; journal measurements ... sl[engths Klmleclk, Parental Using N=60familles Parents i perception of child's Parents' beliefs Self report PA JC, beliefs and Family 5-1011 grade (11-15 physical competence Involved In children These are not Research children's Influence yr. 1)161tem fitness Parents run Is reason for child MVPA. Mom s and dad children but rather Qrtly for mod tovlg Model value scale (parents to participate different reason for adolescents. Ex and PA value participation In Moms and dads similar r/t wanting child to Middle to high SES Sport, mod-vlg PA for athletic competence and value participate. Mothers white 1998 children 2) athletic attached to chHd's were sign. source of Role modeling Is not competence Parent participation. Differed on Influence via their expected to perception of reason why they want child to beliefs about child Influence this children 3)TEOSO participate physical competence sample. -success 4) 33 Item Parents belief r/t to child's and adoption of task reason for child MVPA goal orientation. No participation In Mothers emphasized reasons support In role modeling ...... ntness program for child PA greater extent than found (Mom and Dads w w 5) parent PA-self dads PA not sign corr to report (vlg-mod) children's PA). 6) child self-report Gordon Adolescent Nationally >14,000 us BMI > AA E (39.4%) and Activity and Inactivity Self report but direct larsen P. Physical representadolescents. Grades Hispanic males {30.2%) and E patterns differ by Interview. Journal of Activity and aUve 7-121n US Wave 2 (29.8o/o).lowest for Asian E ethnlclty with minority Pediatrics Inactivity sample of large (n=20,000) (11.1%). Cuban E (37.8%) and groups engaging In less 1999 Vary by from 1996 N for this study was Puerto Rican males (34.1"/a). PA and more Inactivity Ethnlclty: National 13,157, BMI, PA by Inactivity: Greatest for AA than their while National longltud-questionnaire and males and E and lowest for counterparts (excepts longitudinal Ina! Study categorized as low, white males and E. Hispanic Asian females who Study of of Adoles mod or vlg. Physical males and E 2nd In # of have low PA, Inactivity Adolescent cent Inactivity by Inactivity hours spent In TV etc. end overweight). Health. Health of questionnaire and PA: 33.2% of adolescent Hispanics and Back do categorized as low, reported 5 or more episodes of not get sufficient PA med or high., age mod to vlg PA/week. Small dlff. and spend more time and ethnlclty by self among all males. Ethnic watching TV and have report. differences greater for E with higher overall Inactivity while E > then minority E levels than whites. Black, Asian, and Hispanic E engaged In 2 or fewer bouts of mod to vlg, PA age,

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APPENDIX 8 SURVEY INSTRUMENTS 134

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Socioeconomic Status Questionnaire LD. ----Family ID -----Name _______ Date ____ I. Date ofbirth __ ___:..1 __ _,1'----2. Ethnicity: (please circle one) A) Asian B) African American C) Hispanic D) Caucasian E) Other 3. Relationship to the child (please circle one) A) Mother/Father B) Stepmother/Stepfather C) Other (e.g. relative) 4. Are you biologically related to your child? (please circle one) 5. How many adults live in the same home as your child? (please identifjr them) 6. Number of children in the family? (please circle one) A) 1 B)2 C)3 0)4 E)S F)6 G)7 H) more than 7 7. Birth order of the child involved in this project? A)oldest B)2"" oldest C)3rd oldest 0)4"' oldest E)other 8. How many daughters_ and sons _do you have? (please place a number in each blank) 9. How long have you lived at your current address? -------10. Do you plan on moving in the near future? (please circJe one) A) Yes B) No lfyes. when? _______ I 1. How many years of education have you completed? -------12. Are you currently employed? (please circle one) A) No B) Yes Ifyes. whattypeofemployment? ____________ Are you currently in school? A) No B) Yes 13. Current height-------14. Current address: Current weight------15. Phone Number Work Home ------------------THANK YOU !!! 135

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Family Environment Scale FAMILY ENVIRONMENT SCALE There are 63 statements in this booklet. They are about families. You are to decide which of these statements an true of your family and which are false by circling either the "T' for True or "F" for False that is to the right of the statement. I you think the statement is True or mostly True of your family circle "T" if you think that the statement is False or mostly Fa/s( of your family, circle the "F". You may feel that some of the statements are true for some family members and false for others. Mark "T" if the statemen is true for most members. Mark "F". if the statement is false fo most members. If the members are evenly divided, decide wha is the stronger overall impression and answer accordingly. Remember, we would like to know what your family seems like t you. So do not try to figure out how other members see you family, but do give us your general impression of your family to each statement. 136

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Family members really help and support one another. ;). We fight a lot in our family. ..3. We don't do things on our own very often in our family. +. We feel it is important to be the best at whatever you do. S. We spend most weekends and evenings at home. (, Activities in our family are pretty carefully planned. :} Family members are rarely ordered around. We often seem to be killing time at home. 'j Family members rarely become openly angry. I 0. In our family, we are strongly encouraged to be independent. I 1. Getting ahead in life is very important in our family. I 2. Friends often come over for dinner or to visit. f3. We are generally very neat and orderly. t4. There are very few rules to follow in our family. /5. We put a lot of energy into what we do at home. /6. 7. JB. /9. d-0. Family member sometimes get so angry they throw things. We think things out for ourselves in our family. How much money a person makes is not very important to us. Nobody in our family is active in sports, Little League. bowling, etc. It's often hard to find things when you need them in our household. a-.1. There is one family member who makes most of the decisions. There is a feeling of togetherness in our family. 137 T T T T T T T T T T T T T T T T T T T T T T F F F F F F F F F F F F F F F F F F F F F F

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23. Family members hardly ever lose their tempers. T F 24. We come and go as we want to in our family. T F 25. We believe in competition and "may the best win". T F 26. We often go to movies, sports events, camping, etc T F 27. Being on time is very important in our family. T F 28. There are set ways of doing things at home. T F 29. We rarely volunteer when something has to be done T F at home. 30. Family members often criticize each other .. T F 3,. There is very little privacy in our family. T F 32. We always strive to do things just a little better the T F next time. 33. Everyone in our family has a hobby or two. T F 34. People change their minds often in our family. T F 35. There is strong emphasis on following rules in our T F family. 36. Family members really back each other up. T F 37. Family members sometimes hit each other. T F 38. Family members almost always rely on themselves T F when a problem comes up. 39. Family members rarely worry about job promotions, T F school grades, etc. 40. Family members are not very involved in recreational T F activities outside work or school. 41. Family member make sure their rooms are neat. T F 42. Everyone has an equal say in family decisions. T F 43. There is very little group spirit in our family. T F 44. If there's a disagreement in our family, we try hard T F to smooth things over and keep the peace. 138

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45. Family members strongly encourage eacch other to stand up for their rights. 46. In our family, we don't try that hard to ssucceed. 4 7. Family members sometimes attend courl"ses or take lessons for some hobby or interest ( (outside of school). 48. Each person's duties are clearly defirined in our family. 49. We can do whatever we want to in our 1 family. 50. We really get along well with each other:r. 51 Family members often try to one-up or c out-do each other. 52. It's hard to be by yourself withaout hurting someone's feelings in our household. 53. "Work before play" is the rule in our fanmily. 54. Family members go out a lot. 55. Money is not handled very carefully in cour family. 56. Rules are pretty inflexible in our househnold. 57. There is plenty of time and attention for r everyone in our family. 58. In our family, we believe you don't evear get anywhere. by raising your voice. 59. We are not really encouraged to up for ourselves in our family. 60. Family members are often compared willith others as to how well they are doing at work or !i school. 61. Our main form of entertainment is watcching T.V. or listening to the radio. 62. Dishes are usually done immediately af'fter eating. 63. You can't get away with much in our flfamily. 139 T T T T T T T T T T T T T T T T T T T F F F F F F F F F F F F F F F F F F F

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i i r i I I i I J I I I I I I I I I I I I I I I I I J I I I I I i l I I I i I I I i I I I I I I Harter Scale W'hat I Am Like N:une Age Birthday Male or Female (circle which) SAlMPLE SENTENCE Really Sort of True True for aac for me (a) 0 0 SoiiiC kids vrou14 rather play Other kids ..vllld Rlhcr OlltlloorE in spaEe cima:BUT watcbT.V. 0 0 Otha kids 'WO"J' hour wbetbcr I. Soule J.id.r feeJ IMt lfley .ue vay good t their" school BUT U1ey CUI do the school work work.. lolhem. 2. 0 0 Some kids W.d it hard lo Btrr Other kids Cmd it'c pretty easy lllake fiiend$ to m.kc 6ieads. (9 0 0 Some kids do -lltt Btrr Ot.ber kids don't fed dlat they II kinds afapons uc W'Y coocl when it comes lospons. 4. 0 0 Some lcids 8l'e htrpp}' BUT Other kicls happy with abe way they look lhe w.y they s. 0 0 Some Lids ll'C/urppy Btn' Other kids ere not happy with the way they behne !be 'lofty they behave. 6. 0 0 Some lcids ll'C often BUT Ocha-kids ere prdly wolsoppywilla themselves pletaedwidt lhctasel\'OS. 7. 0 0 Same kids feel \ike \hey au-e BUT Other kids an:n 't so uejiat ta Slrlllrt as oCher WVflder iflhc:y -" kids their -ce usman. I. 0 0 Some kids b.t....: a lot of BUT Other kids don 't have very .fiiends a:sany meads. (,) 0 0 Some kids Wish !.bey coulai BUI" Other kicis feel dtey are be lot at spx1S &ood mou&h at sports. 10. 0 0 Some L:icls ace happy with 1 BUI" Otherkids wisb tbeir height tbcir bei&ht and vwci&bt or wci&ht wue diflcrent. ll. 0 0 Some kids usually do the BUT Other kids often dan 'I the right thing do the right thing. 140 Sort of Ru.Uy True Tne forme forme 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

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I I 1 l i l I I I I I RuDy Sortor Sortor Reali I [ True True Tne Tl"'l I forme for me forme far 111 l 12. D 0 Some kids t/Qn 't like the way BUT Other kids t/Q like che way 0 0 I I lhey are le.HUag their lire they are leadiag their life.. I 13. 0 0 Some kids are pRtty siGw BUT OdM::r kids c:m cfo cheir 0 0 I in fiDishing their school work : school work quickly. l 14. 0 0 Some kids would like to BUT Ocher kids as IDliDY D 0 have a lor mon: fiicnds fiieocfs as they waal. I @ 0 0 Some kids dWI1: they could doo Btrr' Other Lids are afiaid lhC)' 0 0 wcU at just about aay 11cw spoats might tUJ{ do well at sports activity they lricd bcflf'ore they au tried. 16. 0 0 Some kids wish their body sur OCher kids like lheic bocf} 0 D was different the way il is. 17. 0 D Some kids usaally ace the Btrr' Other kids Jon 't ad 0 D w.y they bow they are the way they are supposed co. Sllpposed to. II. 0 0 Some kids ue htzppy with sur Other kids an:; ol\ea. not 0 0 lhcmsclvcs as a pen011 happy with themselves. 19. 0 D Soaae kids o&a.forxet what BVT Other kids c:m remember D 0 what dley team thiDI$ 20. D D Some kids arc ahftys doing BVT Olhcr kids usuaUy do 0 0 things with aloe of Lids dUnes by 0 0 Some kids feel tbat they an: sur Othc:r kids don't feel they 0 0 better dim others their age c:an play as well. at spans 22. 0 0 Some kids wish lbeir BUT Otha-kids like lhcic physical 0 0 appcarmc:e (how they look) appearaDOC the way it is. was different. 23. 0 0 Some lcids usually get in trouuhle BUT Other kids usuaUy Jon 't do lhings 0 D becaliSC ofthiqs they do !hat &et them in trouble. 24. 0 0 lcids like the kind of sur Otbc:r kids often wish they 0 D penon lhc:y I1'C ,overc comeone else. 2S. 0 0 Some lcids cfo wry v-el/ al sur Othttkids don't do very well 0 D lheir dasswock. at dteir dassworic. 26. 0 0 Some ltids wish that more sur Other kids feel that most people 0 c people their age liked them their age do like 141

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I I r I I I r I I I I I I I Really Sortor Sort or Reali> True True True Tnae forme forme forme forme i @ 0 0 [D games ancf sports some BUT Olhc:r lcids usually play nlber 0 0 kids usuaUy watch instead !han just w.lch. of play 28. 0 0 Some Lids wish 'omcthing Btrr Other kids /ike dlcir face and 0 0 about their face or hair hair cbe way they lfC. looked diffcn:nL I 29. 0 0 Some kids do tbiogs they BUT Other lcids lrtzrdly do things 0 0 I know they shouldn't cfo lhcy know they shouldn't do. I 30. 0 0 Some Lids .-c BUT Other kids wish .D 0 i being the way they arc dilforent. I 0 0 D 0 I 31. Some Lids have trouble Btrr Other lcids almost alwayr can i tiguriag out the answas liUR out the mswers. l in school l I 32. 0 0 Some kids arc popular with BUT Other kids arc nor vay D 0 i others their age popular. r l 0 D 0 0 0 : Some kids don't do wdl BUT Olbcr kids IIR good al at new outdoor games right away. 34. D D Some kids lhiDk that they BUT Olba-kids thiak that they 0 0 IR good (oalciag aRnot looking. 35. 0 0 Some kids lhcmsclvcs:s BUT Other kids oftCD find it hard D 0 vayweU to bchlvc themsd\U. 36. 0 D Some kids are not vt:ry Upp)'IY BUT Otbr:r kids think the way D 0 with the way they do a lot they do thiags is .fine. ofthiags. Susan Hatter, Ph.D., University ofDcnver, 1991 142

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Prioritization Questionnaire PRIORITIZATION QUESTIONNAIRE Date Subject No. Mocha-Father --Other Age of child __ M I. Can you tell me whlll physical adivity mamsto you? 2. As part of your daily/weddy routine, whlll kinds of physica I adivity do you do7 J. Do you think physical adivity is impmt111t far you? (circle one) Foryourchildrm? (cirdeane) WI-lY is it impmtlnt lOr you WilY is it important far your dlillhn7 4. Compared to other adults of your same age 111d sex, how physically IIClive Ire you? ( cirde ane) .S. How many times during the piSt wa did you mgqe in Ill ldivity thlt made your hart bat rut, mldc: you breathe hlrd. 111d caused you to -17 llow long did thltldivily last? 6. Do you set aside time, in your normal routine, to engage in ph)'3icallldivity for yowsell'1 In OCha-words. do you forego utha-!asks or ldivities to make time lOr physical activily7 (Circle one) (lfparmt111swas YES) C.. you tell me how you do lhal? (lfparmtlllSMD NO] Cln you tell me more about why not? 143 Parmi y N Child y N p c Aloe more A little more A little less A lot less Average NIA Days Minutes y N y N ---F

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Now. lhink about your d1ild, Can you td me if time is set aside for him/her to J*licipate in physia activity1 (circle one) (If parent answers YES) Can you tell me how that happns? I I (If parent answers NO] Can you tell me more about why that may not happal for 7 7. Please rank lhese itans acxording to how impor1ant they are to you: ___ being financially suca:ssful ___ being healthy/not being sick ___ doing well at work ___ enjoying leisure time ___ havins a good &mily life ___ having a good 3pirituallife ___ having good friendships I. WhCR does being physically active fit into this list? y N y N PA Pannt Child 9. Consider your responsibilities and ta3b in a typial day. Now think to yourself about those responsibiliticsftasb that you consider your highest priority in a given day and think to yourself about those responsibilitiesftasks that are your lowest priority. REALISTICALLY, whae might physical activity lit into this scale for you in a typical day1 highest ----------------------------------------priority lowest priority For ldwikl) 7 lowest priority highest ----------------------------------------priority 144

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APPENDIX C 145

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Introductory Letter to Parents September __ 1999 Dear----------Parents, I am a doctoral student in the program of Health and Behavior Sciences at the University of Colorado at Denver. I am beginning an approved research project at Colorado Springs School measuring physical activity in families. My interest pertains to family influences upon children's activity patterns and its relationship to the prevention of childhood obesity. I have had the fortunate experience to gather data in a similar school in _____ investigating parent influences upon children's eating behaviors. My proposal includes measuring children's and parent's energy expenditure over seven days using a device called an accelerometer. I am requesting parents and children (grades 3rd through 5th) to wear the monitor around their waists for seven days. The monitor is very small (1 "X 2" and 1.5 ounces) and will record all of your movement. The measurements are recorded on a small computer chip within the sensor and nothing is emitted from the monitor. There is no hann or discomfort in wearing the monitor. If you fmish the seven-day activity measurement and you return the sensor, you will receive $20.00 per parent and an additional $20 in recreation equipment or cash for each child who participates. Your participation is entirely voluntary. I would like to meet with the children and parents at school possibly before or after school or during non-academic times as to not interrupt the functions of _____ School. We also can come to your home if you prefer. A short 10-item questionnaire is included in the study that asks your opinions and thoughts about physical activity, a survey concerning family environment, height and weight and specific questions relating to children's perception of athletic competence. We will start this project in September and gather data for approximately 5-7 weeks during the 1999 fall semester. If you are interested in participating. will you please drop the enclosed card in the mail so that I may contact you. Thank you for your interest and help in understanding and improving the health and fitness of children who attend school Please feel to call or write should you have any questions. Sincerely, Mary J. Barry University of Colorado at Denver Phone: Address: 146

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Guidelines for Prioritization Questionnaire Guidelines for Prioritization Questionnaire Hello, my name is and I'm here to ask you your opinions and thoughts about physical activity for yourself and your child. There are no right or wrong answers. We are only interested in what you think. All information is confidential. 1. Can you tell me what P A (physical activity) means to YOU? After parent answers question, you can then repeat back his/her answers and ask if they can think of any other thoughts about what P A means to them. This technique can be used in subsequent questions in order to prompt responders. Do not change wording of questions that would possibly change the intent of the proposed question. 2. Ask as written 3. Ask as written 4. Suggestion if needed: Compared to other (men or women) of your same age or you more or less active? Wait for response. If respondent answers "more", then follow with a lot more, a little more, average or N/A. If respondent answers "less", then follow with a lot less, a little less, average or N/A. 5. May need to clarify vigorous activity without using the tenn ''vigorous". The minutes should reflect the average amount of time parent engages in activity that reflects question e.g. heart beat fast, breathe hard, and sweating. 6. This question is intended to elicit information about setting aside specific time for physical activity and how parents go about doing that for themselves and their children. If they respond "no" it is imperative that the question is asked without a "blaming" tone such as "can you tell me about why not" or "how come?'' 7. Suggestion: "This is a list of7 values listed in alphabetical order. Can you arrange them in order of importance to you? Number #1 will be the most important value and 7 the least. Sometimes it is difficult to choose between some of these values. Do the best that you can. Thank you! 8. Ask as written 9. Ask parent to make a mark on the I 00 mrn visual analog scale where PA may fit into this scale for them on a typical day? Repeat question for child? 147

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Information for Accelerometers DEAR PARENTS: Thank you for agrftiag to let your cbDd wear the CSA Monitor for the oat 7 days. Your child'1 activity patttnl will help us uaderstud bow pbysicaUy active aormal, healthy childrea aR on a daBy buis. If you bave any question at any time pleue call Mary J. Barry at 719-633-0499 or 719-651-5400. RULES FOR WEARING THE MONITOR 1. Each morning (after bathing) fastea the belt and attached moaitor around your chDd'1 waist beneath the clothing or over dothiag. It's O.K. if you child wean the belt over aadenvear. 2. War the monitor with the black arrow pointing up. 3. Keep it oa during aD wakiag boun. 4. DO NOT GET IT WEn Take if ofl'to bathe or shower. 5. Just before bedtime, put it iD a we place for the a.ight. 6. Place a remiuder somewhere to hdp you remember to put the monitor on your cbOd eada moruiag. 7. Your cbDd wiD receive SlO worth of physical activity equip meat that brlsbe can cboose from after be/she wears the monitor for the FUU. 7 days. 8. D'you decided you don't waat your cbild to keep wariag the monitor anytime dariag the tft'ea days, please caD Mary Barry at 315-0306 aad leave a message. The moaitor wiD be picked up. 9. Ketura the belt and moaitor to Mary Bany at designated time and place whea the 7 dafl are rmished. 10. Your child wiD receive his/her gift at the moaitor retam time. YOU AGAIN FOR YOUR SUPPORT!!! WE ARE ALL WORKING TOGE'I'HER TO HELP OUR CHILDREN STAY HEALTHY! 148

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I I I I I I I I l I I I I I I I I I i I I I I I i i I I I I I I I i I I i i I I i i I 7 Day Monitoring Record 7 Day Monitor Record Please shade in the times that the activity monitor was ON During the times the monitor was OFF, please indicate what you were doing and the time the monitor was OFF Please mark the times spent cycling or weight lifting and leave the monitor on. If you swim, remove monitor and mark time spent swimming. Day Day 1 Day2 Day3 Day4 DayS Days Day7 M 1a.m. 1a.m-2 2a.m.-3 3a.m-4 4a.m-5 Sa.m-6 6a.m.-7 7a.m.-8 Sa.m.-9 9a.m.-10 10a.m.-11 I 11a.m.-12 N-1p.m. 1p.m.-2 2p.m.-3 3.pm.-4 I 4pm.-5 Sp.m.-6 6p.m.-7 7p.m.-8 Sp.m.-9 I 9p.m.-10 10p.m.-11 11p.m.-M I Swim? Cycle? Wt.Ufting? 149

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APPENDIX D 150

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I I I i I I I I l I I I I I I Parent Consent University of Colorado at Denver Human Researc:h Family la.Oueace Upoa Qildrea'a PhJ'Iiul Adhity Priacipallaftstiptor. {Maql. BuryJ SUBmC'I' CONSENT Project Description Your child is beiag asked to take part i.a a m.dy to measure elementary school-aged children's ph)'licalldivity levels. Your child was cboseD beawse belsbc is a typical healthy elemeotaryaaed lbldeat. This .mcly. to measure cbildreo's physicalactM.tJ levels, is important because physical activity is a vital patt of dlildren's health, and these activity measures can show it childi'ca ., ac:tivity lewis are changing ovcc time. This lbldy requin:s that your cb.iJd wear a amal.l motion acasor (approxim8tely I" X 2" iD size, I ,S ouaces) oa a belt &n:IUIId bWba-waist durias walciag hours fOr seven c;onsec:utive clays. The motioa aeasor will record all of your cbild"a movaneat. This coasem form is to get your 8P(KOval for you child's participation in this study. It is voluntuy; the ICbool does not RqWre your dilld's participation. Proc:ediii'IS lfyau ..-ao let your cbild tab part in this study. you will be asked to do the foUowiDg: l. lip die Colllcat .bm 2. receive iDstluctioa on bow the moaitor works 3. help ,aarc:llild war the moaitor for leWD days 4. t'dlft die moaitor to fhe project cDcinliDitor It the:ead of seven days Your child will be asked to do the foUowins: I. .......-abe IIIODitor d.uriug all WllciDg hoUri for aevea daya. Discoad'o1111aad RIIU The modoa.leDSOr may be noticeable to the cbild wbile wearing it but there should be no pbyliCII cliscomtort due to IDIIll size aad weight. Thc:re may be possible irritation caused by coatact 'With the lkiD. embarnssmeut in waring the device. aad felliag uncomfortable with a.nsweriDg questions coacc:miag their pe:rcciwd athletic competeacc. Tbe IDOtion sensor poses no fJarm to tbe c:llild. MCJ\Ialleat measures arc recorded on a small computer chip within the seasor; DOtbiDg is emitted from. the seosor. You and your dlild will receive ao direct benefit fi:om this audy. 1be ODiy perceived risk is u aoted above-awareness of Uld 8JIDO)'UI(lC with weariDg the motion &eDSOr BeaditJ Non-Tiretapeut!c Sfudies You will m:eive no direct benefit from participating in this research study. You will receive paymem for your participation and the fiadiass of this study will increase our uaderstandiog of different ethnic and socioeconomic groups and their relative differences wit respect to how parents value, panicipate and prioritize physical activity. Initials 151

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I i I i I i I I j I I 1 I I I I I I I I I I i J I I I I I Solll'Ce of'Faadiag AU .6lndiDg for this uuc!y will be provided by The Ceater for Disease Corutol!Pby,ical Activity and Hcaltll Branch. eosi to SabJeet There are ao QOSfS to you or your cbild lor beiDs izJ this rtudy. If your dilld finisbes the .sevenday actMty measumnad.md you rdunl the motion ICIISOr. your child will ceceivc a cboioe of varied sports equipmeut Wlued at $20.00 SubJect PaJIIlcat Your c:bild wiU be paid up to $20.00 wluc of sports equipmcm for participation in this study. Study W"adldnwal You may daoose not to enter your cbild in this study or withdraw bimlher from the study at any time. II you choose o.ot to take part in octo quit tb.is study. it will have no negative impac:t oa you or your c:bild at school You may be n:moved from the study ifyouc child is not wearing the seasor as instructed. mntadoa for Quesdoas You will receive a eopy of this conseat form Please ask questions about this research or c:onsem either DOW oc in the fidure.. You may direct .your questions to Mary J. Bury at (719) -633-o499. If you have questioas regarding your rights as a resean:b au&ject. please call Domtby Yates or Ivy CarroU at UCD (303)556-6379 .. CoaC"ICfeadality Your investip1or 4Dd the Center foe Disease Caattol (CDC) will treat your identity with profcssioaallt.lndards of con6dcntility. Howeva-. the U.S. DepartmeDl ofHealtb IDd Humul Services. CDC and the Ufliwnity ofColondo Jmtirute Review Board have the rigbt to hlspect all of your medical records relltiDg to this n:scan:h for die purpose for veri1Jia8 cfm. nc information obtlined in this study may be published medical joumals. but your idcatity will not be revealed. Injury aad Compeasatioa If Jwrt by this we ...ru mediCI! arc if)OU \1V8Dt if. but ,u will Jaw to pay for tbe care is necdod. Y011 will liCit be paicl & ay CICIIcr loss as rcsuJtofdle injury, suc:has los5 of 'MIBCS. pain ad suflc:rillg. Furdicr iDformaDOII Clll by caJli1Jg MMy 1. 8IUiy c ?19-633-{)499. AUTHORlZA'IlON: I hatlc l'eiJI/ dra paper a6out 1M stlldy Dl" U was l'f!Dd to JW. I blow wltat w/0 6oth 1M JIG#(6li! good awl bGI (benefits and rtsi&).I choose to he (or to ftmre myt:hlkl) In thissfllll)l: I know I ct11t stop betng fn 1M 6lrldy and I (my t:h/14} will sitU get the IISIIQliMdfcal can. hrill get a copy oftkU conrau form.. (lnltfal all prwtOfiS pages ofiM consDI/fonn) Signature: Prillt Name Date Coascatform QplaiDcd by: -----------"Prim Name _____ Date. __ br.Uo __ 152

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Children Assent University of Colorado at Denver Human Research Family InRuence Upon Childral's Physical Activity Principal Investigator. {Mary J. Barry} SUBJECf ASSENT September 22, 1999 Children's explanation: We are interested in understanding how families influence physical activity. In order to do that, we need to know how active children and parents are over time. The monitor we have asked you to wear will measure your activity over seven days. _____ has explained what the activity study is. I have thought about being a part of the study. I have asked and gotten answers to my questions. I understand that the monitor may make my skin itch and be sore. I know I can wear the monitor on the outside of my clothing or underneath, whatever is more comfortable for me. I also know that there may be a possibility of other children making fun of me wearing the monitor. I may feel uncomfortable answering questions about physical activity. I agree to be in this study. I know that I don't have to agree to be in it. Even though I agree to be in it now, I know I may not want to later. I know that I may stop being in the study at any time. Name/Signature Date 153

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REFERENCES Adams P.F., et al. (1992). Health risk behaviors among our nation's youth: United States. Vital Health Statistics, 10, (192). DHHS publication no. (PHS). Allan, J. (1998). Explanatory models of overweight among African American, Euro American, and Mexican American women. Western Journal of Nursing Research, 20 (1 ), 45-66. Allison, K.R., Dwyer, J.J., Makin, S. (1999, February). Self-efficacy and participation in vigorous physical activity by high school students. Health Education Behavior, 26, (1 ), 12-24. Anderson, R., Crespo, C., Bartlett, S., Cheskin, L., and Pratt, M. (1998, March). Relationship of physical activity and television watching with body weight and level of fatness among children. JAMA, 279, (12), 938-942. Ainsworth, B.E., Haskell, W.L. Leon, A.S. et al. (1993). Compendium of physical activities: classification of energy cost of energy cost of human physical activities. Medicine and Science in Sports and Exercise, 25, pp.25-71. Ajzen, I. (1991 ). Theory of planned behavior. Organizational Behavior and Human_Decision Processes, 50, pp. 179-211. APB news. "APB Neighborhood Crime Check" 9/12/00 htpp://www.apbnews.com/resourcecenter/datacenter/crimecheck/result. Bandura A. (1986). Social Foundations of Thought and Action: A Social-Cognitive Theory. Englewood Cliff, NJ: Prentice-Hall. Bandura, A. (1982). The assessment and predictive generality of self-percepts of efficacy. Journal of Behavior Therapy and Experimental Psychiatry, 13, (3),195-199. 154

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Baranowski, T., Bouchard, C., Bar-Or et al. (1992). Assessment, prevalence and cardiovascular health benefits of physical activity and fitness in youth. Medicine and Science in Sports and Exercise, S24, S237247. Baranowski, T., Hooks, P., Tsong, Y, Cieslik, C, and Nader, P. (1987, August). Aerobic physical activity among third to Sixth grade children. Journal of Developmental Behavior in Pediatrics, (4 ), 203-206. Baranowski, T., Perry, CL, and Parcel, G.S. (1997). How individual, environments, and health behavior interact: Social cognitive theory. InK. Glanz, Lewis, F., and Rimer, B (Eds.), Health Behavior and Health Education: Theory. Research. and Practice. 2nd ed., San Francisco, CA: .Jossey-Bass. Baranowski, T., Simons-Morton, B., Hooks, P. Henske, J., Tieman, K., Dunn, JK., Burkhalter H., Harper J., and Palmer, J. (1990, Summer). A center-based program for exercise change among black-American families. Health Education Quarterly, 17, (2), 179-196. Bar-Or, 0. (1998). Physical activity, genetic, and nutritional considerations in childhood weight management. Medicine and Science in Sports and Exercise, 30, (1 ), 2-10. Bar-Or, 0. and Baranowski, T. (1994). Physical activity, adiposity, and obesity among adolescent. Pediatric Exercise Science, 6. pp. 348-360. Becker, M.H. (Ed.) (1994). The health belief model and personal health behavior. Health Education Monographs, 2 (entire issue). Blair, S.N., Clark, D.G., Cureton, K.J., Powel,l K.E. (1989). Exercise and fitness in childhood: Implication for A lifetime of health. In: Gisolfi, C.V., and Lamb, D.R. (Eds.), Perspective in Exercise Science and Sports Medicine., 2_, Youth, Exercise and Sport, pp. 410-430. Indianapolis, IN: Benchmark Press. Bouchard, C. (1997). Obesity in adulthood: The importance of childhood and parental obesity [Letter to the editor]. The New England Journal of Medicine, 337, (13) 926-927. 155

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Bouchard, C. Shepard, R.J. and Stephens, T., (Eds.) (1994). Physical activity. fitnesss. and health: International proceedings and consensus statement. Champaign, IL: Human Kinetics. Bray, G.A. (1996). Health hazards of obesity. Endocrinology and Metabolism Clinics of North America, 25 (4), 907-917. Brustad, J. (1993). Who will go out and play? Parental and psychological influences on children's attraction to physical activity. Pediatric Exercise pp.210-223. Calfas, K. and Taylor, W. (1994). Effects of physical activity on psychological variables in adolescents. Pediatric Exercise Science, 6, pp.406-423. Clark, L. and Hofsess, L. (1998). Acculturation. InS. Laue (Ed.), Handbook of Immigrant Health, pp. 37-59. New York: Plenum. Cockington, R.A. (1980, April). Growth of Australian Aboriginal children related to social circumstances. Australian and New Zealand Journal of Medicine, 1Q (2), 199-208. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (rev.ed). Hillsdale, NJ: Lawrence Erlbaum Associates. Crespo, C.J., Smit, E. Andersen, R.E., Carter-Pokras, 0., Ainsworth, B. E. (2000, January). Race/ethnicity, social class and their relation to physical inactivity during leisure time: results from the Third National Health andNutrition Examination Survey. American Journal of Preventive Medicine, (1) 46-53. Delany, J.P., Harsha, D.W., Kime, J., Kumler, J., Melancon, L., and Bray, G.A. (1995). Energy expenditure in lean and obese pre-prebertal children. Obesity S67-S72. Delany, J.P. and Lovejoy, J. (1996, December). Energy Expenditure. Endocrinology and Metabolism Clinics of North America, 25, (4), 831-843. Dietz, W. and Gortmaker, S. (1985). Do we fatten our children at the television set? Obesity and television viewing in children and adolescents. Pediatrics, 75, pp. 807-812. 156

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Dishman, R. (1994). Advances in Exercise Adherence. Champaign, IL: Human Kinetics. Dishman, R.K. and Sallis, J.F. (1994). Determinants and intervention for physical activity and exercise. In C. Bouchard, R.J. Shephard, and T. Stephens (Eds.), Physical activity, fitness. and health: International proceedings and consensus statement. pp. 214-238. Champaign, IL: Human Kinetics. Dishman, R., Sallis, J., and Orenstein, G. (1985). The determinants of physical activity and exercise. Public Health Reports, 100, 158-171. Epstein, L., Valoski, A.M., Vara, L.S., Me Curley. J., Wisniewski, L., Kalarchian, M.A, Klein, K.R., and Shrager, L.R. (1995, March). Effects of decreasing sedentary behavior and increasing activity on weight change in obese children. Health Psychology, 14, (2), 109-115. Epstein, L., Valoski, A., Wing, R., and McCurley, J. (1994). Tenyear outcomes of behavioral family-based treatment for childhood obesity. Health Psychology, 13, pp. 373-383. Gamel, J. and Tinsley, B. (1999) Life value rankings and health behaviors. Unpublished manuscript. Goran, M.l., Reynolds, K.D., and Lindquist, C.H. (1999, April ). Role of physical activity in the prevention of obesity in children. International Journal of Obesity Related Metabolic Disorders, 23 Supp.3, S18-33. ---------Goran, M.l., Shewchuk;-R; Gower, A, Nagy, T.R., Carpenter, W.H., and Johnson, R.K. (1998, February). Longitudinal changes in fatness in white children: no effect of childhood energy expenditure. American Journal of Clinical Nutrition, 67 (2), 309-316. Gortmaker, S., A. Must, A., Sobal, K., and Paterson et. al. (1996, April). Television viewing as a cause of increasing obesity among children in the UA, 1986-1990. Archives of Pediatric Adolescent Medicine, 150, pp. 356-362. Grilo, C. M. (1995). The role of physical activity in weight loss and weight loss management. Medicine. Exercise. Nutrition. and pp.60-76. 157

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Hair, J.F., Anderson, R.E., Tatham, R.L., and Black, W.C. (1998). Multivariate Data Analysis. 5th ed. Upper Saddle River, NJ: Prentice Hall. Harter, S. (1985). Manual for the Self-perception Prof for Children. Denver, CO: University of Denver. Harter, S. (1982). The Perceived Competence Scale for Children. Child Development. 53, pp. 87-97. Higgins, P.G. and Learn, C.D. (1999, May). Health practices of adult women. Journal of Advanced Nursing, 29, (5), 1105-1112. Hollinsghead, A.B. (1965). Two Factor Index of Social Position (copyrighted 1957), privately printed. Yale Station, New Haven, CN. Hovell, M., Sallis, J., Hofstetter, R., Barrington E., Hackley, M., Elder, J., Castro, F. and Kilbourne, K. (1991, February). Identification of correlates of physical activity among Latino adults. Journal of Community Health, .1, (1 ), 23-36. Howard, D., and Madrigal, R. (1990). Who makes the decision? The parent or the children? The perceived influence of parents and children on the purchase of recreation services. Journal of Leisure Research, 22, pp. 244-258. Janz, K.F. (1994). Validation ofthe CSA accelerometer for assessing children's physical activity. Medicine and Science in Sports and Exercise, 26 (3), 369-375. Kahn, H.S, Tatham, L., Rodriguez, C., Calle, E., Thun, J. and Health, G. (1997). Stable behaviors associated with adults' 10 year change in body mass index and likelihood of gain at the waist. American Journal of Public Health, 87, pp. 747-754. Kann, L., Warren, W., Harris, W.A. et. al. (1996). Youth risk behavior surveillance-United States. Journal of School Health,., pp. 365-377. Kimiecik, J.C. and Horn, T.S. (1998). Parental beliefs and children's moderate to vigorous physical activity. Research Quarterly for Exercise and Sport, 69, (2), 163-175. 158

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Kimiecik J.C, Hom, T.S. and Shurin, C.S. (1996). Relationships among children's beliefs, perceptions of their parents' beliefs, and their moderate to vigorous physical activity. Research Quarterly for Exercise and Sport, 67, (30), 324-336. Klesges, R., Shelton, M., and Klesges, L. (1994). Effects of television on metabolic rate: potential implication for childhood obesity. Pediatrics, 91, (2), 281-285. Lindquist, C.H., Reynolds, K.D., and Goran, M.l. (1999). Sociocultural determinants of physical activity among children. Preventive Medicine, 29, pp. 305-312. Luepker, R.V. (1999, March 23). How physically active are American children and what can we do about it? International Journal of Obesity Related Metabolic Disorders, Suppl2, S12-17. Malina, R.M. (1996, September). Tracking of physical activity and physical fitness across the lifespan. Research Quarterly for Exercise and Sport, 67 (3Suppl) pp. S48-57. Maddux, J. (1993). Social cognitive models of health and exercise behavior: An introduction and review of conceptual issues. Journal of Applied Sport Psychology, Q, pp. 116-140. McKenzie, T.L., Sallis, J., Kolody, B., and Faucette, F. (1997). Longterm effects of a physical education curriculum and staff development program: SPARK. Research Quarterly for Exercise and Sport, 68, pp. 280291. -----------McKenzie, T.L., Sallis, J., Nader, P., Broyles, S., and Nelson, J. (1992). Anglo-and Mexican American preschoolers at home and recess: activity patterns and environmental influences. Developmental and Behavioral Pediatrics, 13, pp. 173-180. McLeroy, K.R., Bibeau, D., Steckler, A., and Glanz, K. (1988). An ecological perspective on health promotion programs. Health Education Quarterly,j_, pp. 351-377. 159

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McMurray, R.G., Bradley, C.B., Harrell, J.S., Bernthal, P.R., Frauman, A.C., and Bangdiwala, S.l. (1993). Parental Influences on childhood fitness and activity patterns. Research Quarterly for Exercise and Sport, 64, (3), 249-255. Montoye, H .. J., Kemper, H.C.G., Saris, W.H.M., and Washburn, R.A. (1996). Measuring physical activity and energy expenditure. Champaign, IL: Human Kinetics. Moore, L. D., Lombardi, M., White, J., Campbell, S., Oliveria et. al. (1991, February). Influence of parents' physical activity levels on activity levels of young children. The Journal of Pediatrics, 118, pp. 215-219. Moos, R. H. and Moos, B.S. (1994). Family environment scale manual: development. applications. research. Palo Alto, CA: Consulting Psychologists Press, Inc .. Morrow, J. and Freedson, P. (1994). Relationship between habitual physical activity and aerobic fitness in adolescents. Pediatric Exercise Science,, pp. 315-329. Must, A., Dallal, G.E., and Dietz, W.H. (1991 ). Reference data for obesity-85th and 95th percents of body mass index and triceps skinfold thickness. American Journal of Clinical Nutrition, 53, pp. 839-846. Nader, P.R., Sallis, J., Patterson, T., Abramson, 1., Rupp J., Senn, K., Rappe, B., Morris, J., Wallace, J. et. al. (1989, Summer). A family approach to cardiovascular risk reduction: results from the San Diego Health Project. Health Education Quarterly, 1Q, (2), 229-44. National Center for Health Statistics. (1994). Plan and operation of the third national health and nutrition examination survey, 1988-1994. Vital Health Statistics, 1, pp. 1-21. Nutrition and Physical Activity. (2000, September 18). Obesity epidemic increases dramatically in the United States. http//www.cdc.goc/nccdphp/dnpa/obesity-epidemic.htm. Padilla, F. (1994). Handbook of hispanic cultures in the united states: sociology. Arte Publico Press. 160

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Paffenbarger, R.S., Hyde, R.T., Wing, A.L., and Hsieh, C. (1986). Physical activity, all-cause mortality, and longevity of college alumni. New England Journal of Medicine, 314, pp. 605-613. Pate, R., Baranowski, T., Dowda, M. and Trost, S. (1996, January). Tracking of physical activity in young children. Medicine and Science in Sports and Exercise, 28, (1 ), 92-96. Perusse, L., LeBlanc, C., and Bouchard, C. (1988) Familial resemblance in lifestyle components: Results from the Canadian Fitness Survey. Canadian Journal of Public Health, 79, pp. 201-205. Pietrobelli, A, Faith, M.S., Allison, D.B., Gallagher, D., Chiumello, G, Heymsfeld, S.B. (1998). Body mass index as a measure of adiposity among children and adolescents: a validation study. Journal of Pediatrics, 132, pp. 204-210. Prochaska, J.O. (1984). Systems of psychltherapy: A transtheoretical analysis. (2nd ed). Pacific Grove, CA: .L Brooks-Cole (Originally published 1979). Raudsepp, L. and Viira, R. (2000). Sociocultural correlates of physical activity in adolescents. Pediatric Exercise Science, 12, pp. 51-60. Rauh, M., Hovell, M., Hofstetter, C., Sallis, J., et. al. (1992). Reliability and validity of self-reported physical activity in Latinos. International Journal of Epidemiology, 21 (5), 966-971. Reaven, P, Nader, P.R., Berry, C., and Hoy, T. (1998, April). Cardiovascular disease insulin risk in Mexican-American and Anglo American children. Pediatrics, 101, (4), E12. Reynolds, K., Killen, J., Bryson, S., Maron, D., Taylor, C., Maccoby, N., and Farquhar J. (1990.) Psychosocial predictors of physical activity in adolescents. Preventive Medicine, 19, pp. 541-551. Rigotti, N.A., Thomas, G.S., Leaf, A. (1983). Exercise and coronary heart disease. Annual Review of Medicine, 34, pp. 391-412. Robinson, T.N. (1999, October 27). Reducing children's television viewing to prevent obesity: A randomized controlled trial. JAMA, 282, (16), 1561-1567. 161

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Robinson, T. and Killen, J. (1 995, March/April). Ethnic and gender differences in the relationships between television viewing and obesity, physical activity, and dietary fat intake. Journal of Health Education, 26, (2), 591-98. Rokeach, M. (1973). The nature of human values. New York, NY: Free Press. Rosner, B., Prineas, R., Loggie, J .and Daniels, S.R. (1998). Percents for body mass index in US children 5 to 17 years of age. Journal of Pediatrics, 132, pp. 211-222. Rowland, T.W. (1991 ). Exercise and children's health. Champaign, IL: Human Kinetics. 162

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Sallis, J.F. (1993). Epidemiology of physical activity and fitness in children and adolescents. Critical Reviews in Food Science and Nutrition, 33, pp. 405-408. Sallis, J.F. (1991 ). Self-report measures of children's physical activity. Journal of School Health, Q1, pp. 215-219. Sallis, J.F., Alcaraz, J.E., McKenzie, T.L., Hovell, M.F., Kolody, B., and Nader, P.R. (1992). Parent behavior in relation to physical activity and fitness in 9-year-olds. American Journal of Diseases of Children, 146, pp. 1383-1388. Sallis, J.F., Johnson, M.F., Calfas, K.J. Caparosa, S. and Nichols, J.F. (1997). Assessing perceived physical environmental variables that may influence physical activity. Research Quarterly for Exercise and Sport, 68, (4 ), 345-351. Sallis, J.F., McKenzie, T., Elder, J., Broyles, S., and Nader, P. (1997). Factors parents use in selecting play spaces for young children. Archives of Pediatrics and Adolescent Medicine, 151, pp. 414-417. Sallis, J.F. and Owen, N. (1999). Physical activity and behavioral medicine. Thousand Oaks, CA. Sage Publication. Sallis, J.F., Patterson, T., Buono, M., Atkins, C.J., and Nader, P.R. (1988). Aggregation of physical activity habits in Mexican-American and Anglo families. Journal of Behavioral Medicine, .11. (1 ), 31-41. -sallis, J.F:,-Prochaska, J.J. and Taylor, W.C. (2000). A review of correlates of physical activity of children and adolescents. Medicine and Science in Sports and Exercise, 32, pp. 963-975. Sallis, J.F., Strikmiller, P.K., Harsha, D.W., Feldman, H.A., Ehlinger, S., Stone, E.J., Williston, B.J., and Woods, S. (1996). Validation of interviewer and self-administered physical activity checklists for fifth grade students. Medicine and Science in Sports and Exercise, 28, pp. 840-851. Shaver, KG. (1987). Principles of social psychology. (3rd ed.) New Jersey: Lawrence Erlbaum Associates. Stefanick, M.L. (1993). Exercise and weight control. Exercise and Sport Sciences Reviews, 21, pp. 363-396. 163

PAGE 180

Strecher, V.J., and Rosenstock, I.M. (1997). The health belief model. In Glanz, K., Lewis, F.M., Rimer, B.K .. Health Behavior and Health Education: Theory. Research and Practice, pp.41-59. San Francisco: Joss-Bass. Stuckey-Ropp, R. and Dilorenzo. (1993). Determinants of exercise in children. Preventive Medicine, 22, pp. 880-889. Stunkard, A., d'Aquili E., Fox, S., and Filion, R.D. (1972, August 7). Influence of social class on obesity and thinness in children. JAMA, 221, (6), 579-584. Taylor, W.C., Baranowski, T.M., and Sallis, J.F. (1994). Family determinants of childhood physical activity: a social-cognitive model. In R.K. Dishman (ed.), Advances in Exercise Adherence, pp. 319-342. Champaign, II: Human Kinetics. Tipton, C.M. (1983). Exercise and resting blood pressure. In: Eckert H.M., Montoye H.J., (eds.). Exercise and health, pp. 32-41. Champaign, IL: Human Kinetics Publishers. Treuth, M.S., Figueroa-Colan, R., Hunter, G.R., Weinsier, R.L., Butte, N.F., and Goran, M. (1998) .. Energy expenditure and physical fitness in overweight vs non-overweight prepubertal girls. International Journal of Obesity, 22, (5), 440-44 7. Troiano, R.P., and Flegal, K.M. (1998). Overweight children and adolescents: description, epidemiology, and demographics. Pediatrics 1 01, pp.497 -504. Trost, S.G., Pate, R.R., Saunders, R., Ward, D.S., Dowda, M., and Felton, G. (1997). A prospective study of the determinants of physical activity in rural fifth-grade children. Preventive Medicine, 26, pp. 257-263. Trost, S.G., Russell, P.R., Ward, D.S., Saunders, R., and Riner, W. (1999). Correlates of objectively measured physical activity in preadolescent youth. American Journal of Preventive Medicine, 17, (2), 120-126. U.S. Department of Health and Human Services. (1990). Healthy People 2000: National health promotion and disease prevention. Washington D.C.: Government Printing Office. 164

PAGE 181

U.S. Department of Health and Human Services. (1996). Physical activity and health: A Report of the Surgeon General. Atlanta, Georgia: U. S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion. Van Mechelen, W., Twisk, J.W., Bertheke Post, G., Snel, J., and Kemper, H.C. (2000). Physical activity of young people: The Amsterdam longitudinal growth and health study. Medicine and Science in Sports and Exercise, 32, (9), 1610-1616. Williamson, D.F., Madans, J., Anda, R. and Kleinman, J. (1993). Recreational physical activity and ten-year weight change in a US national cohort. International Journal of Obesity, 1Z. pp. 279-286. Winkleby, M., Gardner, C., and Barr Taylor, C. (1996, March/April). The influence of gender and socioeconomic factors on Hispanic/White differences in body mass index. Preventive Medicine, 25, (2), 203-211. Winkleby, M.A., Kraemer, H.C., Ahn, O.K., and Varady, A. (1998). Ethnic and socioeconomic differences in cardiovascular disease risk factors: findings for women from The Third National Health and Nutrition Examination Survey. Journal of the American Medical Association, 280, (4), 356-362. Whitaker, R. et. al. (1997). Predicting obesity in young adulthood from childhood and parental obesity. The New England Journal of Medicine, 337, (13), 869-873. 165