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An investigation into the relationship between stress, depression, and diurnal salivary cortisol in western Colorado ranches

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An investigation into the relationship between stress, depression, and diurnal salivary cortisol in western Colorado ranches
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Schulze, Emily Ann
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English
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xii, 61 leaves : ; 28 cm

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Hydrocortisone ( lcsh )
Ranchers -- Health and hygiene -- Colorado ( lcsh )
Stress (Physiology) ( lcsh )
Stress (Psychology) ( lcsh )
Depression, Mental ( lcsh )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Includes bibliographical references (leaves 55-61).
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by Emily Ann Schulz.

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University of Florida
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ocm62879300
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Full Text
AN INVESTIGATION INTO THE RELATIONSHIP BETWEEN STRESS, DEPRESSION,
AND DIURNAL SALIVARY CORTISOL IN WESTERN COLORADO RANCHERS by
Emily Ann Schulze
B.A., Western State College, 2003
A thesis submitted to the University of Colorado at Denver in partial fulfillment of the requirements for the degree of Master of Arts Psychology
2005


The thesis for the Master of Arts
degree by
Emily Ann Schulze has been approved by
Date


Schulze, Emily Ann (M.A., Psychology)
An Investigation into the Relationship between Stress, Depression, and Diurnal Salivary Cortisol in Western Colorado Ranchers
Thesis directed by Assistant Professor Mary Coussons-Read
ABSTRACT
Stress is a part of the human experience. Different lifestyles, however, are exposed to different types of stressors. In the ranching community, many of the stressors are uncontrollable (i.e. weather and market conditions). The experience of uncontrollable stress has been shown to elicit a chronic stress condition in animal models. Related to stress, depression is a common condition. Research has demonstrated both cognitive and physiological connections between these two phenomena. Cognitively, learned helplessness is an etiologic model for depression, which is related to the perceived lack of control over a situation seen in chronic stress. In addition, disruption of the hypothalamic-pituitary-adrenal axis (HPA axis) is related to chronic stress and found in about half of those diagnosed with major depressive disorder (MDD). Disruption of the HPA axis in these conditions results in blunted cortisol feedback inhibition which leads to chronically elevated cortisol levels. The purpose of this study was to ascertain the relationship among the variables of perceived stress, depression, and salivary cortisol in ranchers. We hypothesized that increased levels of stress would be positively related to higher depression ratings and increased cortisol levels. In this study, ranchers were asked to collect saliva samples and maintain health diaries over three separate 2-week periods. At the end of each of these two week periods, the Beck Depression Inventory-II (BDI-II) and Perceived Stress Scale (PSS) were administered. Twenty-


one ranchers participated in the study (12 male). Results showed a strong relationship between BDI-II and PSS scores (r=0.748, p<0.01). In addition, a decreased daytime cortisol decline was associated with higher levels of stress and depression in males, but not females. The decreased daytime cortisol decline supports the notion that the HPA axis negative feedback loop is disrupted in chronic stress and depression, thus resulting in chronically elevated cortisol levels. This study supports the relationship between stress, depression, and HPA dysregulation in ranchers; however, it also brings gender differences in HPA responsivity in these phenomena to attention.
This abstract accurately represents the candidates thesis. I recommend its publication.
Signed
Mary Coussons-Read


DEDICATION
I dedicate this thesis to James L. Vela whom I admire and respect for his steadfast devotion to a life he loves. He has not only taught me many things about ranching, but he has also given me perspective on living life.


ACKNOWLEDGEMENT
My heartfelt thanks to Dr. Mary Coussons-Read for her advice and support, which not only made this project possible, but also made it a positive and enlightening experience. Additionally, Dr. Mark Laudenslager and his lab were instrumental in the collection, extraction, and interpretation of the saliva samples. Finally, the ranchers who chose to participate in this study gave it depth and, beyond the data collection, gave me insights into their unique lifestyle.


CONTENTS
Equations....................................................................x
Figures.....................................................................xi
Tables.....................................................................xii
Chapter
1. Introduction.............................................................1
1.1 Stress and the Ranching Population.......................................2
1.2 Perceived Stress and Appraisal...........................................5
1.3 The Stress Response......................................................6
1.4 Allostatic Load........................................................10
1.5 Stress and Depression..................................................12
1.6 Goals and Hypotheses...................................................14
2. Methods.................................................................16
2.1 Participants...........................................................16
2.2 Recruitment Procedures.................................................16
2.3 Study Protocol.........................................................17
2.3.1 Study Location........................................................17
2.3.2 Human Subjects Approval..............................................17
2.3.3 Activities Involving Subjects........................................17
2.4 Instruments and Sampling Techniques....................................19
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2.4.1 Beck Depression Inventory-II...........................................19
2.4.2 Perceived Stress Scale (PSS)..........................................19
2.4.3 Life Events Scale (LES)...............................................20
2.4.4 Saliva Collection.....................................................20
2.4.5 Salivary Cortisol Extraction..........................................21
2.4.6 Pre-/Post-Study Survey................................................22
2.4.7 Coping Styles Survey and Leisure Activities Questionnaire.............24
2.5 Statistical Analysis....................................................24
3. Results..................................................................27
3.1 Population Statistics...................................................27
3.2 Predicted Stress and Actual Stress Relationship.........................27
3.3 Pre- and Post-Study Survey Results......................................28
3.4 Diurnal Cortisol Pattern................................................28
3.5 Cortisol, Stress, Depressive Symptoms, and Life Events..................29
3.6 Health Symptoms, Stress, Depressive Symptoms, and Cortisol..............32
3.7 Regression Analyses.....................................................33
3.8 Population Factors......................................................35
3.8.1 Age....................................................................35
3.8.2 Gender................................................................35
3.8.3 Ranch and Rancher Characteristics.....................................37
3.9 Coping Styles...........................................................38
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4. Discussion.............................................................40
5. Limitations and Future Directions......................................47
Appendix
A. Monthly Stress Level Questionnaire.....................................51
B. Pre-/Post-Study Survey.................................................52
C. Coping Styles Survey...................................................53
D. Leisure Activities Questionnaire.......................................54
Literature Cited...........................................................55


EQUATIONS
Equation
2.1 Bonferronis Correction...............................................26
x


FIGURES
i
Figure
3.1 Average Diurnal Cortisol Rhythm.........................................29
3.2 PSS and BDI-II Score Scatterplot with Trendline.........................31
3.3 Male and Female Mean Cortisol Rise (nm/L)...............................36
3.4 Coping Mechanism Utilization (0=never, 2=sometimes, 4=very often).......39
i
XI


TABLES
Table
3.1 Population Demographics................................................27
3.2 BDI-II, PSS, LES, and Cortisol Decline Correlations....................31
3.3 Health Items Correlations..............................................32
3.4 BDI-II Regression Model................................................34
3.5 BDI-II Regression Model with Males Only................................34
3.6 Age Correlations.......................................................35
3.7 Ranch Characteristics and Psychological Correlations...................38
3.8 Ranching Characteristic Correlations...................................38


1. Introduction
Stress has affected all people and animals since life began. The term stress was originally defined by a pioneering researcher, Hans Selye, as the rate of all the wear and tear caused by life (Selye, 1956). Another more biological definition describes stress as any threat to the bodys homeostasis (Nelson, 2000). It is also recognized in human research that an event that is stressful to one person, may not cause any stress to another; therefore, perception of the stimulus is also important in modulating the stress response (Sapolsky, 1998).
Many studies across a variety of populations have shown that stress has an effect on general health. These populations include healthy adults, breast cancer patients, caregivers of patients with Alzheimers, surgical patients, and AIDS patients, among others (Kielcolt-Glaser, Marucha, Malarkey, Mercado, & Glaser, 1995; Kielcolt-Glaser, Page, Marucha, MacCallum, & Glaser, 1998; Nelson, 2000; Vedhara, et al., 1999).
Although the effects of stress on health have been studied in numerous urban-dwelling populations, fewer studies have addressed these effects in rural populations, such as farmers and ranchers. The importance of these populations to the Colorado and national economy should not be underestimated. Increasingly, more researchers are becoming interested in understanding the unique stressors and challenges faced by American farmers and ranchers. In the present study, the
1


relationship between psychological stress, depression, and a measure of physiological stress is examined in ranchers to further the knowledge of the effects of stress on human health.
1.1 Stress and the Ranching Population
As in the general population, the ranching population commonly experiences stress; however, the form and types of stress experienced by ranchers differs markedly from that found in urban populations. In contrast to many five-day-a-week occupations, farmers and ranchers work on a daily basis, many for over 10 hours per day (Gregoire, 2002). In addition, their work changes on a seasonal basis, where activities in January are vastly different from those in July and also those in September. Unpredictable stressors such as disease and weather plague farmers in addition to problems with animals and machinery. Farmers tend to live and work with their families, often with multiple generations, and stress between family members is common (Weigel & Weigel, 1990). Stressors affecting multigenerational households include issues of equality, concerns about teamwork, differences in values, and competition (Weigel, D. & Weigel, R., 1990). Physical ailments are also a source of stress among farmers, especially among older farmers who may be unable to continue their work (Gregoire, 2002). Almost a third of farmers under age 50 report having physical difficulties that interfere with their work (Simkin, Hawton, Fagg, & Malmberg, 1998). Many sources of stress lead to
2


farmers feeling fatigued, anxious, and depressed (Tevis, 1982). Financial difficulties also permeate farmers lives (Simkin, Hawton, Fagg, & Malmberg,
1998; Gregoire, 2002). While the population living in the city and farmers share many common stressors, ranchers clearly have a unique set of stressors, many of which are uncontrollable, with which to deal.
Ranching is an occupation characterized by many stresses that come about at different times of the year. In the spring, for some ranchers in Western Colorado, calving, or birthing, season can cause significant stress and depression, depending on whether or how many cows or calves are lost in the process. Cows (especially heifers) must constantly be observed for signs of difficulty with the birthing process. As spring moves towards summer, the land must be cultivated and prepared for planting. Depending on the winters snowfall, the ranchers must calculate how many fields they can sustain throughout the summer. This can be stressful, especially if the winter has been dry, in which case arrangements must be made to purchase hay or corn that cannot be grown. During the summer, haying and management of crops is occurring. Haying includes cutting, baling, and stacking the hay. Some ranchers own grazing permits on National Forest or Bureau of Land Management land. If they do own permits, they bring their cows to those areas during the summer to graze. Fences on the grazing permit should be mended to make sure that they will hold the cows in the right areas. The cows and their new calves are taken to the mountain grazing area around June.
3


Throughout the summer, salt is often distributed on the grazing permit to keep the cows from over-grazing.
In the later summer, corn harvesting (if applicable) occurs. In October/November, cattle return from the higher country. During this time, many trips are made with the trailer to pick up cattle. This is not necessarily stressful, unless many cows are returning without their calves, or many cows are missing. In addition, it is common that the ranchers ride horses on the mountain to speed the cows descent for the winter. This may be stressful, since ranchers must cover thousands of acres to gather their cows. The threat of losing cows to early snow can also be stressful. After gathering, many ranchers wean the calves from their mothers and send them to feedlots. The financial situation is determined by cattle prices and this can either be a stress-relief or a significant strain if it is a bad year. Then, ranching slows down for the winter in December and January. At this point, equipment is winterized and repairs are also made. Organization for the next year may take place. February brings the beginning of calving season once more. The anecdotal ranching scenario above shows that there is a seasonal aspect to ranching that may modulate levels of depression and stress and thus may have implications for overall health in this population.
In the farming and ranching community, many factors contribute to overall stress. In addition to the stress of depending on the market for income, the weather for crop yield, and the labor involved in a successful operation, farmers and
4


ranchers endure unique stressors compared to urban populations. Stressors in farm and ranch families include psychosocial factors (farm/family competition, job tasks, money, and childrearing), decision making, and income disparity between generations working in the operation (Weigel, D. & Weigel R., 1990). These stressors may be especially salient in two-generation households (Weigel D. & Weigel R., 1990; Weigel, et al., 1987). However, farmers and ranchers also experience generic stressors universal to humans including family disputes. Carson and colleagues (1993), found that greater reported hardiness (defined as internal strength and durability of a family) buffered negative effects of stressors and strains in farming families. Many factors contribute to perceived stress in farm families, due to mediating effects of hardiness as well as coping strategies (Weigel, D. &Weigel R 1990).
1.2 Perceived Stress and Appraisal
According to Lazarus and Folkman, the cognitive appraisal of a situation dictates the consequent stress response (1984). Individuals who take an active approach, characterized by effortful coping tend to activate the sympathetic nervous system more predominantly. Conversely, those who take a passive approach perceive a loss of control and feel helpless. This population tends to activate the HPA axis more readily. Repeated, chronic exposures to stress in the passive population could therefore result in depression, among other psychiatric and physiological disorders.
j
5


Along the lines of appraisal and personality characteristics, some have proposed a diathesis-stress model of depression, where the diathesis is a negative attributional style. In a negative attributional style, individuals tend to view stressors as more damaging or reflective of personal weakness than those who do not exhibit this cognitive style (i.e. a failed date results in the thought, Nobody wants to be with me., Kwon & Laurenceau, 2002). In this model, differential reactivity of individuals (that is, some approach stressors with a negative appraisal and others do not) may affect the threshold for developing a depressive syndrome. Those with negative attributional styles will be more vulnerable to depression.
Many factors can modulate the development of a negative attributional style including personality characteristics and frequency and types of stressors experienced; however, a discussion of those factors is beyond the scope of the current paper. Kwon and Laurenceau (2002) did demonstrate, however, a significant relationship between negative attributional style and increased depressive reactivity to stressors over time.
1.3 The Stress Response
Perceived stress is only one aspect of the stress condition in humans; the physical stress response has ubiquitous effects on the body. Formal research on the physiological stress response began in the 1920s with Walter Cannon. Cannon took an interest in the connection between stress and disease. He explored the
6


fight or flight response model in rodents. This response activates the sympathetic nervous system and leads to the release of epinephrine by the adrenal gland. While this system is useful for animals escaping predators, its chronic activation can lead to cardiovascular disease in humans (Sadock & Sadock 2003). Modern stress response research was pioneered by Hans Selye the 1940s (Nelson, 2000). Selyes work elucidated a second class of endocrine hormones that respond to stress: glucocorticoids, which are also released by the adrenal gland (Sapolsky, 1992b ). Seyle described the general adaptation syndrome, as a three-stage response to stress, which included: (1) the alarm reaction, in which the stressor challenges homeostasis; (2) the stage of resistance, during which one adapts and successfully deals with the short-term insult and (3) the stage of exhaustion, during which resistance or adaptation is lost, and disease occurs (Sadock & Sadock, 2003; Sapolsky, 1992b ). Selyes model was not entirely accurate; scientists have found that instead of the body becoming exhausted and not producing as much cortisol or epinephrine, it is actually the fact that the body continuously produces these substances that leads to the disease state (Sapolsky, 1992b ). While adaptive over short time-spans, long-term increased circulation of these substances is deleterious.
The hypothalamic-pituitary-adrenal axis (HPA axis) is a key player in the stress response. The hypothalamus, located in the forebrain, just below the thalamus, monitors the environment and regulates the hormones sent to the body by the pituitary, depending on environmental stimuli (Pinel, 2000; Sadock & Sadock,
7


2003). Emotions also have an effect on the activity of the hypothalamus. In the stress response, the hypothalamus releases corticotrophin-releasing hormone to the pituitary, which releases adrenocorticotrophic hormone (ACTH). ACTH circulates in the blood stream to the adrenal glands where it promotes production of glucocorticoid hormones, such as cortisol. These hormones affect cardiovascular function and renal function and metabolism and, synergistically with the nervous system, adjust our response to the environment (Padgett & Glaser, 2003). When a person experiences stress chronically, however, this system can have negative effects on general health and make one more susceptible to infectious diseases (Glaser, et al., 1999; Padgett & Glaser, 2003).
In healthy, low-stress individuals, cortisol levels exhibit a diurnal pattern of a morning peak and a decline toward evening (Harbuz, et al., 2003). In general, cortisol levels rise in the first 30-40 minutes after waking and then decline steadily throughout the day (Pruessner, et al., 1997). Certainly, this diurnal variation is subject to individual differences and is also affected by age and gender. Ice and colleagues (2004) studied diurnal cortisol patterns in older adults and found that caffeine had a significant impact on regularity of circadian rhythms and patterns of cortisol. Interestingly, they also found the older subset of the group had more regular cortisol patterns than the younger subset.
The diurnal pattern is also responsive to acute stressors (or challenge); cortisol levels typically peak after exposure to an acute stressor. This diurnal


pattern may be observed in saliva as well as blood. Cortisol is found in saliva in its biological free state, representing 1-10% of total as measured in the blood (Kirschbaum & Hellhammer, 1989). Studies show that younger men show greater cortisol response to challenge compared to younger women, but this is reversed in the elderly (Seeman, et al., 2001; Seeman, et al., 1995). In a study examining acute laboratory-induced stress, Kudielka and colleagues (2004) found that bioavailable free cortisol patterns did not differ between ages, but a gender effect was seen in older men, whose response was elevated. The results also suggest a heightened hypothalamic drive in younger men that attenuates with age, which results in similar ACTH responses in elderly men and women. It appears as though younger women have greater adrenal cortex sensitivity.
Under conditions of chronic stress, cortisol levels tend to be elevated due to dysregulation in the HPA axis. In addition, the diurnal pattern may become disrupted. The awakening cortisol response (seen in the first 45-60 minutes after waking) has been used as a marker of stress, but not all of the research has been consistent (Clow, Thorn, Evans, & Hucklebridge, 2004). Flatter diurnal cortisol patterns (smaller differences between peak morning levels and evening levels) have been related to higher mortality in breast cancer patients, maltreated children, and those with poor relationship functioning (Sephton, Sapolsky, Kraemer, & Speigel, 2000; Hart, Gunner, & Cichetti, 1996; Adam & Gunnar, 2001 as cited in Edwards, Hucklebridge, Clow, & Evans, 2003).
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Related to dysregulated diurnal rhythms, chronic stress can also result in elevated cortisol due to malfunctioning negative feedback loops (Tafet & Bernardini, 2003). Constantly elevated levels of cortisol may result in cardiovascular disease (e.g. atherosclerosis) and visceral deposit of adipose tissue. In cases of chronically, severely elevated cortisol, the development of Cushings disease may result (Miller & OCallaghan, 2002). Chronic stress has also been shown to increase susceptibility to acute stressors or threats (such as viruses or bacteria) to an individuals health (Glaser, et al., 1999). Other pathological effects of chronically elevated cortisol include fatigue, steroid diabetes, peptic ulcers, impotence, and accelerated neural degeneration during aging (Sapolsky, 1992a). Selye found that rats responded to different stressors with the same glucocorticoid response; that is, he thought the stress response was nonspecific (Sapolsky, 1992b). This is not the case, however, as different patterns of secretion are found for different stressors (Sadock & Sadock, 2003; Sapolsky, 1992b). In addition, individual differences (genetic, personality, and social) can also contribute to differences in glucocorticoid profiles (Sapolsky, 1992b). These factors need to be kept in mind when evaluating stress research.
1.4 Allostatic Load
Allostatic load is a term by B.S. McEwen (1998) to conceptualize the cumulative biological burden exacted on the body in its attempts to adjust to lifes demands. In
10


other words, allostatic load examines the wear and tear on a body over the lifespan that results from threats to homeostasis, or stressors. According to McEwen, the level of exposure to stress mediators in response to stressors may interact with individual differences (genes, childhood trauma, experiences), which moderate ones coping mechanisms. Over a lifetime, the accumulation of stressors coupled with individual adaptability exacts a price, in the form of a disease state or even death (McEwen & Seeman, 1999). Allostatic load reflects not only experience, but individual health and diet habits, genetics, behavior patterns (coping mechanisms), and early childhood experiences. McEwen has also explored the role of socioeconomic status (SES) in risk differences and has established that gradients in SES have significant implications for health. And abuse in childhood has been shown to result in neurochemical imbalances in adulthood (McEwen & Seeman, 1999). Allostatic load has been operationalized as a set of physiological parameters that are pertinent to disease risk such as blood pressure, urinary cortisol, waist/hip ratio and cholesterol levels (Seeman, Singer, Ryff, Love, & Levy-Storms, 2002). McEwen (1999) emphasizes that allostatic load is more than chronic stress, but encompasses the many other factors discussed above, such as genes and diet. In sum, the concept of allostatic load is an important aspect of stress research that explores the long-term morbidity and mortality aspects of lifetime stressors. In the ranching population, an exploration of the concept of allostatic load as it affects


ranchers would be important for long-term health outcomes, especially in light of the relative paucity of health care resources in rural areas.
1.5 Stress and Depression
As seen in the population suffering from chronic stress, cortisol levels remain constantly elevated in many patients with depression; that is, glucocorticoid receptor sensitivity is lower in depressed patients, leading to a failure to suppress cortisol production (Modell, et al., 1997 as cited in Harbuz, et al., 2003); however, HPA dysregulation is only found in about half of those diagnosed with MDD (Sadock & Sadock, 2003). As mentioned above, these constantly elevated cortisol levels have a negative affect on general health. Stress and depression may both negatively affect a persons general health and well-being. Stress and depression may thus be related in terms of their potential physiological consequences. Not only are stress and depression linked by physical symptoms, but statistically, the stress and the onset of depression go together (Sapolsky, 1998). This relationship is especially strong for a persons first episode (Sadock & Sadock, 2003).
Like stress, depression affects a large percentage of the population (Sadock & Sadock, 2003). Depression is a heterogeneous phenomenon that affects millions of people throughout the world, with a lifetime prevalence of about 15 percent (Sadock & Sadock, 2003). According to DSM-IV diagnostic criteria, major depressive disorder (MDD) is characterized by symptoms including depressed
12


mood, anhedonia, weight gain or loss, appetite disturbance, sleep irregularities, energy loss, feelings of worthlessness, diminished ability to concentrate, psychomotor agitation or retardation, and recurrent thoughts of death (APA, 2000). Depressive syndromes have been described in texts dating back to 400BC, when Hippocrates described mental disturbances using the terms mania and melancholia. In Rome, the physician Celsus described melancholia as depression caused by black bile (Sadock &Sadock, 2003). Today, depression is still a major topic of research, with a variety of etiologic theories and types of presentation.
Authors disagree on whether there is a difference in rural and urban incidence of depression. It is difficult to compare studies, as some examine depressive symptomatology, and others examine number of people who qualify for a diagnosis of MDD. For instance, Wang (2004) found no difference in rural and urban prevalence of major depressive episodes in rural Canadians in the 12 months before the study, but after controlling for race, age, and social status, urban areas were found to have a significantly higher prevalence. This was consistent with a study done in the United Kingdom by Thomas and colleagues (2003), who found a higher rate of suicidal thoughts, but a lower prevalence of psychiatric morbidity in farmers compared to urban dwellers. Patten and colleagues (2003) also found higher rates of depression among Canadian urbanites, which they attributed to street drugs, social support deficits, unemployment, and recent life events. Conversely, other sources cite a higher rate of depression in rural areas (Sadock & Sadock, 2003;
13


Roberts & Lee, 1993 as cited in Scarth, et al., 2000). Although the research is conflicting, depression does still occur in rural areas, and identifying the relationship between depression and its risk factors (e.g., stress) in this population could help elucidate its unique incidence in this population.
1.6 Goals and Hypotheses
In this study, the focus was on identifying seasonal levels of depressed affect and perceived stress in Western Colorado ranchers (both husband and wife) and how those phenomena related to their levels of cortisol. The relationship between these factors was elucidated by assessing stress levels, depressive symptomatology, and diurnal cortisol patterns at three time points in the year. The hypotheses are as follows:
High, medium and low stress periods emerging from the seasonal nature of ranching would demonstrate significant differences in levels of stress and depressed affect
Stress and symptoms of depression would exhibit a positive relationship
Dysregulated cortisol, seen as an increased morning rise (the difference between the wake and thirty minutes after waking samples) or a blunted daytime decline (the difference between the peak at thirty minutes after waking and the value at retiring) would be related to both increased depressive symptoms and stress
14


Lower levels of general health would be exhibited during periods of higher stress (i.e. increased number of symptoms endorsed on symptom checklist)
15


2. Methods
2.1 Participants
A list of potential participants was obtained from the Department of Agriculture through the Freedom of Information Act (FOIA). Cattle ranchers who are permitees on the Grand Mesa were recruited by mail contact. The principle investigator (PI) sent letters to approximately 105 ranchers. Twenty-one (21) ranchers completed the study (9 females, 12 males; all Caucasian).
2.2 Recruitment Procedures
The ranchers were initially contacted by mail. Included in the mail packet were: a cover letter outlining the purpose of the study, a demographic information sheet, and a pre-study survey. The purpose of the pre-study survey was to assess the ranchers baseline levels of stress; that is, the number of items that cause them stress year-round. As compensation for participation, the subjects were offered the choice of one book from the Successful Farming Magazine collection (Titles include: Ageless Iron I, Ageless Iron II, Changing Faces on our Land, and Successful Farming Recipe Collection).
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2.3 Study Protocol
2.3.1 Study Location
The study was located in Mesa and Delta counties in Western Colorado. The PI visited the subjects at their homes (or at an alternative location, whichever was more convenient for the subject). Assessment of diurnal cortisol measurements was conducted at the Behavioral Immunology and Endocrinology Laboratory, Department of Psychiatry at the University of Colorado at Denver and Health Sciences Center.
2.3.2 Human Subjects Approval
In May 2004, the University of Colorado at Denver and Health Sciences Center Human Subjects Research Committee approved the current study protocol (#2004-104). In October 2004, an addendum requesting the addition of a Coping Styles Survey and a Leisure Activities Questionnaire was also approved.
2.3.3 Activities Involving Subjects
The PI met with participants in person before beginning study activities to ensure participants were oriented to the study and understood the protocol. At the initial meeting, the PI obtained written, informed consent and also interviewed the participants about the timing of events and stress levels for their ranching operation. At this time, participants rated stress for each month from July-December on a scale
17


from one to seven, based on their experience and current conditions (drought, insects, etc.). From these ratings, the ranchers identified two-week time periods representing relative high, medium, and low stress (Appendix A). The phase dates were different for each participant. That is, some ranchers identified high, medium, and low stress periods as occurring in July, October, and December respectively, and another might have chosen September, November, and December, respectively. Clearly, there was not a consistent schedule; however, each participant completed three two-week phases during the six-month time period. Participants completed activities detailed below for each phase.
The PI contacted the participants before each time period to verify the starting date of the phase. The first time, the PI delivered the materials in person (to give instructions); materials were delivered by mail for the second two phases. During each phase, the participants took saliva samples three times daily (upon waking, thirty minutes after waking, and at retiring) on three days of their choosing, rated stress levels on saliva collection days, and completed a daily health diary (a symptom checklist). The PI collected these materials at a meeting shortly after the end of each two-week phase. At each meeting, an interview ascertained participants approximate levels of stress by asking for a rating on a scale of 1 to 7,
(1 being the least stressful) and the sources of stress for the past two weeks. In addition, the Beck Depression Inventory (BDI-II; Beck, et al., 1961; Beck & Steer, 1996), a self-report instrument, was administered to determine depressive
18


symptoms. Another self-report measure, the Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983), was given to ascertain perceived stress levels. A life events scale complemented the perceived stress scale. At the end of the study, the participants filled out the Pre-Study survey a second time, as well as a coping styles survey and leisure activity questionnaire.
2.4 Instruments and Sampling Techniques
2.4.1 Beck Depression Inventory II
This inventory was developed by Beck (et al., 1961; & Steer, 1996), and has been widely used to assess depression in psychiatric populations as well as normals (Groth-Marnat, 2003). The inventory consists of 21 statements with responses from 0 to 3, 0 indicating a statement does not occur or is not severe and 3 indicating a high incidence or severity of the item. Mean internal consistency is 0.91 and test-retest reliabilities range from .48 to .93 depending on the interval between testing. Content, concurrent, and discriminant validity are all good for this measure (Dozois, Dobson, & Ahnberg, 1998).
2.4.2 Perceived Stress Scale (PSS)
The PSS is a 14-item self-report scale developed by Cohen and colleagues (1983), which identifies an individuals appraisal of the amount of stress in ones life. The items are ranked with a Likert-type 5-point scale, 0 indicating never and 4 indicating
19


very often. This measure has good psychometric properties, with a reliability coefficient of 0.78 as well as good construct validity (Corcoran & Fischer, 2000).
2.4.3 Life Events Scale (LES)
The LES (Coussons-Read, Okun, Geise, & Schmitt, in press) administered in this study contained 28 items. These items were ordered in terms of severity, with death of a spouse as most severe, and minor violations of the law as least. Subjects were asked to check off the events that occurred in the last two weeks. Events occurring more than one time were checked and the number of times the event occurred was indicated next to the item.
2.4.4 Saliva Collection
Saliva samples were collected from subjects using the Saliva Procurement and Integrated Testing, or SPIT Book (Laudenslager, Neu, Riggs, Goldstein, & Lohman, 2003), provided by Dr. Mark Laudenslager. SPIT booklets contained three pieces of filter paper separated by waxed paper. Subjects were provided with SPIT Books for saliva collection and a package of Trident Original Flavor gum for stimulating saliva flow. This gum is selected as it does not interfere with the enzyme immunoassay that are used to measure steroids in the laboratory. Each subject was requested to collect these samples three times a day: at waking, thirty minutes after waking, and before retiring. These time-points were established to allow for
20


examination of subjects diurnal patterns. As discussed above, diurnal patterns are altered during chronic stress or depression. Subjects collected samples on three different, but typical days during each of the three phases. Because each rancher had unique phases, the sampling dates and times of year were widely varied in the study.
Values outside exceeding two standard deviations were removed from raw salivary cortisol data. Then, within each phase, each individuals daily samples were averaged. For instance, the three waking samples taken during the two-week period were averaged for each person. This resulted in an average diurnal pattern for each phase for each participant. Additional values examined in the study were morning rise and daytime decline. The morning rise was calculated by subtracting the initial waking value from the peak value (waking plus thirty minutes). The daytime decline was calculated by subtracting the cortisol value at retiring from the peak value obtained thirty minutes after waking. These latter two values, as discussed previously, can indicate the presence of stress or illness if they are unusually large or small, respectively.
2.4.5 Salivary Cortisol Extraction
Filter strips were extracted by cutting a section from the previously moistened end. The exact area varies with filter paper lot and must be calibrated with each new lot using a known volume of radiolabeled tracer in a saliva pool. An area equivalent to
21


absorbing 100 pi of saliva was determined using tritiated cortisol added to saliva. The cut filter paper was placed in a 1.4 ml microcentrifuge tube to which 0.25 ml of assay buffer was added. The tube was shaken for 24 hours after which buffer was added in duplicate to the appropriate wells of the assay plate. This effectively dilutes the saliva 1:5. Salivary cortisol levels were determined using a high sensitivity commercial EIA kit (Salimetrics) that detects cortisol levels in the range of 10-1000 pg/ml. Briefly, 50 pi of buffer from extracted filters were added in duplicate to the wells of an antibody (rabbit anti-cortisol) coated microtiter plate. The unknowns competed with horseradish peroxidase conjugated cortisol for the binding sites. The substrate tetramethylbenzidine (TMB) was added; the reaction was stopped with H2SO4, and read at 450nm on a microplate reader. A sigmoid function was fitted by a four-parameter logistic regression for the standard curve and unknown concentrations were determined from this curve. Detection limit for this assay is 35 pg/ml. Inter- and intra-assay coefficients of variation are less than 10% for this assay.
2.4.6 Pre-/Post-Study Survey
The Pre/Post-Study Survey (Appendix B) was developed by the PI for this study to obtain an estimate of baseline stress for each rancher. That is, how much stress are they experiencing on a year-round basis (not connected to season, necessarily)?
This is an important consideration when looking at the acute stressors that ranchers
22


experience as a result of the time of year; keeping in mind the issues that concern them regardless of season could give a deeper understanding to how the ranchers respond to acute stressors.
This Survey was developed by a detailed review of surveys given to farmers and ranchers in the past that ask about day to day life stressors. For this study, four different scales were examined: a Daily Work Inventory, a Farm Work Stress Scale, a Farm/Ranch Stress Scale and a Market Research Panel Questionnaire. The first two items are publications from the Iowa State University Cooperative Extension Service. The Farm/Ranch Stress Scale was developed by Carson, and colleagues (1993) for the purpose of their study examining the mediating effects of hardiness on stress in ranchers. Finally the Market Research Panel Questionnaire was developed by Successful Farming Magazine.
The Pre/Post-Study Survey was given to participants before the study began and then upon completion of the final phase. The instruction asked participants to indicate which items are stressful to them throughout the year and to circle the relative level of stress on a Likert-type scale. The survey was scored by adding the values endorsed for each item.
The coefficient alpha for the Pre-Study survey was 0.743 and for the Post-Study Survey it was 0.750. According to George and Mallery (2003), a value above 0.7 is acceptable for internal validity (p. 231).
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2.4.7 Coping Styles Survey and Leisure Activities Questionnaire
The coping styles survey (Appendix C) and leisure activities questionnaire (Appendix D) were both adapted from a Market Research Panel Survey distributed by Successful Farming Magazine (1999). There were nine items on the coping styles survey. Each item was rated on a Likert-type scale from 0 to 4 (0=never, 2=sometimes, 4=very often). The leisure activities questionnaire contained a list of 19 activities. Subjects checked a box indicating how often they participated in each activity for leisure. There were eight choices ranging from every day to never, with graded intervals between choices.
2.5 Statistical Analysis
Data were analyzed using hierarchical multiple linear regression, correlation analysis, and t-tests.
Hierarchical regression analysis was run to determine the contribution of stress, cortisol, and year-round stressors to the variation in depressive symptoms. Depressive symptoms, as measured by the BDI-II, were entered as the dependent variable. Independent variables, in their order of entry were: age, perceived stress (as PSS scores), diurnal cortisol decline, found by subtracting the retiring value from the wake +30 value, and Pre-Study Survey scores. Age was entered first to account for the effects of age on the depression scores. While the onset of
24


depression can occur throughout the lifetime, it may be more prevalent in the elderly who suffer more physical symptoms. These symptoms can have a negative impact on mood (Koenig & Blazer, 1992). Next, perceived stress was entered, as stress has been related to depression in multiple studies; particularly as chronic stress may contribute to the pathogenesis of depression (Tafet & Bernardini, 2003). Following perceived stress, diurnal cortisol decline was entered, as blunted diurnal decline can be a marker of depression. Finally, the Pre-Study survey results were entered, as they reflect the impact of year-round stressors on the ranchers; although related to the perceived stress levels, the Pre-Study survey results are differentiated by their measurement of actual events or situations that cause the stress instead of the perception of stress in general. The purpose of the regression analysis is to demonstrate the predictive value of the independent variables on the dependent variable. In this case, while a case can be made to substitute some of the other variables for the dependent variable, based on research that places stress and cortisol dysregulation temporally before the onset of depression (clearly this can be argued; Sapolsky, 1998), it was decided to enter the variables based upon that assumption: the occurrence of stress, cortisol dysregulation, and the presence of chronic stressors could precipitate depressive symptomatology.
Correlation analyses determined the relationship between factors, including age, health symptoms, ranch characteristics (size of herd, acres farmed, etc.), BDI-II scores, PSS scores, and Life Events Scale scores. Significance values after
25


Bonferronis correction for multiple comparisons are presented as a conservative calculation to reduce Type-I error. Since the sample size is small, the correlations should be interpreted with caution and as potential trends. The calculation used to find the corrected p-value is shown below, in Equation 2.1.
0.05
p~ 4k^\
Equation 2.1 Bonferronis Correction
Where k is the number of comparisons made.
T-tests examined gender differences in BDI-II scores, PSS scores, Life Events, and health symptoms.
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3. Results
3.1 Population Statistics
Table 3.1 presents the demographic information for the population used in the study.
Table 3.1 Population Demographics
Minimum Maximum Mean Std. Deviation
Age 24.00 81.00 53.38 14.63
Years married .00 59.00 24.95 18.98
Size of herd 0 500 182.05 127.65
Acres owned .00 2000.00 556.86 547.00
Acres farmed .00 1000.00 317.52 311.12
Years on ranch .00 65.00 32.12 18.88
Years head of ranch .00 43.00 19.95 14.79
Number of hired hands 0 3 .24 .70
Outside Job 1 2 1.52 .51
Outside Job hours/week .00 50.00 12.00 16.11
Number of children 0 7 2.52 1.99
Number of children at home 0 3 .62 1.16
3.2 Predicted Stress and Actual Stress Relationship
One of the main hypotheses for this study was that different times of the year likely are associated with varying levels of stress for ranchers due to changes in activity. Additionally, the researcher acknowledged that individuals were likely to perceive activities differentially and thus give unique stress ratings. Despite this attempt to accommodate individual differences, however, ranchers selections of relative high, medium, and low stress times had no correlation with their post-phase ratings of their actual stress during those time periods (High: r=0.28, n.s.; Medium: r=-0.10,
27


n.s.; Low: r=-0.33, n.s.). As a result of the lack of relationship between predicted and actual stress levels, and due to confounds that would arise in attempting to reorganize the data by season, dependent variables were averaged. Hypothesized relationships were examined over the six-month period instead of comparing phases of different stress levels.
3.3 Pre- and Post-Study Survey Results
The top five items endorsed on the Pre-Study survey were: market conditions, government policies, financial constraints and difficulties, machinery problems, and weather, respectively. The bottom four items on the Pre-Study Survey were isolation, being involved in a parent-child operating agreement, accidents and injuries, and competing for land. When the ranchers took the survey a second time, the top five items were: machinery problems, financial constraints and difficulties, market conditions, balancing needs of the ranch and the family, and planning an estate/ranch transfer. The bottom four items on the Post-Study survey were the same as the Pre-Study survey with the latter two items switching order.
3.4 Diurnal Cortisol Pattern
The average diurnal cortisol pattern exhibited by subjects over the course of the study is shown in Figure 3.1 (below). The pattern shows a clear morning rise and a distinct daytime decline. This is the typical pattern expected from healthy adults
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with a normal rhythm (Harbuz, et al., 2003). There were some gender differences in this overall pattern, which will be discussed below.
Figure 3.1 Average Diurnal Cortisol Rhythm
3.5 Cortisol, Stress, Depressive Symptoms, and Life Events
Over the six-month time-period, ranchers average BDI-II scores were significantly positively related to both their Perceived Stress Scale (PSS) scores and Life Events Scale (LES) scores (PSS: r=0.75,p<0.01; LES: r=0.56, p<0.01; Table 3.2). A scatterplot of BDI-II scores and PSS scores reveals a strong positive relationship, with a couple of outliers (Figure 3.2). The average BDI-II score over the course of
29


the study was 6.24 (s.d.=6.17). This falls in the minimal depression category, according to Beck and Steer (1996). It is also notable that the items endorsed most strongly over the course of the study were all physical symptoms: changes in sleeping pattern, loss of energy, tiredness, changes in appetite, and loss of interest in sex were the top five items endorsed, respectively.
In addition, as ranchers reported higher levels of perceived stress, they also reported a higher number of Life Events (r=0.44, p=0.023). Bonferronis correction for multiple correlation would place the value of significance at p=0.022, so this relationship should be interpreted with caution. Daytime cortisol decline (the difference between the peak value at thirty minutes after waking and the cortisol value at retiring) was inversely related to all three factors, but only approaching significance to higher PSS scores (r=-0.37, p=0.053). While the relationships are not significant, their direction is consistent with extant literature that relates chronically elevated daytime cortisol with chronic stress (McEwen, & Seeman, 1999) and depression (Sadock & Sadock, 2003).
30


i
Table 3.2 BDI-II, PSS, LES, and Cortisol Decline Correlations
BDI-II PSS LES
PSS Pearson .75 1
Correlation 1
Sig. (1-tailed) .000
LES Pearson Correlation .56 .44 1
Sig. (1-tailed) .004 .023
Cortisol decline Pearson Correlation -.23 -.37 -.11
Sig. (1-tailed) .167 .053 .328
Figure 3.2 PSS and BDI-II Score Scatterplot with Trendline
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3.6 Health Symptoms, Stress, Depressive Symptoms, and Cortisol
While endorsing higher numbers of health items (in this study, a greater number of items endorsed in the health diary implies lower overall health) did not relate significantly to greater levels of stress or depression, a greater number of life events occurring did relate to more health item endorsement (r=0.38, p<0.05; Table 3.3). Although the correlation only approaches significance, a greater number of health items endorsed related inversely with daytime cortisol decline. Morning cortisol rise was not significantly related to any of these factors.
Table 3.3 Health Items Correlations
Health Items
BDI-II Pearson Correlation .14
Sig. (1-tailed) .274
PSS Pearson Correlation .06
Sig. (1-tailed) .395
LES Pearson Correlation .38
Sig. (1-tailed) .044
Cortisol Decline Pearson Correlation -.27
Sig. (1-tailed) .128
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3.7 Regression Analyses
In Table 3.4, BDI-II scores were predicted by age, average PSS score, daytime cortisol decline, and Pre-study survey results. Together, these factors accounted for 85.4% of the variation in BDI-II scores (adj R2=0.854). The correlation coefficient was significant (F(4,15)=28.688, p<0.01). Collinearity statistics for the regression model indicated that each variable uniquely contributed to the model. The final model for this regression analysis had tolerances ranging from 0.749 to 0.993. This range indicates that the variables did not significantly interrelate and that their contributions are indeed independent. The VIF statistic corroborates this with values ranging from 1.007 to 1.336, indicating that, overall, the regression coefficients are stable. When males alone were entered into the model, these variables accounted for 95.7% of the variation (adj. R2=0.957, Table 3.5). The correlation coefficient was significant (F(4,6)=56.597, p<0.01). In this analysis, the tolerance was not quite as good, but it was within limits: 0.442-0.914. The VIF was also weaker: 1.094-2.2665. Clearly this analysis should be interpreted with extreme caution due to the small sample size. While these results are impressive considering the small sample utilized in the study, this analysis should also be interpreted with extreme caution for the same reason, only 21 subjects were in the study.
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Table 3.4 BDI-II Regression Model
Model Standardized Coefficients t Sig.
Beta
1 (Constant) -1.035 0.314
Age 0.514 2.545 0.020
2 (Constant) -6.634 0.000
Age 0.489 4.708 0.000
Average PSS 0.744 7.169 0.000
3 (Constant) -5.130 0.000
Age 0.487 4.546 0.000
Average PSS 0.753 6.540 0.000
Cortisol Decline 0.025 0.217 0.831
4 (Constant) -6.565 0.000
Age 0.491 5.578 0.000
Average PSS 0.746 7.870 0.000
Cortisol Decline 0.132 1.301 0.213
Pre-Study Survey 0.281 2.941 0.010
Table 3.5 BDI-II Regression Model with Ma es Only
Model (Males only) Standardized Coefficients t Sig.
Beta
1.000 (Constant) -0.832 0.427
Age 0.607 2.294 0.047
2.000 (Constant) -5.261 0.001
Age 0.556 4.217 0.003
Average PSS 0.704 5.335 0.001
3.000 (Constant) -1.326 0.226
Age 0.616 5.661 0.001
Average PSS 0.467 3.191 0.015
Cortisol Decline -0.344 -2.335 0.052
4.000 (Constant) -3.659 0.011
Age 0.657 9.568 0.000
Average PSS 0.336 3.414 0.014
Cortisol Decline -0.275 -2.936 0.026
Pre-Study Survey 0.296 3.476 0.013
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3.8 Population Factors
3.8.1 Age
Of the self-report measures given during the study, age of the participant was only related to BDI score (r=0.51,p<0.01). The older the participant was, the higher their BDI score was likely to be throughout the study (Table 3.6). Even after Bonferronis correction {p=0.02), this relationship is still significant.
Table 3.6 Age Correlations
Age
Pre-Study Survey -0.03
BDI-II 0.51
PSS 0.06
LES 0.15
Cortisol Decline 0.06
Health Items -0.07
Post-Study Survey -0.03
3.8.2 Gender
There was no significant gender difference on any of the main variables measured in the study. Of particular note, the BDI and PSS were stable across genders, as was daytime cortisol decline. However, the relationship of daytime cortisol decline to scores on the BDI was affected by gender; in males, higher BDI scores were related to lower daytime cortisol decline (i.e. flat rhythm; r=-0.58, p<0.05) as were higher PSS scores (r=-0.68, p<0.05) and higher numbers of life events (r=-0.61, p<0.05). None of these relationships were found in females. In terms of morning rise (the difference in cortisol levels between waking and thirty minutes after waking),
35


females tended to have a greater morning rise than males (F(l,18)=2.357, p=0.147), but this was non-significant.. This difference in morning rise between males and females is illustrated in Figure 3.3; values are expressed in nm/L. The large amount of variation in the females likely contributes to the lack of relationship. Future studies may want to re-examine whether a gender difference exists in morning rise.
gender
Error bars: 95.00% Cl
Figure 3.3 Male and Female Mean Cortisol Rise (nm/L)
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3.8.3 Ranch and Rancher Characteristics
Some relationships were found between the size of the ranch and the number of years a rancher had been on the ranch and average score on the BDI and PSS (Table 3.7). The larger the herd and the greater number of acres farmed the lower the scores tended to average on both the BDI (r=-0.43, p<0.05, r=-0.42, p<0.031) and the PSS (r=-0.44, p<0.05, -0.43, p<0.05). Additionally, lower scores on the LES were found in those who farmed larger numbers of acres (r=-0.41, p<0.05). The longer a rancher had been ranching, the higher the BDI score tended to be (r=0.46, /?<0.05); however, the PSS was not significantly related to years on the ranch (r=0.21, n.s.). After Bonferronis correction, however, only values below p=0.013 are considered statistically significant; the remaining relationships should be interpreted cautiously, especially in light of the small sample size.
It is of note that the number of years on the ranch was not significantly related to number of acres farmed (r=0.094, n.s.) or size of herd (r=0.13, n.s.), but ranchers with more acres farmed and larger herds tended to have more hired hands (r=0.60, /?<0.01, r=0.66, p<0.01, see Table 3.8). Even with Bonferronis correction, these values are still under the corrected p-value of 0.022.
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Table 3.7 Ranch Characteristics and Psychological Correlations
Size of Acres Years on BDI PSS
herd farmed ranch
Acres 0.93 0.000
farmed p (1-tailed)
Years on 0.13 0.09
ranch
p (1-tailed) 0.294 0.342
BDI -0.43 -0.42 0.46
p (1-tailed) 0.025 0.031 0.019
PSS -0.44 -0.43 0.21 0.75
p (1-tailed) 0.022 0.027 0.182 0.000
LES -0.30 -0.41 0.36 0.56 0.44
p (1-tailed) 0.096 0.033 0.056 0.004 0.023
r able 3.8 Ranching Characteristic Correlations
Size of Acres Years on
herd farmed ranch
Acres farmed Pearson Correlation .93
Sig. (1-tailed) .000
Years on ranch Pearson Correlation .13 .09
Sig. (1-tailed) .294 .342
Number of hired Pearson .66 .60 .31
hands Correlation
Sig. (1-tailed) .001 .002 .087
3.9 Coping Styles
The most frequently utilized coping mechanisms were changing ones attitude (x =2.59, s.d=0.87) and establishing priorities (x=2.71, s.d.=0.98). Least commonly endorsed were making a list of worries (x=0.24, s.d.=0.44) and consuming alcohol
38


(x=0.65, s.d.=0.93). Figure 3.4 summarizes the frequency of coping style utilization.
For two of the coping styles, talk about it and consume alcohol, there was a significant effect of gender. Females were significantly more likely to utilize talking as a coping style (t( 15)2.526, p<0.05) and males were more likely to consume alcohol to cope (t(15)=-2.898,p<0.05).
Error bars: 95.00% Cl
Figure 3.4 Coping Mechanism Utilization (0=never, 2=sometimes, 4=very often)
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4. Discussion
The hypotheses explored in this study predicted that high, medium and low stress periods would be associated with hypothesized differences in levels of stress and depression, stress and symptoms of depression would exhibit a positive relationship, dysregulated cortisol would be related to both increased depressive symptoms and stress, and that lower levels of general health would be exhibited during periods of higher stress (i.e. increased number of symptoms endorsed on symptom checklist). Although the present data did not clearly establish the relationships originally hypothesized, the findings of this study generally support previous research examining the relationship between stress and depression. This suggests that the interaction of these variables in ranchers is similar to their relationship in the other human populations studied.
The positive relationship between PSS scores, BDI-II scores, and number of life events observed in ranchers is consistent with previous research. Higher numbers of life events have been found to precede the onset of depressive episodes, though this relationship is strongest for the first episode (Sadock & Sadock, 2003). Additionally, psychosocial stress has been shown to be a trigger for the onset of depression (Tafet & Bernardini, 2003). Cohen and colleagues (1983) found a significant positive relationship between number of life events and scores on the PSS; this was replicated in the present study. In this way, the relationship among
40


these three factors in the ranching population is consistent with research with other populations. While this study did not examine major depressive disorder, per se, the positive relationship found between depressive affect and psychological stress indicates that ranchers experiencing higher levels of psychological stress may be more vulnerable to depressive symptomatology.
The Pre- and Post-Study survey revealed that, despite the difference in time of year when the surveys were administered, machinery problems, market conditions, and financial constraints and difficulties topped the list of constant stressors for ranchers. The first two items are uncontrollable factors and the final item is inherent to the profession, but nonetheless is stressful. The ranchers found isolation, being involved in a parent/child operating agreement and accidents and injuries to be the least stressful, year-round. Perhaps these items are more in the control of the ranchers; they can adjust how many people they interact with or whether they work with their parents/children. Accidents and injuries are not necessarily always controllable, but being mindful of the dangers of large equipment is certainly a preventive measure. Despite these similarities in the Pre- and Post-Study survey results, they were also quite disparate in many of their other results. For future studies, modifications that make the survey less susceptible to seasonal variation are recommended. This would improve the validity of the survey, as its primary objective is to measure year-round stressors; susceptibility to season would damage this goal.
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The lack of relationship between number of health items endorsed and scores on the PSS, BDI-II, and daytime cortisol decrease was surprising, as a relationship between general health, stress, depression, and HPA dysregulation has been established (Sapolsky, 1998). However, the results for this item should be interpreted with great caution as participant cooperation for maintaining accurate health diaries was questionable. Several ranchers reported forgetting to fill them out; so the missing data certainly skew the results. In future studies, emphasizing the importance of filling this diary out and reminding the participants would be advised.
The prediction of BDI-II scores by age, PSS scores, average daytime cortisol decline, and pre-study survey results was quite robust. While the relationship between age and BDI-II scores contrasts previous research (Steer, Rissmiller, & Beck, 2000), epidemiological studies show that the onset of MDD can occur throughout the lifetime (Sadock & Sadock, 2003). Additionally, higher Pre-Study survey results predicted higher BDI-II scores in this model, which could indicate that a higher baseline level of stress (that is, not including the additional stressors occurring with the different seasons) could be a risk factor for the onset of depression in ranchers.
Of note are the gender differences found for the relationship of daytime cortisol decline to BDI-II scores, PSS Scores and Life Events. In this study, lack of cortisol decline was related to higher BDI-II scores and PSS scores in men, but not
42


women. Additionally, a higher morning rise was found in women, though this only approached significance. In a study examining positive and negative affect as traits, Polk and colleagues (2005) found that men high in trait negative affectivity (which is associated with affective responses with negative valence) tended to have a high, flat cortisol rhythm. This flat rhythm is consistent with the finding in our study that male ranchers reporting a higher level of stress and depression tended to have flatter rhythms. In addition, the finding that females tended to have a greater morning rise, though only approaching significance, corroborated the results of previous studies (Kunz-Ebrecht, et al., 2004), where women had a greater morning rise on work days. For ranchers, the typical 5-day week does not apply, and unless they take a vacation, every day is a work day. Kunz-Ebrecht and colleagues (2004) found no difference in morning rise between genders on weekend days, and attributed this to the fact that during the week, females tended to have more domestic responsibilities than males and on the weekend this is not the case. Perhaps in ranching families, the wife is expected to provide meals and care for the children in addition to ranching. Future research could focus on identifying differences in gender roles on the ranch and their mediating effects on stress and cortisol levels. Another consideration factor when exploring the relationship between cortisol and stress is that different types of stress could elicit differential responses in males and females. Stroud, Salovey, and Epel (2002) found that men had a greater cortisol response to
43


achievement stress whereas women responded more than men to social rejection challenges.
The lack of a difference between genders for scores on the PSS and BDI-II is also notable. Studies have shown that females tend to score significantly higher than males (Arnau, et al., 2001; Beck & Steer, 1996); however, this is also not consistent, as Dozois, and colleagues (1998) found no significant effect of gender on BDI-II scores among college students. Clearly, a gender difference has not be consistently established across all populations, but an examination of the epidemiology of MDD shows that females are twice as likely to be diagnosed in their lifetimes as males (Sadock & Sadock, 2003). In terms of perceived stress, Farabaugh and colleagues (2004) found significantly higher levels of perceived stress among depressed outpatients. Cohen and colleagues (1983), however, found no effect of gender on PSS scores in their college student population. Perhaps there is a difference between non-clinical and clinical populations. Maybe in the general population (ranchers and college students, for instance), the perception of stress is not specific to gender, but in clinical populations, high levels of stress interacting with gender could play a significant etiologic role, especially since depression is twice as common in females.
No previous studies have examined the relationship between the size of an operation, number of years working on that operation, and levels of stress and depression in ranchers. The preliminary findings from this study suggest that
44


ranchers with larger operations tend to report lower levels of stress and depression. This phenomenon may be, in part, due to the fact that as operations get larger, they tend to have more hired hands and work is dispersed. In smaller operations, generally one or two individuals do the work. When these two individuals are related, additional friction could result; previous research has shown that multigeneration ranching operations have the added stress of differential perceptions of support within the family and transition factors (Weigel R.R., Weigel, D.J., & Blundall, 1987). Interestingly, the greater the number of years one has worked on a ranch, the higher the scores on the BDI-II and PSS tended to be. Part of this relationship can be explained by age; age was one of the predictors for higher BDI-II scores. Additionally, it is possible that age-related declines in abilities also contributed to higher ratings on these scales; however, this was not specifically addressed in this study and should be investigated in future research.
Finally, the coping styles survey revealed that ranchers primarily changed their attitudes and established priorities when they were feeling stressed. Only one maladaptive coping mechanism (consuming alcohol) was on the survey, and was infrequently endorsed; however, those who endorsed this item tended to be male. This is consistent with epidemiological data showing that men are more likely to have alcohol abuse disorders than women (Sadock & Sadock, 2003). Women were more likely to talk to others about their problems in this study. This is also consistent with a Canadian study examining coping strategies in the general
45


population (Wang & Patten, 2002). In constrast, a study examining coping strategies used in farm families found no gender effect for using talking to others as a coping mechanism (Weigel, R.R. & Weigel, D.J., 1987). Weigel. & Weigel (1987) also found that every family endorsed turning to faith. Faith was commonly endorsed in this study, but not invariably.
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5. Limitations and Future Directions
While the present study has elucidated some intriguing relationships among stress, depression, and diurnal salivary cortisol rhythms, several limitations need to be considered when interpreting these results. First, the initial proposed methods for this study proved to be ineffective, resulting in averaging the data across the time period instead of comparing stress periods. Individual variation prevented clear delineation of high and low stress periods. Asking the ranchers to identify typical high, medium, and low stress times for the six month period at the beginning of the study was problematic, in that the ranchers predictions were often incorrect. In general, their predicted stress was higher than their actual stress level. This is an important consideration. Perhaps when attempting to predict their future stress levels, the most salient memories of those time periods are events that were stressful and isolated stressful days. When the ranchers actually experience that time-period, the day-to-day stress level and coping with daily stressors does not seem as bad as when they consider the season as a whole. When originally designing this study, the idea of allowing ranchers to individually identify periods of relative high, medium, and low stress was based on the assumption that different ranchers are likely to perceive the various seasons differently. For this reason, ranchers were not required to take their saliva samples during the same three two-week periods to
47


compare seasonal differences, because individual differences were thought to confound this relationship. Indeed, in the present study, some found haying to be the most stressful period during the six months and others found it to be enjoyable or even relaxing. Perhaps for future studies, with larger populations, pre-selecting the times to take measurements would be desirable. Then, individual differences can be explored within those seasons. The organization of the present study does not allow for this exploration because the time periods are scattered.
Another limitation to this study is the small sample size and limited community from which the sample was taken. Most of the participants for the study lived in one city in Western Colorado and the few participants who did not, lived less than 100 miles away. While extrapolation of the present study results to the general ranching population would be erroneous, these results provide some insights into potential relationships and perhaps also a starting point for future studies.
Future studies that include samples from different parts of the country would be desirable. In addition, several couples participated in the study; the confounds of this were not explored due to the already small sample size. It may be advantageous to have as many couples as possible participate in future studies, as the shared experiences could be important for exploring gender effects on differential stress and depression ratings.
Sampling bias also needs to be considered. Many ranchers chose not to participate in the study. It is possible that the ranchers who participate represent a
48


unique population within the community. Ranchers who did not participate may be more or less stressed or even exhibit a different relationship among the variables examined. This is certainly a risk that all studies face due to their voluntary nature.
Finally, the cross-sectional nature of this study is also limiting. Longitudinal studies examining the changes in stress, depression, and cortisol are needed to fully understand how the interaction of these variables changes across the lifespan. To develop appropriate interaction strategies for this population it is essential to understand not only gender effects, but also age effects. Stressors and risk factors for depression in younger men may differ substantially from those factors that place older men at risk.
The purpose of this study was to identify the relationship between stress, depression and diurnal salivary cortisol. While some significant relationships were found in this pilot study, many questions remain. To fully understand how these phenomena interact in the ranching community, a longitudinal perspective is needed. In addition, many ranching households are multi-generational, so the family dynamic should also be explored further. Future studies might examine the concept of allostatic load in ranching populations, as it has important implications for health outcomes. The combination of repeated stressors and predominantly middle to lower SES could contribute to allostatic load in ranchers and play a role in long-term morbidity and mortality. While stress and depression are phenomena
49


shared by all humans, it is important to understand how niche populations experience them and cope.
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Appendix A. Monthly Stress Level Questionnaire
Monthly Stress Levels PartlcpamlD "
For each month, please indicate your- relative level ot stress on a sale ofl to 7 Ominimal stress, 7=maximum stress). Additionally, please indicate which activity or activities you are doing during that period, if there is greater than one activity and/or stress level for a given month, please indicate it in the space provided and markon the calendar the approximate date(s) the activities change. Thank you!
July 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 August 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 September 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Averaee Stress Level!s): Average Stress Levells): Average Stress Levells):
Activitx(ies): Activitv(ies): Activitvlies):


Comments:
October 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 November 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 December 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Average Stress Levells): Average Stress Levells): Average Stress levells):
Activitv(ies): Activitvlies): Activitvlies):


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Appendix B. Pre-/Post-Study Survey
Post-Study Survey
Stress throughout the Year
From the list below, please indicate which items are stressful to you throughout the year, and circle the relative level of stress (1 = little stress, 2=moderate stress, 3=high stress).
1. Balancing the needs of the farm/ranch with the
needs of the family 1 2 3 NA
2. Being involved in a parent-child operating agreement 1 2 3 NA
3. Farm/ranch accidents or injuries 1 2 3 NA
4. Government policies 1 2 3 NA
5. Having to compete for additional land 1 2 3 NA
6. Financial constraints or difficulties 1 2 3 NA
7. Illness at peak times 1 2 3 NA
8. Irregular cash flow 1 2 3 NA
9. Isolation 1 2 3 NA
10. Problems with machinery (breakdown, repairs, buying new machinery) 1 2 3 NA
11. W eather co nd itio ns 1 2 3 NA
12. Working with bankers and loan officers 1 2 3 NA
13. Market conditions, as they affect profit 1 2 3 NA
14. Facing retirement from ranching/farming (or) taking over the farm/ranch 1 2 3 NA
15. Transfer of farm and responsibilities to a new 1 2 3 NA
generation/planning an estate
This questionnaire has been adapted from the Daily Work In yen tors and Fann Work Stress Seale (Courtesy Iowa State Cooperative Extension Service). Fann/Ranch Stress Scale" published in: Carson, D.K., etal. (1993). Manliness asa Mediator of the Effects of Stressors and Strains on Reported Illnesses and Relational Difficulties in Fann and Ranch Fam Hies 9 (3 i. 215 -226.. and a research panel survey done bx Successftl Fann ing magazine.
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Coping Styles Survey How do you Handle your stress?
Much of this study has focused on the negative aspects ofstress: feelings, thoughts, depression, and health issues. Now, I am inte rested in how you alleviate the negative aspects when you feel stressed. Many people have multiple strategies that they use, some often and others only occasionally. Please examine the list below and indicate how frequently you use a p a rtic u la r s trategy when you are feeling stressed (0= neve r to 4=very often).
When lam feel in a stressed. 1: 0 never 1 aim o st never 2 som etim es 3 fairly ofte n 4 vet o fte
1. Talk with others about it 0 1 2 3 m 4 G0 C n
2. Make a worry list" and include steps to cope with the worst that could happen 0 1 2 3 < 4 ^
3. Take a work break 0 1 2 3 4
4. Change a work activity for a short period of tim e 0 1 2 3 4
5. Establish realistic priorities and goals in life 0 1 2 3 4
6. Consume alcohol 0 1 2 3 4
7. G et m ore sleep or rest 0 1 2 3 4
8. Develop a positive m ental attitude 0 1 2 3 4
9. Turn to faith/spiritual beliefs 0 1 2 3 4
Appendix C. Coping Styles Survey


Please indicate how often you participate in the following activities for leisure or relaxation:
Never Once a year 2-11 times a year Once a month 2-3 times/month Once a week 2-6 times a week Every day
1. Dancing D
2. Eating out
3. Exercise program O
4. Gardening/Yard Work
5. Handicraft/Hobbies/ Music O O
6. Reading
7. Shopping for pleasure
8. Social activities
ft Sports/games -participate
10. Sports spectator
11. Travel for pleasure o
12. TV
13. Movies
14. Reiigion/church activities
Adapted from Successful Farming Magazine's Market Research Panel Survey (1999).
Appendix D. Leisure Activities Questionnaire


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Full Text

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AN INVESTIGATION INTO THE RELATIONSHIP BETWEEN STRESS, DEPRESSION, AND DIURNAL SALIVARY CORTISOL IN WESTERN COLORADO RANCHERS by Emily Ann Schulze B.A., Western State College, 2003 A thesis submitted to the University of Colorado at Denver in partial fulfillment of the requirements for the degree of Master of Arts Psychology 2005 ,. [/J ..........

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The thesis for the Master of Arts degree by Emily Schulze has been approved by Mary CoussonsRead ...... \ Mark L. Laudenslager Date

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Schulze, Emily Ann (M.A., Psychology) An Investigation into the Relationship between Stress, Depression, and Diurnal Salivary Cortisol in Western Colorado Ranchers Thesis directed by Assistant Professor Mary Coussons-Read ABSTRACT Stress is a part of the human experience. Different lifestyles, however, are exposed to different types of stressors. the ranching community, many of the stressors are uncontrollable (i.e. weather and market conditions). The experience of uncontrollable stress has been shown to elicit a chronic stress condition in animal models. Related to stress, depression is a common condition. Research has demonstrated both cognitive and physiological connections between these two phenomena. Cognitively, learned helplessness is an etiologic model for depression, which is related to the perceived lack of control over a situation seen in chronic stress. In addition, disruption of the hypothalamic-pituitary-adrenal axis (HPA axis) is related to chronic stress and found in about half of those diagnosed with major depressive disorder (MDD). Disruption of the HPA axis in these conditions results in blunted cortisol feedback inhibition which leads to chronically elevated cortisol levels. The purpose of this study was to ascertain the relationship among the variables of perceived stress, depression, and salivary cOltisol in ranchers. We hypothesized that increased levels of stress would be positively related to higher depression ratings and increased cortisol levels In this study, ranchers were asked to collect saliva samples and maintain health diaries over three separate 2-week periods. At the end of each of these two week periods, the Beck Depression Inventory-II (BDI-II) and Perceived Stress Scale (PSS) were administered. Twenty-

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one ranchers participated in the study (12 male). Results showed a strong relationship between BDI-II and PSS scores (r=0.748, p
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DEDICATION I dedicate this thesis to James L. Vela whom I admire and respect for his steadfast devotion to a life he loves. He has not only taught me many things about ranching, but he has also given me perspective on living life.

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ACKNOWLEDGEMENT My heartfelt thanks to Dr. Mary Coussons-Read for her advice and support, which not only made this project possible, but also made it a positive and enlightening experience Additionally, Dr. Mark Laudenslager and his lab were instrumental in the collection, extraction, and interpretation of the saliva samples. Finally, the ranchers who chose to participate in this study gave it depth and, beyond the data collection, gave me insights into their unique lifestyle.

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CONTENTS Equations ................................................................................................................. x Figures ............... ................ ............ ......................... ....... ................ ................... xi Tables ................. ................................ ..... ... ...... ..... ..... ....... .... .......... ............... xii Chapter 1. Introduction ................................. ........................ ........................ .................... 1 1.1 Stress and the Ranching Population ................................................................. 2 1.2 Perceived Stress and Appraisal ........................................................................ 5 1.3 The Stress Response ......................................................................................... 6 1.4 Allostatic Load ............................................................................................... 10 1.5 Stress and Depression ..... ................................................................................ 12 1.6 Goals and Hypotheses .......... .......................... ....... ........................................ 14 2. Methods ...................................................................... .... ......... ...................... 16 2.1 Participants ............................................................................ ........................ 16 2.2 Recruitment Procedures .................................................................................. 16 2.3 Study Protocol ................................................................................................ 17 2 .3.1 Study Location ............................................................................................. 17 2 3.2 Human Subjects Approval.. ......................................................................... 17 2.3.3 Activities Involving Subjects ...................................................................... 17 2.4 Instruments and Sampling Techniques ........................................................... 19 vii

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2.4.1 Beck Depression Inventory-II ..................................................................... 19 2.4.2 Perceived Stress Scale (PSS) ....................................................................... 19 2.4.3 Life Events Scale (LES) .............................................................................. 20 2.4.4 Saliva Collection ......................................................................................... 20 2.4.5 Salivary Cortisol Extraction ........................................................................ 21 2.4.6 Pre-fPost -Study Survey ............................................................................... 22 2.4.7 Coping Styles Survey and Leisure Activities Questionnaire ...................... 24 2.5 Statistical Analysis ......................................................................................... 24 3. Results ............................................................................................................... 27 3.1 Population Statistics ................... .... .................... ................. ..... ................ ... 27 3 2 Predicted Stress and Actual Stress Relationship ............................................ 27 3.3 Preand Post-Study Survey Results ............................................................... 28 3.4 Diurnal Cortisol Pattern ............................... .... ............................. .................. 28 3.5 Cortisol, Stress, Depressive Symptoms, and Life Events .......... .... ................ 29 3.6 Health Symptoms, Stre ss, Depressive Symptoms, and Cortisol .................... 32 3.7 Regression Analyses .............. ..... ....... ....... ................... ............................. 33 3 8 Population Factors ...................................................................... .... ............... 35 3.8.1 Age .............................................................................................................. 35 3.8.2 Gender .............................................................................. .......................... 35 3.8.3 Ranch and Rancher Characteristics ............................................................. 37 3.9 Coping Styles ......... ...... ....... .... .................................................... ...... .............. 38 VlJl

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4. Discussion ..... ....... ............................... ............. .................... ....... .............. .... 40 5. Limitations and Future Directions ....................... ... .............. .... ....................... .47 Appendix Monthly Stress Level Questionnaire ............................. ................................. 51 B. Pre-lPost-Study Survey .................................................................................... 52 C. Coping Styles Survey .................... ....................... ... ........................................ 53 D Leisure Activities Questionnaire ..................................................................... 54 Literature Cited ..................................................................................................... 55 lX

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EQUATIONS Equation 2.1 Bonferroni' s Correction ...... ..... ................................................................... 26 x

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FIGURES Figure 3.1 Average Diurnal Cortisol Rhythm ............................... ....... .. ................. ........ 29 3.2 PSS and Score Scatterplot with Trendline ..... ....... ...... .... ......... .......... 31 3.3 Male and Female Mean Cortisol Rise (nmlL) .............. .. ................................ 36 3.4 Coping Mechanism Utilization (O=never, 2=sometimes, 4=very often) ...... .. 39 Xl

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TABLES Table 3.1 Population Demographics .............................................................................. 27 3.2 BOI-II, PSS, LES, and Cortisol Decline Correlations .................................... 31 3.3 Health Items Correlations ............................................................................... 32 3.4 BDI-II Regression Model ............................................................................... 34 3.5 BDI-II Regression Model with Males Only ................................................... 34 3.6 Age Correlations ............................................................................................. 35 3.7 Ranch Characteristics and Psychological Correlations .................................. 38 3.8 Ranching Characteristic Correlations ............................................................. 38 Xli

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Stress has affected all people and animals since life began The term "stress" was originally defined by a pioneering researcher, Hans Selye, as "the rate of all the wear and tear caused by life" (Selye, 1956). Another more biological definition describes stress as any threat to the body's homeostasis (Nelson, 2000). is also recognized in human research that an event that is stressful to one person, may not cause any stress to another; therefore, perception of the stimulus is also important in modulating the stress response (Sapolsky, 1998). Many studies across a variety of populations have shown that stress has an effect on general health. These populations include healthy adults, breast cancer patients, caregivers of patients with Alzheimers, surgical patients, and AIDS patients, among others (Kielcolt-Glaser, Marucha, Malarkey, Mercado, Glaser, 1995; Kie1colt-Glaser, Page, Marucha, MacCallum, Glaser, 1998; Nelson, 2000; Vedhara, et aI., 1999). Although the effects of stress on health have been studied in numerous urban-dwelling populations, fewer studies have addressed these effects in rural populations, such as farmers and ranchers. The importance of these populations to the Colorado and national economy should not be underestimated. Increasingly, more researchers are becoming interested in understanding the unique stressors and challenges faced by American farmers and ranchers. the present study, the

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relationship between psychological stress, depression, and a measure of physiological stress is examined in ranchers to further the knowledge of the effects of stress on human health. Stress As in the general population, the ranching population commonly experiences stress; however, the form and types of stress experienced by ranchers differs markedly from that found in urban populations In contrast to many five-day-a-week occupations, farmers and ranchers work on a daily basis, many for over 10 hours per day (Gregoire, 2002). In addition, their work changes on a seasonal basis, where activities in January are vastly different from those in July and also those in September. Unpredictable stressors such as disease and weather plague farmers in addition to problems with animals and machinery. Farmers tend to live and work with their families, often with multiple generations, and stress between family members is common (Weigel Weigel, 1990). Stressors affecting multigenerational households include issues of equality, concerns about teamwork, differences in values, and competition (Weigel, D. Weigel, R., 1990). Physical ailments are also a source of stress among farmers, especially among older farmers who may be unable to continue their work (Gregoire, 2002). Almost a third of farmers under age 50 report having physical difficulties that interfere with their work (Simkin, Hawton, Fagg, Malmberg, 1998). Many sources of stress lead to 2

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farmers feeling fatigued, anxious, and depressed (Tevis, 1982). Financial difficulties also permeate farmers' lives (Simkin, Hawton, Fagg, Malmberg, 1998; Gregoire, 2002). While the population living in the city and farmers share many common stressors, ranchers clearly have a unique set of stressors, many of which are uncontrollable, with which to deal. Ranching is an occupation characterized by many stresses that come about at different times of the year. In the spring, for some ranchers in Western Colorado, calving, or birthing, season can cause significant stress and depression, depending on whether or how many cows or calves are lost in the process. Cows (especially heifers) must constantly be observed for signs of difficulty with the birthing process. As spring moves towards summer, the land must be cultivated and prepared for planting. Depending on the winter's snowfall, the ranchers must calculate how many fields they can sustain throughout the summer. This can be stressful, especially if the winter has been dry, in which case arrangements must be made to purchase hay or corn that cannot be grown. During the summer, haying and management of crops is occurring. Haying includes cutting, baling, and stacking the hay. Some ranchers own grazing permits on National Forest or Bureau of Land Management land. If they do own permits, they bring their cows to those areas during the summer to graze. Fences on the grazing permit should be mended to make sure that they will hold the cows in the right areas. The cows and their new calves are taken to the mountain grazing area around June.

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Throughout the summer, salt is often distributed on the grazing permit to keep the cows from over-grazing. In the later summer, corn harvesting (if applicable) occurs. In OctoberlNovember, cattle return from the higher country. During this time, many trips are made with the trailer to pick up cattle. This is not necessarily stressful, unless many cows are returning without their calves, or many cows are missing. In addition, it is common that the ranchers ride horses on the mountain to speed the cows' descent for the winter. This may be stressful, since ranchers must cover thousands of acres to gather their cows. The threat of losing cows to early snow can also be stressful. After gathering, many ranchers wean the calves from their mothers and send them to feedlots. The financial situation is determined by cattle prices and this can either be a stress-relief or a significant strain if it is a bad year. Then, ranching slows down for the winter in December and January. At this point, equipment is winterized and repairs are also made. Organization for the next year may take place. February brings the beginning of calving season once more. The anecdotal ranching scenario above shows that there is a seasonal aspect to ranching that may modulate levels of depression and stress and thus may have implications for overall health in this population. In the farming and ranching community, many factors contribute to overall stress. In addition to the stress of depending on the market for income, the weather for crop yield, and the labor involved in a successful operation, farmers and

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ranchers endure unique stressors compared to urban populations. Stressors in farm and ranch families include psychosocial factors (farm/family competition, job tasks, money, and childrearing), decision making, and income disparity between generations working in the operation (Weigel, D. & Weigel 1990). These stressors may be especially salient in two-generation households (Weigel D. & Weigel 1990; Weigel, et aI., 1987). However, farmers and ranchers also experience generic stressors universal to humans including family disputes. Carson and colleagues (1993), found that greater reported hardiness (defined as internal strength and durability of a family) buffered negative effects of stressors and strains in farming families. Many factors contribute to perceived stress in farm families, due to mediating effects of hardiness as well as coping strategies (Weigel, D. &Weigel 1990). According to Lazarus and Folkman, the cognitive appraisal of a situation dictates the consequent stress response (1984). Individuals who take an approach, characterized by effortful coping tend to activate the sympathetic nervous system more predominantly. Conversely, those who take a approach perceive a loss of control and feel helpless. This population tends to activate the HPA axis more readily. Repeated, chronic exposures to stress in the population could therefore result in depression, among other psychiatric and physiological disorders. 5

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Along the lines of appraisal and personality characteristics, some have proposed a diathesis-stress model of depression, where the diathesis is a negative attributional style a negative attributional style, individuals tend to view stressors as more damaging or reflective of personal weakness than those who do not exhibit this cognitive style (i. e a failed date results in the thought, "Nobody wants to be with me.", Kwon Laurenceau, 2002). this model, differential reactivity of individuals (that is, some approach stressors with a negative appraisal and others do not) may affect the threshold for developing a depressive syndrome. Those with negative attributional styles will be more vulnerable to depression. Many factors can modulate the development of a negative attributional style including personality characteristics and frequency and types of stressors experienced; however, a discussion of those factors is beyond the scope of the current paper. Kwon and Laurenceau (2002) did demonstrate, however, a significant relationship between negative attributional style and increased depressive reactivity to stressors over time Perceived stress is only one aspect of the stress condition in humans; the physical stress response has ubiquitous effects on the body. Formal research on the physiological stress response began in the 1920' s with Walter Cannon. Cannon took an interest in the connection between stres s and disease. He explored the 6

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"fight or flight" response model in rodents. This response activates the sympathetic nervous system and leads to the release of epinephrine by the adrenal gland. While this system is useful for animals escaping predators, its chronic activation can lead to cardiovascular disease in humans (Sadock Sadock 2003). Modern stress response research was pioneered by Hans Selye the 1940's (Nelson, 2000). Selye's work elucidated a second class of endocrine hormones that respond to stress: glucocorticoids, which are also released by the adrenal gland (Sapolsky, 1992b ) Seyle described the "general adaptation syndrome," as a three-stage response to stress, which included: (1) the alarm reaction, in which the stressor challenges homeostasis; (2) the stage of resistance, during which one adapts and successfully deals with the short-term insult and (3) the stage of exhaustion, during which resistance or adaptation is lost, and disease occurs (Sadock Sadock, 2003; Sapolsky, 1992b). Selye's model was not entirely accurate; scientists have found that instead of the body becoming exhausted and not producing as much cortisol or epinephrine it is actually the fact that the body continuously produces these substances that leads to the disease state (Sapolsky, 1992b). While adaptive over short time-spans, long-term increased circulation of these substances is deleterious. The hypothalamic-pituitary-adrenal axis (HPA axis) is a key player in the stress response. The hypothalamus, located in the forebrain, just below the thalamus, monitors the environment and regulates the hormones sent to the body by the pituitary, depending on environmental stimuli (Pinel, 2000; Sadock Sadock, 7

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2003). Emotions also have an effect on the activity of the hypothalamus. In the stress response, the hypothalamus releases corticotrophin-releasing hormone to the pituitary, which releases adrenocorticotrophic hormone (ACTH). ACTH circulates in the blood stream to the adrenal glands where it promotes production of glucocorticoid hormones, such as cortisol. These hormones affect cardiovascular function and renal function and metabolism and, synergistically with the nervous system, adjust our response to the environment (Padgett Glaser, 2003). When a person experiences stress chronically, however, this system can have negative effects on general health and make one more susceptible to infectious diseases (Glaser, et aI., 1999; Padgett Glaser, 2003). In healthy, low-stress individuals, cortisol levels exhibit a diurnal pattern of a morning peak and a decline toward evening (Harbuz, et aI., 2003). In general, cortisol levels rise in the first 30-40 minutes after waking and then decline steadily throughout the day (Pruessner, et aI., 1997). Certainly, this diurnal variation is subject to individual differences and is also affected by age and gender. Ice and colleagues (2004) studied diurnal cortisol patterns in older adults and found that caffeine had a significant impact on regularity of circadian rhythms and patterns of cortisol. Interestingly, they also found the older subset of the group had more regular cortisol patterns than the younger subset. The diurnal pattern is also responsive to acute stressors (or challenge); cortisol levels typically peak after exposure to an acute stressor. This diurnal 8

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pattern may be observed in saliva as well as blood. Cortisol is found in saliva in its biological free state, representing 1-10% of total as measured in the blood (Kirschbaum Hellhammer, 1989). Studies show that younger men show greater cortisol response to challenge compared to younger women, but this is reversed in the elderly (Seeman, et ai., 2001; Seeman, et aI., 1995). In a study examining acute laboratory-induced stress, Kudielka and colleagues (2004) found that bioavailable free cortisol patterns did not differ between ages, but a gender effect was seen in older men, whose response was elevated The results also suggest a heightened hypothalamic drive in younger men that attenuates with age, which results in similar ACTH responses in elderly men and women. It appears as though younger women have greater adrenal cortex sensitivity. Under conditions of chronic stress, cortisol levels tend to be elevated due to dysregulation in the HPA axis. addition, the diurnal pattern may become disrupted. The awakening cortisol response (seen in the first 45-60 minutes after waking) has been used as a marker of stress, but not all of the research has been consistent (Clow, Thorn, Evans, Hucklebridge, 2004). Flatter diurnal cortisol patterns (smaller differences between peak morning levels and evening levels) have been related to higher mortality in breast cancer patients, maltreated children, and those with poor relationship functioning (Sephton, Sapolsky, Kraemer, Speigel, 2000; Hart, Gunner, Cichetti, 1996; Adam Gunnar, 2001 Edwards, Hucklebridge, Clow, Evans, 2003) 9

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Related to dysregulated diurnal rhythms, chronic stress can also result in elevated cortisol due to malfunctioning negative feedback loops (Tafet Bernardini, 2003). Constantly elevated levels of cortisol may result in cardiovascular disease (e.g. atherosclerosis) and visceral deposit of adipose tissue. cases of chronically, severely elevated cortisol, the development of Cushing's disease may result (Miller O'Callaghan, 2002). Chronic stress has also been shown to increase susceptibility to acute stressors or threats (such as viruses or bacteria) to an individual's health (Glaser, et aI., 1999). Other pathological effects of chronically elevated cortisol include fatigue, steroid diabetes, peptic ulcers, impotence, and accelerated neural degeneration during aging (Sapolsky, 1992a). Selye found that rats responded to different stressors with the same glucocorticoid response; that is, he thought the stress response was nonspecific (Sapolsky, 1992b). This is not the case, however, as different patterns of secretion are found for different stressors (Sadock Sadock, 2003; Sapolsky, 1992b). addition, individual differences (genetic, personality, and social) can also contribute to differences in glucocorticoid profiles (Sapolsky, 1992b). These factors need to be kept in mind when evaluating stress research. Allostatic load is a term by B.S. McEwen (1998) to conceptualize the cumulative biological burden exacted on the body in its attempts to adjust to life's demands.

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other words, allostatic load examines the wear and tear on a body over the lifespan that results from threats to homeostasis, or stressors. According to McEwen, the level of exposure to stress mediators in response to stressors may interact with individual differences (genes, childhood trauma, experiences), which moderate one's coping mechanisms. Over a lifetime, the accumulation of stressors coupled with individual adaptability exacts a price, in the form of a disease state or even death (McEwen Seeman, 1999). Allostatic load reflects not only experience, but individual health and diet habits, genetics, behavior patterns (coping mechanisms), and early childhood experiences. McEwen has also explored the role of socioeconomic status (SES) in risk differences and has established that gradients in SES have significant implications for health. And abuse in childhood has been shown to result in neurochemical imbalances in adulthood (McEwen Seeman, 1999). Allostatic load has been operationalized as a set of physiological parameters that are pertinent to disease risk such as blood pressure, urinary cortisol, waist/hip ratio and cholesterol levels (Seeman, Singer, Ryff, Love, Levy-Storms, 2002). McEwen (1999) emphasizes that allostatic load is more than chronic stress, but encompasses the many other factors discussed above, such as genes and diet. sum, the concept of allostatic load is an important aspect of stress research that explores the long-term morbidity and mortality aspects of lifetime stressors. In the ranching population, an exploration of the concept of allostatic load as it affects

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ranchers would be important for long-term health outcomes, especially in light of the relative paucity of health care resource s in rural areas As seen in the population suffering from chronic stress, cortisol level s remain constantly elevated in many patients with depression; that is, glucocorticoid receptor sensitivity is lower in depressed patients, leading to a failure to suppres s cortisol production (Modell, et aI., 1997 as cited in Harbuz, et aI., 2003); however, HPA dysregulation is only found in about half of tho s e diagno s ed with MOD (Sadock Sadock,2003). A s mentioned above, these constantly elevated cortisol levels have a negative affect on general health. Stress and depression may both negatively affect a person's general health and well-being. Stress and depression may thus be related in terms of their potential physiological consequences. Not only are stres s and depression linked by physical symptoms, but statistically, the stress and the onset of depression go together (Sapolsky, 1998). This relationship is especially strong for a person s first episode (Sadock Sadock, 2003). Like stress, depression affects a large percentage of the population (Sadock Sadock, 2003). Depression is a heterogeneous phenomenon that affects million s of people throughout the world, with a lifetime prevalence of about 15 percent (Sadock Sadock 2003). According to OSM-JV diagno s tic criteria, major depressive disorder (MOD) is characterized by symptom s including depressed

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mood, anhedonia, weight gain or loss, appetite disturbance, sleep irregularities, energy loss, feelings of worthlessness, diminished ability to concentrate, psychomotor agitation or retardation, and recurrent thoughts of death (APA, 2000). Depressive syndromes have been described in texts dating back to 400BC, when Hippocrates described mental disturbances using the terms "mania" and "melancholia." In Rome, the physician Celsus described melancholia as depression caused by black bile (Sadock &Sadock, 2003). Today, depression is still a major topic of research, with a variety of etiologic theories and types of presentation. Authors disagree on whether there is a difference in rural and urban incidence of depression. It is difficult to compare studies, as some examine depressive symptomatology, and others examine number of people who qualify for a diagnosis of MDD. For instance, Wang (2004) found no difference in rural and urban prevalence of major depressive episodes in rural Canadians in the 12 months before the study, but after controlling for race, age, and social status, urban areas were found to have a significantly higher prevalence. This was consistent with a study done in the United Kingdom by Thomas and colleagues (2003), who found a higher rate of suicidal thoughts, but a lower prevalence of psychiatric morbidity in farmers compared to urban dwellers. Patten and colleagues (2003) also found higher rates of depression among Canadian urbanites, which they attributed to street drugs, social support deficits, unemployment, and recent life events. Conversely, other sources cite a higher rate of depression in rural areas (Sadock & Sadock, 2003;

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Roberts Lee, 1993 Scarth, et aI., 2000). Although the research is conflicting, depression does still occur in rural areas, and identifying the relationship between depression and its risk factors (e.g., stress) in this population could help elucidate its unique incidence in this population. this study, the focus was on identifying seasonal levels of depressed affect and perceived stress in Western Colorado ranchers (both husband and wife) and how those phenomena related to their levels of cortisol. The relationship between these factors was elucidated by assessing stress levels, depressive symptomatology, and diurnal cortisol patterns at three time points in the year. The hypotheses are as follows: High, medium and low stress periods emerging from the seasonal nature of ranching would demonstrate significant differences in levels of stress and depressed affect Stress and symptoms of depression would exhibit a positive relationship Dysregulated cortisol, seen as an increased morning rise (the difference between the wake and thirty minutes after waking samples) or a blunted daytime decline (the difference between the peak at thirty minutes after waking and the value at retiring) would be related to both increased depressive symptoms and stress

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Lower levels of general health would be exhibited during periods of higher stress (i.e. increased number of symptoms endorsed on symptom checklist)

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2. Methods 2.1 Participants A list of potential participants was obtained from the Department of Agriculture through the Freedom of Information Act (FOIA). Cattle ranchers who are permitees on the Grand Mesa were recruited by mail contact. The principle investigator (PI) sent letters to approximately 105 ranchers. Twenty-one (21) ranchers completed the study (9 females, 12 males; all Caucasian). 2.2 Recruitment Procedures The ranchers were initially contacted by mail. Included in the mail packet were: a cover letter outlining the purpose of the study, a demographic information sheet, and a pre-study survey. The purpose of the pre-study survey was to assess the ranchers' baseline levels of stress; that is, the number of items that cause them stress year round. As compensation for participation, the subjects were offered the choice of one book from the collection (Titles include: Ageless Iron I, Ageless Iron II, Changing Faces on our Land, and Successful Farming Recipe Collection).

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2.3 Study Protocol 2.3.1 Study Location The study was located in Mesa and Delta counties in Western Colorado. The PI visited the subjects at their homes (or at an alternative location, whichever was more convenient for the subject). Assessment of diurnal cortisol measurements was conducted at the Behavioral Immunology and Endocrinology Laboratory, Department of Psychiatry at the University of Colorado at Denver and Health Sciences Center. 2.3.2 Subjects Approval In May 2004 the University of Colorado at Denver and Health Sciences Center Human Subjects Research Committee approved the current study protocol (#2004104). In October 2004, an addendum requesting the addition of a Coping Styles Survey and a Leisure Activities Questionnaire was also approved. 2.3.3 Activities Involving Subjects The PI met with participants in person before beginning study activities to ensure participants were oriented to the study and understood the protocol. At the initial meeting, the PI obtained written, informed consent and also interviewed the participants about the timing of events and stress levels for their ranching operation At this time, participants rated stress for each month from July-December on a scale

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from one to seven, based on their experience and current conditions (drought, insects, etc.). From these ratings, the rancher s identified two-week time periods representing relative high, medium, and low stress (Appendix A). The phase dates were different for each participant. That is, some ranchers identified high, medium, and low stress periods as occurring in July, October, and December respectively, and another might have chosen September, November, and December, respectively. Clearly, there was not a consistent schedule ; however, each participant completed three two-week phases during the six-month time period. Participants completed activities detailed below for each phase. The contacted the participants before each time period to verify the starting date of the phase. The first time, the delivered the materials in person (to give instructions); materials were delivered by mail for the second two phases. During each phase, the participants took saliva samples three times daily (upon waking, thirty minutes after waking, and at retiring) on three days of their choosing, rated stress levels on saliva collection days, and completed a daily health diary (a symptom checklist) The collected these materials at a meeting shortly after the end of each two-week phase. At each meeting, an interview ascertained participants approximate levels of stress by asking for a rating on a scale of 1 to 7, being the least stressful) and the sources of stress for the past two weeks. addition, the Beck Depression Inventory (BDIII ; Beck et aI., 1961; Beck Steer 1996), a self-report instrument, was administered to determine depressive

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symptoms. Another self-report measure, the Perceived Stress Scale (Cohen, Kamarck, Mermelstein, 1983), was given to ascertain perceived stress levels. A life events scale complemented the perceived stress scale. At the end of the study, the participants filled out the Pre-Study survey a second time, as well as a coping styles survey and leisure activity questionnaire. This inventory was developed by Beck (et aI., 1961 ; Steer, 1996), and has been widely used to assess depression in psychiatric populations as well as normals (Groth-Marnat, 2003). The inventory consi sts of 21 statements with responses from to 3, 0 indicating a statement does not occur or is not severe and 3 indicating a high incidence or severity of the item. Mean internal consistency is 0.91 and test retest reliabilities range from .48 to .93 depending on the interval between testing. Content, concurrent, and discriminant validity are all good for this measure (Dozois Dobson, Ahnberg, 1998). The PSS is a 14-item self-repOlt scale developed by Cohen and colleagues (1983), which identifies an individual's appraisal of the amount of stress in one s life. The items are ranked with a Likert-type 5-point scale, 0 indicating and 4 indicating

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This measure has good psychometric properties, with a reliability coefficient of 0.78 as well as good construct validity (Corcoran Fischer, 2000). The LES (Coussons-Read, Okun, Geise, Schmitt, in press) administered in this study contained 28 items. These items were ordered in terms of severity, with "death of a spouse" as most severe, and "minor violations of the law" as least. Subjects were asked to check off the events that occurred in the last two weeks. Events occurring more than one time were checked and the number of times the event occurred was indicated next to the item. Saliva samples were collected from subjects using the Saliva Procurement and Integrated Testing, or SPIT Book (Laudenslager, Neu, Riggs, Goldstein, Lohman, 2003), provided by Dr. Mark Laudenslager. SPIT booklets contained three pieces of filter paper separated by waxed paper. Subjects were provided with SPIT Books for saliva collection and a package of Trident Original Flavor gum for stimulating saliva flow. This gum is selected as it does not interfere with the enzyme immunoassay that are used to measure steroids in the laboratory. Each subject was requested to collect these samples three times a day: at waking, thirty minutes after waking, and before retiring. These time-points were established to allow for 20

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examination of subjects' diurnal patterns. As discussed above, diurnal patterns are altered during chronic stress or depression. Subjects collected samples on three different, but typical days during each of the three phases. Because each rancher had unique phases, the sampling dates and times of year were widely varied in the study. Values outside exceeding two standard deviations were removed from raw salivary cortisol data. Then, within each phase, each individual's daily samples were averaged. For instance, the three waking samples taken during the two-week period were averaged for each person. This resulted in an average diurnal pattern for each phase for each participant. Additional values examined in the study were morning rise and daytime decline. The morning rise was calculated by subtracting the initial waking value from the peak value (waking plus thirty minutes). The daytime decline was calculated by subtracting the cortisol value at retiring from the peak value obtained thirty minutes after waking. These latter two values, as discussed previously, can indicate the presence of stress or illness if they are unusually large or small, respectively. Filter strips were extracted by cutting a section from the previously moistened end. The exact area varies with filter paper lot and must be calibrated with each new lot using a known volume of radiolabeled tracer in a saliva pool. An area equivalent to

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absorbing 100 III of saliva was determined using tritiated cortisol added to saliva. The cut filter paper was placed in a 1.4 ml microcentrifuge tube to which 0.25 ml of assay buffer was added. The tube was shaken for 24 hours after which buffer was added in duplicate to the appropriate wells of the assay plate. This effectively dilutes the saliva 1 :5. Salivary cortisol levels were determined using a high sensitivity commercial EIA kit (Salimetrics) that detects cortisol levels in the range of 10-1000 pg/ml. Briefly, 50 III of buffer from extracted filters were added in duplicate to the wells of an antibody (rabbit anti-cortisol) coated microtiter plate. The unknowns competed with horseradish peroxidase conjugated cortisol for the binding sites. The substrate tetramethylbenzidine (TMB) was added; the reaction was stopped with H2S04 and read at 450nm on a microplate reader. A sigmoid function was fitted by a four-parameter logistic regression for the standard curve and unknown concentrations were determined from this curve. Detection limit for this assay is 35 pg/ml. Interand intra-assay coefficients of variation are less than 10% for this assay. 2.4.6 Pre-/Post-Study Survey The Pre/Post-Study Survey (Appendix B) was developed by the PI for this study to obtain an estimate of baseline stress for each rancher. That is, how much stress are they experiencing on a year-round basis (not connected to season, necessarily)? This is an important consideration when looking at the acute stressors that ranchers 22

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experience as a result of the time of year; keeping in mind the issues that concern them regardless of season could give a deeper understanding to how the rancher s respond to acute stressors. This Survey was developed by a detailed review of surveys given to farmers and ranchers in the past that ask about day to day life stressors. For this study, four different scales were examined: a Daily Work Inventory, a Farm Work Stress Scale, a FarmJRanch Stress Scale and a Market Research Panel Questionnaire. The first two items are publications from the Iowa State University Cooperative Extension Service. The FarmJRanch Stress Scale was developed by Carson and colleagues (1993) for the purpose of their study examining the mediating effects of hardiness on stress in ranchers. Finally the Market Research Panel Questionnaire was developed by The Pre/Post-Study Survey was given to participants before the study began and then upon completion of the final phase. The instruction asked participants to indicate which items are stressful to them throughout the year and to circle the relative level of stress on a Likert-type scale. The survey was scored by adding the values endorsed for each item. The coefficient alpha for the Pre-Study survey was 0.743 and for the Post Study Survey it was 0.750. According to George and Mallery (2003), a value above 0.7 is acceptable for internal validity (p. 231) 23

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2.4.7 Coping Styles Survey and Leisure Activities Questionnaire The coping styles survey (Appendix C) and leisure activities questionnaire (Appendix D) were both adapted from a Market Research Panel Survey distributed by (1999) There were nine items on the coping styles survey. Each item was rated on a Likert-type scale from 0 to 4 (O=never, 2=sometimes, 4=very often). The leisure activities questionnaire contained a list of 19 activities. Subjects checked a box indicating how often they participated in each activity for leisure There were eight choices ranging from to with graded intervals between choices. 2.5 Statistical Analysis Data were analyzed using hierarchical multiple linear regression, correlation analysis, and t-tests. Hierarchical regression analysis was run to determine the contribution of stress, cortisol and year-round stressors to the variation in depressive symptoms. Depressive symptoms, as measured by the BDI-II, were entered as the dependent variable Independent variables, in their order of entry were: age, perceived stress (as PSS scores), diurnal cortisol decline, found by subtracting the retiring value from the wake +30 value, and Pre-Study Survey scores. Age was entered first to account for the effects of age on the depression scores. While the onset of 24

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depression can occur throughout the lifetime, it may be more prevalent in the elderly who suffer more physical symptoms. These symptoms can have a negative impact on mood (Koenig Blazer, 1992). Next, perceived stress was entered, as stress has been related to depression in multiple studies; particularly as chronic stress may contribute to the pathogenesis of depression (Tafet Bernardini, 2003). Following perceived stress, diurnal cortisol decline was entered, as blunted diurnal decline can be a marker of depression. Finally, the Pre-Study survey results were entered, as they reflect the impact of year-round stressors on the ranchers; although related to the perceived stress levels, the Pre-Study survey results are differentiated by their measurement of actual events or situations that cause the stress instead of the perception of stress in general. The purpose of the regression analysis is to demonstrate the predictive value of the independent variables on the dependent variable. this case, while a case can be made to substitute some of the other variables for the dependent variable, based on research that places stress and cortisol dysregulation temporally before the onset of depression (clearly this can be argued; Sapolsky, 1998), it was decided to enter the variables based upon that assumption: the occurrence of stress, cortisol dysregulation, and the presence of chronic stressors could precipitate depressive symptomatology. Correlation analyses determined the relationship between factors, including age, health symptoms, ranch characteristics (size of herd, acres farmed, etc.), BOI-II scores, PSS scores, and Life Events Scale scores. Significance values after 25

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Bonferroni's correction for multiple comparisons are presented as a conservative calculation to reduce Type-I error. Since the sample size is small, the correlations should be interpreted with caution and as potential trends. The calculation used to find the corrected p-value is shown below, in Equation 2.1. 0.05 Where is the number of comparisons made. T-tests examined gender differences in BDI-II scores, PSS scores, Life Events, and health symptoms. 26

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3. Results 3.1 Population Statistics Table 3.1 presents the demographic information for the population used in the study. T bl 3 1 P I D h a e opu a Ion emograpl ICS Age 24.00 81.00 53.38 14.63 Years married .00 59.00 24.95 18.98 Size of herd 0 500 182.05 127.65 Acres owned .00 2000.00 556.86 547.00 Acres farmed .00 1000.00 317.52 311.12 Years on ranch .00 65.00 32.12 18.88 Years head of ranch .00 43.00 19.95 14.79 Number of hired hands 0 3 .24 .70 Outside Job 1 2 1.52 .51 Outside Job hours/week .00 50.00 12.00 16.11 Number of children 0 7 2.52 1.99 Number of children at home 0 3 .62 1.16 3.2 Predicted Stress and Actual Stress Relationship One of the main hypotheses for this study was that different times of the year likely are associated with varying levels of stress for ranchers due to changes in activity. Additionally, the researcher acknowledged that individuals were likely to perceive activities differentially and thus give unique stress ratings. Despite this attempt to accommodate individual differences, however, ranchers' selections of relative high, medium, and low stress times had no correlation with their post-phase ratings of their actual stress during those time periods (High: r=0.28, Medium: r=-O.1 0, 27

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Low: r=-0.33, As a result of the lack of relationship between predicted and actual stress levels, and due to confounds that would arise in attempting to reorganize the data by season, dependent variables were averaged. Hypothesized relationships were examined over the six-month period instead of comparing phases of different stress levels. The top five items endorsed on the Pre-Study survey were: market conditions, government policies, financial constraints and difficulties, machinery problems, and weather, respectively. The bottom four items on the Pre-Study Survey were isolation, being involved in a parent-child operating agreement, accidents and injuries, and competing for land. When the ranchers took the survey a second time, the top five items were: machinery problems, financial constraints and difficulties, market conditions, balancing needs of the ranch and the family, and planning an estate/ranch transfer. The bottom four items on the Post-Study survey were the same as the Pre-Study survey with the latter two items switching order. The average diurnal cortisol pattern exhibited by subjects over the course of the study is shown in Figure 3.1 (below). The pattern shows a clear morning rise and a distinct daytime decline. This is the typical pattern expected from healthy adults 28

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with a normal rhythm (Harbuz, et aI., 2003). There were some gender differences in this overall pattern, which will be discussed below. :J' 1/1 Q e c: c: o o "0 o c: :IE Figure 3.1 Average Diurnal Cortisol Rhythm 3.5 Cortisol, Stress, Depressive Symptoms, and Life Events Over the six-month time-period, ranchers' average BDI-II scores were significantly positively related to both their Perceived Stress Scale (PSS) scores and Life Events Scale (LES) scores (PSS: r=0.75, LES: r=0.56, Table 3.2). A scatterplot of BDI-II scores and PSS scores reveals a strong positive relationship, with a couple of outliers (Figure 3.2). The average BDI-II score over the course of 29

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the study was 6 24 (s.d.=6.17). This falls in the category, according to Beck and Steer (1996) It is also notable that the items endorsed most strongly over the course of the study were all physical symptoms: changes in sleeping pattern, loss of energy, tiredness, changes in appetite, and loss of interest in sex were the top five items endorsed, respectively In addition, as ranchers reported higher levels of perceived stress they also reported a higher number of Life Events (r=0.44, Bonferroni's correction for multiple correlation would place the value of significance at so this relationship should be interpreted with caution Daytime cortisol decline (the difference between the peak value at thirty minutes after waking and the cortisol value at retiring) was inversely related to all three factors, but only approaching significance to higher PSS scores (r=-0.37, While the relationships are not significant, their direction is consistent with extant literature that relates chronically elevated daytime cortisol with chronic stress (McEwen, Seeman, 1999) and depression (Sadock Sadock, 2003) 30

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Pearson Correlation Sig. (l-tailed) Pear so n Correlation Sig. (I-tailed) Pearson Correlation Sig. (I-tailed) .167 .053 25. 00 0 20. 00 0 15 0 0 0 .a 0 10.00 0 0 0 5 00 0 0 CD 0 0 0 0 0 0 0 5.00 10 00 20.00 I .328

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While endorsing higher numbers of health items (in this study, a greater number of items endorsed in the health diary implies lower overall health) did not relate significantly to greater levels of stress or depression, a greater number of life events occurring did relate to more health item endorsement (r=0.38, Table 3.3). Although the correlation only approaches significance, a greater number of health items endorsed related inversely with daytime cortisol decline. Morning cortisol rise was not significantly related to any of these factors. Health Items BDI-II Pearson .14 Correlation Sig. (I-tailed) .274 PSS Pearson .06 Correlation Sig. (I-tailed) .395 LES Pearson Correlation Sig. (I-tailed) Cortisol Decline Pearson -.27 Con'elation Sig. (I-tailed) .128 32

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3.7 Regression Analyses In Table 3.4, BOI-II scores were predicted by age, average PSS score, daytime cortisol decline, and Pre-study survey results. Together, these factors accounted for 85.4% of the variation in BOI-II scores (adj R2=0.854). The correlation coefficient was significant (F( 4,15)=28.688, 1). Collinearity statistics for the regression model indicated that each variable uniquely contributed to the model. The final model for this regression analysis had tolerances ranging from 0.749 to 0 993. This range indicates that the variables did not significantly interrelate and that their contributions are indeed independent. The VIF statistic corroborates this with values ranging from 1.007 to 1.336, indicating that, overall, the regression coefficients are stable. When males alone were entered into the model, these variables accounted for 95.7% of the variation (adj. R2=0.957, Table 3.5). The correlation coefficient was significant (F( 4,6)=56.597, 1). In this analysis, the tolerance was not quite as good, but it was within limits: 0.442-0.914. The VIF was also weaker: 1.094-2.2665. Clearly this analysis should be interpreted with extreme caution due to the small sample size. While these results are impressive considering the small sample utilized in the study, this analysis should also be interpreted with extreme caution for the same reason, only 21 subjects were in the study. 33

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T bl 3 4 BDI II R a e -egressIOn o e Beta 1 (Constant) -1.035 0.314 Age 0.514 2.545 0.020 2 (Constant) -6.634 0.000 Age 0.489 4.708 0.000 Average PSS 0.744 7.169 0.000 3 (Constant) -5.130 0.000 0.487 4.546 0.000 Average PSS 0 753 6.540 0.000 Cortisol Decline 0.025 0.217 0.831 4 (Constant) -6.565 0.000 0.491 5.578 0.000 Average PSS 0.746 7.870 0.000 C0l1isol Decline 0.132 1.301 0.213 Pre-Study Survey 0.281 2.941 0.010 T bl 3 5 BDI II R a e egression e WI a es DIy Model (Males only) Standardized t Sig. Coefficients Beta 1.000 (Constant) -0.832 0.427 Age 0.607 2.294 0.047 2.000 (Constant) -5.261 0.001 Age 0.556 4.217 0.003 Average PSS 0.704 5.335 0.001 3.000 (Constant) -1.326 0 226 Age 0.616 5.661 0.001 Average PSS 0.467 3.191 0.015 Cortisol Decline -0 344 -2.335 0.052 4.000 (Constant) -3.659 0.011 Age 0.657 9.568 0.000 Average PSS 0.336 3.414 0.014 Cortisol Decline -0.275 -2.936 0.026 Pre-Study Survey 0.296 3.476 0.013 34

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3.8 Population Factors 3.8.1 Age Of the self-report measures given during the study, age of the participant was only related to BDI score (r=0.51, The older the participant was, the higher their BDI score was likely to be throughout the s tudy (Table 3.6) Even after Bonferroni's correction (p=0.02), this relationship is still significant. T hi 36 A C I a e orre a Ions Age Pre-Study Survey -0.03 BDI-II 0.51 PSS 0.06 LES 0.15 Cortisol Decline 0.06 Health Items -0.07 Post-Study Survey -0.03 3.8.2 Gender There was no significant gender difference on any of the main variables measured in the study Of particular note, the BDI and PSS were stable across genders, as was daytime cortisol decline However, the relationship of daytime cortisol decline to scores on the BDI was affected by gender; in males, higher BDI scores were related to lower daytime cortisol decline (i.e. flat rhythm; r=-0 58, as were higher PSS scores (r=-0.68, and higher numbers of life events (r=-0.61, None of these relationships were found in females. In terms of morning rise (the difference in cortisol levels between waking and thirty minutes after waking), 35

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females tended to have a greater morning rise than males (F( 1,18)=2.357, but this was non-significant.. This difference in morning rise between males and females is illustrated in Figure 3.3; values are expressed in nmfL. The large amount of variation in the females likely contributes to the lack of relationship. Future studies may want to re-examine whether a gender difference exists in morning rise. ::J r:: c 0 r:: Figure 3.3 Male and Female Mean Cortisol Rise (nmIL) 36

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3.8.3 Ranch and Rancher Characteristics Some relationships were found between the size of the ranch and the number of years a rancher had been on the ranch and average score on the BDI and PSS (Table 3.7). The larger the herd and the greater number of acres farmed the lower the scores tended to average on both the BD! (r=-0.43, r=-0.42, and the PSS (r=-0.44, -0.43, Additionally, lower scores on the LES were found in those who farmed larger numbers of acres (r=-0.41, The longer a rancher had been ranching, the higher the BDI score tended to be (r=0.46, however, the PSS was not significantly related to years on the ranch (r=0.21, After Bonferroni's correction, however, only values below are considered statistically significant; the remaining relationships should be interpreted cautiously, especially in light of the small sample size. It is of note that the number of years on the ranch was not significantly related to number of acres farmed (1"=0.094, or size of herd (r=O.13, but ranchers with more acres farmed and larger herds tended to have more hired hands (r=0.60, r=0.66, 3.8). Even with Bonferroni's correction, these values are still under the corrected of 0.022.

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Table 3.7 Ranch Characteristics and Psychological Correlations 0.93 0.000 0 .13 0.09 0.294 0.342 -0.43 -0.42 0.46 0.025 0.031 0.019 -0.44 -0.43 0 .2 1 0.75 0.022 0.027 0.182 0.000 -0.41 0.56 0.44 0.033 0.004 0.023 T bl 38 R h' Ch a e anc t C arac erls IC orre a Ions Size of Acres Years on herd farmed ranch Acres farmed Pear s on .93 Correlation Sig. (I-tailed) .000 Year s on ranch Pear so n .13 .09 Correlation Sig. (I-tailed) .294 .342 N umber of hired Pearson .66 .60 .31 hands Correlation Sig. (I-tailed) .001 .002 .087 3.9 Coping Styles The most frequently utilized coping mechanisms were changing one's attitude (x =2. 59, s.d=0.87) and establishing prioritie s (x=2. 71, s.d =0.98). Lea s t commonly endor s ed were making a list of worries (x=0.24, s.d.=0.44) and con s uming alcohol 38

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(3<.=0.65, s.d.=0.93). Figure 3.4 summarizes the frequency of coping style utilization. For two of the coping sty les, "talk about it" and "consume alcohol," there wa s a significant effect of gender. Females were significantly more likely to utili z e talking as a coping s tyle (t(15)2.526, and male s were more likely to con s ume alcohol to cope (t(15)=-2.898, r-t-.--f-c r-I--r-ff-I--.--I-) 39

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4. Discussion The hypotheses explored in this study predicted that high, medium and low stress periods would be associated with hypothesized differences in levels of stress and depression, stress and symptoms of depression would exhibit a positive relationship, dysregulated cortisol would be related to both increased depressive symptoms and stress, and that lower levels of general health would be exhibited during periods of higher stress (i.e. increased number of symptoms endorsed on symptom checklist). Although the present data did not clearly establish the relationships originally hypothesized, the findings of this study generally support previous research examining the relationship between stress and depression. This suggests that the interaction of these variables in ranchers is similar to their relationship in the other human populations studied. The positive relationship between PSS scores, BDI-II scores, and number of life events observed in ranchers is consistent with previous research. Higher numbers of life events have been found to precede the onset of depressive episodes, though this relationship is strongest for the first episode (Sadock Sadock, 2003). Additionally, psychosocial stress has been shown to be a trigger for the onset of depression (Tafet Bernardini, 2003). Cohen and coJleagues (1983) found a significant positive relationship between number of life events and scores on the PSS; this was replicated in the present study. In this way, the relationship among 40

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these three factors in the ranching population is consistent with research with other populations. While this study did not examine major depressive disorder, per se, the positive relationship found between depressive affect and psychological stress indicates that ranchers experiencing higher levels of psychological stress may be more vulnerable to depressive symptomatology. The Preand Post-Study survey revealed that, despite the difference in time of year when the surveys were administered, machinery problems, market conditions, and financial constraints and difficulties topped the list of constant stressors for ranchers. The first two items are uncontrollable factors and the final item is inherent to the profession, but nonetheless is stressful. The ranchers found isolation, being involved in a parent/child operating agreement and accidents and injuries to be the least stressful, year-round. Perhaps these items are more in the control of the ranchers; they can adjust how many people they interact with or whether they work with their parents/children Accidents and injuries are not necessarily always controllable, but being mindful of the dangers of large equipment is certainly a preventive measure. Despite these similarities in the Preand Post Study survey results, they were also quite disparate in many of their other results. For future studies, modifications that make the survey less susceptible to seasonal variation are recommended. This would improve the validity of the survey, as its primary objective is to measure year-round stressors; susceptibility to season would damage this goal.

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The lack of relationship between number of health items endorsed and scores on the PSS BOI-II, and daytime cortisol decrea s e was surprising as a relationship between general health, stress, depression, and HP A dysregulation has been established (Sapolsky, \998). However, the results for this item should be interpreted with great caution as participant cooperation for maintaining accurate health diaries was questionable. Several ranchers reported forgetting to fill them out; so the missing data certainly skew the results. In future studies, emphasizing the importance of filling this diary out and reminding the participants would be advised. The prediction of BDI-II scores by age, PSS scores, average daytime cortisol decline, and pre-study survey results was quite robust. While the relationship between age and BDI-II scores contrasts previous research (Steer, Rissmiller, Beck, 2000), epidemiological studies show that the onset of MDD can occur throughout the lifetime (Sadock Sadock, 2003). Additionally, higher Pre-Study survey results predicted higher BDI-II scores in this model, which could indicate that a higher baseline level of stress (that is, not including the additional stressors occurring with the different seasons) could be a risk factor for the onset of depression in ranchers Of note are the gender differences found for the relation s hip of daytime cortisol decline to BOI-II scores, PSS Scores and Life Events. In this study, lack of cortisol decline was related to higher BDI-II s cores and PSS scores in men, but not 42

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women. Additionally, a higher morning rise was found in women, though this only approached significance. In a study examining positive and negative affect as traits, Polk and colleagues (2005) found that men high in trait negative affectivity (which is associated with affective responses with negative valence) tended to have a high, flat cortisol rhythm. This flat rhythm is consistent with the finding in our study that male ranchers reporting a higher level of stress and depression tended to have flatter rhythms. In addition, the finding that females tended to have a greater morning rise, though only approaching significance, corroborated the results of previous studies (Kunz-Ebrecht, et aI., 2004), where women had a greater morning rise on work days. For ranchers, the typical 5-day week does not apply, and unless they take a vacation, every day is a work day. Kunz-Ebrecht and colleagues (2004) found no difference in morning rise between genders on weekend days, and attributed this to the fact that during the week, females tended to have more domestic responsibilities than males and on the weekend this is not the case. Perhaps in ranching families, the wife is expected to provide meals and care for the children in addition to ranching. Future research could focus on identifying differences in gender roles on the ranch and their mediating effects on stress and cortisol levels. Another consideration factor when exploring the relationship between cortisol and stress is that different types of stress could elicit differential responses in males and females. Stroud, Salovey, and Epel (2002) found that men had a greater cortisol response to 43

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achievement stress whereas women responded more than men to social rejection challenges. The lack of a difference between genders for scores on the PSS and BDI-II is also notable Studies have shown that females tend to score significantly higher than males (Arnau, et aI., 2001; Beck Steer, 1996); however, this is also not consistent, as Dozois, and colleagues (1998) found no significant effect of gender on BDI-II scores among college students. Clearly, a gender difference has not be consistently established across all populations, but an examination of the epidemiology of MDD shows that females are twice as likely to be diagnosed in their lifetimes as males (Sadock Sadock, 2003). In terms of perceived stress, Farabaugh and colleagues (2004) found significantly higher levels of perceived stress among depressed outpatients. Cohen and colleagues (1983), however, found no effect of gender on PSS scores in their college student population. Perhaps there is a difference between non-clinical and clinical populations. Maybe in the general population (ranchers and college students, for instance), the perception of stress is not specific to gender, but in clinical populations, high levels of stress interacting with gender could playa significant etiologic role, especially since depression is twice as common in females No previous studies have examined the relationship between the size of an operation, number of years working on that operation, and levels of stres s and depression in ranchers. The preliminary findings from this study suggest that 44

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ranchers with larger operations tend to report lower levels of stress and depression. This phenomenon may be, in part, due to the fact that as operations get larger, they tend to have more hired hands and work is dispersed. In smaller operations, generally one or two individuals do the work. When these two individuals are related, additional friction could result; previous research has shown that multi generation ranching operations have the added stress of differential perceptions of support within the family and transition factors (Weigel RR, Weigel, 0.1., Blundall, 1987). Interestingly, the greater the number of years one has worked on a ranch, the higher the scores on the BOI-II and PSS tended to be. Part of this relationship can be explained by age; age was one of the predictors for higher BDIII scores. Additionally, it is possible that age-related declines in abilities also contributed to higher ratings on these scales; however, this was not specifically addressed in this study and should be investigated in future research. Finally, the coping styles survey revealed that ranchers primarily changed their attitudes and established priorities when they were feeling stressed. Only one maladaptive coping mechanism (consuming alcohol) was on the survey, and was infrequently endorsed; however, those who endorsed this item tended to be male. This is consistent with epidemiological data showing that men are more likely to have alcohol abuse disorders than women (Sadock Sadock, Women were more likely to talk to others about their problems in this study. This is also consistent with a Canadian study examining coping strategies in the general 45

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population (Wang Patten, 2002). In constrast, a study examining coping strategies used in farm families found no gender effect for using talking to others as a coping mechanism (Weigel, R.R. Weigel, DJ., 1987). Weigel. Weigel (1987) also found that every family endorsed turning to faith. Faith was commonly endorsed in this study, but not invariably. 46

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5. While the present study has elucidated some intriguing relationships among stress, depression, and diurnal salivary cortisol rhythms, several limitations need to be considered when interpreting these results. First, the initial proposed methods for this study proved to be ineffective, resulting in averaging the data across the time period instead of comparing stress periods. Individual variation prevented clear delineation of high and low stress periods. Asking the ranchers to identify typical high, medium, and low stress times for the six month period at the beginning of the study was problematic, in that the ranchers' predictions were often incorrect. general, their predicted stress was higher than their actual stress level. This is an important consideration Perhaps when attempting to predict their future stress levels, the most salient memories of those time periods are events that were stressful and isolated stressful days. When the ranchers actually experience that time-period, the day-to-day stress level and coping with daily stressors does not seem as bad as when they consider the season as a whole. When originally designing this study, the idea of allowing ranchers to individually identify periods of relative high, medium, and low stress was based on the assumption that different ranchers are likely to perceive the various seasons differently. For this reason, ranchers were not required to take their saliva samples during the same three two-week periods to 47

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compare seasonal differences, because individual differences were thought to confound this relationship. Indeed, in the pre s ent study, some found haying to be the most stressful period during the six months and others found it to be enjoyable or even relaxing. Perhaps for future studies, with larger populations, pre-selecting the times to take measurements would be desirable. Then, individual differences can be explored within those seasons. The organization of the present study does not allow for this exploration because the time periods are scattered. Another limitation to this study is the small sample size and limited community from which the sample was taken. Most of the participants for the study lived in one city in Western Colorado and the few participants who did not, lived less than 100 miles away While extrapolation of the present study results to the general ranching population would be erroneous, these results provide some insights into potential relationships and perhaps also a starting point for future studies. Future studies that include samples from different parts of the country would be desirable. In addition, several couples participated in the study; the confounds of this were not explored due to the already small sample size. may be advantageous to have as many couples as possible participate in future studies, as the shared experiences could be important for exploring gender effects on differential stress and depression ratings. Sampling bias also needs to be considered. Many ranchers chose not to participate in the study. is possible that the ranchers who participate represent a 48

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unique population within the community. Ranchers who did not participate may be more or less stressed or even exhibit a different relationship among the variables examined. This is certainly a risk that all studies face due to their voluntary nature. Finally, the cross-sectional nature of this study is also limiting. Longitudinal studies examining the changes in stress, depression, and cortisol are needed to fully understand how the interaction of these variables changes across the lifespan. To develop appropriate interaction strategies for this population it is essential to understand not only gender effects, but also age effects. Stressors and risk factors for depression in younger men may differ substantially from those factors that place older men at risk. The purpose of this study was to identify the relationship between stress, depression and diurnal salivary cortisol. While some significant relationships were found in this pilot study, many questions remain. To fully understand how these phenomena interact in the ranching community, a longitudinal perspective is needed. In addition, many ranching households are multi-generational, so the family dynamic should also be explored further. Future studies might examine the concept of allostatic load in ranching populations, as it has important implications for health outcomes. The combination of repeated stressors and predominantly middle to lower SES could contribute to allostatic load in ranchers and playa role in long-term morbidity and mortality. While stress and depression are phenomena 49

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shared all humans, it is important to understand how niche populations experience them and cope. 50

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Stress Participant lD: __ month, p lease i n d iClte relative level o ( o n a Sell e 1 t o 7 (1=mi n imal stre s s 7 =maximu m Additionally, i n diCJte which at lctivitics you doing durin'::! that period. the r e i s greater thln OIle activity llJd/ot str e s s level given month, p l e lse i ndicate it ill the space p rovide d alld mark all the the date(s) the lcth'itie s chan
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Appendix B. Pre-/Post-Study Survey From the list below, please indicate which items are stressful to you throughout the year, and c irc Ie the relative I e vel 0 f stre ss = little stress, 2= moderate s tress, :I=high s tress). Balancing the needs of the farm/ranch with the needs of the family 2 :I NA 2. Being involve d in a parent-child operating agreement 2 :I NA 3. Farm/ranch accidents or injuries 2 3 NA 4 Government policies 2 3 NA 5 Having to compete for additional land 2 3 NA Financial constraints or difficulties 2 :I NA 7 Illness at peak times 2 :I NA 8. Irregular cash flow 2 :I NA 9 Isolation 2 :I NA 10 Problems with machinery (breakdown, repairs, 2 :I NA buying new machinery) 11. Weather conditions 2 :I NA 12. Working with bankers and loan officers 2 :I NA 13 Market conditions, as they affect profit 2 :I NA 14. Facing retirement from ranching/farming (o r) 2 :I NA taking over the farm/ranch IS Transfer of farm and responsibilities to a new 2 :I NA generation/planning an estat e .. 52

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'.i> ----. ----------.-------.--------------------------------------------_ YOU Q.. ('1 ('1 Q o 1. 0 2. 0 3 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 00 00 C '-<

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.j::>. 1 2 3. 4. 5 6. 7 8 9 11. 12. 13 14. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 a 0 0 0 0 0 0 0 0 0 0 0 0 0 0 week 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 = Q.. \I) = = = =

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Steer, R.A., Rissmiller, D.J., Beck, A.T. (2000). Use of the Beck Depression Inventory-II with depressed geriatric inpatients. 38, 311-318. Stroud, L.R., Salovey, P., Epel, E.S. (2002). Sex differences in stress responses: Social rejection versus achievement stress. 52,318-327. Tafel, G.E., Bernardini, R. (2003). Psychoneuroendocrinologicallinks between chronic stress and depression. 27, 893-903. Tevis, (1982, February). Stress. Thomas, H.Y., Lewis G., Thomas, D.R., Salmon, R.L., Chalmbers, R.M., Coleman, T.J., Kench, S.M., Morgan-Capner, P., Meadows, D., Sillis, M., Softley, P. (2003). Mental health of British farmers. Yedhara, K, Cox, N.KM., Wilcock, G.K, Perks, P., Hunt, M., Anderson, S., Lightman, S.L., Shanks, N.M. (1999). Chronic stress in elderly caregivers of dementia patients and antibody response to influenza vaccination. 353,627-631. Wang, J.L. (2004). Rural-urban differences in the prevalence of major depression and associated impairment. 39, 19-25. Wang, J.L., Patten, S.B. (2002). The moderating effects of coping strategies on major depression in the general population. 47(2), 167-173 Weigel, D.J., Weigel, R.R. (1990). Family satisfaction in two-generation farm families: The role of stress and resources. 39(4), 449455 Weigel, R.R., Weigel, D.J. (1987). Identifying stressors and coping strategies in two-generation farm families. 36(4),379-384. 60

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Weigel, R.R., Weigel, DJ., Blundall, J. (1987). Stress, coping, and satisfactions: Generational differences in farm families.