thesis final manuscript 2014
TRANSCRIPT
i
ASSOCIATIONS WITH STRESS: A CROSS-SECTIONAL COMPARISON OF
WELLNESS IN OLDER ADULTS
By
SHELBY BENCI, B.S. (California Polytechnic State University, San Luis Obispo) 2012
CHAD EARL, B.S. (Bradley University) 2000
APRIL IRVINE, B.S. (Johnson & Wales University) 2012
JULIE LONG, B.S. (California Polytechnic State University, San Luis Obispo) 2012
NIKKI NIES, B.S. (Montclair State University) 2013
JESSICA SCHIAPPA, B.S. (Benedictine University) 2013
RESEARCH MANUSCRIPT
Submitted in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE in NUTRITION AND WELLNESS
In the College of Education and Health Service,
Benedictine University, Lisle, Illinois
Research Advisor:
Dr. Bonnie Beezhold, MHS, CHES
December 2014
ii
ASSOCIATIONS WITH STRESS: A CROSS-SECTIONAL COMPARISON OF
WELLNESS IN OLDER ADULTS
By
SHELBY BENCI, B.S.
CHAD EARL, B.S.
APRIL IRVINE, B.S.
JULIE LONG, B.S.
NIKKI NIES, B.S.
JESSICA SCHIAPPA, B.S.
The Research Manuscript submitted has been read and approved by the Research
Advisor. It is hereby recommended that this Research Manuscript be accepted as
fulfilling part of the Master of Science in Nutrition and Wellness graduate degree in the
College of Education and Health Services at Benedictine University, Lisle, Illinois.
________________________________ _________________________________
Signature of Bonnie Beezhold, PhD, Signature of Karen Plawecki, M.S., Ph.D.
MHS, CHES, Research Advisor Director, M.S. in Nutrition and Wellness
APPROVED FOR BINDING
_________________________________
Signature of Catherine Arnold, M.S., Ed.D.
Chairperson, Nutrition Department
APPROVED COMPLETION OF
RESEARCH REQUIREMENT
__________________________________
Signature of Alan Gorr, Ph.D., M.P.H.
Dean, College of Education and Health
Services
December 11, 2014________________ December, 2014___________________
Date of Oral Defense Intended Graduation Date (December 2014)
iii
iv
© Copyright by
Shelby Benci, Chad Earl, April Irvine, Julie Long, Nikki Nies, Jessica Schiappa
2014: All Rights Reserved
v
TABLE OF CONTENTS
Page
LIST OF TABLES vii
ACKNOWLEDGEMENTS x
STRUCTURED RESEARCH ABSTRACT xi
CHAPTER 1: INTRODUCTION 1
Introduction 1
Study Purpose 3
Hypotheses 4
Variables to be Examined 6
CHAPTER 2: LITERATURE REVIEW 8
Dimensions of Wellness 8
Mental Wellness by Chad Earl 9
Physical Wellness by Chad Earl 9
Social Wellness by Chad Earl 10
Spiritual Wellness by Chad Earl 11
Health and Wellness of Older Adults 12
Depression by Jessica Schiappa 13
Associations of Stress and Depression by Jessica Schiappa 14
Weight by April Irvine 15
Physical Activity by April Irvine 16
Dietary Patterns in Older Adults by April Irvine 17
Health and Wellness of the Vowed Religious Community 19
Dietary Patterns in Vowed Religious Communities by Nikki Nies 19
Blood Pressure by Nikki Nies 19
Comparison of Groups by Nikki Nies 20
Mechanisms of Stress 22
Impact of Chronic Stress on Physical Wellness by Shelby Benci 24
Impact of Chronic Stress on Mental Wellness by Shelby Benci 26
Impact of Chronic Stress Eating Behaviors and Weight by Shelby Benci 28
Stress and Aging by Shelby Benci 30
vi
Mitigating Factors of Stress 30
Multivitamin/Mineral Supplementation by Julie Long 31
Omega 3 Fatty Acids by Julie Long 32
Fruits and Vegetables by Julie Long 34
Physical Activity by Chad Earl 35
Social Support by Chad Earl 36
Spiritual Practices by Chad Earl 37
CHAPTER 3: METHODOLOGY 39
Research Study Design 39
Research Study Recruitment 39
Data Collection Methods and Process 41
Validity and Reliability of Methods 44
Measurement Tools 48
Statistical Procedures 54
CHAPTER 4: FINDINGS 56
Stress & Health & Lifestyle Factors Hypotheses 1-4
by Shelby Benci 59
Alcohol & Health & Lifestyle Factors Hypotheses 5-8
by Jessica Schiappa 62
Sweets Intake & Health & Lifestyle Factors Hypotheses 9-13
by Julie Long 65
Physical Health Measures & Health & Lifestyle Factors Hypotheses 14-18
by Chad Earl 68
Geriatric Depression Scale & Health & Lifestyle Factors Hypotheses 19-23
by Nikki Nies 72
Amount of Sleep & Health & Lifestyle Factors Hypotheses 24-27
by April Irvine 75
CHAPTER 5: DISCUSSION 80
Overall Findings 80
Stress 80
Depression 84
Sweets Intake 85
Alcohol Intake 88
Sleep 90
Physical Health Measures 91
Strengths and Limitations 93
Conclusions 94
vii
REFERENCES 95
APPENDIX A: Cross-Sectional Wellness Study IRB Document 115
APPENDIX B: Wellness Survey 136
APPENDIX C: Recruitment Tools 143
APPENDIX D: Signed Informed Consent Form 146
APPENDIX E: Registration and Testing Procedures 147
APPENDIX F: Health Assessment Data Collection Tools 150
viii
LIST OF TABLES
Table Page
1. Demographic and Lifestyle Characteristics by Group…………………………...57
2. Health and Wellness Characteristics by Group………………………………….58
3. Comparison of Means between Living Groups………………………………….59
4. Associations between PSS and Health and Lifestyle Factors……………………61
5. PSS Multiple Linear Regression Analysis……………………………………….62
6. Comparison of Means of Weekly Alcohol Intake between Living Groups……...63
7. Comparison of Means between Binned Weekly Alcohol Intake Groups………..64
8. Associations between Alcohol Intake and Stress………………………………...65
9. Comparison of Means of Sweet Intake…………………………………………..66
10. Significant Correlations of Variables with Sweets Intake……………………….67
11. Multiple Linear Regression Analysis of Sweets Intake………………………….68
12. Comparison of Means between Groups of Heart Rate & Body Fat……………..69
13. Correlations with Physical Parameters and Perceived Stress……………………69
14. Associations with Muscle Mass………………………………………………….70
15. Body Fat and Heart Rate Associations…………………………………………..71
16. Comparison of Stress Means between Muscle Mass Groupings………………...72
17. Comparison of Means with Geriatric Depression Scale Scores…………………73
18. Significant Correlations of Variables with Geriatric Depression Scale………….73
ix
19. Multivariate Analyses of Predictors of Depression……………………………...74
20. Significant Correlations of Variables with Geriatric Depression Scale………….75
21. Comparison of Means between Genders and Hours of Sleep……………………75
22. Comparison of Means between Living Groups with Hours of Sleep……………76
23. Comparison of Means between Sleep Hour Binned Groups…………………….77
24. Significant Correlations of Variables with Sleep Hours…………………………79
x
ACKNOWLEDGEMENTS
We would like to first thank our advisor, Dr. Bonnie Beezhold, for her support
and guidance through this entire process. We would also like to thank our family and
friends for their endless love and support. We express our sincere gratitude and thanks to
one another, as none of this could have been completed without each other’s support,
effort, and time. Thank you to all who have helped us on this journey.
xi
ABSTRACT OF RESEARCH MANUSCRIPT
ASSOCIATIONS WITH STRESS: A CROSS-SECTIONAL COMPARISON OF
WELLNESS IN OLDER ADULTS
By
SHELBY BENCI, B.S.
CHAD EARL, B.S.
APRIL IRVINE, B.S.
JULIE LONG, B.S.
NIKKI NIES, B.S.
JESSICA SCHIAPPA, B.S.
Benedictine University, Lisle, Illinois
December 2014
Research Advisor: Bonnie Beezhold, PhD, MHS, CHES
Background: Chronic stress negatively impacts wellness and is associated with physical
and mental chronic disease. Certain lifestyle factors can mitigate stress and improve
health outcomes.
Objective: To examine the relationships of stress with physical, emotional, social,
spiritual health measures, and diet and lifestyle factors in older adults living in two
different communal environments.
Methods: Cross-sectional study of 67 participants were recruited from vowed religious
communities and an independent retirement community. Study assessments included a
survey containing demographic and lifestyle questions, brief validated questionnaires
measuring perceived stress and other wellness dimensions, a 24-hour recall questionnaire
and anthropometric measurements.
xii
Results: Of the 67 participants, 35 resided in vowed religious communities and 32
resided in an independent retirement community. A significant difference in reported
depression, as measured by the Geriatric Depression Scale-15, was found with the vowed
religious community reporting a higher mean score than the independent retirement
community (2.12 vs. 1.16, p = .020). Percent body fat (38.55 vs. 33.26, p = .025) and
heart rate (75.86 vs. 68.41, p = .029) were also significantly different by living group,
with higher values in the vowed religious community compared to the independent
retirement community. Spirituality, vitamin D intake, and daily sweets intake explained
50% of the variance in perceived stress scores in multivariate analyses.
Conclusion: Our findings suggest that older adults living in vowed religious
communities do not experience greater well-being than those living in independent
retirement community. Perceived stress in older adults may be reduced by certain
lifestyle practice.
1
CHAPTER 1
INTRODUCTION
Problem Description and Rational
Worldwide, stress is the second most common health problem that can negatively
impact an individual’s wellness 1. Unhealthy levels of stress can negatively impact both
mental and physical health in every age group. The U.S. Census Bureau projects that by
2050, 20% of the U.S. population will be over the age of 65 2. Increased exposure to
stressful life events and oxidative damage from chronic stress may specifically impact
older adults over younger generations 3. Stress and negative emotions activate the
hypothalamic-pituitary-adrenal (HPA) axis to release cortisol into circulation 4.
Prolonged activation of this axis has been associated with inflammation, physical and
mental health problems, and mortality 5. Specifically, stress can also induce
inflammatory brain-altering processes and are now thought to exacerbate brain aging 6,7.
Chronic exposure to acute stress and cortisol is related to DNA and RNA damage in older
adults 7. In a recent study that compared stress levels of caregivers and non-caregiving
controls, it was shown that the cumulative effect of daily stressors promoted elevations in
blood inflammatory markers 8.
2
Moreover, chronic stress is associated with negative physical and mental health
outcomes such as cardiovascular disease, metabolic syndrome, weight gain and late-life
depressive symptoms 2,9. Stress can affect mental health through dysfunction of the HPA
axis and increased serum cortisol levels, which may cause depression, decreased quality
of life and negative emotions. In older adults, increased perceived stress and stressful life
events can lead to an increase in depressive symptoms 2. Research also suggests that there
is increasing variability in self-esteem at progressively older ages, which increases stress
levels 10,11. Age-related declines in older adults’ self-esteem could derive from a loss of
social roles, social isolation, or an increase in physical health problems 12. In fact,
optimism has been found to buffer the association between perceived stress and elevated
levels of diurnal cortisol 13.
Dietary factors can influence mental health. A healthy diet and physical activity
has been shown to decrease perceived stress and improve health outcomes and health-
related quality of life 14. A recent prospective study published in the Journal of the
Academy of Nutrition and Dietetics assessed the associations between self-reported stress
and dietary intakes and dietary behaviors of adults in the United States 15. The study
found that higher perceived stress scores were associated with higher fat intake of the
calories consumed, greater intake of high-fat snacks, and fast food 15. This suggests that
people who perceive themselves to be more stressed are more likely to eat an unhealthy
diet, which over time can lead to health problems including excess weight gain and
obesity 15.
Lifestyle and environmental factors can also be influential with respect to mental
health. The stress or support in one’s everyday living environment may affect perceived
3
stress or depression. A vowed religious life lived in a close community may positively
influence these factors and even provide physical health benefits. Far removed from 21st
century social and cultural norms and pace, an ascetic lifestyle is one of self-discipline,
an absence of self-indulgence and regular acts of fasting, all of which may benefit ones
mental and physical health 16,17. For example, a prospective study in Italy that
investigated blood pressure, an indicator of stress, followed 144 nuns and 138 similar
laywomen controls for 20 years, and found that blood pressure did not increase with age
in the nuns compared to laywomen, an unexpected result only found in comparisons with
hunter-gatherer groups 18. While monks and nuns live a structured, cohesive, minimalist
lifestyle, adults living in an independent community typically are not limited by such
constraints, which may lead to mental health differences between the two populations. In
American older adults, 80% have at least one chronic disease and 50% have two or more.
In a study of 1085 independently living adults over the age of 60, those with more
chronic disease diagnoses had an increase in depressive symptoms and a decrease in
health-related quality of life 19.
Study Purpose
The aim of our study was to explore various dimensions of wellness: physical,
emotional, social, and spiritual, with a focus on stress, and associations with diet, lifestyle
factors, and physical health parameters in older adults. We also compared the wellness of
adults in different communal environments, by exploring these factors in both a vowed
religious community and an independent living community. Due to the older age of
adults in vowed religious environments, we limited our community group to 65 years and
4
older. Participants completed a survey with demographic questions as well as four
wellness scales; we also obtained physical measurements and took a 24-hour dietary
recall. We hypothesize that those living in vowed religious communities have less stress
and healthier dimensions of wellness than those living in an independent living
community.
Hypotheses
Relationship between Stress and Health and Lifestyle Factors
o H10: There is no difference in stress reported by gender in older adults.
o H20: There is no difference in stress reported by the vowed religious
community and the independent retirement community in older adults.
o H30: Perceived stress is not related to health and lifestyle factors in older
adults.
o H41: Certain health and lifestyle factors contribute to or predict perceived
stress in older adults.
Relationship between Alcohol and Health and Lifestyle Factors
o H50: There is no difference in weekly alcohol intake between genders in
older adults.
o H60: There is no difference in weekly alcohol intake between the vowed
religious community and independent retirement community in older
adults.
o H70: Perceived stress scores will not be different in levels of alcohol
intake in older adults.
5
o H80: Weekly alcohol intake is not related to stress or other lifestyle and
health factors in older adults.
Relationship between Sweets Intake and Health and Lifestyle Factors
o H90: There is no difference in sweets intake by gender in older adults.
o H100: Sweets intake per day does not differ in the vowed religious
community compared to the independent retirement community in older
adults.
o H111: Sweets intake is related to perceived stress in older adults and other
health and lifestyle factors
o H121: Perceived stress scores are different by sweets intake level in older
adults.
Perceived Stress and Body Composition:
o H131: Physical health parameters are associated with stress in older adults.
o H141: Muscle mass was associated with lifestyle factors in older adults.
6
H150: There are no differences in physical health parameters between
older adults in the two living environments.
o H161: Body fat and heart rate are associated with lifestyle factors in older
adults.
o H170: Perceived stress scores do not differ in older individuals with lower
and higher muscle mass.
Relationship between Geriatric Depression Scale and Health and Lifestyle Factors
o H181: Older adults living in the vowed religious group will report less
depression than those living in the independent retirement group.
o H191: Health and lifestyle factors significantly related to depression
explain the difference in depression we observed between living groups in
older adults.
o H201: Depressive symptoms reported by participants will be associated
with health and lifestyle factors in older adults.
Relationship between Amount of Sleep and Health and Lifestyle Factors
o H210: There is no difference in reported hours of sleep per night by gender
in older adults.
o H220: There is no difference in reported hours of sleep per night between
the vowed religious community and independent retirement community in
older adults.
7
o H230: There is no difference in health and lifestyle factors related to sleep
in three categories in older adults.
o H240: Reported sleep hours per night is not related to health and lifestyle
factors in older adults.
Variables To Be Examined:
o Demographics
o Perceived Stress
o Social Support
o Spirituality
o Depression
o Body Composition and Anthropometrics
o Blood pressure and heart rate
o Diet Composition
8
CHAPTER 2
LITERATURE REVIEW
Dimensions of Wellness
Wellness can be defined as the quantifiable daily practice, state or condition of
being in adequate physical, emotional, and mental health 20. In 1959, wellness research
originated with the work of Dr. Halbert Dunn. He coined the term “High Level Wellness
for Man and Society”, and his research focused on the synergistic relationship and impact
of health status relating to the mind, body and spirit 21. The research efforts and models of
practitioners since then have attempted to create, clarify and quantify variables that
impact “high level wellness” 20. Currently, in allied healthcare there are several
classification systems used to measure wellness including the Six Dimensional Model,
the Twelve Dimensional Model of Wellness, and the Sixteen Dimensional Model of
Wellness. All the models are multidimensional in nature and attempt to quantify the
physical, mental, social, and spiritual behaviors that contribute to health 20,21. The rest of
this section will focus on the four most common domains of wellness: mental, physical,
social, and spiritual.
9
Mental Wellness
Positive mental wellness has a positive impact on a person’s overall health.
Mental wellness or health as defined by the World Health Organization is a state of well-
being in which the individual realizes his or her own abilities, can cope with the normal
stresses of life, can work productively and fruitfully, and is able to make a contribution to
his or her community. An optimistic mental outlook has been shown to have a positive
impact on physical health measures, recovery from disease or trauma, and maintenance of
routine social engagement 22-24. A cohort study of 41,275 men diagnosed with clinically
localized prostate cancer from 2004 to 2007 were recruited to examine the relationship
between mood disorders and treatment outcomes 25. The study found that men with
depressive disorder overall had worse mortality than those who were not depressed 25.
In addition, a prospective study of 46 college students looked at the impact of a
positive emotion and risk of depression following a traumatic experience, September 11,
2001 26. The study found that students who exhibited the highest levels of optimism,
maintained a positive outlook on life, experienced frequent positive emotions and tended
to resist depressive symptoms following the events of September 11, 2001 26. These
studies illustrate that individuals who displayed an optimistic perspective tended to better
mental wellness, than those who with a negative outlook.
Physical Wellness
People with better physical wellness including measurements such as BMI,
normal lipid and glucose levels are more likely to have a better quality of life and longer
life expectancy. The second dimension of wellness, physical wellness, is classified by
10
having healthy ranges of anthropometric values, laboratory blood parameters,
cardiovascular measures, and physical capacity scores 27. A prospective cohort study of
1023 community-dwelling older adults tracked changes in allostatic load, which is a
measure of physiological wear and tear on the body including measurements such as
BMI, lipid panels, and blood glucose levels, over a 10-year period and compared these
factors to the sample’s mortality rate 27. Findings revealed that higher allostatic load or
rapidly increased allostatic load scores significantly increased mortality risk in older
adults 27.
In addition, a prospective study of 489 African American youth in the rural south
were assessed for changes in allostatic load at 11 years old and then at 19 years old 28.
The study illustrated that those who received consistent, supportive parenting and
positive friend influence had more ideal physical health measures, greater emotional
stability, and less behavior problems in school, at home and in the community 28. These
two studies demonstrate that objective physical health change is a valid and reliable
measurement of individual global wellness. Both studies demonstrate that changes to
physical health markers correlate to physiological function that strongly contribute to
overall life span and health.
Social Wellness
The third dimension of wellness that has a large impact on one’s overall health is
social wellness. The social dimension recognizes the need for contribution and positive
interaction with one’s family, friends and community members 22,29,30. In a cross-
sectional study of 316 Korean older adults, the effect of social support, religious
11
practices, and daily stressors on overall well-being was examined 23. The results showed
that higher perceived stress levels were associated with higher incidence of depression
and decreased life satisfaction. The individuals that received the most social support,
performed regular spiritual practices, engaged in frequent family interaction, and
participated in scheduled group leisure activities had significantly lower stress values and
higher quality of life 23.
In another cross sectional study of 755 pregnant Chinese women in their second
trimester were recruited to examine the direct and moderating effects of social support in
mitigating perceived stress associated with depressive or anxiety symptoms 31. The
findings showed that perceived stress, anxiety, and depression were lower in individuals
who had family members that were actively engaged in their lives. The study also
showed that individuals benefit from positive environments including: occupation, home,
local community, and medical providers that were supportive and showed concern for
their needs 31. These studies demonstrate that those who have more social support and
are actively involved in community activities have better social wellness. This increase in
social wellness positively effects overall wellness.
Spiritual Wellness
The final dimension of interest is spiritual well-being; research shows that those
with increased spirituality are healthier. Spiritual wellness addresses the search for a
meaning and purpose to human existence, and includes a deep appreciation for the
expanse of life and natural forces that exist in the universe. It is important to note that the
terms spiritual and religious are not synonymous. Religiousness as defined by Merriam-
12
Webster dictionary refers to being dutiful and conscientious when performing a specific
practice. Spiritual defined by Merriam-Webster dictionary means relating to, consisting
of, or affecting the spirit and or relating to sacred matters.
A study of 502 African Americans aged 50-105 years old were surveyed to
observe the impact of church attendance and level of involvement in their congregation
on perceived stress and mental health parameters 29. Results indicated that individuals
who were highly involved in their church community felt that they had a church family
that would help them in times of illness or tragedy, and had the ability to pray to God for
help with their personal burdens, concerns, or crises 29. People who were spiritually
active had lowered perceived stress values when compared to those who did not engage
in similar behaviors 29. In another study of 316 adults, 65 years old or greater living in a
retirement community examined the impact of spiritual coping practices and social
support on depression and life satisfaction. The study found individuals who exhibited
the greatest utilization of spiritual coping practices combined with social support
demonstrated the lowest depression scores and highest life satisfaction 23. These studies
demonstrate that those who are spiritually active had overall better quality of life and
health. This shows that belief in something greater is an important aspect to living a
healthy lifestyle.
Health and Wellness of Older Americans
Mental disorders such as stress, depression, and anxiety are common in the older
American population and can have detrimental effects on a person’s livelihood. Research
shows that mental disorders, such as perceived stress, can be destructive to an
13
individual’s life. In a cross-sectional study of 689 women aged 45-60, qualitative data,
such as stressful life events, health-related quality of life, mental health, chronic disease,
and depression were collected using the Life Stressor Checklist-Revised (LSC-R), Short
Form Health-Related Quality of Life (SF-12), and the Center for Epidemiologic Studies
Depression Scale (CES-D). Researchers found was that those who reported more life
stressors also reported more chronic disease 32. Similarly, in a population-based study of
6,207 adults measured socio-demographics, health behaviors, psychosocial measures,
cognitive function and health history. The findings of the study included that increasing
levels of stress was associated with cognitive decline in older adults aged 65 years and
older 33. Thus these studies show that perceived stress may lead to more chronic disease
and cognitive decline in older adults.
Depression
Depression in older adults may increase inflammation and risk of chronic illness.
In an experimental study of 138 adults, depressive symptoms, anxiety, and stress were
measured using the Center for Epidemiological Studies Depressive Scale, the Beck
Anxiety Inventory, Trier Social Stress Scale and the Childhood Trauma Questionnaire.
Whole blood was also drawn and analyzed to measure interleukin-6 concentrations. The
researchers found that participants who expressed more depressive symptoms also
demonstrated more inflammation and increased inflammation increased the risk for
chronic diseases, such as cancer, heart disease, and diabetes 34.
In a similar study, data was analyzed from the Health and Retirement Study. This 12-
year prospective study examined 3,645 individuals between the ages of 62-74 years old.
14
The study used the Center for Epidemiological Studies Depressive Scale to observe self-
reported depression, and a self-report of chronic illness. They found that in older
working adults, participants with depression at baseline had a significantly higher risk of
developing chronic diseases, specifically diabetes mellitus, heart disease and arthritis 35.
This indicates is that depression in older adults may have negative effects on health;
specifically it may increase inflammation and risk of chronic disease.
Associations of Stress and Depression
Research shows that depression and perceived stress in older adults are associated
with one another. In a longitudinal study involving 70 elderly depressed subjects,
hippocampal volume, perceived stress levels and life stressors were evaluated using the
Montgomery-Asberg Depression Rating Scale, MRI data, and a self-report questionnaire
concerning life stress. The researchers found that among the depressed participants there
was a higher prevalence of negative life events and higher perceived stress scores 36.
Similarly, in a cross-sectional study of 54 community-dwelling older women, memory
function, perceived stress, life events, activities, and depression were measured with a
questionnaire that the participants completed, that included the General Frequency of
Forgetting Scale, Perceived Stress Scale, Geriatric Scale of Recent Life Events, Activities
Checklist, and Geriatric Depression Scale 37. Researchers found that perceived stress,
along with anxiety and depression was affiliated with memory complaints, as stress can
impact the brain’s memory center, the hippocampus 37. This suggests that adverse mental
health issues in older adults, in particular stress and depression, may influence one
another and lead to further mental illness and memory problems.
15
Weight
Weight status plays an important role in overall health and wellness of older adults. In a
cross-section study published in the Journal of American Medical Association, Flegal et
al. examined the prevalence of overweight and obesity in the aging population 38. The
researchers used Body Mass Index (BMI) to measure body fat a person carries based on
height. The results showed that the obesity prevalence in 2011-2012 overall was 35.4%
for the whole sample, 32% for men, and 38.1% for women 38. Over one-third of the older
adult population is obese. Since obesity has been linked with increase risk of heart
disease, diabetes, and hypertension this is a very serious concern.
Similarly, in a cross-sectional analysis of US adults aged 65 years and older,
Fakhouri et al. examined the prevalence of overweight and obesity based on BMI 39. The
researchers found that for both men and women the prevalence of obesity was higher
among those aged 65‒74 years compared with those aged 75 years and older, and over
the past 10 years the prevalence has overweight and obesity has increased in this
population 39. Also, non-Hispanic black women were more obese than non-Hispanic
white women, and those with a college degree were less obese than those with some
college experience 39. These findings suggest that over time there has been a increase in
prevalence of overweight/ obesity in the older adult population and that weight status
varies by ethnicity and education level. However, it appears that those who are over 75
years have a decrease in weigh, which may be due to changes in dietary intake and
physical activity as person ages.
16
Physical Activity
Physical inactivity of the American older adult may contribute to a decline in
overall well-being. The Older American Report 2012, measured older adults’ physical
activity patterns using self-reported surveys and comparing the results to the 2008 US
Physical Activity Guidelines 40. The results showed there has been a 5% increase in the
number of individuals meeting the federal physical activity guidelines from 1998 to 2010
40. However, even with this improvement in the number of older adults meeting physical
activity recommendations the 11% of individuals meeting US physical activity guidelines
remains substantially low. A cross-sectional study of 975 adults aged 65 years and older
published in the American Journal of Epidemiology, examined associations between
physical activity level (e.g. sedentary to vigorous activity) and well-being variables (e.g.
chronic health complications, BMI, life satisfaction, depression, and perceived stress) 41.
Researchers found that participation in physical activity was positively associated with
physical health and well-being 41.
In addition, greater sedentary time was negatively associated with physical health
and perceived well-being; whereas, light, moderate, and high physical activities were all
positively associated with physical health and perceived well-being 41. Additionally, a
study by Bankoski et al. investigated the association between sedentary activity and
metabolic syndrome among 1,367 older adults, aged 60 and older 42. Sedentary times
during waking hours were measured by an accelerometer and metabolic syndrome was
defined using the Adult Treatment Panel III criteria. Over all, the sample spent 9.5 hours
sedentary, and individuals with metabolic syndrome spent even more time sedentary than
compared with people without metabolic syndrome 42. Independent of physical activity,
17
the amount of sedentary time was significantly related to metabolic risk 42. Overall,
participation in physical activity was positively associated with physical health and well-
being for the older adult population, but despite this finding, the majority of older adults
spend their time sedentary and physical inactivity, which can increase the risk metabolic
syndrome and other chronic diseases.
Dietary Patterns in Older Adults
Diet plays an important role in overall health and well-being. The current trends
in health and wellness of the older adult population aged 65 years and older is
characterized by poor diet quality, as defined by not meeting United States (US) dietary
guidelines. The Older American Report 2012, a cross-sectional analysis, examined health
and wellness factors of 40 million US adults, aged 65 years and older. Diet was measured
using the Healthy Eating Index-2005, and diet quality of participants was compared to
recommendations of the 2005 Dietary Guidelines for Americans 40. According to the
report, 79% of adults between the ages 65-74 years believed they were in good health,
but the data actually indicated that this population was not meeting US dietary guideline
recommendations through their current dietary patterns 40. This is a concern because
older adults with overall poor quality diets have an increased risk of chronic disease
compared to those with high quality diets.
A 10 year cohort study of 2,200 participants aged 55 years and older, published in
the Journal of Academy of Nutrition and Dietetics, investigated the association between
diet quality, quality of life, and activities of daily living 43. The researchers found that the
majority of participants had poor diet quality; however, those who had adequate nutrient
18
intake reported better quality of life 43. In fact, participants who consumed more than 5
servings of vegetables per day, ate low-fat dairy products and whole grains, and followed
a low sodium diet had a 50% reduction of disability of activities of daily living in 5 years
43. In addition, improved dietary intake was associated with more education, increased
duration of exercise, and lower body mass index 43. All of these findings support the idea
that regularly eating a high quality diet improves overall health and wellness of older
adults. Additionally, a study from the Journal of Cancer, investigated health behaviors
and associations with quality of life outcomes in 753 participants aged 65-87 years old 44.
The researchers found that individuals who participated in regular moderate-to-vigorous
exercise and consumed a plant based, low-fat diet had better quality of life health
outcomes 44. Also, researchers found that physical inactivity may predict poor diet
quality, decreased social function, and an increase in chronic health complications 44.
The findings from the Older Adult American report and the studies by Gopinath
et al. and Mosher et al., suggest that overall, older adults’ dietary patterns are
characterized by poor quality including consuming below the recommended 5 servings of
vegetables per day, choosing white grains instead of whole wheat grains, and eating
foods high in concentrated sweets and sodium. Furthermore, the data suggests that older
age, less education, and higher BMI were associated with increased risk of activities of
daily living disability. These results suggest that diet may be a predictor in the health and
wellness of the aging population, and diet plays an important role in the overall health
and wellness of the aging population.
19
Health and Wellness of the Vowed Religious Community
The vowed-religious community adheres to a life of self-discipline and active spiritual
practices, and there is a theory that this kind of lifestyle positively impacts the health and
wellness of this community. People in religious orders often follow a stricter diet and do
not participate in many activities that can increase daily stress 45,46.
Dietary Patterns in Vowed Religious Communities
Monks and nuns often adhere to strict dietary practices that align with their
contemplative lifestyle, which can affect overall health. Many adopt a lacto-ovo
vegetarian diet and as a result of these dietary restrictions, some vowed religious persons
diets’ are low in B vitamins, calcium, iron, magnesium and zinc 45,46. For example, zinc
deficiencies may be explained by high intake of phytate rich foods and decreased calcium
intake due to fasting. Monks who fast regularly have favorable nutrient and food intake
profiles. Overall, they had decreased intake of total fat, saturated fat, and trans fatty acids,
with higher intake of iron, folate, legumes, fish, seafood, and fiber in comparison to
laypersons. While fasting is an integral part of the monastic life, benefits go beyond
spiritually, including a greater nutrient composition 25,46.
Blood Pressure
It appears that those living in religious orders have lower blood pressure, which
may be result psychosocial influences. A 32-year prospective study by Timio et al.,
looked at differences of anthropometric and blood pressure measurements, blood panels
and overall health practices of 144 white nuns and 138 healthy laypersons 18.
Researchers found that over the 32 years laywomen’s blood pressure significantly
20
increased, whereas nuns’ blood pressure remained nearly stable 18. Researchers noted that
other variables that often affect blood pressure including age, race, lifestyle habits, did
not vary between the two groups. Therefore, researchers speculated that psychosocial
influences including conflict, anxiety and aggression might have been the determining
factor for an increase in blood pressure in laywomen. This study suggests that women in
religious orders may have better mental health factors lead to a healthier lifestyle.
Moreover, an additional study found nuns’ cardioprotective health remains stable
compared to laywomen who have increased blood pressure with age 47,48. The study
found that laywomen had more non-fatal cardiovascular events than nuns, 31 versus 69,
with psychological stress being the underlying cause of such events 47,48. In these studies
it appears that psychosocial experiences of those in religious orders may be a factor in the
prevalence of lower blood pressure.
Comparison of Groups
While older adults’ daily habits are not as uniform as those living in the vowed
religious community, many older adults appear to be living a happy, healthy life. A
cross sectional study conducted by Cha et al., 2012, sought to uncover the successful
aging factors in Korean adults 49. Using the self-liking/self-competence scale, self-
efficacy scale, interpersonal relationship scale, self-achievement instrument, and
successful aging scale, it was found the largest contributor to successful aging was self-
esteem. Additional factors included level of involvement in religious activities, which
provides a positive view on life, including group meditation, social gatherings, prayer,
and increased positive thinking. While religion cannot be held entirely responsible for
21
older adults’ mindset, it does indicate it is an activity that promotes a positive, active
lifestyle 50.
Moreover, a study led by Schlehofer et al., 2008, aimed to gain a better
understanding of how the average older adult sees religion and spirituality and if there
was a difference in views found between the sample 50. Participants had a hard time
providing concrete definitions of spirituality, even though they considered themselves
highly religious, and subjects saw religion as an opportunity to be part of a community,
ability to make connections with others, and to be part of a larger identity 50. While older
adults’ perspective on religion is not as structured as those living in the vowed religious
community, those living in the independent retirement community recognize the
importance of constant spiritual practices.
It’s evident the vowed-religious community and independent retirement
community older adults have distinct qualities. The vowed-religious live a very
structured life, with activities and roles clearly defined and are given a balance of solitude
and communal scheduled time, recognizing the importance of both for overall personal
growth. Material possessions and food consumption are secondary to serving, with
obedience, fasting, and discipline being key aspects of the culture. Comparatively,
independent older adults living a modern life are characterized more by “free will”. Diets
are more liberal with age, yet the amount of physical activity is often left unadjusted with
increased food intake. Additionally, older adults’ make their own schedules, which are
dictated by personal interests, not by rank or position in the community. While the
vowed-religious live a minimalist life, independent older adults live at the other end of
the spectrum, with less structure and more flexible decisions.
22
Mechanisms of Stress
Stress is a state of altered homeostasis in response to mental or physical stressors.
Many things can cause stress in an individual’s life such as work, life events and financial
problems. Stress can cause symptoms such as depression, anxiety and sleep issues as well
as negative health outcomes such as cardiovascular disease, weight gain, and insulin
resistance 51.
The normal stress response includes both physiological and behavior responses
that strive to restore homeostasis. Two main physiological systems are involved in the
normal stress response, the sympathetic nervous system and the hypothalamic-pituitary-
adrenal axis (HPA axis) 52. The sympathetic nervous system is very fast acting and works
to quickly adapt to stressful situations through the release of epinephrine and
norepinephrine 52. The HPA axis is slower acting, which allows for long-term adaption to
a stressful condition 52. The HPA axis activates the corticotropin-releasing factor in the
hypothalamus, which then stimulates the release of adrenocorticotropin hormone from
the pituitary gland. This causes the release of glucocorticoids, stress hormones, from the
cortex of the adrenal glands. Glucocorticoids regulate the stress response through a
negative feedback loop with the hypothalamus and pituitary gland. The normal stress
response occurs in response to acute stressors. Prolonged exposure to acute stressors is
known as chronic stress. Chronic stress can alter the body’s normal stress response,
metabolism and homeostasis, and may produce psychological and physiological damage
4. Cortisol is a main glucocorticoid that is associated with pro-inflammatory molecules
and cytokines such as interleukin-6 (IL-6) and C-reactive protein (CRP) 8. High amounts
of daily stressors can lead to chronic low-grade elevation of those inflammatory markers
23
8. Elevation of IL-6 and CRP is associated with increased risk of weight gain, depression,
cardiovascular disease, insulin resistance, diabetes, cancer, autoimmune disease, frailty,
and mortality 8. A cross sectional study of 53 caregivers and 77 non-caregivers were
observed to determine if daily stressors impact circulating levels of IL-6 and CRP. The
caregivers had a greater occurrence of daily stressors as well as an increase in the
inflammatory markers IL-6 and CRP 8. This demonstrates the inflammatory response that
is associated with chronic stress.
Cortisol levels have been found to increase rapidly after awakening. This
measure, if monitored frequently, can be used as a baseline for adrenocortical and HPA
axis activity 53. After awakening, serum cortisol increases by 50-60% regardless of sleep
duration, quality and routines 53. Since the cortisol awakening response is consistent, if
monitored closely, it can reveal subtle changes in cortisol levels and HPA axis activity 53.
In a twin study of 104 pairs aged 8-64, cortisol awakening was measured with saliva
samples 0, 30, 45 and 60 minutes after awakening, and participants filled out surveys
regarding psychosocial factors such as stress, self-esteem and self-efficacy. Those with
higher perceived chronic stress had increased cortisol awakening responses, showing the
relationship between chronic stress and altered hormonal cycles 53. A study of 22 healthy
individuals had their blood and saliva tested 0, 15, 30, 45 and 60 minutes after awakening
54. The participants who were chronically stressed had an enhanced cortisol awakening
response and those whose chronic stress lasted for years or had reached a burn out stage,
where they were no longer able to cope with their stress, had a blunted cortisol response
and increased feedback sensitivity 54. This demonstrates the relationship between chronic
stress and the disruption of normal hormone responses. The normal stress response in the
24
body involves multiple physiological and behavioral responses. When there is over
exposure to stress, there can be a dysfunction of the normal stress response, which can
lead to negative health outcomes.
Impact of Chronic Stress on Physical Wellness
Chronic stress has been linked to negative health outcomes such as cardiovascular
disease, metabolic syndrome and weight gain. Job stress, marital stress and financial
stress all impact these negative health outcomes. Repeated social or environmental stress
can cause a dysregulation of the normal stress response and alter the activation HPA axis
and glucocorticoids, leading to cardiovascular, immune and metabolic symptoms 2.
Cardiovascular disease is a common negative health outcome related to chronic
stress. The mechanisms relating stress and cardiovascular disease include both behavioral
and physiological factors such as smoking, lack of exercise, insulin resistance, and
increased blood pressure 55. The INTERHEART study, a case-control study that matched
11,119 participants with a first myocardial infarction and 13,648 healthy controls across
52 countries, measured psychosocial stress, including work, home, financial and life
stress in participants. The results of INTERHEART study demonstrated the association
between increased psychosocial stress and risk for myocardial infarction 51. Behavioral
factors are also involved in cardiovascular risk and stress. A group of 10,308 government
employees, aged 35-55 years old, were studied to determine the risk for coronary heart
disease related to chronic work stress. Work stress was associated with lower physical
activity, poor diet, metabolic abnormalities and a higher rise of morning cortisol 56.
25
The mechanism by which stress increases cardiovascular risk likely involves HPA
axis dysfunction and cortisol regulation 57. In a prospective cohort study of 479 initially
healthy men and women, blood pressure and cortisol reactivity were measured at baseline
and at a three-year follow up. There was an association between hypertension and cortisol
reactivity 57. Cortisol can directly influence the physiological systems that are
responsible for regulating blood pressure; the results of this study demonstrate that HPA
axis hyperactivity is involved in the mechanism that related stress to cardiovascular risk.
Chronic stress is related to both increased cardiovascular disease and death associated
with cardiovascular disease. A 2012 study focused on perceived stress following an acute
myocardial infarction (AMI) in hospitalized patients in the United States. Patients with
higher perceived stress following their AMI hospitalization had an increase in mortality
within two years 55.
Cortisol is an insulin antagonist; during chronic stress there are high levels of
serum cortisol and this may alter normal insulin production and functionality in the body
58. Metabolic syndrome is a group of risk factors related to cardiovascular disease, insulin
resistance and obesity. Chronic stress can contribute to the risk for metabolic syndrome,
through both physiological mechanisms and behavioral mechanisms associated with
stress such as poor diet and smoking. A prospective cohort study of 10,308 participants
had work stress and biological markers of metabolic syndrome measured four different
times over a course of fourteen years. Work stress increased the risk for metabolic
syndrome in a dose-response manner and those with chronic work stress had double the
chance of developing metabolic syndrome in their lifetime 58. Additionally, in a
prospective cohort study of 120 women followed for fifteen years, psychosocial factors
26
such as perceived stress and depression were measured, as well as serum metabolic
syndrome markers. Women who had higher amounts of stress in their life had an
increased risk of developing metabolic syndrome 59. Psychosocial factors, such as stress,
can increase risk of developing metabolic syndrome through physiological or behavioral
mechanisms.
The allostatic load model demonstrates how psychological demands such as
excess stress can negatively impact ones physiological health. An Australian cross-
sectional study looked at psychosocial factors and their affect on arthritis in women ages
51-61 years old. Those with moderate to high perceived stress had a 2.5 fold increase in
report of arthritis demonstrating that increased perceived stress can manifest through
negative physiological health outcomes 60. Critical illness is an example of an acute
stressor and therefore often results in elevated cortisol levels and pro-inflammatory
cytokines. A case control study matched 158 patients in the intensive care unit (ICU)
with 64 controls and measured different markers of the hormonal stress response. The
ICU patients had elevated cortisol levels caused from both over production of cortisol as
well as altered cortisol clearance during the time of acute stress 61.
Impact of Chronic Stress on Mental Wellness
The normal stress responses involving glucocorticoids and the HPA axis is also
related to mental health. Chronic stress may be related to cognitive impairment 4.
Increased activity in the HPA axis and elevated amounts of serum cortisol is associated
with depression 62. Cortisol is able to cross the blood brain barrier, where it can activate
receptors and alter central nervous system activity 52. A high concentration of stress
27
hormones can also inhibit neurogenesis, the creation of new neurons, which may alter
mental health 63. Five hundred and sixty-five participants who met the Diagnostic and
Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for major
depressive disorder were evaluated using surveys and blood samples. Those with
dysfunction in the HPA axis had agitation symptoms and cognitive disorders within their
major depressive disorder diagnosis 62. In 2013, 125 adults ranging from 67-94 years old
were studied to determine an association between allostatic load, the dysfunction of the
HPA axis and glucocorticoid response due to increased environmental and social stress,
and depressive symptoms. Participants were interviewed to determine allostatic load
score and overall depression risk. Higher allostatic load scores were associated with
increased depressive symptoms 2. These studies demonstrate the association between the
HPA axis and mental health. Dysfunction of the normal stress response and increased
exposure to acute stressors can negatively impact mental health.
Mental health may also be affected by the stress response through behavioral side effects
of stress, such as altered sleep patterns and quality of life. A cross-sectional study of 181
older adults focused on the relationship between perceived stress and mental health.
Those with higher perceived stress had reduced quality of life, increased depressive
symptoms, and increased sleep disturbances 32. This demonstrates a different relationship
between stress and mental health.
Stress may also affect mental health through mood and emotions. Stress is often
related to negative affect and may be due to high cortisol levels through the dysfunction
of the HPA axis. A randomized controlled trial of 232 participants underwent either a
Trier Social Stress Test or a placebo stress test and had their saliva tested for cortisol
28
levels, emotional responses were rated using the Positive and Negative Affect Schedule
52. Those who experienced the Trier Social Stress Test had higher cortisol levels and
higher negative affect than those who underwent the placebo stress test, which
demonstrated that stress can alter mood and emotions through dysfunction of the HPA
axis and hormonal mechanisms 52. Stress can affect mental health through dysfunction of
the HPA axis and increased serum cortisol levels, which may cause depression, decreased
quality of life and negative emotions.
Impact of Stress on Eating Behaviors and Weight
Weight gain is often caused from a positive energy balance, but stress and its
effects on behavior and metabolism can contribute to obesity risk 64. As discussed earlier,
chronic stress can be a predictor of metabolic syndrome and cardiovascular disease, both
of which are also related to obesity 64. In a 2011 longitudinal study of 72 participants,
BMI was measured as well as social stressors, including work and social life. Social
stressors were found to be significant predictors of BMI 65. A prospective, 19-year study
in London aimed to evaluate the relationship between chronic work stress and obesity in
over 10,000 participants aged 35-55 years old. The study revealed that chronic work
stress predicted both general and central obesity 64. Chronic stress alters the normal stress
response, leading to altered adrenocortical activity, insulin resistance, abdominal obesity
and metabolic syndrome 64. A 2013 study examined the relationship between stress and
physical health in older Australian adults ages 60-70 years old. The results showed that
those who reported higher life stressors had higher BMI and increased occurrence of
chronic disease 32.
29
Chronic stress may impact obesity both directly and indirectly through behaviors
such as poor diet, alcohol consumption and low physical activity 64. An observational
study on government in employees sought to demonstrate a relationship between work
stress and blood pressure. Results showed that increased work stress led to increased use
of coping mechanisms such as alcohol consumption, unhealthy eating patterns and
physical inactivity 66. These coping mechanisms are associated with obesity. Stress may
change diet and exercise behaviors, which may impact and influence body weight and
weight gain during times of chronic stress 67. In a 9-year longitudinal cohort study, 1,355
US adults were followed with psychosocial stress and BMI being measured regularly.
Results showed that psychosocial stress contributed to weight gain in those who had a
higher baseline BMI, and stress can caused some participants to eat more or less than
usual and alter eating habits 67.
A healthy diet and physical activity have shown to decrease perceived stress and
improve health outcomes and health-related quality of life 14. A randomized controlled
trial of overweight and obese women aimed to determine if diet and exercise could
increase psychosocial factors and health related quality of life. The women were assigned
to one of four interventions: dietary weight loss, aerobic exercise, combined diet and
exercise, or control. The combined diet and exercise group saw the largest positive
outcomes on psychosocial factors, including stress, and health related quality of life 14.
Stress can negatively impact weight and eating behaviors through both direct and indirect
mechanisms such as alteration of the normal stress response and coping devices like junk
food and alcohol.
30
A healthy diet and exercise may improve health outcomes and lead to better quality of
life. Control of stress may improve eating habits, weight and quality of life.
Stress and Aging
The U.S. Census Bureau projects that by 2050, 20% of the U.S. population will be
over the age of 65 2. Within this age group, increased perceived stress and stressful life
events can lead to an increase in depressive symptoms 2. Increased exposure to stress can
accelerate the biological aging mechanisms such as inflammation and telomere length 7.
Psychological stress is associated with increased oxidative damage, which contributes to
aging and age-related chronic diseases such as neurodegenerative, metabolic,
cardiovascular diseases and cancer 7. The stress hormone cortisol is released after
stimulation by an acute stressor and chronic exposure to acute stress is related to DNA
and RNA damage in older adults 7.
Mitigating Factors of Stress
While perceived stress is a mental health factor that affects many Americans,
even those in the older Adult population, there is a growing body of evidence that has
found that there are many healthy ways to mitigate the symptoms of stress 68-70. These
stress relieving tactics range from dietary habits to physical activity to social and spiritual
support. Many researchers focus on dietary patterns and foods that are associated with
increased and decreased stress in a variety of populations. Research has found diets high
in fruits and vegetables, high in omega-3 fatty acids, using multi-vitamin supplements are
predictors for decreased stress in people.
31
Multivitamin/Mineral Supplements
Currently, there is a belief that regular multivitamin/mineral supplementation may
lower stress. Reasons for taking these supplements include improving mental function
and for improvements in stress and tiredness. Researchers have looked at one supplement
in particular, Berocca, a high dose B-complex vitamin and mineral and its effects on
mood. A double blind randomized control trial of 80 healthy men, between the ages of
18-42 years, were given either the Berocca supplement or placebo for 28 days.
Participants’ health was assessed before the 28-day intervention and after, using the
General Health Questionnaire, Hospital Anxiety and Depression Scale, and the Perceived
Stress Scale 71. Post-hoc test revealed that the treatment group had significantly lower
perceived stress scores than the placebo group after the 28-day intervention 71. Similarly,
a double blind, randomized, placebo controlled trial study of 215 males between the ages
30 and 55 years was given either the Berocca supplement or placebo for 33 days, and
then health and mood was assessed using varies health surveys, including the Perceived
Stress Scale 72. Once again after the 33-day treatment period, participants in the treatment
group had significantly lower perceived stress scores 72. Both of these studies
demonstrate that multi-vitamin/mineral supplementation in males can reduce perceived
stress of healthy individuals.
Finally, a double blind randomized trial of 173 men without a history of
aggression or impulsive behavior assessed how a multivitamin/mineral, DHA, or both
affected aggression, impulsivity, and stress. The men were divided into one of four
groups: placebo group, multivitamin/mineral group, DHA group, or
multivitamin/mineral/DHA group 73. The researchers found that the only group that had a
32
significant decrease in stress after the intervention was the vitamin/mineral group 73.
Once again, this reiterates that the use of a multivitamin and mineral can be helpful in
reducing stress of healthy males. Little research has looked at how a vitamin/mineral
supplement would affect females or older adults, but based on the current research, one
may hypothesize that these groups would have similar outcomes as younger, healthy
males.
Omega-3 Fatty Acids
In recent years, omega-three fatty acid supplementation and its affect on a
person’s perceived stress level has become increasingly popular area of research. The
thought behind consuming these fatty acids to reduce stress includes idea that the
polyunsaturated fatty acids act on the hypothalamic-pituitary-adrenocortical (HPA) axis,
by reducing pro-inflammatory cytokine production and stop the IL-1 signally pathway,
which in the end reduces corticotropin-releasing factor 1 (CRF) and HPA activation, and
ultimately prevents stress from rising 74. Because there is scientific research to
demonstrate that omega-3 fatty acid supplementation may physiologically affect stress
levels, researchers have tried to demonstrate such findings in human clinical trials.
One study investigated whether omega-3 phosphatidylserine (PS)
supplementation affected the psychological and physiological measures to the acute
stressor, the Trier Social Stress Test (TSST). This was a randomized, double blind,
placebo-controlled trial, and men between the ages of 30-60 years were assigned to either
the placebo group (n =30) or the treatment group (n =30) 75. Stress was measured before
and after the 13-week supplement intervention and perceived stress was measured using
33
visual analog scales (VAS). The results showed that after 13 weeks participants with high
chronic stress who were given omega-3 phosphatidylserine supplement had significantly
lower stress scores than those who were given the placebo, but this change was not noted
in participants who were characterized as having low chronic stress levels 75. This is an
interesting finding because it suggests that omega-3 fatty acid supplementation may only
lower a person’s perceived stress if the person has relatively high levels of chronic stress.
For people who have short episodes of chronic stress fatty acid supplementation may not
be effective in lower stress levels.
In addition as study published in 2003, assessed the effect of 7.2 gm/day of
omega-3 fatty acid supplementation on the sympathetic nervous system and stress
hormones associated with mental stress. Participants underwent mental stress tests before
beginning supplementation and 3 weeks after, and blood samples were collected to assess
stress hormones including cortisol and insulin, as well as blood pressure and heart rate 68.
After the 3-week supplementation period blood markers of stress in participants who
underwent mental stress tests significantly decreased 68. This shows once again that
omega-3 fatty supplementation may be beneficial in reducing mental stress, which is
important since high levels of chronic stress are associated with increased risk of many
diseases.
While these studies demonstrate that omega-3 fatty acid supplementation has
beneficial effects of perceived stress levels, there is some research that states that omega-
3 fatty acids are not beneficial for improving mood. In a randomized, double-blind,
placebo-controlled trial of 302 independent-living older adults (over 65 years) the effect
of supplementing EPA + DHA on mental wellbeing was assessed 76. Mental well-being
34
was measured using the Center for Epidemiologic Studies Depression Scale,
Montgomery Asberg Rating Scale, Geriatric Depression Scale, and Hospital Anxiety and
Depression Scale, and participants were either given 1800 mg/d EPA + DHA, 400 mg/d
EPA + DHA, or placebo for 26 weeks. At the end of the study no differences in mental
wellness were found between the three groups, indicating that omega-3 fatty acids do not
improve older adult mental well-being 76. Authors argue that changes in mood may not
have been seen because it is unclear what level of supplementation is needed 76, and that
most of the surveys assessed depression, not stress, therefore for those who were not
depressed, changes in mood may not have been observed.
Fruits and Vegetables
Finally, reducing stress may be that as simple as a well-rounded, primarily plant
based diet. There is a body of evidence that shows that people who eat mostly fruits and
vegetables have lower perceived stress than those who are eating more traditional
Western diet. This diet includes greater consumption of refined grains, added sugars, and
fats and oils. A recent cross-sectional study of 3706 university students in the United
Kingdom looked at how diet affects overall mental health. Participants’ intake was
assessed with a food frequency questionnaire and mood was measured with the Perceived
Stress Scale and Beck Depression Inventory 77. Consumption of healthy foods including
fruits and vegetables was significantly negatively associated with perceived stress and
depression. Similarly, consuming unhealthy foods like sweets, cookies, snacks, and fast
food was positively associated with perceived stress in females only 77.
35
Similar studies have been produced in the older adult population. A cross-
sectional study of 1336 Puerto Rican older adults, 45-75 years old, looked at associations
between psychological stress and nutrition. Perceived stress was measured with a Spanish
version of the Perceived Stress Scale, and general health status and behaviors were
measured with a survey based on the NHANES III 69. Perceived stress was negatively
associated with lower intake of protein, fruit, vegetables, fiber, and omega-3 fatty acids;
and positively associated with foods characterized by salty snacks and sweets 69. While
these studies demonstrate the negative association between fruits and vegetables and
perceived stress, it does not indicate a casual effect between the two variables. Further
research that can show changes in perceived stress overtime in necessary for one to be
able to make the statement that diet high in fruits and vegetables can reduce stress.
Physical Activity
Research demonstrates that physical activity and formal exercise are associated
with lower perceived stress. While the terms physical activity and exercise are often used
interchangeably, they actually have different meanings. Physical activity is used to
describe low to moderate intensity aerobic chores including household, occupational or
recreational movements and physical hobbies. In comparison, exercise is a subset of
physical activity that can include aerobic movement patterns, but most appropriately used
to describe intense and deliberate physical stress including anaerobic activities. Formal
exercise is planned, structured, progressive, and performed to improve at least one aspect
of physical fitness such as: muscular strength, muscular endurance, flexibility, balance or
cardiovascular conditioning 47.
36
In a 2013 cross sectional study of 14,804 college students, the association
between vigorous activity and perceived stress was examined to better understand the
relationship between the two 70. Perceived stress and activity level were self-reported, and
the results indicated that individuals who performed at least twenty minutes of vigorous
exercise three days a week had lower perceived stress scores than those who had lower
frequencies of activity 70. A similar study examined the impact of moderate physical
activity and perceived stress in a senior living population. The researchers assessed 164
individuals with who had mean age of 72 over a 4-year timeframe 78. The results showed
that individuals who participated in moderate activities for 2-5 hours a week had lower
perceived stress scores and reduced co-morbidities when compared to those individuals
who did not 78. These studies demonstrate that even if people are physical active only a
few hours a week, perceived stress decreases. This emphasizes the importance of
choosing an active lifestyle.
Social Support
Increased social support and community involvement are associated with better
mental health including lower perceived stress. Research shows that social engagement is
a stand-alone core behavior that can be utilized to strongly improve overall health status
64,79. In several studies social support has demonstrated to be as significant as diet or
physical activity and can work synergistically with them to lower perceived stress and
improve physical health measures. In a 2013 cross sectional study of 14,804 college
students, researchers aimed to investigate the relationship of social activity and perceived
stress. Findings demonstrated that individuals who had five or more close friends or spent
37
two or more hours a day in some form of social communication or shared group activities
had lower perceived stress scores 70. However, those who also exercised showed further
modulation of stress.
This study highlights that positive, consistent social support from friends and
family members are every bit as significant as diet and physical activity when improving
or sustaining health and lifespan in the long run. Individuals who want to effectively
manage chronic stress levels will need to include some degree of constructive routine
engagement with their family, friends and local community as part of a comprehensive
program 29,70,80.
Spiritual Practices
Research shows that people who are spiritually active experience less perceived
stress than those who are not. A study of 111 undergraduate college students, between the
ages of 18 to 40 years old, looked at whether praying before a stressful situation lowered
physiological and psychological markers of stress 81. Heart rate, blood pressure, an
Anxiety Thermometer, and the State-Trait Anxiety Inventory, Importance of Religion
scale, and Prayer Experience survey were used to measure prayer and stress scores.
Results showed that prayer lowered systolic and diastolic blood pressure values when
exposed to an acutely stressful situation, but self-talk also positively reduced levels of
stress 81. While prayer, an aspect of spiritual practice, reduced stress, which was not the
only factor that reduced stress, in comparison no self-talk prayer did reduce stress.
Similarly, a cross-section study of 316 older adults 65 years and older living in
assisted living facilities assessed how perceived stress, spiritual coping and support,
38
active, and avoidance coping impacted depression 23. The study found that perceived
stress and spiritual coping are significantly related to psychological well-being in older
adults including stress and depression 23. These studies show that increased spiritual
practices positively impact a person’s stress levels. People who regularly pray, attend
church, and/or meditate may have better levels of stress and overall a healthier lifestyle.
39
CHAPTER 3
METHODOLOGY
Research Study Design
The research design was a cross-sectional study, the participants were evaluated
with a wellness survey, physical stress measures, (systolic blood pressure, diastolic blood
pressure, heart rate), anthropometric values and 24-hour dietary recall. Participants
signed consent forms that identified study parameters and personal acceptance of risk
during the data collection process.
The three requirements for participation in the study were: participants had to be
65 years of age or older. Second, individuals had to be able to engage in daily activities
without assistance and be without significant cognitive impairment. Last, the study
participant had to live in either a monastic community or in an independent living senior
community exclusively, opposed to a residential home or apartment unit.
Individuals could not participate in the study if they required assistance with
activities of daily living or had significant cognitive difficulties.
Research Study Recruitment
The total study population was collected through a convenient sample of thirty-six
individuals from four monastic communities and thirty-two individuals from an
independent retirement community.
40
Data of one participant from a monastic community had to be removed from the
sample, due to their inability to complete the survey information. The validity of our
sample was improved by having similar sex, age, ethnicity, physical health, and
socioeconomic status findings between the two communities.
The recruitment protocol began by contacting local suburban monastic and
independent living facility Directors. They were initially contacted through an
introductory standardized email, “I'm a graduate student in the Nutrition Department at
Benedictine University. My study mentor, Dr. Bonnie Beezhold, and a few other
graduate students are conducting a study to investigate diet, lifestyle, and health
measurements associated with perceived wellness….” Several days after the email was
sent out, a follow-up phone call was placed to gauge interest and further clarify
participation questions. The communities that were interested scheduled an onsite
interview with a student representative accompanied by the study mentor for a detailed
overview of the research process. The communities that decided to proceed forward with
the study were given a formal flyer advertising the study to be placed at key
thoroughfares inside their facilities. The flyer was accompanied by a sign-up form several
weeks before the data collection date. The forms and scripts are listed in Appendix C.
Study participants were asked to complete a wellness survey at station one that took
approximately 25 minutes and then move through three additional stations ranging in
time from five to twenty minutes each. Station two collected blood pressure and pulse.
Station three measured anthropometrics and station four recorded previous day’s dietary
intake.
41
Data Collection Methods
We used objective health measures that could validly assess our study sample and
were deemed reliable to measure our desired wellness dimensions of study. We started
by researching variables that could be used to quantify participants’ health and lifestyle
factors. Our efforts concluded with a set of anthropometric, physical stress measures, diet
and daily behaviors that when combined create a comprehensive summation of physical,
emotional, spiritual and mental health status. We next examined previous research studies
for tools and survey instruments that were appropriate for our study design and age
group. A complete discussion of the all the equipment used during our data collection is
listed in the measurement tools section.
Data Collection Process
The data collection process ran over a three-month period, March through May,
with data collection days occurring on several Fridays and Saturdays.
The on-site data collection followed a sequential process. The survey was
provided in a quiet area, including a consent form notifying the participants of any
potential risks during the assessment process as well as written acknowledgement of the
terms of participation. Second, blood pressure and pulse was gathered in a seated
position. The third station administered height and waist measurements, as well as the
body fat, lean muscle and weight totals. The last station, collected 24-hour dietary recall
performed in a one-on-one interview format. All data was collected on site at each
facility.
42
The study took place at five locations. The following is a listing of the
participating sites in the study with a brief description of their populations:
● St. Procopius Abbey (5601 College Rd, Lisle, IL 60532)
● Marmion Abbey (850 Butterfield Rd, Aurora, IL 60502)
● Sacred Heart Monastery (1910 Maple Ave, Lisle, IL 60532)
● School Sisters of St. Francis of Christ the King (13900 Main Street, Lemont, IL
60439)
● Monarch Landing (2255 Monarch Dr, Naperville, IL 60563)
The first three vowed religious communities listed practiced Benedictine
monasticism. Their teachings originated in medieval Italy by its principal founder St.
Benedict and can be practiced by both women and men 82. Their lives are arranged by a
charism, or guide book that can be summarized into five large themes of the order:
Hospitality -welcoming all who enter their community, indiscriminate of their
religion or background 83. Prayer- daily mindful focus on God individually and
collectively 83,84. Obedience-Taking an active position of openness and availability to
God’s voice and direction in life 83,84. Stewardship and Stability- respect for wise and
moderate use of natural resources for the good of all. Some even call Benedictines the
forerunners of the green movement and ecological consciousness. Stability refers to
remaining and working diligently in one abbey and community for one’s lifetime. Thus,
fostering the development of deep lasting relationships and concern for fellow brothers,
community organizations and members 82,84. Love of Learning – centers around teaching
the integration of thought and action as complementary aspects of life. The actions
include preserving the intellectual and material works created from previous generations
43
and creating scholarly, artistic and scientific works which enrich and enlarge human life.
The majority of these monastic communities are in congregations for purposes of mutual
assistance and common discipline. However, Benedictine communities are diverse, with
some individuals pursuing an enclosed life with little involvement in the local church and
society. While, others insist on various degrees of involvement, ranging from
educational instruction at all levels, parochial ministry, evangelization, publication,
health care, etc. 82-84.
School Sisters of St. Francis of Christ the King was the only Franciscan
community who participated in our study. The family of Franciscan orders was founded
in the 13th century by its principal founder St. Francis of Assisi. Franciscans take vows
of poverty, chastity and obedience and all share in the mission of living the Gospel and
serving the poor 85. Similar to the Benedictine orders, men and women can become
followers. Some of the roles they fill in the community along with being constant
witnesses for Christ are educators, administrators, catechists in parishes, religious
teachers in parish, public schools, while simultaneously keeping a focus on promoting
and strengthening Christian values 85,86.
In the independent living community population Monarch Landing offers a robust
independent living experience that promotes a vibrant lifestyle for active seniors. The
independent retirement community is located on a scenic campus, which is thoughtfully
constructed to be in harmony with nature. The various units are designed with welcoming
living areas, dining rooms, country kitchens, artful lighting and specialty accents
throughout its several floor plans. Residents are encouraged to make decisions about their
schedules, dining preferences, social activities, care choices, faith services, cooking,
44
fitness classes and more. Monarch Landing offers a newly constructed assisted living
memory support and soon to open rehabilitation and skilled nursing services; thus
providing complete continuing care for seniors throughout the later stages of life 87.
The Institutional Review Board at Benedictine University approved this study.
The IRB approval level was exempt based on the anonymous survey data and low risk
nature of the physical health measures collected.
Validity and Reliability of Methods
During our study we utilized wellness surveys that are validated for older adults
in their original form and calculated outcomes based on their specific scoring instruction
88-91. The four instruments that were used to measure the mental wellness of our
population as part of our survey were the 15-question Geriatric Depression Scale (GDS),
the Multidimensional Scale of Perceived Social Support (MSPSS), the 12-item
Spirituality Index of Well-Being and the 10-item Perceived Stress Scale (PSS). The first
instrument was the 15-question GDS, which has been used in many research studies
illustrating high validity and reliability scores (Cronbach’s alpha of 0.80) 88,92,93. One
such study involving sixty-four outpatients aged 60 or older who met criteria for
depressive disorder comparing ICD-10 Checklist of Symptoms, Montgomery-Asberg
Depression Rating Scale (MADRS), and DSM-IV diagnostic criteria to the GDS-15
scoring values. The results were that the GDS-15 produced sensitivity and specificity
rates of 92.7% and 65.2% respectively, and positive and negative predictive values of
82.6% and 83.3% respectively 88. These findings illustrate that the GDS -15 is a good
screening instrument for major depression as defined by both the ICD-10 and DSM-IV.
The second survey used in our assessment was the MSPSS, which is found to
45
have excellent internal consistency and test retest reliability with a Cronbach’s alpha of
0.81-0.98 in nonclinical samples and 0.92-0.94 in clinical samples 94. The MSPSS
produced item and scale scores with adequate reproducibility; over a 2-3 month period of
time, its reliability is r=.72-.85 94. In regards to validity, MSPSS positively correlates
with a self-concept measure and negatively with measure of depression and anxiety,
which confirms the validity of survey 95.
The third scale added to our survey was the 12-item Spirituality Index of Well-
Being (SIWB). The SIWB is a scale that has been validated to determine subjective well-
being of an individual. Internal reliability analysis performed on the SIWB scale
indicated good reliability with a Cronbach’s alpha of .91. The 6-item subscales also
showed strong reliability values: α = .86 for self-efficacy and α =.89 for life scheme.
The last scale utilized in our survey was the 10-item PSS-10. It has been shown to
have relatively high reliability and validity within all age groups with a Cronbach’s alpha
of .82 90,96,97. In addition to the survey data, we also collected diet information and
physical health measures. These measures have demonstrated in past research to both
independently and collectively measure risk of disease and mortality in older adults and
are also used as standards of care in the fields of traditional medicine, nutrition, public
health, exercise and complementary health. They are as follows: waist circumference,
systolic blood pressure, diastolic blood pressure, pulse, Body Mass Index, body fat and
lean mass 27,98-103. In addition, a 24-hour dietary recall was used to collect dietary data.
The 24-hour recall approach is used in research, but has proven be reliable but invalid 104.
46
Individuals may not report their food consumption accurately, most commonly
underreporting, due to knowledge deficits, memory lapse, demeanor of the examiner or
the environment interview situation 105.
Threats to Internal and External Validity
Concerns with validity included wellness survey instruments, physical health variables
used to quantify wellness status and the equipment used to capture the physical health
data. To minimize these concerns, the research group members researched the literature
for the appropriate scales that were shown to be valid for the wellness parameters of
interest as well as the age group of our sample. Our team members were careful once the
scales were determined not to alter the instruments in any way and to calculate the survey
totals per the particular scale instruction. The four scales are listed as follows: Geriatric
Depression Scale (GDS), the Multidimensional Scale of Perceived Social Support
Scoring (MSPSS), the Perceived Stress Scale (PSS) and the Spirituality Index of Well-
Being (SIWB). The validity and reliability for each scale was discussed in the previous
paragraph by stating each scales average Cronbach’s value. However, several scales and
measurement techniques used in this study had individual limitations.
The PSS-10 scale is most accurate for capturing acute stress of a specific life
event or stressor that occurs within a 4-8 week period of measurement 90. A limitation in
the SIWB in the validation of this scale is the absence of work that tests the conceptual
framework. A myriad of pathways, sequences, and relationships are suggested in the
framework, which was developed from qualitative data, but the scale lacks robust
empirical testing 89,106.
47
The 24-hour recall is most prone to study participants “underreporting” their food
consumption 105. To overcome these issues the interview process is conducted by trained
team members who used food models and standardized serving sizes as well as
prompting and probing of the participants to reduce incidence of misreporting or
inaccurate stating of food intake. 24-hour diet recalls are most appropriate for cross-
sectional research investigations when the study purpose requires quantitative estimates
of intake 107.
The group also utilized physical health measures to classify wellness status. The
physical measures chosen in our study were all taken with validated equipment and by
study team members trained in its specific and proper use. To ensure consistency and
reliability each team member performed data collection at only the station they were
trained on and did not interchange between stations at any time during the data intake
process. The dietary intake was captured from the previous day by utilizing the 24-hour
dietary intake process. The 24-hour intake was taken by a member of the research team in
a one-on-one interview format utilizing standardized food models, serving size sizes cups
and questions designed to spur memory and promote accurate caloric intake reporting.
Reliability Concerns
Concerns with potential reliability existed within the data collection process.
Possible concerns were within three areas: inconsistency with the data collection
methods, inconsistency with the data processing, and pre-assessment participant factors.
To minimize reliability concerns the research group members were placed in a training
process which consisted of performing several trials on team members and being given
detailed instruction on their device or tool operation prior to the onsite collection of data.
48
The training instruction included the proper set-up, use, calibration and preparation of
that device or tool utilized to gather intake data. Team members were careful to perform
pre-checks on the equipment onsite to ensure proper working order before any data from
participants were collected. The participant factors in the study included individuals who
exercised the day of collection, ate or drank directly before the assessment, wore clothing
that was thicker or thinner than an average t-shirt, or had orthopedic injuries that could
compromise their posture and stability during measurement. To minimize these
occurrences data collection was taken in the morning at the majority of the collection
sites used in our sample. Study participants that were dressed is a way that posed a barrier
to proper assessment were asked to change or modify their clothing so that the proper
measurements could be recorded. Any individuals that had compromised posture or
balance were lightly assisted and stabilized into the best positions to gather the most
accurate data readings.
Measurement Tools
Geriatric Depression Scale (GDS-15)
A survey instrument included in our wellness survey was the 15-item Geriatric
Depression Scale (GDS-15). The 15 question Geriatric Depression Scale (GDS-15) is a
tool used to diagnose depression in the older adult population and is frequently used in
the research setting 108,109. The survey has not only proven to successfully diagnosis
depression in the general older adult population, but also in the very old 110,111. Our study
assesses health parameters of adults over 65 years old, therefore the GDS-15 is
appropriate for use in our research population. The questionnaire takes about 10 minutes
or less to complete. Answering ‘yes’ to the first 10 questions indicates depression; and or
49
answering ‘no’ to the remaining 5 questions also signifies depression. The answers then
that indicate depression are given a positive score of 1. The scores of all 15 questions are
added together, with a sum of 5 or greater being indicative of depression 112.
Multidimensional Scale of Perceived Social Support Scoring (MSPSS)
A second instrument utilized in our study was the 12-question Multidimensional
Scale of Perceived Social Support Scoring (MSPSS). This tool is a subjective assessment
scale that can be used as a predictor of well-being, helps examine the influence of
stressful life events, general depression, health status and treatment effects 91. MSPSS
measures perceived social support and adequacy of emotional support presently available
in an individual’s life. Perceived social support appears to be the most important
measurement in an individual’s perception of received support 94. The MSPSS addresses
the availability of social support from 3 major relationships: significant others (#1, 2, 5
and 10), friends (#6, 7, 9 and 12) and family members (#3, 4, 8 and 11). Each potential
source of support is used to assess a subject’s satisfaction with support on a 7 point Likert
scale of 0 (very strongly disagree) to 7 (very strongly agree). The scoring range for the
12 questions, is between: 7 to 84; with the highest possible social support score being 84.
The categories breakdown into the following rankings: 69-84 High Acuity, 49-68
Moderate Acuity, and 12-48 Low Acuity.
Perceived Stress Scale (PSS-10)
A third tool incorporated in the survey was the 10-item Perceived Stress Scale
(PSS-10). It is a tool used to globally measure how seemingly stressful situations impact
50
a participant’s life 90. This tool has widely been utilized by clinicians and researchers to
quantify perceived stress in a variety of populations including the older adult 7,14,78,113.
When the PSS-10, is utilized to collect information the participants are asked how often
they feel or have felt in a specific manner over the past month; their options are: never,
almost never, sometimes, fairly often, and very often. The PSS-10 is scored by assigning
point values to how often specific feelings are experienced: never (0), almost never (1),
sometimes (2), fairly often (3), very often (4). Points are then reversed for the four
positively stated items, questions 4, 5, 7 and 8 and summed together 90. The highest total
score possible is 24 and scores of 20 or greater indicate a period of high distress 90.
Spirituality Index of Well-Being (SIWB)
The final tool included in the survey was the Spirituality Index of Well-Being
(SIWB). This is a subjective 12 item scale intended to determine an individual’s
perception of their spiritual quality of life 89. The SIWB is validated and consistently
used to determine general well-being 89. The first six items on the SIWB scale address the
concept of self-efficacy. Items seven through twelve address the concept of life scheme
106. The SIWB employs a five point Likert scale used to determine how the participant
feels about each statement given in the SIWB scale. A “one” signifies they “strongly
agree;” two signifies they “agree;” three signifies they “neither agree nor disagree;” four
signifies they “disagree;” and five signifies the “strongly disagree.” The scale utilizes a
scoring, system that indicates higher SIWB scores translates into greater degrees of
spirituality and/or well-being 89. To score, the mean of the items on each of the two
subscales is calculated, as well as the mean score of the combined scales. Higher scores
51
indicate increased spirituality and/or self-efficacy, with the highest total score being 60,
and the lowest total score being 0. The Highest score possible for each of the two
concepts, self-efficacy and life scheme, is 30 and the lowest score is 0 for both sections
89.
Instrumentation and Procedures of Physical Health Measures
Physical assessments and stress measures were collected using several tools. The
first measurement collected of these parameters was blood pressure. Systolic, diastolic
and pulse were collected on the same arm three consecutive times in approximately 1
minute recurring intervals. We did not utilize the first value and formed a score by
averaging the next two blood pressure readings. The BP Tru BPM -200 automatic unit
inflates the cuff up to above the systolic pressure 35 mm hg then slowly deflates at a
constant rate until a reading can be established. The unit will automatically calculate the
systolic, diastolic, and pulse values on a screen that must be recopied to a data sheet. The
collection process was initiated with the examiner instructing the participant to sit quietly
for a few minutes prior to measurement. The examiner then asked the participant to place
their arm on the table palm up and maintain constant breathing without speaking. Then
the examiner placed the cuff around the participants arm just above the elbow and
activated the machine.
Standing Height
Height was measured using a portable stadiometer, Seca 213 portable unit. This
model can record height values ranging from 20 to 205 cm with increments as small as a
millimeter. To collect the height information, participants were asked to remove their
52
shoes, stand with their back towards the measurement post and maintain a light three
point contact position with the post (buttocks, shoulder blades, back of head). They were
instructed to look straight ahead and maintain best possible posture (chin up, head neural,
shoulders pulled back, arms relaxed with hands at the side of the thighs). The headboard
is then lowered to the top of the cranium just to the point of skull contact or significant
hair depression. Height was then recorded in centimeters and the headboard was raised
and the person was asked to step away.
Waist Circumference
Waist circumference was recorded with a pliable, but stretch resistant body tape
measure. The measurement process consisted of the examiner asking permission to locate
the umbilicus and the participant standing with feet together while maintaining optimal
posture (chin up, head neural, shoulders pulled back, arms relaxed with hands at the side
of the thighs). The participant pointed to their umbilicus and the examiner, measured
around a t-shirt, tight enough to prevent any lag in the tape. The examiner recorded the
value to the nearest 0.1 centimeter.
Weight and Body Composition
Weight and body composition were collected by employing the use of the Inbody
230 BIA Scale. This scale allows for the collection of lean body mass, fat mass, dry lean
mass, intracellular, and extracellular water, total body water, body mass index, percent
body fat, and basal metabolic rate. The Inbody can measure these aspects through the use
of eight polar tactile electrodes that sends a 50 khz electrical currents through the various
tissues of the body. That frequency is one of the highest reactance currently available on
53
the professional market for identifying various components of body composition 114.
Research participants were asked to remove shoes, socks, electrical devices, and jewelry.
The participants were then asked to stand on the scale with bare feet and recite intake
information (height, age, sex) for the scale to tabulate findings. The scale then created a
printed profile. The examiner printed two copies one for data configuration and the other
for personal use for the client. The examiner then used hygienic wipes to clean and
sanitize the hand and feet contact points on the scale after each use.
24-Hour Diet Recall
Diet data was collected from study participants by utilizing the 24-hour diet recall
method. This method consists of listing all foods consumed by the individual during the
previous 24-hour period. The dietary interview was performed face-to-face by trained
research staff to collect general menu information and then probe for critical details. The
questions are standardized and include cooking methods, brands, time of consumption,
food types, recipes and portion sizes. Other data collected from the 24-hour recall
included length of meals and general eating framework (eat alone, eat while watching
TV, etc.). The examiners also asked study participants the time and location of meal
consumption to stimulate memory and help facilitate greater recall accuracy. The
research team members also employed the use of visual aids such as food models and
measuring cups to assist with improved intake precision and correct portion
identification. The data was reviewed again with the participant a final time before being
placed into Elizabeth Stewart Hands and Associates (ESHA) software program. The
energy, macro and micronutrient intakes were determined using a nutrient analysis
software called Food Processor, by ESHA Research, Inc. The Food Processor server
54
derives food nutrient composition from the United States Department of Agriculture’s
(USDA) national nutrient database, which is used as its primary standard reference.
ESHA Diet software
The Food Processor nutrition software has been used by dietitians, nutrition
professionals, academic institutions and other healthcare professionals for 30 years. The
data reported in the ESHA software comes from over 1800 sources, including the USDA
database, international databases, and nutrient data from food manufacturers, restaurants,
national food councils and associations.
Statistical Procedures
Our data was coded into the Statistical Package for the Social Sciences (SPSS)
numerically. SPSS by IBM is a group of an integrated products that addresses the entire
research analytical process, beginning with organizing the collected data, followed by
analysis of variables and last reporting of results. Any new variables needed based on
combined metrics or varying interpretation were created in the program and added into a
continuously evolving data set.
The following tests of statistical analysis were performed in our research study to
qualify outcomes and generate findings. A Pearson’s Correlation Coefficient was used
measure the nature of the association between two variables and the strength of their
relationship. The associations were reported if they have a p-value of less than .05.
Multiple linear regression was used to determine if a linear relationship between a
dependent variable and one or more independent variables existed, as well as the strength
of those variables to the outcome measure. Results were reported if values were
55
significant defined by p-values less than .05.
A Mann-Whitney U Test examines the differences between the two living groups
and genders. Results were reported if the p-values were less than 0.05. A Kruskal-
Wallis Test was used to verify that three or more samples were statistically the same
between groups, or if the groups were significantly different between one another.
Results were reported if the p-values were less than 0.05. In our study a Pearson’s
Correlation Coefficient examined the relationship between stress and or depression scores
and lifestyle factors, physical health measures and dietary intake. Mann-Whitney U Tests
were used to compare the values of stress, depression, lifestyle factors, physical health
measures, and dietary intake between groups. Kruskal-Wallis Tests were used to stratify
significant variables with other study data to observe if there was a statistical difference
between low, moderate or high values. Lastly multiple linear regression was utilized on
specific occasion to best understand which lifestyle factors, physical health measures and
dietary intake choices made the greatest contribution to predicting outcome measures.
56
CHAPTER 4
FINDINGS
Our sample consisted of 67 independent older adults aged 65 years and older of
whom 52.2% (n = 35) were living in vowed religious communities (VRC) and 47.8% (n
= 32) were living in an independent retirement community (IRC). List-wise deletion was
selected as the method for treating missing data. No outliers were deleted for the analysis
of these results. One participant was excluded before analysis because of functional
disability, so 66 participants remained.
Approximately 60% of our sample was female (41/67). The majority of the
sample was Caucasian White (approximately 75%) and very educated, with about half of
the participants holding a graduate degree. Table 1 shows the population characteristics
by the two living groups. Activity hours were significantly different by group (U =
194.50, p = .001), with the vowed religious community reporting 27 more hours a week
of activity than the independent retirement community (r = .46). See Table 1 for
demographic and lifestyle characteristics.
57
Table 1 - Demographic and Lifestyle Characteristics by Group
Variables
N
Vowed religious
community
Independent
retirement
community
Test
statistic
P
value
Mean ± SE Mean ± SE
Age (years) 67 78.91 ± 1.50 79.28 ± 1.34 542.501 .826
Gender
(males/females)
67 15/20 11/21 0.512 .477
Non-White/White 67 10/25 6/26 0.892 .346
Bachelor’s degree or
higher
67 4/31 15/17 10.332 .001*
Total exercise
(minutes/week)
32 46.79 ± 17.85 29.50 ± 3.18 89.501 .165
Hours of sleep/night 67 7.10 ± 0.16 6.98 ± 0.20 535.001 .749
Work-related activity
(hours/day)
59 29.79 ± 5.11 4.00 ± 0.78 194.501 .001*
Alcohol serving/week 65 1.11 ± 0.28 2.39 ± 0.39 332.501 .008*
Number of
servings/day of
vegetables
64 1.84 ± 0.13 1.72 ± 0.13 459.501 .432
Number of
servings/day of fruits
64 1.78 ± 0.17 2.06 ± 0.14 409.001 .141
Number of
servings/day of sweets
63 1.29 ± 0.15 0.84 ± 0.14 345.001 .026*
*p<0.05 is significant 1Mann-Whitney U test; 2Chi Square test
Mean body mass index for the whole sample was 27.96 ± 4.88. Groups did not vary with
regard to reported stress or blood pressure. See Table 2 for health and wellness
characteristics, all of which were our outcome measures.
58
Table 2- Health and Wellness Characteristics by Group
Variables
N
Vowed
religious
community
Independent
retirement
community
Mann-
Whitney U
test
P
value
Mean ± SE Mean ± SE
Perceived Stress
Scale
61 11.81 ± 0.97 9.76 ± 0.97 362.00 .140
Geriatric Depression
Scale
66 2.12 ± 0.37 1.16 ± 0.27 369.00 .020*
Social Support Scale 67 63.77 ± 2.94 68.06 ± 2.69 461.50 .216
Spirituality Index of
Well-Being Scale
67 53.53 ± 1.07 52.06 ± 1.16 471.00 .262
Body mass index
kg/m2
65 28.88 ± 0.93 26.94 ± 0.73 400.00 .095
Waist circumference
(cm)
66 39.74 ± 1.14 40.13 ± 3.70 465.50 .314
Body fat percentage 64 38.55 ± 1.68 33.26 ± 1.74 345.50 .025*
Muscle mass 62 55.86 ± 2.54 54.43 ± 2.51 463.50 .811
Systolic blood
pressure (mmHg)
67 128.37 ± 4.15 131.89 ± 3.34 447.00 .156
Diastolic blood
pressure (mmHg)
67 71.49 ± 2.62 70.63 ± 1.82 495.50 .418
Heart rate
(beats/minute)
67 75.86 ± 2.08 68.41 ± 1.99 386.50 .029*
*p<0.05 is significant
We also measured the nutrient composition of a 24 hour dietary recall survey, and
found no significant differences by group except for Vitamin C and carbohydrate intake.
The vowed religious community had a mean vitamin C intake of 65.02 mg/day ± 10.52
mg/day vs independent retirement community mean intake of 106.09 mg/day ± 20.23 (U
= 382.0, p = .038). The vowed religious community had a mean carbohydrate intake of
221.38 grams/day ± 26.26 vs independent retirement community mean intake of 280.29
grams/day ± 23.15, (U = 360.0, p = .012).
59
Relationship between Stress and Health and Lifestyle Factors
H10: There is no difference in stress reported by gender in older adults.
Of the total sample, 61 participants completed the Perceived Stress Scale (PSS)
with the mean score of the sample of 10.84 + 0.69. A Mann-Whitney U test was used to
examine the differences in PSS score by gender. No significant difference of PSS score
was found between males and females (U = 346.00, p > .05). The mean PSS score for
males was 9.50 ± 0.97 and the mean for females was 11.83 ± 0.95. The results failed to
reject the null hypothesis.
H20: There is no difference in stress reported by the vowed religious community and the
independent retirement community in older adults.
A Mann-Whitney U test was used to examine the difference in PSS score between
the vowed religious community and independent retirement community. No significant
difference was found (U = 362.00, p > .05). The vowed religious community had a mean
PSS score of 11.81 and the independent retirement community had a mean PSS score of
9.76. The results failed to reject the null hypothesis. Table 3 shows the comparison of
means between living groups.
Table 3-Comparison of Means between Living Groups
Variable
Vowed religious
community
Independent retirement
community
Test
Statistic1
P
value
Mean ± SE Mean ± SE
PSS 11.81 ± 0.97 9.76 ± 0.96 362.00 .140 1Mann-Whitney U test; actual PSS scores shown vs mean ranks.
60
H30: Perceived stress is not related to health and lifestyle factors in older adults.
A Pearson correlation coefficient was calculated for the relationship between PSS
score and all other scales, anthropometric measures and dietary intake. Table 4 shows
significant associations between PSS scores and health and lifestyle factors. A negative
correlation was found between PSS score and the spirituality index of wellbeing, (r(59) =
-.444, p = .000) indicating a significant linear relationship. Those with higher reported
spirituality also reported lower perceived stress. A positive correlation was found
between PSS score and GDS score, (r(59) = .374, p = .003) indicating a significant linear
relationship. Those with higher reported depression scores also reported higher perceived
stress. A positive correlation was found between PSS and intake of sweets/day, (r(55) =
.328, p = .013) indicating a significant linear relationship. Those with higher reported
sweet intake/day also reported higher perceived stress. A negative correlation was found
between PSS score and muscle mass, (r(54) = -.327, p = .014) indicating a significant
linear relationship. Those with higher muscle mass also reported lower perceived stress.
A negative correlation was found between PSS score and intake of alcohol/week, (r(49) =
-.331, p = .009) indicating a significant linear relationship. Those with higher reported
alcohol/week also reported lower perceived stress. A negative correlation was found
between PSS score and Vitamin D intake, (r(58) = -.305, p = .018) indicating a
significant linear relationship. Those with higher reported Vitamin D intake also reported
lower perceived stress. See Table 4. The null hypothesis was rejected.
61
Table 4-Associations between PSS and Health and Lifestyle Factors
Variable N Correlation (r) P value
Spirituality Index of Wellbeing 61 -.444 .000
Geriatric Depression Scale 61 .374 .003
Number of servings of sweets/day 57 .328 .013
Muscle mass 56 -.327 .014
Number of servings of alcohol/week 61 -.331 .009
Fiber (g/day) 61 -.271 .035
B6 (mg/day) 60 -.286 .027
B12 (mcg/day) 60 -.269 .038
Vitamin D (IU) 60 -.305 .018
Mg (mg/day) 60 -.256 .048
K (mcg/day) 60 -.287 .026
H41: Certain health and lifestyle factors contribute to or predict perceived stress in older
adults.
Multiple linear regression was used to assess the ability of six health and lifestyle
factors (Spirituality Index of Wellbeing, GDS-15, sweets/day, muscle mass, alcohol/week
and Vitamin D) to predict levels of stress. Preliminary analyses were conducted to ensure
no violation of the assumptions of normality, linearity, multicollinearity and
homoscedasticity. The total variance explained by the model as a whole was 50.5% with
adjusted R squared = .444. In the final model, only the Spirituality Index of Wellbeing
(p=.002), vitamin D (p = .014) and sweets/day (p=.046) were statistically significant. The
Spirituality Index of Wellbeing made the strongest contribution to explaining stress when
other variables were controlled for, uniquely explaining 11% (standardized β = -.347) of
the total variance in stress in the model. See Table 5. The alternative hypothesis was
accepted.
62
Table 5-PSS Multiple Linear Regression Analysis
Variables Standardized β P value R2 Adjusted R2
Spirituality Scores -.347 .002
Vitamin D (IU) -.271 .010
Sweets per day .216 .046
Muscle Mass -.199 .080
GDS-15 .189 .080
Alcohol
beverages/week
-.186 .083
Model total .505 .444
Relationship between Alcohol and Health and Lifestyle Factors
H50: There is no difference in weekly alcohol intake between genders in older adults.
Of our total sample, 59% reported drinking more than half a drink of alcohol per
week. Descriptive statistics to assess normality were conducted with the alcohol intake
per week variable and we found that the distribution of the variable was not normal. A
Mann-Whitney U test was conducted to examine the difference in reported alcohol intake
per week by gender. No significant difference in alcohol intake per week was found (U =
379.50, p > .05). We stratified the results by gender, and found a significant difference
between the independent retirement community and vowed religious community (U =
77.50, p = .001, r = .54) in females. Males averaged 2.02 drinks per week and females
averaged 1.51 drinks per week. The null hypothesis was rejected. See Table 6 for the
comparison between living groups and gender.
63
Table 6 - Comparison of Means between Living Groups
Variables
N Weekly alcohol
intake
SE
Test
statistic1
P
value
Vowed religious community 34 1.11 0.28
332.50
.008
Independent retirement
community
31 2.39 0.39
Males 26 2.02 0.37
379.50
.078 Females 39 1.51 0.33
Females—VRC 19 0.45 0.30
77.50
.001 Females—IRC 20 2.53 0.29
Males—VRC 15 1.94 0.35
79.00
.853 Males—IRC 11 2.14 0.30 1Mann-Whitney U test; actual alcoholic drinks shown vs mean ranks.
H60: There is no difference in weekly alcohol intake between the vowed religious
community and independent retirement community in older adults.
A Mann-Whitney U test was used to examine the difference in reported alcohol
intake per week between these groups. A significance difference was found in alcohol
intake between the two groups (U = 332.50, p = .008, r = .33). Alcohol intake per week
in the independent retirement community averaged 2.39 drinks and the vowed religious
community averaged 1.11 drinks per week. The null hypothesis was rejected.
H70: Perceived stress scores will not be different in levels of alcohol intake in older
adults.
In order to investigate whether health and lifestyle factors we measured were
different by alcohol intake, we created the following three-level categorical variable: less
than or equal to half an alcohol drink per week, greater than one half and less than or
64
equal to two alcohol drinks per week, and greater than two alcohol drinks per week. A
Kruskal-Wallis test was conducted comparing perceived stress in the three alcohol intake
levels. A significant result was found in PSS scores (H(2) = 12.08, p = .002), indicating
that the alcohol levels differed from each other. The difference in PSS scores was found
between those who reported less than or equal to one half alcohol drinks per week and
greater than 2 alcohol drinks per week (r = .28). Participants reporting more than two
alcohol drinks per week had lower PSS scores than participants in other weekly alcohol
intake levels. The null hypothesis was rejected. See Table 7.
Table 7 - Comparison of Means
Variables
N
≤0.50
drinks/week
>0.50 and ≤2.00
drinks/week
>2.00
drinks/week
Test
statistic1
P
value
Mean ± SE Mean ± SE Mean ± SE
PSS2 61 13.36 ± 1.00 10.58 ± 1.24 7.41 ± 1.02 12.00 .002 1Kruskal-Wallis test; 2Differences were between lowest weekly alcohol intake and
highest weekly alcohol intake.
H80: Weekly alcohol intake is not related to stress or other lifestyle and health factors in
older adults.
A Pearson correlation coefficient was calculated for the relationship between
participants’ weekly alcohol intake and PSS scores. A negative correlation was found
(r(59) = -.331, p = .009), indicating a linear relationship between the variables.
Participants who consumed more alcohol weekly reported less stress. When stratified by
gender, however, a positive correlation was found in females only (r(33) = -.422, p =
.001) , indicating a significant linear relationship between the two variables. Females
65
who drank more alcohol had lower PSS scores. The null hypothesis was rejected. See
Table 8.
Table 8 - Associations between Alcohol Intake and Stress
Variables N Correlations (r) P value
Total sample
PSS Scores 61 -.331 .009
Females Only
PSS Scores 35 -.422 .001
Relationship between Sweets Intake and Health and Lifestyle Factors
H90: There is no difference in sweets intake per day by gender in older adults.
Almost half of the total sample (44.8%) reported eating one sweet per day.
Descriptive statistics were run to assess the normality of the sweets per day variable, and
we found that the variable was not normally distributed. A Mann-Whitney U test was run
to examine the difference in reported sweets per day by gender. No significant
differences in sweets intake was found (U = 456.50, p > .05). Males averaged 1.08 sweets
per day and females averaged 1.05 sweets. The null hypothesis was accepted.
H100: Sweets intake per day does not differ in the vowed religious community compared
to the independent retirement community in older adults.
A Mann-Whitney U test was conducted to examine the difference in reported
sweets per day between these groups. A significant difference was found (U = 345.50, p
= .026), with a medium effect size (r = .28). Sweets per day in the independent retirement
community averaged 0.84, and the vowed religious community averaged 1.29 sweets.
The null hypothesis was rejected.
66
H111: Perceived stress scores differ by frequency of sweets intake level in older adults.
To compare whether sweets intake and perceived stress varied at different levels,
we created a three-level categorical variable: zero sweets per day, one sweet per day, and
two or more sweets per day. A Kruskal-Wallis test was conducted comparing the variable
perceived stress with the three levels of sweets intake. A significant result was found in
perceived stress levels (H(2) = 7.798, p = .020), indicating that the three levels of sweets
intake differed from each other. The differences in perceived stress were found between
those who reported zero sweets per day and two or more sweets per day with large effect
size (r = .49), and between those who reported one sweet per day and two or more sweets
per day with a medium effect size (r = .33). Participants who reported eating two or more
sweets per day had higher perceived stress levels. See Table 9. The alternative hypothesis
was accepted.
Table 9 - Comparison of Means
Variable
N
0 sweets
1 sweets
2 sweets
Test statistic1
P value
Mean ± SE Mean ± SE Mean ± SE
PSS2 57 9.00 ± 1.04 10.32 ± 1.00 14.20 ± 1.41 7.79 .020 1Kruskal-Wallis test; 2Differences were between lowest sweets intake level and greatest
sweets intake level, and between middle sweets intake level and greatest sweets intake
level.
H121: Sweets intake is related to perceived stress in older adults and other health and
lifestyle factors.
In order to compare what health and lifestyle factors measured were correlated
with sweets intake, a Pearson correlation coefficient test was conducted. A positive
67
correlation was found between sweets intake and perceived stress (r(55) = .328, p =
.013), sweets intake and iron (r(60) = .448, p = .000) and sweets intake and thiamine
(r(60) = .371, p = .003), indicating a significant linear relationship between the variables.
A negative correlation was found between sweets intake and soluble fiber (r(60) = -.261,
p = .039), indicating a significant linear relationship between the two variables. The data
was split by gender and correlations comparing sweets intake and perceived stress were
run. A positive correlation was found between sweets intake and perceived stress in
males only (r(22) = .496, p = .014). The alternative hypothesis was accepted. See Table
10.
Table 10 - Significant Correlations of Variables with Sweets Intake
Variables N Correlation (r) P value
Total sample
Perceived Stress Score 57 .328 .013
Iron (mg/day) 62 .448 .000
Thiamine (mg/day) 62 .371 .003
Riboflavin (mg/day) 62 .269 .035
Soluble Fiber (g/day) 63 -.261 .039
Zinc (mg/day) 62 .260 .041
Males
Perceived Stress Score 24 .496 .014
H131: Certain health and lifestyle factors contribute to or predict sweets intake in older
adults.
A multiple linear regression was used to assess the ability of three health and
lifestyle factors (perceived stress score, iron intake, and thiamine intake) to predict levels
of sweets intake. A significant regression equation was found (F(3,53) = 10.499, p =
.000), with an R2 of .373. Participants’ predicted sweets intake is equal to -.265 + .023
68
(iron intake) + .313 (thiamine intake) + .057 (perceived stress), where iron and thiamine
is measured in mg and perceived stress is measured using the PSS. Perceived stress
explained 13% of the total variance in sweets intake in our population. Perceived stress
makes the strongest unique contribution to sweets intake. See Table 11. The alternative
hypothesis was accepted.
Table 11 – Multiple Linear Regression Analysis of Sweets Intake
Variables Standardized β P value R2 Adjusted R2
Perceived Stress Score .373 .001
Iron (mg/day) .315 .012
Thiamine (mg/day) .296 .020
Model Total .373 .337
Relationship between Physical Health Measures and Health and Lifestyle Factors
H140: There are no differences in physical health measures between the vowed religious
community and the independent retirement community in older adults.
A Mann-Whitney U test was conducted to examine the difference in physical
health measures between the vowed religious community and independent retirement
community. A significant difference was found between the two groups in regard to body
fat percent (U = 345.5, p = .025, r = .28) and heart rate (U = 386.5, p = .029, r = .27).
Body fat percent was higher for the vowed religious community with a mean of 38.5
percent compared to the independent retirement community of 33.3 percent. Heart rate
for the vowed religious community averaged 76 beats per minute compared to the
independent retirement community which averaged 68.5 beats per minute. See Table 12.
The null hypothesis was rejected.
69
Table 12 – Comparison of Means between Groups
Variables
N
Vowed religious
community
Independent
retirement
community
Test
statistic1
P
value
Mean ± SE Mean ± SE
Heart Rate
(beats/minute)
67 75.86 ± 12.31 68.41 ± 11.24 386.5 .029
Body Fat
(percentage)
62 38.55 ± 9.51 33.26 ± 9.86 345.5 .025
1Mann-Whitney U test; actual heart rate beats per minute and body fat percent shown vs
mean ranks.
H151: Physical health measures are associated with stress in older adults.
A Pearson correlation test was conducted to examine the relationships between
stress and physical health measures. A negative correlation was found between muscle
mass and stress (r(60) = .-327, p = .014), indicating a significant negative linear
relationship between muscle mass and stress. These findings indicate that as the
participant’s stress increased, their muscle mass decreased. See Table 13. The alternative
hypothesis was accepted.
Table 13 – Correlations with Physical Parameters and Perceived Stress
Variables N Correlation (r) P value
Muscle mass (kg) 62 -.327 .014
H161: Muscle mass is associated with health and lifestyle factors in older adults.
A Pearson correlation test was conducted to examine the relationships between
muscle mass and lifestyle factors. A positive association was found between muscle
mass and activity hours (r(60) = .291, p = .034), chromium intake (r(60) = .304, p =
.017) . These findings show that as participant activity hours per week and chromium
70
intake per day increased muscle mass increased. Also, a negative correlation was found
between muscle mass and percent body fat (r(60) = -.280, p = .028) and muscle mass and
age (r(60) = -.295, p = .020) indicating an inverse linear relationship. These findings
illustrate that as participant’s body fat and age increased, muscle mass decreased. See
Table 14. The alternate hypothesis was accepted.
Table 14-Associations with Muscle Mass
Variables N Correlation (r) P value
Activity hours (per week) 53 .291 .034
Chromium (mcg/day) 61 .304 .017
Age (years) 62 -.295 .020
Body Fat (percent) 62 -.280 .028
H171: Body fat and heart rate are associated with lifestyle factors in older adults.
A Pearson correlation test was conducted to examine the relationships between
body fat, heart rate and lifestyle factors. Again, as mentioned earlier, a negative
correlation was found between percent body fat and muscle mass (r(60) = -.280, p =
.028), calories from saturated fat (r(62) = -.279, p = .026), calcium (r(61) = -.282, p =
.025), and the b –vitamin group (r(61) = -.275, p = .029). These findings indicate that as
percent body fat decreased, calories from saturated fat, b- vitamin index (Thiamine,
Riboflavin, Niacin, Pantothenic Acid, Pyridoxine, Biotin, Folate, Choline and
Cobalamin), and calcium intake increased. Additionally, as participant’s muscle mass
increased, body fat percentage decreased.
71
Heart rate had a negative correlation with vitamin C (r(64) = -.291 p = .018),
indicating a linear relationship between the two variables. As vitamin C intake increased
heart rate activity decreased. See Table 15. The alternate hypothesis was accepted.
Table 15- Body Fat and Heart Rate Associations
Variables N Correlation (r) P value
Body fat percent 62
Muscle mass (kg) 62 -.280 .028
Saturated fat calories 64 -.279 .026
Calcium (mg/day) 63 -.282 .025
B Vitamins Index (B-1,B-2, B-3,B-5,B-
6,B-7,B-9,B-12)
63 -.275 .029
Heart Rate (beats/minute) 67
Vitamin C (mg/day) 66 -.291 .018
H180: Perceived stress scores do not differ in older individuals with lower and higher
muscle mass.
A Mann-Whitney U test was conducted to examine the difference in stress scores
between the lower half of the sample’s muscle mass scores (<54.3 kilograms) and the
upper half of the sample’s muscle mass scores (>54.4 kilograms). No significant
difference was found between the two (U = 307.5, p > .05). Stress scores in the low
muscle mass group averaged 9.96 compared to the high muscle mass group which
averaged 11.65. See Table 16 The null hypothesis was accepted.
72
Table 16- Comparison of Stress Means between Muscle Mass Groupings
Variable
N
Muscle mass (lower
half)
Muscle mass (upper
half)
Test
statistic1
P
value
Mean ± SE Mean ± SE
PSS
Score
61 11.65 ± 1.00 9.96 ± 1.30 307.5 .186
1Mann-Whitney U test; actual muscle mass in kilograms shown vs mean ranks
Relationship between Geriatric Depression Scale and Health and Lifestyle Factors
H191: Older adults living in the vowed religious group will report less depression than
those living in the independent retirement group.
In our sample population, 7.6% of our participants reported to be depressed.
Descriptive statistics to assess normality were conducted with the Geriatric Depression
Scale-15 (GDS-15). Distribution of the variable was not normal. A Mann-Whitney U
test was used to examine the difference in reported depression between the vowed
religious community and independent retirement community. We found a significant
difference between the two groups (U = 369.0, p = .020). The vowed religious
community reported a higher depression score, with a mean score of 2.12 in comparison
to 1.16 for the independent retirement community. The alternative hypothesis was
accepted. See Table 17.
H201: There is no difference in depressive symptoms by gender in older adults.
A Mann-Whitney U test was conducted to examine the difference in reported
depression between males and females. No significant difference was found (U = 443.0,
p > .050). The null hypothesis was rejected. See Table 17.
73
Table 17 - Comparison of Means
Variable
N GDS-15
mean
SE M-W Test
Statistic1
P
value
Vowed religious community 34 2.12 0.36
369.00
.020 Independent retirement
community
32 1.16 0.27
Males 26 1.65 0.38
443.0
.297 Females 40 1.61 0.30
1Mann-Whitney U test actual depression scores shown vs mean ranks.
H211: Depressive symptoms reported by participants will be associated with health and
lifestyle factors in older adults.
To better understand what lifestyle, anthropometric and/or health factors were
related to participants’ depression levels, a Pearson correlation coefficient was calculated.
The three significant variables related to depression was perceived stress (r(59) = .374, p
= .003), social support (r(64) = -.288, p = .019) and living environment (r(64) = -.254, p
= .040). The hypothesis was accepted. See Table 18.
Table 18 - Significant Correlations of Variables with Geriatric Depression Scale
Variables N Correlation with GDS-15 (r) P value
Total Sample Population
Perceived stress 61 .374 .003
Social support 66 -.288 .019
Living environment1 66 -.254 .040 1 Religious vs. nonreligious group
74
H221: Health and lifestyle factors will be predictors of depression in older adults.
A multivariate analysis was run to better understand of the three significant
correlations (p < .025) found with depression, perceived stress, social support and living
environment, which variables was the most significant contributor of depression. It was
found 21% of the variance in depression scores between the two living groups was
explained. Perceived stress makes the strongest unique contribution, and is the only
statistically significant contribution to depression scores when gender and social support
are controlled for. Perceived stress uniquely explained 8% of the total variance in
depression scores in our population. The alternative hypothesis was accepted. See Table
19.
Table 19 - Multivariate analyses
Variables Standardized β P value R2 Adjusted R2
Perceived Stress .295 .014
Social support -.196 .033
Living environment -.171 .044
Model total .210 .169
H231: Health and lifestyle factors will be predictors of depression in older adults living
in the vowed religious group only.
The population was stratified by living group. A Mann-Whitney U test was
conducted to identify correlations in the vowed religious group only. Perceived stress
contributed to GDS (r(30) = .378, p = .033) and trans fat intake (g) was positively
correlated with GDS (r(33) = .365, p = .034). See table 20. The null hypothesis was
accepted.
75
Table 20 - Significant Correlations of Variables with Geriatric Depression Scale
Variables N Correlation with GDS-15 (r) P value
Vowed Religious Group 35
Perceived stress 32 .378 .033
Trans fat intake (g) 35 .365 .034
Relationship between Amount of Sleep and Health and Lifestyle Factors
H240: There is no difference in reported hours of sleep per night by gender in older
adults.
More than a quarter of the total sample (28.4%) reported less than seven hours of
sleep. Descriptive statistics to assess normality were conducted with the sleep hours per
night variable and we found that the distribution of the variable hours of sleep was not
normal. A Mann-Whitney U test was used to examine the difference in reported sleep
hours by gender. No significant difference of sleep hours was found (U = 458.50, p >
.05). Males averaged 7.17 hours of sleep and females averaged 6.98 hours of sleep. The
null hypothesis was accepted. See Table 21.
Table 21 - Comparison of Means between Genders
Variables Males Females Test Statistic1 P value
Mean ± SE Mean ± SE
Hours of sleep/night 7.17 ± 0.23 6.98 ± 0.16 458.50 .327 1Mann-Whitney U test; actual hours of sleep shown vs mean rank.
76
H250: There is no difference in reported hours of sleep per night between the vowed
religious community and independent retirement community in older adults.
A Mann-Whitney U test was used to examine the difference in reported sleep
hours per night between these groups. No significant difference was found (U = 535.00, p
> .05). Sleep hours per night in the independent retirement community averaged 6.98
hours and the vowed religious community averaged 7.12 hours. The null hypothesis was
accepted. See Table 22.
Table 22 - Comparison of Means between Living Groups
Variable
Vowed religious
community
Independent retirement
community
Test
Statistic1
P
value
Mean ± SE Mean ± SE
Hours of
sleep/night
7.12 ± 0.16 6.98 ± 0.20 535.00 .749
1Mann-Whitney U test; actual hours of sleep shown vs mean ranks.
H260: There is no difference in health and lifestyle factors related to sleep in three
categories in older adults.
In order to investigate whether health and lifestyle factors we measured was
different by sleep levels; we created the following three-level categorical variable: less
than seven hours of sleep, the recommended seven to eight hours of sleep, and more than
eight hours of sleep. Kruskal-Wallis tests were conducted comparing variables of interest
in the three sleep levels. A significant result was found in iron intakes (H(2) = 10.65, p <
.01, indicating that the sleep levels differed from each other. The difference in iron
intakes was found between those who reported less than seven hours of sleep and greater
than eight hours of sleep (r = .61), and between seven to eight hours of reported sleep and
77
greater than eight hours of reported sleep (r = .46). Participants reporting more than eight
hours of sleep per night consumed more iron than participants in other sleep levels. See
Table 23. A Pearson correlation coefficient was calculated for the relationship between
participants’ sleep hours and iron intake. A positive correlation was found (r(64) = .360,
p = .003), indicating a significant linear relationship between the two variables.
Participants who consumed more iron slept longer per night. When stratified by gender,
however, a positive correlation was found in males only (r(24) = .417, p = .034),
indicating a significant linear relationship between the two variables. Males who
consumed more iron slept longer per night. The null hypothesis was rejected. See Table
24.
Table 23 – Comparison of Means
Variables N <7 hrs 7-8 hrs >8 hrs Test
statistic1
P
value
Mean ±
SE
Mean ± SE Mean ± SE
Sweets/day2 63 0.88 ±
0.18
1.02 ± 0.12 2.25 ± 0.25 8.40 .015
Iron
(mg/day)2
66 11.8 ±
1.34
12.92 ±
0.84
44.08 ±
15.30
10.60 .005
1Kruskal-Wallis test; 2Differences were between lowest sleep level and greatest sleep
level, and between middle sleep level and greatest sleep level.
A Kruskal-Wallis test also found a significant result in daily sweet intakes (H(2) =
8.46, p < .05), indicating that the sleep levels differed from each other. The difference of
daily sweet intakes was found between those who reported less than seven hours of sleep
and greater than eight hours of sleep (r = .60), and between seven to eight hours of
78
reported sleep and greater than eight hours of reported sleep (r = .40). Participants
reporting more than eight hours of sleep per night consumed more daily sweets than those
in other sleep levels. See Table 23. A Pearson correlation coefficient was calculated for
the relationship between participants’ sleep hours and daily sweet intakes, and a positive
correlation was found in females only (r(37) = .374, p = .019), indicating a significant
linear relationship between the two variables. Females who consumed more daily sweets
slept longer per night. See Table 24.
H270: Reported sleep hours per night is not related to health and lifestyle factors in older
adults.
A Pearson correlation coefficient was calculated for the relationship between
participants’ sleep hours and exercise variables and found negative correlations between
sleep hours and both mild and moderate exercise in males (r(11) = -.589, p = .034) and
(r(19) = -.464, p = .034, respectively), indicating a significant linear relationship between
the hours of sleep and the two variables. Males who participated in less exercise slept
longer per night. The null hypothesis was rejected. See Table 24.
79
Table 24 - Significant Correlations of Variables with Sleep Hours
Variables N Correlation (r) P value
Total sample
Iron (mg/day) 66 .360 .003
Males only
Moderate exercise
(hours/week)
21 -.464 .034
Mild exercise (hours/week) 13 -.589 .034
Iron (mg/day) 26 .417 .034
Females only
Sweets/day 39 .374 .019
80
CHAPTER 5
DISCUSSION
Overall Findings
Our study was the first to investigate health and lifestyle factors that impact stress
in two different cohesive older adult communities. We found that spirituality was the
largest predictor of perceived stress in these older adults. Each of the major topics in our
results will be discussed.
Stress
The role of stress in older adults was the major focus of this study. We found that
the vowed religious community did not report more stress than the comparison
community, the independent retirement community. As mentioned earlier, mechanisms
of a chronic stress response can negatively impact health 52. Our results showed that
there was no difference in perceived stress between the two communities. However,
based on the results of a regression analysis, spirituality was the biggest predictor of
perceived stress. While there was no difference in spirituality or perceived stress between
communities, in the total sample, as reported spirituality increased, perceived stress
decreased. Therefore, our results confirmed previous literature in this field, which
indicated that a religious lifestyle can positively impact wellness. A 32-year follow up
study of 144 nuns and 138 laypersons in Italy found those living in a religious
community had more stable blood pressures, a common measure of stress, throughout the
study compared to the control group 18.
81
Another study, in the Netherlands focused on the relationship between a monastic
lifestyle and mortality. In the 1,523 Benedictine and Trappist monks, the religious
lifestyle was associated with longer life expectancy 115. The vowed religious community
in our study actually reported higher stress, albeit not significant and there was no
difference in blood pressure between groups. However, we collected data during the
Lenten season, which is characterized by increased religious services and responsibilities
from the church and may have impacted the stress level of the vowed religious
community.
According to the American Psychological Association, women report more stress
than men, possibly due to disparities in sex hormones, gender-roles and/or different types
of stressors experienced 116. A cross-sectional study of 501 females and 679 male, white-
collar employees that were matched for educational and managerial level looked at the
difference in perceived stress by gender. Females in the study reported higher levels of
stress and work overload due to household responsibilities in addition to job related
duties 116. Additionally, a cross-sectional study of 2816 men and women in Spain focused
on perceived stress and coping mechanism disparities between genders. Results showed
that women have higher perceived stress than men, yet they managed stressful
experiences by using emotion-focused coping mechanisms 117. These studies established
that gender-roles and the type of stressor(s) might contribute to females historically
reporting higher stress than males. In our study, females did report a higher mean
perceived stress, however it was not significant and overall did not confirm past literature
in the field.
82
In addition to differences in stress between groups, the current study explored
associations between perceived stress and differences in health and lifestyle factors.
Perceived stress was positively correlated with depression and an increased consumption
of sweets per day. Perceived stress was negatively correlated with spirituality, muscle
mass and an increased consumption of alcohol per week. Stress and spirituality was
discussed earlier as it relates to current literature.
Stress was also negatively correlated with the consumption of certain nutrients:
fiber, B6, B12, vitamin D, magnesium and potassium. In our sample, as perceived stress
increased, intake of healthful foods containing these key nutrients decreased. An
observational study on government in employees sought to demonstrate a relationship
between work stress and blood pressure. Increased work stress led to increased use of
coping mechanisms such as alcohol consumption, unhealthy eating patterns and physical
inactivity 66. In a study of 457 women, Groesz et al.,2012 aimed to determine the
association between stress, the drive to eat and food choices made. Increased perceived
stress was associated with a stronger drive to eat, especially comfort foods that were
higher in fat and sugar 118. These studies demonstrate that an increase in perceived stress
is associated with an increase of unhealthy food choices, which may contribute to the
decrease of healthy nutrients that was observed in our population. The findings of the
current study confirmed past literature regarding stress and food choices.
Recent studies have found that the mechanism regarding stress and food choices
may lay in the hormone leptin, which regulates appetite 119,120. Leptin is released from
adipose cells and is involved in the reward center of the brain 119,120. In Brazil, a study of
57 women aimed to determine an association between basal leptin levels, stress and
83
dietary choices. They found that increased basal leptin levels were related to cravings of
sweets in stressed women 120. Another study of 40 women had their blood leptin levels
and food intake measured in response to acute stressors. Researchers concluded that
leptin might act as a modulator of stress eating comfort foods 119. The results of these
studies exhibit a possible biochemical mechanism that may relate increased stress to poor
dietary choices.
Vitamin D intake was also a major predictor of stress in our sample based on a
multiple regression model. Vitamin D deficiency is a common problem in older adults
and recent literature is showing possible links between vitamin D status and mental
health in older adults. A cross-sectional analysis of the Iowa Women’s Health study by
Motsinger et al.,2012 aimed to determine the association between vitamin D, mood
disorders, such as depression and anxiety, and health related quality of life in older
women. They found that those who consumed less than 400 IU of vitamin D daily had
lower mental health related quality of life 121. A study of 10,086 adults in Norway aimed
to determine the association between blood levels of vitamin D and depression and
mental distress. They found that those with low vitamin D levels had an increase in
mental distress and depressive symptoms 122. A recent review of vitamin D and acute
stress found that while vitamin D can modulate the effects of proinflammatory cytokines,
there is, so far, an inconsistent relationship between vitamin D and inflammation during
times of acute stress 123. Vitamin D receptors are widely distributed in the human brain,
including the hippocampus and myocardium of the heart, which may explain the
mechanism that links vitamin D intake to stress 124.
84
Depression
We found the vowed religious communities reported higher depressive symptoms
than the independent retirement community, with reported stress the largest contributor to
depression. Since research shows that depression differs by gender, we compared
depressive symptoms by gender, but there was no difference in reported depression
scores when we compared males and females in the whole sample.
While our study is the first to look at monastics’ level of depression, depression is
a ubiquitous part of all life stages. Cortisol is associated with higher levels of depression
and anxiety due to prolonged activation of hypothalamic-pituitary-adrenocortical axis,
which interferes with physiological systems known to cause inflammation 69,125. For
instance, in a study led by Fagundes et al.,2013 they evaluated the relationships between
depressive symptoms and stress-induced inflammation in 138 participants. Findings
included that the more depressive symptoms produced more interleukin (IL)-6 in
response to the stressor, as well as higher levels of IL-6 both at 45 minutes and after the
two hour mark of the stressor 34. Interleukins are a group of cytokines that mediate
communication between cells.
For our study, in men, with lower feelings of social support, reported depressive
symptoms rose. Friend support and family functioning seems to play the largest role in
the prediction of social support levels and reported depression 126. In a longitudinal
survey study led by Jensen et al., 2014, 1416 individuals completed surveys to help
explore how support varied with age and gender, highlighting that maintaining social
support is important in psychological health and in the reduction of depression 127
85
When the living groups were stratified, the vowed religious community was found
to have increased reported depressive symptoms with increased perceived stress and trans
fat intake. Trans fats are artificial fats that have a longer shelf life than unsaturated fats
and are used in processed foods 128. Those that consume a large amount of trans fats have
been found to have a 48% increase risk of depression due to the biological changes linked
to heart disease and depression and the association with IL-6 and high sensitive-C
reactive protein in women with higher body mass indices 129. Furthermore, those that
consume a large amount of trans fats have been found to have an increased risk of
depression due to the low-grade inflammatory status and endothelial dysfunction 129.
These results show a linear relationship between these variables and we cannot draw
causal conclusions.
Sweets Intake
We looked at sweets intake as it is relates to perceived stress and other health and
lifestyle factors, finding sweets intake is associated with perceived stress levels in our
sample. While researchers know that perceived stress is associated with increased added
sugar intake, the causal pathway between these two factors has yet to be established.
There are a few theories about what drives the association; some researchers believe
chronic stress stimulates the glucocorticoid-augmented central neural network 130. The
glucocorticoids may act on the brain in a forward-feed to increase a person’s desire to eat
calorically dense foods like sweets 130. Alternately, consumption of highly caloric foods
like sugar and fat may down regulate dopamine receptors. Since dopamine reduces stress
sensitivity and depression, the decreased dopamine receptors may lead to increased stress
131.
86
In our study, we did not find any differences in the amount of sweets consumed by
gender. This is in direct contrast with a longitudinal, observational study of 416 older
men and women by Hsiao et al.,2013 found women were more likely to consume “more
healthy” diets than men 132. These healthy diets consisted of primarily plant-based foods,
and foods lower in saturated fat and added sugar. With a larger sample size, we may
have observed similar divisions in diet quality between genders.
Furthermore, in our study as older adults’ perceived stress levels increased so did
the consumption of sweets per day. This link between higher perceived stress scores and
added sugar intake has been demonstrated in other studies. A cross-sectional study, led
by Mikolajczyk et al., 1839 college students in Europe found that college women who
had higher perceived stress scores ate more carbohydrate dense foods including sweets,
cookies, snacks, and fast food when compared to women who had lower perceived stress
scores 133. Similarly a cross-sectional study of 853 men and women, by Yannakoulia et
al.,2008 reported that greater sweets and meat consumption was associated with anxiety
levels in women 134. While these studies found associations between sweets consumption
and stress and anxiety only in women, we did not find this pattern in our results. In fact,
when we stratified our results by gender, sweets intake and perceived stress was only
significantly associated in males. Our study has a much older aged population compared
to populations sampled in Mikolajczyk and Yannakoulia’s studies. The variance in age
may contribute the difference in our findings.
A cross-sectional study by Laugero et al., 2011 looked at many health measures
associated with perceived stress in adults aged 45-70 years old, and they found that those
who were characterized as being the most stressed had greatest intake of sweets 69. This is
87
similar to our findings, which found that older adults who ate 2 or more sweets per a day
had the greatest perceived stress scores. It is important to note that our study and the
Laugero et al.,2011 study looked at adults who were older, so these correlations can most
specifically be applied to older adults. While our study and previous studies demonstrate
that higher perceived stress levels are associated with greater consumption of foods with
added sugars, a causal relationship cannot be established. Future longitudinal and
experimental studies should explore the causal relationship between these two variables.
Our study also looked at what health and lifestyle factors, besides perceived
stress, were correlated with sweets intake. We found that sweets intake was associated
with intakes of iron, thiamine, and riboflavin. We believe this association is seen because
in the United States white flour is enriched with iron, thiamine, riboflavin, niacin, and
folate, and most sweets are made with white flour in the United States. Therefore, people
who are consuming more sweets are consuming more enriched flour products. We also
found an association between soluble fiber and sweets intake. We hypothesized that when
people eat more sweets they are displacing the consumption of fruits and vegetables,
foods known to contain large amounts of soluble fiber. In fact, Mikolajczyk et al.,2009
found that people who had higher perceived stress levels consumed more sweets and less
fruits and vegetables, in comparison to people with lower stress levels 133. This study
emphasizes our theory that sweets intake displacing foods with soluble fiber in a diet.
Further research should explore the idea that sweets intake displaces foods with soluble
fiber in people with high levels of perceived stress.
88
Alcohol Intake
Another domain of stress that was examined was weekly alcohol intake. We
found a strong negative correlation of weekly alcohol intake with the Perceived Stress
Scale (PSS)-10 scale. Older adults consuming moderate amounts of alcohol reported less
stress than those consuming no alcohol to half a drink per week. Moderate alcohol intake
is defined as the consumption of up to one drink per day for women and up to two drinks
per day for men. Twelve fluid ounces of regular beer, 5 fluid ounces of wine, or 1.5 fluid
ounces of 80 proof distilled spirits count as one drink 135. Older adults ages 55 and older
drink about four drinks per week, which would be considered low alcohol intake, as
defined by the US Department of Health and Human Services and the US Department of
Agriculture 135,136.
This is in concurrence with the thought that moderate alcohol intake reduces
stress, since alcohol has a calming effect, with the ability to reduce tension 90,137.
Moreover, alcohol may transmit protective changes in cerebral vasculature, which is the
circulation of blood, as alcohol increases hippocampal acetylcholine release. Those that
drink moderate amounts have a lower prevalence of white matter lesions and subclinical
infarcts, which may be attributed to increased acetylcholine release, higher high density
lipoprotein cholesterol levels and fibrinogens that helps stop bleeding, although they may
only have a modest protective effect 138,139.
In our study, those living in the vowed religious community drank less alcoholic
beverages than those living in the independent living community. Specifically, those in
the vowed religious community drank about one drink per week, while those in the
89
independent retirement community drank about two and a half drinks per week. This is
in accordance with past studies that measured alcohol consumption within vowed
religious communities, finding monks and nuns consume less alcohol than the general
population 140,141. Vowed religious communities, such as those who participated in our
study, may drink less alcohol as they follow the Rule of St. Benedict “ora et labora,”
which translates from Latin as “pray and work.” The Rule of St. Benedict symbolizes
sobriety, and embodies their way of life 142,143.
Additionally, we found an association with weekly alcohol intake and stress in
our population, when stratified by gender. There was a negative correlation between
female weekly alcohol intake and perceived stress scale. This was in accordance with
recent studies that reported females who drank the least displayed greater perceived stress
15,144. Variances in gender may be the result of differences in both stress and alcohol use,
as research has shown that women undergo more family related stress than men. For
example, a recent epidemiological survey that explored over 4,000 current male and
female drinkers age sixty and over and their perceived stress levels in comparison to
alcohol consumption. It was found that women who drank the least displayed greater
perceived stress, although the mechanism behind this was not identified 144.
Upon further investigation, our study found associations between weekly alcohol
intake and stress among different levels of alcohol intake levels. Those who consumed
two or more drinks per week reported less stress than those who consumed less than one
half alcohol drink, which is in agreement with the theory that alcohol may contribute to a
reduction in tension 90,137 This is in agreement with a recent studies that found those who
drank less, reported higher levels of perceived stress 15,144. In a prospective study that
90
analyzed over 65,000 men and women between the ages of 50 and 76, participants were
evaluated on self-reported levels of stress and dietary behaviors. It was reported that
those who drank one alcohol serving per week reported higher levels of perceived stress
than those who drank four alcohol servings per week, although the mechanism behind
which alcohol consumption in older adults is related to cognitive health continues to be
unclear 15,145
Sleep
We looked at the amount of hours of sleep as a related domain of mental and
physical health. In our study, while the hours spent sleeping did not vary between the
independent retirement community and the vowed religious community nor by gender,
the amount of sleep influenced specific variables related to gender. We found that
increasing physical activity was associated with a decrease in sleep duration in men. This
result is inexplicable as current literature supports that physical activity is associated with
better sleep quality, duration, and improved sleep outcomes 146,147. This inexplicable
result may be explained by the discrepancy between self-reported physical activity and
objective measures of physical activity. Aadahl et al., 2003 compared self-reported
physical activity versus an accelerometer measuring physical activity in a randomized
control trial of 2500 participants 148. The researchers found decreased reliability of self-
reported exercise because it depends on the respondents’ ability to accurately quantify
their exercise while the accelerometer measures the actual movement. Furthermore, in a
randomized controlled trial of 248 participants, Hagstromer et al., 2008 investigated the
reliability of self-reported physical activity versus using accelerometer and found self-
reported physical activity does not correspond with objective measures of physical
91
activity. The participants reported up to three times greater physical activity compared to
the amount actually recorded by the accelerometer 149.
With respect to sleep and dietary intakes, we found that iron intakes were
positively associated with sleep duration. Our results confirmed a previous study that
found as iron intake increased sleep duration increased as well as in a cross-sectional of
3304 participants 150. Additionally, Kuhn et al., 1988 found sleep deprivation can produce
as much as a 50% reduction in serum iron levels due to a disruption in circadian rhythm
151. We found that those who had more than 8 hours of sleep had the greatest iron intakes
followed by those who met the 7-8 hours of sleep recommendation.
We found older adults who reported more than eight hours of sleep also reported a
higher intake of sweets. This result confirms previous studies that found women who
reported a greater intake of sweets, reported longer sleep duration. Because longer sleep
duration disrupts conventional eating times, consequently the dominance of snacks and
sweets over meals may ensue 150,152.
Physical Health Measures
We investigated the relationship of perceived stress on physical health measures
and anthropometric values. Our results found that as perceived stress scores increased,
muscle mass decreased. Our results confirmed a previous cross-sectional study led by
Poornima et al., 2014, who examined the impact of perceived stress on 64 participants’
muscle strength and endurance 153. The results showed perceived stress values were
negatively associated with the ability to reach and hold a maximal peak muscular
contraction 153.
92
We found that muscle mass was positively associated with weekly activity hours,
which is line with past studies. For example, a cohort study of 4232 participants,
examined activity minutes per day excluding exercise on risk factor and chronic disease
incidence 154. The findings showed at baseline and follow-up evaluations, non-exercise
activity minutes per day was associated with better lower waist circumferences, blood
lipid values, and healthy glucose levels when compared to exercise frequency per week
and sedentary hours per day 154. Furthermore, a prospective cohort study of 357
participants looked at muscle strength’s role in the reduction of muscle mass and muscle
fatigue, hypothesizing grip strength, grip fatigue time, biceps thickness, and fat free mass
would be associated with impaired mobility-related activities of daily living (mrADLs)
155. The study found those that had a decline of mrADLs at 30 days had a significant
difference in weakness, grip fatigue or fat free mass 155.
In contrast, we found inverse correlations between muscle mass and body fat and
between muscle mass and age. Body fat percent is the ratio of skeletal muscle and organ
mass to subcutaneous adipose and visceral fat mass in the body 100. In addition, a
previous study confirmed that as an individual ages, muscle tissue mass and metabolism
decreases 154. This supports our findings that as participants age, muscle mass decreased.
Additionally, we looked at how physical health measures varied by living groups,
finding percentage of body fat and heart rate significantly differed between the two
communities. Body fat percent was positively associated with muscle mass, dietary
calcium and dietary B-vitamin intake. A cross-sectional study of 531 men age 29 to 71
years old were grouped in low, moderate and intense weekly exercise groups to examine
the impact on anthropometric measures. The results showed that individuals who
93
exercised with the most intensity had the lowest waist circumference, body fat
percentages, overall weight, and highest muscle mass when compared to the moderate
and low categories. 100.
Our results found that as vitamin C increases, heart rate decreases. In a cross-
sectional study that confirms our findings a sample of 541 participants were examined to
determine the relationship between dietary intake and serum blood concentrations of
vitamin C on blood pressure and heart rate values 156. The finding showed that plasma
ascorbate concentration was inversely correlated to systolic and diastolic blood pressures
and pulse rate. In a second study led by Bruno et al., 2012, the study looked at 32
untreated patients with essential hypertension and 20 normotensive subjects who received
3 grams of vitamin C, with heart rate, noninvasive beat-to-beat blood pressure, and
muscle sympathetic nerve activity monitored 157. The results found that the hypertensive
patients’ systolic blood pressure was lowered than normotensive subjects, confirming the
positive affect of vitamin C157.
Strengths and Limitations
Using an affluent independent retirement community as our control group
provided us a better ability to compare the two groups, as both were financially secure.
Additionally, having an equal number of participants in each living group allowed for an
equal comparison of groups. Socio-demographic characteristics were also similar in both
groups, including education, race and age. By conducting the 24-hour recall, the study
was able to obtain detailed dietary data through the process of elaboration and
clarification. Furthermore, we utilized a properly trained research team, validated tools
and instruments to obtain anthropometric measurements. Finally, this was the first study
94
of its kind to compare a vowed religious community to an independent retirement
community’s perceived stress’ impact on health and lifestyle factors.
Our study was not without its limitations. Since this was a cross-sectional study,
we cannot make causal inferences about the data collected. Not only was our sample size
small, but we had more female participants than male, therefore our results have less
information about the men in our communities. All data recorded was self-reported,
which may have been biased. For example, participants may have had selective memory
in terms of what they ate. Partial data was collected from participants during the Lenten
season, this may have influenced dietary intake.
Conclusion
Those living in the vowed religious community tended to eat more sweets, drink
less alcohol, report higher levels of depression, and have higher amounts of body fat and
higher heart rates than those living in the independent retirement community. Perceived
stress scores were reportedly higher in participants who were less spiritual, ate more
sweets, consumed less vitamin D, had less muscle mass, and drank less weekly alcohol.
As the first study to investigate health and lifestyle factors that impact stress in two
different cohesive older adult communities, further research is needed to examine causal
relationships between variables and validate our findings.
95
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APPENDIX A
CROSS-SECTIONAL WELLNESS STUDY IRB DOCUMENT
Benedictine University--Institutional Review Board
Statement of Exemption Form
Version 10-1-2011
Principal Investigator (Faculty or lead advisor responsible for students): Dr. Bonnie
Beezhold
Title of Investigator: Bonnie Beezhold, PhD, CHES
Department or Program: Nutrition
Address: 5700 College Road Lisle, IL 60532
Phone: 630-829-6528 E-Mail address: [email protected]
Student Investigator (Grad): Shelby Benci
Address: 5750 Abbey Drive #4D, Lisle, IL 60532
Phone: 760-415-0939 E-Mail address: [email protected]
Student Investigator (Grad): Chad Earl
Address: 1404 Knoll Drive, Naperville, IL 60565
Phone: 630-8546469 E-Mail address: [email protected]
Student Investigator (Grad): April Irvine
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Address: 5750 Abbey Drive #4D, Lisle, IL 60532
Phone: 303-887-2356 E-Mail address: [email protected]
Student Investigator (Grad): Julie Long
Address: 8520 Hillcrest Drive, Orland park, IL 60462
Phone: 708-828-3545 E-Mail address: [email protected]
Student Investigator (Grad): Nikki Nies
Address: 5750 Abbey Drive #4D, Lisle, IL 60532
Phone: 201-790-1370 E-Mail address: [email protected]
Student Investigator (Grad): Jessica Schiappa
Address: 1111 W. Hillgrove Avenue, LaGrange, IL 60525
Phone: 720-480-2557 E-Mail: [email protected]
Check all that apply: Student project X Faculty project X Joint
faculty/student project X
Other Specify:
Grant research Specify:
Title of Project
Wellness investigation in older adults in community: a cross-sectional comparison
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HIPAA: Health Insurance Portability and Accountability Act
Yes x No Will health information be obtained from the covered entity (a
health care provider who bills health insurers)?
Yes x No Will the study involve the provision of healthcare in a covered entity, such
as Benedictine’s student health center?
Yes x No If the study involves the provision of healthcare, will a health insurer or
billing agency be contacted for billing or eligibility?
If you answered “NO” to all three questions, you are not subject to HIPAA and do not
need to address Page 4 of this form. If you answered “YES” to any of the questions
above, you are subject to HIPAA and must attach the HIPAA Worksheet.
Citation of Exempt Category (definitions below): 1 x 2 3 4
5 6
EXCEPTIONS: Research involving vulnerable populations such as the mentally or
cognitively impaired, prisoners, parolees, pregnant women, and fetuses, cannot be
exempt from review even though it meets the criteria of one of the categories below.
Research using survey procedures or interview procedures upon children cannot be
exempt. Research involving observation of children’s behavior cannot be exempt if the
investigator is a participant in the behaviors observed.
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EXEMPTION CATEGORIES (45 CFR 46.101(b)): Research activities in which the
only involvement of human subjects will be in one or more of the following categories:
1. Research conducted in established or commonly accepted educational settings,
involving normal educational practices, such as (i) research on regular and special
education instructional strategies, or (ii) research on the effectiveness of or the
comparison among instructional techniques, curricular or classroom management
methods. (Cannot implement ANY identifiers or minor children)
2. Research involving the use of educational tests (cognitive, diagnostic, aptitude,
achievement), survey procedures, interview procedures or observation of public
behavior, unless: (i) information obtained is recorded in such a manner that
human subjects can be identified, directly or through identifiers linked to the
subjects; and (ii) any disclosure of the human subjects’ responses outside the
research could reasonably place the subjects at risk of criminal or civil liability or be
damaging to the subjects’ financial standing, employment or reputation. Research
which deals with sensitive aspects of the subject’s own behavior such as illegal
conduct, drug use, sexual behavior, or use of alcohol, cannot be exempt from review.
3. Research involving the use of educational tests (cognitive, diagnostic, aptitude,
achievement), survey procedures, interview procedures, or observation of public
behavior that is not exempt under paragraph (b) (2) of this section if (i) the human
subjects are elected or appointed public officials or candidates for public office; or (ii)
119
federal statue(s) require(s) without exception that the confidentiality of the personally
identifiable information will be maintained throughout the research and thereafter.
Research which deals with sensitive aspects of the subject’s own behavior such as
illegal conduct, drug use, sexual behavior, or use of alcohol, cannot be exempt from
review.
4. Research involving the collection or study of existing data, documents, records,
pathological specimens or diagnostic specimens, if these sources are publicly
available or if the information is recorded by the investigator in such a manner that
subjects cannot be identified, directly, or through identifiers linked to the subjects.
5. Research and demonstration projects which are conducted by or subject to the
approval of federal department or agency heads and which are designed to study,
evaluate, or otherwise examine: (i) public benefit or service programs; (ii)
procedures for obtaining benefits or services under those programs; (iii) possible
changes in or alternatives to those programs or procedures; or (iv) possible changes in
methods or levels of payment for benefits or services under those programs.
6. Taste and food quality evaluation and consumer acceptance studies, (i) if wholesome
foods without additives are consumed or (ii) if a food is consumed that contains a
food ingredient at or below the level and for a use found to be safe, or agricultural
chemical or environmental contaminant at or below the level found to be safe, by the
U.S. Food and Drug Administration or approved by the Environmental Protection
120
Agency or the Food and Safety and Inspection Service of the U.S. Department of
Agriculture.
CONTINUING STUDIES:
Is this a continuation of an existing IRB approved study? Yes X No
If yes, please indicate when the IRB approved of the study:
______________________________________
and attach a copy of last year’s approved exempt study.
Description of the Proposed Project: Please give a description of the proposed project
on a separate page. In addition, indicate how subjects will be recruited, from where, and
when, and how they will remain confidential. Follow the checklist to be sure you’ve
covered all necessary questions. Include attachments that are needed to conduct this
study (i.e., Informed/ Parent Consent Form, copies of any instruments/surveys to be used
as well as copyright for use when necessary, permission to use existing data and for what
purpose, research or publication).
Also address the critical elements of your exemption category as indicated below:
Category 1: Specify whether 1. i or 1.ii applies and briefly explain.
Category 2: Assure that condition 2.i will be met and briefly explain how; and assure
that condition 2. ii applies; and confirm that copies of test/survey/interview questions or
items are attached.
121
Category 3: Explain why conditions 2.i and 2.ii cannot be met; and attach copy of
test/survey/interview questions or items; and either assures and briefly explains that
condition 3. ii applies, or explain subject’s public office and how it precludes anonymity
(i.e., 3.i).
Category 4: Briefly explain the nature of the existing data/documents; and briefly
explain either their public availability or the procedures to ensure anonymity and
confidentiality.
Category 5: Briefly explain method by which the project is reviewed and approved by a
federal department/agency head; and
identify and describe which of the 5.i - 5.iv categories apply.
Category 6: Assure that condition 6.i will be met; and assure via documentation
regarding approved safety levels that condition 6.ii will be met.
SIGNATURES
Principal Investigator (Faculty or lead advisor responsible for student):
______ ________________ Date____3-04-14_______
I certify that I have the appropriate credentials and privileges to conduct this study and
that the facilities are adequate.
Student Investigators (Graduate)
______________________________________________ _ Date____3-04-14_______
122
______________________________________________ _ Date____3-04-14_______
______________________________________________ _ Date____3-04-14_______
______________________________________________ _ Date____3-04-14_______
______________________________________________ _ Date____3-04-14_______
______________________________________________ _Date___ _3-04-14_______
Required for student investigators
Department Chair or Program Head:
_________________________________________________ Date___3-04-14_______
I certify that the investigator has the appropriate credentials and privileges to
conduct this study and that the facilities are adequate.
Dean of College:
_________________________________________________Date_________________
(Only required if research involves clinical studies with medical procedures or medical
tests.)
Research Personnel
Please list ALL research personnel (students/ faculty) involved in the conduct of this
study. All faculty and advisors must complete the IRB approved educational program on
123
the protection of human subjects and provide to the IRB the certification forms verifying
completion of the courses. The IRB will not review a study without such forms on file
for all research personnel.
Name Title
Department__________________
Dr. Bonnie Beezhold Assistant Professor Nutrition
Shelby Benci Graduate student Nutrition
Chad Earl Graduate student Nutrition
April Irvine Graduate student Nutrition
Julie Long Graduate student Nutrition
Nikki Nies Graduate student Nutrition
Jessica Schiappa Graduate student Nutrition
IRB Use Only: IRB Review and Approval
IRB Chair_________________________________________________Approval
Date________________________
Exempt Review Category # ______________Expiration Date______________________
Minimal Risk: yes no
124
HIPAA: Waiver of Authorization Recruitment Authorization
Description of Study
Study Rationale
Stress and negative emotions activate the hypothalamic-pituitary-adrenal (HPA) axis to
release cortisol into circulation (Dickerson & Kemeny, 2004). Prolonged activation of
this axis has been associated with inflammation, physical health problems, and mortality
(Rueggeberg et al, 2012). Specifically, stress can also induce inflammatory brain-altering
processes and are now thought to exacerbate brain ageing (Kyrou & Tsigos, 2009; Denis
et al, 2013). In a recent study that compared stress levels of caregivers and non-
caregiving controls, it was shown that the cumulative effect of daily stressors promoted
elevations in blood inflammatory markers (Gouin et al, 2011). Moreover, chronic stress is
associated with late-life depressive symptoms (Juster et al, 2011; Kobrosly et al, 2014).
Research also suggests that there is increasing variability in self-esteem at progressively
older ages (Trzesniewski et al., 2003) which increases stress levels (Pruessner et al,
1999). Age-related declines in older adults’ self-esteem could derive from a loss of social
roles, social isolation, or an increase in physical health problems (Orth et al, 2010). In
fact, optimism has been found to buffer the association between perceived stress and
elevated levels of diurnal cortisol (Jobin, 2013).
According to the American Psychological Association, a majority of Americans
have tried to reduce their stress but fewer than 10% report success in doing so (APA,
2012). Dietary factors can be stress-protective. For example, a growing body of evidence
125
now suggests that omega-3 fats are involved in HPA axis regulation and thus in
individual reactivity and sensitivity to stress (McNamara and Carlson, 2006). A recent
placebo-controlled, double-blind randomized trial compared the effect of fish oil
supplementation with placebo in stressed medical students, and found that those students
who received fish oil had decreases in blood inflammatory markers and reduction in
anxiety symptoms compared to controls. Lifestyle and environmental factors can also be
protective. For example, a prospective study in Italy that investigated blood pressure, an
indicator of stress, followed 144 nuns and 138 similar laywomen controls for 20 years,
and found that blood pressure did not increase with age in the nuns compared to
laywomen, an unexpected result only found in comparisons with hunter-gatherer groups
(Timio et al, 2001).
Aims and Hypotheses
The main aim of our study will be to explore various dimensions of wellness - physical,
emotional, social, and spiritual, with a particular focus on perceived stress - and
associations with diet, lifestyle factors, and physical measurements, such as blood
pressure, BMI and percent body fat, in older adults living in different communities,
focusing on a comparison of ascetic communities, such as St. Procopius, and independent
living senior communities in the western suburbs. This study will provide separate
hypotheses for six master’s students who will be collecting and analyzing the data,
writing a thesis manuscript, and presenting the results to the community.
The project’s general hypotheses are:
1) Older adults living in monastic communities report less stress (and/or depressive
symptoms) than individuals living in lay retirement communities.
126
2) Older adults who consume a healthy diet (and/or more regular activity) will report
less stress (and/or depressive symptoms) than individuals who do not consume a
healthy diet.
3) Older adults who report a higher level of spiritual wellness or a higher level of social
support will also report less stress (and/or depressive symptoms).
4) Older adults who report higher levels of wellness have lower blood pressures and
heart rates than adults who report lower levels of wellness.
5) Older adults who are obese will report more stress (and/or depression).
Survey design
We plan to conduct a cross-sectional wellness study of older healthy adults residing in
monastic and independent living communities. Our research group has constructed a
survey composed of questions about demographics, health and lifestyle factors, and
wellness dimensions specifically involving stress, depression, spiritual wellness and
social wellness. We will also be recording a 24-hr diet recall, and taking blood
pressure/pulse and weight (BMI, waist circumference, and percent body fat)
measurements. We plan to recruit participants at the Benedictine and possibly other
nearby monastic communities, and at independent living facilities in and around Lisle
and Naperville in order to compare group outcome measures in these two different
environments. We hope to recruit 50 participants in both groups for a total of 100
participants.
Study measures
All study assessments will take place on site. Our survey (attached) is composed of
questions from validated scales used in older adults when possible. The first section
127
contains demographic, health and lifestyle questions. The second section has four
validated embedded scales that have been used in older adults: the SF-36v2 Health
Survey to measure perceived physical and mental health, the Perceived Stress Scale to
measure stress, The Spirituality Index of Well-being to measure spiritual wellness, and
the Multidimensional Perceived Social Support Scale to measure social wellness. We will
also utilize a 24-hr diet record form to record dietary intakes, and will subsequently enter
the data into the National Cancer Institute’s ASA24 diet software program (with their
permission) to analyze the intakes. Physical measurements will include blood pressure
and pulse, waist circumference, weight and height, and percent body fat. Height will be
measured with a portable stadiometer and weight and percent body fat will be measured
with a segmental bioelectrical impedance analyzer. All equipment will be brought to each
site.
Participant recruitment
Participants will be recruited with the permission and assistance of directors and/or health
care managers at the sites, including St. Procopius Abbey, Sacred Heart Monastery,
Marmion Abbey, and independent living facilities selected in the Naperville/Lisle area. A
flyer (attached) will attract volunteers for the study day which will be handed out to
potential volunteers or posted at various locations at the sites at least a week before we
arrive for data collection. A signup sheet will be given to our contact at each site.
Eligibility criteria
All volunteers who are 65 years of age and older and who do not require assistance to
engage in their daily activities will be eligible to participate.
Methods
128
The study protocol will include four stations: the survey, the diet recall, the blood
pressure/pulse measurements, and the weight measurements. The survey will begin with
a consent form (attached). Volunteers will be informed of the study eligibility and how
long the study assessment will take to complete. Participants will be instructed that they
can stop participation at any time and that their survey responses and measurements will
be destroyed. Participants should be able to complete the study in one sitting and we
estimate completion time at 30-45 minutes.
Starting and Ending Dates
Data collection will convene once we have IRB approval, estimated to begin at the end of
March, excluding Holy Week, and proceeding through May 2014, however, possibly
requiring additional time in June 2014.
Potential Benefits
Aggregate results of this study will be conveyed in a thesis manuscript and in a
community research presentation in fall 2014, and potentially at research conferences and
in a journal publication. Participants will have the satisfaction of participating in research
that can ultimately improve public health. In addition, participants may also become more
aware of their own diet and lifestyle choices and the link to quality of life and wellness.
Potential Risks
This research does not involve greater than minimal risk for the participants, such as
potentially feeling mild discomfort when completing the wellness scales embedded in the
survey, when disclosing personal information, or when having physical measurements
taken. Anonymity of participants and confidentiality of responses and measurements will
be protected. Surveys and physical measurement records will not contain names but be
129
numbered only. All paper documents will be stored in the principal investigator’s files
within a locked department office. All electronically stored data will use the numerical
identifiers (no personal identifying or HIPAA information) and be password-protected in
a secure database. Although the paper surveys will have consent forms, only signatures
will be required; after the participant completes their participation, the consent forms will
be separated from the numbered surveys, thus further protecting anonymity. Paper
surveys will be scanned and electronic versions of the surveys and related data files will
be maintained for seven years in the Nutrition Department of Benedictine University;
paper surveys will be destroyed through shredding, once all data has been entered and
analyzed in the SPSS statistical software program.
Study Significance
This research will add to the body of scientific knowledge regarding the role of certain
modifiable lifestyle factors in physical and mental wellness, particularly in older adults,
and potentially contribute to public health recommendations for healthy aging.
[Please see the informed consent and recruitment email on the next page. The
survey and a recruitment flyer are attached.]
Informed Consent
130
WELLNESS INVESTIGATION OF OLDER ADULTS IN COMMUNITY
Spring, 2014
Dear Study Participant:
My graduate students and I are researchers in the Nutrition Department at Benedictine
University. The main aim of our study will be to explore various dimensions of wellness
- physical, emotional, social, and spiritual – and their relationships with diet, lifestyle
factors, and physical measurements in older adults living in different types of
communities. This research will add to the body of scientific knowledge about factors
that can influence physical and mental wellness, particularly in older adults, and
potentially contribute to public health recommendations for healthy aging.
Thank you for your willingness to participate in important research. You will be asked to
complete a survey, recall your diet over the last 24 hours, and have blood pressure and
weight measures taken. Your participation is completely voluntary. If at any time you do
not want to continue with the study, you may stop. Your time and involvement is
profoundly appreciated. The entire session should take no more than 30 minutes.
All personal data will be anonymous – surveys and measurement data forms will only
have numerical identifiers to protect your identity and confidentiality. Data will be
entered into a statistical program on a password-protected computer. Individual responses
131
will be compiled and results presented only in the aggregate. The study will be the
subject of a thesis manuscript and a campus research presentation in the fall of 2014, and
will potentially also be the subject of a journal publication. Under no circumstances will
your personal information ever be a focus of attention or your name or identifying
characteristics appear in writing. I personally will secure and ultimately dispose of the
information. You can reach me at 480-620-6773 or at [email protected] if you have
any further questions about the study.
Please sign below on the line provided to indicate that you have read this form and
consent to participation. The study has been approved by the Institutional Review Board
of Benedictine University. The chair of the board is Dr. Alandra Weller-Clarke, who can
be reached at (630) 829 – 6295 or at [email protected] for concerns about the study.
Sincerely,
Dr. Bonnie Beezhold
Assistant Professor
_______________________________________________
____________________________
Participant signature Date
132
Recruitment email + attached study description
Dear _____:
I'm a graduate student in the Nutrition Department at Benedictine University. My mentor,
Dr. Bonnie Beezhold, and a few other graduate students are conducting a study to
investigate diet, lifestyle, and health measurements associated with perceived wellness.
Building on the results of previous studies, we hope to compare older adults in nearby
monastic communities (St. Procopius Abbey, Sacred Heart Monastery, etc.) with those
residing in independent senior living communities. We are looking for participants who
are at least 65 years old and able to engage in their daily activities without assistance.
Volunteers will be asked to complete a survey of demographic/health questions and a diet
recall, and we will also take blood pressure and weight measurements (BMI, percent
body fat, waist circumference).
Would it be possible for us to meet with you regarding including adults in your
community? All assessments would be done at your site, so we would work together with
you to find a day that would be convenient for us to come out to a common area in your
facility. All assessments will be anonymous with only participant number identifiers, and
results would only be presented in the aggregate in a future research presentation and
publication.
133
I've attached a brief one-page study description for your review. Thank you so much for
your consideration in participating in this research, and I look forward to hearing from
you!
[student name]
[Attached Study Description below.]
Brief study rationale: Stress and negative emotions activate the hypothalamic-pituitary-
adrenal (HPA) axis to release cortisol into circulation (Dickerson & Kemeny, 2004).
Prolonged activation of this axis has been associated with inflammation, physical health
problems, and mortality (Rueggeberg et al, 2012). Specifically, stress can also induce
inflammatory brain-altering processes and are now thought to exacerbate brain ageing
(Kyrou & Tsigos, 2009; Denis et al, 2013). In a recent study that compared stress levels
of caregivers and non-caregiving controls, it was shown that the cumulative effect of
daily stressors promoted elevations in blood inflammatory markers (Gouin et al, 2011).
Moreover, chronic stress is associated with late-life depressive symptoms (Juster et al,
2011; Kobrosly et al, 2014). Research also suggests that there is increasing variability in
self-esteem at progressively older ages (Trzesniewski et al., 2003) which increases stress
levels (Pruessner et al, 1999). Age-related declines in older adults’ self-esteem could
derive from a loss of social roles, social isolation, or an increase in physical health
problems (Orth et al, 2010). In fact, optimism has been found to buffer the association
between perceived stress and elevated levels of diurnal cortisol (Jobin, 2013).
According to the American Psychological Association, a majority of Americans
have tried to reduce their stress but fewer than 10% report success in doing so (APA,
134
2012). Dietary factors can be stress-protective. For example, a growing body of evidence
now suggests that omega-3 fats are involved in HPA axis regulation and thus in
individual reactivity and sensitivity to stress (McNamara and Carlson, 2006). A recent
placebo-controlled, double-blind randomized trial compared the effect of fish oil
supplementation with placebo in stressed medical students, and found that those students
who received fish oil had decreases in blood inflammatory markers and reduction in
anxiety symptoms compared to controls. Lifestyle and environmental factors can also be
protective. For example, a prospective study in Italy that investigated blood pressure, an
indicator of stress, followed 144 nuns and 138 similar laywomen controls for 20 years,
and found that blood pressure did not increase with age in the nuns compared to
laywomen, an unexpected result only found in comparisons with hunter-gatherer groups
(Timio et al, 2001).
Study aim, methods, and significance: The aim of our study will be to explore various
dimensions of wellness - physical, emotional, social, and spiritual, with a particular focus
on perceived stress - and associations with diet, lifestyle factors, and physical health
parameters in older adults living in different communities, focusing on a comparison of
monastic communities and independent living senior communities in the western
suburbs. Eligible participants will be over the age of 65 and able to engage in daily
activities without assistance. The study protocol, consisting of a survey and non-invasive
physical measurements, will be presented as a wellness investigation. This research will
add to the body of scientific knowledge regarding the role of certain modifiable lifestyle
factors in physical and mental wellness, particularly in older adults, and potentially
135
contribute to public health recommendations for healthy aging. This study will provide
thesis hypotheses for six master’s students who will be collecting the data, and analyzing
and presenting the aggregate results.
Study assessments: (on site)
1) Survey – questions about demographics and lifestyle factors, with embedded
validated stress, depression, spirituality and social support scales used in older
populations;
2) 24-hr diet recall;
3) Blood pressure/pulse measurements and weight measurements (BMI, percent
body fat, waist circumference).
136
APPENDIX B
WELLNESS SURVEY
S U R V E Y
Site ____________________ Date ______________________
Participant No. __________
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - - -
PLEASE START HERE. This survey is anonymous. Do NOT write your
name.
What is your AGE? _____yrs GENDER: ____male
____female
Are you able to engage in your daily activities mostly without assistance?
____Yes ____No
What ETHNICITY do you consider yourself? Check all that apply.
Hispanic, Latino or
Spanish
White (not Middle
Eastern)
American Indian or
Alaska native
Asian
Black or African
American
White (Middle
Eastern)
Native Hawaiian or non-
Asian Pacific Islander
Unknown
What is your MARITAL status? Check all that apply. ____single ____married
____divorced ___widowed
What was the highest level of SCHOOL that you completed?
____grade school ____high school ____some college, nursing,
or professional school
____bachelor’s degree ____graduate degree
How many ALCOHOL beverages do you drink weekly? ____ per wk [1 glass of
wine, 1 beer, 1 cocktail]
Do you SMOKE? ____No ____Yes
Check if you regularly take any of the following SUPPLEMENTS:
137
____multiple vitamin/mineral _____fish oil _____herbs:
_______________________________
Other:
________________________________________________________________
_________
How many MEDICATIONS (prescribed by a doctor) of the same type do you take
regularly? ______
Check if you take medication for any of the following disease diagnoses:
____heart disease ____cancer ____diabetes ____depression
____anxiety
How many hours do you spend at volunteer ACTIVITIES each week?
______hours
How many hours do you spend at paid WORK each week? ______hours
How many hours of SLEEP do you typically get per night? ______hours
In general, would you say your health is:
Excellent Very good Good Fair Poor
Compared to one year ago, how would you rate your health in general now?
138
The questions in this scale ask you about your feelings and thoughts during the last month. In each case, check the box that indicates how often you felt or thought a certain way.
Never
Almost never
Some times
Fairly often
Very often
How often have you been upset because of something that
happened unexpectedly?
How often have you felt that you were unable to control the
important things in your life?
How often have you felt nervous and “stressed”?
How often have you felt confident about your ability to handle
your personal problems?
How often have you felt that things were going your way?
How often have you found that you could not cope with all the
things that you had to do?
How often have you been able to control irritations in your life?
How often have you felt that you were on top of things?
How often have you been angered because of things that were
outside of your control?
How often have you felt difficulties were piling up so high that you
could not overcome them?
139
Read each statement carefully and indicate how you feel about each statement. [‘Family’ can mean your order.]
Very strongly disagree
Strongly disagree
Mildly disagree
Neutral
Mildly agree
Strongly agree
Very strongly agree
There is a special person who is
around when I am in need.
There is a special person with whom
I can share my joys and sorrows.
My family really tries to help me.
I get the emotional help and support
I need from my family.
I have a special person who is a real
source of comfort to me.
My friends really try to help me.
I can count on my friends when
things go wrong.
I can talk about my problems with
my family.
I have friends with whom I can share
my joys and sorrows.
There is a special person in my life
who cares about my feelings.
My family is willing to help me make
decisions.
I can talk about my problems with
my friends.
Which response best describes how you feel about each statement?
Strongly disagree
Disagree
Neither agree or disagree
Agree
Strongly agree
There is not much I can do to help myself.
Often, there is no way I can complete what I have
started
I can’t begin to understand my problems.
I am overwhelmed when I have personal difficulties
and problems.
I don’t know how to begin to solve my problems.
There is not much I can do to make a difference in
my life.
I haven’t found my life’s purpose yet.
I don’t know who I am, where I came from, or where I
am going.
I have a lack of purpose in my life.
In this world, I don’t know where I fit in.
I am far from understanding the meaning of life.
140
Much better now than a year ago Somewhat better now than a year ago About the same as one year ago
Somewhat worse now than one year ago Much worse now than one year ago
The following items are about activities you might do during a typical day. Does your health now limit you in these activities? If so, how much?
Yes,
limited a lot
Yes,
limited a little
No, not limited at all
a. Vigorous activities, such as running, lifting
heavy objects, participating in strenuous sports
b. Moderate activities, such as moving a
table, pushing a vacuum cleaner, bowling, or
playing golf?
c. Lifting or carrying groceries.
d. Climbing several flights of stairs.
e. Climbing one flight of stairs.
f. Bending, kneeling or stooping.
g. Walking more than one mile.
h. Walking several blocks.
i. Walking one block.
j. Bathing or dressing yourself.
During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of your physical health?
YES
NO
a. Cut down the amount of time you spent on work or
other activities?
b. Accomplished less than you would like?
c. Were limited in the kind of work or other activities
d. Had difficulty performing the work or other activities
(for example, it took extra time)
During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious)?
YES
NO
There is a great void in my life at this time.
141
a. Cut down the amount of time you spent on work or
other activities?
b. Accomplished less than you would like?
c. Didn't do work or other activities as carefully as
usual?
During the past 4 weeks, to what extent has
your physical health or emotional problems
interfered with your normal social activities
with family, friends, neighbors, or groups?
Not at all
Slightly
Moderately
Quite a bit
Extremely
How much bodily pain have you had during the past 4 wks?
During the past 4 wks, how much did pain
interfere with your normal work (including both
work outside the home and housework)?
These questions are about how you feel and how things have been with you during the past 4 weeks. For each question, please give the one answer that comes closest to the way you have been feeling.
All of the time
Most of the time
A
good bit of the time
Some of the time
A little of the time
None of the time
How much of the time during the past 4 weeks…
a. did you feel full of pep?
b. have you been a very nervous
person?
c. have you felt so down in the
dumps nothing could cheer you
up?
d. have you felt calm and
peaceful?
e. did you have a lot of energy?
f. have you felt downhearted and
blue?
g. did you feel worn out?
h. have you been a happy
person?
i. did you feel tired?
142
During the past 4 weeks, how much of the time has your physical health or emotional problems interfered with your social activities (like visiting friends, relatives, etc.)?
How TRUE or FALSE is each of the following statements for you?
Definitely
true
Mostly
true
Don't know
Mostly false
Definitely
false
a. I seem to get sick a little
easier than other people.
b. I am as healthy as
anybody I know.
c. I expect my health to get
worse.
d. My health is excellent.
143
APPENDIX C
RECRUITMENT TOOLS: RECRUITMENT LETTER
Dear, _________________
I'm a graduate student in the Nutrition Department at Benedictine University. My
mentor, Dr. Bonnie Beezhold, and a few other graduate students are conducting a study
to investigate diet, lifestyle, and health measurements associated with perceived wellness.
Building on the results of previous studies, we hope to compare older adults in nearby
monastic communities (St. Procopius Abbey, Sacred Heart Monastery, etc.) with those
residing in independent senior living communities. We are looking for participants who
are at least 65 years old and able to engage in their daily activities without assistance.
Volunteers will be asked to complete a survey of demographic/health questions and a diet
recall, and we will also take blood pressure and weight measurements (BMI, percent
body fat, waist circumference). Assessments would be done at your site, only one time,
and would take about 30 minutes per participant. All data collected will be anonymous
with only participant number identifiers, and results would be presented only in the
aggregate in a future research presentation and possible publication. I've attached a brief
one-page study description for your review.
Would it be possible for us to meet with you briefly to discuss including your
community, as well as a possible study date in April or May? We believe that our results
will contribute to knowledge about wellness and successful aging. Thank you so much
for your consideration, and I look forward to hearing from you!
Sincerely,
____________________
Nutrition Department
Benedictine University
Bonnie Beezhold, PhD, MHS, CHES
Assistant Professor, Nutrition
Benedictine University
5700 College Drive, Lisle, IL 60532
144
APPENDIX C
RECRUITMENT TOOLS: SIGN UP SHEET & STUDY FLIER
Sign-up Sheet for May 16th
Wellness research study
Dr. Bonnie Beezhold
Assistant Professor, Nutrition
Graduate Students 2014
1:15 1:15
1:30 1:30
1:45 1:45
2:00 2:00
2:15 2:15
2:30 2:30
2:45 2:45
3:00 3:00
3:15 3:15
3:30 3:30
3:45 3:45
145
APPENDIX D
SIGNED INFORMED CONSENT FORM
WELLNESS INVESTIGATION OF OLDER ADULTS IN COMMUNITY
Spring, 2014
Dear Study Participant:
My graduate students and I are researchers in the Nutrition Department at Benedictine
University. The main aim of our study will be to explore various dimensions of wellness -
physical, emotional, social, and spiritual – and their relationships with diet, lifestyle
factors, and physical measurements in older adults living in different types of
communities. This research will add to the body of scientific knowledge about factors
that can influence physical and mental wellness, particularly in older adults, and
potentially contribute to public health recommendations for healthy aging.
Thank you for your willingness to participate in important research. You will be asked to
complete a survey, recall your diet over the last 24 hours, and have blood pressure and
weight measures taken. Your participation is completely voluntary. If at any time you do
not want to continue with the study, you may stop. Your time and involvement is
profoundly appreciated. The entire session should take about 30 minutes.
All personal data will be anonymous – surveys and measurement data forms will only
have numerical identifiers to protect your identity and confidentiality. Data will be entered
into a statistical program on a password-protected computer. Individual responses will
be compiled and results presented only in the aggregate. The study will be the subject of
a thesis manuscript and a campus research presentation in the fall of 2014, and
potentially will also be the subject of a journal publication. Under no circumstances will
your personal information ever be a focus of attention or will your name or identifying
characteristics appear in writing. I personally will secure and ultimately dispose of the
information. You can reach me at 480-620-6773 or at [email protected] if you have
any further questions about the study.
Please sign below on the line provided to indicate that you have read this form and
consent to participation. The study has been approved by the Institutional Review Board
of Benedictine University; the chair of the board is Dr. Alandra Weller-Clarke, who can
be reached at (630) 829 – 6295 or at [email protected] if you have concerns about the
study.
Sincerely,
146
APPENDIX D
SIGNED INFORMED CONSENT FORM
WELLNESS INVESTIGATION OF OLDER ADULTS IN COMMUNITY Spring, 2014 Dear Study Participant:
My graduate students and I are researchers in the Nutrition Department at
Benedictine University. The main aim of our study will be to explore various dimensions
of wellness - physical, emotional, social, and spiritual – and their relationships with diet,
lifestyle factors, and physical measurements in older adults living in different types of
communities. This research will add to the body of scientific knowledge about factors
that can influence physical and mental wellness, particularly in older adults, and
potentially contribute to public health recommendations for healthy aging.
Thank you for your willingness to participate in important research. You will be
asked to complete a survey, recall your diet over the last 24 hours, and have blood
pressure and weight measures taken. Your participation is completely voluntary. If at any
time you do not want to continue with the study, you may stop. Your time and
involvement is profoundly appreciated. The entire session should take about 30 minutes.
All personal data will be anonymous – surveys and measurement data forms will
only have numerical identifiers to protect your identity and confidentiality. Data will be
entered into a statistical program on a password-protected computer. Individual
responses will be compiled and results presented only in the aggregate. The study will
be the subject of a thesis manuscript and a campus research presentation in the fall of
2014, and potentially will also be the subject of a journal publication. Under no
circumstances will your personal information ever be a focus of attention or will your
name or identifying characteristics appear in writing. I personally will secure and
ultimately dispose of the information. You can reach me at 480-620-6773 or at
[email protected] if you have any further questions about the study.
Please sign below on the line provided to indicate that you have read this form
and consent to participation. The study has been approved by the Institutional Review
Board of Benedictine University; the chair of the board is Dr. Alandra Weller-Clarke, who
can be reached at (630) 829 – 6295 or at [email protected] if you have concerns about
the study.
Sincerely,
Dr. Bonnie Beezhold
Assistant Professor
___________________________________________ _____________________
Participant signature Date
147
APPENDIX E
REGISTRATION AND TESTING PROCEDURES
Script for Survey
[Be ready with a clipboard and the three forms: survey, measurement form and diet form.
Be sure to number the survey, starting with 101. Print the acronym for the site: SP, SHM,
MA, etc]
Good morning! We are so glad you came!
Have a seat. We’d like you to take a survey first. Please read the top page which
describes the process. And when you’re done, we would like you to sign and date it to
give your written consent. The top page will be separated from the survey so that your
responses will be confidential.
[So they would read and sign. You will take the survey, detach the consent, give them the
survey, and put the consent in the box.]
OK, you can begin the survey now. [Hover, but not too close. Be mindful that they
should be undisturbed for the survey. If you see them struggling with reading or staying
on the same line, offer a ruler.]
[Watch them to see when they’re done.]
OK, take your clipboard and pen, and I’ll walk you over to Shelby who will take your
blood pressure next
Script for Blood Pressure/Pulse
Hi, welcome to the blood pressure station. Please have a seat and roll up your sleeve.
[take BP 3X, and note on sheet.]
Now I’m going to walk you over to Nikki who is going to measure your height and waist
circumference.
Script for Height and WC
Hi! Would you please have a seat and remove your shoes and socks?
First, I’ll have you stand on the stadiometer with your back to it. Stand up straight with
your hands to your sides.
OK, now I’d like to measure your waist around your navel [unless you want to say ‘belly
button’. Write down the measure.]
Now Chad is going to measure your body fat, and give you a printout.
Script for BIA
148
[Chad, you need to wipe down the machine.]
Please step on the footprints so that your feet make contact with the metal.
[Put in gender, age, height into machine.]
Please hold the handles tightly, and make sure your arms are not touching your body.
[Run and note measures. As soon as it starts printing, you can tell them to step off. Wipe
down the machine for the next person.]
OK, you can sit here and put your shoes and socks back on. Here’s a printout of your
body fat.
OK, now I’m going to take you over to Julie and April who will ask you about your diet.
24 HOUR RECALL CHECKLIST
1. I am going to ask you to recall your diet over the last 24 hours.
2. When I ask you how much food and drink you had, I would like you to tell me in
as much detail as possible, so I will introduce the methods of remembering
portion sizes…
3. OK, I’d like you to try to remember everything you ate or drank from midnight to
midnight yesterday – even small amounts, and no matter where you were. Please
tell me any foods or drinks as soon as you remember them.
Please estimate your portion size using the food models or kitchen measures. Did you eat
the whole thing or were there leftovers? Did you have a 2nd helping? Ask about the
cooking method (fried, baked, etc?) and brand name, if appropriate. DO NOT
INTERRUPT. WHEN PARTICIPANT STOPS, ASK: What else?
Other prompts: Perhaps it will help you to think about what you did on Thursday. Was
this homemade, did you buy it from a store, or did you eat it in the residential dining
room? If homemade, ask what was in the recipes; if retail, ask for the brand name. Do
NOT use probes that suggest specific meals or foods such as, “What did you have for
breakfast?” or, “Do you usually have a cup of coffee first?”
4. Was there anything you have forgotten? I’ll list some foods to help your recall:
Coffee tea, soft drinks or milk, alcoholic drinks, biscuits, cakes, sweets, chocolate bars
and other candy, chips, peanuts and other snacks, sauces, dressings, condiments, salt and
sugar, nutritional supplements such as Boost/Ensure.
5. Is there anything else you haven’t already told me about? Did you eat anything at
meetings, or while cleaning, or while waiting to eat or preparing a meal?
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6. So I’d like to review your 24 hrs of food and drink with you: The first thing you
ate was (first item), and it was (detail about food). Did you have anything else
between that food and (next item)? Repeat for each item on their list.
7. Check your list for any missing brand names, if applicable, or measurements.
8. Thank you for participating in the study!
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APPENDIX F
HEALTH ASSESSMENT DATA COLLECTION TOOLS
Site: _________________________ Date: _________________ Participant No.
________
STUDY ASSESSMENTS RECORD (to be completed by research staff)
BLOOD PRESSURE / PULSE ______ arm – 3 X, 1 min intervals Pulse for each reading
ANTHROPOMETRICS
Weight (nearest 0.10 kg) using Inbody BMI Height (nearest ½ cm) Waist circumference, at umbilicus (to nearest ½ cm)
BODY COMPOSITION (record values and provide printout from Inbody to participant) Percent body fat
________________________________
2nd reading
/
3rd reading
/
1st reading
/
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24 Hour Diet Recall
Food Item Amount Time Where
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Is this a typical day? If not, is this day more or less than usual intake?
Now I would like to ask you about different types of food. How
many times per day, on average, do you eat:
Times per day
Vegetables, including leafy greens (NOT including potatoes or corn)?
(1 cup raw or ½ cup cooked)
Fruit and fruit products (NOT including fruit juice)?
(1 fruit or med serving)
Sweets, like sugar-sweetened cake, cookies, candy, pie, or pastries?
(1 serving)
Do you include the following ANIMAL FOODS in your diet at least monthly?
[Read each one, check all that apply]
____meat (beef, pork, lamb) ____chicken or turkey ____fish or
shellfish
____eggs ____ dairy foods (milk, cheese, yogurt)
On a scale from 1 to 7, 1 being healthy and 7 being unhealthy, how healthy
do you think a VEGAN diet (totally plant-based, no animal foods) would be?
1............2............3............4............5............6............7 [circle]
Unhealthy Healthy
On a scale from 1 to 7, 1 being very capable and 7 being not very capable,
to what extent do you see yourself capable of following a vegan diet in the
future?
1............2............3............4............5............6............7
Not very capable Very capable