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Nikki NiesFollow
Restaurant and Culinary Registered Dietitian in Dallas, Texas at Christian Care CenterAdvertisement
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Thesis Final Slides
- Associations with stress: a cross-sectional comparison of wellness in older adults Shelby Benci, B.S. Chad Earl, B.S. April Irvine, B.S. Julie Long, B.S. Nikki Nies, B.S. Jessica Schiappa, B.S. Mentor: Bonnie Beezhold, Ph.D.
- Study background • By 2050, 20% of the U.S. population will be over the age of 65 (Kobrosly, 2013) • Older adults report higher stress levels than a healthy range (APA, 2012) • Many older adults do not meet dietary guidelines for their age (Fakhouri, 2012) • Aging is associated with increasing BMI and body fat (Flegal, 2012; Fakhouri, 2012; Kizer, 2011)
- Background Research question: Do older adults living in a vowed religious community have less stress than those living in an independent retirement community? •Vowed religious communities can positively impact health and lifestyle factors oBlood pressure in nuns did not increase with age (Timio, 1997) oLife expectancy higher than outside community (Gouw, 1995)
- Study objectives (1) To explore relationships of various health and lifestyle factors that may impact stress and other wellness dimensions in older adults – physical, emotional, social, and spiritual; and, (2) To compare these factors in different communal environments – the vowed religious community and an independent retirement community
- Methods - Participants • Sites – 4 vowed religious communities (n=35); 1 independent retirement community (n=32) • Total participants – 67 (41 females/26 males) St. Procopius Abbey, Lisle
- Sacred Heart Monastery, Lisle Marmion Abbey, Aurora
- Monarch Landing Community, Naperville School Sisters of St. Francis of Christ the King, Lemont
- Participants - Comparison of communities • Similarities oCommunal oNo financial strain oAccess to religious facilities • Differences oVoluntary vs obligatory activities oCoed vs single gender living environment oCommunity involvement and responsibility
- Methods Design and recruitment process •Cross sectional study design •Participant recruitment: convenience sample recruited at vowed religious sites and independent retirement community •Fliers posted, sign-up sheets Jessica administered the wellness surveys.
- Methods Eligibility criteria •65 years and older •Live independently - function without significant physical or cognitive impairment •Willing to participate April collected 24 hour recall data.
- Methods Wellness survey •Demographic questions •Lifestyle questions •Four embedded questionnaires: • Perceived Stress Scale-10 • Geriatric Depression Scale-15 • Spirituality Index of Well-being • Multidimensional Scale of Perceived Social Support Julie collected 24 hour food recall data.
- Methods Data collection process • Areas were segmented and participants rotated to stations • Data collection was exclusively performed by six team members on five Saturdays in five sites Shelby measured blood pressure and heart rate.
- Methods Stations • Station 1: Wellness survey • Station 2: Blood pressure, pulse • Station 3: Anthropometrics • Station 4: Diet surveys Nikki and Chad measured height, weight, waist circumference and percent body fat.
- Results – Population characteristics by group Variable N VRC IRC Test Stat P value Mean ± SE Mean ± SE Age 67 78.91±1.50 79.28±1.34 542.51 .826 Gender (m/f) 67 15 / 20 11 / 21 0.52 .477 Degree/No3 Degree 67 4 / 31 15 / 17 10.32 .001 Activity Hrs4 59 29.79±5.11 4.00±0.78 194.51 .001 Social Support 67 63.77±2.94 68.06±2.68 461.51 .216 Spirituality 67 53.53±1.06 52.06±1.15 471.01 .262 1 Mann-Whitney U test statistic 2 Chi-Square test statistic 3 Degree/No Degree Effect Size: φ = 1.59 4 Activity Hours Effect Size: r = 0.46
- Results - Education
- Results – Population characteristics by group Variable N VRC IRC Test Stat1 P value Mean ± SE Mean ± SE Total exercise 32 46.79±17.85 29.50±3.18 89.5 .165 Body mass index 65 28.80± 0.93 26.94±0.72 400.0 .095 (BMI) Waist circumference 66 39.74± 1.14 40.13±3.69 465.5 .314 Muscle mass 62 55.86± 2.54 54.43±2.51 463.5 .811 Systolic blood 67 128.37± 4.14 131.89±3.34 447.0 .156 pressure Diastolic blood pressure 67 71.49± 2.62 70.63±1.82 495.5 .418 1 Mann-Whitney U test statistic
- Results – Blood Pressure
- Results – Reliability of scales Cronbach’ s Alpha Internal Consistency Perceived Stress Scale-10 0.80 0.7 ≤ α ≤ 0.9; Good Geriatric Depression 0.70 0.7 ≤ α ≤ 0.9; Good Scale – 15 Multidimensional Perceived Social Support Scale 0.97 α ≥ 0.9; Excellent Spirituality Index of Well-being Scale 0.90 α ≥ 0.9; Excellent
- Background - Stress Research question: Does a more spiritual environment affect perceived stress in older adults, and are health and lifestyle factors associated with perceived stress? • Americans report a mean stress level of 4.9 on 10-point scale where 1=little/no stress and 10=a great deal of stress (APA Stress in America, 2012) • Stress is an altered state of homeostasis in response to mental or physical stressors (Het, 2012) • Chronic stress can cause depression, anxiety, cardiovascular disease, weight gain and insulin resistance (Het, 2012)
- Stress mechanisms Sweis, 2012
- Methods – Measuring stress • Measured perceived stress using the 10-item Perceived Stress Scale (PSS) oExample question: In the last month, how often have you felt that you were unable to control the important things in your life? N Min Max Mean SE PSS-10 61 1 24 10.84 0.69
- Results – Comparison by groups H10: There is no difference in stress scores reported by the vowed religious community and the independent retirement community Living Site N Mean SE St. Procopius Abbey 6 7.17 1.68 Sacred Heart Monastery 8 15.63 1.03 Marmion Abbey 9 10.89 1.70 School Sisters of St. Francis of 9 12.44 2.15 Christ the King Monarch Landing 29 9.76 0.97 PSS national average for those 65 and older: 12.0
- Results – Comparison by groups H10: There is no difference in stress scores reported by the vowed religious community and the independent retirement community PSS-10 Mean±SE M-W Statistic * P value Vowed Religious Community 11.81 ± 0.97 362.0 .140 Independent Retirement Community 9.76 ± 0.97 Males 9.50 ± 0.97 346.5 .113 Females 11.83 ± 0.95 *Actual PSS scores shown vs mean ranks.
- Results – Associations with PSS-10 scores H20: Perceived stress is not related to health and lifestyle factors in older adults Variable Correlation (r) p value Spirituality score -.444 .000 Depression score .374 .003 Sweets per day .328 .013 Muscle mass -.327 .014 Alcohol per week -.331 .009 Fiber -.271 .035 Vitamin B6 -.286 .027 Vitamin B12 -.269 .038 Vitamin D (IU) -.305 .018 Magnesium -.256 .048 Potassium -.287 .026
- Results – Multivariate analysis H31: Certain health and lifestyle factors contribute to or predict perceived stress in older adults Variable Standardized β p value R2 Spirituality scores -.347 .002 Vitamin D (IU) -.271 .010 Sweets per day .216 .046 Muscle mass -.199 .080 Depression scores .189 .080 Alcohol per wk -.186 .083 Model total .505* *Adjusted R square = .444
- Discussion - Stress • There was no difference in reported perceived stress in the vowed religious and independent retirement communities of older adults • Stress was not related to blood pressure in this population • Spirituality was the biggest lifestyle predictor of lower perceived stress in older adults, followed by vit D oA spiritual lifestyle is associated with less stress (Timio, 1997) oLow vit D status is associated with depression, anxiety and low mental health related quality of life (Motsinger, 2012)
- Background - Weekly alcohol intake Research question: Does alcohol intake per week impact stress and other health and lifestyle factors in older adults? • Alcohol intake has a wide variety of health outcomes (Rehm, 2003) • Regular light to moderate drinking may have cardioprotective effects (O’Keefe, 2007) Weekly alcohol intake in U.S. Older adults (55 & over) 3.9 drinks/wk General population 4.2 drinks/wk (USDA; Gallup 2012)
- Methods – Measuring alcohol intake Research question: Does alcohol intake per week impact stress and other health and lifestyle factors in older adults? •Measured alcohol intake by this question: “How many alcoholic beverages do you drink weekly?” o 1 beverage = 1 glass of wine, 1 beer, 1 cocktail • 65/67 participants answered the question • Total mean intake was 1.72 drinks/wk o Range was 0 – 7 drinks per week
- Results - Comparison of groups H10: There is no difference in weekly alcohol intake between groups in the two living sites. Alcohol servings/wk N Mean SE MW Test* P value Vowed Religious Community 34 1.11 .28 332.5 .0081 Independent Retirement Community 31 2.39 .39 Males 26 2.02 .37 379.5 .078 Females 39 1.51 .33 *Mann-Whitney U tests showing actual mean scores versus mean rank. 1 Effect Size
- Results - Associations with weekly alcohol intake H20: Weekly alcohol intake is not related to stress or other health and lifestyle factors. Variable N Correlation (r) P value Total sample Perceived Stress Scale 61 -.331 .009 Females only Perceived Stress Scale 35 -.422 .011
- Results- Comparison of groups H30: Perceived stress scores (PSS-10) will not be different in levels of alcohol intake. N None – 1/2 drink/wk 1-2 drinks/wk >2 drinks/wk K-W Stat1 P value Mean ± SE Mean ± SE Mean ± SE PSS-10 scores 61 13.36 ± 1.00 10.58 ± 1.24 7.41± 1.02 12.1 .0022 1 Kruskal-Wallis statistic; actual mean PSS scores shown versus mean ranks.= 2 Mann-Whitney U tests.
- Discussion • Older adults in independent retirement communities are drinking more alcoholic beverages than the vowed religious communities • Alcohol intake was associated with reporting less stress • Older adults drinking 2 or more alcoholic beverages/wk reported less stress than those drinking none to ½ beverage/week. oDrinking less alcohol is related to higher levels of perceived stress (Barrington, 2014) oDrinking in moderation is linked to better well-being than abstinence (Lang, 2007)
- Introduction – Sweets intake Research question: Does consuming sweets impact stress and other health and lifestyle factors in older adults? • Recommendations for added sugars: oDietary Guidelines: reducing calories from added sugars (USDA & USDHSS, 2010) oWHO - less than 10% of total energy intake per day (WHO, 2014) • U.S. older adult population consumes 10.7%/11.2% (males/females) of its total calories from added sugar (Ervin & Ogden, 2013) • Higher perceived stress levels associated with increased intake of sweets and decreased intake of fruits and vegetables (Mikolaiczyk, 2009)
- Methods – Measuring sweets intake • The number of sweets consumed per a day was measured with the following question: o How many times per day, on average, do you eat sweets, like sugar-sweetened cake, cookies, candy, pie, or pastries? (1 serving) • 63/67 participants answered the question
- Results – Associations with sweets intake H11: Sweets intake is related to perceived stress and other health and lifestyle factors in older adults Variable N Correlation (r) P value PSS scores 57 .328 .013* Iron (mg) 62 .448 .000* Vit B1 (mg) 62 .371 .003* Vit B2 (mg) 62 .269 .035 Soluble fiber 63 -.261 .039 Zinc 62 .260 .041 *Correlations entered into the multiple linear regression model.
- Results – Associations with sweets intake H11: Sweets intake is related to perceived stress and other health and lifestyle factors in older adults Variable Standardized β P value R2 PSS scores .373 .001 Iron (mg) .315 .012 Vit B1 (mg) .296 .020 Model total .373* *Adjusted R square .337
- Results – Comparison of groups H20: There is no difference in daily sweets intake between the two living sites VRC IRC M-W statistic1 P value Mean ± SE Mean ± SE Servings of sweets/day 1.29 ± 0.15 0.84 ± 0.14 345.5 .0262 1 Mann-Whitney U test; actual mean serving per day shown vs mean rank. 2 Effect size r = .28.
- Results – Comparison of groups H31: Perceived stress scores differ by level of daily sweets intake in older adults Sweets per day N PSS-10 K-W statistic1 P value Mean ± SE None 14 9.00 ± 1.04 7.9 .0202 1 serving per day 28 10.32 ± 1.00 2+ servings per day 15 14.20 ± 1.41 1Kruskal Wallis test; showing actual mean PSS-10 scores 2Mann-Whitney U tests showed difference between groups 1 and 3 (effect size = .49) and groups 2 and 3 (effect size = .33)
- Discussion • Stress is linked with sweets intake in older adults • Those who consumed more sweets per day reported higher perceived stress than those who consumed less sweets oAssociation of added sugar and stress observed in older adults studies (Barrington, 2014; Laugero, 2011) • An increase in sweets intake is associated with intake of nutrients used in enrichment but displacement of foods with soluble fiber (Mikolaiczyk, 2009)
- Background – Depression Research question: Does a more spiritual living environment reduce the risk of depression in older adults, and what health and lifestyle factors are associated with that risk? • Prevalence: 5.5% of Americans ≥65 years (American Psychiatric Association, 2013) • DSM-V criteria includes mood and somatic symptoms • Biochemical, genetic, environmental including diet, and psychological factors contribute to development; women report more depression than men • Consequences: increased healthcare costs, visits to ER, poorer quality of life, suicide (Lamers, 2013)
- Methods - Measuring depression Research question: Does a more spiritual living environment reduce the risk of depression in older adults, and what health and lifestyle factors are associated with that risk? • Measured depressive symptoms with GDS-15 (Marc, 2008) oScores of 15 questions were totaled • 66/67 of our participants completed the scale Substance Abuse and Mental Health Services Administration, 2012
- Results – Comparison between groups H10: Older adults living in the vowed religious group will report less depression than those living in the independent retirement group. N GDS-15 Mean ± SE M-W Statistic1 P value Vowed Religious Community 34 2.12 ± 0.36 369.0 .0202 Independent Retirement Community 32 1.16 ± 0.27 1 Mann-Whitney U test; actual scores are shown vs ranks. 2 Effect size .20
- Results – Associations with GDS-15 scores H21: Depressive symptoms reported by participants will be associated with health and lifestyle factors in older adults. 1 Religious / non-religious group.
- Results – Multivariate analysis H31: Health and lifestyle factors will be predictors of depression in older adults. Variable Standardized β P value R2 Perceived stress .295 .014 Social support -.196 .033 Living environment -.171 .044 Model total .210* *Adjusted R squared = .169
- Results – Associations with depressive symptoms H40: Associations of health and lifestyle factors with depression scores will be significant in older adults.
- Discussion • The religious environment was not protective with regard to depression for older adults. • Depressive symptoms were related to stress, lack of social support, and living environment in older adults o Individuals with more depressive symptoms exhibited more pro-inflammatory cytokines and IL-6 levels (Fagundes, 2013) o Older adults and lack of social support results in greater rates of depression (Aziz, 2013)
- Background – Sleep • Adequate sleep improves health, wellness, and quality of life. • Consequences of sleep deficit: behavior patterns that negatively affect health and interpersonal relationships (Lui, 2013) • Recommendation: 7-8 hours for adults and older adults (CDC, 2003) • Prevalence: 7% adults (>65 yrs) report sufficient sleep (CDC, 2003) • <7hrs negatively affects cognitive function, but >8 hours also increases disease risk (McKnight, 2014)
- Methods – Measuring sleep hours Research question: Does living environment affect sleep in older adults, and is sleep duration related to other health and lifestyle factors in this population? •Reported hours of sleep per night o“How many hours of sleep do you typically get per night?” (US Bureau Labor and Statistics, 2012)
- Results – Comparison of groups H10: There is no difference in reported hours of sleep per night between living groups. Variable N Mean ± SE1 M-W Test Statistic1 P value VRC 35 7.12 ± 0.16 535.0 .749 IRC 32 6.98 ± 0.20 Males 26 7.17 ± 0.23 Females 41 6.98 ± 0.16 458.5 .327 1Mann-Whitney U test; showing actual mean hours of sleep versus mean rank
- Results – Associations with hours of sleep/night H21: Sleep hours per night is related to health and lifestyle factors in older adults. Variable N Correlation (r) with sleep hrs P value Total sample Iron (mg) intake 66 .360 .003 Males only Moderate exercise/wk 21 -.464 .034 Mild exercise/wk 13 -.589 .034 Iron intake (mg) 26 .417 .034 Females only Sweets intake/day 39 .374 . 019
- Results – Comparison of groups H30: There are no differences in health or lifestyle factors between sleep levels in older adults. Variable N <7 hours 7-8 hours >8 hours K-W Stat1 P value Mean ± SE Mean ± SE Mean ± SE Sweets/day 63 0.88±0.19 1.02±0.12 2.25±0.25 8.4 .0152 Iron (mg) 66 11.80±1.34 12.92±0.84 44.08±15.31 10.6 .0053 1Kruskal-Wallis statistic; actual mean hours of sleep shown versus mean ranks. 2 Mann-Whitney U tests showed a difference between level 1 and 3; effect size = 0.60 3 Mann-Whitney U tests showed a difference between level 1 and 3; effect size = 0.61
- Discussion • There was no difference in the amount of sleep reported by gender or living site • Older adults who slept more than 8 hrs consumed more sweets and iron than those who slept less than 7 hrs • Hours of sleep was associated with exercise and iron in older men, and sweets intake in older women. o Too much sleep → disruption in traditional meal times and increase in snacking (Kim, 2011; Sato-Mito, 2011)
- Background – Physical health measures Research question: How is physical health impacted by stress and other lifestyle factors in older adults? • Stress measures: blood pressure, heart rate, body mass index, body fat, waist circumference muscle mass o PSS scores associated with increased blood pressure and pulse (Hawkley, 2006) o Highest mean scores of BMI, WC, BP, HR were from the group with highest mean stress scores (Farag, 2008)
- Methods – Measuring physical health measures Research question: How is physical health impacted by stress and other lifestyle factors in an older population? • Blood pressure and heart rate were measured by the BpTRU BPM-200 • Waist circumference was taken at the umbilicus with standard measuring tape • Weight and percent body fat were measured by Inbody 230 • Height was measured with a stadiometer
- Results – Associations of physical health measures H11: Physical health measures are associated with stress in older adults. Variable N Correlation (r) with PSS-10 P value Muscle mass 56 -.327 .014 Percent body fat 58 .160 .232 Heart rate 61 .051 .696 Body mass index 59 -.061 .647 Diastolic BP 61 -.188 .146 Systolic BP 61 -.042 .747 Waist circumference 60 .134 .308
- Results – Associations of physical health measures H21: Muscle mass was associated with lifestyle factors in older adults. Variable N Correlations (r) with muscle mass P value Age 56 -.295 .020 Percent body fat 56 -.280 .028 Activity hours 53 .291 .034
- Results – Comparison of groups H30: There is no difference in physical health measures between older adults in the two living sites. Vowed Religious Community Independent Retirement Community M-W Stat* P value N Mean ± SE Mean ±SE Heart rate 67 75.86±2.08 68.41±1.99 386.5 .0291 % body fat 64 38.55±1.68 33.26±1.74 345.5 .0251 *Mann-Whitney U tests showing actual mean scores versus mean rank 1 Effect sizes for heart rate and body fat are .27 and .28, respectively.
- Physical health measures by group Variable N VRC IRC Test Stat1 P value Mean ± SE Mean ± SE Heart rate 67 75.86±2.08 68.41±1.99 386.5 .0291 Percent body fat 64 38.55±1.68 33.26±1.74 345.5 .0251 Waist circumference 66 39.74±1.14 40.13±3.69 465.5 .314 Muscle mass 62 55.86±2.54 54.43±2.51 463.5 .811 Systolic BP 67 128.37±4.14 131.89±3.34 447.0 .156 Diastolic BP 67 71.49±2.62 70.63±1.82 495.5 .418 1 Mann-Whitney U test statistic
- Results – Associations of physical health measures H41: Percent body fat and heart rate are associated with lifestyle factors in older adults. Variables N Correlations (r) P value Percent body fat 64 Muscle mass (kg) 56 -.280 .028 Saturated fat (kcals) 64 -.279 .026 Calcium (mg) 63 -.282 .025 B vitamins (mg) 63 -.275 .029 Heart rate 67 Vitamin C (mg) 66 -.291 .018
- Results – Comparison of groups H50: Perceived stress scores do not differ in older individuals with lower and higher muscle mass. Variable Muscle mass <54.3 kg Muscle mass >54.4 kg M-W stat* P value Mean ± SE Mean ± SE PSS-10 scores 9.96 ± 1.30 11.65 ± 1.00 307.5 .186
- Discussion • Lower muscle mass was associated with higher perceived stress o Negative body composition changes were associated with stress (Farag, 2008) • Percent body fat and heart rate were lower in the independent retirement community o Majority of individuals were not highly stressed, but mean % BF and WC were in elevated risk ranges for chronic disease o Age-related loss of muscle and increase of abdominal fat has been shown to increase risk of hypertension, diabetes, hypercholesterolemia, atherosclerosis, insulin resistance (Goh, 2010)
- Study strengths • Affluent control group → equalizer for groups • Equal number of participants in groups • Similar age range of groups, males and females • Conducted 24 hour recall • Properly trained research team obtained validated anthropometric measurements • Examined a population where little evidence-based research exists
- Study limitations • Cross sectional study design • Sample size was small • Self reported data: cannot be independently verified • Bias: selective memory (with 24 hour recall) • Data collection started during Lenten season
- Study conclusions • Compared to the independent retirement community, the vowed religious community had a lower level of wellness as indicated by our measures. • Lower stress may be related to certain lifestyle practices in older adults, particularly greater spirituality, but also eating fewer sweets, more vitamin D foods, and responsible alcohol intake.
- THANK YOU ! QUESTIONS ?
Editor's Notes
- In the United States, we have an aging population; the U.S. Census Bureau projects that by 2050, 20% of the U.S. population will be over the age of 65. According to the American Psychological Association, older adults are likely to report less stress than younger generations, but still report stress levels higher than what they think of as a healthy range. In older adults, increased stressful life events can lead to an increase in depressive symptoms. Many lifestyle factors, including diet, can impact our mood and stress levels. Older adults do not meet dietary guidelines for their age, they often eat less fruits, vegetables and whole grains, and more total fat and saturated fat than recommended. Poor dietary choices in the elderly can have negative outcomes on physical and mental health. Aging is also associated with increasing BMI and body fat which are related to increased blood pressure, blood glucose and lipids.
- We were given an opportunity through our contact with Father David to work with the Benedictine Monks at St. Procopius Abbey, the institution that founded our university. This is a group of older men who live in a cohesive community based in religious values. This opportunity made us curious about the impact of living environment on stress and other health and lifestyle factors, and so our research question was shaped by this population. Past literature indicated that a religious community can positively impact wellness, a 32 year follow up study of 144 nuns and 138 laypersons in Italy found that those living in a religious community had a more stable blood pressures, a common measure of stress, throughout the study compared to the control group. 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. Based on the previous literature, we hypothesized that older adults living in a vowed religious community would have less stress and healthier dimensions of mental and physical wellness than those living in a retirement community.
- Our objectives were two-fold; we wanted to explore various wellness dimensions including physical, emotional, social, and spiritual, with a focus on stress, as well as associations with health and lifestyle factors in older adults. We also wanted to compare stress and various other health and lifestyle factors of older adults living in a vowed religious community with those not living in an overt spiritual environment.
- We’d like to talk about our participants first, and then will go into more details of the recruitment process later. We started recruitment at St Procopius, the abbey associated with the University. At St Procopius we were able to recruit 6 of the 25 monks. In the end our study was comprised of 4 different vowed religious communities and 1 independent retirement community.
- We had a rolling recruitment, and added religious sites when groups were willing to participate. The second site we worked with was Sacred Heart Monastery, located in Lisle and home to 24 Benedictine Sisters. We also added a second Benedictine monk community, Marmion Abbey in Aurora, where 9 of the 20 men who live there participated.
- To increase our vowed-religious female participation we also worked with the School Sisters of St Francis of Christ the King. They are located in Lemont, and 10 of the sisters living there participated. For our comparison community, we were fortunate enough to work with the Monarch Landing Retirement Community in Naperville. Because the population at this site is large, we were able to get a similar number of participants from Monarch Landing as from the 4 vowed religious communities combined. Our recruitment process was very time intensive, and we would like to take this time to thank all the communities that participated in our study.
- There are similarities between the vowed religious communities and the independent retirement community. The demographics of the two living communities including age, race, and gender are very similar. Also, both groups have the ability to eat meals as a community that are prepared by a chef. Neither group experiences financial strains – the monks and nuns are financially taken care of by their abbeys and monasteries, and the people of Monarch Landing are largely affluent. While there are similarities between the two groups there are distinct differences. Daily responsibilities of the vowed religious group include prayer and meditation, overseeing care of the community’s grounds, and managing daily religious and special services. Many of the sisters and monks teach at their associated high schools and universities. In contrast, the retirement community is not required to have a religious based lifestyle. Monarch Landing provides their residents with many activities, but they are voluntary. Also, the residents have on campus access to extra resources like medical care, a salon, bank, and gym. Additionally, men and women both reside at Monarch Landing, whereas the religious communities are gender exclusive. Many of the retirement community residents live with a spouse and have children and grandchildren who visit and provide social support, whereas in the religious groups the majority of their daily emotional support comes from fellow monks and sisters.
- The study design was cross sectional and began with an email request to surrounding vowed religious and independent living community directors. Following the email transmission a phone call was performed to gauge interest level and clarify participation criteria. The next step, if the community decided to move forward with the study was to dispatch a group comprised of several students and the study mentor- Professor Dr. Beezhold, The group interacted with the facility point person in several ways: first they furthered explained the study goals, second they explained that metrics that would be collected, third they surveyed the facility for the best area in which to asses study participants and finally determined the best area to post recruitment flyers inside the facility. The flyer and sign-up sheet were then later designed by the student group and given to the facility point person several weeks prior to onsite data collection
- Our inclusion criteria was that the participant was 65 years or older, lived independently, that is, was able to perform all of their activities of daily living without help, and were willing to participate. So, our exclusion criteria included individuals who had extreme physical difficulty with routine activities of daily living, to the point of requiring constant assistance and individuals who because of cognitive difficulty would be unable to complete the surveys.
- The survey we designed included demographic questions as well as questions about lifestyle factors that could impact stress and wellness such as physical activity, sleep, activity hours, smoking and alcohol intake. Validated questions were used where possible. We also embedded four validated questionnaires to measure stress and other non-physical wellness dimensions. The group chose these questionnaires after exploring the literature to find those that were appropriate for older adults.
- The onsite data collection process began by securing several rooms or dividing up a large space with portable walls to form several data collection stations. Each group member was assigned to the same station each time for increased reliability during assessment.
- Data collection began with asking them to complete the survey in a quiet area, which took about 15 minutes. As you see from the pictures, each group member was assigned to the same stations each of the five days we collected data for more reliability of assessments. Subsequently, the data was entered into an Excel document and then prepared for analysis with SPSS software. Now April will talk about some of our results.
- When analyzing the data, we found that the distribution of the data was not normal therefore we used nonparamtetric tests to assess the data. So looking at the table, VRC stands for the vowed religious community and IRC stands for the independent retirement community. So, the sample consisted of 67 independent older adults aged 65 years and older. Of whom, 52% were in the vowed religious community and 48% were living in the independent retirement community. 39% of our sample were men and 61% of our sample were women. 75% of our sample was white. As you can see from our table, the independent retirement community had significantly more participants who had a degree compared to the vowed religious community. Activity hours or hours spent related to paid work or volunteer hours was significantly different by group with a large effect size. The vowed religious community spent significantly more time in work-related activity than compared to the independent retirement community. Additionally, we hypothesized that the vowed religious community would have higher scores on the spirituality and well-being scale. Interestingly, no significant differences were observed by group. There was also no significant associations found with the social support scale. Other related outcome variables will be explored by others on our team.
- Here is an illustration showing the various level of education attainment. As you can see, looking at all of our participants, the majority had a college degree with a little over half having a graduate degree.
- We also tested whether there were significant differences in physical health and lifestyle factors between each group. As you can see no significant differences were found in these particular variables. (short pause to let audience look at the table). Other physical health outcome variables will be focused on later.
- Although no significant differences were found in blood pressure levels by group. You can see from the graph that overall, the independent retirement community had slightly higher blood pressures than the vowed religious community.
- Cronbach alpha coefficients were also calculated for each of the wellness scales that we used in our sample. As you can see, we had good internal consistency reliability within our sample for the stress and depression scales, and excellent reliability for the spirituality and social support scales. Next, Shelby will present the relationships between stress and health and lifestyle factors.
- We explored the major research question about the role of stress in older adults and investigated whether it differed in the two living groups. According to the APA, Americans report a mean stress level of 4.9 on 10-point scale. Older adults are likely to report less stress than younger generations and they are most likely to report personal health concerns as a source of stress. They also are more likely to use going to church as a stress management tool than younger generations. So what exactly is stress? When we use the term stress, we are referring to chronic stress which leads to what is called ‘allostatic load’. Allostatic load is a state of ‘wear and tear’ on your body, and can be caused from increased mental or physical stressors such as work, life events, financial problems or inflammation.
- The hypothalamic-pituitary-adrenal axis, or the HPA axis, works to allow the body to adapt to prolonged exposure to these acute stressors which then becomes chronic stress. The HPA axis uses a negative feedback system and involves the release of cortisol, a stress hormone, as well as proinflammatory cytokines. A graphic of the HPA axis is shown. These mechanisms can be influenced by diet and other lifestyle factors. Chronic stress can alter the body’s normal stress response, metabolism and homeostasis and may produce psychological and physiological damage. High amounts of daily stressors is associated with oxidative stress and inflammation, and can lead to abdominal weight gain, depression, anxiety, cardiovascular disease, insulin resistance, frailty and mortality. So, chronic stress can accelerate biological aging and contribute to age-related chronic diseases.
- The perceived stress scale is the most commonly used tool to measure stress in research participants, including older adults. We used the 10-item version to assess perceived stress in our population. The scale asks participants to measure how often in the last month they felt specific ways. The answers include never, almost never, sometimes, fairly often and very often. There was no cap or normal range of the PSS, a higher score is associated with higher perceived stress, however scores can be compared to national averages for age and gender groups. As you can see, 61 participants completed the scale, and the mean for the sample was 10.84. The national average score of the PSS for this age group is a score of 12 so the mean for our participants was actually lower.
- We wanted to examine whether perceived stress was higher in the vowed religious community compared to the independent retirement community. First, here are average scores for the individual sites, the four vowed religious sites and the independent retirement community. The national average scores for the PSS for this age group is also shown above. Two of the sites had mean scores higher than the national average, Sacred Heart and the Franciscan Sisters.
- In order to test this hypothesis, we combined the religious sites into one and compared this group with the independent retirement community. A Mann-Whitney U test was conducted, and as you can see, perceived stress reported by the vowed religious community was greater than the independent retirement community, but the difference was not significant, therefore the null hypothesis was accepted. According to the APA, women historically report higher levels of stress, so we analyzed the sample by gender and conducted another Mann Whitney U test, and while females did have a higher mean score, it was not significant. We also compared stress scores by younger and older age groups with the cut off at 80 years old and there was no significant difference.
- We also wanted to examine the relationships between perceived stress and different health and lifestyle factors. The correlations shown are the ones that were significant. This is a cross sectional study so all correlations shown are linear relationships and not causal. Stress scores were not associated with blood pressure, a typical physical measure of stress. The strongest association was with spirituality scores, indicating that as reported spirituality increased, perceived stress decreased. Stress was also associated with depression, sweets intake, alcohol intake, and muscle mass which others will touch on later in the presentation. Perceived stress was negatively associated with a few healthy nutrients, listed above, so as perceived stress increased in our population, intake of these nutrients decreased. Overall, the null hypothesis was rejected.
- We entered the most significant (p&lt;.025) variables into a multiple linear regression test in order to investigate which variables were the biggest predictors of stress, and found that spirituality made the strongest unique contribution to explaining stress when these other variables were controlled for. Vitamin D and daily sweets consumption also made significant contributions to perceived stress. This set of variables explains 50% of the variance in total perceived stress scores. Spirituality uniquely explained about 11% of the total variance with Vitamin D uniquely explaining about 7% of the total variance in stress scores in the model. The alternative hypothesis was accepted.
- To wrap up stress, we found there was no difference in reported perceived stress in our two population groups and stress was not related to blood pressure, a common indicator of stress. The vowed religious community in our study actually reported higher stress, albeit not significant. We collected data in the Lenten season, which is characterized by increased religious services and responsibilities from the church and may have impacted the stress level of the religious community. Greater spirituality in our overall population was associated with lower stress, which confirms the previously mentioned study regarding nuns in Italy. Vitamin D intake was also important with regard to perceived stress in our sample. 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 the elderly. A cross-sectional analysis of the Iowa Women’s Health study found that those who consumed less than 400 IU of Vitamin D each day had lower mental health related quality of life. A recent review of Vitamin D and acute stress found that while Vitamin D can modulate the effects of proinflammatory molecules, there is, so far, an inconsistent relationship between Vitamin D and inflammation during times of acute stress (Quraishi&Camargo, 2012). Vitamin D receptors are widely distributed in the human brain, as well as the myocardium of the heart which may explain the mechanism that links Vitamin D intake to stress and stress mechanisms (Jiang et al 2012). Now, Jessica will discuss stress and alcohol intake
- We decided to look at alcohol intake and how it relates to health and wellness in our older adults. Alcohol use has a variety of health outcomes, depending on the amount one is drinking and how often it is drank. But what is of interest to many researchers is the benefits of drinking alcohol in moderation. Studies have suggested that low to moderate ETOH intake may be cardioprotective. This may result from improvements in insulin sensitivity and high density lipoprotein cholesterol, although the biological mechanisms between ETOH and their cardioprotective effects are not fully understood. (Rehm et al, 2003; O’Keefe et al, 2007) Also, moderate ETOH use may decrease the risk of dementia (Coker 2004; Mukamal 2003). Alcohol may transmit protective changes in cerebral vasculature. Those that drink moderate amounts have a lower prevalence of white matter lesions and subclinical infarcts, which may be attributed to HDL levels and fibrinogens, although they may only have a modest protective effect. Also, experimental studies have found that ethanol increases hippocampal acetylcholine, which could improve memory. And the inverse association of dementia and ETOH consumption was most pronounced in participants without a specific allele, which are a particular version of a trait (Coker 2004; Mukamal 2003). Those that have the specific allele, called the APOE e4 allele tend to form more plaque because of increased oxidation of apolipoprotein E, and from binding to beta-amyloid. And ETOH may suppress this binding due to its antioxidants. And research studies have suggested that people who consume moderate doses of alcohol have lower functional decline and mortality rates than heavy drinkers as well as non-drinkers (Chen 2009; Lang 2007; Paganini 2007). In fact, in studies comparing moderate drinkers and non-drinkers, moderate drinkers reported greater well-being and better quality of life than non-drinkers (Chan 2009; Lang 2007). The USDA defines moderate ETOH consumption as 1 drink per day for women and 2 drinks per day for men. Now that’s equal to: Twelve fluid ounces of regular beer, or 5 fluid ounces of wine, or 1.5 fluid ounces of 80-proof distilled spirits. [*APOE= (apolipoprotein E epsilon-4 genotype) e4 allele]
- So we asked our participants about their alcohol consumption with the question you see above. We adapted this question from NHANES 2003-2006. (Their question states: “ALQ101. The next questions are about drinking alcoholic beverages. Included are liquor (such as whiskey or gin), beer, wine, wine coolers, and any other type of alcoholic beverage. In any one year, have you had at least 12 drinks of any type of alcoholic beverage? By a drink, I mean a 12 oz beer, a 5 oz glass of wine, or 1½ oz of liquor.”) Our participants reported that on average, they drank 1.72 drinks per week, which is less than the average reported for older adults age 55 and older in the US in a Gallup Poll, and considered low alcohol intake according to the US Dietary Guidelines. (http://www.health.gov/dietaryguidelines/dga2005/document/pdf/Chapter9.pdf) Our sample size for the alcohol consumption question was 65 participants and data was not normal, so we used nonparametric analyses to assess the data.
- We also wanted to see whether there was a mean difference in alcohol intake by living site. We conducted a Mann-Whitney test and found that there was a difference between living sites, as the independent retirement community consumed about one more alcohol serving per week, with a medium effect size. There was no significant difference in weekly alcohol intake between males and females in the total sample.
- We also wanted to know if weekly alcohol consumption was related to other lifestyle and health factors we measured. We ran a Pearson correlations on alcohol per week with all other variables and we’re showing the significant association here. In our sample, as alcohol consumption rose, participants reported less stress. We also ran correlations by gender, and found that stress scores were only significantly correlated with alcohol intake in FEMALES, not in males, indicating that as alcohol intake rose, stress declined in females.
- We then categorized the weekly alcohol intake data into three categories you see here, so that I could investigate whether perceived stress and depression were different in increasing levels of alcohol intake. We ran a Kruskal Wallis test and found that there was a different between categories FOR BOTH SCALES. A Kruskal Wallis is a statistical test used on nonparametric data, that tests whether or not several independent samples come from the same population. Mann-Whitney tests revealed that stress scores were higher in those who are drinking no alcohol or a ½ beverage a week than those who are drinking 2 or more drinks per week, so reported stress was lower in those drinking more per week, WITH a large EFFECT. Depression scores were also different between alcohol intake categories (p=.025), and again, the difference was between the lowest and highest intake categories, and had a medium effect size, but GDS SCORES WERE NOT RELATED TO ALCOHOL INTAKE. ( see output- slide 8.)
- Less stress was reported in those drinking more alcohol than those who didn’t drink among our participants, and drinking alcohol was associated with less stress. Stress reduction is a popular way of conceptualizing the benefits of drinking alcohol. This is in accordance with the Tension reduction hypothesis, that alcohol has a sedative effect, and this may contribute to the reduction of tension (Conger 1956; Cappell & Greeley, 1987). Alcohol can also provide positive sensations and experiences for drinkers, stating that it’s relaxing (Hall et al, 1991; Pernanen 1991). In 2 different surveys, 54% of respondents identified relaxation, stress reduction, and improved psychological well-being as benefits of drinking alcohol (Hall et al 1992; Hall 1996). In a prospective study that analyzed over 65,000 men and women between the ages of 50 and 76, participants were evaluated on self-reported levels of perceived 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 (Barrington et al 2014). In a prospective study from 2007, over 6,000 participants over 50 years old participated in the English Study of Aging (ELSA) study, which examined cognitive function, subjective well-being, and depressive symptoms with various levels of alcohol intake. What they found was better cognition and higher levels of subjective well-being in those participants who drank in moderation, compared with those that never drank any alcohol. Another study, however, failed to show these associations. In a general population survey of over 6,000 males and 8,000 females aged 18 to 76 years, researchers asked about alcohol of four types of measures- frequency of use, usual and maximum quantity per occasion, volume drank, and heavy episodic drinking, covering both the past week and the past year, and 2 types of depression measures. What they found was that there was no evidence that light drinking promoted well-being when compared with lifetime abstainers, although light drinkers did report fewer recent symptoms of depressed affect. (Graham et al 2007). This inconsistency could be due to confounding factors, such as varying socio-demographic variables or the effect of chronic disease. On another note, there is growing concern of the elderly mixing alcohol with their medications (AMA Council on Scientific Affairs 1996). So as light to moderate alcohol intake may benefit one’s stress and depression levels, it is advised to forgo alcohol while taking medications. Speaking of depression, Nikki will report her findings of depression and its correlations among our participants.
- Another interesting topic within our research is the relationship between sweets intake and stress. Sweets refers to foods that have added sugars, including cookies, cakes, pastries, pies, and candy. The current Dietary Guidelines for Americans 2010 states Americans should: “Reduce the intake of calories from solid fats and added sugars & Limit the consumption of foods that contain refined grains especially refined grain foods that contain solid fat, added sugar and sodium.” These are rather vague recommendations, compared to the World Health Organization’s (WHO) recommendation that states that sugars should be no more than 10% of total energy intake per day. All of these guidelines emphasize the importance of choosing diets lower in added sugar because many health problems are associated with high sugar diets. Current data states that US older adults get about 11% of their total calories from foods with added sugar. This is still higher than the guidelines set by the WHO. There are several studies, but a large, recent cross-sectional study of European university students found that perceived stress was associated with more frequent consumption of sweets and fast food, and less frequent consumption of fruits and vegetables. Theories for why sugar intake and perceived stress are related go both ways…on one hand, chronic stress stimulates the glucocorticoid-augmented central neural network. This stimulation may act on the brain in a forward-feed to increase a person’s desire to eat calorically dense foods like sweets. Alternately, consumption of highly caloric foods like sugar and fat may down regulate dopamine receptors. Since dopamine reduces stress and depression, this decrease dopamine receptors may lead to increased stress in a person.
- During our study, sweets intake was measured with one question, “How many times per day, on average, do you eat sweets, like sugar-sweetened cake, cookies, candy, pie, or pastries?”. This question was taken from the Epic-Oxford survey and was adapted to include examples of sweets to clarify the question. In our study, the average number of sweets eaten per day was 1.06 for the whole sample.
- First, we looked at whether sweets intake was related to stress and other variables, so Pearson’s Correlations were run. Above you see only the significant correlations with sweets intake. This is a one-day snapshot of diet, and we only measured intake, not tissue concentrations, but interpretation can be as follows. If this were typical intake for participants, as intakes of all of these nutrients increased, except soluble fiber, perceived stress would increase as well. As soluble fiber intake increased, perceived stress decreased. Therefore, the null hypothesis was rejected.
- We also entered the most significant correlates into a multiple linear regression test, to investigate which one was the biggest predictor of sweets intake, and we found that perceived stress made the strongest unique contribution to explaining sweets when the other variables were controlled for. As perceived stress increased, sweets intake increased. Iron and thiamine intake also made significant contributions to sweets intake, and the three variables explain 37% of the variance in sweets intake. Perceived stress scores uniquely explained about 13% of the total variance of sweets intake in the model. The alternative hypothesis was accepted.
- Next, we investigated whether sweets intake differed by living environment, so a Mann-Whitney U test was run. Results showed there was a mean difference in sweets intake between the two groups with medium effect - the vowed religious community ate more sweets per day than the independent retirement community. Therefore, the null hypothesis was rejected. Also, it should be noted that Mann-Whitney U tests were run to compared sweets intake between genders and between the age groups old and oldest of old. No differences were found between these groups.
- Finally, we wanted to see whether perceived stress levels differed by the number of sweets eaten per day, so we categorized the sweets intake variable into three levels by the servings seen in the table. Most people ate only one sweet per day. A Kruskal Wallis test was conducted, and it showed that there was difference in stress scores between the 3 groups. Mann-Whitney U tests were conducted to assess where the scores differed, and we found that those who consumed 2+ sweets per day reported significantly higher stress scores than those who ate no sweets with large effect and between those who ate 1 sweet per day, with medium effect. So those who ate more sweets also reported more stress. The alternative hypothesis was accepted.
- First, we found that sweets intake was linked with stress, but it is difficult to know which one drove the other because this is a cross-sectional study and a causal relationship cannot be established. Also, we found that those who consumed more sweets per day reported higher perceived stress than those who consumed less sweets. This confirms findings from previous literature. Including, 2 large, cross-sectional, older adult studies that found that perceived stress was associated with a greater intake of sweets, high fat snacks and although it was not statistically significant, sugar sweetened beverages. Finally, we found nutrient associations with sweets in our sample. As sweets intake increased, intake of certain nutrients also increased. This can possibly be explained by the fact that in the U.S., white flour in enriched with iron, thiamine, riboflavin, niacin, and folate, and most sweets are made from the enriched white flour. Also, as sweets intake increased, soluble fiber intake decreased. We believe this occurs because sweets intake displaces intake of high fiber foods like fruits and vegetables. Now here is Nikki to discussion the associations of stress and depression in our sample
- 5.5% of older Americans have been diagnosed with depression. The DSM-V provides standard criteria for the classification of mental disorders. In addition, past literature repeatedly finds women report more depression than men. Symptoms include low mood, physical symptoms and evidence of chronic diseases. The consequences can be costly and serious. A quote that characterizes this condition well states, “...everyone feels blue sometimes, but depression is sadness that persists and interferes with daily life.”
- We used the Geriatric Depression Scale 15 questionnaire (GDS-15) as it’s been identified as appropriate to use with older adults to successfully diagnose depression, but has high reliability and validity. The fifteen questions are scored based on a point system, with a higher GDS score indicative of depression. 7.6% of our participants reported depression, which was higher than the overall reported depression for older adults in America at 5.5%.
- Based on review of literature, we wanted to investigate whether reported depressive symptoms differed between the two major living sites. Our hypothesis was that older adults living in a vowed religious environment would report less depression. We conducted a Mann-Whitney U test and found there was a significant difference between the living groups, with the vowed religious group reported a higher mean depression score than the community group, indicating they were more depressed. The null hypothesis was rejected. Since research shows that depression differs by gender, we conducted another test by gender, but there was NO difference in depression scores when we compared males and females in the whole sample (p=.297).
- We went on to investigate relationships between depressive symptoms and health and lifestyle factors since there is a lot of research showing depression is multifactorial. We conducted Pearson’s correlations with higher GDS scores and the significant correlations are shown here. Depression scores were associated with associated with higher perceived stress, and negatively associated with social support, indicating that as stress increased, depression increased, and as social support decreased, depression increased. Depression scores were also associated with living in the vowed religious community. The alternative hypothesis was accepted. Again, depression is usually associated with gender, but in this population it was not.
- Since these factors were significantly related to the GDS scores, we conducted a multiple linear regression to investigate how much of the variance in depression scores we observed between living groups. We entered perceived stress, social support, and living environment into the regression model, and found that 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.
- So coming back to our result of the vowed religious group reporting significantly more depression based on what we measured, we ran correlations with depression scores in the vowed religious group alone, and found that as stress and trans fat intake increased, depressive symptoms increased. Furthermore, those that consume a large amount of trans fats have been found to have a 48% risk of depression due to the low grade inflammatory status and endothelial dysfunction (Villegas et al., 2011). These results show a linear relationship between these variables and we cannot draw causal conclusions. Therefore, my null hypothesis was rejected.
- Our study was the first to compare levels of depression in different cohesive environments in older adults, surprisingly, our vowed religious participants reported more depression than those living in a retirement community. We obviously did not measure all factors related to development of depression, but did find stress was a contributor. For example, in study led by Fagundes et al. they evaluated relationships between depressive symptoms and stress-induced inflammation. Of the 138 participants, the more depressive symptoms produced more interleukin-6 in response to the stressor. Another study led by Aziz et al., 2013 looked at how perceived stress, social support and home based physical activity affect older adults’ fatigue, loneliness and depression on 163 participants. The findings indicated higher social support predicted lower levels of loneliness, fatigue and depression). North Am. 2013;36(4):497-516.
- We also wanted to capture data on sleep as it is well known that sleep plays a key role in mental health, physical health, and overall well-being 1,2. Ongoing sleep deficits are linked to increased levels of stress and negatively affects health such as increasing risk of heart disease and diabetes. Less than 7 hours of sleep can affect cognitive function such a concentration and memory loss. Also, not getting enough sleep is associated with increased weight and obesity1, 3, 4, 5Both the National Institute of Health and Centers for Disease Control and Prevention recommend 7-8 hours of sleep for both adults and elderly (6,7). Adequate sleep is necessary to fight infection, support metabolism, and enhance performance of day-to-day activity. Currently, 6.9% of adults get enough sleep. Some studies suggest that not only getting too little sleep but also getting too much sleep can have negative effects on health. A study from the Journal of Sleep found those who slept more than the current 7-8 hours of recommendation have an increased risk of heart disease, diabetes and obesity10.
- We wanted to know if environment impacted older adults with regard to sleep, so we were interested in both comparing sleep hours by living group, as well as investigating what sleep hours were related to. So, we asked the participants “How many hours of sleep do you typically get per night?” 66 participants averaged about 7 hours of sleep each night, which is on the lower end but certainly still within CDC’s recommendation. Thus our population appeared to be getting enough sleep, but less than the general population of older adults.
- The first thing we examined was whether there was a difference in reported hours of sleep per night between the two living groups. A Mann-Whitney test was conducted, and as you can see, the mean difference was small, and the p value was more than .05, so there was no difference, and the null hypothesis was accepted. There was also no difference in hours of sleep per night by gender. We also compared scores by younger and older age groups with the cut off at 80 years old and there was no significant difference.
- According to the literature, sufficient sleep is associated with mental and physical well-being in older adults. We wanted to investigate what factors we measured were related to sleep. A Pearson correlation was conducted on the whole population to explore relationships with sleep hrs. A significant positive correlation with sleep and iron intake (mg) was found, so as the hrs of sleep increased, intake of iron increased. We also ran correlations by gender. In older males, as mild and moderate exercise increased, the amount of sleep decreased. And, again, as iron intake increased, sleep hrs increased as well. Lastly, in older females, as the consumption of daily sweets increased, sleep hrs increased. So the alternative hypothesis was accepted.
- We then categorized the sleep hr variable into three levels so that we could investigate whether there was a difference in these significant correlates by sleep level. A Kruskal-Wallis test was then conducted and there was a difference between these sleep levels with respect to sweets/d and iron intake, so the null hypothesis was rejected. With both variables, differences were between those who slept more than 8 hours versus those who slept less than 7 hours, so between the highest and lowest sleep categories. Those who slept more than 8 hours had an additional serving of daily sweets and about 32 mg of iron on the day we measured dietary intake compared to those who slept less than 7 hours.
- There was no difference in living in a vowed community than living in an independent retirement community. But we did find that those sleeping 8 or more hours consumed more sweets and more iron. Our data involving iron confirms an earlier cross-sectional study which investigated the effects of sleep on dietary nutrients in 3300 participants; they also found that increased iron intakes were associated with increased hours of sleep. However, the reason why remains unexplained. Research shows that sleeping patterns influence the circadian rhythm of iron, and perhaps somehow affects intake. With regard to the finding that as exercise increased, sleep decreased in older men, research has shown only that exercise is associated with better quality of sleep. With regard to sweets intake in females, our data confirms a previous study (Kim et al.) that examined dietary intakes and sleep duration in 1000 participants in a US cohort analysis (35-75 yrs women). Increased intake of sweets was related to an increase in the hours of sleep. Too much sleep can promote eating during non-conventional hours and more likely to choose concentrated sweets/snacks. The two populations that we looked at were in secure environments with minimal concerns, overall they were able to achieve sufficient sleep. Next. Chad will report on associations with physical health measures. Kim S, Deroo LA, Sandler DP. Eating patterns and nutritional characteristics associated with sleep duration. Public Health Nutr. 2011;14(5):889-95. Sato-mito N, Sasaki S, Murakami K, et al. The midpoint of sleep is associated with dietary intake and dietary behavior among young Japanese women. Sleep Med. 2011;12(3):289-94.
- We also wanted to examine the difference in physical health measures between the groups and in comparison to lifestyle factors. We started by examining the cardiovascular stress and obesity measures of our sample against individuals of similar age in the US population. Our samples cardiovascular markers (Systolic, and diastolic blood pressure values,) were markedly lower being just 42% of what the cdc projected in a typical senior population Our population obesity measures (waist circumference, BMI and body fat) were found to be just slightly above the expected cdc percentage. The results of these findings are supported by research- which illustrate that high socioeconomic status and low perceived stress values are correlated with healthier cardiovascular readings and body composition as one ages.
- The physical health measures were again collected with the following equipment Blood pressure and pulse values: with a BpTRU -200 Portable automated Blood Pressure Monitor The waist circumference: with a traditional elastic body tape measure at the umbilcus BMI, muscle mass and body fat: with an inbody 230, bioelectrical impedance assessment scale
- We, first wanted to investigate the associations with stress and the 7 physical health measures. Thus, we ran a Pearson’s correlation test and found that only muscle mass was significantly associated with stress. The data revealed a moderate inverse relationship, indicating that as, stress increases, muscle mass decreases SO OUR ALTERNATE HYPOTHESIS WAS ACCEPTED
- Next, we wanted to investigate associations with muscle mass in our total sample. To do so we ran a Pearson’s correlation and found that muscle mass had three significant relationships The first two, body fat percentage and age had a small inverse association with muscle mass, indicating that as these two variables increased, muscle mass decreased. The third, activity hours had a small positive association with; indicating that as activity hours increased muscle mass also increased. Therefore the alternate hypothesis was accepted-
- As you saw previously, there was no difference in BMI, waist circumference, muscle mass, or blood pressure between living groups. But when we conducted Mann-Whitney tests on body fat and heart rate, there were significant differences. Thus, the null hypothesis is rejected. The values that were closer to optimal in the significant two parameters both occurred in the retirement community. Heart Rate in the retirement community was 68 bpm with the optimal range being between 55 and 65 bpm (Roitman J. 1998). Body fat in the retirement community was 33.26% above the elevated ranged of 30 entering into an area of concern.
- Next, we wanted to find out whether muscle mass or any of the other physical health parameters were different between living groups. We conducted a Mann-Whitney U test and found that muscle mass was not significantly different between groups, but body fat and heart rate values were. Thus, the null hypothesis was rejected.
- We then went further and ran a Pearson’s Correlation with the two significant variables and found four inverse associations with body fat and one inverse association with heart rate. Illustrating that as muscle mass, saturated fat calories, calcium and total B vitamin intake increased, body fat decreased. Heart rate values showed that as dietary intake of vitamin c increased heart rate values decreased. Thus alternative hypothesis was accepted.
- Due to stress being significantly associated with muscle mass we wanted to divide the muscle mass grouping equally in half and observe if there was a difference in stress values between the two. So we performed a Mann –Whitney U test and compared the groups. The results showed no significant difference between the two, however the mean stress scores were different illustrating the top half was under slightly more stress. Thus the null hypothesis was accepted.
- To summarize: muscle mass was the only physical health measure to be significantly impacted by stress. The relationship was inverse meaning as stress increased muscle mass tended to decrease. Previous research supports these findings first In the Whitehll two study evaluating in the impact on increasing daily work stressors on 6900 men and 3400 women aged 35-55 years old illustrated that muscle loss and increased body fat were most correlated with those experiencing the highest stress levels Another study of 74 female teachers in a rural public school system aged between 34 to 75 years old showed that those who experienced the most daily stressors over the school year had the highest body fat, body mass index, and waist circumference mean values. Between the two groups the retirement community adults recorded better mean physical health measures in the significantly different values. Heart Rate in the retirement community had a mean value of 68 bpm compared to the vowed religious community being 76 bpm. The optimal range for heart rate is being between 55 and 65 bpm (Roitman J. 1998). Thus both groups were outside of optimal but fell well below the high risk 90 bpm or greater measure. Body fat in the retirement community was 33% compared to 39% in the vowed religious community both well above the healthy range of 30 for a mixed sample. Thus increasing the risk for multiple chronic disease conditions {{285 Fontana,L. 2007;}}{{238. De Lorenzo A. 2013}}. In addition both groups also had overweight but not obese mean body mass values, and increased risk waist circumference measures , according to ACSM&apos;s Resource Manual for Guidelines for Exercise Testing and Prescription- seventh edition. Thus placing body composition improvement and mild fat loss the top concern for both groups. Associations with reduced body fat and greater muscle mass from our sample were partially supported in research. Research supports that being active vs, being sedentary helps to maintain muscle throughout the life cycle. For the activity to be beneficial in can take many forms: low intensity daily, moderate intensity 3 to 4 days a week or very intense 2 to 3 days a week (Goh V 2010) (Ekblom-Bak 2014). studies have proven that individuals with greater muscle mass report better glucose metabolism, higher resting basal metabolic rate, greater caloric expenditure during exercise, less triglyceride production, and less systemic inflation which all work together to maintain a normal bmi and reduce fat storage (Goh 2010). Our sample also showed reduced body fat percentages with increased dietary calories from saturated fat, calcium and b – vitamin intake. Research shows however that increasing the intake of saturated fat intake is not desirable due to the elevated nature of inflammatory markers that are circulating as a result of high body fat levels and chronic imbalance in the consumption of omega 6 to omega 3 fat foods (Ilich 2014). Research However does support limiting low nutritional value food selections while increasing omega 3, monounsaturated fat, low fat dairy, lean protein, seeds and low sugar fruit and non-starchy green vegetables one consumes to best lower all obese measures.
- With an affluent independent retirement community as our control group, this provided us a better ability to compare the two groups since both communities were generally financially secure. Socio-demographic characteristics were similar in both groups, including education, race/ethnicity, and age. Also, with an equal number of participants in each group, it allowed us to more equally compare the groups, and we had similar ages and also were able to recruit both males and females. By conducting the 24 hour recall, the study was provided a better picture of each participants’ diets, allowing for elaboration and clarification; unfortunately it covered just one day, and we don’t know if that day was typical. Furthermore, by using a properly trained research team, we were able to use validated tools and instruments to obtain our anthropometric measurements. Lastly, this was the first study of its kind to compare a vowed religious community to an independent retirement community with regard to perceived stress and other health and lifestyle factors.
- There were some limitations to our study. Since the design was cross sectional, we were not able to draw any causal conclusions. We could only investigate linear relationships and differences by group. We had a small sample size, however, to our knowledge, no other studies have compared these two types of communities, so a great follow up study would be to continue the research with a larger sample size. A more equal gender sample would benefit the study too. Our survey and diet recall depended on self report which is always a limitation. The population were older adults, so memory regarding foods eaten the previous day may not have been consistently accurate. Also, dietary intake may have been slightly modified during the Lenten season, although we did not collect data during Holy Week.
- Our results suggest that the vowed religious community had a lower level of wellness than the independent retirement community. They consumed more sweets, drank less alcohol, reported more depression & had higher body fat & heart rates. Spirituality was similar in both environments, and that factor was the biggest predictor of lower stress. Dietary practices may also be related to lower stress, such as eating less sweets, getting more vitamin D and drinking responsibly.
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