A preliminary survey of university employee's perceptions of work related stress: association with diet and exercise on campus.
Abstract: Objective: This study examined university employees' perceptions of work related stress and coping in relation to the impact on perceived health status and health promoting behaviors.

Participants: All faculty and staff employed at a southeastern university in the United States received an e-mail invitation to participate in an online survey.

Methods: This study identified high and low stress risk groups in a unique population of university employees based on perceived stress and perceived coping skills. The diet and exercise patterns were subsequently assessed based on stress risk.

Results: University employees with high stress and poor coping skills were more likely to use food as a coping mechanism and were less likely to exercise due to work-related stress. Conclusion: Future researchers should investigate steps that college administrators can take to help alleviate some of these problems, such as offering workshops on stress relief and time management to faculty and staff.
Subject: Workers (Surveys)
College administrators (Surveys)
Workers (Beliefs, opinions and attitudes)
Universities and colleges
Job stress
Stress management
Authors: Khubchandani, Jagdish
Nagy, M. Christine
Watkins, Cecilia M.
Nagy, Stephen
Balls, Joyce E.
Pub Date: 03/22/2009
Publication: Name: American Journal of Health Studies Publisher: American Journal of Health Studies Audience: Professional Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2009 American Journal of Health Studies ISSN: 1090-0500
Issue: Date: Spring, 2009 Source Volume: 24 Source Issue: 2
Product: Product Code: 8220000 Colleges & Universities; 8000141 Nutrition & Diet Programs NAICS Code: 61131 Colleges, Universities, and Professional Schools; 621498 All Other Outpatient Care Centers SIC Code: 8221 Colleges and universities
Accession Number: 308743739

Wellness and health promotion programs that endorse best practices frequently target their interventions on high risk audiences. More recent public health initiatives have focused on excess weight and sedentary lifestyles since these behaviors have health care costs in excess of $90 billion a year (Finkelstein, Fiebelkorn, & Wang, 2003). Employers in industrial and academic settings have confirmed that modifying unhealthy behaviors results in cost savings. These savings include, reduced number of primary care patient visits along with increased employee productivity (Stein, Shakour, & Zuidema, 2000). Sedentary lifestyles, decreased physical activity and high calorie diets are the leading factors related to health problems of adult workers like heart disease, cancers, stroke and diabetes (CDC, 2008). The benefits of healthy diet and physical activity have been exhaustively studied and documented; however, the physical activity and dietary habits of the working adult population in the United States have witnessed a modest change over the past decade (Mokdad, Marks, Stroup, & Gerberding, 2004).

In theory and practice there is accumulating evidence that poor psychosocial characteristics have adverse effects on employee wellbeing (Noblet, 2003). A common psychosocial concept that has been examined is 'stress'; with research relationships between stressors and health behaviors of employees showing mixed results. Several studies have reported positive associations between stress and increased fat intake (Hellerstedt & Jeffrey, 1997); higher consumption of snacks, caffeine, and fast food (Pak, Olsen, & Mahoney, 2000); higher consumption of red meat, pizza, soda, and milk (Spillman, 1990); higher intake of soft drinks and candy, especially chocolate (Steptoe, Lipsey, & Wardle, 1998) and higher intake of junk food (Watkins, Lartey, Golla, & Khubchandani, 2008). Studies on the relationship between stress and physical activity have been less consistent with some studies reporting that men and women exercised more when stressed (Spillman, 1990) and other studies reporting no differences in exercise by stress level (Watkins et al, 2008). It is clear that current measures of stress fail to consistently produce findings that would benefit health promotion programs for targeting at risk audiences. Surprisingly, most of the studies exploring effects of stress on employee well being had been conducted in industrial settings and non-academic work places. Furthermore, these agencies measure the incidence and prevalence rates of occupational stress indirectly, by looking at clinical outcomes (days of employee absence, injuries and illness). The Bureau of Labor Statistics' Survey of Occupational Injuries and Illnesses (BLS, 1999) classifies occupational stress as "neurotic reaction to stress." There were 3,418 such illness cases in 1997. The median absence from work for these cases was 23 days, greater than four times the total number of all nonfatal occupational injuries and illnesses. And more than two-fifths of the cases resulted in 31 or more lost workdays, compared to one-fifth for all injury and illness cases (BLS, 1999). The concept of working employees and their perceptions of stress in relation to diet and physical activity have been explored inadequately, especially in the academic workplaces.

Lazarus and Folkman (Thoits, 1995), the pioneers in the field of stress and coping have postulated that stress by itself does not negatively impact on health and health behaviors. They have implied that excess and chronic stress that overextends the individual's ability to cope with their challenges results in undesirable outcomes. Generally individuals can cope by using two primary methods; namely, "emotion-focused coping" and "problem-focused coping" (Monat & Lazarus, 1991). Emotion-focused coping addresses the undesirable characteristics of the stress response such as irritated stomach, and anxiety while problem-focused coping directly addresses the source of stress. A healthy coping response would therefore, use both types of coping; using positive emotion-focused coping strategies to reduce anxiety and unwanted distractions to allow an individual to utilize cognitive, problem-focused strategies to directly alleviate the stress. Given this coping approach to deal with excessive stress, one would expect low health risk and better measures of health in such individuals. However, individuals who utilize negative emotion-focused strategies such as poor diet, and distraction approaches, such as watching television, end up using their coping abilities to deal with emotional issues and are hampered in using their cognitive abilities to resolve stress.

Coping behavior and work environment in general affect the health outcomes of employees which indirectly affects the corporate outcomes. Individuals who perceive high workplace stress and subsequently engage in negative emotion focused coping are at-risk subjects having poorer health outcomes. These individuals could benefit from health promotion interventions (Green & Kreuter, 2005). This study explores the work related stress and coping responses of a unique population of university employees. The purpose of this study was twofold: 1) To identify university employees with high perceived stress and negative emotion-focused coping; and 2) To compare this group of university employees with high perceived stress and negative emotion focused coping with their counterparts on self-reported BMI (body mass index), perceived health status, exercise and dietary patterns and the number of perceived barriers for exercise and good dietary habits. Determining whether one of these stress defined groups is at higher risk should assist health promotion program planners to more effectively develop programs.



The online survey was sent to faculty and staff (N = 1980) working full time at a university located in the south eastern United States during the summer of 2007. Following the initial solicitation, two follow up reminders were sent to encourage participation in the online survey. Published techniques to increase the response rate were used (Dillman, 2006). Study procedures, solicitation documents, and the survey questionnaire were approved by an Institutional Review Board. The solicitation emails had detailed information about the procedures for taking the survey and respondents were informed about implied consent if they agreed to respond. Risks and benefits were similarly explained in the solicitation email. An a priori power analysis was conducted for this study. Based on a total population of 1980 college employees and a 50/50 split with regard to the practice of interest (i.e., it was assumed that 50% of the college employees would report that stress at work does not influence them), it was determined that a sample of 322 college employees would be needed to make inferences to the total population with a sampling error of + 5% at the 95% confidence level (Price, Dake, Murnan, Dimmig & Akpanudo, 2005).


The online survey consisted of 21 questions. Face validity of the questionnaire was established by way of a comprehensive literature review. Content validity was established by sending the questionnaire to an expert panel for review (n = 4). Specifically, a panel of individuals with expertise in the content area and/or survey research methods reviewed the initial version of the questionnaire. Minor revisions were made to the instrument based on the panel's recommendations. Respondents rated their level of agreement with the items using Likert-type scales as well as multiple response formats. Demographic and background items were included for descriptive purposes (e.g., gender, designation, age and duration of employment). The theoretical foundation for the survey included Social Cognitive Theory (SCT) and a key component of the Health Belief Model (HBM). With regard to HBM, a meta-analysis of its various constructs found that the best predictors of health behaviors were perceived barriers (Harrison, Mullen, Green, 1992). Thus, these two theories were a part of the practical underpinnings for the questionnaire used for this study.

Stress risk was the dependent variable for the study and was derived from two items on the questionnaire. The first item used a 5-point rating scale to measure work-related stress. The responses were divided into three categories, namely, high, moderate and low stress. The second item, "How do you feel you are dealing with your work related stress?" had five possible response options ranging from 'deal with workplace stress very well' to 'feel unable to deal with workplace stress'. Response options were divided into two categories representing 'good coping' and 'poor coping'. The final measure for the dependent variable was then established by combining both items (perceived stress and perceived coping ability) and then categorizing them into two categories; high stress risk and low stress risk.

The 'stress risk' variable therefore incorporated perceptions of stress level and perceived good or poor coping into one measure. Additional survey items identified perceived barriers for exercise and healthy diets on campus. Other items asked the respondents to rate their perceived health status, and to provide their height and weight. Respondents' height and weight were used to calculate body mass index (BMI). The U.S Centers for Disease Control specify that overweight and obesity ranges are determined by using weight and height to calculate a number called the "body mass index" (BMI). An adult who has a BMI between 25 and 29.9 is considered overweight. An adult who has a BMI of 30 or higher is considered obese (CDC, 2008).


The online survey was developed using Easy Survey Package Software (The MAPILab Company, 2007). The software randomizes the submission of responses to preserve anonymity.


Data were analyzed using the Statistics Package for Social Science (SPSS) version 14.0. Level of significance was set at a priori p < .05. Descriptive statistics (% in each category or M and SD) were calculated to describe the respondents and their responses to the questionnaire. Categorical data were analyzed using Pearson chi-square ([chi square]) tests. Independent samples t-tests were used for continuous variables.



A total of 415 employees completed the survey (Table 1). The respondents were predominantly females (64.6 %) and the majority identified themselves as university staff members (63.6%). Nearly half of the respondents reported being employed for fewer than 5 years (44.8%). Respondents showed a good mix of ages; (55.3%) were between 18 to 47 years of age.

To assess whether the respondents were representative of total study population the university human resources department was requested to furnish demographic details of all the employees. The university human resources employee summary document indicated that our survey respondents were highly representative of the total employee population. Almost 35% respondents were males (the total population had 38.7% males), 35.4% respondents were self identified faculty members (the total population had 34.9% faculty members), and 44.8% respondents reported being employed for less than 5 years (the total population had 42.3% individuals employed for less than 5 years).

Almost 9 out of 10 respondents reported that they experienced moderate or high levels of work-related stress (Table 2). About one quarter (26.3%) of the respondents indicated that they were having difficulty dealing with work-related stress. Nearly two thirds of the employees (65.8%) reported that they were in very good health. Scores on body mass index ranged from 16.7 to 67.5 with a mean of 26.77 (S.D = 5.93); BMI scores were then divided into two categories with more than half of the respondents (54.5%) being classified in the overweight/obese category and the rest classified as normal/underweight. When asked how work-related stress influenced their eating patterns, 99.8% of the respondents indicated that food was used as a coping mechanism. Respondents were allowed to have multiple responses. Respondents reported that due to work related stress they exclusively ate smaller (10.8%) or larger (13.5%) amounts of foods or they ate more (32.3%) or less (0.2%) junk food. When asked how work-related stress influenced their exercise patterns, 47.7% of the respondents reported that it did not affect their exercise patterns, 15.2% reported that they exercised more while 36.9% indicated that they exercised less.

Respondents identified a number of barriers that prevented them from eating a healthy diet on campus. They were allowed to have multiple responses. These included the time constraints (42.9%), cost (29.4%) and quality (19.3%) of food available, distance from food services (20%) and the lack of parking (22.2%) as well as work assignments (14.7%). Respondents also identified a number of barriers that prevented them from getting enough exercise on campus. These included the cost associated with a membership to the gym (24.6%), time constraints (61.9%), distance from the exercise facility (20.5%) as well as the lack of parking (24.6%) and work assignments (27.7%).


Nearly 90% of the respondents reported that they experienced moderate or high levels of work-related stress (Table 2). Further analyses indicated that perceptions of work-related stress were not significantly different for males or females, younger or older employees (18-47 years of age or 48 and older), health status or body mass index. Chi square analyses identified significant differences on perceptions of work-related stress based on years of services ([chi square] = 9.580, p = .008), and faculty or staff designation ([chi square] = 8.658, p = .013). Employees with more than 4.9 years of experience were significantly more likely than those with fewer years of experience to report that they perceived their work-related stress as high or very high ([chi square]= 9.182, p = .002). In addition, faculty were more likely than staff to report that they were experiencing high ([chi square] = 5.733, p = .017), or moderate stress [chi square] = 6.366, p = .012).


About one quarter (26.3%) of the respondents indicated that they were having difficulty dealing with work-related stress (Table 2). Chi square analyses identified only two differences with respect to perceived ability to deal with stress; these were on health status and BMI. Employees were more likely to report that they were not able to deal with stress if they were overweight or obese ([chi square] = 5.733, p = .017), or if they were not in excellent or very good health [chi square] = 21.460, p < .001).


The dependent variable 'stress risk' was created using responses to two measures 'perceived stress levels at work' and 'perceived ability to deal with stress'. Of the 415 university employees, 44.1% were classified in the high stress risk group and 55.9% in the low stress risk group (Table 3). Although most employees reported that they were in excellent or very good health, those in the high stress risk group were significantly more likely than those in the low stress risk group to report that their health was good, fair or poor ([chi square] = 17.161, p < .001). Chi square analysis compared the BMI categories of the high and low stress risk groups. Results indicated that employees in the high stress risk group were significantly more likely than those in the low stress risk group to be in the overweight or obese category ([chi square] = 7.721, p = .005).

Examination of exercise patterns found that university employees in the high stress risk group were significantly more likely than those in the low stress risk group to exercise less due to work-related stress ([chi square] = 19.195, p < 0.001). In addition, university employees in the high stress risk group were significantly more likely than those in the low stress risk group to consume smaller amounts of food ([chi square] = 6.727, p = .009), larger amounts of food ([chi square] = 4.47, p = .03) and consume more junk food ([chi square] = 8.652, p = .003) in response to work-related stress. Work-related stress did not affect exercising more or eating less junk food.

Respondents identified a number of barriers that prevented them from exercising and eating a healthy diet on campus. The number of barriers for exercise for each employee was summed to create an exercise barrier score. Scores ranged from 0 to 5 with a mean of 1.65 (SD = 1.24). Independent t-test found that the mean exercise barrier score for those in the high stress group (M = 2.02) was significantly higher than the mean for the low stress group (M = 1.36) (t = 5.287, p < .001). The number of barriers for not eating a healthy diet for each employee was also summed to create a healthy diet barrier score. Scores on this measure ranged from 0 to 6 with a mean of 2.01(SD = 1.19). Independent t-test found that the mean healthy diet barrier score for those in the high stress group (2.24) was significantly higher than the mean healthy diet barrier score (1.83) for the low stress group (t = 3.285, p = .001).


The purpose of this study was to examine university employees' perceived level of work-related stress and how they were coping with stress in relation to its impact on perceived health status and health promoting behaviors in an academic setting. Most comparisons between high stress risk group and low stress risk group individuals on various measures (barriers in getting adequate exercise, barriers in eating a healthy diet, health status and BMI) were significant. These analyses confirmed that individuals in the high stress risk group had riskier health profiles than their low stress risk counterparts; this has been documented periodically in research at non-academic workplaces. However, the findings from this study point to information that may assist program planners in academic and campus settings. Individuals who self-identified as having high stress levels and also self-identified as displaying poor coping had scores that were consistent with profiles of poorer health status, poorer health indicators and more perceived barriers for healthy practices such as exercise and healthy diets. Given these findings, program planners should be sensitized to target audiences who self-identify as having high levels of stress coupled with poorer self-identified coping skills. It is highly likely that this group has higher BMI's, and displays more unhealthy health practices. Furthermore, this group is less likely to adopt healthy eating patterns and also exercise since they perceive more barriers to possible program participation. It may be wise for program developers to conduct focus groups or other similar needs assessments with high stress risk target groups to gain insight into methods that can be used to increase participation in health promotion activities. Additional research focused on clearly defining high stress risk and perceptions of health status and health promotion barriers is warranted.

Several limitations need to be addressed while discussing the findings of this research. The convenience sample of employees was recruited from only one public university located in the southeastern United States. Additionally, the study was based on a self-administered questionnaire and therefore, respondents may have answered some of the questions in a socially desirable way. If so, this would be a threat to the internal validity of the findings. Furthermore, the response rate was modest, which may be linked to the fact that the data were collected using an internet survey. Finally, the questionnaire was monothematic (only covering stress at workplace) which may have created a mindset in responding to the questions that may not have been indicative of the respondents true perceptions and practices. The measure of stress risk was established in a relatively simple manner that may not fully recognize all the complexities associated with coping responses. Our measure was consistent with coping research which has indicated that individuals with poorer coping abilities tend to become more emotion focused in their efforts while individuals with better coping abilities tend to address stress related issues and feel more in control. While this may be a general view, there will always be some individuals who may be experiencing extreme stress and are good at coping and also experience health problems.

The limitations of the study may also point out the possible strengths of the findings. In a case where we had a voluntary group respond to issues of stress, it is highly likely that individuals under extreme stress do not have the time or energy to participate in a voluntary activity. To find significant associations with minimal participation from the entire population of study holds promise for future studies in academic settings.


Substantial numbers of workers in the responding sample had relatively high perceived levels of stress, had difficulty coping with stress and engaged in high risk behaviors of sedentary lifestyle and poor dietary practices. Clearly this group of workers is at high risk for chronic disease conditions in the future. This is likely to be accompanied with lower work productivity that may be negatively impacted by these developing chronic problems. Administrators and policy makers should consider how work conditions may be modified to change perceptions of stress. This may incorporate more clearly defined job descriptions or modifying work environments to make them less stressful.

Secondly, administrators and policy makers must realize that investments in policies and work environments that promote positive responses to stress such as exercise and better diets are advantageous to both employers and employees. A thorough review of how an ecological perspective of the work environment may assist in promoting effective and positive stress management is warranted.

Other universities may benefit from similar assessments and reviews. The perceptions of stress, coping techniques and the administrative response on how to address these issues have considerable potential for improving work environments and worker productivity.


Centers for Disease Control and Prevention (2008). Overweight and Obesity. Economic Consequences. Retrieved June 28, 2008 from http://www.cdc.gov/nccdphp/dnpa/obesity/economic-consequences.htm

Centers for Disease Control and Prevention (2008). About BMI for adults. Retrieved September 4, 2008, from http://www.cdc.gov/nccdphp/dnpa/healthyweight/assessing/bmi/

Dillman, D.A. (2006). Mail and Internet Surveys: The Tailored Design Method. NJ: Wiley.

Finkelstein, E.A., Fiebelkorn, I.C., Wang G. (2003). National medical spending attributable to overweight and obesity: How much, and who's paying? Retrieved September 4, 2008, from http://content.healthaffairs. org/cgi/reprint/hlthaff.w3.219v1.pdf

Green, L.W., Kreuter, M.W. (2005). Health Program Planning: An Educational and Ecological Approach. NY: McGraw-Hill Higher Education.

Harrison, J. A., Mullen, P. D., Green, L. W. (1992). A meta-analysis of studies of the health belief model with adults. Health Education Research, 7, 107-116.

Hellerstedt, W.L., & Jeffrey, R.W. (1997). The association of job strain and health behaviors in men and women. International Journal of Epidemiology, 26, 575-583.

Kornitzer, M., & Kittel, F. (1986). How does stress exert its effects: smoking, diet and obesity, physical activity? Postgraduate Medical Journal, 62, 695-696.

Mokdad, A.H., Marks, J.S., Stroup, D.F., Gerberding, J.L. (2004). Actual causes of death in the United States. Journal of American Medical Association, 291:1238-1245.

Monat, A., & Lazarus, R. (1991). Stress and coping: An anthology. West Sussex, NY: Columbia University Press.

Noblet, A. (2003). Building health promoting work settings: Identifying the relationship between work characteristics and occupational stress in Australia. Health Promotion International, 18, 351-359.

Pak, S.K., Olsen, L.K., & Mahoney, B.S. (2000). The relationships of health behaviors to perceived stress, job satisfaction, and role modeling among health professionals in South Korea. International Quarterly of Community Health Education, 19, 65-76.

Price, J.H., Dake, J.A., Murnan, J., Dimmig, J., & Akpanudo, S. (2005). Power analysis in survey research: Importance and use for health educators. American Journal of Health Education, 34, 202-207.

Prochaska, J. O., Redding, C. A., & Evers, K. E. (2002). The Transtheoretical Model and Stages of Change. In K. Glanz, B. K. Rimer, and F. M. Lewis (Eds.), Health behavior and health education: Theory research and practice (3rd ed). San Francisco: Jossey Bass.

Spillman, D (1990). Survey of food and vitamin intake responses reported by university students experiencing stress. Psychological Reports, 66, 499-502.

Stein, A.D., Shakour, S.K., & Zuidema, R.A. (2000). Financial incentives, participation in employer-sponsored health promotion, and changes in employee health and productivity: Health Plus Health Quotient Program. Journal of Occupational Medicine, 42, 1148-1155.

Steptoe, A., Lipsey, Z., & Wardle, J. (1998). Stress, hassles and variations in alcohol consumption, food choice and physical exercise: A diary study. British Journal of Health Psychology, 3, 51-63.

The MAPILab Company (2007). MAPILab easy survey. Retrieved September 4, 2008, from: http://www. mapilab.com/outlook/easy_survey/

Thoits, A.P. (1995). Stress, coping and social support processes: Where we are? What next? Journal of Health and Social Behavior, 35, 53-79.

U.S. Department of Labor Bureau of Labor Statistics (1999). Occupational Stress. Retrieved July 18, 2008 from: http://www.bls.gov/opub/ils/pdf/opbils35.pdf

Watkins, C.M., Lartey, G.K, Golla, V., Khubchandani, J. (2008). Worker's perception: Environmental factors influencing obesity at the workplace. American Journal of Health Studies, 23, 74-80.

Jagdish Khubchandani, MBBS, MPH, is a Doctoral Graduate Assistant in University of Toledo. M. Christine Nagy, PhD, is an Associate Professor in Western Kentucky University. Cecilia M. Watkins, PhD, is an Associate Professor in Western Kentucky University. Stephen Nagy, PhD, is an Associate Professor in Western Kentucky University. Joyce E. Balls, MPE, is a Doctoral Student in University of Toledo. Please address all correspondence to Jagdish Khubchandani, Doctoral Graduate Assistant, College of Health Science and Human Services, Department of Health and Rehabilitative Services, Mail Stop # 119, HH 1003 B, University of Toledo. 2801 W. Bancroft St. Toledo, Ohio -43606-3390. Phone: (O) 419-530-8591, Phone: (M) 703-474-7623, Fax: (419) 530-4759, Email: Jagdish.Khubchandani@Utoledo.edu.
Table 1. Demographic Characteristics of the respondents (N = 415)

Trait                    N     %


Female                  268   64.6
Male                    136   32.8


Staff                   264   63.6
Faculty                 151   36.4

Current Age

18-27 Years              45   10.8
28-37 Years              96   23.1
38-47 years              89   21.4
48-57 years             137   33.0
58 years and above       48   11.6

Time since Employment

Less than 4.9 years     186   44.8
5 years-9.9 years        94   22.7
10 years-14.9 years      48   11.6
15 years-19.9 years      36    8.7
More than 20 years       50   12.0

Table 2. Percentage of Respondents by Study Variables

Variables                  N     %

Perceived stress
levels at work

High or very high         140   33.7
Moderate                  209   50.4
Low or very low            66   15.9

Perceived ability to
deal with stress

Well or fairly well       306   73.7
Poor                      109   26.3

Perceived Health Status

Excellent or very good    273   65.8
Good, Fair or poor        142   34.2

BMI Categories
(Based on self reported
height and weight)

Overweight or obese       226   54.5
Under weight or normal    177   42.7

Perceived Barriers for
Eating Healthy (On

Time constraints          178   42.9
Cost of food              122   29.4
Lack of parking            92   22.2
Distance from food         83   20.0
Quality of food            80   19.3
Work assignments           61   14.7

Perceived Barriers for
Getting Exercise (On

Time constraints          257   61.9
Work assignments          115   27.7
Cost of Gym Membership    102   24.6
Lack of parking           102   24.6
Distance from exercise     85   20.5

Table 3. Percentage of Respondents by Independent Measures and High
(n = 183) and Low (n = 232) Stress Risk Group

Independent measures      High Stress Risk   Low Stress Risk
                           (N = 183) N (%)    (N = 232) N (%)

Perceived health status

Excellent or very good        106(57.9)         167(72)
Good, Fair or Poor             77(42)            65(28)

Low/Normal                    64(36.2)          113(50)
Overweight/ Obese             113(63.8)         113(50)

Influence of perceived
Stress on exercise

Exercise less                 89(48.6)          64(27.7)
Exercise more                 32(17.5)          31(13.4)

Influence of perceived
Stress on eating

Eat more junk food            73(39.9)          61(26.3)
Eat smaller amount            28(15.3)          17(7.3)
  of food
Eat larger amounts            32(17.5)          24(10.3)
  of food
Independent measures          P value   [chi square]

Perceived health status
Excellent or very good         0.000       17.161
Good, Fair or Poor


Overweight/ Obese              0.005        7.721

Influence of perceived
Stress on exercise

Exercise less                  0.000       19.195
Exercise more

Influence of perceived
Stress on eating

Eat more junk food             0.003        8.652
Eat smaller amount             0.009        6.727
  of food
Eat larger amounts             0.034        4.470
  of food
Gale Copyright: Copyright 2009 Gale, Cengage Learning. All rights reserved.