THE
C I E N C E
O F
L I F E S T Y L E
C H A N G E
Applied Research Brief: Social Health; Behavior Change
Promoting Changes in Obesogenic Behaviors: Does Coworker Social Support Play a Role? Sara L. Tamers, MPH, PhD; Bed Thompson, MA, PhD; Allen D. Cheadle, PhD; Yingye Zheng, MA, MS, PhD; Sonia K. Bishop, BS; Shirley A. A. Beresford, MSc, MA, PhD
Abstract Purpose. To examine the association between worksite social support and changes in diet, physical activity, and body mass index (BMI). Design. Cohort analysis of an underlying randomized, controlled, weight gain prevention worksite trial: Promoting Activity and Changes in Eating. Setting. The trial occurred in the greater Seattle area. Subjects. Baseline and follow-up data xoere obtained on a nested cohort o f employees (n = 958-1078) from 33 small- to medium-sized worksites. Measures. Worksite social support, diet, physical activity, and B M I measures were assessed using a self-reported questionnaire. Analysis. To adjust fo r multilevel data and multiple time points, we used generalized estimating equations and logistic mixed models. Results. Higher baseline worksite social support was associated with greater changes in fru it and vegetable intake (p = .001; summary food-frequency questions). Conclusion. This study does not support a conclusive relationship between worksite social support and health behavior change. (Am J Health Promot 2015;29[5]:311-313.) Key Words: Nutritional Status, Physical Activity, Body Mass Index, Social Support, Worksite Prevention Research. Manuscript format: research; Research purpose: relationship testing, descriptive; Study design: cohort analysis of underlying randomized controlled trial; Outcome measure: behavioral; Setting: workplace; Health focus: fitness/physical activity, nutrition, social health; Strategy: skill building/behavior change, policy, built environment; Target population age: adults; Target population circumstances: low/medium/high income level, greater Seattle area, mostly White
PURPOSE Higher levels of social support have been linked to improved diet, 1 physical activity? and lower body mass index (BMI)2; explanations include reduced stress, promoting healthy behaviors,3 and healthy norms and values encour aged by network ties.4 Many studies have examined the impact that social support from friends and family may have on health1"’; comparatively less evidence exists on the role of coworker social support6 and, in particular, its impact on obe sogenic behaviors. Furthermore, rela tively fewer studies6 have assessed the relationship between an overall sense of feeling supported—rather than that which is behavior focused—and health behaviors, especially at the worksite, although it too may have implications for behavior change. The goal of this study was to examine worksite social support and its association with changes in diet, phys ical activity, and BMI. METHODS
Sara L. Tamers, MPH, PhD, is with the Department of Social and Behavioral Sciences, Harvard School of Public Health and the Dana-Farber Cancer Institute, Boston, Massachusetts, and the University o f Washington and the Fred Hutchinson Cancer Research Center, Seattle, Washington. Beti Thompson, MA, PhD; Yingye Zheng, MA, MS, PhD; and Shirley A. A. Beresford, MSc, MA, PhD, are with the University of Washington and the Fred Hutchinson Cancer Research Center in Seattle, Washington. Allen D. Cheadle, PhD, is with the University of Washington, Seattle, Washington. Sonia K. Bishop, BS, is with the Fred Hutchinson Cancer Research Center, Seattle, Washington. Send re p rin t requests to Sara L. Tam ers, MPH, PhD, D e p artm en t o f Social a n d Behavioral Sciences, H arvard School o f Public H ealth, 677 H u n tin g to n Ave., Boston, MA 02115; stam ers® p o st.harvard.edu. T his m anuscript was submitted July 9, 2013; revisions were requested October 2 0 and December 18, 2013; the m anuscript was accepted fo r publication December 31, 2013. Copyright © 2 0 1 5 by American Journal o f H ealth Promotion, Inc. 08 9 0 -1 1 7 1 /1 5 /S 5 .00 + 0 DOI: 1 0 .4 2 78/ajhp. 1 3 0 709-ARB-352
American Journal of Health Promotion
D esign
We used data provided by the Promoting Activity' and Changes in Eating (PACE) worksite randomized controlled trial7 to examine the asso ciation between baseline levels of worksite social support and changes in diet, physical activity, and BMI. This research was approved by the institu tional review board of the Fred Hutchinson Cancer Research Center. Sam ple
Thirty-four small- to medium-sized worksites in the greater Seattle area
May/June 2015, Vol. 29, No. 5
311
Table Predicted Effect of Worksite Social Support on Changes in BMI, Physical Activity, and Diet for Nested Cohort of PACE Worksite Employees (N = 33t; n = 1078t) For One Unit Difference in Worksite Social Support
Predicted Mean/Odds Ratio§
BMI Physical activity Physical activity score Sweat-producing exercise Dietary behaviors Fruits and vegetablesH Fruits and vegetables# Fast-food restaurant meals Soft drink consumption Eating while doing other activities
95% Cl
P*
-0 .0 6
-0.31 , 0.18
0.619
-0 .2 2 0.89II
-2.96 , 2.52 0.51, 1.53
0.874 0.667
0.01 0.29 -0.14 0.02 1.2111
-0.08 , 0.12, -0.36, -0.25 , 0.73,
0.285 0.001 0.190 0.864 0.461
0.28 0.46 0.07 0.29 2.00
PACE indicates Promoting Activity and Changes in Eating; BMI, body mass index; and Cl, confidence interval. Note: For all outcomes, we coded 1 as the more positive change (e.g., reduced BMI, increased fruit and vegetable intake). t One worksite dropped out after baseline survey administration. $ The subsample varies from 958 to 1078, depending on outcome. § Adjusted for baseline outcome, worksites, intervention, gender, age, education, and race/ ethnicity. II Results that are odds ratios as opposed to predicted means. 1j Single question. # Summary food-frequency questions. * P for test of no association between worksite social support and each outcome.
were recruited and randomized to a 2year weight gain prevention interven tion/ Two independent cross-sectional surveys were conducted at baseline and follow-up. To perform longitudinal analyses, we restricted our focus to the nested cohort of PACE employees who filled out a survey at both time points and who were part of the intervention and control arm (n = 1240) with complete data for at least one statistical model (n = 958-1078). Measures
Worksite Social Support. We performed a principal components analysis to de velop a continuous worksite social support scale (1 = low to 4 = high), with an eigenvalue of 2.04 and a Cronbach a of .77/ Questions includ ed the following: I look forward to being with those on my shift or in my work group; people take a personal interest in each other on my shift or in my work group; members of my shift or work group really help and support one another. Diet. Dietary behaviors included daily servings of fruits and vegetables (using both a single-question and summary
312
American Journal of Health Promotion
food-frequency measure9); monthly fast-food restaurant meals; weekly soft drink consumption (regular or diet); and frequency of eating while doing other activities (never to always). Physical Activity. Physical activity mea sures included a computed metabolic equivalent score encompassing regu larity of free-time physical activity (strenuous, moderate, and mild) and a measure gauging the intensity of the workout (sweat: never/rarely, some times, often).10 Body Mass Index. BMI was calculated using PACE participants’ self-reported height (meters) and weight (kilo grams) . Analysis
For continuous outcomes, we used correlated data transition models to account for correlation caused by repeated measures, adjusting for base line outcomes with a derived outcome variable representing the difference between follow-up and baseline mea sures for each respective outcome. Each person contributed one observa tion to the model. To account for individuals clustered within the same
worksites, we ran generalized estimat ing equations with an identity-link, normal distribution, and exchangeable working correlation, using STATA ver sion 10.11 For categorical outcomes, we used a repeated measures model; each par ticipant contributed two observations to the analysis. To account for correla tion due to repeated measures and clustering within worksites for these binary outcomes, we used logistic mixed models with nested random effects, also using STATA version 10.11 To test our hypotheses, we modeled the association between baseline work site social support and changes in each outcome, adjusted for baseline out comes, worksites, intervention status, and covariates, for the entire nested cohort. RESULTS
Sociodemographics (results not shown) revealed an equal representa tion by gender and a mean age of roughly 44 years. Forty-five percent of participants were high school gradu ates or general educational develop ment recipients, and 77% of participants self-identified as White. The Table illustrates results from multivariate models testing for associ ations between worksite social support and changes in BMI, physical activity, and diet in the nested cohort. The mean social support score was high and not statistically different at base line and follow-up (results not shown; mean: 3.2; standard deviation: .5). Higher baseline worksite social support was associated with greater positive changes in fruit and vegetable intake (p= .001; summary food-frequency questions) only. DISCUSSION Summary
Our results showed that worksite social support was significantly associ ated with greater changes in fruit and vegetable intake only. One explanation could be that coworkers may not be a critical source of support. Alternatively, coworker support might only play a role if that support is specifically targeted at supporting healthy behav-
May/June 2015, Vol. 29, No. 5
iors rath er than at supporting an overall sense of well-being. Indeed, a sem inal study by Sallis et al . 12 suggest ed that general support m easures versus behavior-specific ones m ight be lim ited in assessing diet and physical activity. Still, the authors posited that general support may have distinct implications for different populations, such as those with smaller networks. Interestingly, we found a significant association with only one of o u r fruit and vegetable questions; this could fu rther support that ascertainm ent of diet may alter d epending upon the m easure used . 13 In the majority of similar studies, support measures used included those that captured behavior-specific support and its relationship with health behav iors. Thus, it is difficult to ju d g e our results com pared with those from previous studies that did not include non-behavior-specific support mea sures. Nevertheless, o u r findings are mostly distinct from those 14 and in line with the few that have focused on an overall feeling of support instead .1’’8 L im itations an d S trengths
T he self-reported measures may be subject to reporting bias due to social desirability. The lim ited variability in o u r social support m easure m ight have limited our ability to find significant relationships. Still, the longitudinal follow-up of the PACE intervention provided a unique opportunity to assess the im pact of general worksite social support on individual level changes in diet, physical activity, and BMI.
general social support on health be havior change, broadly, and at the worksite, m ore specifically. Hence, worksite interventions could benefit from results derived from supplem en tary research using such measures.
2000 .
SO WHAT? Implications for Health Promotion Practitioners and Researchers What is already known on this topic?
Behavior-specific social support can have a beneficial impact on health behaviors. What does this article add?
Less is known about the impact of non-behavior-specific coworker social support on changes in diet, physical activity, and body mass index. What are the implications for health promotion practice or research?
This study does not support a conclusive relationship between worksite social support and healthy behavior change. Implications may be limited to testing additional mea sures in other populations and using qualitative data to elicit any benefits of social support on health behavior change.
Acknowledgments The authors wish to acknowledge the training and support of the University of Washington's Department of Health Services; the National Cancer Institute’s Biobehavioral Cancer Prevention and Control Fellowship Grant (R25 CA092408); the National Heart, Lung, and Blood Institute Grant (R01 H L079491); and the N IH /N C I Harvard Education Program in Cancer Prevention and Control (R25 CA05 7713).
R eferences
Significance
While many of o u r hypotheses were not substantiated in this study, rela tively little data exist on the effects of
American Journal of Health Promotion
2. Greaves CJ, Sheppard KE, Abraham C, et al. Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions. BMC Public Health. 2011;11:119. 3. Berkman L, Kawachi K. Social Epidemiology. New York, NY: Oxford University Press;
1. Resnicow K, Campbell MK, Carr C, et al. Body and soul. A dietary intervention conducted through African-American churches. Am J Prev Med. 2004;27:97-105.
4. Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med. 2007;357:370-379. 5. Untas A, Thum m aJ, Rascle N, et al. The associations of social support and other psychosocial factors with mortality and quality of life in the dialysis outcomes and practice patterns study. Clin J Am Soc Nephrol. 2011;6:142-152. 6. Sorensen G, Stoddard AM, Dubowitz T, et al. The influence of social context on changes in fruit and vegetable consumption: results of the healthy directions studies. Am J Public Health. 2007; 97:1216-1227. 7. Beresford SAA, Locke E, Bishop S, et al. Worksite study promoting activity and changes in eating (PACE): design and baseline results. Obesity. 2007;15(suppl 1): 4S-15S. 8. Tamers SL, Beresford SA, Cheadle AD, et al. The association between worksite social support, diet, physical activity and body mass index. Prev Med. 2011;53:53-56. 9. Thompson FE, Byers T. Dietary assessment resource manual. JNutr. 1994;124(suppl 11):2245S-2317S. 10. Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci. 1985;10: 141-146. 11. Stata Statistical Software [computer program]. Release 10. College Station, Tex: StataCorp; 2007. 12. Sallis JF, Grossman RM, Pinski RB, et al. The development of scales to measure social support for diet and exercise behaviors. Prev Med. 1987;16:825-836. 13. Willel W. Nutritional Epidemiology. 2nd ed. Oxford, UK: Oxford University Press; 1998. 14. Lemon SC, ZapkaJ, Li W, et al. Perceptions of worksite support and employee obesity, activity, and diet. Am J Health Behav. 2009;33:299-308.
May/June 2015, Vol. 29, No. 5
313
Copyright of American Journal of Health Promotion is the property of American Journal of Health Promotion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
C I E N C E
O F
L I F E S T Y L E
C H A N G E
Applied Research Brief: Social Health; Behavior Change
Promoting Changes in Obesogenic Behaviors: Does Coworker Social Support Play a Role? Sara L. Tamers, MPH, PhD; Bed Thompson, MA, PhD; Allen D. Cheadle, PhD; Yingye Zheng, MA, MS, PhD; Sonia K. Bishop, BS; Shirley A. A. Beresford, MSc, MA, PhD
Abstract Purpose. To examine the association between worksite social support and changes in diet, physical activity, and body mass index (BMI). Design. Cohort analysis of an underlying randomized, controlled, weight gain prevention worksite trial: Promoting Activity and Changes in Eating. Setting. The trial occurred in the greater Seattle area. Subjects. Baseline and follow-up data xoere obtained on a nested cohort o f employees (n = 958-1078) from 33 small- to medium-sized worksites. Measures. Worksite social support, diet, physical activity, and B M I measures were assessed using a self-reported questionnaire. Analysis. To adjust fo r multilevel data and multiple time points, we used generalized estimating equations and logistic mixed models. Results. Higher baseline worksite social support was associated with greater changes in fru it and vegetable intake (p = .001; summary food-frequency questions). Conclusion. This study does not support a conclusive relationship between worksite social support and health behavior change. (Am J Health Promot 2015;29[5]:311-313.) Key Words: Nutritional Status, Physical Activity, Body Mass Index, Social Support, Worksite Prevention Research. Manuscript format: research; Research purpose: relationship testing, descriptive; Study design: cohort analysis of underlying randomized controlled trial; Outcome measure: behavioral; Setting: workplace; Health focus: fitness/physical activity, nutrition, social health; Strategy: skill building/behavior change, policy, built environment; Target population age: adults; Target population circumstances: low/medium/high income level, greater Seattle area, mostly White
PURPOSE Higher levels of social support have been linked to improved diet, 1 physical activity? and lower body mass index (BMI)2; explanations include reduced stress, promoting healthy behaviors,3 and healthy norms and values encour aged by network ties.4 Many studies have examined the impact that social support from friends and family may have on health1"’; comparatively less evidence exists on the role of coworker social support6 and, in particular, its impact on obe sogenic behaviors. Furthermore, rela tively fewer studies6 have assessed the relationship between an overall sense of feeling supported—rather than that which is behavior focused—and health behaviors, especially at the worksite, although it too may have implications for behavior change. The goal of this study was to examine worksite social support and its association with changes in diet, phys ical activity, and BMI. METHODS
Sara L. Tamers, MPH, PhD, is with the Department of Social and Behavioral Sciences, Harvard School of Public Health and the Dana-Farber Cancer Institute, Boston, Massachusetts, and the University o f Washington and the Fred Hutchinson Cancer Research Center, Seattle, Washington. Beti Thompson, MA, PhD; Yingye Zheng, MA, MS, PhD; and Shirley A. A. Beresford, MSc, MA, PhD, are with the University of Washington and the Fred Hutchinson Cancer Research Center in Seattle, Washington. Allen D. Cheadle, PhD, is with the University of Washington, Seattle, Washington. Sonia K. Bishop, BS, is with the Fred Hutchinson Cancer Research Center, Seattle, Washington. Send re p rin t requests to Sara L. Tam ers, MPH, PhD, D e p artm en t o f Social a n d Behavioral Sciences, H arvard School o f Public H ealth, 677 H u n tin g to n Ave., Boston, MA 02115; stam ers® p o st.harvard.edu. T his m anuscript was submitted July 9, 2013; revisions were requested October 2 0 and December 18, 2013; the m anuscript was accepted fo r publication December 31, 2013. Copyright © 2 0 1 5 by American Journal o f H ealth Promotion, Inc. 08 9 0 -1 1 7 1 /1 5 /S 5 .00 + 0 DOI: 1 0 .4 2 78/ajhp. 1 3 0 709-ARB-352
American Journal of Health Promotion
D esign
We used data provided by the Promoting Activity' and Changes in Eating (PACE) worksite randomized controlled trial7 to examine the asso ciation between baseline levels of worksite social support and changes in diet, physical activity, and BMI. This research was approved by the institu tional review board of the Fred Hutchinson Cancer Research Center. Sam ple
Thirty-four small- to medium-sized worksites in the greater Seattle area
May/June 2015, Vol. 29, No. 5
311
Table Predicted Effect of Worksite Social Support on Changes in BMI, Physical Activity, and Diet for Nested Cohort of PACE Worksite Employees (N = 33t; n = 1078t) For One Unit Difference in Worksite Social Support
Predicted Mean/Odds Ratio§
BMI Physical activity Physical activity score Sweat-producing exercise Dietary behaviors Fruits and vegetablesH Fruits and vegetables# Fast-food restaurant meals Soft drink consumption Eating while doing other activities
95% Cl
P*
-0 .0 6
-0.31 , 0.18
0.619
-0 .2 2 0.89II
-2.96 , 2.52 0.51, 1.53
0.874 0.667
0.01 0.29 -0.14 0.02 1.2111
-0.08 , 0.12, -0.36, -0.25 , 0.73,
0.285 0.001 0.190 0.864 0.461
0.28 0.46 0.07 0.29 2.00
PACE indicates Promoting Activity and Changes in Eating; BMI, body mass index; and Cl, confidence interval. Note: For all outcomes, we coded 1 as the more positive change (e.g., reduced BMI, increased fruit and vegetable intake). t One worksite dropped out after baseline survey administration. $ The subsample varies from 958 to 1078, depending on outcome. § Adjusted for baseline outcome, worksites, intervention, gender, age, education, and race/ ethnicity. II Results that are odds ratios as opposed to predicted means. 1j Single question. # Summary food-frequency questions. * P for test of no association between worksite social support and each outcome.
were recruited and randomized to a 2year weight gain prevention interven tion/ Two independent cross-sectional surveys were conducted at baseline and follow-up. To perform longitudinal analyses, we restricted our focus to the nested cohort of PACE employees who filled out a survey at both time points and who were part of the intervention and control arm (n = 1240) with complete data for at least one statistical model (n = 958-1078). Measures
Worksite Social Support. We performed a principal components analysis to de velop a continuous worksite social support scale (1 = low to 4 = high), with an eigenvalue of 2.04 and a Cronbach a of .77/ Questions includ ed the following: I look forward to being with those on my shift or in my work group; people take a personal interest in each other on my shift or in my work group; members of my shift or work group really help and support one another. Diet. Dietary behaviors included daily servings of fruits and vegetables (using both a single-question and summary
312
American Journal of Health Promotion
food-frequency measure9); monthly fast-food restaurant meals; weekly soft drink consumption (regular or diet); and frequency of eating while doing other activities (never to always). Physical Activity. Physical activity mea sures included a computed metabolic equivalent score encompassing regu larity of free-time physical activity (strenuous, moderate, and mild) and a measure gauging the intensity of the workout (sweat: never/rarely, some times, often).10 Body Mass Index. BMI was calculated using PACE participants’ self-reported height (meters) and weight (kilo grams) . Analysis
For continuous outcomes, we used correlated data transition models to account for correlation caused by repeated measures, adjusting for base line outcomes with a derived outcome variable representing the difference between follow-up and baseline mea sures for each respective outcome. Each person contributed one observa tion to the model. To account for individuals clustered within the same
worksites, we ran generalized estimat ing equations with an identity-link, normal distribution, and exchangeable working correlation, using STATA ver sion 10.11 For categorical outcomes, we used a repeated measures model; each par ticipant contributed two observations to the analysis. To account for correla tion due to repeated measures and clustering within worksites for these binary outcomes, we used logistic mixed models with nested random effects, also using STATA version 10.11 To test our hypotheses, we modeled the association between baseline work site social support and changes in each outcome, adjusted for baseline out comes, worksites, intervention status, and covariates, for the entire nested cohort. RESULTS
Sociodemographics (results not shown) revealed an equal representa tion by gender and a mean age of roughly 44 years. Forty-five percent of participants were high school gradu ates or general educational develop ment recipients, and 77% of participants self-identified as White. The Table illustrates results from multivariate models testing for associ ations between worksite social support and changes in BMI, physical activity, and diet in the nested cohort. The mean social support score was high and not statistically different at base line and follow-up (results not shown; mean: 3.2; standard deviation: .5). Higher baseline worksite social support was associated with greater positive changes in fruit and vegetable intake (p= .001; summary food-frequency questions) only. DISCUSSION Summary
Our results showed that worksite social support was significantly associ ated with greater changes in fruit and vegetable intake only. One explanation could be that coworkers may not be a critical source of support. Alternatively, coworker support might only play a role if that support is specifically targeted at supporting healthy behav-
May/June 2015, Vol. 29, No. 5
iors rath er than at supporting an overall sense of well-being. Indeed, a sem inal study by Sallis et al . 12 suggest ed that general support m easures versus behavior-specific ones m ight be lim ited in assessing diet and physical activity. Still, the authors posited that general support may have distinct implications for different populations, such as those with smaller networks. Interestingly, we found a significant association with only one of o u r fruit and vegetable questions; this could fu rther support that ascertainm ent of diet may alter d epending upon the m easure used . 13 In the majority of similar studies, support measures used included those that captured behavior-specific support and its relationship with health behav iors. Thus, it is difficult to ju d g e our results com pared with those from previous studies that did not include non-behavior-specific support mea sures. Nevertheless, o u r findings are mostly distinct from those 14 and in line with the few that have focused on an overall feeling of support instead .1’’8 L im itations an d S trengths
T he self-reported measures may be subject to reporting bias due to social desirability. The lim ited variability in o u r social support m easure m ight have limited our ability to find significant relationships. Still, the longitudinal follow-up of the PACE intervention provided a unique opportunity to assess the im pact of general worksite social support on individual level changes in diet, physical activity, and BMI.
general social support on health be havior change, broadly, and at the worksite, m ore specifically. Hence, worksite interventions could benefit from results derived from supplem en tary research using such measures.
2000 .
SO WHAT? Implications for Health Promotion Practitioners and Researchers What is already known on this topic?
Behavior-specific social support can have a beneficial impact on health behaviors. What does this article add?
Less is known about the impact of non-behavior-specific coworker social support on changes in diet, physical activity, and body mass index. What are the implications for health promotion practice or research?
This study does not support a conclusive relationship between worksite social support and healthy behavior change. Implications may be limited to testing additional mea sures in other populations and using qualitative data to elicit any benefits of social support on health behavior change.
Acknowledgments The authors wish to acknowledge the training and support of the University of Washington's Department of Health Services; the National Cancer Institute’s Biobehavioral Cancer Prevention and Control Fellowship Grant (R25 CA092408); the National Heart, Lung, and Blood Institute Grant (R01 H L079491); and the N IH /N C I Harvard Education Program in Cancer Prevention and Control (R25 CA05 7713).
R eferences
Significance
While many of o u r hypotheses were not substantiated in this study, rela tively little data exist on the effects of
American Journal of Health Promotion
2. Greaves CJ, Sheppard KE, Abraham C, et al. Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions. BMC Public Health. 2011;11:119. 3. Berkman L, Kawachi K. Social Epidemiology. New York, NY: Oxford University Press;
1. Resnicow K, Campbell MK, Carr C, et al. Body and soul. A dietary intervention conducted through African-American churches. Am J Prev Med. 2004;27:97-105.
4. Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med. 2007;357:370-379. 5. Untas A, Thum m aJ, Rascle N, et al. The associations of social support and other psychosocial factors with mortality and quality of life in the dialysis outcomes and practice patterns study. Clin J Am Soc Nephrol. 2011;6:142-152. 6. Sorensen G, Stoddard AM, Dubowitz T, et al. The influence of social context on changes in fruit and vegetable consumption: results of the healthy directions studies. Am J Public Health. 2007; 97:1216-1227. 7. Beresford SAA, Locke E, Bishop S, et al. Worksite study promoting activity and changes in eating (PACE): design and baseline results. Obesity. 2007;15(suppl 1): 4S-15S. 8. Tamers SL, Beresford SA, Cheadle AD, et al. The association between worksite social support, diet, physical activity and body mass index. Prev Med. 2011;53:53-56. 9. Thompson FE, Byers T. Dietary assessment resource manual. JNutr. 1994;124(suppl 11):2245S-2317S. 10. Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci. 1985;10: 141-146. 11. Stata Statistical Software [computer program]. Release 10. College Station, Tex: StataCorp; 2007. 12. Sallis JF, Grossman RM, Pinski RB, et al. The development of scales to measure social support for diet and exercise behaviors. Prev Med. 1987;16:825-836. 13. Willel W. Nutritional Epidemiology. 2nd ed. Oxford, UK: Oxford University Press; 1998. 14. Lemon SC, ZapkaJ, Li W, et al. Perceptions of worksite support and employee obesity, activity, and diet. Am J Health Behav. 2009;33:299-308.
May/June 2015, Vol. 29, No. 5
313
Copyright of American Journal of Health Promotion is the property of American Journal of Health Promotion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
