Journal of Public Health Management & Practice:
Development and Reliability Testing of the Worksite and Energy Balance Survey
Hoehner, Christine M. PhD, MSPH; Budd, Elizabeth L. MPH; Marx, Christine M. MA; Dodson, Elizabeth A. PhD, MPH; Brownson, Ross C. PhD
Division of Public Health Sciences, Department of Surgery, Washington University in St Louis, St Louis, Missouri (Drs Hoehner and Brownson and Ms Marx); Prevention Research Center in St Louis, Brown School (Ms Budd and Drs Dodson and Brownson).
Correspondence: Ross C. Brownson, PhD, Prevention Research Center in St Louis, Brown School, Washington University in St Louis, One Brookings Dr, St Louis, MO 63130 (firstname.lastname@example.org).
This research was supported by the National Cancer Institute (Transdisciplinary Research in Energetics and Cancer) grant number U48/CA155496 and by the Barnes-Jewish Hospital Foundation. The authors thank Robert Fields and Margaret Van Bakergem for their contributions to developing and testing the survey.
The authors declare no conflicts of interest.
Context: Worksites represent important venues for health promotion. Development of psychometrically sound measures of worksite environments and policy supports for physical activity and healthy eating are needed for use in public health research and practice.
Objective: Assess the test-retest reliability of the Worksite and Energy Balance Survey (WEBS), a self-report instrument for assessing perceptions of worksite supports for physical activity and healthy eating.
Design: The WEBS included items adapted from existing surveys or new items on the basis of a review of the literature and expert review. Cognitive interviews among 12 individuals were used to test the clarity of items and further refine the instrument. A targeted random-digit-dial telephone survey was administered on 2 occasions to assess test-retest reliability (mean days between time periods = 8; minimum = 5; maximum = 14).
Setting: Five Missouri census tracts that varied by racial-ethnic composition and walkability.
Participants: Respondents included 104 employed adults (67% white, 64% women, mean age = 48.6 years). Sixty-three percent were employed at worksites with less than 100 employees, approximately one-third supervised other people, and the majority worked a regular daytime shift (75%).
Main Outcome Measures: Test-retest reliability was assessed using Spearman correlations for continuous variables, Cohen's κ statistics for nonordinal categorical variables, and 1-way random intraclass correlation coefficients for ordinal categorical variables.
Results: Test-retest coefficients ranged from 0.41 to 0.97, with 80% of items having reliability coefficients of more than 0.6. Items that assessed participation in or use of worksite programs/facilities tended to have lower reliability. Reliability of some items varied by gender, obesity status, and worksite size. Test-retest reliability and internal consistency for the 5 scales ranged from 0.84 to 0.94 and 0.63 to 0.84, respectively.
Conclusions: The WEBS items and scales exhibited sound test-retest reliability and may be useful for research and surveillance. Further evaluation is needed to document the validity of the WEBS and associations with energy balance outcomes.
Worksite wellness programs and policies represent promising strategies for making a positive impact on the physical and psychological health of working adults, with the added benefit of reducing absenteeism, injuries, and health care costs.1–3 The worksite represents a particularly important setting for promoting physical activity, healthy eating, and healthy weight. For example, Healthy People 2020 includes an objective to increase the number of worksites that provide classes or counseling on nutrition and weight management.4 Moreover, in the Guide for Community Preventive Services, the Centers for Disease Control and Prevention highlights worksite wellness programs as evidence-based community interventions for controlling employee weight.5
Supportive worksite environments and policies assist employees in making healthful choices during and after work.5–8 A recent meta-analysis found that worksite physical activity and dietary behavior interventions contributed to a greater reduction in body weight among employees if the interventions contained an environmental component.9 Another review observed that multicomponent strategies, including education, employee and peer support for physical activity, incentives, and access to places to exercise, have strong evidence for influencing physical activity and good nutrition.10 Other reviews have been less conclusive about the unique contribution of environmental and policy approaches to influence healthy eating, physical activity, and obesity, noting the limited number of studies that modified the work environment.5,11 Several cross-sectional studies have observed associations between self-reported access to specific environments and policies and employee physical activity.7,8,12–14 Moreover, having multiple worksite policies has been associated with recreational physical activity7,8 and active commuting.13
Worksite environments and policies can be assessed by direct observation, manager interviews, and employee surveys.15 Although several tools have been tested for assessing worksite-level environmental supports for physical activity and healthy eating,16–20 the majority of surveys assessing employee perceptions in the general population have not undergone psychometric testing7,8,12,14,21 or are limited to assessing the worksite environment as it relates to physical activity only22 or nutrition offered through vending machines at the workplace.23 While direct observations of worksite environments and policies are useful for intervention planning, they are expensive for assessing population-level exposures. A survey instrument that reliably and comprehensively assesses employees' perceptions of worksite environments and policies would provide a valuable research tool for examining individual-level relationships with health outcomes and could be incorporated into surveillance systems. Altogether, improving the metrics for assessing worksite health promotion strategies will contribute to a better understanding about what strategies are most effective in promoting energy balance (caloric intake and energy expenditure via physical activity) and, thus, will inform best practices. The purpose of this study was to develop and test a survey instrument for assessing perceived worksite environmental and policy supports for healthy eating and physical activity.
The Worksite and Environment Balance Survey (WEBS) was developed following a literature review of existing instruments in which items were classified by the following worksite domains relevant for physical activity and healthy eating: promotions and programs (eg, exercise classes, diet counseling), organizational policies (eg, paid time for physical activity), social environment (eg, role models for making healthy food choices), internal physical environment (eg, exercise equipment, healthy vending options), and external environment (eg, walkable streets, fast food restaurants). In addition, items were identified that captured important contextual information about worksite and occupational characteristics, as well as behaviors occurring during work hours (eg, where meals eaten at work). The final WEBS included 7 sections (Table 1), with 84 items that were new or derived or adapted from existing instruments. The sections for worksite environmental and policy supports, and associated scales described later, were organized by specific worksite settings (ie, neighborhood outside the worksite, within the worksite as a whole, in the cafeteria, and at vending machines) or as part of the social environment/culture of the workplace. The sections are ordered by their appearance in the survey. Section 1 consisted of 12 descriptive open-ended and categorical items about the respondent's primary job and worksite characteristics. Items in this section were new (eg, supervise others, day/hours per week work) or derived from existing surveys.24–27 Section 2 included twelve 4-point Likert scale (strongly disagree to strongly agree) items about the neighborhood around the respondent's primary workplace, adapted from the Physical Activity Neighborhood Environment Scale,28 Moore et al,29 or new items. Section 3 included 32 yes/no/do not know response items about programs, facilities, and policies the respondent's primary employer offers. Most were adapted from previous surveys, for example, from the Neighborhood Quality of Life Study7,14 or others.8,16,17,30 Fourteen of these items assessed participation or use of worksite supports among participants who reported having the specified program/facility/policy. Section 4 was made up of 12 yes/no/do not know response items about the cafeteria, snack bar, or food service, many of which were new or adapted from existing instruments.16,20,31 These items were asked only among employees who reported having a cafeteria, snack bar, or employee food service. Section 5 included 5 questions pertaining to vending machines asked among employees who reported having vending machines at their workplace. These items were either new or adapted.31 Section 6 consisted of 5 open-ended questions about where the respondent obtained his or her meals during lunch breaks or other breaks while at work during the past week and were either new or adapted from existing instruments (K. Glanz, written communication, 2012). Section 7 included six 4-point Likert scale (n = 3 with strongly disagree to strongly agree and n = 3 with never to often response choices) questions about the organizational and social environment. Most were new items with 1 item from an existing instrument.31
Survey development and cognitive testing
The WEBS was part of a larger questionnaire being used for the Supports at Home and Work for Maintaining Energy balance (SHOW-ME) study. The entire survey was reviewed by 6 external researchers and 2 practitioners with expertise in physical activity, diet, worksite wellness, and health promotion. Edits were made following their review. Next, the survey underwent cognitive response testing. Volunteers from a research registry who were representative of the SHOW-ME participant population were recruited by telephone to participate in the cognitive response testing session. Additional volunteers (n = 4) were sought to add diversity of occupations. Twelve participants consented and participated in telephone interviews with 2 trained project staff (mean administration time, 53 minutes; range, 37-66 minutes). Interviews consisted of asking participants each question from the WEBS, followed by specific questions to determine information retrieval, question comprehension, decision processing, and confidence in the answer selected.32,33 Interviews were tape-recorded to facilitate note-taking. Participants were sent a $40 gift card after interview completion. Findings from the interviews were summarized and reviewed by the project team, resulting in the rewording of several questions to improve clarity. Additional cognitive response testing findings led to changes in the interviewer script and instructions to enhance participants' understanding of question intent.
Participants for the reliability study were sampled from Missouri regions within race-ethnicity and walkability strata being used for the larger SHOW-ME study. For this study, 5 Missouri census tracts were randomly sampled from the St Louis and Kansas City metropolitan areas. The tracts varied with respect to race-ethnicity (n = 2 tracts in high racial-ethnic minority stratum; n = 3 tracts in low racial-ethnic minority stratum) and walkability (n = 2 tracts in low walkability stratum; n = 2 tracts in moderate walkability stratum; n = 1 tract in high walkability stratum). High racial-ethnic minority was defined as 50% or less white or 50% or more Hispanic and low as more than 50% white and less than 50% Hispanic. Walkability was based on an index created from the sum of the z scores for intersection density, retail density, and household density, modified from a similar index.34 Adults within each of the 5 selected census tracts were recruited using list-assisted telephone random-digit-dialing methods, with a target sample size of 20 respondents per tract. Inclusion criteria for participation included (a) 21 to 65 years of age, (b) employed at least 20 h/wk, (c) works at 1 primary location, (d) primary workplace having 5 or more employees, (e) not pregnant, and (f) no physical limitation to prevent walking or bicycling in the past week. Participants completed the survey at 2 time points. Response rate for the baseline interview was 49%; 82% of participants at baseline participated in the retest survey. Mean time between test and retest surveys was 8 days (range, 5-14). Participants received a $20 incentive for participating. This study was approved by the Institutional Review Boards of Washington University in St Louis and University of Missouri-Columbia.
Data were analyzed using Statistical Package for the Social Sciences Version 20. To examine test-retest reliability, Spearman correlations were calculated for all continuous variables because of nonnormality of their distributions; Cohen's κ statistics for nonordinal, categorical variables; and 1-way model intraclass correlation coefficients for the ordinal, categorical variables derived from 1-way analysis of variance. “Refused” and “do not know” responses were included when calculating κ statistics because “do not know” was considered an important response to understand for questions about worksite supports; however, participants who answered “do not know” or “refused” were set to missing when calculating intraclass correlation coefficients and correlation coefficients for ordinal or continuous variables, respectively. Notably, the maximum number of participants with missing data for any of these ordinal or continuous variables was 6.
Scales were developed for all sections except the job and worksite characteristics (section 1) and meals (section 6) items. The items about the neighborhood around the workplace and about the organizational and social environment were dichotomized and coded so that higher values represented positive supports for physical activity and healthy eating, similar to what has been done previously for items pertaining to the neighborhood around the home.28,35 Next, items within each section of the WEBS were summed to yield 5 scales. The scales can be interpreted as the number of perceived healthy eating and physical activity supports within specific worksite settings or as part of the social environment/culture of the workplace. Items related to use of programs, facilities, and policies were excluded from the scales because they measured behaviors, not a worksite environmental or policy support. Test-retest was calculated with the intraclass correlation coefficients and internal consistency with Cronbach α.36
Differences in test-retest reliability of the items were examined by obesity status (<30 and ≥30 kg/m2) and worksite size (<100 employees and ≥100 employees) to test whether consistency in reporting of worksite supports varied by these factors. For example, employees in smaller worksites may more reliably report certain facilities and policies than employees in larger, and potentially more dispersed, worksites. As a rough guide in interpreting results, we followed the adjectival ratings suggested by Landis and Koch37 in the following categories: 1.0 to 0.8 (almost perfect agreement), 0.8 to 0.6 (substantial agreement), 0.6 to 0.4 (moderate agreement), 0.4 to 0.2 (fair agreement), and 0.2 to 0.0 (poor agreement).
Table 2 shows the demographic characteristics of the sample of 104 respondents at first completion (test portion) of the survey. Approximately two-thirds of participants were between 45 and 65 years old, female, non-Hispanic white, or married. The majority lived with one or more other people. About half of the respondents had a household income of $70 000 or more, and most (62.5%) had at least a college degree. Years employed at primary workplace varied. Approximately half of the participants were employed at worksites with less than 100 employees, approximately one-third supervised other people, and 75% worked a regular daytime shift. Overall, more than half reported very good to excellent health, most did not smoke at all, and more than one-fourth were obese.
Table 3 summarizes the mean and distribution of test-retest reliability for the WEBS items by each section of the tool. Most items (80.5%) demonstrated substantial to nearly perfect reliability, and no items had less than moderate reliability. Mean test-retest reliability was 0.70 (SD, 0.13) among all items and ranged from 0.41 to 1.0. In addition, there were 34 more “do not know” responses at baseline than at retest (data not shown).
Of the 12 items within the job and worksite characteristics section (section 1), 7 had almost perfect reliability, 4 had substantial reliability, and 1 had moderate reliability (ie, item about the number of days missed because of problems with physical or mental health). All of the neighborhood around workplace items (section 2) and organizational and social environment supports items (section 7) had substantial reliability. Of the 30 items related to programs, facilities, and policies (section 3), 6 items had almost perfect reliability, 18 had substantial reliability, and 6 had moderate reliability. The reliability of 2 items that assessed use/participation in physical activity breaks during meetings and incentives to walk/bike to work could not be calculated because of an insufficient number of respondents reporting these supports. Both of the items that assessed the presence of these supports had moderate reliability. The 4 other items with moderate reliability were those that assessed use of or participation in other worksite supports (eg, use of outdoor exercise facilities or flexible time for physical activity during the work day). The cafeteria and vending items were asked among the respondents who reported having a cafeteria, snack bar, or food service (n = 47) or vending machine (n = 84). Of the cafeteria items (section 4), 1 had almost perfect, 6 had substantial, and 5 had moderate reliability. Items with moderate reliability included ones assessing availability of the following in the cafeteria: nonfried meat entrees, low-fat snack items, low-fat dairy products, food in smaller or half-sized portions, and posters/signs that encourage healthy eating. Section 5 had 2 items with almost perfect reliability and 3 with substantial reliability. The meals section (section 6) had 1 item with substantial reliability (frequency of bringing lunch to work) and 4 with moderate reliability (frequency of purchasing meals at a cafeteria/food service, sit-down restaurant, fast food restaurant, or other type of restaurant). Test-retest reliability and internal consistency of the WEBS scales were strong. Deletion of the 7 items with moderate reliability did not alter the internal consistency of their respective scales (ie, cafeteria scale and program, facilities, and policies scale).
Reliability by obesity status
When stratified by obesity status (obese vs nonobese), 3 items had an insufficient number of respondents to calculate stratum-specific reliability coefficients. Thirty items had reliability coefficients that differed by more than |0.20| between obese and nonobese participants, and half of the differences were higher among obese participants with the other half higher among nonobese participants. Fourteen of the notable differences in reliability coefficients were in the workplace programs, facilities, and policies section. In general, most of the differences were among items that were asked among respondents who had reported a specified worksite support (ie, with small numbers) and/or items that were asked about a behavior that may have changed between assessment periods (eg, frequency of fast-food consumption).
Reliability by size of worksite
Three items had an insufficient number of respondents to calculate reliability coefficients by size of worksite (<100 employees or ≥100 employees). There were 26 instances in which the coefficients for an item were more than |0.20| different by size of worksite (data available upon request). Nine coefficients were higher among respondents from larger worksites, and 17 coefficients were higher among participants from smaller worksites. The program, facilities, and policies section had 11 of the 26 reliability differences, and 9 of those showed a higher reliability among the smaller worksites than the larger worksites. Eight of the differences in reliability coefficients in this section were for questions that asked about participation/use of a program or facility. Nine additional differences were found for items about food and beverage offerings among respondents with a cafeteria or food service. All but 2 of these had reliability coefficients that were higher among respondents employed in smaller worksites.
This study demonstrated high reliability of the WEBS among a diverse sample of working adults. Relationships between some of these worksite support measures and physical activity behavior have been observed in previous cross-sectional studies,7,8,12–14 but the psychometric properties of the measures were unknown. To our knowledge, no other self-report instruments for assessing worksite supports for healthy eating have been tested; thus, this study contributes to a growing literature on measurement of the food environment in different settings.15
All WEBS items had reliability coefficients that exceeded 0.40, with 80% of items exhibiting test-retest reliability coefficients above 0.60. The test-retest reliability coefficients were similar to findings from other studies of surveys used to assess worksite environments for physical activity22,38 as well as neighborhood environments. For example, the worksite neighborhood items and scale in the WEBS showed similar test-retest reliability as the home neighborhood environment items from which they were adapted.28 Altogether, of the 16 items with coefficients in the moderate range (0.40-0.59) across all sections, 9 items assessed behaviors or conditions, which had the potential to vary between assessment periods; thus, the lower reliability may reflect true changes in behavior or health condition rather than measurement error. Moreover, we observed a reduction in responses of “do not know” at retest. Taking the survey could have been enough to raise the awareness of some respondents about their worksite environment and policies, and in the time between the test and retest, respondents may have sought an answer to a survey question. This testing effect is only a concern if the tool were used as part of a pre- and posttest assessment for a worksite intervention.
Reliability differed for some items by obesity status and size of worksite. There were more items for which reliability was higher for respondents at smaller worksites (17 of 26 items) than for respondents at larger worksites. No clear patterns in reliability emerged by obesity status. Overall, the strength of coefficients within the various strata supports the reliability of the WEBS for diverse populations in worksites of various sizes.
A few limitations deserve mention. First, further evaluation is needed to document the validity of the WEBS and associations with physical activity and diet outcomes. Second, the relatively long length of the WEBS may preclude its adoption into surveillance systems. Yet, the WEBS can be shortened in the future when more evidence is available about associations with physical activity, diet, and obesity. Third, use or adaptation of existing items was a priority, resulting in some inconsistencies in response options. Specifically, factual items in the WEBS typically used a yes/no response format (eg, programs, facilities, and policies), with the exception of items pertaining to the neighborhood around the workplace, which used a Likert scale response because they were derived from an existing survey.7,14 Fourth, the sampling methods may limit generalizability in that participants were required to work at 1 primary location and possess a landline telephone; thus, wireless-only households were not represented.39
In summary, worksites are excellent venues for health promotion.8 Because of the rising costs of health care associated with obesity-related illness and disability, employers are increasingly interested in offering programs or benefits to assist employees in making healthful decisions.40 The WEBS showed promise as a useful tool for assessing workers' perceptions and knowledge about a comprehensive set of worksite facilities, programs, information, and policies for encouraging physical activity and healthy food options, both inside and outside the worksite. Moreover, it assessed coworker supports and norms concerning healthy lifestyle. WEBS items that are later shown to be associated with energy balance outcomes could be incorporated into ongoing surveys and surveillance systems to assist the public health and business community in understanding priorities for worksites, as well as uptake of available worksite programs and policies for activity and healthy eating.
1. US Chamber of Commerce and Partnership for Prevention. Leading by Example: Leading Practices for Employee Health Management. Washington, DC: Partnership for Prevention; 2007.
2. Combs S. Gaining Costs, Losing Time: The Obesity Crisis in Texas. Austin, TX: Office of the Comptroller; 2011.
3. Ickes M, Sharma M. Worksite health promotion: a practical strategy for obesity prevention. Am J Health Stud. 2009;24:343–352.
5. Anderson LM, Quinn TA, Glanz K, et al. The effectiveness of worksite nutrition and physical activity interventions for controlling employee overweight and obesity: a systematic review. Am J Prev Med. 2009;37(4):340–357.
6. Pratt CA, Lemon SC, Fernandez ID, et al. Design characteristics of worksite environmental interventions for obesity prevention. Obesity (Silver Spring). 2007;15(9):2171–2180.
7. Crespo NC, Sallis JF, Conway TL, Saelens BE, Frank LD. Worksite physical activity policies and environments in relation to employee physical activity. Am J Health Promot. 2011;25(4):264–271.
8. Dodson EA, Lovegreen SL, Elliott MB, Haire-Joshu D, Brownson RC. Worksite policies and environments supporting physical activity in midwestern communities. Am J Health Promot. 2008;23(1):51–55.
9. Verweij LM, Coffeng J, van Mechelen W, Proper KI. Meta-analyses of workplace physical activity and dietary behaviour interventions on weight outcomes. Obes Rev. 2011;12(6):406–429.
10. Matson-Koffman DM, Brownstein JN, Neiner JA, Greaney ML. A site-specific literature review of policy and environmental interventions that promote physical activity and nutrition for cardiovascular health: what works? Am J Health Promot. 2005;19(3):167–193.
11. Engbers LH, van Poppel MN, Chin APMJ, van Mechelen W. Worksite health promotion programs with environmental changes: a systematic review. Am J Prev Med. 2005;29(1):61–70.
12. Lucove JC, Huston SL, Evenson KR. Workers' perceptions about worksite policies and environments and their association with leisure-time physical activity. Am J Health Promot. 2007;21(3):196–200.
13. Kaczynski AT, Bopp MJ, Wittman P. Association of workplace supports with active commuting. Prev Chronic Dis. 2010;7(6):A127.
14. Schwartz MA, Aytur SA, Evenson KR, Rodriguez DA. Are perceptions about worksite neighborhoods and policies associated with walking? Am J Health Promot. 2009;24(2):146–151.
15. McKinnon RA, Reedy J, Morrissette MA, Lytle LA, Yaroch AL. Measures of the food environment: a compilation of the literature, 1990-2007. Am J Prev Med. 2009;36(4 suppl):S124–S133.
16. Dejoy DM, Wilson MG, Goetzel RZ, et al. Development of the Environmental Assessment Tool (EAT) to measure organizational physical and social support for worksite obesity prevention programs. J Occup Environ Med. 2008;50(2):126–137.
17. Oldenburg B, Sallis JF, Harris D, Owen N. Checklist of Health Promotion Environments at Worksites (CHEW): development and measurement characteristics. Am J Health Promot. 2002;16(5):288–299.
18. Dannenberg AL, Cramer TW, Gibson CJ. Assessing the walkability of the workplace: a new audit tool. Am J Health Promot. 2005;20(1):39–44.
19. Shimotsu ST, French SA, Gerlach AF, Hannan PJ. Worksite environment physical activity and healthy food choices: measurement of the worksite food and physical activity environment at four metropolitan bus garages. Int J Behav Nutr Phys Act. 2007;4:17.
20. Kim S, Adamson KC, Balfanz DR, et al. Development of the Community Healthy Living Index: a tool to foster healthy environments for the prevention of obesity and chronic disease. Prev Med. 2010;50(suppl 1):S80–S85.
21. Hoebbel C, Golaszewski T, Swanson M, Dorn J. Associations between the worksite environment and perceived health culture. Am J Health Promot. 2012;26(5):301–304.
22. Blunt GH, Hallam JS. The worksite supportive environments for active living survey: development and psychometric properties. Am J Health Promot. 2010;25(1):48–57.
23. Voss C, Klein S, Glanz K, Clawson M. Nutrition environment measures survey-vending: development, dissemination, and reliability. Health Promot Pract. 2012;13(4):425–430.
24. Centers for Disease Control and Prevention, National Center for Health Statistics. National Health and Nutrition Examination Survey Questionnaire. Hyattsville, MD: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2009.
25. Hill EJ, Hawkins AJ, Ferris M, Weitzman M. Finding an extra day a week: the positive influence of perceived job flexibility on work and family life balance. Fam Relat. 2001;50(1):49–58.
26. Kessler RC, Barber C, Beck A, et al. The World Health Organization Health and Work Performance Questionnaire (HPQ). J Occup Environ Med. 2003;45(2):156–174.
28. Sallis JF, Kerr J, Carlson JA, et al. Evaluating a brief self-report measure of neighborhood environments for physical activity research and surveillance: Physical Activity Neighborhood Environment Scale (PANES). J Phys Act Health. 2010;7(4):533–540.
29. Moore LV, Diez Roux AV, Nettleton JA, Jacobs DR, Franco M. Fast-food consumption, diet quality, and neighborhood exposure to fast food: the multi-ethnic study of atherosclerosis. Am J Epidemiol. 2009;170(1):29–36.
30. Maxwell AE, Yancey AK, AuYoung M, et al. A midpoint process evaluation of the Los Angeles Basin Racial and Ethnic Approaches to Community Health Across the US (REACH US) Disparities Center, 2007-2009. Prev Chronic Dis 2011;8(5):A115. http://www.cdc.gov/pcd/issues/2011/sep/10_0187.htm
. Accessed August 9, 2012.
32. Jobe JB, Mingay DJ. Cognitive research improves questionnaires. Am J Public Health. 1989;79(8):1053–1055.
33. Forsyth BH, Lessler JT. Cognitive laboratory methods: a taxonomy. In: Biemer PP, Groves RM, Lyberg LE, Mathiowetz NA, Sudman S, eds. Measurement Errors in Surveys. New York, NY: Wiley-Interscience; 1991:395–418.
34. Frank LD, Sallis JF, Saelens BE, et al. The development of a walkability index: application to the Neighborhood Quality of Life Study. Br J Sports Med. 2010;44(13):924–933. doi: 10.1136/bjsm.2009.058701.
35. Sallis JF, Bowles HR, Bauman A, et al. Neighborhood environments and physical activity among adults in 11 countries. Am J Prev Med. 2009;36(6):484–490.
36. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16:297–334.
37. Landis J, Koch G. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–174.
38. Brownson RC, Chang JJ, Eyler AA, et al. Measuring the environment for friendliness toward physical activity: a comparison of the reliability of 3 questionnaires. Am J Public Health. 2004;94:473–483.
40. Heinen L, Darling H. Addressing obesity in the workplace: the role of employers. Milbank Q. 2009;87(1):101–122.
diet; exercise; occupation; test-retest reliability; worksite environment
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