Features of the Neighborhood Environment and Walking by U.S. Adults

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1 Research Articles Features of the Neighborhood Environment and Walking by U.S. Adults Richard R. Suminski, PhD, MPH, Walker S. Carlos Poston, PhD, MPH, Rick L. Petosa, PhD, Emily Stevens, BS, Laura M. Katzenmoyer, BS Background: Methods: Results: Conclusions: Manipulating the physical environment may be an efficacious way to promote physical activity. This study examined the relationships between features of the neighborhood environment and walking in the neighborhood by U.S. adults. A random sample of women (n 266) and men (n 208) aged 18 years participated. Door-to-door interviews were conducted in 2003 to collect information about demographics, walking behavior, and features of the neighborhood environment. The analyses conducted in 2004 revealed that women were more likely to walk for exercise (odds ratio [OR] 4.6, 95% confidence interval [CI] ) or walk a dog (OR 3.3, 95% CI ) in the neighborhood if neighborhood safety was average as opposed to below average (p 0.05). Women with an average number of neighborhood destinations were more likely to walk for transportation in the neighborhood (OR 5.7, 95% CI ) than women with a below average number of neighborhood destinations (p 0.01). In men, none of the neighborhood features were significantly associated with walking for exercise or walking a dog. Men were less likely to walk for transportation in the neighborhood if the functional (OR 0.22, 95% CI ) or aesthetic (OR 0.17, 95% CI ) features of the neighborhood were average versus below average. Prospective studies are needed to determine if changes in neighborhood safety and awareness of neighborhood destinations promote increases in walking by women. Evaluations of the relationships between other environmental features and walking behavior in men are warranted. (Am J Prev Med 2005;28(2): ) 2005 American Journal of Preventive Medicine Introduction Despite extensive documentation of the health benefits of regular physical activity, a large segment of the U.S. population is not physically active. 1,2 In the early 1990s, the prevalence of adults not participating in any leisure-time physical activity was about 31%. 3 The revision of physical activity guidelines to include moderate-intensity activities did not have a substantial impact on physical activity participation. 4 The most recent estimates indicate that 38% of U.S. adults do not participate in enough physical activity to meet recommended guidelines, 16% are inactive, and nearly 25% do not participate in any leisure-time physical activity. 2 From the School of Physical Activity and Educational Services, Ohio State University (Suminski, Petosa, Stevens, Katzenmoyer), Columbus, Ohio; and Health Research Group, University of Missouri-Kansas City (Poston), and Mid-America Heart Institute (Poston), Kansas City, Missouri Address correspondence and reprint requests to: Richard R. Suminski, School of Physical Activity and Educational Resources, Ohio State University, 344 Larkins, Columbus OH suminski.1@osu.edu. The full text of this article is available via AJPM Online at Theoretical models are useful for improving our understanding of human behaviors. Social ecologic models recognize that behavior is influenced by the reciprocal and dynamic interactions that occur among intrapersonal, social environment, physical environment, and public policy variables. 5 Recently, researchers have begun to examine features of the physical environment and their relationships with physical activity. Significant associations have been found between physical activity and exercise equipment in the home, neighborhood aesthetics, convenient facilities for physical activity, and proximity of retail shops. 6 9 Improving the conditions of environmental features may be a viable and effective method for promoting increases in physical activity. Positive changes in neighborhood aesthetics, and improvements in convenience have been shown to result in substantial (twofold) increases in physical activity. 10 In the United States, walking for exercise is the most frequently reported activity among adults. 2 Walking is a moderate-intensity activity that can promote improvements in aerobic fitness, body composition, and lipid profiles (low-density lipoprotein cholesterol and total cholesterol/high-density lipoprotein cholesterol). 11,12 Am J Prev Med 2005;28(2) /05/$ see front matter 2005 American Journal of Preventive Medicine Published by Elsevier Inc. doi: /j.amepre

2 Findings from cross-sectional and longitudinal investigations suggest that features of the physical environment are related to walking. 10,13,14 The relationship appears to be mediated by the reasons for the walk. Humpel et al. 15 found that walking for exercise was associated with aesthetic appeal, while walking for pleasure increased as the accessibility of places increased. Because of the widespread acceptability of walking and the health benefits associated with this activity, research efforts aimed at elucidating factors that influence walking are warranted. Focusing on features of the physical environment is appealing from the standpoint that interventions that attempt to change the physical environment for the purpose of promoting increases in physical activity have the potential to impact a substantial proportion of the population. To date, most studies examining the relationship between features of the physical environment and walking for different reasons in the neighborhood have been conducted in non-u.s. populations. This study tested the hypothesis that features of the neighborhood environment are associated with different forms of walking in the neighborhood in a sample of U.S. adults. This hypothesis was examined for women and men, separately, an approach suggested by previous research. 15 Methods Participants and Design Sampling procedure. A random sample of 1200 addresses was generated from county auditor records. All addresses were located within the boundaries of a large, Midwestern metropolitan area. Trained interviewers visited each of the 1200 addresses in order to complete a survey with one eligible participant at each address. To be eligible for the study, a participant had to be a resident of the neighborhood where the interview was taking place, aged 18 years, and not limited in their ability to be physically active because of a health condition. Of the 1200 addresses visited, an individual answered the door 68% (n 818) of the time. Forty-one percent refused (n 335); 14% were not eligible (n 68); and 45% (n 415) completed an interview. All participants signed an informed consent form before being interviewed. The research protocol was approved by the Ohio State University s human participants protection committee. Residential survey procedure. Trained interviewers completed face-to-face, door-to-door interviews over a 13-day period in July Once an eligible resident consented to being a participant in the study, they were given a binder containing interview questions and definitions. For example, when asked about environmental features, participants were able to view a caption containing the interview question and verbal descriptors associated with the response scale. Similarly written definitions for each of the types of walking were provided in the binder. This written/verbal approach was used to increase comprehension among participants and maintain consistency across different interviewers. Interviews lasted an average 15 minutes, and all interviews initiated were completed. Measurements Physical activity. A reliable (correlation coefficient r 0.58) and valid (relationship with physical activity log; correlation coefficient r 0.71) questionnaire was used to assess walking behavior and other forms of physical activity. 16,17 From a list, participants selected all lifestyle (e.g., dog walking, walking for transportation, etc.) and exercise (e.g., walking for exercise) physical activities that they engaged in during the 7 days before the interview. They then indicated the frequency and duration of each physical activity. If a participant indicated walking for any reason, follow-up questions were used to determine if it was done in the participant s neighborhood. The walking variables examined in this study were walking for transportation, walking a dog, and walking for exercise. Two categories were created for each of these variables. One category consisted of participants who performed the activity in their neighborhood. The other category was comprised of participants who did not perform the activity and participants who performed the activity but not in their neighborhood. For the dog-walking variable, only participants who owned a dog were included in the analyses. Features of the physical environment. A ten-item questionnaire was developed in accordance with a previously proposed framework and approach for assessing features of the neighborhood environment. 15,18 A two-stage, expert panel review process was used to establish face and content validity for each item. In stage one, panel members reviewed each item and proposed appropriate revisions. During stage two, panel members reached consensus on proposed item revisions in order to maximize face and content validity. Intraclass correlations for the questionnaire ranged from 0.85 to 0.94, and the Cronbach s alpha coefficient of internal consistency was The ten items were associated with one of the four environmental features proposed by Pikora et al. 18 The first feature was labeled functional, and was represented by three items related to the construction/integrity of neighborhood sidewalks and streets. The second feature was termed safety and included four items associated with neighborhood traffic volume and speed, lighting, and crime. The third feature was called the aesthetic feature, and was described by two items about neighborhood cleanliness and views of buildings and scenery. The fourth feature was labeled destinations, and was described by one item that asked about the availability of places in and around the participant s neighborhood to which they could walk such as shops, parks, work, or schools (see Appendix). For each item, participants selected one number from a 10-point scale (1 10) that corresponded to the condition of the environmental feature. Verbal descriptors were used to describe a continuum on the scale ranging from the worst rating (1 on the scale) to the best rating (10 on the scale). The scores from each of the items were summed and divided by the number of items per feature to yield an average score for the feature. The average feature scores were transformed into categorical variables with three levels the lowest, middle, and highest tertiles for ratings of the feature using 150 American Journal of Preventive Medicine, Volume 28, Number 2

3 Table 1. Participants engaged in walking activity types by gender Women (n 266) Men (n 208) % engage in activity % engage in activity in neighborhood % engage in activity % engage in activity in neighborhood Transportation 51.9 (138/266) a 32.0 (85/266) b 57.2 (119/208) a 33.2 (69/208) b Dog walking 30.5 (81/266) a 60.0 (75/125) c 24.5 (51/208) a 53.3 (48/90) c Exercise 63.9* (170/266) a 52.6* (140/266) b 47.6 (99/208) a 38.5 (80/208) b a Participants engaged in activity/total participants. b Participants engaged in activity in the neighborhood versus those not engaged in activity plus those engaged in it but not in their neighborhood. c Participants who owned a dog and walked it in the neighborhood versus participants who owned a dog and either did not walk it or walked it but not in the neighborhood. *Significantly greater in women compared with men (p 0.005) (bolded). cut-points based on the tertiles of the distributions for each feature score. Demographic questions. The last part of the interview required participants to respond to questions about their health, ethnic background, educational attainment, age, dog ownership, and gender. Two demographic variables were dichotomized for the statistical analyses as follows: aged 18 to 37 years vs 37, and high school degree. Statistical Analyses Chi-square analyses were used to examine the relationships between neighborhood walking and gender. Binary logistic regression was employed to explore associations between neighborhood walking and features of the neighborhood environment while controlling for age and education. Three models were constructed for women and three for men. Walking for transportation was the dependent variable for the first model, walking a dog was the dependent variable for the second model, and walking for exercise was the dependent variable for the third model. The independent variables for all models were the four features of the neighborhood environment with the below-average group serving as the referent group. The level of significance was set at p 0.05; all analyses were conducted in Results The participants included 266 women (mean age 36.6 years, standard deviation [SD] 13.5) and 208 men (mean age 36.6, SD 15.7). A total of 56.9% had some college-level education. Most of the participants were Caucasian (89.7%), 1.7% Hispanic, 1.5% African American, and 1.3% Asian American. Shown in Table 1 are the percentages of women and men who engaged in a particular type of walking and the percentages that did the activity in the neighborhood, compared to those who did not do the activity plus those who did the activity but not in the neighborhood. Approximately 33% of the men and 32.0% of the women walked for transportation in the neighborhood. A total of 125 or 47% of the women and 90 (43.3%) of the men owned a dog. Over half of the women (60%) dog owners and 53.3% of the men dog owners walked a dog in their neighborhood. Women and men did not differ in walking for transportation or walking a dog. However, women were more likely to walk for exercise compared to men (63.9% vs 47.6%; ; p 0.005), and a larger percentage of women than men walked for exercise in the neighborhood (52.6% vs 38.5%; ; p 0.005). Presented in Table 2 are the median values and ranges for the four features of the physical environment. No significant differences were found between women and men for any of the environmental features. Interfeature correlation coefficients are also presented in Table 2. Similar patterns were seen in men and women. The functional, aesthetic, and destination subscale scores were Table 2. Descriptive statistics for environmental features Inter-item correlation coefficients Feature Median Range Functional Safety Aesthetic Women Functional Safety ** Aesthetic ** 0.08 Destination ** ** Men Functional Safety * Aesthetic ** 0.02 Destination ** ** *p 0.05 (bolded). **p (bolded). Am J Prev Med 2005;28(2) 151

4 Table 3. Odds of walking in neighborhood given conditions of neighborhood features (women) Exercise Dog walking Transportation Functional Lowest tertile (referent) (referent) (referent) Middle tertile 0.33 ( ) 0.56 ( ) 0.73 ( ) Highest tertile 0.37 ( ) 3.52 ( ) 1.28 ( ) Safety Lowest tertile (referent) (referent) (referent) Middle tertile 4.58 ( )* 3.33 ( )* 0.53 ( ) Highest tertile 0.33 ( ) 0.41 ( ) 2.12 ( ) Aesthetics Lowest tertile (referent) (referent) (referent) Middle tertile 0.29 ( ) 0.71 ( ) 0.66 ( ) Highest tertile 0.70 ( ) 0.30 ( ) 0.34 ( ) Destinations Lowest tertile (referent) (referent) (referent) Middle tertile 0.63 ( ) 0.46 ( ) 5.67 ( )** Highest tertile 3.25 ( ) 1.83 ( ) 1.48 ( ) Age 37 years (referent) (referent) (referent) years 2.19 ( ) 1.00 ( ) 1.68 ( ) Education High school degree (referent) (referent) (referent) Some college/college degree 0.82 ( ) 0.84 ( ) 0.80 ( ) CI, confidence interval; OR, odds ratio. *p 0.05 (bolded). **p 0.01 (bolded). significantly and positively associated with each other. The safety subscale score was positively associated with the function subscale score (p 0.05) but it was not related to the aesthetic and destination subscale scores (p 0.05). Depicted in Tables 3 (women) and 4 (men) are the results of the logistic regression analyses. Women were 4.5 times more likely to walk for exercise in their neighborhood if neighborhood safety was average compared to below average (p 0.05). Women also were more likely (threefold) to walk their dog if neighborhood safety was average versus below average (p 0.05). Women were 5.7 times more likely to walk for transportation in their neighborhood if they indicated having an average number of available places in and around their neighborhood to which they could walk (p 0.01). Environmental features were not associated with walking for exercise or walking a dog in men; however, inverse relationships between walking for transportation and environmental features were noted in men. Men who said that the functional and aesthetic features of their neighborhoods were average compared to below average were approximately 80% less likely to walk for transportation in their neighborhoods (p 0.05). Discussion This study examined associations between features of the neighborhood environment and different types of walking engaged in by U.S. adults in their neighbor- Table 4. Odds of walking in neighborhood given conditions of neighborhood features (men) Exercise Dog walking Transportation Functional Lowest tertile (referent) (referent) (referent) Middle tertile 0.28 ( ) 1.12 ( ) 0.22 ( )* Highest tertile 0.67 ( ) 1.81 ( ) 0.67 ( ) Safety Lowest tertile (referent) (referent) (referent) Middle tertile 5.90 ( ) 1.34 ( ) 0.64 ( ) Highest tertile 0.74 ( ) 2.80 ( ) 0.21 ( ) Aesthetics Lowest tertile (referent) (referent) (referent) Middle tertile 0.45 ( ) 0.77 ( ) 0.17 ( )* Highest tertile 7.79 ( ) 0.87 ( ) 3.34 ( ) Destinations Lowest tertile (referent) (referent) (referent) Middle tertile 1.09 ( ) 0.93 ( ) 2.73 ( ) Highest tertile 0.60 ( ) 5.19 ( ) 0.07 ( ) Age 37 years (referent) (referent) (referent) years 1.28 ( ) 1.18 ( ) 0.36 ( ) Education High school degree (referent) (referent) (referent) Some college/college degree 0.40 ( ) 1.50 ( ) 1.35 ( ) CI, confidence interval; OR, odds ratio. *p 0.05 (bolded). 152 American Journal of Preventive Medicine, Volume 28, Number 2

5 hoods. As reported in previous studies, 7,10,13,15 specific neighborhood features were related with different types of walking among women and men. For example, while the literature does not provide a clear picture concerning the impact of safety on physical activity, 15,19 21 neighborhood safety emerged as an important determinant of walking for exercise and dog walking in women, but not for men. Greater neighborhood safety (i.e., from low- to mid-tertile of perceived safety) resulted in a 4.5-fold and threefold increase in the odds of women who reported walking in their neighborhoods for exercise or walking the dog, respectively. Giles-Corti and Donovan 19 found that dog ownership resulted in a 58% increase in the odds of walking at recommended levels, but their analysis included both women and men. Finally, those reporting the highest tertile of safety scores were not more likely to walk for any reason than those in the lowest tertile, suggesting a potential threshold effect rather than a dose response relationship between safety perceptions and walking for exercise or dog walking. The results are somewhat consistent with those reported by Weinstein et al., 20 who found that women were more likely to report that poorer neighborhood safety influenced physical inactivity than men. In addition, there was not a dose response relationship between increasing levels of safety after neighborhoods were classified as quite safe. Humpel et al. 15 did not find a significant association or a dose response relationship between safety and being classified as high walkers among women. This inconsistency may be due to a number of factors, including different methods for measuring safety, different outcomes (e.g., physical inactivity vs walking for various purposes) and sample differences. Women with more destinations to walk to in their neighborhoods, which was conceived of as a dimension of accessibility or convenience, were over 5.5 times more likely to walk for transportation than women with fewer destinations. King et al. 14 found that women who had more places within a convenient walking distance ( 20 minutes) achieved higher pedometer readings than women with fewer places. Women also have been shown to be more likely to walk for transportation if they perceive the walk as easy. 22 Thus, while several studies found relationships between accessibility, ease, or convenience, and walking for exercise 7 and regular physical activity in general, 13 no relationship for women or men was found between accessibility and walking for transportation by Humpel et al. 15 However, women were three times more likely to walk for pleasure with moderate accessibility, but high accessibility did not result in even greater odds of walking for pleasure. Men were significantly less likely to walk in their neighborhood (odds ratio 0.30) if they reported it as highly accessible. Men living in neighborhoods rated in the middle tertile of functional and aesthetic features were less likely to walk for transportation in the neighborhood than men living in neighborhoods where these features rated in the lowest tertile. In contrast, Saelens et al. 23 found that a neighborhood classified as walkable had significantly higher aesthetic scores than a neighborhood classified as being less walkable. In addition, Humpel et al. 15 found that high aesthetic environments were positively associated with both neighborhood exercise walking, but found no relationship between walking for pleasure or transportation. Thus, these results are at odds with those reported in previous studies. As noted previously, this inconsistency may be due to a number of factors, including different methods for measuring safety, different outcomes (e.g., physical inactivity vs walking for different purposes), and sample differences. The results of this study must be considered in the context of several limitations. The measure of walking was based on participant recall, which is susceptible to reporting bias. However, participants provided detailed descriptions of their walking behavior, including the reason for the walk, the behavior setting where the walk primarily occurred, and information about the physical condition of the behavior setting and the interview format used to obtain information has been shown to improve approximations of physical activity. 24,25 The measure of the perceived environment also was subject to biases inherent to measures of individual s perceptions, that is, recall of certain environmental features (e.g., presence of convenient exercise facilities) often does not accurately reflect the actual state of affairs as determined using objective methods. 26 Although objective measures would provide additional insight into the relation between environmental features and walking, an individual s perceptions may be just as important for defining their behavior. In addition, the measure was based on a strong conceptual framework, 18 and demonstrated good reliability and content validity. Thus, this study allowed for an in-depth examination of the environment physical activity relationship, an approach that has been strongly recommended. 5,15 Next, the 95% confidence intervals for many of the odds ratios were quite large, suggesting that the estimates are somewhat imprecise. Finally, the cross-sectional study design does not allow for inferences to be made regarding causal effects. The design does provide a basis for hypothesis formation and rationales for longitudinal studies. In conclusion, some features of the neighborhood environment were positively associated with walking for exercise, walking a dog, and walking for transportation in the neighborhood, especially for women. Health practitioners and researchers are encouraged to use the present approach in order to (1) identifying modifiable environmental characteristics that affect physical activity, and (2) plan health promotion strategies for increasing physical activity. For example, efforts to impact neighborhood safety might involve educating residents concerning safety issues, developing safe areas or routes for physical activity, Am J Prev Med 2005;28(2) 153

6 What This Study Adds... Improving environmental conditions could substantially impact walking, the most common form of physical activity among U.S. adults. This study found neighborhood safety to be an important determinant of walking. Women in safer neighborhoods were over four times more likely to walk in their neighborhoods than women in less safe neighborhoods. Health practitioners are encouraged to use our approach to identify modifiable environmental characteristics affecting physical activity and plan health promotion strategies for increasing physical activity. and/or targeting local policies in order to change mechanisms that impact safety. Determining the cost-to-benefit ratio associated with these efforts is a priority for future research. The degree to which walking for transportation can be modified is not known. Walking for transportation could be enhanced by increasing awareness about existing neighborhood destinations, at least potentially for women. This could be accomplished by using reference signage, improving the conditions of neighborhood destinations, developing walking maps that highlight neighborhood destinations, or by providing services that reduce the burden on the walker (free delivery of goods from stores) after purchase. The results also suggest caution with respect to altering physical environments. For example, enhancing the aesthetics or functionality of environments is viewed as an easily implemented intervention, but as the data show, neither are related with walking for any reason, and results of other studies have been mixed. 7,15 However, one longitudinal study found that increases in participants perceptions of aesthetics were related to increases in walking in men. 10 Thus, use of similar outcomes and more coherent and theoretically based methods for measuring perceived environmental features are needed. Prospective studies also are warranted to assess how alterations in neighborhood safety and/or the proximity/ appeal of neighborhood destinations impacts different types of walking. Investigations are also needed to determine the amount of change needed in environmental features to produce optimal changes in walking. Funding for this study was provided by the Centers for Disease Control and Prevention (RO6/CCR521805). No financial conflict of interest was reported by the authors of this paper. References 1. U.S. Department of Health and Human Services. Physical activity and health: a report of the Surgeon General. Atlanta GA: U.S. Department of Health and Human Services. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, National Center for Health Statistics. Early release of selected estimates based on data from the National Health Interview Survey, April Available at: Accessed March Centers for Disease Control and Prevention. Physical activity trends United States, MMWR Morb Mortal Wkly Rep 2001;50: Pate RR, Pratt M, Blair SN, et al. ACSM guidelines for exercise. Physical activity and public health a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995;273: Sallis JF, Bauman A, Pratt M. Environmental and policy interventions to promote physical activity. Am J Prev Med 1998;15: Jakicic JM, Wing RR, Butler BA, Jeffery RW. The relationship between presence of exercise equipment in the home and physical activity level. Am J Health Promotion 1997;11: Ball K, Bauman A, Leslie E, Owen N. Perceived environmental aesthetics and convenience and company are associated with walking for exercise among Australian adults. Prev Med 2001;33: Sallis JF, Hovell MF, Hofstetter CR, et al. A multivariate study of determinants of vigorous exercise in a community sample. Prev Med 1989;18: Frank LD, Pivo G. Impacts of mixed use and density on utilization of three modes of travel: single-occupant vehicle, transit, and walking. Transportation Res Rec 1995;1466: Humpel N, Marshall AL, Leslie E, Bauman A, Owen N. Changes in neighborhood walking are related to changes in perceptions of environmental attributes. Ann Behav Med 2004:27: Kelley GA, Kelley KS, Tran ZV. Walking, lipids, and lipoproteins: a metaanalysis of randomized controlled trials. Prev Med 2004;38: Asikainen TM, Miilunpalo S, Oja P, et al. Randomised, controlled walking trials in postmenopausal women: the minimum dose to improve aerobic fitness? Br J Sports Med 2002;36: Powell KE, Martin LM, Chowdhury PP. Places to walk: convenience and regular physical activity. Am J Public Health 2003;93: King WC, Brach JS, Belle S, Killingsworth R, Fenton M, Kriska AM. The relationship between convenience of destinations and walking levels in older women. Am J Health Promotion 2003;18: Humpel N, Owen N, Iverson D, Leslie E, Bauman A. Perceived environment attributes, participantial location, and walking for particular purposes. Am J Prev Med 2004;26: Taylor HL, Jacobs DR, Schucker-Knudsen BJ, Leon AS, DeBacker G. A questionnaire for the assessment of leisure time physical activities. J Chronic Dis 1978;31: Dishman RK, Steinhardt M. Reliability and concurrent validity for a 7-d recall of physical activity in college students. Med Sci Sports Exerc 1988;20: Pikora T, Giles-Corti B, Bull F, Jamrozik K, Donovan R. Developing a framework for assessment of the environmental determinants of walking and cycling. Soc Sci Med 2003;56: Giles-Corti B, Donovan RJ. Relative influence of individual, social environmental, and physical environmental correlates of walking. Am J Public Health 2003;93: Weinstein A, Feigley P, Pullen P, Mann L, Redman L. Neighborhood safety and the prevalence of physical activity-selected states, MMWR Morb Mortal Wkly Rep 1999;48: King AC, Castro C, Wilcox S, Eyler AA, Sallis JF, Brownson RC. Personal and environmental factors associated with physical inactivity among different racial-ethnic groups of U.S. middle-aged and older-aged women. Health Psychol 2000;19: Bourdeaudhuij ID, Sallis JF, Saelens BE. Environmental correlates of physical activity in a sample of Belgian adults. Am J Health Promotion 2003;18: Saelens BE, Sallis JF, Black JB, Chen D. Neighborhood-based differences in physical activity: an environmental scale evaluation. Am J Public Health 2003;93: Timperio A, Salmon J, Crawford D. Validity and reliability of a physical activity recall instrument among overweight and non-overweight men and women. J Sci Med Sport 2003;6: Melanson EL, Freedson PS. Physical activity assessment: a review of methods. Crit Rev Food Sci Nutr 1996;36: Sallis JF, Hovell MF, Hofstetter CR, et al. Distance between homes and exercise facilities related to the frequency of exercise among San Diego participants. Public Health Rep 1990;105: American Journal of Preventive Medicine, Volume 28, Number 2

7 Appendix Features and related items with response scales Am J Prev Med 2005;28(2) 155

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