Larkin L. Strong, PhD Lorraine R. Reitzel , PhD University of Texas MD Anderson Cancer Center Department of Health D

1. Neighborhood matters: How characteristics of the residential environment relate to physical activity, sedentary behavior, and body mass index among African American adults Larkin L. Strong, PhD Lorraine R. Reitzel, PhD University of Texas MD Anderson Cancer Center Department of Health Disparities Research

2. Agenda • Brief overview and study sample • A tale of two studies • Study 1: Associations of perceived neighborhood physical and social environments with physical activity and television viewing in African American men and women • Study 2: Density and proximity of fast food restaurants and body mass index among African Americans

3. Brief Overview • Growing interest in how neighborhood factors influence health and health behaviors over and above individual-level factors • Very little research has focused on African American populations in this regard • African Americans at particular risk of health disparities • More understanding is needed to inform policy and interventions to affect these disparities

4. Study Sample • Project CHURCH • Creating a Higher Understanding of cancer Research and Community Health • Designed to assess behavioral, social, and environmental cancer risk factors in 1,501 African American adults • Cross-sectional analysis of self-reported baseline data collected in 2008-2009 • Setting • Large mega-church in Houston, TX • Sampling Protocols • Participants recruited through church media channels • Inclusion: >age 18; residence in Houston area; functional telephone number; must attend church

5. Study 1 Strong LL, Reitzel LR, Wetter DW, McNeill LH American Journal of Health Promotion. 2013;27(6):401-9.

6. Introduction Moderate-to-Vigorous Physical Activity (PA) • Most adults in the US • Are not physically active • Spend over 50% of their waking time in sedentary behaviors • Some racial/ethnic groups are disproportionately affected CDC BRFSS, 2011 TVViewing The Nielsen Company, 2011

7. The Role of the Environment • Strong evidence that characteristics of the built environment are associated with PA • What about sedentary behavior? • What about the role of the neighborhood social environment?

8. Study Purpose • To investigate the associations of perceived aspects of neighborhood social and physical environments with PA and TV viewing in a large, church-based sample of African American men and women

9. Methodology (cont’d) • Measures • Outcomes • Meeting PA guidelines (International Physical Activity Questionnaire; yes/no) • Average TV viewing time per day (log-transformed) • Neighborhood Perceptions • Social Cohesion and Trust (Sampson et al., 1997) • Neighborhood Problems (Steptoe & Feldman, 2001) • Analysis • Multivariate generalized estimating equations • Stratified by gender • Controlled for sociodemographics

10. Results: Participant Characteristics N= 1,374 • Age = 45.5 (12.6) • 76% female • 50% <Bachelor’s degree • 45% married/living with partner • 25% unemployed • 25% <$40,000 annual income • BMI = 31.7 (7.2) • 29.8% overweight, 53.9% obese

11. Results: Neighborhood Problems aConditions dichotomized to represent “some problem/serious problem” and “not a problem”

12. Results: Associations between Neighborhood Perceptions and Behaviors Models adjusted for sociodemographics (age, education, income, employment, marital status, presence of children in home, number of years in neighborhood) *p<0.01

13. Predicted Outcomes Predicted Mean Daily TV Viewing Predicted Probabilities of Meeting PA Guidelines

14. Results: Associations between Specific Conditions and Behaviors Models adjusted for sociodemographics (age, education, income, employment, marital status, presence of children in home, number of years in neighborhood) aConditions dichotomized to represent “some problem/serious problem” and “not a problem” *p<0.05 **p<0.01

15. Limitations • Cross-sectional data • Self-report • Recall, social desirability bias, e.g. IPAQ • Neighborhood data are subjective, may not represent actual conditions • Convenience sample of church-based African American adults • May not be generalizable

16. Conclusions • Among the first studies to suggest that social and physical aspects of neighborhood environments may affect sedentary in addition to active behaviors • Social cohesion was positively associated with PA, although only significant in women • Perceiving greater disorder within neighborhood was associated with increased TV viewing in women • Identified specific neighborhood conditions associated with PA in men and TV viewing in women

17. Implications • Important to consider neighborhood social characteristics and the design and conditions of physical environment for intervention/policy efforts • Intervention strategy – facilitate positive interactions among residents while also promoting healthy behaviors • Additional research is needed to understand the mechanisms through which neighborhood attributes affect behavior

18. Study 2 Reitzel LR, Regan SD, Nguyen N, Cromley EK, Strong LL, Wetter DW, McNeill LH American Journal of Public Health. Published online ahead of print May 16, 2013: e1-e7. doi:10.2105/AJPH.2012.301140

19. Background • Racial/ethnic disparities in obesity prevalence • 38.8% African American vs 36.2% White men • 58.5% African American vs 32.2% White women • BMI gap is widening too • African American neighborhoods have higher density of FFRs than White neighborhoods • Studies suggest FFR availability and FF consumption stronger among non-Whites than Whites • African Americans may be more likely to consume FF if available, and it is more likely to be available

20. The Current Study • Recent study examined FFR density and BMI among 4500 African Americans from Jackson • Null relations • Other studies in area, mixed results overall • No previous studies have looked at FFR proximity among African Americans and relations with BMI • No previous studies have examined income as a moderator, despite that reasons for frequent FF consumption = accessibility and affordability • Current study was meant to redress these gaps

21. Methodology • Obtained FFR addresses from InfoUSA • FFRs = limited service restaurants, hamburger/ hotdog establishments • Geocoded residential addresses of study sample and FFR addresses • Calculated FFR density at 0.5, 1, 2, and 5 miles around participant’s homes • Calculated proximity to closest FFR from the home • BMI – calculated from height/weight measured twice by stadiometer/scale

22. Fast Food Restaurants

23. Variable of Interest -Density Fast Food Restaurants 1 mile Density Buffer* Participant’s Home * Note: Density Buffer s were calculated at .05, 1, 2, and 5 miles for this study. 1 mile buffer presented as an example.

24. Variable of Interest - Proximity Fast Food Restaurants Proximity to Closest Fast Food Restaurant Participant’s Home

25. Statistical Approach • Adjusted generalized linear regression models, without and later with interaction term (income) • Analyses controlled for: • sociodemographics: age, gender, partner status, total annual household income, educational level, and employment status • tenure in years at the reported home address • presence of children in the home • physical activity level • television viewing time • neighborhood median household income

26. Results: FFR Density & BMI • Mean # of FFRs • 2.5 (1.9) in .5 mile buffer; 4.5 (4.2) in 1 mile buffer; 11.4 (9.8) in 2 mile buffer; 71.3 (50.4) in 5 mile buffer • Main effects were non-significant • Significant interaction terms at 0.5, 1, & 2 miles • Stratified analyses: density = BMI for participants earning <$40,000/year • 0.5 mile buffer (b = 1.15; p= .009) • 1 mile buffer (b = 1.23; p=.008) • 2 mile buffer (b = 1.69; p=.025)

27. Figure 1: Adjusted relations of FFR density within a .5 mile buffer and predicted BMI by income higher density values = greater density

28. Results: FFR Proximity & BMI • Mean FFR Proximity = 1.01 miles (.77) • Lower income participants were more likely to live closer to FFR than higher income participants • Main effects: closer proximity = BMI (b= 0.98; p< .001) • Significant interaction term (p = .029) • Stratified analyses: closer proximity = BMI for both income groups • <$40,000/year (b= 0.92; p=.013) • >$40,000/year (b= 0.99; p=.014) • Every mile closer to a FFR = 2.4% higher BMI

29. Figure 1: Adjusted relations of FFR proximity and predicted BMI by income higher proximity values = greater distance

30. Implications • Why links between FFR density and BMI among lower income participants? • More affordable? More convenient? More exposure (cueing)? Places for socialization? Transportation issues? • Why links between FFR proximity and BMI? • Only need 1 to purchase FF? Ease and convenience? Cueing? Transportation? • Utility of zoning laws or conditional use permits to regulate locations and numbers of FFRs around residential areas

31. Limitations • Cross-sectional • Need to assess consumption frequency and consumption choices • Need to understand entire food landscape • No information on disposable income • No information in FFR locations around other locations of importance (e.g., work) • Sample was mostly female, well-educated, church-going, metropolitan/urban

32. Research Support • The University Cancer Foundation • The Duncan Family Institute • The Ms. Regina J. Rogers Gift: Health Disparities Research Program • The Cullen Trust for Health Care Endowed Chair Funds for Health Disparities Research • The Morgan Foundation Funds for Health Disparities Research and Educational Programs • The National Cancer Institute through The University of Texas MD Anderson's Cancer Center Support Grant (grant number CA016672)