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Epidemiology and Population Health

Neighborhood racial/ethnic segregation and BMI: A longitudinal analysis of the Multi-ethnic Study of Atherosclerosis

International Journal of Obesity volume 43, pages 1601–1610 (2019)Cite this article

Subjects

Abstract

Background

Current knowledge regarding the relationship between segregation and body weight is derived mainly from cross-sectional data. Longitudinal studies are needed to provide stronger causal inference.

Methods

We use longitudinal data from the Multi-Ethnic Study of Atherosclerosis and apply an econometric fixed-effect strategy, which accounts for all time-invariant confounders, and compare results to conventional cross-sectional analyses. We examine the relationship between neighborhood-level racial/ethnic segregation, neighborhood poverty, and body mass index (BMI) separately for blacks, Hispanics, and whites. Segregation*gender interactions are included in all models. Neighborhood segregation was operationalized by the local Gi* statistic, which assesses the extent to which a neighborhood’s racial/ethnic composition is under (Gi* statistic < 0) or over (Gi* statistic > 0) represented, given the composition in the broader (e.g., county) area. For black, Hispanic, and white stratified models, the Gi* statistic reflects the level of black, Hispanic, and white segregation, respectively. The Gi* statistic was scaled such that a unit change represents a 1.96 difference in the score.

Results

Cross-sectional models indicated higher segregation to be negatively associated with BMI for white females and positively associated for Hispanic females. No association was found for black females or males in general. In contrast, fixed-effect models adjusting for neighborhood poverty, higher segregation was positively associated with BMI for black females (coeff = 0.25 kg/m2; 95% CI = [0.03, 0.46]; p-value = 0.03) but negatively associated for Hispanic females (coeff = −0.17 kg/m2; 95% CI = [−0.33, −0.01]; p-value  = 0.04) and Hispanic males (coeff = −0.20; 95% CI = [−0.39, −0.01]; p-value = 0.04). Further controls for socioeconomic factors fully explained the associations for Hispanics but not for black females.

Conclusions

Fixed-effect results suggest that segregation’s impacts might not be universally harmful, with possible null or beneficial impacts, depending on race/ethnicity. The persistent associations after accounting for neighborhood poverty indicate that the segregation–BMI link may operate through different pathways other than neighborhood poverty.

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References

  1. National Institute of Diabetes and Digestive and Kidney Diseases. Overweight and obesity statistics. NIH Publication no. 04-4158; 2012.

  2. Ogden CL, Carroll MD, Fryar CD, et al. Prevalence of obesity among adults and youth: United States, 2011–2014. NCHS Data Brief. Hyattsville, MD: National Center for Health Statistics; 2015.

    Google Scholar 

  3. Rogers RG, Hummer RA, Krueger PM. The effect of obesity on overall, circulatory disease- and diabetes-specific mortality. J Biosoc Sci. 2003;35:107–29.

    Article  Google Scholar 

  4. Pan L, Galuska DA, Sherry B, et al. Differences in prevalence of obesity among black, white, and Hispanic adults—United States, 2006–2008. Morb Mortal Wkly Rep. 2009;58:740–4.

  5. Bruce MA, Sims M, Miller S, et al. One size fits all? Race, gender and body mass index among US adults. J Natl Med Assoc. 2007;99:1152.

    PubMed  PubMed Central  Google Scholar 

  6. Robert SA, Reither EN. A multilevel analysis of race, community disadvantage, and body mass index among adults in the US. Soc Sci Med. 2004;59:2421–34.

    Article  Google Scholar 

  7. Kramer MR, Hogue CR. Is segregation bad for your health? Epidemiol Rev. 2009;31:178–94.

    Article  Google Scholar 

  8. Kershaw KN, Diez Roux AV, Burgard SA, et al. Metropolitan-level racial residential segregation and black-white disparities in hypertension. Am J Epidemiol. 2011;174:537–45.

    Article  Google Scholar 

  9. Kershaw KN, Osypuk TL, Do DP, et al. Neighborhood-level racial/ethnic residential segregation and incident cardiovascular disease: The Multi-Ethnic Study of Atherosclerosis. Circulation. 2015;131:141.

    Article  Google Scholar 

  10. Chang VW. Racial residential segregation and weight status among US adults. Soc Sci Med. 2006;63:1289–303.

    Article  Google Scholar 

  11. Chang VW, Hillier AE, Mehta NK. Neighborhood racial isolation, disorder and obesity. Soc Forces. 2009;87:2063–92.

    Article  Google Scholar 

  12. Do DP, Dubowitz T, Bird CE, et al. Neighborhood context and ethnicity differences in body mass index: a multilevel analysis using the NHANES III survey (1988–1994). Econ Hum Biol. 2007;5:179–203.

    Article  Google Scholar 

  13. Mobley LR, Root ED, Finkelstein EA, et al. Environment, obesity, and cardiovascular disease risk in low-income women. Am J Prev Med. 2006;30:327–32.

    Article  Google Scholar 

  14. Osypuk TL, Diez Roux AV, Hadley C, et al. Are immigrant enclaves healthy places to live? The Multi-ethnic Study of Atherosclerosis. Soc Sci Med. 2009;69:110–20.

    Article  Google Scholar 

  15. Portes A, Shafer S. Revisiting the enclave hypothesis: Miami twenty-five years later. Res Sociol Organ. 2007;25:157–90.

    Article  Google Scholar 

  16. Portes A, Rumbaut RG. Immigrant America: a portrait. 3rd ed. Berkeley, CA: University of California Press; 2006.

    Google Scholar 

  17. Logan J. Separate and unequal: The neighborhood gap for blacks and Hispanics in metropolitan America. US2010 Project Discover America in a new century; 2011.

  18. Kirby JB, Liang L, Chen H-J, et al. Race, place, and obesity: the complex relationships among community racial/ethnic composition, individual race/ethnicity, and obesity in the United States. Am J Public Health. 2012;102:1572–8.

    Article  Google Scholar 

  19. Wen M, Maloney TN. Latino residential isolation and the risk of obesity in Utah: the role of neighborhood socioeconomic, built-environmental, and subcultural context. J Immigr Minor Health. 2011;13:1134–41.

    Article  Google Scholar 

  20. U.S. Census Bureau. Quick facts: Detroit city, Michigan. 2016. http://www.census.gov/quickfacts/table/PST045215/2622000. Accessed 8 Sept 2016.

  21. U.S. Census Bureau. Quick facts: United States. 2016. http://www.census.gov/quickfacts/table/PST045215/00. Accessed 8 Sept 2016.

  22. Kershaw KN, Albrecht SS, Carnethon MR. Racial and ethnic residential segregation, the neighborhood socioeconomic environment, and obesity among Blacks and Mexican Americans. Am J Epidemiol. 2013;177:299–309.

    Article  Google Scholar 

  23. Massey D, Denton N. American apartheid: segregation and the making of the underclass. Cambridge: Harvard University Press; 1993.

    Google Scholar 

  24. Do DP, Frank R, Iceland J. Black-white metropolitan segregation and self-rated health: investigating the role of neighborhood poverty. Soc Sci Med. 2017;187:85–92.

    Article  Google Scholar 

  25. Morland K, Wing S, Diez Roux A, et al. Neighborhood characteristics associated with the location of food stores and food service places. Am J Prev Med. 2002;22:23–9.

    Article  Google Scholar 

  26. Zenk SN, Schulz AJ, Israel BA, et al. Neighborhood racial composition, neighborhood poverty, and the spatial accessibility of supermarkets in metropolitan Detroit. Am J Public Health. 2005;95:660–7.

    Article  Google Scholar 

  27. Larson NI, Story MT, Nelson MC. Neighborhood environments: disparities in access to healthy foods in the U.S. Am J Prev Med. 2009;36:74–81.

    Article  Google Scholar 

  28. Lovasi GS, Hutson MA, Guerra M, et al. Built environments and obesity in disadvantaged populations. Epidemiol Rev. 2009;31:7–20.

    Article  Google Scholar 

  29. Tucker-Seeley RD, Subramanian SV, Li Y, et al. Neighborhood safety, socioeconomic status, and physical activity in older adults. Am J Prev Med. 2009;37:207–13.

    Article  Google Scholar 

  30. Getis A, Ord JK. The analysis of spatial association by use of distance statistics. Geogr Anal. 1992;24:189–206.

    Article  Google Scholar 

  31. Auchincloss AH, Diez Roux AV, Brown DG, et al. Association of insulin resistance with distance to wealthy areas: The Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 2007;165:389–97.

    Article  Google Scholar 

  32. Hajat A, Diez-Roux A, Franklin TG, et al. Socioeconomic and race/ethnic differences in daily salivary cortisol profiles: The Multi-Ethnic Study of Atherosclerosis. Psychoneuroendocrinology 2010;35:932–43.

  33. Allison P. Fixed effects regression models. Los Angeles: Sage; 2009.

    Book  Google Scholar 

  34. Vaisey S, Miles A. What You can—and can’t—do with three-wave panel data. Sociol Methods Res. 2014;46:44–67.

    Article  Google Scholar 

  35. Wooldridge JM. Introductory econometrics: a modern approach. 5th ed. South-Western: Cengage Learning; 2013.

  36. Pool LR, Carnethon MR, Goff DCJ, et al. Longitudinal associations of neighborhood-level racial residential segregation with obesity among Blacks. Epidemiology. 2018;29:207–14.

    Article  Google Scholar 

  37. Mackenbach JD, Rutter H, Compernolle S, et al. Obesogenic environments: a systematic review of the association between the physical environment and adult weight status, the SPOTLIGHT project. BMC Public Health. 2014;14:233.

    Article  Google Scholar 

  38. Salas-Wright CP, Robles EH, Vaughn MG, et al. Toward a typology of acculturative stress: results among Hispanic immigrants in the United States. Hisp J Behav Sci. 2015;37:223–42.

    Article  Google Scholar 

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Funding

This research was supported by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169 from the National Heart, Lung, and Blood Institute, by grants UL1-TR-000040 and UL1-TR-001079 from NCRR, by grant R01 HL071759 from National Heart, Lung, and Blood Institute at the National Institutes of Health, and by grant P60 MD002249 from National Institute of Minority Health and Health Disparities. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Authors and Affiliations

  1. Zilber School of Public Health, University of Wisconsin-Milwaukee, 1240 N 10th St, Milwaukee, WI, 53205, USA

    D. Phuong Do

  2. Department of Epidemiology & Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA

    Kari Moore, Sharrelle Barber & Ana Diez Roux

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Correspondence to D. Phuong Do.

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Do, D.P., Moore, K., Barber, S. et al. Neighborhood racial/ethnic segregation and BMI: A longitudinal analysis of the Multi-ethnic Study of Atherosclerosis. Int J Obes 43, 1601–1610 (2019). https://doi.org/10.1038/s41366-019-0322-3

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