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Epidemiology and Population Health

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain

International Journal of Obesity volume 45, pages 1914–1924 (2021)Cite this article

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Abstract

Objective

To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults.

Methods

Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18–64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values.

Results

Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg.

Conclusions

Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

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Fig. 1: Patient analytic sample exclusion/inclusion decision flow diagram.
Fig. 2: Mean difference in weight at baseline comparing the first and third tertiles of built environment characteristics at different buffer sizes, after adjusting for baseline demographics, height, and year-specific patient property values.

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References

  1. Drewnowski A, Buszkiewicz J, Aggarwal A, Rose C, Gupta S, Bradshaw A. Obesity and the built environment: a reappraisal. Obesity. 2020;28:22–30.

    Article  PubMed  Google Scholar 

  2. Parise I. The built environment and obesity: you are where you live. Aust J Gen Pract. 2020;49:226–30.

    Article  PubMed  Google Scholar 

  3. Congdon P. Obesity and urban environments. Int J Environ Res Public Health. 2019;16:464. https://doi.org/10.3390/ijerph16030464.

    Article  PubMed Central  Google Scholar 

  4. Garfinkel-Castro A, Kim K, Hamidi S, Ewing R. Obesity and the built environment at different urban scales: examining the literature. Nutr Rev. 2017;75:51–61.

    Article  PubMed  Google Scholar 

  5. Wilkins E, Radley D, Morris M, Hobbs M, Christensen A, Marwa WL, et al. A systematic review employing the GeoFERN framework to examine methods, reporting quality and associations between the retail food environment and obesity. Health Place. 2019;57:186–99. https://doi.org/10.1016/j.healthplace.2019.02.007.

  6. Mooney SJ, Hurvitz PM, Moudon AV, Zhou C, Dalmat R, Saelens BE. Residential neighborhood features associated with objectively measured walking near home: revisiting walkability using the Automatic Context Measurement Tool (ACMT). Health Place. 2020;63. https://doi.org/10.1016/j.healthplace.2020.102332. Published online ahead of print.

  7. Smith M, Hosking J, Woodward A, Witten K, MacMillan A, Field A, et al. Systematic literature review of built environment effects on physical activity and active transport-an update and new findings on health equity. Int J Behav Nutr Phys Act. 2017;14:158. https://doi.org/10.1186/s12966-017-0613-9.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Lake A, Townshend T, Burgoine T, Buttriss J, Welch A, Kearney J, et al. Obesogenic neighbourhood food environments. In: Buttriss J, Welch A, Kearney JM, Lanham-New SA, editors. Public Health Nutrition (The Nutrition Society Textbook) 2nd edn. Wiley-Blackwell, 2017. p. 327–38.

  9. Devarajan R, Prabhakaran D, Goenka S. Built environment for physical activity—an urban barometer, surveillance, and monitoring. Obes Rev. 2020;21. https://doi.org/10.1111/obr.12938. Published online ahead of print.

  10. McCormack G, Blackstaffe A, Nettel-Aguirre A, Csizmadi I, Sandalack B, Uribe F, et al. The Independent Associations between Walk Score® and Neighborhood Socioeconomic Status, Waist Circumference, Waist-To-Hip Ratio and Body Mass Index Among Urban Adults. Int J Environ Res Public Health. 2018;15:1226.

    Article  PubMed Central  Google Scholar 

  11. Kowaleski-Jones L, Zick C, Smith KR, Brown B, Hanson H, Fan J. Walkable neighborhoods and obesity: Evaluating effects with a propensity score approach. SSM Popul Health. 2018;6:9–15.

    Article  PubMed  Google Scholar 

  12. Hobbs M, Griffiths C, Green MA, Jordan H, Saunders J, McKenna J. Neighbourhood typologies and associations with body mass index and obesity: a cross-sectional study. Prev Med (Baltim). 2018;111:351–7.

    Article  CAS  Google Scholar 

  13. Salvo G, Lashewicz B, Doyle-Baker P, McCormack G. Neighbourhood built environment influences on physical activity among adults: a systematized review of qualitative evidence. Int J Environ Res Public Health. 2018;15:897.

    Article  PubMed Central  Google Scholar 

  14. Bancroft C, Joshi S, Rundle A, Hutson M, Chong C, Weiss CC, et al. Association of proximity and density of parks and objectively measured physical activity in the United States: a systematic review. Soc. Sci. Med.2015;138:22–30.

    Article  PubMed  Google Scholar 

  15. Kaczynski AT, Besenyi GM, Stanis SWA, Koohsari MJ, Oestman KB, Bergstrom R, et al. Are park proximity and park features related to park use and park-based physical activity among adults? Variations by multiple socio-demographic characteristics. Int J Behav Nutr Phys Act. 2014;11:1–14.

    Article  Google Scholar 

  16. Kaczynski AT, Koohsari MJ, Stanis SAW, Bergstrom R, Sugiyama T. Association of street connectivity and road traffic speed with park usage and park-based physical activity. Am J Health Promot. 2014;28:197–203.

    Article  PubMed  Google Scholar 

  17. Drewnowski A, Aggarwal A, Tang W, Moudon A. Residential property values predict prevalent obesity but do not predict 1‐year weight change. Obesity. 2015;23:671–6.

    Article  PubMed  Google Scholar 

  18. Powell-Wiley T, Moore K, Allen N, Block R, Evenson K, Mujahid M, et al. Associations of Neighborhood Crime and Safety and With Changes in Body Mass Index and Waist Circumference: The Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 2017;186:280–8.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Leonard T, Ayers C, Das SR, Neeland IJ, Powell-Wiley TM. Do neighborhoods matter differently for movers and non-movers? Analysis of weight gain in the longitudinal Dallas Heart Study. Health Place. 2017;44:52–60.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ou S. Are some neighborhoods bad for your waistline? A test of neighborhood exposure effects on BMI. J Health Econ. 2019;63:52–63.

    Article  PubMed  Google Scholar 

  21. Okuyama K, Li X, Abe T, Hamano T, Franks PW, Nabika T, et al. Fast food outlets, physical activity facilities, and obesity among adults: a nationwide longitudinal study from Sweden. Int J Obes. 2020;44:1703–11. https://doi.org/10.1038/s41366-020-0588-5.

    Article  Google Scholar 

  22. Mooney SJ, Bobb JF, Hurvitz PM, Anau J, Theis MK, Drewnowski A, et al. Impact of Built Environments on Body Weight (the Moving to Health Study): Protocol for a Retrospective Longitudinal Observational Study. JMIR Res Protoc. 2020;9:e16787.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Drewnowski A, Arterburn D, Zane J, Aggarwal A, Gupta S, Hurvitz PM, et al. The Moving to Health (M2H) approach to natural experiment research: a paradigm shift for studies on built environment and health. SSM Popul Health. 2019;7:100345.

    Article  CAS  PubMed  Google Scholar 

  24. ESRI. ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research Institute; 2011.

  25. Hurvitz PM, Moudon AV, Kang B, Saelens BE, Duncan GE. Emerging technologies for assessing Physical activity behaviors in space and time. Front Public Health. 2014;2:2.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Pouliou T, Elliott SJ. Individual and socio-environmental determinants of overweight and obesity in Urban Canada. Health Place. 2010;16:389–98.

    Article  PubMed  Google Scholar 

  27. Huang R, Moudon AVA, Cook AJ, Drewnowski A. The spatial clustering of obesity: does the built environment matter? J Hum Nutr Diet. 2015;28:604–12. https://doi.org/10.1111/jhn.12279.

    Article  CAS  PubMed  Google Scholar 

  28. Sarkar C, Webster C, Gallacher J. Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participants. Lancet Planet Health. 2017;1:e277–88.

    Article  PubMed  Google Scholar 

  29. Lopez RP. Neighborhood risk factors for obesity. Obesity. 2007;15:2111–9.

    Article  PubMed  Google Scholar 

  30. Lovasi GS, Neckerman KM, Quinn JW, Weiss CC, Rundle A. Effect of individual or neighborhood disadvantage on the association between neighborhood walkability and body mass index. Am J Public Health. 2009;99:279–84.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Rundle A, Field S, Park Y, Freeman L, Weiss CC, Neckerman K. Personal and neighborhood socioeconomic status and indices of neighborhood walk-ability predict body mass index in New York City. Soc Sci Med. 2008;67:1951–8.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Durand CP, Oluyomi AO, Gabriel KP, Salvo D, Sener IN, Hoelscher DM, et al. The effect of light rail transit on physical activity: design and methods of the travel-related activity in neighborhoods study. Front Public Health. 2016;4:103.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Lovasi GS, Grady S, Rundle A. Steps forward: review and recommendations for research on walkability, physical activity and cardiovascular health. Public Health Rev. 2011;33:484–506.

    Article  Google Scholar 

  34. Vernez Moudon A, Drewnowski A, Duncan GE, Hurvitz PM, Saelens BE, Scharnhorst E. Characterizing the food environment: pitfalls and future directions. Public Health Nutr. 2013;16:1238–43.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Pushkarev B, Zupan J. Public transportation and land use policy. Bloomington: Indiana University Press; 1977.

  36. Frank LD, Pivo G. Impacts of mixed use and density on utilization of three modes of travel: single-occupant vehicle, transit, and walking. Transp Res Rec. 1994;1466:44–52.

    Google Scholar 

  37. Casey JA, Schwartz BS, Stewart WF, Adler NE. Using Electronic Health Records for Population Health Research: a review of methods and applications. Annu Rev Public Health. 2016;37:61–81.

    Article  PubMed  Google Scholar 

  38. Hurvitz PM, Moudon AV. Home versus nonhome neighborhood: quantifying differences in exposure to the built environment. Am J Prev Med. 2012;42:411–7.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Lee C, Moudon AV, Courbois JYP. Built environment and behavior: spatial sampling using parcel data. Ann Epidemiol. 2006;16:387–94.

    Article  PubMed  Google Scholar 

  40. Lamb KE, White SR. Categorisation of built environment characteristics: the trouble with tertiles. Int J Behav Nutr Phys Act. 2015;12:1–8.

    Article  Google Scholar 

  41. Mayne SL, Auchincloss AH, Michael YL. Impact of policy and built environment changes on obesity-related outcomes: A systematic review of naturally occurring experiments. Obes Rev. 2015;16:362–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Townshend T, Lake A. Obesogenic environments: current evidence of the built and food environments. Perspect. Public Health. 2016;137:38–44. https://doi.org/10.1177/1757913916679860.

    Article  Google Scholar 

  43. Caspi CE, Sorensen G, Subramanian SVVS, Kawachi I. The local food environment and diet: a systematic review. Health Place. 2012;18:1172–87.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Rundle AG, Chen Y, Quinn JW, Rahai N, Bartley K, Mooney SJ, et al. Development of a Neighborhood Walkability Index for Studying Neighborhood Physical Activity Contexts in Communities across the U.S. over the Past Three Decades. J Urban Health. 2019;96:583–90.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Morgan Hughey S, Kaczynski AT, Porter DE, Hibbert J, Turner-McGrievy G, Liu J. Development and testing of a multicomponent obesogenic built environment measure for youth using kernel density estimations. Health Place. 2019;56:174–83.

    Article  CAS  PubMed  Google Scholar 

  46. Martínez-García Trescastro-López, Galiana-Sánchez Pereyra-Zamora. Data collection instruments for obesogenic environments in adults: a scoping review. Int J Environ Res Public Health. 2019;16:1414.

    Article  PubMed Central  Google Scholar 

  47. Barquera S, Hernández-Barrera L, Rothenberg SJ, Cifuentes E. The obesogenic environment around elementary schools: food and beverage marketing to children in two Mexican cities. BMC Public Health. 2018;18:1–9.

    Article  Google Scholar 

  48. Jones A, Bentham G, Foster C, MH, Panter J. Tackling obesities: future choices-obesogenic environments-evidence review. London; 2007. https://www.researchgate.net/profile/Andy-Jones-16/publication/252029378_Tackling_Obesities_Future_Choices_-_Obesogenic_Environments_-_Evidence_Review/links/00463539592c87995b000000/Tackling-Obesities-Future-Choices-Obesogenic-Environments-Evidence-Review.pdf.

  49. Bader MDM, Schwartz-Soicher O, Jack D, Weiss CC, Richards CA, Quinn JW, et al. More neighborhood retail associated with lower obesity among New York City public high school students. Health Place. 2013;23:104–10.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Sharp L, Macrorie R, Turner A. Resource efficiency and the imagined public: Insights from cultural theory. Glob Environ Change. 2015;34:196–206.

    Article  Google Scholar 

  51. Chaix B. Mobile sensing in environmental health and neighborhood research. Annu Rev Public Health. 2018;39:367–84.

    Article  PubMed  Google Scholar 

  52. Kestens Y, Thierry B, Shareck M, Steinmetz-Wood M, Chaix B. Integrating activity spaces in health research: Comparing the VERITAS activity space questionnaire with 7-day GPS tracking and prompted recall. Spat Spatiotemporal Epidemiol. 2018;25:1–9.

    Article  PubMed  Google Scholar 

  53. An R, Sturm R. School and residential neighborhood food environment and diet among California youth. Am J Prev Med. 2012;42:129–35.

    Article  PubMed  PubMed Central  Google Scholar 

  54. McClure E, Feinstein L, Cordoba E, Douglas C, Emch M, Robinson W, et al. The legacy of redlining in the effect of foreclosures on Detroit residents’ self-rated health. Health Place. 2019;55:9–19.

    Article  PubMed  Google Scholar 

  55. Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017;389:1453–63. https://doi.org/10.1016/S0140-6736(17)30569-X.

    Article  PubMed  Google Scholar 

  56. Jacoby SF, Dong B, Beard JH, Wiebe DJ, Morrison CN. The enduring impact of historical and structural racism on urban violence in Philadelphia. Soc Sci Med. 2018;199:87–95.

    Article  PubMed  Google Scholar 

  57. Drewnowski A, Aggarwal A, Cook A, Stewart O, Moudon AV. Geographic disparities in Healthy Eating Index scores (HEI-2005 and 2010) by residential property values: Findings from Seattle Obesity Study (SOS). Prev Med (Baltim). 2016;83:46–55.

    Article  Google Scholar 

  58. Drewnowski A, Aggarwal A, Rehm C. Environments perceived as obesogenic have lower residential property values. Am J Prev Med. 2014;47:260–74.

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

This manuscript was supported by three grants from the National Institutes of Health: 1 R01 DK 114196, 5 R01 DK076608, and 4 R00LM012868.

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Authors and Affiliations

  1. Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA

    James H. Buszkiewicz, Shilpi Gupta & Adam Drewnowski

  2. Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA

    James H. Buszkiewicz, Stephen J. Mooney, Shilpi Gupta & Adam Drewnowski

  3. Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

    Jennifer F. Bobb, David Arterburn, Andrea Cook, Maricela Cruz, Paula Lozano, Dori E. Rosenberg, Mary Kay Theis & Jane Anau

  4. Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA

    Philip M. Hurvitz & Anne Vernez Moudon

  5. Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA

    Philip M. Hurvitz

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  1. James H. Buszkiewicz
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  2. Jennifer F. Bobb
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Correspondence to James H. Buszkiewicz.

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Conflict of interest

AD has received grants, honoraria, and consulting fees from numerous food, beverage, and ingredient companies and from other commercial and nonprofit entities with an interest in diet quality and nutrient density of foods. The University of Washington receives research funding from public and private sectors. The remaining authors declare no competing interests.

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Buszkiewicz, J.H., Bobb, J.F., Hurvitz, P.M. et al. Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain. Int J Obes 45, 1914–1924 (2021). https://doi.org/10.1038/s41366-021-00836-z

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