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Epidemiology and Population Health

Differential associations of the built environment on weight gain by sex and race/ethnicity but not age



To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults.


Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18–64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values.


Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (−0.49 kg, 95% CI: −0.68, −0.30) and females (−0.17 kg, 95% CI: −0.33, −0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (−0.47 kg, 95% CI: −0.61, −0.32), NH Blacks (−0.86 kg, 95% CI: −1.37, −0.36), Hispanics (0.10 kg, 95% CI: −0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures.


The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

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Fig. 1: Analytic sample exclusion/inclusion decision flow diagram.
Fig. 2: Mean difference in weight change from baseline.


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

Author information




JFB, AD, and DA developed the initial study concepts. AVM and PMH developed the SmartMaps exposure assessment tool. JFB, AC, MC, SJM, DA, and JHB developed the study design and analytic plan with consultation from all other co-authors, and JFB conducted analyses. JHB wrote the manuscript with the assistance of AD and under the supervision of AD and DA. All authors provided critical feedback and helped shape the research, analysis, interpretation of findings, and the manuscript. AD and DA provided project supervision. JA provided project support.

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Correspondence to James H. Buszkiewicz.

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Competing interests

Adam Drewnowski 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. All other authors have no conflicts of interest to declare.

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Buszkiewicz, J.H., Bobb, J.F., Kapos, F. et al. Differential associations of the built environment on weight gain by sex and race/ethnicity but not age. Int J Obes 45, 2648–2656 (2021).

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