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Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain
Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain
- Source :
- International journal of obesity (2005)
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
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-meter buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1,600, and 5,000-meter 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 kilograms at 1 year (95% CI: 0.03, 0.10); 0.64 kilograms at 3 years (95% CI: 0.59, 0.68), and 0.95 kilograms 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 kilograms. Conclusion: 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.
- Subjects :
- Adult
Male
obesity
Adolescent
Urban Population
Endocrinology, Diabetes and Metabolism
Population
Medicine (miscellaneous)
030209 endocrinology & metabolism
Article
03 medical and health sciences
0302 clinical medicine
electronic medical records
medicine
Humans
030212 general & internal medicine
education
Built environment
geographic information systems
education.field_of_study
Nutrition and Dietetics
Weight change
Regression analysis
Middle Aged
medicine.disease
built environment
Obesity
Geography
Cohort
Regression Analysis
Body-Weight Trajectory
Female
medicine.symptom
Body mass index
Weight gain
Demography
Subjects
Details
- ISSN :
- 14765497 and 03070565
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- International Journal of Obesity
- Accession number :
- edsair.doi.dedup.....e44231785d5b9eb05bd092f458c4a665
- Full Text :
- https://doi.org/10.1038/s41366-021-00836-z