Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Aug 1;177(8):847-855.
doi: 10.1001/jamapediatrics.2023.1329.

Association of Place With Adolescent Obesity

Ashlesha Datar  1 , Nancy Nicosia  2 , Amy Mahler  3 , Maria J Prados  1 , Madhumita Ghosh-Dastidar  2
Affiliations

Association of Place With Adolescent Obesity

Ashlesha Datar et al. JAMA Pediatr. .

Abstract

Importance: Despite strong evidence linking place and obesity risk, the extent to which this link is causal or reflects sorting into places is unclear.

Objective: To examine the association of place with adolescents' obesity and explore potential causal pathways, such as shared environments and social contagion.

Design, setting, and participants: This natural experiment study used the periodic reassignment of US military servicemembers to installations as a source of exogenous variation in exposure to difference places to estimate the association between place and obesity risk. The study analyzed data from the Military Teenagers Environments, Exercise, and Nutrition Study, a cohort of adolescents in military families recruited from 2013 through 2014 from 12 large military installations in the US and followed up until 2018. Individual fixed-effects models were estimated that examined whether adolescents' exposure to increasingly obesogenic places over time was associated with increases in body mass index (BMI) and probability of overweight or obesity. These data were analyzed from October 15, 2021, through March 10, 2023.

Exposure: Adult obesity rate in military parent's assigned installation county was used as a summary measure of all place-specific obesogenic influences.

Main outcomes and measures: Outcomes were BMI, overweight or obesity (BMI in the 85th percentile or higher), and obesity (BMI in the 95th percentile or higher). Time at installation residence and off installation residence were moderators capturing the degree of exposure to the county. County-level measures of food access, physical activity opportunities, and socioeconomic characteristics captured shared environments.

Results: A cohort of 970 adolescents had a baseline mean age of 13.7 years and 512 were male (52.8%). A 5 percentage point-increase over time in the county obesity rate was associated with a 0.19 increase in adolescents' BMI (95% CI, 0.02-0.37) and a 0.02-unit increase in their probability of obesity (95% CI, 0-0.04). Shared environments did not explain these associations. These associations were stronger for adolescents with time at installation of 2 years or longer vs less than 2 years for BMI (0.359 vs. 0.046; P value for difference in association = .02) and for probability of overweight or obesity (0.058 vs. 0.007; P value for difference association = .02), and for adolescents who lived off installation vs on installation for BMI (0.414 vs. -0.025; P value for association = .01) and for probability of obesity (0.033 vs. -0.007; P value for association = .02).

Conclusion and relevance: In this study, the link between place and adolescents' obesity risk is not explained by selection or shared environments. The study findings suggest social contagion as a potential causal pathway.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest Disclosures: Dr Datar reported grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Institute of Diabetes and Digestive and Kidney Diseases during the conduct of the study. Dr Nicosia reported grants from the National Institutes of Health during the conduct of the study. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. County Obesity Rate and Cumulative Sample Distribution Across Installation Counties in the Analysis Sample
Figure 2.
Figure 2.. Individual-Level Trajectories of Installation County Obesity Rate (COR) Exposure for Adolescents in Families Assigned to 12 Largest Installations at Baseline
Each graph shows the individual-specific trajectories of COR exposure over the study period for adolescents whose families were assigned to the indicated installation at baseline. For example, adolescents who were at Fort Carson at baseline were exposed to El Paso County, Colorado, that had a COR of 21.2% but were subsequently exposed to substantially different (and seemingly random) CORs due to a combination of relocations and within-county changes in obesity rates. The lines represent individuals.
See this image and copyright information in PMC

References

    1. Koh HK, Piotrowski JJ, Kumanyika S, Fielding JE. Healthy people: a 2020 vision for the social determinants approach. Health Educ Behav. 2011;38(6):551-557. doi:10.1177/1090198111428646 - DOI - PubMed
    1. US Department of Health and Human Services . Healthy people 2030: building a healthier future for all. Accessed April 21, 2023. https://health.gov/healthypeople
    1. Chetty R, Stepner M, Abraham S, et al. . The Association between income and life expectancy in the United States, 2001-2014. JAMA. 2016;315(16):1750-1766. doi:10.1001/jama.2016.4226 - DOI - PMC - PubMed
    1. Couillard BK, Foote CL, Gandhi K, Meara E, Skinner J. Rising geographic disparities in US Mortality. J Econ Perspect. 2021;35(4):123-146. doi:10.1257/jep.35.4.123 - DOI - PMC - PubMed
    1. Deryugina T, Molitor D. The causal effects of place on health and longevity. J Econ Perspect. 2021;35(4):147-170. doi:10.1257/jep.35.4.147 - DOI - PMC - PubMed

Publication types