Does Unmeasured Confounding Influence Associations between the Food Environment and Body Mass Index over Time? The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Rummo, Pasquale E.; Guilkey, David K.; Ng, Shu Wen; Meyer, Katie A.; Popkin, Barry M.; Reis, Jared P.; Shikany, James M.; & Gordon-Larsen, Penny. (2017). Does Unmeasured Confounding Influence Associations between the Food Environment and Body Mass Index over Time? The Coronary Artery Risk Development in Young Adults (CARDIA) Study. International Journal of Epidemiology, 46(5), 1456-64. PMCID: PMC Journal - In Process

Rummo, Pasquale E.; Guilkey, David K.; Ng, Shu Wen; Meyer, Katie A.; Popkin, Barry M.; Reis, Jared P.; Shikany, James M.; & Gordon-Larsen, Penny. (2017). Does Unmeasured Confounding Influence Associations between the Food Environment and Body Mass Index over Time? The Coronary Artery Risk Development in Young Adults (CARDIA) Study. International Journal of Epidemiology, 46(5), 1456-64. PMCID: PMC Journal - In Process

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Background: Findings in the observational food environment and obesity literature are inconsistent, potentially due to a lack of adjustment for residual confounding. Methods: Using data from the CARDIA study (n=12,174 person-observations; 6 exams; 1985-2011) across four U.S. cities (Birmingham, AL; Chicago, IL; Minneapolis, MN; Oakland, CA), we used instrumental-variables (IV) regression to obtain causal estimates of the longitudinal associations between the percentage of neighborhood food stores or restaurants (per total food outlets within 1-km network distance of respondent residence) with body mass index (BMI), adjusting for individual-level sociodemographics, health behaviors, city, year, total food outlets, and market-level prices. To determine the presence and extent of bias, we compared the magnitude and direction of results to ordinary least squares (OLS) and random effects (RE) regression, which do not control for residual confounding; and fixed effects (FE) regression, which does not control for time-varying residual confounding. Results: Relative to neighborhood supermarkets (which tend to be larger and have healthier options than grocery stores), a higher percentage of grocery stores (mean=53.4%; SD=31.8%) was positively associated with BMI (β=0.05; 95% CI=0.01, 0.10) using IV regression. However, associations were negligible or null using OLS (β=-0.001; 95% CI=-0.01, 0.01), RE (β=-0.003; 95% CI=-0.006, 0.0001), and FE (β=-0.003; 95% CI=-0.006, 0.0002) regression. Neighborhood convenience stores and fast food restaurants were not associated with BMI in any model. Conclusion: Longitudinal associations between neighborhood food outlets and BMI were greater in magnitude using a causal model, suggesting that weak findings in the literature may be due to residual confounding.




JOUR



Rummo, Pasquale E.
Guilkey, David K.
Ng, Shu Wen
Meyer, Katie A.
Popkin, Barry M.
Reis, Jared P.
Shikany, James M.
Gordon-Larsen, Penny



2017


International Journal of Epidemiology

46

5

1456-64








PMC Journal - In Process


10040

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