The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study

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Citation

Boone-Heinonen, Janne; Diez-Roux, Ana V.; Goff, David C., Jr.; Loria, Catherine M.; Kiefe, Catarina I.; Popkin, Barry M.; & Gordon-Larsen, Penny (2013). The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study. PLOS ONE, 8(12), e85141. PMCID: PMC3874030

Abstract

BACKGROUND: Recent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood.
METHODS AND FINDINGS: We used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25th to 75th percentile) predicted inter-exam reduction in BMI of 0.09 kg/m2 [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m2 in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m2 in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.
CONCLUSIONS: Findings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.

URL

http://dx.doi.org/10.1371/journal.pone.0085141

Reference Type

Journal Article

Year Published

2013

Journal Title

PLOS ONE

Author(s)

Boone-Heinonen, Janne
Diez-Roux, Ana V.
Goff, David C., Jr.
Loria, Catherine M.
Kiefe, Catarina I.
Popkin, Barry M.
Gordon-Larsen, Penny

PMCID

PMC3874030

ORCiD

Gordon-Larsen - 0000-0001-5322-4188
Popkin - 0000-0001-9495-9324
Boone - 0000-0002-0368-0545