title: The neighborhood energy balance equation: does neighborhood food retail environment + physical activity environment = obesity? The CARDIA study.
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.
  
  
  RESULTS
  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 25(th) to 75(th) percentile) predicted inter-exam reduction in BMI of 0.09 kg/m(2) [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m(2) 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/m(2) 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.
authors.affiliation: Department of Public Health and Preventive Medicine, Oregon Health and Science University, Portland, Oregon, United States of America.
authors.forename: Janne
authors.initials: J
authors.lastname: Boone-Heinonen
authors.affiliation: Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Ana V
authors.initials: AV
authors.lastname: Diez-Roux
authors.affiliation: Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America.
authors.forename: David C
authors.initials: DC
authors.lastname: Goff
authors.affiliation: Division of Epidemiology and Clinical Applications, National Heart, Lung, and Blood Institute, Bethesda, Maryland, United States of America.
authors.forename: Catherine M
authors.initials: CM
authors.lastname: Loria
authors.affiliation: Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worchester, Massachusetts, United States of America.
authors.forename: Catarina I
authors.initials: CI
authors.lastname: Kiefe
authors.affiliation: Department of Nutrition, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
authors.forename: Barry M
authors.initials: BM
authors.lastname: Popkin
authors.affiliation: Department of Nutrition, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
authors.forename: Penny
authors.initials: P
authors.lastname: Gordon-Larsen
mesh_terms: D000293:Adolescent; D000328:Adult; D015992:Body Mass Index; D005260:Female; D005522:Food Services; D006801:Humans; D008297:Male; D008954:Models, Biological; D009043:Motor Activity; D009765:Obesity / Q000453:epidemiology / Q000209:etiology / Q000523:psychology; D012737:Sex Factors; D012959:Socioeconomic Factors; D055815:Young Adult