4.7 Article

Neighborhood socioeconomic status predictors of physical activity through young to middle adulthood: The CARDIA study

Journal

SOCIAL SCIENCE & MEDICINE
Volume 72, Issue 5, Pages 641-649

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.socscimed.2010.12.013

Keywords

Environment design; Socioeconomic status; Physical activity; Epidemiologic methods; Confounding factors; USA; Race

Funding

  1. Interdisciplinary Obesity Training postdoctoral fellowship [T32MH075854-04]
  2. National Institutes of Health [R01 HL104580, R01-CA109831, R01-CA121152, R01-AA12162, DK056350]
  3. UNC-CH Center for Environmental Health and Susceptibility (CEHS)(NIH) [P30-ES10126]
  4. UNC-CH Clinic Nutrition Research Center (NIH) [DK56350]
  5. Carolina Population Center
  6. University of Alabama at Birmingham, Coordinating Center [N01-HC-95095]
  7. University of Minnesota, Field Center [N01-HC-48048]
  8. Northwestern University, Field Center [N01-HC-48049]
  9. Kaiser Foundation Research Institute from the National Heart, Lung and Blood Institute [N01-HC-48050]

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Neighborhood socioeconomic status (SES) is related to a wide range of health outcomes, but existing research is dominated by cross-sectional study designs, which are particularly vulnerable to bias by unmeasured characteristics related to both residential location decisions and health-related outcomes. Further, little is known about the mechanisms by which neighborhood SES might influence health. Therefore, we estimated longitudinal relationships between neighborhood SES and physical activity (PA), a theorized mediator of the neighborhood SES-health association. We used data from four years of the Coronary Artery Risk Development in Young Adults (CARDIA) study (n = 5115, 18-30 years at baseline, 1985-1986), a cohort of U.S. young adults followed over 15 years, and a time-varying geographic information system. Using two longitudinal modeling strategies, this is the first study to explicitly examine how the estimated association between neighborhood SES (deprivation) and PA is biased by (a) measured characteristics theorized to influence residential decisions (e.g., controlling for individual SES, marriage, and children in random effects models), and (b) time-invariant, unmeasured characteristics (e.g., controlling for unmeasured motivation to exercise that is constant over time using repeated measures regression modeling, conditioned on the individual). After controlling for sociodemographics (age, sex, race) and individual SES, associations between higher neighborhood deprivation and lower PA were strong and incremental in blacks, but less consistent in whites. Furthermore, adjustment for measured characteristics beyond sociodemographics and individual SES had little influence on the estimated associations: adjustment for unmeasured characteristics attenuated negative associations more strongly in whites than in blacks. (C) 2011 Elsevier Ltd. All rights reserved.

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