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Investigating associations between physical activity-related neighborhood built environment features and child weight status to inform local practice

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Listed:
  • Carlson, Jordan A.
  • Shook, Robin P.
  • Davis, Ann M.
  • Papa, Amy
  • Steel, Chelsea
  • Bejarano, Carolina
  • Noel-MacDonnell, Janelle R.
  • Summar, Shelly
  • Dean, Kelsey
  • Hampl, Sarah E.

Abstract

Despite evidence of the importance of neighborhood built environment features in relation to physical activity and obesity, research has been limited in informing localized practice due to small sample sizes and limited geographic coverage. This demonstration study integrated data from a local pediatric health system with nationally available neighborhood built environment data to inform local decision making around neighborhood environments and childhood obesity. Height/weight from clinic visits and home neighborhood measures from the U.S. Environmental Protections Agency and WalkScore were obtained for 15,989 6–17 year olds. Multilevel models accounted for the nested data structure and were adjusted for neighborhood income and child sociodemographics. In 9–17 year olds, greater street connectivity and walkability were associated with a 0.01–0.04 lower BMIz (Ps = .009-.017) and greater residential density, street connectivity, and walkability were associated 5–7% lower odds of being overweight/obese (Ps = .004-.044) per standard deviation increase in environment variable. 45.9% of children in the lowest walkability tertile were overweight or obese, whereas 43.1% of children in the highest walkability tertile were overweight or obese. Maps revealed areas with low walkability and a high income-adjusted percent of children overweight/obese. In the Kansas City area, data showed that fewer children were overweight/obese in more walkable neighborhoods. Integrating electronic health records with neighborhood environment data is a replicable process that can inform local practice by highlighting the importance of neighborhood environment features locally and pointing to areas most in need of interventions.

Suggested Citation

  • Carlson, Jordan A. & Shook, Robin P. & Davis, Ann M. & Papa, Amy & Steel, Chelsea & Bejarano, Carolina & Noel-MacDonnell, Janelle R. & Summar, Shelly & Dean, Kelsey & Hampl, Sarah E., 2021. "Investigating associations between physical activity-related neighborhood built environment features and child weight status to inform local practice," Social Science & Medicine, Elsevier, vol. 270(C).
  • Handle: RePEc:eee:socmed:v:270:y:2021:i:c:s0277953621000265
    DOI: 10.1016/j.socscimed.2021.113694
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    1. Sallis, James F & Bull, Fiona & Burdett, Ricky & Frank, Lawrence D. & Griffiths, Peter & Giles-Corti, Billie & Stevenson, Mark, 2016. "Use of science to guide city planning policy and practice: how to achieve healthy and sustainable future cities," LSE Research Online Documents on Economics 68652, London School of Economics and Political Science, LSE Library.
    2. Greves Grow, H. Mollie & Cook, Andrea J. & Arterburn, David E. & Saelens, Brian E. & Drewnowski, Adam & Lozano, Paula, 2010. "Child obesity associated with social disadvantage of children's neighborhoods," Social Science & Medicine, Elsevier, vol. 71(3), pages 584-591, August.
    3. Cain, Kelli L. & Millstein, Rachel A. & Sallis, James F. & Conway, Terry L. & Gavand, Kavita A. & Frank, Lawrence D. & Saelens, Brian E. & Geremia, Carrie M. & Chapman, James & Adams, Marc A. & Glanz,, 2014. "Contribution of streetscape audits to explanation of physical activity in four age groups based on the Microscale Audit of Pedestrian Streetscapes (MAPS)," Social Science & Medicine, Elsevier, vol. 116(C), pages 82-92.
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    1. Kong, Hui & Wu, Jingyi & Li, Pengfei, 2024. "Impacts of active mobility on individual health mediated by physical activities," Social Science & Medicine, Elsevier, vol. 348(C).
    2. Stolte, Allison & Merli, M. Giovanna & Hurst, Jillian H. & Liu, Yaxing & Wood, Charles T. & Goldstein, Benjamin A., 2022. "Using Electronic Health Records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research," Social Science & Medicine, Elsevier, vol. 296(C).

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