Child obesity associated with social disadvantage of children’s neighborhoods.

Auteur(s) :
Cook AJ., Grow HM., Arterburn DE.
Date :
Août, 2010
Source(s) :
SOC SCI MED. #71:3 p584-91
Adresse :
University of Washington and Seattle Children's Research Institute, Seattle, WA 98101, USA.

Sommaire de l'article

Evidence suggests variability in adult obesity risk at a small-scale geographic area is associated with differences in neighborhood socioeconomic status (SES). However, the extent to which geographic variability in child obesity is associated with neighborhood SES is unknown. The objective of this paper was to estimate risk of child obesity associated with multiple census tract SES measures and race within a large urban U.S. county. Height, weight, age, sex, medical insurance type and census tract residence were obtained for 6-18 year old children (n=8616) who received medical care at a health plan in King County, Washington, in 2006. Spatial analyses examined the individual risk of obesity (BMI > or = 95th percentile) with 2000 US census tract measures of median household income, home ownership, adult female education level, single parent households, and race as predictors. Conditional autoregressive regression models that incorporated adjacent census tracts (spatial autocorrelation) were applied to each census tract variable, adjusting for individual variables. We found that in adjusted spatial models, child obesity risk was significantly associated with each census tract variable in the expected direction: lower household income, lower home ownership, and for each 10% increase in less educated women, and single parent households, as well as non-white residents. In a spatial model including all variables, the SES/race variables explained approximately 24% of geographic variability in child obesity. Results indicated that living in census tracts with social disadvantage defined by multiple different measures was associated with child obesity among insured children in a large U.S. urban county. These results contribute new information on relationships between broader social and economic context and child obesity risk using robust spatial analyses.

Source : Pubmed