University of Washington and Seattle Children's Research Institute, Seattle, WA, USA.
Group Health Research Institute, Seattle, WA, USA.
Soc Sci Med. 2010 Aug;71(3):584-591. doi: 10.1016/j.socscimed.2010.04.018. Epub 2010 May 12.
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.
有证据表明，小范围地理区域内成年人肥胖风险的变化与邻里社会经济地位（SES）的差异有关。然而，儿童肥胖的地理变化与邻里 SES 的关系程度尚不清楚。本文的目的是估计与美国一个大城市县多个普查区 SES 指标和种族相关的儿童肥胖风险。在 2006 年，华盛顿金县的一项健康计划为 6-18 岁的儿童（n=8616）提供医疗服务，获取了他们的身高、体重、年龄、性别、医疗保险类型和普查区居住信息。空间分析使用 2000 年美国普查区的中位数家庭收入、住房拥有率、成年女性受教育程度、单亲家庭和种族等指标来评估个体肥胖风险（BMI>或=第 95 百分位数）。条件自回归回归模型纳入相邻普查区（空间自相关），并调整个体变量。我们发现，在调整后的空间模型中，儿童肥胖风险与每个普查区变量均呈预期方向显著相关：家庭收入越低、住房拥有率越低、受教育程度较低的女性比例每增加 10%、单亲家庭比例越高，以及非白人居民比例越高，儿童肥胖风险越大。在包括所有变量的空间模型中，SES/种族变量可以解释儿童肥胖地理差异的大约 24%。结果表明，生活在由多种不同指标定义的社会劣势的普查区与美国大城市县有保险的儿童肥胖有关。这些结果利用稳健的空间分析为更广泛的社会和经济背景与儿童肥胖风险之间的关系提供了新的信息。
