A new method to visualize obesity prevalence in Seattle-King County at the census block level.
A new method to visualize obesity prevalence in Seattle-King County at the census block level.
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DOI：
10.1002/osp4.144
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发表时间：
2018-03
影响因子：
2.2
通讯作者：
Moudon AV
中科院分区：
文献类型：
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作者：
Drewnowski A;Buszkiewicz J;Aggarwal A;Cook A;Moudon AV
本研究的目的是绘制西雅图金县人口普查区肥胖患病率图。1632名成年男性和女性的数据来自西雅图肥胖研究i。人口统计、社会经济和人体测量数据通过电话调查收集。家庭住址是地理编码的，税包住宅物业价值是从金县税务评估员那里获得的。多元逻辑回归检验了房价与肥胖率之间的关系。汇总到人口普查街区的房价被分成十分位数，用来生成肥胖热图。西雅图肥胖研究参与者的财产价值十分位数与全县十分位数相对应。低住宅物业价值与高肥胖率相关（比值比，OR: 0.36； 95%置信区间，CI[0.25, 0.51]，在样本3和样本1中），调整了年龄、性别、种族、住房所有权、教育程度和收入。人口普查区的肥胖热图显示了地理区域的差异。住宅物业价值是衡量个人和地区社会经济地位的客观指标，是观察饮食质量和健康方面社会经济差异的有用工具。
The aim of this study is to map obesity prevalence in Seattle King County at the census block level. Data for 1,632 adult men and women came from the Seattle Obesity Study I. Demographic, socioeconomic and anthropometric data were collected via telephone survey. Home addresses were geocoded, and tax parcel residential property values were obtained from the King County tax assessor. Multiple logistic regression tested associations between house prices and obesity rates. House prices aggregated to census blocks and split into deciles were used to generate obesity heat maps. Deciles of property values for Seattle Obesity Study participants corresponded to county‐wide deciles. Low residential property values were associated with high obesity rates (odds ratio, OR: 0.36; 95% confidence interval, CI [0.25, 0.51] in tertile 3 vs. tertile 1), adjusting for age, gender, race, home ownership, education, and incomes. Heat maps of obesity by census block captured differences by geographic area. Residential property values, an objective measure of individual and area socioeconomic status, are a useful tool for visualizing socioeconomic disparities in diet quality and health.