Food environment, diet quality, and disparities in obesity

描述(由申请者提供)：这个项目将研究物理、社会和经济环境如何影响饮食选择，从而导致肥胖率的差异。目前的假设是，低成本和容易获得高能量密度的食物可能是肥胖率较高的独立预测因素。这项研究将把调查研究技术与新的空间分析方法结合起来，以获得关于参与者的物理和食物环境以及他们获得食物来源的深入信息。一项对华盛顿州金县2000名成年居民的分层电话调查将提供参与者的社会经济地位(SEP)、购物和饮食习惯、食物支出、肥胖和健康的自我报告数据。将对所有地址进行地理编码，以促进空间分析和地图绘制。SEP的客观衡量将基于可用的最详细的解决方案的数据--县税务师在税包级别。将使用基于地理信息系统的定制应用程序和物理环境的新指标，在个人一级计算实际获得三个关键食物来源的客观衡量标准，这些衡量标准是根据质量、距离和时间为每个受访者定义的。地理信息系统软件中的定制程序将在调查参与者的家庭环境及其主要食物来源附近捕获并执行地理空间数据的初步几何分析。将使用当地食品价格和将邮寄给所有2000名调查对象的额外饮食问卷工具来估计个人饮食的饮食能量密度和货币成本。将使用市场篮子技术评估食品价格的地方差异。空间分析和多水平回归模型将被用来检验这样一个假设，即身体和经济上获得食物来源可以预测饮食能量密度和肥胖率。

DESCRIPTION (provided by applicant): This project will examine how the physical, social, and economic environments influence dietary choices and, thereby, contribute to disparities in obesity rates. The present hypothesis is that the low cost and easy access to energy-dense foods may be an independent predictor of higher obesity rates. This study will combine survey research techniques with novel methods of spatial analysis to obtain in-depth information about the participants' physical and food environment and their access to food sources. A telephone survey of a stratified sample of 2,000 adult residents of King County, WA, will provide self-reported data on the participants' socioeconomic position (SEP), shopping and eating habits, food expenditures, obesity, and health. All addresses will be geocoded to facilitate spatial analysis and mapping. Objective measures of SEP will be based on data at the most detailed resolution available -- the County tax assessor at the tax parcel level. Objective measures of physical access to three key food sources, defined for each respondent in terms of quality, distance and time, will be calculated at the individual level using custom GIS based applications and novel metrics of the physical environment. Custom programs within GIS software will capture and perform preliminary geometric analysis of geospatial data within the proximity of the survey participants' home environment and their chief food sources. Dietary energy density and monetary cost of individual diets will be estimated using local food prices and an additional diet questionnaire instrument that will be mailed to all 2000 study respondents. Local variation in food prices will be assessed using a market basket technique. Spatial analyses and multilevel regression models will be used to test the hypothesis that physical and economic access to foods sources may predict dietary energy density and obesity rates.