Impact of the Food Environment on Child Body Mass Index - Resubmission - 1

项目摘要 在过去的几年里，人们越来越多地关注 “饮食环境”使美国肥胖率上升。早期经验 有证据表明，不同地理区域的可获得性存在显著差异。 不同种类的食物。在经济和社会上处于不利地位的社区越贫穷 饮食环境，健康食品较少，不健康食品较多 社区。似乎有越来越多的证据表明，食物环境的特征 与饮食行为和结果有关，但仍有许多问题悬而未决 这片区域。在很大程度上，我们还不能确切知道食物环境的哪些特征 最具影响力、有多大影响力、在哪些地理空间环境中以及在哪些方面 人口。然而，公共政策在这一领域进展迅速，卡路里标签，限制快速 食品区，为服务不足的社区的超市提供财政激励，“健康杂货店” 倡议，以及许多社区已经实施的其他监管杠杆。进一步研究 因此，这方面的工作是必要的。 我们建议将纽约市教育部FITNESSGRAMdata合并为 包括BMI、学校和居住地点，适用于纽约市所有公立学校的儿童 2005年后，提供有关每个儿童家庭周围食物环境的详细数据 学校。然后，我们将使用各种增强的方法技术来估计真实的 饮食环境与肥胖的关系。我们使用的方法改进 过去的工作包括： ？一个庞大而详细的数据集，包括纽约市100多万公立学校儿童的数据。 随着时间的推移，纵向检查相同的儿童，检查BMI发生了什么 随着健康和不太健康的食品店的开张和关闭。(子固定效果) 检查食物资源的细粒度差异，即使在同一人口普查区域内也是如此。 例如，居住在500英尺或两个城市街区内的相对影响与 比那更远。(人口普查区域固定效果) ？关于家庭和学校食物环境的数据，一起建模。 有了这些变化，我们将能够对食物的影响提供公正的估计 关于儿童体重指数的环境问题，实质上回答了关键的健康和政策相关问题。

Project Summary The last several years have witnessed growing interest in the potential contribution of the "food environment" to the epidemic increase in obesity rates in the United States. Early empirical evidence suggests that there is significant variation across geographic areas in the availability of different kinds of foods. More economically and socially disadvantaged communities have poorer food environments, with healthy food less available and unhealthy food more available in those communities. There appears to be growing evidence that characteristics of the food environment are associated with dietary behaviors and outcomes, but there are still many unanswered questions in this area. In large part we don't yet know exactly which characteristics of the food environment are most influential, how influential they are, in which geospatial environments, and for which populations. Yet public policy is proceeding apace in this area, with calorie labeling, restrictive fast food zoning, financial incentives for supermarkets in underserved neighborhoods, "healthy bodega" initiatives, and other regulatory levers already implemented in many communities. Further research in this area is thus required. We propose to combine New York City Department of Education FITNESSGRAMdata, which includes BMI, school and residential locations, for all New York City public school children from 2005 onward with detailed data on the food environment surrounding each child's home and school. Then, we will use a variety of enhanced methodological techniques to estimate the true relationship between food environment and obesity. The methodological enhancements we utilize over past work are: ¿ A large, detailed dataset, including data on over 1 million NYC public school children. ¿ Examining longitudinally the same children over time, examining what happens to BMI as healthy and less healthy food stores open and close. (Child fixed effects) ¿ Examining fine-grained differences in food resources, even within the same Census tract. For example, the relative influence of living within 500 feet, or two city blocks, versus farther than that. (Census tract fixed effects) ¿ Data on both the home and school food environment, modeled together. With these changes, we will be able to provide unbiased estimates on the influence of the food environmental on child BMI, substantially answering key health and policy-related questions.