Impact of the Built Environment on Child Body Mass Index

项目摘要 在过去的几年里，人们对“人造环境”的潜在贡献越来越感兴趣。 美国肥胖率的普遍上升。这包括两个大的结构方面， 邻里和物理特性的家庭和学校在非常微观的水平（内部和 这些建筑物的相关场地）。住宅周围的邻里结构 学校包括城市设计特征，如街道和高速公路，土地使用组合，街道连通性， 公共交通基础设施（即，地铁站），公园土地，娱乐基础设施，所有的 这可能会影响身体活动以及食物和其他资源的获取。物理 家庭或学校的特点，包括建筑物的大小，电梯，楼梯，空间的存在， 身体活动和相关因素-可以决定身体活动的机会和数量 导航空间所需的活动。到目前为止，还没有确定这些因素中的每一个如何有助于 儿童BMI以独特和相互关联的方式和/或这些因素的变化如何影响 肥胖率是有因果关系的考虑到改变的高昂成本， 建筑环境以及投资的长期性。我们的研究有望提供 对规划城市基础设施投资的决策者至关重要的洞察力。特别重要的是要考虑到 是否存在差异，以及建筑环境的差异是否可以解释肥胖率的差异， 关键人口群体，包括收入和种族/民族。我们提议将联合收割机和纽约市 教育部FITNESSGRAM数据，包括所有人的BMI，学校和居住地点 纽约市公立学校的学生从2005年起，详细数据的建筑环境 每个孩子的家和学校周围以及他们的家和学校内。然后，我们将使用各种 增强的方法技术，以估计建立的 环境与肥胖我们在过去的工作中使用的方法改进是： ·一个庞大而详细的数据集，包括超过100万纽约公立学校儿童的数据。 ·在儿童、学校和人口普查区各级，对同一儿童进行长期纵向调查 固定效应，以及其他方法来确定伤亡。 ·检查建筑环境中的细粒度差异。例如， 居住在公园或其他建筑环境资源500英尺范围内 ·关于家庭和学校建筑环境的数据，包括建筑物内部和建筑物内部的数据。 邻里，一起建模。 有了这些增强功能，我们将能够提供更好的估计， 环境对儿童BMI的影响，实质性地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 “built environment” to the epidemic increase in obesity rates in the United States. This includes both the large structural aspects of the neighborhood and physical characteristics of homes and schools at the very micro level (the interiors and associated grounds of these buildings). The structural aspects of the neighborhood that surround the home and school includes urban design features such as streets and highways, land use mix, street connectivity, public transportation infrastructure (i.e., subway stations), park land, and recreational infrastructure, all of which could affect both physical activity and the accessibility of food and other resources. The physical characteristics of the home or school—including building size, the presence of elevators, stairs, spaces for physical activity, and related factors—could determine opportunities for physical activity and amount of activity needed to navigate the space. Thus far not established is how each of these factors contributes to childhood BMI in a distinct and interconnected way and/or how changes in such factors could influence obesity rates in a causal manner. This gap in knowledge is particularly troubling given the high cost of changing the built environment as well as the longevity of investments once made. Our research promises to provide insight critical to policymakers planning urban infrastructure investment. Particularly important to consider are disparities, and whether differences in the built environment could explain differences in obesity rates in key demographic groups, including income and race/ethnicity. We propose to combine New York City Department of Education FITNESSGRAM data, which includes BMI, school and residential locations, for all New York City public school children from 2005 onward, with detailed data on the built environment surrounding each child’s home and school as well as within their home and school. Then, we will use a variety of enhanced methodological techniques to estimate a less-biased, more causal relationship between the built 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, using both child, school and census tract level fixed effects, among other methods, to determine casualty. • Examining fine-grained differences in the built environment. For example, the relative influence of living within 500 feet of a park or other built environment resources • Data on both the home and school built environment, both inside the building and in the neighborhood, modeled together. With these enhancements, we will be able to provide improved estimates on the influence of the built environment on child BMI, substantially answering key health and policy-related questions.