Impact of the Built Environment on Child Body Mass Index

项目摘要 在过去的几年里，人们对“建筑环境”的潜在贡献越来越感兴趣。 与美国肥胖率的普遍上升有关。这既包括大型结构方面的 家庭和学校在非常微观层面上的邻里关系和物理特征(室内和 这些建筑物的相关场地)。住宅周围社区的结构方面 学校包括城市设计特征，如街道和高速公路，土地利用组合，街道连通性， 公共交通基础设施(即地铁站)、公园用地和娱乐基础设施，所有这些 这可能会影响体力活动以及食物和其他资源的可获得性。体能 家庭或学校的特点-包括建筑大小、是否有电梯、楼梯、空间 体力活动及相关因素--可决定体力活动的机会和 在太空中导航所需的活动。到目前为止，还没有确定这些因素中的每一个是如何促成 儿童体重指数以不同和相互关联的方式和/或这些因素的变化如何影响 肥胖率是一种因果关系。考虑到变革的高昂成本，这种知识差距尤其令人担忧 建筑环境以及曾经进行的投资的寿命。我们的研究承诺提供 洞察力对于政策制定者规划城市基础设施投资至关重要。特别重要的是要考虑 是否存在差异，以及建筑环境的差异是否可以解释 主要人口群体，包括收入和种族/族裔。我们建议将纽约市与 教育部全民健身图数据，其中包括体重指数、学校和居住地点 从2005年起，纽约市公立学校的孩子们，以及建筑环境的详细数据 围绕着每个孩子的家和学校，以及他们的家和学校。然后，我们将使用各种 增强的方法论技术，以估计构建的 环境和肥胖。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，包括纽约市100多万公立学校儿童的数据。 ·根据儿童、学校和人口普查地区的水平，对同一批儿童进行纵向检查 固定效果，以及其他确定伤亡情况的方法。 ·考察建筑环境中细粒度的差异。例如，相对影响 居住在离公园或其他已建环境资源500英尺的范围内 ·关于家庭和学校建筑环境的数据，包括建筑物内部和 邻里关系，一起做模特。 有了这些增强功能，我们将能够提供更好的估计，以改善建设的影响 环境对儿童体重指数的影响，基本上回答了关键的健康和与政策相关的问题。

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.