Environmental Changes and Health Outcomes across 25 Years: Four US Cities

摘要 虽然观察性研究表明，肥胖相关的社会环境因素与 肥胖和心脏代谢的危险因素，很少有研究涉及具体的因素和途径 将社会环境与心脏新陈代谢风险联系起来。缺乏研究的主要原因是：1)缺乏 关于饮食、运动、随时间测量的身高和体重与心脏代谢风险相关的高质量数据 生物标志物；2)缺乏关于食品引进、更新和关闭的细粒纵向数据-以及 与活动相关的环境特征；以及3)缺乏复杂的统计模型来检查每一块 依赖时间的复杂系统，说明食物、活动和运输的过程 设施的建立和扩展，以及个人有选择地迁移到附近的可能性 这样的设施。25年来青年冠状动脉纵向风险发展(CARDIA)研究 提供广泛的年龄范围、高质量的纵向、生物学、行为和人体测量以及生物标记物 CARDIA数据、地理多样性以及四个基线上不同的变化模式和速度 城市：伯明翰、芝加哥、明尼阿波利斯和奥克兰。研究小组开发了一种独特的方法来 使用追溯和当代来源创建关于介绍的时间和位置的数据， 翻新和关闭：1)食品资源(如餐馆、食品购物)；2)娱乐设施 (例如，步道、公园)；以及3)伯明翰的交通基础设施(例如，轻轨、自行车停车场、自行车道)， 芝加哥、明尼阿波利斯和奥克兰在25年的时间里。此外，我们还开发了复杂的 统计模型，用于有目的(而不是随机)地将相关资源放置在 社会环境以及个人有选择地迁徙到靠近这些资源的地方的能力。学习 目标包括：1)开发和验证新的细粒度措施，以捕获介绍、翻新和 关闭代表以下方面的变化：a)公园、步道和其他娱乐场所；b)食物环境；以及 C)运输基础设施将同时与CARDIA调查对象的地理位置相联系 25年以上的地点；以及2)使用这一独特的数据源，估计介绍的影响， 翻新和关闭关键的食品和活动设施以及关于饮食和活动的交通基础设施 在过去25年中，四个野外城市的行为、体重和心脏代谢风险，同时占 食物和活动设施的内生放置和选择性迁徙。我们将特别关注 跨个人水平的种族、收入和教育群体的比较，以检查环境因素如何 从青壮年到中年，饮食、肥胖和心脏代谢风险方面的种族和SES不平等都会造成这种情况。 这项拟议中的研究将提高目前对社会责任机制的理解 环境(特别是更广泛的社会、经济和环境背景)影响健康结果。

ABSTRACT While observational research suggests an association between obesity-related social environment factors with obesity and cardiometabolic risk factors, very little research has addressed the specific factors and pathways linking the social environment to cardiometabolic risk. The primary reasons for this lack of research are: 1) lack of high quality data on diet, activity, measured height and weight over time linked to cardiometabolic risk biomarkers; 2) lack of fine-grain longitudinal data on the introduction, renovation, and closure of food- and activity-related environmental features; and 3) lack of complex statistical models examining each piece of the time-dependent, complex system, accounting for the process by which food, activity, and transportation facilities are established and expanded and the potential for individuals to selectively migrate to locate near such facilities. The 25-year, longitudinal Coronary Artery Risk Development in Young Adults (CARDIA) study provides a wide age range, high quality longitudinal, biological, behavioral and anthropometry and biomarker data of CARDIA, geographic diversity, and different patterns and pace of change across the four baseline cities: Birmingham, Chicago, Minneapolis and Oakland. The research team has developed a unique method to use retrospective and contemporary sources to create data on the timing and placement of introductions, renovations, and closures of: 1) food resources (e.g., restaurants, food shopping); 2) recreation facilities (e.g., trails, parks); and 3) transportation infrastructure (e.g., light rail, bike parking, bike paths) in Birmingham, Chicago, Minneapolis, and Oakland over a 25-year period. Furthermore, we have developed sophisticated statistical models that account for purposeful (as opposed to random) placement of relevant resources in the social environment as well as individuals' ability to selectively migrate to locate near such resources. Study objectives include: 1) Develop and validate new fine-grain measures to capture introductions, renovations, and closures representing changes in: a) parks, trails, and other recreational sites; b) food environments; and c) transportation infrastructure that will be contemporaneously linked to CARDIA respondents' geographic locations over 25 years; and 2) Using this unique data source, estimate the effects of introductions, renovations, and closures of key food and activity facilities and transportation infrastructure on diet and activity behaviors, body weight and cardiometabolic risk in the four field cities over 25 years, while accounting for the endogenous placement of food and activity facilities and selective migration. We will specifically focus on comparisons across individual-level race, income, and education groups to examine how environmental factors contribute to race and SES inequalities in diet, obesity, and cardiometabolic risk from young- to mid-adulthood. The proposed research will improve current understanding of the mechanisms through which social environments (specifically broader societal, economic, and environmental contexts) influence health outcomes.