Leveraging a Natural Experiment to Estimate the Effects of School Racial Segregation on Cardiovascular Risk Factors among Youth and Young Adults

利用自然实验来评估学校种族隔离对青少年和年轻人心血管危险因素的影响

• 批准号: 10456634
• 负责人: Rita Hamad
• 金额: $ 76.5万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10456634
• 关键词: Address; Adolescence; Adolescent; Adult; Affect; Age; Behavior; Biological Markers; Black race; Cardiovascular Diseases; Characteristics; Child; Childhood; Chronic stress; Clinical; Cognition; Cohort Studies; Complex; Counseling; Country; Court Decisions; Data; Data Set; Desegregation; Development; Diabetes Mellitus; Discrimination; Disease Outcome; Economics; Education; Family Characteristics; Future; Gender; Genetic; Goals; Health; Health behavior; Heart Diseases; Hour; Hypertension; Income; Individual; Intervention; Knowledge; Life; Life Cycle Stages; Life Stress; Light; Link; Literature; Logistics; Long-Term Effects; Longitudinal Studies; Measures; Mediating; Mental Health; Methodology; National Heart, Lung, and Blood Institute; National Longitudinal Survey of Adolescent to Adult Health; Natural experiment; Obesity; Occupational; Outcome; Outcomes Research; Pathway interactions; Persons; Physical activity; Population; Preventive; Public Health; Quasi-experiment; Race; Reporting; Research; Risk Factors; Schools; Smoking; Socioeconomic Status; Specific qualifier value; Stress; Subgroup; Techniques; Testing; Vulnerable Populations; Work; Youth; archive data; archived data; base; black/white disparity; cardiovascular disorder risk; cardiovascular risk factor; community intervention; data archive; design; disparity reduction; forest; health care availability; high risk; improved; innovation; insight; machine learning method; middle age; novel marker; panel study of income dynamics; peer influence; peer networks; physical inactivity; programs; psychologic; racial disparity; resilience; response; school district; segregation; social; social norm; socioeconomics; teenage fertility; theories; treatment effect; trend; young adult

ABSTRACT Cardiovascular disease (CVD) risk factors disproportionately affect black adults, and these disparities are evident early in the life course. Genetic factors do not appear to explain this difference, and studies have increasingly implicated socioeconomic risk factors. Among the most prominent risk factors for racial disparities in CVD is educational attainment, which is strongly correlated with smoking, hypertension, and CVD over the life course. Yet it is unclear which aspects of schooling are most salient. One possible explanation for racial disparities in CVD is that black youth often attend highly racially segregated schools. Segregation is thought to be linked with CVD due to increased stress and discrimination; social norms and peer influence; and the constraining of socioeconomic opportunities that reduces income and healthcare access later in life. Yet despite the fact that school segregation has increased in recent years, there are no studies examining the effects of recent school segregation trends on CVD risk factors. The goal of this study is to provide this urgently needed evidence. In particular, we take advantage of a unique natural experiment, overcoming methodological challenges in the previous literature on the effects of education on CVD. Since 1990, numerous local court decisions have resulted in “resegregation” in school districts across the country. We link nationwide data on these court decisions and school district-level measures of school segregation with CVD outcome data from two large nationally representative U.S. cohort studies of affected youth: the National Longitudinal Study of Adolescent to Adult Health (Add Health, N≈90,000) and the Panel Study of Income Dynamics (N≈8,000). We employ the quasi-experimental technique of instrumental variables analysis, which reduces typical confounding by factors such as unobserved individual and family characteristics. In Aim 1, our goal is to estimate the short- term effects of school segregation on CVD risk factors—including smoking, physical activity, obesity, and mental health—among youth while they are still in school. In Aim 2, we will examine the long-term effects of school segregation in the decades that follow, with outcomes including those in Aim 1 in addition to objectively measured CVD biomarkers, diabetes, and hypertension. We will also undertake exploratory analyses to determine possible mediating pathways. In Aim 3, we will identify vulnerable subgroups whose development of CVD risk factors differs in response to school racial segregation. This will enable future interventions to be tailored to the most vulnerable individuals. We will employ both hypothesis-driven and hypothesis-generating statistical techniques, including innovative machine learning methods that allow for more complex and robust subgroup identification. Overall, the expected outcome of this research is to produce rigorous evidence on the effects of school racial segregation on CVD risk factors, helping to inform school-based, clinical, and community interventions to reduce persistent and inequitable racial disparities in CVD.

抽象的 心血管疾病 (CVD) 危险因素对黑人成年人的影响尤为严重，而这些差异是 在生命历程的早期就很明显。遗传因素似乎无法解释这种差异，研究表明 社会经济风险因素日益复杂化。种族差异最突出的风险因素之一 CVD 中最重要的是受教育程度，它与吸烟、高血压和 CVD 密切相关。 生命历程。然而，尚不清楚学校教育的哪些方面最为突出。种族的一种可能解释 CVD 的差异在于黑人青少年经常就读高度种族隔离的学校。隔离被认为 由于压力和歧视增加而与心血管疾病相关；社会规范和同伴影响；和 社会经济机会受到限制，从而减少了晚年的收入和医疗保健机会。然而 尽管近年来学校隔离有所增加，但没有研究检验 最近的学校隔离趋势对 CVD 危险因素的影响。本研究的目的是提供这一 急需证据。特别是，我们利用独特的自然实验，克服了 先前关于教育对心血管疾病影响的文献中的方法论挑战。自1990年以来，无数 地方法院的裁决导致全国各地学区出现“重新隔离”。我们链接全国 这些法院判决的数据和学区级学校隔离措施以及 CVD 结果数据 来自两项针对受影响青少年的具有全国代表性的美国大型队列研究：国家纵向研究 青少年到成人健康（添加健康，N≈90,000）和收入动态小组研究（N≈8,000）。我们 采用工具变量分析的准实验技术，减少了典型的混杂因素 受诸如未观察到的个人和家庭特征等因素的影响。在目标 1 中，我们的目标是估计短期 学校隔离对心血管疾病危险因素的长期影响——包括吸烟、体力活动、肥胖和 心理健康——青少年在校期间的心理健康。在目标 2 中，我们将研究以下措施的长期影响： 在接下来的几十年里，学校隔离的结果除了客观上之外还包括目标 1 中的结果 测量了 CVD 生物标志物、糖尿病和高血压。我们还将进行探索性分析 确定可能的中介途径。在目标 3 中，我们将确定弱势群体，其发展 CVD 危险因素因学校种族隔离而异。这将使未来的干预措施能够 为最弱势群体量身定制。我们将同时采用假设驱动和假设生成 统计技术，包括创新的机器学习方法，可以实现更复杂、更稳健的计算 亚组识别。总体而言，这项研究的预期结果是提供严格的证据 学校种族隔离对 CVD 危险因素的影响，有助于为学校、临床和医疗机构提供信息 社区干预措施，以减少心血管疾病方面持续存在和不公平的种族差异。