Early Life Precusors of Chronic Disease

项目摘要(见说明)：成人慢性病是当今工业化世界和发展中国家的主要公共卫生问题。尽管通常与老年人的衰老和健康有关，但越来越多的证据表明，在美国，慢性病开始于较年轻的年龄。这个子项目汇集了项目研究人员互补和全面的专业知识，创新地整合了在第五波项目中收集的不同的多层次数据与早期的纵向添加健康数据：1)记录临床前慢性病风险和坦率的疾病在青壮年的流行情况，以及2)评估支持在健康与疾病发展起源(DOHaD)范式中出现慢性病的三种生命历程模型的证据，包括潜在影响生命历程模型、累积模型和路径生命历程模型。ADD Health Data非常适合于实现这些目标，因为这项研究包含了一个具有代表性的大样本，其中包含对健康和健康行为的丰富重复测量(调查和基于生物标记物的)、社会和物理环境的纵向特征以及整个生命过程中孕育的经验信息。描述性分析将包括从V波和更早的波产生的衍生变量(例如，BMI)和构造变量(例如，平衡负荷)，以及根据生物性别、种族/族裔、社会经济地位和地理区域等关键人口统计数据，记录慢性病风险和疾病发生率和流行率的人口水平。评估DOHaD模型将需要多种适合于解决其各自假设的方法，包括结构方程建模和潜在班级增长模型，以按类型对受访者特定的轨迹进行分类。模型将纳入单独的时变风险指标和累积风险的综合指数。完成这些目标将通过将年轻人的健康和疾病风险与孕期、儿童期和青春期期间发生的身体和社会暴露联系起来，转变关于导致慢性病的相加和互动途径的知识，对预防和干预工作具有重要影响。

PROJECT SUMMARY (See instructions): Adult chronic disease is the major public health problem of both the industrialized and developing world today. Although typically associated with aging and health of the elderly, there is mounting evidence that chronic conditions are beginning at younger ages in the US. This subproject brings together complementary and comprehensive expertise of program project investigators in an innovative collaborative integration of the diverse multilevel data collected in the Wave V Program Project with earlier longitudinal Add Health data: 1) to document the prevalence of preclinical chronic disease risk and frank disease in young adulthood, and 2) to evaluate evidence supporting three life course models of chronic disease emergence within the Developmental Origins of Health and Disease (DOHaD) paradigm, including the Latent Effects Life Course Model, the Cumulative Model, and the Pathways Life Course Model. Add Health data are uniquely suited to address these aims because the study encompasses a large, diverse, representative sample with rich repeated measures (survey and biomarker based) of health and health behavior, longitudinal characterization of social and physical environments, and experiential information from gestation across the life course. Descriptive analyses will include production of derived (e.g., BMI) and constructed variables (e.g., allostatic load) from Wave V and earlier waves, and documentation of population levels of chronic disease risk and incidence and prevalence of disease according to key demographics such as biological sex, race/ethnicity, SES, and geographical region. Evaluating DOHaD models will entail multiple approaches suited to address their respective hypotheses, including structural equation modeling and latent class growth models to cluster respondent-specific trajectories by type. Models will incorporate individual time-varying risk indicators and aggregated indices of cumulative risk. Completion of these aims will transform knowledge on the additive and interactive pathways leading to chronic disease by linking young adult health and disease risk to physical and social exposures that occur during gestation, childhood, and adolescence, with vital implications for prevention and intervention efforts.