Early Life Precusors of Chronic Disease

项目摘要（见说明）：成人慢性疾病是当今工业化国家和发展中国家的主要公共卫生问题。尽管慢性疾病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，慢性疾病的发病年龄越来越小。该子项目将项目调查员的互补和全面的专业知识汇集在Wave V项目项目中收集的各种多层次数据与早期纵向添加健康数据的创新协作集成中：1)记录临床前慢性疾病风险和坦率疾病在年轻成年期的流行情况；2)评估支持健康和疾病发育起源（DOHaD）范式中慢性疾病出现的三种生命过程模型的证据，包括潜在效应生命过程模型、累积模型和途径生命过程模型。Add Health数据非常适合解决这些问题，因为该研究包含了大量、多样化、具有代表性的样本，具有丰富的健康和健康行为的重复测量（基于调查和生物标志物），社会和物理环境的纵向特征，以及从妊娠到整个生命过程的经验信息。描述性分析将包括从第V波和更早的波中产生衍生变量（如BMI）和构建变量（如适应负荷），并根据关键人口统计数据（如生物性别、种族/民族、社会经济地位和地理区域）记录慢性病风险和疾病发病率和流行程度的人口水平。评估DOHaD模型将需要多种方法来解决各自的假设，包括结构方程建模和潜在类别增长模型，以按类型聚集受访者特定的轨迹。模型将纳入个别时变风险指标和累积风险综合指数。这些目标的完成将把青壮年健康和疾病风险与妊娠、童年和青春期的身体和社会暴露联系起来，从而改变对导致慢性疾病的累加性和相互作用途径的认识，对预防和干预工作具有重要意义。

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.