Genetic Risk, Pathways to Adulthood, and Health Inequalities

描述（由申请人提供）：本项目将研究遗传因素影响一系列行为和社会事件的方式，这些行为和社会事件最终会造成青年期的健康不平等。这些遗传因素包括与多巴胺能和血清素能系统相关的等位基因，健康因素包括高血压、糖尿病、肥胖和高胆固醇血症的生物标志物。拟议的研究将审查将这些遗传风险因素和健康指标联系起来的社会机制，特别强调教育过程和成就、青年角色的社会融合以及与健康有关的行为。我们还将研究可能减弱风险途径的社会资本和控制形式的保护能力。数据来自全国青少年健康纵向调查（Add Health）的四波，这是一个具有全国代表性的数据集（nh15600，涵盖11岁至32岁），其中包括新发布的遗传数据和健康生物标志物。从这种规模的研究中获得的纵向社会数据与生物标本相结合，提供了一个前所未有的机会，可以检查与年轻人角色相关的遗传风险、社会经济成就和压力因素如何与健康不平等的出现联系起来。首先，我们研究了SES-健康梯度模型，该模型将原生家庭的社会经济地位、青春期的健康和健康相关行为、青年期的社会经济成就和角色以及健康的生物标志物联系起来。其次，我们扩展了这些模型来检验基因-环境相关性，根据这些相关性，ses -健康梯度过程反映了与多巴胺能和血清素能系统相关的行为倾向。这些分析将描述神经遗传因素、教育过程和社会角色与健康不平等相关的冥想社会过程。第三，我们将检查基因-环境的相互作用，根据社会资本和控制促进福祉青年成年尽管遗传风险因素。因此，这些分析将揭示早期健康不平等如何反映遗传和社会因素的纵向相互作用。

DESCRIPTION (provided by applicant): This project will examine the ways in which genetic factors influence a cascade of behaviors and social events that ultimately create health inequalities in young adulthood. Such genetic factors include alleles associated with the dopaminergic and serotonergic systems and health factors include biomarkers of hypertension, diabetes, obesity, and hypercholesterolemia. The proposed research will examine social mechanisms that link these genetic risk factors and indicators of health with special emphasis on educational processes and attainment, social integration into young adult roles, and health-related behaviors. We will also examine the protective capacity of forms of social capital and control that may attenuate pathways of risk. Data come from four waves of the National Longitudinal Survey of Adolescent Health (Add Health), a nationally representative dataset (nH15,600, spanning ages 11 to 32) that will include newly-released genetic data and biomarkers of health. The combination of longitudinal social data with biological specimens from a study of this size provides an unprecedented opportunity to examine how genetic risks, socioeconomic achievements, and stressors associated with young adult roles are linked to the emergence of health inequalities. First, we examine SES- health gradient models that link socioeconomic status of the family-of-origin, health and health- related behaviors in adolescence, socioeconomic attainments and roles in young adulthood, and biomarkers of health. Second, we extend these models to examine gene-environment correlations according to which SES-health gradient processes reflect behavioral predispositions associated with the dopaminergic and serotonergic systems. These analyses will describe the meditational social processes by which neurogenetic factors, educational processes, and social roles are associated with inequalities in health. Third, we will examine gene-environment interactions according to which social capital and control promote well-being in young adulthood despite genetic risk factors. The analyses will thus shed light on how early health inequalities reflect the longitudinal interplay of genetic and social factors.