Work-life, Health Habits, and Health: Longitudinal Analysis

社会将受益于更好地理解影响健康的复杂过程。 寿命。特别有用的是，更好地了解可能受到影响的关键因素的作用 通过公共和私人政策。我们将重点关注工作-生活和健康习惯作为健康和 研究他们在一生中是如何与健康互动的。关于工作和生活的早期选择(例如 职业)和健康习惯(开始吸烟、饮酒和肥胖)可以产生持久的影响，因此 会影响以后的健康。 这一建议的总体思路是检查工作-生活之间在生命周期中的动态相互作用， 健康习惯和健康结果。我们将使用几个纵向数据集构建生命周期模型 涵盖了从青春期到晚年的年龄范围。我们的模型旨在评估关联和潜力 这些因素之间存在多向因果关系。我们将通过衔接方法来实现我们的目标 以最好地解决我们的研究问题。 具体目标1：分析劳动力市场经历和健康习惯作为老年健康的决定因素， 并调查静态测量和动态过程哪个更好地描述这些特性。 具体目标2：模拟源自目标1的主要风险因素之间的相互作用，认识到和 建模哪些因素是预先确定的，哪些是生命周期中不同时间点的因果关系。允许 对于劳动力市场变量、健康习惯和健康结果之间的多方向性，以及 这些与年龄的关系。 具体目标3：确定目标1和目标2中确定的关系是否存在差异 在健康指标、种族和性别亚群中。使用多个数据集来评估 调查结果的稳健性。 具体目标4：根据我们的调查结果，确定关键的公共和私人政策，特别是在早期 在生活中，对健康的轨迹有重要的影响，导致长寿和高功能的寿命。 向学术受众传播研究成果，并将研究成果翻译为更广泛的受众 可以从这些知识中受益的观众。 将使用的主要数据集是：收入动态小组研究(PSID)和健康 和退休研究(MRS)。我们还将使用国家青年纵向研究(NLSY)和 关注年轻人和老年人的高龄老年人资产和健康动态研究 分别是个人。这些纵向数据集一起覆盖了寿命，每个数据集都包含 衡量健康、健康习惯和劳动力市场特征的指标。

Society would benefit from a better understanding of the complicated processes that affect health over the life span. Particularly useful would be a better understanding of the role of key factors that can be influenced by public and private policy. We will focus on work-life and health habits as key determinants of health and examine how they interact with health over the life course. Early choices with regard to work-life (e.g. occupation) and health habits (initiation of smoking, drinking, and obesity) can have durable effects and thus can affect later health. The overallaim of this proposal is to examine the dynamic interplay over the life cycle among work-life, health habits, and health outcomes. Wewill build a life cycle model using several longitudinal datasets covering the age range from adolescence to late life. Our model aims to assess associations and potential multidirectional causality among these factors. We will accomplish our goals by bridging methodologies across disciplines to best address our research questions. Specific Aim 1: Analyze labor market experiences and health habits as determinants of health in old age, and investigate whether these are better characterized by static measures or dynamic processes. Specific Aim 2: Model the interplay among the principalrisk factors derived from Aim 1, recognizing and modeling which factors are pre-determined and which are causal at different points in the life cycle. Allow for multi-directionality among labor market variables, health habits, and health outcomes, and changes in these relationships with age. Specific Aim 3: Determine whether there are differences in the relationships identified in Aims 1 and 2 across health measures and race and gender sub-populations. Usemultiple datasets to assessthe robustness of findings. Specific Aim 4: Based on our findings, identify key public and private policies that could, especially early in life, have important impacts on the trajectory of health leading to a long and high functioning life. Disseminate findings to academic audiences andtranslate findings to be more accessible to broader audiences who could benefit from the knowledge. The primary datasets that will be used are: the Panel Study of Income Dynamics (PSID) and the Health and Retirement Study (MRS). We will also use the National Longitudinal Study of Youth (NLSY) and the Study of Assets and Health Dynamics among the Oldest Old (AHEAD) to focus on younger and older individuals, respectively. Together these longitudinal datasets cover the life span and each contains measures of health, health habits and labor market characteristics.