Geographic Trends And Disparities In Psychosocial Wellbeing, Health Behaviors, And Mortality In Midlife

近几十年来，美国中年死亡率大幅上升，结束了预期寿命的增长 2010年左右，并在2014年后引发下降。COVID-19疫情加剧了这一趋势。 这种增长最明显的特征之一是其地理模式。它在中西部地区已经被宣布， 南部各州、农村地区和小城市。解释这些日益增长的地理差异是一个 这是确定总体中年死亡率上升的病因的必要步骤。的总体目标 该项目旨在评估州政策背景和县经济背景如何共同预测增长 1）全因中年死亡率，2）中年死亡率的主要趋势驱动死亡原因的地理差异： 自杀、药物过量、酒精引起的原因和心脏代谢疾病，以及3）心理社会和健康 这些死亡原因的行为风险因素该项目回答了有关日益增长的 中年死亡率的地理差异一直是理解他们的主要障碍。一个问题 考虑到国家和地方背景的集体影响。研究往往侧重于国家或地方背景， 提供不完整的解释。我们通过同时检查州和地方环境来推进这项工作， 这是关键的，因为它们可以通过独立和协同的过程影响死亡率。第二个问题 涉及国家政策“背景”的影响。各州制定了高度相关或“捆绑”的政策， 这需要新的方法来理解它们对死亡率的影响。我们推进这项工作， 使用创新方法为可解释的政策包制定年度分数。第三个问题涉及 州和地方背景共同预测个人心理社会健康的程度， 健康行为-即，中年人口增长背后的四大死亡原因的直接决定因素 mortality.去工业化，好工作的减少，以及随之而来的对家庭和社区的破坏， 有些地方可能会损害中年人的心理健康，特别是那些没有4年 大学学历，导致消费毒品，酒精和不健康的食物。我们推进这项工作， 研究州和地方环境如何共同预测心理社会和健康行为风险因素， 四大死因该项目将通过三个具体目标实现其目标。目标1确定 国家政策和县经济背景如何共同预测县级死亡率（所有原因和 1990-2025年所有中年人的四个具体原因），并按年龄、性别、种族-民族、教育和 地铁状况。目标2确定了国家政策和县经济背景如何共同预测个人层面 2021-2025年的心理社会和健康行为风险因素，并检查假设的途径， 所有中年人，按年龄、性别、种族/民族、教育和都市状况分类。Aim 3合并了100+年度 通过UM的虚拟数据飞地，将州和县的测量数据转换为多个地理编码调查。我们将 还通过ICPSR传播数据、文件和代码，并提供关于这些资源的研讨会。

The rise in U.S. midlife mortality in recent decades has been substantial, ending the increase in life expectancy around 2010 and triggering its decline after 2014. The trend has been exacerbated by the COVID-19 pandemic. One of the most telling features of the rise is its geographic pattern. It has been pronounced in Midwestern and Southern states and in rural areas and small cities. Explaining these growing geographic disparities is a necessary step toward identifying the etiologies of rising midlife mortality overall. The overarching objective of this project is to assess how state policy contexts and county economic contexts collectively predict growing geographic disparities in 1) all-cause midlife mortality, 2) major trend-driving causes of death for midlife mortality: suicide, drug overdose, alcohol-induced causes, and cardiometabolic diseases, and 3) psychosocial and health behavior risk factors for those causes of death The project answers key unresolved questions about the growing geographic disparities in midlife mortality that have been major obstacles to understanding them. One question regards the collective influence of state and local contexts. Studies tend to focus on state or local contexts, providing an incomplete explanation. We advance this work by examining state and local contexts concomitantly, which is critical because they may affect mortality via independent and synergistic processes. A second question concerns the influence of states’ policy “contexts”. States have enacted highly correlated, or “bundled”, policies which necessitates new approaches for understanding their influence on mortality. We advance this work by using innovative methods to develop annual scores for interpretable policy bundles. A third question concerns the degree to which state and local contexts collectively predict individual-level psychosocial wellbeing and health behaviors—i.e., the proximate determinants of the four major causes of death behind rising midlife mortality. Deindustrialization, declines in good jobs, and concomitant disruptions to families and communities in some places may have harmed the psychosocial wellbeing of midlife adults, particularly those without a 4-year college degree, leading to consumption of drugs, alcohol, and unhealthy food. We advance this work by examining how state and local contexts collectively predict psychosocial and health behavior risk factors for the four major causes of death. The project will accomplish its objective through three Specific Aims. Aim 1 identifies how state policy and county economic contexts collectively predict county-level mortality (from all causes and the four specific causes) from 1990-2025 for all midlife adults and by age, sex, race-ethnicity, education, and metro status. Aim 2 identifies how state policy and county economic contexts collectively predict individual-level psychosocial and health behavior risk factors from 2021-2025, and examines hypothesized pathways, among all midlife adults and by age, sex, race/ethnicity, education, and metro status. Aim 3 merges the 100+ annual state and county measures into multiple geocoded surveys available via the UM’s Virtual Data Enclave. We will also disseminate the data, documentation, and code via ICPSR and offer workshops on these resources.