UNASSIGNED: Using data from five survey waves (1998-2006) of the General Social Survey-National Death Index dataset and the County Presidential Election Return 2000 dataset, we fit weighted Cox proportional hazards models to estimate the associations between (1) political group density and (2) partisan polarization measured at the county level in 2000 (n = 313 counties) categorized into quartiles with individual-level mortality (n = 14,983 participants) from all causes and CHD, controlling for individual- and county-level factors. Maximum follow-up was from one year after the survey up until 2014. We conducted these analyses using two separate measures based on county-level vote share differences and party affiliation ideological extremes.
UNASSIGNED: In the overall sample, we found no evidence of associations between county-level political group density and individual-level mortality from all causes. There was evidence of a 13% higher risk of dying from heart disease in the highest quartile of county-level polarization (hazards ratio, HR = 1.13; 95% CI = 0.74-1.71). We observed heterogeneity of effects based on individual-level political affiliation. Among those identifying as Democrats, residing in counties with high (vs. low) levels of polarization appeared to be protective against mortality, with an associated 18% lower risk of dying from all causes (HR = 0.82, 95% CI = 0.71-0.94). This association was strongest in areas with the highest concentrations of Democrats.
UNASSIGNED: Among all study participants, political group density and polarization at the county level in 2000 were not linked to individual-level mortality. At the same time, we found that Democratic party affiliation may be protective against the adverse effects of high polarization, particularly in counties with high concentrations of Democrats. Future research should further explore these associations to potentially identify new structural interventions to address political determinants of population health.
■使用来自一般社会调查-国家死亡指数数据集和县总统选举回归2000数据集的五个调查波(1998-2006)的数据,我们拟合了加权Cox比例风险模型,以估计(1)政治团体密度和(2)在2000年县级(n=313个县)测量的党派两极分化之间的关联,分为四分位数与个人水平的死亡率(n=14,983名参与者)来自所有原因和CHD,控制个人和县级因素。最大的随访时间是从调查后的一年到2014年。我们根据县级投票份额差异和政党隶属意识形态极端情况,使用两种单独的方法进行了这些分析。
■在整个样本中,我们没有发现县级政治团体密度和个体层面的全因死亡率之间存在关联的证据.有证据表明,在县级极化的最高四分位数中,死于心脏病的风险增加了13%(危险比,HR=1.13;95%CI=0.74-1.71)。我们观察到基于个人层面政治派别的效应异质性。在那些被认定为民主党人的人中,居住在高县(vs.低)两极分化水平似乎对死亡率有保护作用,所有原因导致死亡的风险降低18%(HR=0.82,95%CI=0.71-0.94)。在民主党人最集中的地区,这种联系最为强大。
■在所有研究参与者中,2000年县级的政治群体密度和两极分化与个体死亡率无关.同时,我们发现,民主党的隶属关系可能对高度两极分化的不利影响有保护作用,特别是在民主党高度集中的县。未来的研究应进一步探索这些关联,以确定新的结构性干预措施,以解决人口健康的政治决定因素。