Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US.
Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US.
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美国中风过早死亡率的县际差异评估
DOI：
10.1001/jamanetworkopen.2021.4488
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发表时间：
2021-05-03
影响因子：
13.8
通讯作者：
Zheng ZJ
中科院分区：
文献类型：
--
作者：
Song S;Ma G;Trisolini MG;Labresh KA;Smith SC Jr;Jin Y;Zheng ZJ
人口构成、社会经济地位、医疗保健和环境特征以及人口健康与过早卒中死亡率相关吗？在这项横断面研究中，研究了美国各县之间过早卒中死亡率的差异，对于卒中病房外发生的死亡，县级死亡率在很大程度上与人口构成（31.6%）以及医疗保健和环境特征（25.8%）相关。对于院内死亡，29.8%的县级死亡率与人口健康相关，28.7%与人口构成相关。这些发现表明，在对最需要的县实施干预措施之前，需要在县一级制定解决早发卒中的策略。确定与过早中风死亡率相关的因素并测量县间差异可能有助于了解如何减少差异并实现更公平的健康结果。为了检查美国过早卒中死亡率的县间差异，调查与死亡率相关的县级因素，并描述按死亡地点和卒中亚型划分的死亡率差异差异。这项回顾性横断面研究将疾病控制和预防中心 WONDER 数据库中的美国各县的死亡率和人口数据与多个数据库中的县级特征联系起来。结果指标是 1999 年至 2018 年美国 2637 个县 25 至 64 岁成年人的县级年龄调整卒中死亡率。这项研究于 2019 年 4 月 1 日至 2020 年 10 月 31 日进行。拟合广义线性泊松回归来调查与县级死亡率相关的 4 组因素：人口构成、社会经济状况、医疗保健和环境特征以及人口健康。计算泰尔指数评分以评估死亡率差异。中风死亡率是根据数据集中因中风导致的死亡人数来衡量的。卒中病房外死亡被定义为发生在门诊或急诊室或转运前地点的任何死亡。分析中包括五种中风亚型。尽管死亡率从 1999 年到 2018 年没有显着变化（从每 10 万人口 12.62 例增加到 11.81 例），但卒中单位以外的死亡比例从 23.56%（18 369 例中的 4 328 例）增加到 34.57%（20 188 例中的 6 978 例）。据报道，很大一部分原因不明的卒中，大多数死亡（55.20%）发生在卒中单元之外。过早脑卒中死亡率最高的县，其发病率是死亡率最低县的20.78倍（每10万人口中有65.04人死亡，比3.13人死亡）。不明原因中风的县间差异最大。对于卒中单位外死亡，县级死亡率在很大程度上与人口构成（31.6%）以及医疗保健和环境特征（25.8%）相关。对于院内死亡，29.8%的县级死亡率与人口健康相关，28.7%与人口构成相关。这些研究结果表明，在对最需要的县实施干预措施之前，针对导致美国各县死亡率差异的具体因素，特别是卒中单元外死亡和原因不明的卒中，在针对县级具体情况进行调整时，可能会有用。这项横断面研究比较了美国各县中青年人中风死亡的人数和相关因素。
Are demographic composition, socioeconomic status, health care and environmental features, and population health associated with premature stroke mortality? In this cross-sectional study examining the differences in premature stroke mortality in terms of between-county disparity in the US, for deaths that occurred out of the stroke unit, county-level mortality was largely associated with demographic composition (31.6%) and health care and environmental features (25.8%). For in-hospital death, 29.8% of county-level mortality was associated with population health and 28.7% was associated with demographic composition. These findings suggest the need to tailor strategies to address premature stroke in the county-level context before implementing interventions for the neediest counties. Identifying the factors associated with premature stroke mortality and measuring between-county disparities may provide insight into how to reduce variations and achieve more equitable health outcomes. To examine the between-county disparities in premature stroke mortality in the US, investigate county-level factors associated with mortality, and describe differences in mortality disparities by place of death and stroke subtype. This retrospective cross-sectional study linked the mortality and demographic data of US counties from the Centers for Disease Control and Prevention WONDER database to county-level characteristics from multiple databases. The outcome measure was county-level age-adjusted stroke mortality among adults aged 25 to 64 years in 2637 US counties from 1999 to 2018. This study was conducted from April 1, 2019, to October 31, 2020. Generalized linear Poisson regressions were fitted to investigate 4 sets of factors associated with county-level mortality: demographic composition, socioeconomic status, health care and environmental features, and population health. The Theil index score was calculated to assess the mortality disparities. Stroke mortality was measured as the number of deaths attributed to stroke in the data set. Out-of-stroke-unit death was defined as any death occurring in outpatient or emergency departments or at the pretransport location. Five stroke subtypes were included in the analysis. Although mortality did not change substantially from 1999 to 2018 (from 12.62 to 11.81 per 100 000 population), the proportion of deaths occurring out of the stroke unit increased from 23.56% (4328 of 18 369) to 34.57% (6978 of 20 188). A large percentage of stroke of an uncertain cause was reported, with most deaths (55.20%) occurring out of the stroke unit. In the county with the highest premature stroke mortality, the incidence was 20.78 times as high as that in the county with the lowest mortality (65.04 vs 3.13 deaths per 100 000 population). The highest between-county disparities were found for stroke of uncertain cause. For out-of-stroke-unit death, county-level mortality was largely associated with demographic composition (31.6%) and health care and environmental features (25.8%). For in-hospital death, 29.8% of county-level mortality was associated with population health and 28.7% was associated with demographic composition. These findings suggest that strategies addressing specific factors that underlie the mortality disparities among US counties, especially for out-of-stroke-unit death and stroke of uncertain cause, may be useful when tailored to the county-level context before implementing interventions for the neediest counties. This cross-sectional study compares the numbers and factors associated with death due to stroke in younger and middle-aged adults among US counties.
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影响因子：
5.4
作者：
Mochari-Greenberger H;Xian Y;Hellkamp AS;Schulte PJ;Bhatt DL;Fonarow GC;Saver JL;Reeves MJ;Schwamm LH;Smith EE
通讯作者：
Smith EE
1999 年至 2017 年美国各县心源性过早死亡的差异：时间趋势和主要驱动因素
影响因子：
5.4
作者：
Jin Y;Song S;Zhang L;Trisolini MG;Labresh KA;Smith SC Jr;Zheng ZJ
通讯作者：
Zheng ZJ
影响因子：
12.7
作者：
Rossen LM;Schoendorf KC
通讯作者：
Schoendorf KC
影响因子：
3.9
作者：
Hyldgard, Vibe Bolvig;Johnsen, Soren Paaske;Sogaard, Rikke
通讯作者：
Sogaard, Rikke
影响因子：
22.4
作者：
BUDESCU, DV
通讯作者：
BUDESCU, DV