Decomposing County-Level Working-Age Mortality Trends in the United States Between 1999-2001 and 2015-2017.
Decomposing County-Level Working-Age Mortality Trends in the United States Between 1999-2001 and 2015-2017.
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DOI：
10.1007/s40980-021-00095-6
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发表时间：
2022-04
影响因子：
1.9
通讯作者：
Elo, Irma T.
中科院分区：
文献类型：
--
作者：
Graetz, Nick;Elo, Irma T.
关键词：
研究表明，近几十年来美国的死亡率存在显著的地理差异。然而，很少有研究调查了县级死亡率趋势在多大程度上可以用国家、州和大都市水平的趋势来解释，以及哪些县特有的因素导致了剩余的变化。结合死亡人口统计数据和人口普查数据以及时变的县级背景特征，我们使用空间显式贝叶斯分层模型分析了2000年至2017年间工作年龄死亡率、州、大都市地位和县级社会经济条件、家庭特征、劳动力市场条件、健康行为和人口特征之间的关系。此外，我们采用Shapley分解来说明每个变化的县级特征对1999-2001年和2015-2017年期间观察到的美国县死亡率变化的附加贡献，超过了全国、州和大都市-非大都市死亡率趋势。死亡率趋势因州和城市而异，县级特征的贡献也是如此。与居住的州相比，大都市的地位更能预测县一级的死亡率差异。在县一级的特征中，大学毕业生百分比、吸烟率和外国出生人口百分比的变化促成了这一时期全因死亡率的下降，而贫困、失业和单亲家庭水平的增加以及制造业就业的下降减缓了这些改善，并且在许多非大都市地区，这些变化大到足以压倒保护因素的积极贡献。
Studies have documented significant geographic divergence in U.S. mortality in recent decades. However, few studies have examined the extent to which county-level trends in mortality can be explained by national, state, and metropolitan-level trends, and which county-specific factors contribute to remaining variation. Combining vital statistics data on deaths and Census data with time-varying county-level contextual characteristics, we use a spatially explicit Bayesian hierarchical model to analyze the associations between working-age mortality, state, metropolitan status and county-level socioeconomic conditions, family characteristics, labor market conditions, health behaviors, and population characteristics between 2000 and 2017. Additionally, we employ a Shapley decomposition to illustrate the additive contributions of each changing county-level characteristic to the observed mortality change in U.S. counties between 1999–2001 and 2015–2017 over and above national, state, and metropolitan–nonmetropolitan mortality trends. Mortality trends varied by state and metropolitan status as did the contribution of county-level characteristics. Metropolitan status predicted more of the county-level variance in mortality than state of residence. Of the county-level characteristics, changes in percent college-graduates, smoking prevalence and the percent of foreign-born population contributed to a decline in all-cause mortality over this period, whereas increasing levels of poverty, unemployment, and single-parent families and declines manufacturing employment slowed down these improvements, and in many nonmetropolitan areas were large enough to overpower the positive contributions of the protective factors.
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DOI：
10.1001/jama.2016.4226
发表时间：
2016-04-26
期刊：
JAMA
影响因子：
--
作者：
Chetty R;Stepner M;Abraham S;Lin S;Scuderi B;Turner N;Bergeron A;Cutler D
通讯作者：
Cutler D
DOI：
10.1016/s0140-6736(17)31758-0
发表时间：
2017-11-11
期刊：
Lancet (London, England)
影响因子：
--
作者：
Golding N;Burstein R;Longbottom J;Browne AJ;Fullman N;Osgood-Zimmerman A;Earl L;Bhatt S;Cameron E;Casey DC;Dwyer-Lindgren L;Farag TH;Flaxman AD;Fraser MS;Gething PW;Gibson HS;Graetz N;Krause LK;Kulikoff XR;Lim SS;Mappin B;Morozoff C;Reiner RC Jr;Sligar A;Smith DL;Wang H;Weiss DJ;Murray CJL;Moyes CL;Hay SI
通讯作者：
Hay SI
影响因子：
10.7
作者：
Chetty, Raj;Hendren, Nathaniel;Katz, Lawrence F.
通讯作者：
Katz, Lawrence F.
影响因子：
7.7
作者：
Blue, Laura;Fenelon, Andrew
通讯作者：
Fenelon, Andrew
影响因子：
3.6
作者：
ANSELIN, L
通讯作者：
ANSELIN, L