US County-Level Trends in Mortality Rates for Major Causes of Death, 1980-2014
US County-Level Trends in Mortality Rates for Major Causes of Death, 1980-2014
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DOI：
10.1001/jama.2016.13645
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发表时间：
2016-12-13
影响因子：
120.7
通讯作者：
Murray, Christopher J. L.
中科院分区：
文献类型：
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作者：
Dwyer-Lindgren, Laura;Bertozzi-Villa, Amelia;Murray, Christopher J. L.
重要性按死因分类的县级死亡率模式尚未得到系统描述，但对公共卫生官员、临床医生、以及寻求改善健康和减少地理差异的研究人员。水平估计，并估计1980年至2014年美国各县21种相互排斥的死亡原因的年死亡率。设计，地点，和参与者垃圾代码的再分配方法（不可信或不够具体的死因代码）和小区域估计方法（估计小亚群死亡率的统计方法）应用于国家生命统计系统的死亡登记数据，以估计21种死因的年度县级死亡率。对这些估计数进行了排序（按沿着多个维度进行调整），以确保各种原因之间的一致性以及与现有国家一级估计数的一致性。确定了2014年年龄标准化死亡率的地理模式以及1980年至2014年10个最高负担原因的年龄标准化死亡率变化。暴露居住县。主要结果和指标原因特异性年龄标准化死亡率。结果从1980年1月1日起，共有80 412 524人死亡，其中10人死亡。截至2014年12月31日，在美国。其中，1940万人被分配了垃圾代码。死亡率分析了3110个县或县组。每个原因的县之间差异都很明显，90年代和10年代县之间年龄标准化死亡率的差距从每10万人口14.0例死亡（肝硬化和慢性肝病）到每10万人口147.0例死亡（心血管疾病）不等。死亡率升高的地理区域因原因而异：例如，心血管疾病死亡率沿着密西西比河南半部最高，而自残和人际暴力的死亡率在西南部各县升高，慢性呼吸道疾病的死亡率在肯塔基州东部和西弗吉尼亚州西部最高。在1980年至2014年期间，各州的死因死亡率变化也存在很大差异。对于大多数原因（例如，肿瘤，神经系统疾病，自我伤害和人际暴力），在县级死亡率的增加和减少都observed.Conclusions和相关性在1980年至2014年的美国特定原因县级死亡率的分析中，每种死亡原因都存在很大的县间差异，尽管地理模式因死亡原因而变化很大。本研究中使用的小区域模型县级分析方法有可能为美国疾病特异性死亡时间趋势及其在地理区域之间的差异提供新的见解。
IMPORTANCE County-level patterns in mortality rates by cause have not been systematically described but are potentially useful for public health officials, clinicians, and researchers seeking to improve health and reduce geographic disparities.OBJECTIVES To demonstrate the use of a novel method for county-level estimation and to estimate annual mortality rates by US county for 21 mutually exclusive causes of death from 1980 through 2014.DESIGN, SETTING, AND PARTICIPANTS Redistribution methods for garbage codes (implausible or insufficiently specific cause of death codes) and small area estimation methods (statistical methods for estimating rates in small subpopulations) were applied to death registration data from the National Vital Statistics System to estimate annual county-level mortality rates for 21 causes of death. These estimates were raked (scaled along multiple dimensions) to ensure consistency between causes and with existing national-level estimates. Geographic patterns in the age-standardized mortality rates in 2014 and in the change in the age-standardized mortality rates between 1980 and 2014 for the 10 highest-burden causes were determined.EXPOSURE County of residence.MAIN OUTCOMES AND MEASURES Cause-specific age-standardized mortality rates.RESULTS A total of 80 412 524 deaths were recorded from January 1, 1980, through December 31, 2014, in the United States. Of these, 19.4 million deaths were assigned garbage codes. Mortality rates were analyzed for 3110 counties or groups of counties. Large between-county disparities were evident for every cause, with the gap in age-standardized mortality rates between counties in the 90th and 10th percentiles varying from 14.0 deaths per 100 000 population (cirrhosis and chronic liver diseases) to 147.0 deaths per 100 000 population (cardiovascular diseases). Geographic regions with elevated mortality rates differed among causes: for example, cardiovascular disease mortality tended to be highest along the southern half of the Mississippi River, while mortality rates from self-harm and interpersonal violence were elevated in southwestern counties, and mortality rates from chronic respiratory disease were highest in counties in eastern Kentucky and western West Virginia. Counties also varied widely in terms of the change in cause-specific mortality rates between 1980 and 2014. For most causes (eg, neoplasms, neurological disorders, and self-harm and interpersonal violence), both increases and decreases in county-level mortality rates were observed.CONCLUSIONS AND RELEVANCE In this analysis of US cause-specific county-level mortality rates from 1980 through 2014, there were large between-county differences for every cause of death, although geographic patterns varied substantially by cause of death. The approach to county-level analyses with small area models used in this study has the potential to provide novel insights into US disease-specific mortality time trends and their differences across geographic regions.