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首页> 外文期刊>The Lancet Public Health >Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015
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Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015

机译：1990-2014年，美国华盛顿州金县附近居民的平均预期寿命和死亡率差异：2015年全球疾病负担研究的人口普查水平分析

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Summary Background Health outcomes are known to vary at both the country and local levels, but trends in mortality across a detailed and comprehensive set of causes have not been previously described at a very local level. Life expectancy in King County, WA, USA, is in the 95th percentile among all counties in the USA. However, little is known about how life expectancy and mortality from different causes of death vary at a local, neighbourhood level within this county. In this analysis, we estimated life expectancy and cause-specific mortality within King County to describe spatial trends, quantify disparities in mortality, and assess the contribution of each cause of death to overall disparities in all-cause mortality. Methods We applied established so-called garbage code redistribution algorithms and small area estimation methods to death registration data for King County to estimate life expectancy, cause-specific mortality rates, and years of life lost (YLL) rates from 152 causes of death for 397 census tracts from Jan 1, 1990, to Dec 31, 2014. We used the cause list developed for the Global Burden of Disease 2015 study for this analysis. Deaths were tabulated by age group, sex, census tract, and cause of death. We used Bayesian mixed-effects regression models to estimate mortality overall and from each cause. Findings Between 1990 and 2014, life expectancy in King County increased by 5·4 years (95% uncertainty interval [UI] 5·0–5·7) among men (from 74·0 years [73·7–74·3] to 79·3 years [79·1–79·6]) and by 3·4 years (3·0–3·7) among women (from 80·0 years [79·7–80·2] to 83·3 years [83·1–83·5]). In 2014, life expectancy ranged from 68·4 years (95% UI 66·9–70·1) to 86·7 years (85·0–88·2) for men and from 73·6 years (71·6–75·5) to 88·4 years (86·9–89·9) for women among census tracts within King County. Rates of YLL by cause also varied substantially among census tracts for each cause of death. Geographical areas with relatively high and relatively low YLL rates differed by cause. In general, causes of death responsible for more YLLs overall also contributed more significantly to geographical inequality within King County. However, certain causes contributed more to inequality than to overall YLLs. Interpretation This census tract-level analysis of life expectancy and cause-specific YLL rates highlights important differences in health among neighbourhoods in King County that are masked by county-level estimates. Efforts to improve population health in King County should focus on reducing geographical inequality, by targeting those health conditions that contribute the most to overall YLLs and to inequality. This analysis should be replicated in other locations to more fully describe fine-grained local-level variation in population health and contribute to efforts to improve health while reducing inequalities. Funding John W Stanton and Theresa E Gillespie.
机译：发明背景众所周知，健康结果在国家和地方两级都有所不同，但是以前在非常本地的水平上并未详细描述过一系列详细而全面的原因的死亡率趋势。美国华盛顿州金县的预期寿命在美国所有县中排名第95％。但是，对于这个县内地方，社区一级的不同死亡原因的预期寿命和死亡率如何变化知之甚少。在此分析中，我们估算了金县的预期寿命和特定原因的死亡率，以描述空间趋势，量化死亡率差异，并评估每种死亡原因对全因死亡率中总体差异的贡献。方法我们将建立的所谓垃圾代码重新分配算法和小面积估计方法应用于金县的死亡登记数据，以估计397个死因中的152个死因的预期寿命，特定原因的死亡率和寿命损失率（YLL）从1990年1月1日至2014年12月31日进行的人口普查。我们使用针对2015年全球疾病负担研究开发的原因清单进行了分析。按照年龄，性别，人口普查和死亡原因对死亡进行列表。我们使用贝叶斯混合效应回归模型来估计总体死亡率以及每个病因的死亡率。调查结果1990年至2014年之间，金县的男性预期寿命增长了5·4年（95％不确定区间[UI] 5·0-5·7）（从74·0岁[73·7–74·3]）至女性的79.3岁[79·1–79·6]）​​和3至4年（3·0–3·7）（从80·0岁[79·7–80·2]到83· 3年[83·1–83·5]。 2014年，男性的预期寿命从68·4岁（95％UI 66·9–70·1）到86·7岁（85·0–88·2）和73·6岁（71·6–9）不等。在金县的人口普查区中，女性的年龄为75·5）至88·4岁（86·9–89·9）。在每个死亡原因的人口普查范围内，按原因分类的YLL率也有很大差异。 YLL率相对较高和相对较低的地理区域因原因而有所不同。一般而言，造成更多YLL的死亡原因也对金县内部的地理不平等产生了更大的影响。但是，某些原因对不平等的影响大于对整个YLL的影响。解释这项对预期寿命和特定原因的YLL率的人口普查级别分析突出显示了金县各社区之间在健康方面的重要差异，这些差异被县级估计所掩盖。金郡县改善人口健康的工作应着眼于减少地理不平等，方法是针对那些对整个YLL和不平等产生最大影响的健康状况。应当在其他位置重复进行此分析，以更全面地描述人口健康状况的细粒度本地变化，并有助于在减少不平等现象的同时改善健康状况。资助John W Stanton和Theresa E Gillespie。

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