County-Level Trends in Suicide Rates in the US, 2005-2015
County-Level Trends in Suicide Rates in the US, 2005-2015
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DOI：
10.1016/j.amepre.2018.03.020
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发表时间：
2018-07-01
影响因子：
5.5
通讯作者：
Warner, Margaret
中科院分区：
文献类型：
--
作者：
Rossen, Lauren M.;Hedegaard, Holly;Warner, Margaret
前言：了解自杀的地理模式可以帮助有针对性的预防工作。尽管各州在年龄调整后的自杀率上的差异已经有了很好的记录，但县级的趋势在很大程度上还没有被探索过。本研究采用小区域估算法，得出稳定的县级自杀率估计值，以考察2005 - 2015年自杀的地理、时间和城乡分布模式。方法：利用2005-2015年国家生命统计潜在死亡原因档案，采用分层贝叶斯模型估计3140个县的自杀率。研究人员绘制了基于模型的自杀率估算图，以探索地理和时间模式，并检验城乡差异。分析在2016-2017年进行。结果：从2005年到2015年，美国99%的县的后验预测平均县级自杀率上升了10%，其中87%的县上升了20%。基于模型的自杀率最高的县一直分布在美国西部和西北部，除了南加州和华盛顿的部分地区。从2005年到2015年，与更多的城市县相比，更多的农村县的估计自杀率最高，而且随着时间的推移，自杀率也增长最快。结论：绘制县级自杀率地图为描述自杀的地理模式提供了更大的粒度，有助于更好地理解自杀率随时间的变化。研究结果可能为更有针对性的预防工作以及未来社区层面自杀死亡率风险和保护因素的研究提供信息。由爱思唯尔公司代表美国预防医学杂志出版
Introduction: Understanding the geographic patterns of suicide can help inform targeted prevention efforts. Although state-level variation in age-adjusted suicide rates has been well documented, trends at the county-level have been largely unexplored. This study uses small area estimation to produce stable county-level estimates of suicide rates to examine geographic, temporal, and urban-rural patterns in suicide from 2005 to 2015.Methods: Using National Vital Statistics Underlying Cause of Death Files (2005-2015), hierarchical Bayesian models were used to estimate suicide rates for 3,140 counties. Model-based suicide rate estimates were mapped to explore geographic and temporal patterns and examine urban-rural differences. Analyses were conducted in 2016-2017.Results: Posterior predicted mean county-level suicide rates increased by >10% from 2005 to 2015 for 99% of counties in the U.S., with 87% of counties showing increases of >20%. Counties with the highest model-based suicide rates were consistently located across the western and northwestern U.S., with the exception of southern California and parts of Washington. Compared with more urban counties, more rural counties had the highest estimated suicide rates from 2005 to 2015, and also the largest increases over time.Conclusions: Mapping county-level suicide rates provides greater granularity in describing geographic patterns of suicide and contributes to a better understanding of changes in suicide rates over time. Findings may inform more targeted prevention efforts as well as future research on community-level risk and protective factors related to suicide mortality. Published by Elsevier Inc. on behalf of American Journal of Preventive Medicine