Penn Injury Science Center, University of Pennsylvania, Philadelphia.
Department of Social Policy and Intervention, University of Oxford, Oxford, United Kingdom.
JAMA Netw Open. 2022 Jun 1;5(6):e2215557. doi: 10.1001/jamanetworkopen.2022.15557.
Firearm violence remains a critical public health challenge, disproportionately impacting some US regions. County-level variation may hold key insights into how firearm mortality rates vary across the US.
To model county-level changes in firearm mortality rates (total, homicide, and suicide) from 1989 to 1993 vs 2015 to 2019 and identify and characterize hot spots showing unexpected changes over time.
DESIGN, SETTING, AND PARTICIPANTS: This is a cross-sectional study with 2 time points using a novel small area estimation method to analyze restricted access mortality microdata by cause of death and US county. The analysis included 3111 US counties from 49 states and the District of Columbia from January 1, 1989, to December 31, 2019. Bayesian spatial models were fitted to map geographical variation in changes in age-standardized firearm mortality rates (per 100 000 person-years) from 1989 to 1993 vs 2015 to 2019. County outliers (or hot spots) were defined as having observed rates that fell outside the 95% credible intervals of their expected posterior predictive distribution. These counties were characterized using visualization and descriptive statistics of their characteristics. Data were analyzed from June to December 2021.
County of residence.
Five-year age-standardized mortality rates by US county, age, and cause of death for 1989 to 1993 and 2015 to 2019.
Between 1989 and 2019, 1 036 518 firearm deaths were recorded in counties across the US. Suicide was the most common cause of firearm mortality (589 285 deaths) followed by homicide (412 231 deaths). Age-standardized rates (deaths per 100 000 individuals) for firearm deaths and suicides increased from 1989 to 1993 vs 2015 to 2019 (mean [SD] change, 0.16 [8.78] for firearm deaths and 1.21 [6.91] for suicides), while firearm homicides decreased (mean [SD] change, -0.39 [3.96]). However, these national trends were not homogeneous across counties and often varied by geographical region. The West and Midwest showed the most pronounced increases in firearm suicide rates, whereas the Southeast showed localized increases in firearm homicide rates, despite the national decreasing trend. Critical hot spots were identified in urban counties of Alabama, and firearm homicide rates (per 100 000) in Baltimore City, Maryland, almost doubled from 29.71 to 47.43, and by 2015 to 2019 it accounted for 66.7% of all firearm homicide in Maryland. By contrast, District of Columbia showed promising improvements over time, decreasing from 56.5 firearm homicides per 100 000 in 1989 to 1993 to 14.45 in 2015 to 2019.
There was substantial variation in rates and changes in firearm deaths among US counties. Geographical hot spots may be useful to inform targeted prevention efforts and local policy responses.
枪支暴力仍然是一个严重的公共卫生挑战,对美国一些地区的影响尤为严重。县级差异可能为了解美国各地的枪支死亡率差异提供重要线索。
从 1989 年至 1993 年与 2015 年至 2019 年,对枪支死亡率(总死亡率、凶杀率和自杀率)的县级变化进行建模,并确定和描述显示随时间意外变化的热点地区。
设计、地点和参与者:这是一项具有两个时间点的横截面研究,使用一种新的小区域估计方法,按死因和美国县分析受限访问死亡率微观数据。分析包括来自 49 个州和哥伦比亚特区的 3111 个美国县,时间范围为 1989 年 1 月 1 日至 2019 年 12 月 31 日。贝叶斯空间模型被拟合以绘制 1989 年至 1993 年与 2015 年至 2019 年期间年龄标准化枪支死亡率(每 10 万人年)变化的地理差异。县外离群值(或热点)被定义为观察到的比率落在其预期后验预测分布的 95%置信区间之外。这些县通过其特征的可视化和描述性统计进行特征描述。数据分析于 2021 年 6 月至 12 月进行。
居住的县。
1989 年至 1993 年和 2015 年至 2019 年期间,美国各县按年龄和死因分类的五年年龄标准化死亡率。
在 1989 年至 2019 年期间,全美各县共记录了 1036518 例枪支死亡。自杀是枪支死亡的最常见原因(589285 例死亡),其次是凶杀(412231 例死亡)。与 1989 年至 1993 年相比,枪支死亡和自杀的年龄标准化率(每 10 万人中的死亡人数)有所增加(枪支死亡的平均[标准差]变化为 0.16 [8.78],自杀的平均[标准差]变化为 1.21 [6.91]),而枪支凶杀则有所下降(平均[标准差]变化为-0.39 [3.96])。然而,这些全国性趋势在各县之间并不均匀,而且往往因地理区域而异。西部和中西部地区枪支自杀率的上升最为明显,而东南部地区的枪支凶杀率则出现局部上升,尽管全国呈下降趋势。在阿拉巴马州的城市县和马里兰州的巴尔的摩市确定了关键的热点地区,马里兰州的枪支凶杀率(每 10 万人)几乎翻了一番,从 1989 年至 1993 年的 29.71 上升到 2015 年至 2019 年的 47.43,到 2015 年至 2019 年,占马里兰州所有枪支凶杀的 66.7%。相比之下,哥伦比亚特区的情况随着时间的推移有所改善,枪支凶杀率从 1989 年至 1993 年的每 10 万人 56.5 起下降到 2015 年至 2019 年的 14.45 起。
美国各县的枪支死亡率和变化率存在很大差异。地理热点地区可能有助于为有针对性的预防工作和当地政策应对提供信息。