Renaissance School of Medicine at Stony Brook, Stony Brook, NY, USA.
Howard University College of Medicine, Washington, D.C, USA.
J Natl Med Assoc. 2024 Jun;116(3):302-308. doi: 10.1016/j.jnma.2024.05.003. Epub 2024 May 20.
BACKGROUND: Social variables are correlates of mortality. A number of social variables were used by the Centers for Disease Control and Prevention (CDC) to create a Social Vulnerability Index (SVI). SVI has been used as a correlate of health status. Age-adjusted mortality rates have been higher in Mississippi than in other states. Within Mississippi, the Delta region has had higher mortality. To test the hypothesis that social vulnerability was associated with mortality rate within the state, we examined SVI of counties in Mississippi as related to mortality from all causes in 2016-2020. METHODS: The CDC/ATSDR SVI ranks each census tract on 16 social factors, including poverty, lack of vehicle access, and crowded housing, and groups them into four related themes. Using CDC Wonder, we gathered data analyzing age-adjusted rate of death from all causes (AAR) in Mississippi Counties from 2016 to 2020, combined (reporting the death rate per 100,000 persons). Descriptive statistics were computed for each variable. Pearson correlation analysis, bivariable and multivariable regression analysis was done using Microsoft Excel version 16.77. The dependent variable was AAR and independent variables were for themes from the SVI. RESULTS: AAR varied greatly amongst counties in Mississippi. Higher AAR was seen in northwestern areas of Mississippi. The county with the lowest AAR (730 per 100,000 persons) had only half the AAR of the county with the highest AAR (1313.3 per 100,000 persons). The association of SVI THEME 1 (socioeconomic status) with AAR in Mississippi was positive. Linear regression analysis showed a coefficient of 203.5, 95 % CI 111.9-295.0, p = 0. 0.0000305. R square was 0.20. The addition of the following themes added little to the variation in AAR explained: SVI THEME 2 (household characteristics), SVI THEME 3 (racial and ethnic minority status), and SVI THEME 4 (housing type/transportation). CONCLUSION: Socioeconomic status explained a fifth of the variation in AAR among Mississippi counties in 2016-2020.
背景:社会变量与死亡率相关。美国疾病控制与预防中心(CDC)使用了许多社会变量来创建社会脆弱性指数(SVI)。SVI 已被用作健康状况的相关指标。与其他州相比,密西西比州的年龄调整后死亡率更高。在密西西比州,三角洲地区的死亡率更高。为了验证社会脆弱性与该州死亡率相关的假设,我们研究了密西西比州各县的 SVI 与 2016-2020 年所有原因导致的死亡率之间的关系。
方法:CDC/ATSDR 的 SVI 根据 16 个社会因素对每个普查区进行排名,包括贫困、缺乏交通工具和住房拥挤,并将它们分为四个相关主题。我们使用 CDC Wonder 收集了密西西比州各县 2016 年至 2020 年所有原因导致的死亡年龄调整率(AAR)的数据,将其合并(每 10 万人报告死亡率)。计算了每个变量的描述性统计数据。使用 Microsoft Excel 版本 16.77 进行 Pearson 相关性分析、双变量和多变量回归分析。因变量为 AAR,自变量为 SVI 主题。
结果:密西西比州各县的 AAR 差异很大。密西西比州西北部地区的 AAR 较高。AAR 最低的县(每 10 万人 730 人)只有 AAR 最高的县(每 10 万人 1313.3 人)的一半。SVI 主题 1(社会经济地位)与密西西比州的 AAR 呈正相关。线性回归分析显示系数为 203.5,95%CI 为 111.9-295.0,p=0.0000305。R 方为 0.20。添加以下主题后,对 AAR 解释的变化影响不大:SVI 主题 2(家庭特征)、SVI 主题 3(种族和民族少数群体地位)和 SVI 主题 4(住房类型/交通)。
结论:2016-2020 年,密西西比州各县的社会经济地位解释了 AAR 变异的五分之一。
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