METHODS: Using death certificates, we identified all COVID-19 deaths that occurred between January 2020 and May 2022 among workers aged 18-64 years in California (CA). We derived estimates for at-risk worker populations using the Current Population Survey. The waves of COVID-19 mortality in the pre-vaccine availability period were March 2020-June 2020 (wave 1), and July 2020-November 2020 (wave 2), and in the post-vaccine availability period: December 2020-May 2021 (wave 3), June 2021-January 2022 (wave 4), and February 2022-May 2022 (wave 5). Poisson regression models with robust standard errors were used to determine wave-specific mortality rate ratios (MRRs). We examined the change in MRR across waves by including an interaction term between each demographic characteristic and wave period in different models. The role of potential misclassification of Race/ethnicity on death certificates was examined using probabilistic quantitative bias analysis as sensitivity analysis.
RESULTS: Among the 24.1 million working age CA population included in the study, there were 26,068 COVID-19 deaths in the period between January 2020 and May 2022. Compared with their respective reference groups, workers who were 50-64 years old, male, Native Hawaiian, Latino, or African American, foreign-born; individuals who had lower education; and unmarried were disproportionately affected by COVID-19 mortality. While disparities by sex, race/ethnicity and foreign-born status narrowed in later waves (post-vaccine availability), disparities by age, education level and marital status did not change substantially across waves.
CONCLUSIONS: Demographic disparities in COVID-19 mortality narrowed in the post-vaccine availability waves. However, the existence of disparities across all waves of the pandemic, even in an era of widespread vaccine coverage, could indicate remaining gaps in prevention and differential vulnerability. Addressing the underlying social, structural, and occupational factors that contribute to these disparities is critical for achieving health equity.
方法:使用死亡证明,我们确定了2020年1月至2022年5月间发生在加利福尼亚州(CA)18-64岁工人中的所有COVID-19死亡.我们使用当前人口调查得出了高危工人人口的估计值。在疫苗接种前的有效期内,COVID-19死亡率的波动是2020年3月至2020年6月(第一波),和2020年7月至2020年11月(第二波),在疫苗后有效期:2020年12月至2021年5月(第三波),2021年6月-2022年1月(第4波),和2022年2月至2022年5月(第5波)。使用具有稳健标准误差的泊松回归模型来确定波特异性死亡率比率(MRR)。我们通过在不同模型中包含每个人口统计学特征和波浪周期之间的相互作用项,检查了波浪之间MRR的变化。使用概率定量偏倚分析作为敏感性分析,检查了种族/种族的潜在错误分类在死亡证明上的作用。
结果:在纳入研究的2410万工作年龄CA人群中,在2020年1月至2022年5月期间,有26068例COVID-19死亡。与他们各自的参照组相比,50-64岁的工人,男性,夏威夷原住民,拉丁裔,或者非洲裔美国人,外国出生的;受教育程度较低的人;和未婚的人不成比例地受到COVID-19死亡率的影响。虽然性别差异,种族/民族和外国出生的身份在后来的浪潮中缩小(疫苗后的可用性),按年龄划分的差距,教育水平和婚姻状况在不同时期没有实质性变化.
结论:COVID-19死亡率的人口统计学差异在疫苗后可用波中缩小。然而,在大流行的所有浪潮中都存在差异,即使在疫苗覆盖广泛的时代,可能表明在预防和脆弱性方面仍然存在差距。解决潜在的社会问题,结构,造成这些差异的职业因素对于实现健康公平至关重要。