Center for Health and Community, University of California, San Francisco.
Department of Epidemiology and Biostatistics, University of California, San Francisco.
JAMA Netw Open. 2022 Apr 1;5(4):e228406. doi: 10.1001/jamanetworkopen.2022.8406.
Racial and ethnic inequities in COVID-19 mortality may be driven by occupation and education, but limited evidence has assessed these mechanisms.
To estimate whether occupational characteristics or educational attainment explained the associations between race and ethnicity and COVID-19 mortality.
DESIGN, SETTING, AND PARTICIPANTS: This population-based retrospective cohort study of Californians aged 18 to 65 years linked COVID-19 deaths to population estimates within strata defined by race and ethnicity, gender, age, nativity in the US, region of residence, education, and occupation. Analysis was conducted from September 2020 to February 2022.
Education and occupational characteristics associated with COVID-19 exposure (essential sector, telework option, wages).
All confirmed COVID-19 deaths in California through February 12, 2021. The study estimated what COVID-19 mortality would have been if each racial and ethnic group had (1) the COVID-19 mortality risk associated with the education and occupation distribution of White people and (2) the COVID-19 mortality risk associated with the lowest-risk educational and occupational positions.
Of 25 235 092 participants (mean [SD] age, 40 [14] years; 12 730 395 [50%] men), 14 783 died of COVID-19, 8 125 565 (32%) had a Bachelor's degree or higher, 13 345 829 (53%) worked in essential sectors, 11 783 017 (47%) could not telework, and 12 812 095 (51%) had annual wages under $51 700. COVID-19 mortality ranged from 15 deaths per 100 000 for White women and Asian women to 139 deaths per 100 000 for Latinx men. Accounting for differences in age, nativity, and region of residence, if all races and ethnicities had the COVID-19 mortality associated with the occupational characteristics of White people (sector, telework, wages), COVID-19 mortality would be reduced by 10% (95% CI, 6% to 14%) for Latinx men, but increased by 5% (95% CI, -8% to 17%) for Black men. If all working-age Californians had the COVID-19 mortality associated with the lowest-risk educational and occupational position (Bachelor's degree, nonessential, telework, and highest wage quintile), there would have been 43% fewer COVID-19 deaths among working-age adults (8441 fewer deaths; 95% CI, 32%-54%), with the largest absolute risk reductions for Latinx men (3755 deaths averted; 95% CI, 3304-4255 deaths) and Latinx women (2329 deaths averted; 95% CI, 2038-2621 deaths).
In this population-based cohort study of working-age California adults, occupational disadvantage was associated with excess COVID-19 mortality for Latinx men. For all racial and ethnic groups, excess risk associated with low-education, essential, on-site, and low-wage jobs accounted for a substantial fraction of COVID-19 mortality.
COVID-19 死亡率中的种族和民族不平等可能是由职业和教育造成的,但有限的证据评估了这些机制。
评估职业特征或教育程度是否可以解释种族和族裔与 COVID-19 死亡率之间的关联。
设计、地点和参与者:这项基于人群的回顾性队列研究对加利福尼亚州 18 至 65 岁的人群进行了研究,将 COVID-19 死亡与按种族和族裔、性别、年龄、在美国的出生地、居住地区、教育程度和职业划分的人群估计数联系起来。分析于 2020 年 9 月至 2022 年 2 月进行。
与 COVID-19 暴露相关的教育和职业特征(必要部门、远程工作选择、工资)。
截至 2021 年 2 月 12 日,加利福尼亚州所有确诊的 COVID-19 死亡病例。该研究估计,如果每个种族和族裔群体(1)具有与白人的教育和职业分布相关的 COVID-19 死亡率,(2)具有与最低风险教育和职业地位相关的 COVID-19 死亡率,那么 COVID-19 死亡率会是多少。
在 25235092 名参与者(平均[标准差]年龄为 40[14]岁;12730395[50%]为男性)中,有 14783 人死于 COVID-19,8125565(32%)拥有学士学位或更高学历,13345829(53%)在必要部门工作,11783017(47%)无法远程工作,12812095(51%)年薪低于 51700 美元。COVID-19 的死亡率从白人女性和亚裔女性的每 100000 人 15 例死亡到拉丁裔男性的每 100000 人 139 例死亡不等。在考虑年龄、出生地和居住地区差异后,如果所有种族和族裔都具有与白人职业特征(部门、远程工作、工资)相关的 COVID-19 死亡率,拉丁裔男性的 COVID-19 死亡率将降低 10%(95%CI,6%至 14%),而黑人男性的 COVID-19 死亡率将增加 5%(95%CI,-8%至 17%)。如果所有处于工作年龄的加利福尼亚人都处于 COVID-19 死亡率最低的教育和职业地位(学士学位、非必要、远程工作和最高工资五分位数),那么工作年龄成年人的 COVID-19 死亡人数将减少 43%(减少 8441 人死亡;95%CI,32%-54%),其中拉丁裔男性(可预防 3755 人死亡;95%CI,3304-4255 人死亡)和拉丁裔女性(可预防 2329 人死亡;95%CI,2038-2621 人死亡)的绝对风险降幅最大。
在这项针对加利福尼亚州工作年龄成年人的基于人群的队列研究中,职业劣势与拉丁裔男性 COVID-19 死亡率过高有关。对于所有种族和族裔,与低教育、必要、现场和低工资工作相关的高风险导致了 COVID-19 死亡率的很大一部分。