Dataset Information

Differential occupational risk for COVID-19 and other infection exposure according to race and ethnicity.

ABSTRACT: BACKGROUND:There are racial and ethnic disparities in the risk of contracting COVID-19. This study sought to assess how occupational segregation according to race and ethnicity may contribute to the risk of COVID-19. METHODS:Data about employment in 2019 by industry and occupation and race and ethnicity were obtained from the Bureau of Labor Statistics Current Population Survey. This data was combined with information about industries according to whether they were likely or possibly essential during the COVID-19 pandemic and the frequency of exposure to infections and close proximity to others by occupation. The percentage of workers employed in essential industries and occupations with a high risk of infection and close proximity to others by race and ethnicity was calculated. RESULTS:People of color were more likely to be employed in essential industries and in occupations with more exposure to infections and close proximity to others. Black workers in particular faced an elevated risk for all of these factors. CONCLUSION:Occupational segregation into high-risk industries and occupations likely contributes to differential risk with respect to COVID-19. Providing adequate protections to workers may help to reduce these disparities.

SUBMITTER: Hawkins D

PROVIDER: S-EPMC7323065 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Differential occupational risk for COVID-19 and other infection exposure according to race and ethnicity.

Hawkins Devan D

American journal of industrial medicine 20200615 9

<h4>Background</h4>There are racial and ethnic disparities in the risk of contracting COVID-19. This study sought to assess how occupational segregation according to race and ethnicity may contribute to the risk of COVID-19.<h4>Methods</h4>Data about employment in 2019 by industry and occupation and race and ethnicity were obtained from the Bureau of Labor Statistics Current Population Survey. This data was combined with information about industries according to whether they were likely or possi ...[more]

PMID: 32539166

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Project description:ImportanceFood insecurity is prevalent among racial/ethnic minority populations in the US. To date, few studies have examined the association between pre-COVID-19 experiences of food insecurity and COVID-19 infection rates through a race/ethnicity lens.ObjectiveTo examine the associations of race/ethnicity and past experiences of food insecurity with COVID-19 infection rates and the interactions of race/ethnicity and food insecurity, while controlling for demographic, socioeconomic, risk exposure, and geographic confounders.Design, setting, and participantsThis cross-sectional study examined the associations of race/ethnicity and food insecurity with cumulative COVID-19 infection rates in 3133 US counties, as of July 21 and December 14, 2020. Data were analyzed from November 2020 through March 2021.ExposuresRacial/ethnic minority groups who experienced food insecurity.Main outcomes and measuresThe dependent variable was COVID-19 infections per 1000 residents. The independent variables of interest were race/ethnicity, food insecurity, and their interactions.ResultsAmong 3133 US counties, the mean (SD) racial/ethnic composition was 9.0% (14.3%) Black residents, 9.6% (13.8%) Hispanic residents, 2.3% (7.3%) American Indian or Alaska Native residents, 1.7% (3.2%) Asian American or Pacific Islander residents, and 76.1% (20.1%) White residents. The mean (SD) proportion of women was 49.9% (2.3%), and the mean (SD) proportion of individuals aged 65 years or older was 19.3% (4.7%). In these counties, large Black and Hispanic populations were associated with increased COVID-19 infection rates in July 2020. An increase of 1 SD in the percentage of Black and Hispanic residents in a county was associated with an increase in infection rates per 1000 residents of 2.99 (95% CI, 2.04 to 3.94; P < .001) and 2.91 (95% CI, 0.39 to 5.43; P = .02), respectively. By December, a large Black population was no longer associated with increased COVID-19 infection rates. However, a 1-SD increase in the percentage of Black residents in counties with high prevalence of food insecurity was associated with an increase in infections per 1000 residents of 0.90 (95% CI, 0.33 to 1.47; P = .003). Similarly, a 1-SD increase in the percentage of American Indian or Alaska Native residents in counties with high levels of food insecurity was associated with an increase in COVID-19 infections per 1000 residents of 0.57 (95% CI, 0.06 to 1.08; P = .03). By contrast, a 1-SD increase in Hispanic populations in a county remained independently associated with a 5.64 (95% CI, 3.54 to 7.75; P < .001) increase in infection rates per 1000 residents in December 2020 vs 2.91 in July 2020. Furthermore, while a 1-SD increase in the proportion of Asian American or Pacific Islander residents was associated with a decrease in infection rates per 1000 residents of -1.39 (95% CI, -2.29 to 0.49; P = .003), the interaction with food insecurity revealed a similar association (interaction coefficient, -1.48; 95% CI, -2.26 to -0.70; P < .001).Conclusions and relevanceThis study sheds light on the association of race/ethnicity and past experiences of food insecurity with COVID-19 infection rates in the United States. These findings suggest that the channels through which various racial/ethnic minority population concentrations were associated with COVID-19 infection rates were markedly different during the pandemic.

Dataset Information

Differential occupational risk for COVID-19 and other infection exposure according to race and ethnicity.

Publications

Differential occupational risk for COVID-19 and other infection exposure according to race and ethnicity.

Similar Datasets

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