ArticleDiscover public health2026
Applying a NIOSH Industry and Occupation Coding tool to evaluate occupational risk of SARS-CoV-2 infection in pregnant women.
Article in Discover public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
7 authors.
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Abstract
Background: Certain industries and occupations (I&O) are linked to higher SARS-CoV-2 risk. Research on this association among pregnant women has been limited to clinical settings or small samples. Objectives: To estimate occupational risk of SARS-CoV-2 infection during pregnancy by applying machine-learning-based I&O coding to population-based data. Methods: We performed population-based analyses of 116,424 Massachusetts residents aged 18-54 with in-state live-birth deliveries during 4/1/2020-12/31/2021. SARS-CoV-2 infections were obtained from statewide case surveillance and matched to birth certificates. We used the NIOSH Industry and Occupation Computerized Coding System (NIOCCS) to code I&O text from birth certificates. We used generalized estimating equations with log link, Poisson distribution and exchangeable correlation to estimate adjusted risk ratios (aRR) and 95% confidence intervals (CI) for SARS-CoV-2 infection comparing each I&O group to low-risk I&O reference groups, adjusting for race/ethnicity, age, education, insurance, language, and nativity. Results: Among the study population, 66.7% ( Conclusions: During the first two years of the COVID-19 pandemic, women in healthcare and social assistance industries and protective service occupations had highest risk of SARS-CoV-2 infection in pregnancy. NIOCCS facilitates use of birth certificate I&O text data to assess risk of occupational exposures on maternal/infant health outcomes.
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