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Background <p>Certain industries and occupations (I&amp;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.</p> Objectives <p>To estimate occupational risk of SARS-CoV-2 infection during pregnancy by applying machine-learning-based I&amp;O coding to population-based data.</p> Methods <p>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&amp;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&amp;O group to low-risk I&amp;O reference groups, adjusting for race/ethnicity, age, education, insurance, language, and nativity.</p> Results <p>Among the study population, 66.7% (<i>n</i> = 77,596) had complete employment data; of these, 4744 (6.1%) had a laboratory-confirmed SARS-CoV-2 infection during pregnancy. By industry, women working in healthcare/social assistance (aRR = 1.63; 95%CI 1.45–1.84) and public administration (aRR = 1.59; 95%CI 1.31–1.93) had highest risk of infection. By occupation, women in protective services (aRR = 1.82; 95%CI 1.32–2.51) and health care practitioners and technical occupations (aRR = 1.49; 95%CI 1.32–1.68) had highest infection risk.</p> Conclusions <p>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&amp;O text data to assess risk of occupational exposures on maternal/infant health outcomes.</p>

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Applying a NIOSH Industry and Occupation Coding tool to evaluate occupational risk of SARS-CoV-2 infection in pregnant women

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月20日

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  • Chia-ling Liu,
  • Susan E. Manning,
  • Hanna Shephard,
  • Angela Laramie,
  • Eirini Nestoridi,
  • Catherine Brown,
  • Mahsa M. Yazdy

摘要

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% (n = 77,596) had complete employment data; of these, 4744 (6.1%) had a laboratory-confirmed SARS-CoV-2 infection during pregnancy. By industry, women working in healthcare/social assistance (aRR = 1.63; 95%CI 1.45–1.84) and public administration (aRR = 1.59; 95%CI 1.31–1.93) had highest risk of infection. By occupation, women in protective services (aRR = 1.82; 95%CI 1.32–2.51) and health care practitioners and technical occupations (aRR = 1.49; 95%CI 1.32–1.68) had highest infection risk.

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.