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Industry and occupation in California birth certificates (1998-2019): Reporting disparities and classification
Linda L Remy1, Louise Kaseff1, Rita Shiau1
1Family Health Outcomes Project (FHOP), Family and Community Medicine, School of Medicine, University of California San Francisco, San Francisco, California, USA.
Missing parental industry and occupation data on birth certificates disproportionately affects minority and less educated parents, potentially biasing exposure and economic stability analyses. Improving data collection is crucial for equitable research.
Area of Science:
- Public Health
- Epidemiology
- Sociology
Background:
- Missing and noncodable parental industry and occupation (I/O) information on birth certificates (BCs) can bias analyses of parental worksite exposures and family economic stability.
- Accurate I/O data is essential for understanding socioeconomic factors influencing health outcomes.
Purpose of the Study:
- To assess trends in missing and noncodable parental industry and occupation (I/O) information on California birth certificates (BCs) from 1989-2019.
- To identify demographic disparities in I/O missingness and codability.
Main Methods:
- Utilized the National Institute for Occupational Safety and Health (NIOSH) software to code parental I/O data from 21,739,406 California BCs (1989-2019).
- Assessed I/O missingness and codability across different reporting periods, parental sex, race/ethnicity, age, and education levels.
Main Results:
- Parental I/O missingness increased from 4.4% to 9.4% between 1989-2019.
- Missing I/O data was more prevalent among male, Black, American Indian/Alaska Native (AIAN) parents, and those with high school education or less.
- Less than 2% of reported I/O data was noncodable by NIOSH software, with minor disparities observed across demographic groups.
Conclusions:
- Systematic disparities exist in I/O missingness on California BCs, particularly affecting male, Black, AIAN, younger, and less educated parents.
- While I/O codability is generally high, improving data collection completeness is vital for equitable research on family economic contexts and outcomes.
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