Demographic Differences and Potential Bias from Automated Occupation Coding Among Mothers of Babies Born with or Without Cleft Lip and/or Cleft Palate in the Texas Birth Defects Registry

Details

• Personal Author:
  Agopian AJ ; Benjamin RH ; Gimeno Ruiz de Porras D ; Oluwafemi OO ; Patel JR ; Shumate CJ
• Description:
  Objective: To compare maternal demographics based on occupation coding status and evaluate potential bias by excluding manually coded occupations. Methods: This case-control study assessed cases with clefts obtained from the Texas Birth Defects Registry. The NIOSH Industry and Occupation Computerized Coding System automatically coded occupations, with manual coding for unclassified cases. Maternal demographics were tabulated by occupation coding status (manual vs. automatic). Logistic regression examined associations between major occupation groups and clefts. Results: Automatic coding covered over 90% of all mothers. Building, grounds cleaning, and maintenance occupations, and office and administrative support occupations were significantly associated with cleft lip with or without cleft palate, even after excluding manually coded occupations. Conclusion: We found consistent associations before and after excluding manually coded data for most comparisons, suggesting that machine learning can facilitate occupation-related birth defects research. [Description provided by NIOSH]
• Subjects:
  Automation Demography Occupational Health Safety Women
• Keywords:
  Author Keywords: Cleft Lip Birth Defects Case Control Studies Cleft Palate Demographic Characteristics Machine Learning NIOCCS Occupation Occupations
• ISSN:
  1076-2752
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Dallas Region [OSHA] ; Texas
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  66
• Issue:
  10
• NIOSHTIC Number:
  nn:20069885
• Citation:
  J Occup Environ Med 2024 Oct; 66(10):839-847
• Contact Point Address:
  Jenil R. Patel, PhD, Department of Epidemiology, Human Genetics and Environmental Sciences, UTHealth Houston School of Public Health, 2777 N Stemmons Fwy, Suite 8400, Dallas, TX 75207
• Email:
  Jenil.Patel@uth.tmc.edu
• Federal Fiscal Year:
  2025
• Performing Organization:
  University of Texas Health Science Center, Houston
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Journal of Occupational and Environmental Medicine
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:1e0b9f4180190b58e522f580227e8ee3e5114278364f11a02938e3037088128d6cd15d388801fdedb502c2dcce47f9999e45c4bedda8173cbd7fb64c8cd29fdf
• Download URL:
  https://stacks.cdc.gov/view/cdc/208223/cdc_208223_DS1.pdf
• File Type:
  [PDF - 172.61 KB ]