Increasing sample size in prospective birth cohorts: back-extrapolating prenatal levels of persistent organic pollutants in newly enrolled children

Details

• Personal Author:
  Bradman A ; Chevrier J ; Eskenazi B ; Gaspar FW ; Gunier RB ; Sjödin, Andreas ; Verner M-A
• Description:
  Study sample size in prospective birth cohorts of prenatal exposure to persistent organic pollutants (POPs) is limited by costs and logistics of follow-up. Increasing sample size at the time of health assessment would be beneficial if predictive tools could reliably back-extrapolate prenatal levels in newly enrolled children. We evaluated the performance of three approaches to back-extrapolate prenatal levels of p,p'-dichlorodiphenyltrichloroethane (DDT), p,p'-dichlorodiphenyldichloroethylene (DDE) and four polybrominated diphenyl ether (PBDE) congeners from maternal and/or child levels 9 years after delivery: a pharmacokinetic model and predictive models using deletion/substitution/addition or Super Learner algorithms. Model performance was assessed using the root mean squared error (RMSE), R2, and slope and intercept of the back-extrapolated versus measured levels. Super Learner outperformed the other approaches with RMSEs of 0.10 to 0.31, R2s of 0.58 to 0.97, slopes of 0.42 to 0.93 and intercepts of 0.08 to 0.60. Typically, models performed better for p,p'-DDT/E than PBDE congeners. The pharmacokinetic model performed well when back-extrapolating prenatal levels from maternal levels for compounds with longer half-lives like p,p'-DDE and BDE-153. Results demonstrate the ability to reliably back-extrapolate prenatal POP levels from levels 9 years after delivery, with Super Learner performing best based on our fit criteria. [Description provided by NIOSH]
• Subjects:
  Demography Insecticides Occupational Health Pregnancy Race Factors Safety Software Women
• Keywords:
  Analytical-processes Children Computer-models Computer-software Demographic-characteristics Humans Organic-chemicals Organic-compounds Pesticides Pesticides-and-agricultural-chemicals Prenatal-exposure Racial-factors Sociological-factors Statistical-analysis

  More +
• ISSN:
  0013-936X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  California ; Georgia ; OSHA Region 4 ; OSHA Region 9
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  49
• Issue:
  6
• NIOSHTIC Number:
  nn:20047162
• Citation:
  Environ Sci Technol 2015 Mar; 49(6):3940-3948
• Contact Point Address:
  Marc-Andre Verner, Universitede Montreal Public Health Research Institute (IRSPUM), Universitede Montreal, Montreal, Quebec H3T 1J4, Canada
• Email:
  marc-andre.verner.1@umontreal.ca
• CAS Registry Number:
  DDT (CAS RN 50-29-3) ; p,p′-DDE (CAS RN 72-55-9)
• Federal Fiscal Year:
  2015
• Performing Organization:
  University of California, Berkeley
• Peer Reviewed:
  True
• Start Date:
  20010930
• Source Full Name:
  Environmental Science and Technology
• End Date:
  20060929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:740ad38c7cea57190fca5668df376d6d6865eefdfd3155728b555da881b0237ba050c1d7a517e2e95158ba3e35bd1308e10e912c802634969f694736358c42f5
• Download URL:
  https://stacks.cdc.gov/view/cdc/202331/cdc_202331_DS1.pdf
• File Type:
  [PDF - 383.68 KB ]