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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
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Adjusting for multiple-misclassified variables in a study using birth certificates.

Anne M Jurek1, Sander Greenland

  • 1Center for Healthcare Research & Innovation, Allina Health, Minneapolis, MN 55407, USA. jure0007@umn.edu

Annals of Epidemiology
|June 27, 2013
PubMed
Summary

Birth certificate data on maternal smoking and cleft lip/palate is often inaccurate. Adjusting for errors significantly changes the association estimates, highlighting the need for quantitative methods to account for data uncertainties in epidemiological studies.

Keywords:
BiasBirth certificatesCigarette smokingCleft lip and palateMisclassificationSensitivity analysisSensitivity and specificity

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Area of Science:

  • Epidemiology
  • Public Health
  • Biostatistics

Background:

  • Birth certificates are a common data source for epidemiological research.
  • However, significant inaccuracies in birth certificate data are well-documented.
  • Studies often do not account for these data errors.

Purpose of the Study:

  • To investigate the association between maternal cigarette smoking and cleft lip and palate using birth certificate data.
  • To assess the impact of data misclassification on this association.

Main Methods:

  • Adjusted odds ratio estimates for simultaneous exposure and outcome misclassification.
  • Calculated odds ratios adjusted for exposure misclassification only.
  • Calculated odds ratios adjusted for outcome misclassification only.

Main Results:

  • Adjusted odds ratios varied widely, from <1.0 to >>1.16 (unadjusted estimate).
  • Most adjusted estimates fell outside the 95% confidence limits of the unadjusted estimate.
  • The association between maternal smoking and clefting was substantially altered by error adjustment.

Conclusions:

  • Birth certificate classification errors can significantly impact study findings.
  • Inferences from birth certificate data should incorporate quantitative methods to address data uncertainties.
  • Researchers should be cautious when interpreting results based on potentially inaccurate birth records.