Attributable fraction for cardiac malformations

Am J Epidemiol. 1998 Sep 1;148(5):414-23. doi: 10.1093/oxfordjournals.aje.a009666.


To the authors' knowledge, attributable fractions for cardiac malformations have not been reported before. The Baltimore-Washington Infant Study published factors associated with several major cardiac malformations in Maryland, the District of Columbia, and adjacent counties of northern Virginia in 1981-1989. For eight of these malformations, the authors provide attributable fractions of those factors that are potentially causal. Summary attributable fractions range from 13.6% (four factors) for hypoplastic left heart to 30.2% (seven factors) for transposition of great arteries with intact ventricular septum. Extra attributable fraction for factor x, defined as summary attributable fraction for all factors minus that for all but x, is largest for: 1) paternal marijuana use in transposition of great arteries with intact ventricular septum, 7.8%; 2) paternal anesthesia in tetralogy of Fallot, 3.6%; 3) painting in atrioventricular septal defect with Down syndrome, 5.1 %; 4) solvent/degreasing agent exposure in hypoplastic left heart, 4.6%; 5) sympathomimetics in coarctation of aorta, 5.8%; 6) pesticide exposure in isolated membranous ventricular septal defect, 5.5%; 7) hair dye in multiple/multiplex membranous ventricular septal defect, 3.3%; and 8) urinary tract infection in atrial septal defect, 6.4%. Percent-of-cases-exposed dominates relative risk in attributable fraction. If these factors are causal, the larger extra attributable fractions suggest the potential for prevention by specific interventions before/during pregnancy.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Case-Control Studies
  • Data Collection
  • Female
  • Heart Defects, Congenital / epidemiology*
  • Heart Defects, Congenital / prevention & control
  • Humans
  • Infant, Newborn
  • Logistic Models
  • Male
  • Maternal Exposure
  • Paternal Exposure
  • Risk Assessment
  • Risk Factors