168 Examining the Utility of Birth Defect Data on Birth Certificates for Testing Etiological Hypotheses

Monday, June 15, 2015: 10:00 AM-10:30 AM
Exhibit Hall A, Hynes Convention Center
Steven H. Lamm , Center for Epidemiology and Global Health, washington, DC
Elisabeth Dissen , Consultants in Epidemiology and Occupational Health, Washington, DC
Ji Li , Johns Hopkins University School of Medicine, Baltimore, MD
Manning Feinleib , Consultants in Epidemiology and Occupational Health, washington, DC
Shayhan Robbins , Consultants in Epidemiology and Occupational Health, Washington, DC
Nana Ama Afari-Dwamena , Consultants in Epidemiology and Occupational Health, Washington, DC
Hamid Ferdosi , Consultants in Epidemiology and Occupational Health, washington, DC
Chao Zhou , Consultants in Epidemiology and Occupational Health, Washington, DC

BACKGROUND:   In 1974, we proposed that data from birth certificates could be used to test environmental or occupational etiological hypotheses for birth defects. Unfortunately few attempts have tested that.  Ahern (2011) demonstrated a positive test of this hypothesis by using birth certificate data to seek associations between birth defect rates and maternal residence in Mountain-Top Mining(MTM) counties in four central Appalachian States (KY, TN, VA, WV).  We have explored the West Virginia data in order to confirm their findings. 

METHODS:   We used 1990-2009 live birth certificate data for West Virginia. Forty-four hospitals contributed 98% of the MTM-county births and 95% of the non-mining-county births, of which six had more than 1,000 births from both MTM and non-mining counties.  Adjusted and stratified prevalence rate ratios for congenital anomalies (birth defects) were computed both by using Poisson regression and Mantel-Haenszel analysis.

RESULTS:   Unbalanced distribution of hospital births was observed by mining groups.  The congenital anomaly prevalence rate, higher in MTM-counties (0.021) than in non-mining-counties (0.015), yielded a significant crude prevalence rate ratio (cPRR = 1.43, 95% CI = 1.36-1.52) but not a significant hospital-adjusted prevalence rate ratio (adjPRR = 1.08, 95% CI = 0.97-1.20; p = 0.16) for the 44 hospitals. Similarly, data analysis for the six hospitals with large numbers of births from residents of both MTM and non-mining counties showed no increased risk after adjustment for hospital of birth (adjPRR = 1.01; 95% CI, 0.89-1.14; p = 0.87). 

CONCLUSIONS: We were unable to confirm our 40-year old hypothesis.  Rather we found that the apparent “Mountain-Top Mining” effect was a consequence of marked variation in congenital anomaly recording by hospitals.  Further attempts to use congenital anomaly data reports in birth certificates should seek to standardize recording across birth centers and examine for institutional variability.  We seek other examples where birth defect hypothesis could be tested using birth certificate information.