Birth defects are important public health issues because they are the leading cause of infant mortality causing one in every five infant deaths in the United States. Geographic factors are important determinants of risk of birth defects. Therefore, it is important to investigate geographic disparities of birth defects so as to identify factors responsible for identified patterns. This information is important in guiding disease control and prevention efforts. Thus, the objective of this study was to investigate the spatial patterns of birth defects and identify areas with significantly high risk of the condition.
METHODS:
Data from Nevada Birth Outcomes Monitoring System and Nevada live birth certificate covering the time period 2005-2011 and aggregated at the ZIP Code level were used for the study. Data on social economic variables, at the ZIP Code level, were obtained from the US census. Spatial Empirical Bayesian smoothing was used to compute the risks of birth defects. Spatial clusters were investigated using spatial scan statistic under the Poisson model assumption. Monte Carlo permutation approach was used to assess significance. Cartographic manipulation and displays were done in ArcGIS.
RESULTS:
A total of 266,357 live births and 17,626 (7%) birth defects were reported during the study period. Of the 156 ZIP Codes in Nevada, 23 had no birth defects. Females accounted for 41% of the birth defects. The race/ethnicity categories of mothers with infants who had birth defects were 43% White, 12% Black, 35% Hispanic, 6% Asian, 1% Native American, and 3% unknown. The Zip Code level birth defect risks for the study period ranged from 0 to 10,000 per 10,000 live births, with 47% of the ZIP Codes exceeding the state’s birth defects risk (661.7 per 10,000 live births). The raw unsmoothed birth defects risks by mother’s race/ethnicity per 10,000 live births were: 654.4 White, 902.0 Black, 609.2 Hispanic, 553.5 Asian, and 605.7 Native American. The results show that birth defects risk varies widely within Nevada counties at ZIP Code level. Furthermore, a statistically significant (p<0.0001) cluster of birth defects was identified in Clark County, the most populated county in Nevada.
CONCLUSIONS:
The findings indicate evidence of significant spatial clustering of birth defects in Nevada. Future epidemiological studies should focus on the area with the significant cluster to elucidate factors associated with birth defects. Prevention efforts should focus on areas with high birth defects prevalence and populations in ZIP Codes forming the significant cluster.