Bayesian estimates of Low Birth Weight Rate by U.S. County

Several studies have shown that infants with low birth weight (less than 2500 grams) have greater risk of mortality, long term neurologic disability, impaired language development, and chronic diseases such as diabetes and cardiovascular disease as compared to infants with normal birth weight. County-level estimates of low birth weight rate can be used to identify areas of the U.S. where prevention programs might have the greatest impact toward reducing the rate of low birth weight. However, estimates of low birth weight rate are available primarily at the state level. The aim of the present study was to explore the spatial pattern of low birth weight rate at the county level in the U.S. Data on birth weight was obtained from the National Association for Public Health Statistics and Information Systems for the duration 2006-2016. The raw Standardized Incidence Ratio (SIR) of low birth weight for each county was estimated by comparing observed cases relative to expected cases. The estimated raw SIRs were smoothed by log linear Bayesian Poisson regression model. Higher than expected rate of low birth weight was found in several counties in California, Nevada, Arizona, Oregon, Washington, North Dakota, Montana, New Mexico, Texas and in southeastern states. Concentrating intervention and prevention efforts on these high burden counties can be an effective strategy for preventing future cases of low birth weight.