This study evaluated persistency in county-level rates of low birthweightoutcomes to identify “hotspot counties” and their associated area-levelcharacteristics. Administrative data from the National Center for HealthStatistics Birth Data Files, years 2011 to 2016 were used to calculate annualcounty-level rates of low birthweight. Counties ranking in the worst quintile(Q5) for ≥3 years with a neighboring county in the worst quintile wereidentified as hotspot counties. Multivariate logistic regression was used toassociate county-level characteristics with hotspot designation. Adverse birthoutcomes were persistent in poor performing counties, with 52% of counties in Q5for low birthweight in 2011 remaining in Q5 in 2016. The rate of low birthweightamong low birthweight hotspot counties (n = 495) was 1.6 times the rate of lowbirthweight among non-hotspot counties (9.3% vs 5.8%). The rate of very lowbirthweight among very low birthweight hotspot counties (n = 387) was twice ashigh compared to non-hotspot counties (1.8% vs 0.9%). A one standard deviation(6.5%) increase in the percentage of adults with at least a high school degreedecreased the probability of low birthweight hotspot designation by1.7 percentage points (P = .006). A one standard deviation(20%) increase in the percentage of the population that was of minorityrace/ethnicity increased hotspot designation for low birthweight by5.7 percentage points (P < .001). Given the associationbetween low birthweight and chronic conditions, hotspot counties should be afocus for policy makers in order to improve health equity across the lifecourse.
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