The Geographical Correlation Between Historical Preterm Birth Disparities and COVID-19 Burden

Similar to obstetric outcomes, rates of SARS-CoV-2 (COVID-19) infection are not homogeneously distributed among populations; risk factors accumulate in discrete locations. This study aimed to investigate the geographical correlation between pre-COVID-19 regional preterm birth (PTB) disparities and subsequent COVID-19 disease burden. We performed a retrospective, ecological cohort study of an upstate New York birth certificate database from 2004 to 2018, merged with publicly available community resource data. COVID-19 rates from 2020 were used to allocate ZIP codes to “low-,” “moderate-,” and “high-prevalence” groups, defined by median COVID-19 diagnosis rates. COVID-19 cohorts were associated with poverty and educational attainment data from the US Census Bureau. The dataset was analyzed for the primary outcome of PTB using ANOVA. GIS mapping visualized PTB rates and COVID-19 disease rates by ZIP code. Within 38 ZIP codes, 123,909 births were included. The median COVID-19 infection rate was 616.5 (per 100 K). PTB (all) and COVID-19 were positively correlated, with high- prevalence COVID-19 ZIP codes also being the areas with the highest prevalence of PTB ( F = 11.06, P = .0002); significance was also reached for PTB