Spatial Patterning of Spontaneous and Medically Indicated Preterm Birth in Philadelphia

Am J Epidemiol. 2024 Feb 5;193(3):469-478. doi: 10.1093/aje/kwad207.


Preterm birth (PTB) remains a key public health issue that disproportionately affects Black individuals. Since spontaneous PTB (sPTB) and medically indicated PTB (mPTB) may have different causes and interventions, we quantified racial disparities for sPTB and mPTB, and we characterized the geographic patterning of these phenotypes, overall and according to race/ethnicity. We examined a pregnancy cohort of 83,952 singleton births at 2 Philadelphia hospitals from 2008-2020, and classified each PTB as sPTB or mPTB. We used binomial regression to quantify the magnitude of racial disparities between non-Hispanic Black and non-Hispanic White individuals, then generated small area estimates by applying a Bayesian model that accounts for small numbers and smooths estimates of PTB risk by borrowing information from neighboring areas. Racial disparities in both sPTB and mPTB were significant (relative risk of sPTB = 1.83, 95% confidence interval: 1.70, 1.98; relative risk of mPTB = 2.20, 95% confidence interval: 2.00, 2.42). The disparity was 20% greater in mPTB than sPTB. There was substantial geographic variation in PTB, sPTB, and mPTB risks and racial disparity. Our findings underscore the importance of distinguishing PTB phenotypes within the context of public health and preventive medicine. Future work should consider social and environmental exposures that may explain geographic differences in PTB risk and disparities.

Keywords: geographic information systems; medically indicated preterm birth; preterm birth; small area estimation; spontaneous preterm birth.

MeSH terms

  • Bayes Theorem
  • Ethnicity
  • Female
  • Humans
  • Infant, Newborn
  • Philadelphia / epidemiology
  • Pregnancy
  • Premature Birth* / epidemiology
  • Risk Factors