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Examining the role of neighborhood-level sociostructural indices in predicting spontaneous preterm birth in the New York City metropolitan area

  • Daniel L. Kuhr
  • , Nicola F. Tavella
  • , Zahava P. Michaelson
  • , Raina Kishan
  • , Nicole Parkas
  • , Rebecca M. Cohen
  • , Chelsea A. DeBolt
  • , Helen Feltovich
  • , Kimberly B. Glazer

Research output: Contribution to journalArticlepeer-review

Abstract

BackgroundPrior predictive models of spontaneous preterm birth that include cervical length and other individual covariates have achieved only moderate discriminative strength. Indices which reflect the sociostructural environment have been associated with preterm birth overall, but the extent to which these measures may improve prediction of spontaneous preterm birth among individuals with measured cervical length has not been tested.ObjectivesTo determine whether a cervical length model including measures of the neighborhood-level social environment increases spontaneous preterm birth discrimination compared with a cervical length model without such indices.MethodsThis was a retrospective cohort study of all gestations with (1) delivery between January, 2013 and August, 2023 and (2) at least one transvaginal cervical length measurement between 16 weeks and 0 days’ and 24 weeks and 6 days’ gestation. The primary outcome was spontaneous preterm birth. We ascertained neighborhood-level sociostructural determinants of health from the Index of Concentration at the Extremes (ICE) and Child Opportunity Index (COI). We used logistic regression to predict the probability of spontaneous preterm birth in models with (1) cervical length alone, (2) cervical length plus social indices, and (3) cervical length, social indices, and individual characteristics. We examined model discrimination using the area under the receiver operating characteristics curve (AUC) and 95% confidence intervals. We used the net reclassification index (NRI) to quantify the improvement in predictive ability between nested models.Results1884 pregnancies were included, of which 119 (6.3%) resulted in spontaneous preterm birth. A model with cervical length alone achieved an AUC of 0.66 (0.60, 0.72), increasing to 0.75 (0.70, 0.79) with individual covariates. Adding social indices yielded a model with an AUC of 0.75 (0.71, 0.80). The model with cervical length, individual covariates, and social indices had an NRI of 0.04 (0.01, 0.08), indicating improved performance compared with the previous models.ConclusionsAmong individuals with cervical length screening, the inclusion of social indices improved the prediction of spontaneous preterm birth compared to a model with only individual-level covariates.

Original languageEnglish
Article number101837
JournalAmerican Journal of Obstetrics and Gynecology MFM
Volume8
Issue number1
DOIs
StatePublished - Jan 2026

Keywords

  • Preterm birth
  • cervical length
  • child opportunity index
  • index of concentration at the extremes
  • net reclassification index
  • preterm birth prediction
  • sociostructural indices

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