A Pregnancy Cohort to Study Multidimensional Correlates of Preterm Birth in India: Study Design, Implementation, and Baseline Characteristics of the Participants

Am J Epidemiol. 2019 Apr 1;188(4):621-631. doi: 10.1093/aje/kwy284.


Globally, preterm birth is a major public health problem. In India, 3.6 million of the 27 million infants born annually are preterm. Risk stratification of women based on multidimensional risk factors assessed during pregnancy is critical for prevention of preterm birth. A cohort study of pregnant women was initiated in May 2015 at the civil hospital in Gurugram, Haryana, India. Women are enrolled within 20 weeks of gestation and are followed until delivery and once postpartum. The objectives are to identify clinical, epidemiologic, genomic, epigenomic, proteomic, and microbial correlates; discover molecular-risk markers by using an integrative -omics approach; and generate a risk-prediction algorithm for preterm birth. We describe here the longitudinal study design, methodology of data collection, and the repositories of data, biospecimens, and ultrasound images being created. A total of 4,326 pregnant women, with documented evidence of recruitment before 20 weeks of gestation, have been enrolled through March 2018. We report baseline characteristics and outcomes of the first 2,000 enrolled participants. A high frequency of preterm births (14.9% among 1,662 live births) is noteworthy. The cohort database and the repositories will become global resources to answer critical questions on preterm birth and other birth outcomes.

Keywords: India; cohort studies; fetal growth retardation; pregnancy outcome; premature birth; risk factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Epidemiologic Research Design*
  • Epigenomics
  • Female
  • Genomics
  • Humans
  • India / epidemiology
  • Longitudinal Studies
  • Pregnancy
  • Pregnancy Outcome / epidemiology*
  • Premature Birth / epidemiology*
  • Premature Birth / etiology
  • Proteomics
  • Risk Assessment / methods*
  • Risk Factors
  • Ultrasonography, Prenatal / statistics & numerical data