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

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.

[1]  T. Manuck Racial and ethnic differences in preterm birth: A complex, multifactorial problem. , 2017, Seminars in perinatology.

[2]  I. Rudan,et al.  Understanding biological mechanisms underlying adverse birth outcomes in developing countries: protocol for a prospective cohort (AMANHI bio–banking) study , 2017, Journal of global health.

[3]  D. Hamer,et al.  Development and validation of a simplified algorithm for neonatal gestational age assessment – protocol for the Alliance for Maternal Newborn Health Improvement (AMANHI) prospective cohort study , 2017, Journal of global health.

[4]  D. Nayak,et al.  Assessment of risk factors and predictors for spontaneous pre-term birth in a South Indian antenatal cohort , 2017 .

[5]  R. Pathak,et al.  Revised Kuppuswamy and B G Prasad socio-economic scales for 2016 , 2017 .

[6]  P. D. Nicola,et al.  International estimated fetal weight standards of the INTERGROWTH‐21st Project , 2017, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

[7]  A. Fogarty,et al.  Factors associated with preterm delivery and low birth weight: a study from rural Maharashtra, India , 2017, F1000Research.

[8]  S. Acharya,et al.  Risk Factors for Preterm Birth and Low Birth Weight Among Pregnant Indian Women: A Hospital-based Prospective Study , 2016, Journal of preventive medicine and public health = Yebang Uihakhoe chi.

[9]  B. Padhi,et al.  Risk of Adverse Pregnancy Outcomes among Women Practicing Poor Sanitation in Rural India: A Population-Based Prospective Cohort Study , 2015, PLoS medicine.

[10]  Jamie Perin,et al.  Global, regional, and national causes of child mortality in 2000–13, with projections to inform post-2015 priorities: an updated systematic analysis , 2015, The Lancet.

[11]  M. Esplin Overview of Spontaneous Preterm Birth: A Complex and Multifactorial Phenotype , 2014, Clinical obstetrics and gynecology.

[12]  Parvati Bhat,et al.  A Case-Control Study on Risk Factors for Preterm Deliveries in a Secondary Care Hospital, Southern India , 2014, ISRN obstetrics and gynecology.

[13]  D. Altman,et al.  Estimation of gestational age in early pregnancy from crown-rump length when gestational age range is truncated: the case study of the INTERGROWTH-21st Project , 2013, BMC Medical Research Methodology.

[14]  T. Fenton,et al.  A systematic review and meta-analysis to revise the Fenton growth chart for preterm infants , 2013, BMC Pediatrics.

[15]  Ann-Beth Moller,et al.  National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications , 2012, The Lancet.

[16]  Katherine C Sexton,et al.  Development of the ISBER Best Practices for Repositories: Collection, Storage, Retrieval and Distribution of Biological Materials for Research. , 2012, Biopreservation and biobanking.

[17]  Hannah E Knight,et al.  Challenges in defining and classifying the preterm birth syndrome. , 2012, American journal of obstetrics and gynecology.

[18]  R. Mikolajczyk,et al.  A global reference for fetal-weight and birthweight percentiles , 2011, The Lancet.

[19]  D. Haas Preterm birth. , 2011, BMJ clinical evidence.

[20]  ACOG Practice Bulletin No. 102: management of stillbirth. , 2009, Obstetrics and gynecology.

[21]  D. Kanon,et al.  Fetal crown-rump length: reevaluation of relation to menstrual age (5-18 weeks) with high-resolution real-time US. , 1992, Radiology.

[22]  J. Khoury,et al.  New Ballard Score, expanded to include extremely premature infants. , 1991, The Journal of pediatrics.

[23]  F. P. Hadlock,et al.  Estimation of fetal weight with the use of head, body, and femur measurements--a prospective study. , 1985, American journal of obstetrics and gynecology.