Cohort profile of the ICMR-Stillbirth Pooled India Cohort (ICMR-SPIC): Estimating Prevalence, Analyzing Risk Factors, and Developing Prediction Models for Stillbirths in India

PurposeStillbirth is a significant public health problem in India, yet comprehensive epidemiological data on its prevalence and risk factors are lacking. This initiative develops a pooled dataset from 10 well-characterized pregnancy cohorts across urban and rural India to estimate the national prevalence of stillbirths, identify risk factors and their population-attributable fractions, and develop a predictive risk stratification model for evidence-based clinical decision-making and interventions in high-risk pregnancies. ParticipantsPregnant women were recruited from the health facilities and community settings during the antenatal period. Recruitment spans four urban, four rural, and two mixed urban-rural sites, ensuring diversity in geographic and demographic representation. Findings to DateThe ICMR stillbirth pooled India cohort (ICMR-SPIC) comprises 229,695 pregnant women. The mean (standard deviation) maternal Age at recruitment was 23.5(3.3) years. 30.5% were underweight (BMI <18.5 kg/m2) and 16.8% were overweight or obese (BMI [&ge;]23 kg/m2). Short stature (<145 cm) was observed in 6.9% of participants. The mean (SD) gestational Age at birth was 38.7 (2.5) weeks. A third of the participants (33.3%) experienced moderate to severe anaemia during pregnancy (Hb<9.5g/dL), 52.8% were multiparous, and 22.5% conceived within 18 months of their previous childbirth. Core maternal risk factors such as short stature, BMI, parity, prior stillbirths, and anaemia during pregnancy were recorded in all cohorts. Additional variables, including gestational weight gain, preeclampsia/eclampsia, antepartum hemorrhage, and fetal distress, were available for over 80% of the cohorts, ensuring robust data coverage for risk factor analysis and modeling. Future PlansICMR-SPIC will be used to conduct individual-level pooled data analyses to estimate prevalence, identify key risk factors, and develop predictive models for stillbirths. Findings will inform policies, clinical guidelines, and targeted interventions for high-risk pregnancies. The harmonized ICMR-SPIC dataset is a landmark collaborative effort to advance maternal and newborn health in India. STRENGTHS AND LIMITATIONSO_LIThe harmonized ICMR-SPIC pooled dataset is the largest and most comprehensive resource for investigating the prevalence and determinants of stillbirths in India. It represents diverse geographical regions, encompassing both urban and rural recruitment sites, and provides a broad demographic spectrum. C_LIO_LIGestational Age at birth was objectively determined using ultrasound measurements or last menstrual period data, enabling accurate categorization of stillbirths. C_LIO_LIThe prospective cohort design facilitates identification of at-risk populations by providing demographic data across most cohorts and enabling longitudinal tracking of some modifiable risk factors. C_LIO_LIDespite rigorous efforts to harmonize data, variations in the measurement methods for certain modifiable risk factors (e.g., reproductive tract infections, preeclampsia, and haemoglobin concentrations) may result in residual misclassification, potentially affecting the precision of some risk analyses. C_LIO_LIA notable limitation of the dataset is the lack of detailed data in several cohorts to distinguish between antepartum and intrapartum stillbirths, or assess the quality of care during labour and childbirth. This restricts the ability to provide robust prevalence estimates or identify specific determinants for the two types of stillbirths. C_LI