{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T09:29:10Z","timestamp":1791538150208,"version":"4.3.4"},"reference-count":16,"publisher":"BMJ","issue":"8","license":[{"start":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T00:00:00Z","timestamp":1756080000000},"content-version":"unspecified","delay-in-days":24,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001411","name":"Indian Council of Medical Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001411","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2025,7,23]]},"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Stillbirth is a significant public health problem in India, yet comprehensive epidemiological data on its prevalence and risk factors are lacking. The objectives of this research were to develop a dataset pooled from 10 well-characterised pregnancy cohorts across urban and rural India to estimate the prevalence of stillbirths, identify and quantify risk factors and develop a predictive risk stratification model for evidence-based clinical decision-making in high-risk pregnancies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>Pregnant women were enrolled during the antenatal period in 10 existing cohorts across India. Enrolment occurred through either health facilities or community settings at four urban, four rural and two mixed urban\u2013rural sites spanning nine states. All participants were enrolled before childbirth, with follow-up completed at least until delivery.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings to date<\/jats:title>\n                    <jats:p>The Indian Council of Medical Research (ICMR) stillbirth pooled India cohort (ICMR-Stillbirth Pooled India Cohort Dataset (SPIC)) comprises 229\u2009695 pregnant women. The mean (SD) maternal age at recruitment was 24.8 (4.5) years. 22.2% were underweight (body mass index (BMI)&lt;18.5\u2009kg\/m\u00b2) and 16.6% were overweight or obese (BMI\u226523\u2009kg\/m\u00b2). Short stature (&lt;145\u2009cm) was observed in 6.9% of participants. The mean (SD) gestational age at birth was 38.4 (2.1) weeks. One-third of the participants (33.3%) experienced moderate-to-severe anaemia during pregnancy (haemoglobin&lt;95\u2009g\/L), 52.8% were multiparous and 27.6% 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, pre-eclampsia\/eclampsia, antepartum haemorrhage and fetal distress, were available for over 80% of the cohorts, ensuring robust data coverage for risk factor analysis and modelling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Future plans<\/jats:title>\n                    <jats:p>ICMR-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 harmonised ICMR-SPIC dataset is a landmark collaborative effort to advance maternal and newborn health in India.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2025-099401","type":"journal-article","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T02:11:43Z","timestamp":1756174303000},"page":"e099401","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":3,"title":["Cohort profile of the ICMR-Stillbirth Pooled India Cohort (ICMR-SPIC): estimating prevalence, analysing risk factors and developing prediction models for stillbirths in India"],"prefix":"10.1136","volume":"15","author":[{"name":"ICMR-SPIC Consortium","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9754-5637","authenticated-orcid":false,"given":"Reema","family":"Mukherjee","sequence":"additional","affiliation":[{"name":"Reproductive and Child Health, Indian Council of Medical Research, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2025,8,25]]},"reference":[{"key":"2025123106472834000_15.8.e099401.1","unstructured":"World Health Organization . Stillbirth, Available: https:\/\/www.who.int\/health-topics\/stillbirth"},{"key":"2025123106472834000_15.8.e099401.2","doi-asserted-by":"crossref","DOI":"10.1136\/bmjoq-2022-001971","article-title":"Progressing towards SDG 2030 goals with system changes: the India Newborn Action Plan","volume":"11","author":"Datta","year":"2022","journal-title":"BMJ Open Qual"},{"key":"2025123106472834000_15.8.e099401.3","doi-asserted-by":"crossref","first-page":"1955","DOI":"10.1016\/S0140-6736(24)01925-1","article-title":"Global, regional, and national stillbirths at 20 weeks\u2019 gestation or longer in 204 countries and territories, 1990\u20132021: findings from the Global Burden of Disease Study 2021","volume":"404","author":"Comfort","year":"2024","journal-title":"Lancet"},{"key":"2025123106472834000_15.8.e099401.4","doi-asserted-by":"crossref","first-page":"100509","DOI":"10.1016\/j.lansea.2024.100509","article-title":"Turning the tide with better data to address stillbirths in India","volume":"32","author":"Dandona","year":"2025","journal-title":"Lancet Reg Health - Southeast Asia"},{"key":"2025123106472834000_15.8.e099401.5","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(21)01112-0"},{"key":"2025123106472834000_15.8.e099401.6","doi-asserted-by":"crossref","DOI":"10.1186\/s12916-019-1265-1","article-title":"Deferred and referred deliveries contribute to stillbirths in the Indian state of Bihar: results from a population-based survey of all births","volume":"17","author":"Dandona","year":"2019","journal-title":"BMC Med"},{"key":"2025123106472834000_15.8.e099401.7","doi-asserted-by":"crossref","DOI":"10.1186\/s12978-020-00991-y","article-title":"Stillbirth 2010-2018: a prospective, population-based, multi-country study from the Global Network","volume":"17","author":"McClure","year":"2020","journal-title":"Reprod Health"},{"key":"2025123106472834000_15.8.e099401.8","doi-asserted-by":"publisher","DOI":"10.2471\/BLT.22.288906"},{"key":"2025123106472834000_15.8.e099401.9","doi-asserted-by":"crossref","DOI":"10.1016\/j.lansea.2022.100116","article-title":"Stillbirth rates and its spatial patterns in India: an exploration of HMIS data","volume":"9","author":"Purbey","year":"2023","journal-title":"Lancet Reg Health Southeast Asia"},{"key":"2025123106472834000_15.8.e099401.10","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1002363","article-title":"Identification of factors associated with stillbirth in the Indian state of Bihar using verbal autopsy: A population-based study","volume":"14","author":"Dandona","year":"2017","journal-title":"PLoS Med"},{"key":"2025123106472834000_15.8.e099401.11","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(10)62187-3"},{"key":"2025123106472834000_15.8.e099401.12","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1186\/s40249-019-0587-8","article-title":"Recommendation on unbiased estimation of population attributable fraction calculated in \u201cprevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study\u201d","volume":"8","author":"Khosravi","year":"2019","journal-title":"Infect Dis Poverty"},{"key":"2025123106472834000_15.8.e099401.13","unstructured":"VanderWeele TJ , Knol MJ . 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