Association of history of neonatal death with neonatal & early neonatal mortality rate: Implications for identifying vulnerable group in resource constrained economies

Tuesday Seminar
Event Speaker: 
Mudit Kapoor
Event Time: 
03:30 PM to 05:00 PM
Event Venue: 
HSS Committee Room (MS 610)

Reducing neonatal mortality rate (NMR) to 12 per 1000 livebirths by 2030 is one of the Sustainable Development Goals (SDGs). One effective way to achieve this is by identifying the most vulnerable population for targeted intervention. This is especially relevant in resource constrained countries like India. We perform a retrospective analysis of prospectively collected National Family Health Survey round 4 (NFHS IV) data from India for 2015-16. We identify history of neonatal death as an important predictor for neonatal mortality in univariate and multivariate logistic analyses. NMR among livebirths with such a history was compared to those without, while adjusting for environmental, and biological risk factors, and factors related to antenatal care. Our sample consists of singleton livebirths of 127,336 multiparous women. Of the sampled livebirths, 8.68% (95% CI 8.47% to 8.89%) had history of neonatal death in previous pregnancies, equating to an estimated 1.45 million (95% CI 1.41 million to 1.49 million) livebirths. The adjusted NMR was higher for livebirths with history of neonatal death, (32.07 vs. 15.07; P < 0.001). Mothers’ with such a history when compared to those without were poorer (40.12% vs. 26.15%; P < 0.001), received no antenatal care (23.96% vs. 19.41%; P < 0.001), and had livebirths not weighed at birth (29.42% vs. 20.15%; P < 0.001). Unadjusted and adjusted odds ratio (OR) for neonatal mortality was higher for livebirths with such a history: 3.51 (95% CI 3.10 to 3.97; P < 0.001) and 2.24 (95% CI 1.96 to 2.56; P < 0.001), respectively. Results were similar for early neonatal mortality. These findings remained consistent across multiple sensitivity analyses. History of neonatal death is an important predictor of NMR. Mothers with such a history are an important vulnerable group to target for achieving the desired reduction in NMR.

About the speaker:
Mudit Kapoor is an Associate Professor of Economics at the Indian Statistical Institute (ISI), New Delhi. He has formally worked at the Indian School of Business (ISB) in Hyderabad and the World Bank in Washington DC. His research papers have been published in international academic journals such as Management Science, Journal of Econometrics, Review of Economics and Statistics, Regional Science and Urban Economics, Journal of Financial Intermediation, Economic and Political Weekly, World Economy and BE Journal of Economic Analysis and Policy. Currently, he is working on data and analytics in healthcare where his mission is to “Convert Data into Information for Optimal Decision Making.” In this endeavor, he has partnered with large public and private health institutions to help improve performance in terms of resource utilization, identification of Healthcare Acquired Infection (HAI), etc. He has also partnered with a research think tank to democratize health related information by creating a Health monitor index – a tool to assess government performance at the level of a district. He has a PhD in Economics from University of Maryland in College Park, USA and an MA in Economics from Delhi School of Economics.