Literature DB >> 29659831

Institutional delivery in India, 2004-14: unravelling the equity-enhancing contributions of the public sector.

William Joe1, Jessica M Perkins2, Saroj Kumar3, Sunil Rajpal3, S V Subramanian4.   

Abstract

To achieve faster and equitable improvements in maternal and child health outcomes, the government of India launched the National Rural Health Mission in 2005. This paper describes the equity-enhancing role of the public sector in increasing use of institutional delivery care services in India between 2004 and 2014. Information on 24 661 births from nationally representative survey data for 2004 and 2014 is analysed. Concentration index is computed to describe socioeconomic-rank-related relative inequalities in institutional delivery and decomposition is used to assess the contributions of public and private sectors in overall socioeconomic inequality. Multilevel logistic regression is applied to examine the changes in socioeconomic gradient between 2004 and 2014. The analysis finds that utilization of institutional delivery care in India increased from 43% in 2004 to 83% in 2014. The bulk of the increase was in public sector use (21% in 2004 to 53% in 2014) with a modest increase in private sector use (22% in 2004 to 30% in 2014). The shift from a pro-rich to pro-poor distribution of public sector use is confirmed. Decomposition analysis indicates that 51% of these reductions in socioeconomic inequality are associated with improved pro-poor distribution of public sector births. Multilevel logistic regressions confirm the disappearance of a wealth-based gradient in public sector births between 2004 and 2014. We conclude that public health investments in India have significantly contributed towards an equitable increase in the coverage of institutional delivery care. Sustained policy efforts are necessary, however, with an emphasis on education, sociocultural and geographical factors to ensure universal coverage of institutional delivery care services in India.

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Year:  2018        PMID: 29659831     DOI: 10.1093/heapol/czy029

Source DB:  PubMed          Journal:  Health Policy Plan        ISSN: 0268-1080            Impact factor:   3.344


  16 in total

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10.  Closing the gap on institutional delivery in northern India: a case study of how integrated machine learning approaches can enable precision public health.

Authors:  Vincent S Huang; Kasey Morris; Mokshada Jain; Banadakoppa Manjappa Ramesh; Hannah Kemp; James Blanchard; Shajy Isac; Bidyut Sarkar; Vikas Gothalwal; Vasanthakumar Namasivayam; Pankaj Kumar; Sema K Sgaier
Journal:  BMJ Glob Health       Date:  2020-10
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