Evidence map›Paper›PMID 33413412›Full record

ArticleInternational journal for equity in health2021

Regional inequality in the Janani Suraksha Yojana coverage in India: a geo-spatial analysis.

Prem Shankar Mishra, Pradeep Kumar, Shobhit Srivastava

Abstract read
In one paragraph

Article in International journal for equity in health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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0cells of the map it votes in
10citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Prem Shankar MishraInstitute for Social and Economic Change, Bengaluru, Karnataka, 560072, India.ORCID 0000-0003-0601-7025
Pradeep KumarInternational Institute for Population Sciences, Mumbai, Maharashtra, 400088, India.ORCID 0000-0003-4259-820X
Shobhit SrivastavaInternational Institute for Population Sciences, Mumbai, Maharashtra, 400088, India. shobhitsrivastava889@gmail.com.ORCID 0000-0002-7138-4916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough India has made significant progress in institutional delivery after the implementation of the National Rural Health Mission under which the Janani Suraksha Yojana (JSY) is a sub-programme which played a vital role in the increase of institutional delivery in public facilities. Therefore, this paper aims to provide an understanding of the JSY coverage at the district level in India. Further, it tries to carve out the factors responsible for the regional disparity of JSY coverage at district levels.

methodsThe study used the National Family Health Survey data, which is a cross-sectional survey conducted in 2015-16, India. The sample size of this study was 148,145 women aged 15-49 years who gave last birth in the institution during 5 years preceding the survey. Bivariate and multivariate regression analysis was used to fulfill the study objectives. Additionally, Moran's I statistics and bivariate Local Indicator for Spatial Association (LISA) maps were used to understand spatial dependence and clustering of JSY coverage. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of JSY utilization.

resultsThe value of spatial-autocorrelation for JSY was 0.71 which depicts the high dependence of the JSY coverage over districts of India. The overall coverage of JSY in India is 36.4% and it highly varied across different regions, districts, and even socioeconomic groups. The spatial error model depicts that if in a district the women with no schooling status increase by 10% then the benefits of JSY get increased by 2.3%. Similarly, if in a district the women from poor wealth quintile, it increases by 10% the benefits of JSY also increased by 4.6%. However, the coverage of JSY made greater imperative to understand it due to its clustering among districts of specific states only.

conclusionIt is well reflected in the EAGs states in terms of spatial-inequality in service coverage. There is a need to universalize the JSY programme at a very individual level. And, it is required to revisit the policy strategy and the implementation plans at regional or district levels.

Indexed as

AdolescentAdultCross-Sectional StudiesDelivery, ObstetricFemaleFinancing, GovernmentHealthcare DisparitiesHealth FacilitiesHealth Services AccessibilityHumansIndiaMaternal Health ServicesPregnancyRural HealthSpatial AnalysisYoung AdultIndiaJanani Suraksha YojanaLISASpatial analysis

Identifiers

PMID33413412
PMCPMC7792199

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.