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. 2022 Jul 18;2(7):e0000441.
doi: 10.1371/journal.pgph.0000441. eCollection 2022.

Estimates and correlates of district-level maternal mortality ratio in India

Srinivas Goli  1   2 , Parul Puri  1 , Pradeep S Salve  1 , Saseendran Pallikadavath  3 , K S James  1
Affiliations

Estimates and correlates of district-level maternal mortality ratio in India

Srinivas Goli et al. PLOS Glob Public Health. .

Abstract

Despite the progress achieved, approximately one-quarter of all maternal deaths worldwide occur in India. Till now, India monitors maternal mortality in 18 out of its 36 provinces using information from the periodic sample registration system (SRS). The country does not have reliable routine information on maternal deaths for smaller states and districts. And, this has been a major hurdle in local-level health policy and planning to prevent avoidable maternal deaths. For the first time, using triangulation of routine records of maternal deaths under the Health Management Information System (HMIS), Census of India, and SRS, we provide Maternal Mortality Ratio (MMR) for all states and districts of India. Also, we examined socio-demographic and health care correlates of MMR using large-sample and robust statistical tools. The findings suggest that 70% of districts (448 out of 640 districts) in India have reported MMR above 70 deaths-a target set under Sustainable Development Goal-3. According to SRS, only Assam shows MMR of more than 200, while our assessment based on HMIS suggests that about 6-states (and two union territories) and 128-districts have MMR above 200. Thus, the findings highlight the presence of spatial heterogeneity in MMR across districts in the country, with spatial clustering of high MMR in North-eastern, Eastern, and Central regions and low MMR in the Southern and Western regions. Even the better-off states such as Kerala, Tamil Nadu, Andhra Pradesh, Karnataka, and Gujarat have districts of medium-to-high MMR. In order of their importance, fertility levels, the sex ratio at birth, health infrastructure, years of schooling, postnatal care, maternal age and nutrition, and poor economic status have emerged as the significant correlates of MMR. In conclusion, we show that HMIS is a reliable, cost-effective, and routine source of information for monitoring maternal mortality ratio in India and its states and districts.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Geographical pattern of maternal mortality ratio by states/union territories in India, HMIS.
(https://github.com/datameet/maps/). (Authors generated the estimates employing the HMIS data).
Fig 2
Fig 2. Geographical pattern of maternal mortality ratio by 640 districts in India, HMIS.
(https://github.com/datameet/maps/). (Authors generated the estimates employing the HMIS data).
Fig 3
Fig 3. Univariate Moran’s I for maternal mortality ration in India.
(https://github.com/datameet/maps/). (Authors generated the estimates employing the HMIS data). 3A. (https://github.com/datameet/maps/). (Authors generated the estimates employing the HMIS data). 3B. (https://github.com/datameet/maps/). (Authors generated the estimates employing the HMIS data).
Fig 4
Fig 4. Percentage of reported live births out of estimated live births by states in HMIS, 2017–19.
Fig 5
Fig 5. Correspondence between MMR estimates from SRS and HMIS.
Fig 6
Fig 6. Correlation between IMR estimates from SRS and MMR estimates from HMIS.
See this image and copyright information in PMC

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