Evidence map›Paper›PMID 40348997›Full record

ArticleBMC public health2025

Spatial disparities in death registration across states and districts of India, 2019-21.

Aditya Singh, Ananya Kundu, Sumit Ram, Rakesh Chandra, Arabindo Tanti, Shivani Singh, Vineet Kumar

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Aditya SinghDepartment of Geography, Banaras Hindu University, Varanasi, India.ORCID http://orcid.org/0000-0003-3031-5225
Ananya KunduDepartment of Geography, University of Calcutta, Kolkata, India. kunduananya55@gmail.com.ORCID http://orcid.org/0000-0002-9536-6069
Sumit RamDepartment of Geography, Banaras Hindu University, Varanasi, India. sumitram657@gmail.com.ORCID http://orcid.org/0000-0001-9163-5287
Rakesh ChandraSchool of Health System Studies, Tata Institute of Social Sciences, Mumbai, India.ORCID http://orcid.org/0000-0002-8330-9809
Arabindo TantiDepartment of Public Health and Community Medicine, Central University of Kerala, Kasaragod, India.ORCID http://orcid.org/0000-0002-7510-562X
Shivani SinghIndependent Researcher, Lucknow, India.ORCID http://orcid.org/0000-0001-6441-0576
Vineet KumarDepartment of Geography, Banaras Hindu University, Varanasi, India.ORCID http://orcid.org/0000-0003-1104-8336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe persistent issue of incomplete death registration in India, with a significant number of deaths going unrecorded, underscores the critical need for a granular understanding of spatial variations. Given the nation's vast geographic and demographic diversity, this granular understanding, particularly at the district level, is crucial for effective interventions. This analysis, therefore, aims to examine spatial disparities in death registration at both the state and district levels across India. DATA AND

methodsUsing data from the fifth round of the National Family Health Survey (NFHS-5) conducted in 2019-21, this study analyzed information on 79,449 deaths occurring in the three years preceding the survey, across 707 districts in India. The study explored spatial patterns and identified clusters of death registration using Moran's I and univariate Local Indicators of Spatial Association (LISA) maps. Additionally, spatial regression models were employed to examine the factors influencing death registration at the district level.

resultsIn 2019-21, only 71% of deaths in India were registered, with significant variations across states and districts. The univariate Moran's I value of 0.69 (p < 0.001) indicated strong spatial clustering in death registration at the district level. Two notable 'cold spots'-districts with low death registration rates surrounded by other low-registration districts-were identified across 152 districts, primarily in the eastern states of Uttar Pradesh, Jharkhand, Bihar, and the northeastern regions of Arunachal Pradesh, Nagaland, and parts of Manipur. Results from regression models revealed that factors such as the proportion of poor households, rural households, Muslim and Scheduled Tribe (ST) households, and households with at least one uneducated member were negatively associated with death registration at the district level.

conclusionsThe findings suggest the necessity for region-specific focused interventions to improve death registration in India, taking the social determinants of death registration into consideration and raising societal awareness about it.

Indexed as

Death CertificatesMortalityRegistriesSpatial AnalysisAdultFemaleHealth SurveysHumansIndiaMaleMiddle AgedDeath registrationHotspotsMoran’s INFHS-5Spatial autocorrelationSpatial patterns

Identifiers

PMID40348997
PMCPMC12065171

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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.