Have inequalities in completeness of death registration between states in India narrowed during two decades of civil registration system strengthening?

Neonatal, Infant, and Child Mortality in India: Progress and Future Directions

In India, considerable progress has been made in reducing child mortality rates. Despite this achievement, wide disparities persist across and socio-economic strata, and persistent challenges, such as malnutrition, poor sanitation, and lack of clean water. This paper provides a comprehensive review of the state of child health in India, examining key risk factors and causes of child mortality, assessing the coverage of child health interventions, and highlighting critical public health programs and policies. The authors also discuss future directions and recommendations for bolstering ongoing efforts to improve child health. These include state- and region-specific interventions, prioritizing social determinants of health, strengthening data systems, leveraging existing programs like the National Health Mission (NHM) and Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), and the proposed Public Health Management Cadre (PHMC). The authors argue that reducing child mortality requires not only scaled-up interventions but a comprehensive approach that addresses all dimensions of health, from social determinants to system strengthening.

Death registration coverage 2019-2021, India

Objective

To investigate coverage and factors associated with death registration in India.

Methods

We used data from the Indian National Family Health Survey 2019-2021. Based on responses of eligible household members, we estimated death registration in 84 390 deaths in all age groups across the country. We used multilevel logistic regression analysis to determine sociodemographic variables associated with death registration at state, district and individual levels.

Findings

Nationally, 70.8% (59 748/84 390) of deaths were registered. Of 707 districts in our study period, 122 and 53 districts had death registration levels less than 40% in females and males, respectively. The likelihood of death registration was significantly lower for females than males (adjusted odds ratios, aOR: 0.61; 95% confidence interval, CI: 0.59-0.64). Death registration increased significantly with age of the deceased person, with the highest odds in 35-49-year-olds (aOR: 5.05; 95% CI: 4.58-5.57) compared with 0-4-year-olds. Death registration was less likely among rural households, disadvantaged castes, the poorest wealth quintile, Muslims and households without a below poverty level card. Higher education was associated with higher death registration with the greatest likelihood of registration in households with a member with post-secondary school education (aOR: 1.54; 95% CI: 1.42-1.66). District-level factors were not significantly associated with death registration.

Conclusion

Sociodemographic characteristics of the deceased person were significantly associated with death registration. Strategies to raise awareness of death registration procedures among disadvantaged population groups and the introduction of a mobile telephone application for death registration are recommended to improve death registration in India.

Mortality Statistics in India: Current Status and Future Prospects

When plague epidemics swept India in the second half of the 19th century, there was an epidemiological need for mortality statistics; as a result, vital event registration systems were established. However, despite the existence of multiple sources of mortality statistics in many ministries/departments of the government, neither the number of deaths nor the causes of deaths reported annually are complete yet. Multilateral international organisations have supported modelling for the generation of mortality statistics in developing countries rather than supporting and funding the development of real-time mortality data. With specific initiatives for decentralising the registration process to primary health centres and sub-health centres, the civil registration system despite its flaws, can be improved for gathering accurate data on mortality, including the causes of deaths.

All-cause mortality during the COVID-19 pandemic in Chennai, India: an observational study

BACKGROUND

India has been severely affected by the ongoing COVID-19 pandemic. However, due to shortcomings in disease surveillance, the burden of mortality associated with COVID-19 remains poorly understood. We aimed to assess changes in mortality during the pandemic in Chennai, Tamil Nadu, using data on all-cause mortality within the district.

METHODS

For this observational study, we analysed comprehensive death registrations in Chennai, from Jan 1, 2016, to June 30, 2021. We estimated expected mortality without the effects of the COVID-19 pandemic by fitting models to observed mortality time series during the pre-pandemic period, with stratification by age and sex. Additionally, we considered three periods of interest: the first 4 weeks of India's first lockdown (March 24 to April 20, 2020), the 4-month period including the first wave of the pandemic in Chennai (May 1 to Aug 31, 2020), and the 4-month period including the second wave of the pandemic in Chennai (March 1 to June 30, 2021). We computed the difference between observed and expected mortality from March 1, 2020, to June 30, 2021, and compared pandemic-associated mortality across socioeconomically distinct communities (measured with use of 2011 census of India data) with regression analyses.

FINDINGS

Between March 1, 2020, and June 30, 2021, 87 870 deaths were registered in areas of Chennai district represented by the 2011 census, exceeding expected deaths by 25 990 (95% uncertainty interval 25 640-26 360) or 5·18 (5·11-5·25) excess deaths per 1000 people. Stratified by age, excess deaths numbered 21·02 (20·54-21·49) excess deaths per 1000 people for individuals aged 60-69 years, 39·74 (38·73-40·69) for those aged 70-79 years, and 96·90 (93·35-100·16) for those aged 80 years or older. Neighbourhoods with lower socioeconomic status had 0·7% to 2·8% increases in pandemic-associated mortality per 1 SD increase in each measure of community disadvantage, due largely to a disproportionate increase in mortality within these neighbourhoods during the second wave. Conversely, differences in excess mortality across communities were not clearly associated with socioeconomic status measures during the first wave. For each increase by 1 SD in measures of community disadvantage, neighbourhoods had 3·6% to 8·6% lower pandemic-associated mortality during the first 4 weeks of India's country-wide lockdown, before widespread SARS-CoV-2 circulation was underway in Chennai. The greatest reductions in mortality during this early lockdown period were observed among men aged 20-29 years, with 58% (54-62) fewer deaths than expected from pre-pandemic trends.

INTERPRETATION

Mortality in Chennai increased substantially but heterogeneously during the COVID-19 pandemic, with the greatest burden concentrated in disadvantaged communities. Reported COVID-19 deaths greatly underestimated pandemic-associated mortality.

FUNDING

National Institute of General Medical Sciences, Bill & Melinda Gates Foundation, National Science Foundation.

TRANSLATION

For the Hindi translation of the abstract see Supplementary Materials section.