Assessment of the national and subnational completeness of death registration in Nepal

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

BACKGROUND

The 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 METHODS

Using 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.

RESULTS

In 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.

CONCLUSIONS

The 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.

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.

Estimation of national and subnational all-cause mortality indicators in Nepal, 2017

BACKGROUND

Despite the civil registration and vital statistics (CRVS) system in Nepal operating for several decades, it has not been used to produce routine mortality statistics. Instead, mortality statistics rely on irregular surveys and censuses that primarily focus on child mortality. To fill this knowledge gap, this study estimates levels and subnational differentials in mortality across all ages in Nepal, primarily using CRVS data adjusted for incompleteness.

METHODS

We analyzed death registration data (offline or paper-based) and CRVS survey reported death data, estimating the true crude death rate (CDR) and number of deaths by sex and year for each province and ecological belt. The estimated true number of deaths for 2017 was used with an extension of the empirical completeness method to estimate the adult mortality (45q15) and life expectancy at birth by sex and subnational level. Plausibility of subnational mortality estimates was assessed against poverty head count rates.

RESULTS

Adult mortality in Nepal for 2017 is estimated to be 159 per 1000 for males and 116 for females, while life expectancy was estimated as 69.7 years for males and 73.9 years for females. Subnationally, male adult mortality ranges from 129 per 1000 in Madhesh to 224 in Karnali and female adult mortality from 89 per 1000 in Province 1 to 159 in Sudurpashchim. Similarly, male life expectancy is between 64.9 years in Karnali and 71.8 years in Madhesh and female male life expectancy between 69.6 years in Sudurpashchim and 77.0 years in Province 1. Mountain ecological belt and Sudurpashchim and Karnali provinces have high mortality and high poverty levels, whereas Terai and Hill ecological belts and Province 1, Madhesh, and Bagmati and Gandaki provinces have low mortality and poverty levels.

CONCLUSIONS

This is the first use of CRVS system data in Nepal to estimate national and subnational mortality levels and differentials. The national results are plausible when compared with Global Burden of Disease and United Nations World Population Prospects estimates. Understanding of the reasons for inequalities in mortality in Nepal should focus on improving cause of death data and further strengthening CRVS data.