Subnational estimates of life expectancy at birth in India: evidence from NFHS and SRS data

Abstract

Abstract Background Mortality estimates at the subnational level are of urgent need in India for the formulation of policies and programmes at the district level. This is the first-ever study which used survey data for the estimation of life expectancy at birth ($$ {\text{e}}_{0}$$) for the 640 districts from NFHS-4 (2015-16) and 707 districts from NFHS-5 (2019-21) for the total, male and female population in India. Methods This study calculated annual age-specific mortality rates from NFHS-4 and NFHS-5 for India and all 36 states for the total, male and female population. This paper constructed the abridged life tables and estimated life expectancy at birth $$({e_0})$$ and further estimated the model parameters for all 36 states. This study linked state-specific parameters to the respective districts for the estimation of life expectancy at birth $$({e_0})$$for 640 districts from NFHS-4 and 707 districts from NFHS-5 for the total, male and female population in India. Results Findings at the state level showed that there were similarities between the estimated and calculated $${e_0}$$ in most of the states. The results of this article observed that the highest $${e_0}$$ varies in the ranges of 70 to 90 years among the districts of the southern region. $${e_0}$$ falls below 70 years among most of the central and eastern region districts. In the northern region districts $${e_0}$$ lies in the range of 70 years to 75 years. The estimates of life expectancy at birth $$({e_0})$$ shows the noticeable variations at the state and district levels for the person, male, and female populations from the NFHS (2015-16) and NFHS (2019-21). In the absence of age-specific mortality data at the district level in India, this study used the indirect estimation method of relating state-specific model parameters with the IMR of their respective districts and estimated $${e_0}$$ across the 640 districts from NFHS-4 (2015-16) and 707 districts from NFHS-5 (2019-21). The findings of this study have similarities with the state-level estimations of $${e_0}$$ from both data sources of SRS and NFHS and found the highest $${e_0}$$ in the southern region and the lowest $${e_0}$$ in the eastern and central region districts. Conclusions In the lack of $${e_0}$$ estimates at the district level in India, this study could be beneficial in providing timely life expectancy estimates from the survey data. The findings clearly shows variations in the district level $${e_0}$$. The districts from the southern region show the highest $${e_0}$$ and districts from the central and eastern region has lower $${e_0}$$. Females have higher $${e_0}$$ as compared to the male population in most of the districts in India.