Assessing mortality registration in Kerala: the MARANAM study

Abstract

Complete or improving civil registration systems in sub-national areas in low- and middle-income countries provide several opportunities to better understand population health and its determinants. In this article, we provide an assessment of vital statistics in Kerala, India. Kerala is home to more than 33 million people and is a comparatively low-mortality context. We use individual-level vital registration data on more than 2.8 million deaths between 2006 and 2017 from the Kerala MARANAM (Mortality and Registration Assessment and Monitoring) Study. Comparing age-specific mortality rates from the Civil Registration System (CRS) to those from the Sample Registration System (SRS), we do not find evidence that the CRS underestimates mortality. Instead, CRS rates are smoother across ages and less variable across periods. In particular, the CRS records higher death rates than the SRS for ages, where mortality is usually low and for women. Using these data, we provide the first set of annual sex-specific life tables for any state in India. We find that life expectancy at birth was 77.9 years for women in 2017 and 71.4 years for men. Although Kerala is unique in many ways, our findings strengthen the case for more careful attention to mortality records within low- and middle-income countries, and for their better dissemination by government agencies.

Population perspectives and demographic methods to strengthen CRVS systems: introduction

“…In the sixth paper in this Genus thematic series, Gupta and Mani ( 2022 ) construct annual life-tables from death registration and sample registration data by sex for the southern state of Kerala from 2006–2017. Their analysis shows that, for Kerala, mortality data from the civil registration system and sample registration system are consistent and the civil registration provides smoother rates, given its more comprehensive approach.…”

“…Gupta and Mani ( 2022 ) make the important point that sustained improvements in the civil registration system in India are now making possible the production of high-quality mortality statistics from the official death registration system in some states of India. This point, also made by Rao and Gupta ( 2020 ), has at least three important policy implications.…”

Analysis of daily COVID-19 death bulletin data during the first two waves of the COVID-19 pandemic in Thiruvananthapuram district, Kerala, India

“…The median age of the reported deaths falls well below the most recent average life expectancy at birth of 78 years for women and 71 years for men. [ 32 ] The lack of a longevity advantage in women in COVID-19 deaths needs further exploration. Thus, exploring patterns discernible from available surveillance data remains useful.…”

Can administrative health data be used to estimate population level birth and child mortality estimates? A comparison of India's Health Information Management System data with nationally representative survey data

“…We use these data instead of India's official population projections because the official projections do not provide state- and age-specific estimates of population for all the years we consider in our analysis. Previous work has shown that using the official estimates or those by the DHS makes little difference to demographic estimates ( Gupta & Mani, 2022 ).…”