Assessing mortality registration in Kerala: the MARANAM study

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.

Adapting and validating the log quadratic model to derive under-five age- and cause-specific mortality (U5ACSM): a preliminary analysis

Background The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0–27 days), infants (0–11 months), and children age 12–59 months. Methods We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known. Results We estimate U5ACSM within 0.1–0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios. Conclusion The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.

Maternal Deaths in India: A Review of Trends and Programmes

High-quality services during childbirth in a health care facility reduce maternal morbidity and mortality. High maternal mortality in India is a critical concern. In an attempt to decrease the maternal mortality rate (MMR), the Government of India has launched many programmes. This article discusses the trends in maternal mortality in India with the inter-state disparities. As per Sample Registration System (SRS), MMR in India was estimated to be 556 in 1990, but globally it was only 385 at that time. India has achieved about a 77% reduction in maternal mortality compared to the global average of 43% between 2005 and 2017, but a huge inter-state disparity in maternal death still exists. Approximately 65%-75% of the estimated maternal deaths in India occur in a few states, including the eight Empowered Action Group (EAG) states (Bihar, Jharkhand, Madhya Pradesh, Chhattisgarh, Odisha, Rajasthan, Uttar Pradesh, and Uttarakhand), and Assam. For instance, the MMR reported for Assam (state which has the highest MMR) was 215 in 2017-18 which is five times higher than that of Kerala (43), which has the least MMR of all states. Most of the maternal deaths are due to direct causes and are largely preventable and treatable. There was a consistent reduction in MMR as a result of a number of interventions and programmes including Janani Suraksha Yojana (JSY) which helped in surging institutional deliveries.

Penilaian Kualitas Data Penyebab Kematian di Indonesia Tahun 2014

Sample Registration System (SRS) is a demographic survey for providing data on causes of death (COD) in Indonesia. The quality of COD will be taken into consideration for health policies development. This paper aims to assess the quality of data on the causes of death in Indonesia through the proportion and level of garbage codes on the impact when used in policy making. The 2014 National COD data set were assessed by applying the Analysis of National Causes of Death for Action (ANACONDA) software tool version 3.7.0. Distributions and levels of unusable and insufficiently specified “garbage” codes were analyzed. The Result shows, Diseases of the circulatory system (62.6%) contributed the most to garbage cause of death. The proportion of unusable COD was 31% of total data. 80% of garbage code were unspecified deaths group. Most of the garbage codes has low-level on severity of impact level for policy, while 11% of total codes has medium, high dan very high level of impact. In Conclusion, the 2014 SRS data was not at high quality, but the implications of garbage code in making inappropriate policies are mostly at low level. The use of low-level codes has less important impact on public health policy. The 2014 SRS data could be considered as a scientific basis evidence for public health policy. Quality improvement still needs to be done by conducting training and refreshing to determine the cause of death for doctors and data collection techniques for data collectors Keywords : Cause of Death, quality of data, Sample Registration System, ANACONDA Abstrak Sample Registration System (SRS) merupakan survei demografi untuk menyediakan data penyebab kematian (COD) di Indonesia. Kualitas COD akan menjadi bahan pertimbangan dalam membuat kebijakan kesehatan. Tulisan ini bertujuan untuk menilai kualitas data penyebab kematian di Indonesia melalui besar proporsi dan level kode sampah terhadap dampak yang ditimbulkan ketika digunakan dalam membuat kebijakan. Data penyebab kematian nasional tahun 2014 dinilai dengan menggunakan perangkat lunak Analisis Penyebab Kematian Nasional untuk Tindakan (ANACONDA) versi 3.7.0. Distribusi dan level kode "sampah" yang tidak dapat digunakan dianalisis dengan menggunakan ANACONDA. Hasil analisis menunjukkan, Diseases of the circulatory system (62.6%) berkontribusi terbanyak dalam hal kode sampah. Proporsi kode sampah yang tidak dapat digunakan adalah 31% dari total kode. Kode sampah yang paling umum digunakan adalah kelompok penyebab kematian tidak spesifik dan kelompok penyebab kematian antara. Berdasarkan tingkat keparahan dalam membuat kebijakan, sebagian besar kode sampah termasuk kategori level rendah, hanya 11% dari total kode memiliki tingkat dampak sedang, tinggi dan sangat tinggi. Kesimpulannya, kualitas data SRS 2014 masih kurang baik, namun implikasi yang ditimbulkan kode sampah dalam membuat kebijakan yang salah sebagian besar berada pada level rendah. Penggunaan kode-kode level rendah memiliki dampak yang kurang penting bagi kebijakan kesehatan masyarakat. Data penyebab kematian SRS 2014 layak dipertimbangkan untuk digunakan sebagai dasar kebijakan Kesehatan masyarakat. Pelatihan penentuan penyebab kematian untuk dokter dan juga petugas AV perlu dilakukan agar kualitas data COD selanjutnya dapat lebih baik Kata kunci: penyebab kematian, kualitas data, Sample Registration System, ANACONDA

Routes to improved mortality monitoring: Evidence from the Kerala MARANAM Study

Despite having universal mortality registration, vital registration systems in many regions of contemporary developing countries do not receive adequate attention. Using 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, we examine completeness of vital statistics and reliability of mortality rates estimated using them. Our findings show that age-specific mortality rates obtained from vital statistics system in Kerala, a comparatively low-mortality context in a low- and middle-income setting, are more reliable than the ones estimated by India's Sample Registration System. This is particularly true for ages where mortality is 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 attention to mortality records within developing countries, and for their better dissemination by government agencies.

Measurement of Inequality and Compression of Mortality in India for 4 Decades: 1970–2015

The studies relating to measurement of compression of Mortality in India is scarce. Most of the studies relating to mortality in India are focused on either life expectancy, or adult, and child mortality. We have used methods suggested by Kannisto (2000) and Canudos (2008) to measure the compression of mortality phenomenon for India for four decades viz. 1970-2015. Dispersion measures like simple mean, median, modal age at death; and some complicated measures like life disparity, standard deviation above mode, standard deviation in highest quartile, Interquartile range, Gini coefficient, AID and C-family were calculated for India from 1970-2015. We used the age specific death rates from abridged Life tables given by Sample Registration System published by Govt. of India. Our results show that inequality in mortality is decreasing in general but the gap between male and female is increasing. There was an average of three years difference in mean and modal age at death between male females in 2011-15. Overall, mean, median and modal age at death has increased in four decades but other inequality measures like Gini coefficient, AID, Standard deviation (SD) and coefficient of variation has decreased in four decades in India. C50 indicator, which indicates that 50 percent of deaths are happening in that age interval, declined from 26 years to 20 years for males and 27 years to 17 years for females, thus indicating the rate of compression of mortality is higher for females than males in India during 1970-75 till 2011-15.

Long-Term Trend in Infant Mortality in India: A Joinpoint Regression Analysis for 1971–2018

Infant mortality rate (IMR) in India remains high by international standards. India accounts for the largest number of global infant deaths. This study analyses the trend in IMR in India over almost four decades beginning 1971 through 2018. The analysis is based on annual estimates of IMR available through India’s official sample registration system and follows the joinpoint regression analysis approach. The analysis reveals that the trend in IMR in India changed three times during 1971–2018 and the pace of decrease has been different in different sub-periods with a considerable deceleration in the decrease during 1992–2006. It is only after the launch of National Rural Health Mission in 2005 that the decrease in IMR in India and selected states accelerated to more than 4 per cent per year.

Pauses and reversals of infant mortality decline in India in 2017 and 2018

This note examines recent trends in infant mortality in India, based on summary reports from the Sample Registration System (SRS). We find evidence of slowdown, pauses, and reversals in infant mortality decline in large parts of India in 2017 and 2018, the last two years for which SRS data are available. In urban areas, the infant mortality rate stagnated at 23 deaths per 1,000 births between 2016 and 2018. Worse, overall infant mortality increased in the poorer states of Chhattisgarh, Jharkhand, Madhya Pradesh, and Uttar Pradesh in this period. This occurred despite sustained improvements in household access to sanitation and clean fuel. One possible interpretation of these findings is that, in addition to their impact on unemployment and poverty, the demonetization experiment in late 2016 and the subsequent economic slowdown had an adverse effect on child health. In any case, these trends reinforce earlier evidence of faltering human development in India in recent years.

India’s Civil Registration System: a potentially viable data source for reliable subnational mortality measurement

ABSTRACTIntroductionThe Indian national Civil Registration System (CRS) is the optimal data source for mortality measurement, but is yet under development. As an alternative, data from the Sample Registration System (SRS) which covers less than 1% of the national population is used. This article presents a comparative analysis of mortality measures from the SRS and CRS in 2017, and explores the potential of the CRS to meet these subnational data needs.MethodsData on population and deaths by age and sex for 2017 from each source were used to compute national and state level life tables. Sex specific ratios of death probabilities in five age categories (0-4, 5-14, 15-29, 30-69, 70 -84, 85+) were used to evaluate CRS data completeness, using SRS probabilities as reference values. The quality of medically certified causes of death was assessed through hospital reporting coverage and proportions of deaths registered with ill-defined causes from each state.ResultsThe CRS operates through an extensive infrastructure with high reporting coverage, but child deaths are uniformly under reported, as well as female deaths in some states. However, at ages 30 to 69 years, CRS death probabilities are higher than the SRS values in 15 states in males and 10 states in females. SRS death probabilities are of limited precision for measuring mortality trends and differentials. Medical certification of cause of death is affected by low hospital reporting coverage.ConclusionsThe Indian CRS is more reliable than the SRS for measuring adult mortality in several states. Targeted initiatives to improve the recording of child and female deaths, to strengthen the quality of medical certification of cause of death, and to promote use of verbal autopsy methods are necessary to establish the CRS as a reliable source of sub national mortality statistics in the near future.KEY MESSAGESThe Sample Registration System (SRS) is currently the main source of mortality statistics in India, since the Civil Registration System (CRS) is yet under developmentLimitations in sample size as well as problems with quality of causes of death result in considerable uncertainty in population level mortality estimates from the SRSThis research evaluated the quality of the sex and age specific mortality risks from the CRS, using the SRS values in each state as reference valuesThe CRS has high levels of reporting coverage for death registration, and also measures higher levels of mortality at ages 30 to 69 years in several states, with high precisionInterventions are required to improve child death registration, strengthen medical certification of cause of death in hospitals, and introduce verbal autopsy for home deathsThese interventions will establish the CRS as a routine and reliable source for national and subnational mortality measurement in India in the near future