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IntroductionThe majority of low-income and middle-income countries (LMICs) have incomplete death registration systems and so the proportion of deaths that occur at home (ie, home death percentage) is generally unknown. However, home death percentage is important to estimate population-level causes of death from integration of data of deaths at home (verbal autopsies) and in hospitals (medical certification), and to monitor completeness of death notification and verbal autopsy data collection systems. This study proposes a method to estimate home death percentage using data readily available at the national and subnational level.MethodsData on place of death from 152 country-years in 49 countries from 2005 to 2019, predominantly from vital registration systems, were used to model home death percentage standardised for population age and cause distribution. A national-level model was developed using Bayesian model averaging to estimate national, regional and global home death percentage. A subnational-level model was also developed and assessed in populations where alternative data on home death percentage were available.ResultsGlobally, it is estimated that 53.4% (95% uncertainty interval (UI) 50.8%–55.9%) of deaths occur at home, slightly higher (59.7%, 95% UI 56.5%–62.7%) in LMICs, substantially higher in low-income countries (79.5%, 95% UI 77.3%–81.5%) and much lower (27.3%, 95% UI 25.2%–29.6%) in high-income countries. Countries with the highest home death percentage are mostly found in South, East and Southeast Asia and sub-Saharan Africa (above 90% in Ethiopia, Chad and South Sudan). As expected, the national model has smaller error than the subnational model.ConclusionThe study demonstrates substantial diversity in the location of deaths in LMICs and fills a significant gap in knowledge about where people die, given its importance for health systems and policies. The high proportion of deaths in LMICs that occur at home reinforces the need for routine verbal autopsy to determine the causes of death.

Many national and subnational governments need to routinely measure the completeness of death registration for monitoring and statistical purposes. Existing methods, such as death distribution and capture-recapture methods, have a number of limitations such as inaccuracy and complexity that prevent widespread application. This paper presents a novel empirical method to estimate completeness of death registration at the national and subnational level. Random-effects models to predict the logit of death registration completeness were developed from 2,451 country-years in 110 countries from 1970-2015 using the Global Burden of Disease 2015 database. Predictors include the registered crude death rate, under-five mortality rate, population age structure and under-five death registration completeness. Models were developed separately for males, females and both sexes. All variables are highly significant and reliably predict completeness of registration across a wide range of registered crude death rates (R-squared 0.85). Mean error is highest at medium levels of observed completeness. The models show quite close agreement between predicted and observed completeness for populations outside the dataset. There is high concordance with the Hybrid death distribution method in Brazilian states. Uncertainty in the under-five mortality rate, assessed using the dataset and in Colombian departmentos, has minimal impact on national level predicted completeness, but a larger effect at the subnational level. The method demonstrates sufficient flexibility to predict a wide range of completeness levels at a given registered crude death rate. The method can be applied utilising data readily available at the subnational level, and can be used to assess completeness of deaths reported from health facilities, censuses and surveys. Its utility is diminished where the adult mortality rate is unusually high for a given under-five mortality rate. The method overcomes the considerable limitations of existing methods and has considerable potential for widespread application by national and subnational governments.

Background In recent years, there have been adverse trends in premature cardiovascular disease (CVD) mortality rates (35–74 years) in the USA and Australia. Following long-term declines, rates in the USA are now increasing while falls in Australia have slowed rapidly. These two countries also have the highest adult obesity prevalence of high-income countries. This study investigates the role of overweight and obesity in their recent CVD mortality trends by using multiple cause of death (MCOD) data—direct individual-level evidence from death certificates—and linking the findings to cohort lifetime obesity prevalence. Methods We identified overweight- and obesity-related mortality as any CVD reported on the death certificate (CVD MCOD) with one or more of diabetes, chronic kidney disease, obesity, lipidemias or hypertensive heart disease (DKOLH-CVD), causes strongly associated with overweight and obesity. DKOLH-CVD comprises 50% of US and 40% of Australian CVD MCOD mortality. Trends in premature age-standardized death rates were compared between DKOLH-CVD and other CVD MCOD deaths (non-DKOLH-CVD). Deaths from 2000 to 2017 in the USA and 2006–2016 in Australia were analyzed. Trends in in age-specific DKOLH-CVD death rates were related to cohort relative lifetime obesity prevalence. Results Each country’s DKOLH-CVD mortality rate rose by 3% per annum in the most recent year, but previous declines had reversed more rapidly in Australia. Non-DKOLH-CVD mortality in the USA increased in 2017 after declining strongly in the early 2000s, but in Australia it has continued declining in stark contrast to DKOLH-CVD. There were larger increases in DKOLH-CVD mortality rates at successively younger ages, strongly related with higher relative lifetime obesity prevalence in younger cohorts. Conclusions The increase in DKOLH-CVD mortality in each country suggests that overweight and obesity has likely been a key driver of the recent slowdown or reversal of CVD mortality decline in both countries. The larger recent increases in DKOLH-CVD mortality and higher lifetime obesity prevalence in younger age groups are very concerning and are likely to adversely impact CVD mortality trends and hence life expectancy in future. MCOD data is a valuable but underutilized source of data to track important mortality trends.

Background In the United States (US), premature cardiovascular disease (CVD) mortality rates (35–74 years) have exhibited increases in recent years, particularly in younger adults, and large differentials by educational attainment. This trend has occurred concurrently with high and increasing obesity prevalence, which also show significant differences by education. This study aims to jointly model premature CVD mortality trends in the US according to obesity status and educational attainment. Methods We used multiple cause of death data from the National Center for Health Statistics, obesity prevalence data from the National Health and Nutrition Examination Survey (NHANES), and educational attainment data from the American Community Survey and NHANES. We applied Bayes’ theorem to these data to calculate the conditional probability of premature CVD mortality given obesity status and educational attainment for 2003–2019. We then projected this conditional probability for 2020–2029 using the Lee-Carter model. Results The probability of premature CVD mortality was greatest for obesity and low education (not graduated high school) and was substantially higher (females 6.7 times higher, males 5.9) compared with non-obesity and high education (Bachelor’s degree or higher) in 2019. There was a widening of the gap in premature CVD mortality from 2003 to 2019 between the obese and non-obese populations, which occurred at each education level and was projected to continue in 2020–2029, especially for males. The conditional probability of premature CVD death for obesity and middle education (finished high school but no Bachelor’s degree) increased substantially and was projected to surpass the level for non-obesity and low education in coming years for males and in younger age groups. At high education, the conditional probability of premature CVD death for the obese population was projected to increase to 2029, while for non-obesity it was projected to remain steady for females and fall for males; this projected widening is greatest at older age groups. Conclusions The findings demonstrate the public health challenge to reduce premature US CVD mortality posed by continued high obesity prevalence, especially for younger ages, lower education groups and males. The relative importance of obesity in influencing premature CVD mortality trends has risen partly due to the decline in CVD mortality attributable to other risk factors.

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.

Background In India the number of registered deaths increased substantially in recent years, improving the potential of the civil registration and vital statistics (CRVS) system to be the primary source of mortality data and providing more families of decedents with the benefits of possessing a death certificate. This study aims to identify whether inequalities in the completeness of death registration between states in India, including by sex, have narrowed during this period of CRVS system strengthening. Methods Data used in this study are registered deaths by state and year from 2000 to 2018 (and by sex from 2009 to 2018) reported in the Civil Registration Reports published by the Office of Registrar General of India. Completeness of death registration is calculated using the empirical completeness method. Levels and trends inequalities in completeness are measured in each state a socio-economic indicator – the Socio-Demographic Index (SDI). Results Estimated completeness of death registration in India increased from 58% in 2000 to 81% in 2018. Male completeness rose from 60% in 2009 to 85% in 2018 and was much higher than female completeness, which increased from 54 to 74% in the same period. Completeness remained very low in some states, particularly from the eastern (e.g. Bihar) and north-eastern regions. However, in states from the northern region (e.g. Uttar Pradesh) completeness increased significantly from a low level. There was a narrowing of inequalities in completeness according to the SDI during the period, however large inequalities between states remain. Conclusions The increase in completeness of death registration in India is a substantial achievement and increases the potential of the death registration system as a routine source of mortality data. Although narrowing of inequalities in completeness demonstrates that the benefits of higher levels of death registration have spread to relatively poorer states of India in recent years, the continued low completeness in some states and for females are concerning. The Indian CRVS system also needs to increase the number of registered deaths with age at death reported to improve their usability for mortality statistics.

Background Reliable and timely mortality data from a civil registration and vital statistics (CRVS) system are of crucial importance for generating evidence for policy and monitoring the progress towards national and global development goals. In Nepal, however, the death registration system is not used to produce mortality statistics, because it does not providing data on age at death and only reporting deaths by year of registration. This study assesses the completeness of death registration in Nepal – both the existing offline system and the newer online system – as well as the completeness of death reporting from a CRVS Survey, and assesses differences by year, sex, ecological belt, and province. Methods The empirical completeness method is used to estimate completeness at all ages from the offline (paper-based) registration system (2013-17), the online registration system (2017-19) and the CRVS Survey (2014-15). Results Completeness of the offline death registration system was 69% in 2017, not increasing since 2013 and being higher for males (73%) than females (65%). Completeness of online registration was only 32% in 2019, but almost double the 2017 figure. Completeness of death reporting in the CRVS Survey was 75% in 2015. The largest subnational differentials in completeness exist for the offline registration system, ranging from 90% in Gandaki to just 39% in Karnali. Conclusions Improvement in the utility of the Nepalese death registration system for mortality statistics is dependent on continued roll-out of the online death registration system (which reports age at death and deaths by year of occurrence) throughout the country, focusing on areas with low registration, building a strong coordination mechanism among CRVS stakeholders and implementing public awareness programs about death registration.

The widely-used estimates of completeness of birth registration collected by Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) and published by UNICEF primarily rely on registration status of children as reported by respondents. However, these self-reported estimates may be inaccurate when compared with completeness as assessed from nationally-reported official birth registration statistics, for several reasons, including over-reporting of registration due to concern about penalties for non-registration. This study assesses the concordance of self-reported birth registration and certification completeness with completeness calculated from civil registration and vital statistics (CRVS) systems data for 57 countries. Self-reported estimates of birth registration and certification completeness, at ages less than five years and 12-23 months, were compiled and calculated from the UNICEF birth registration database, DHS and MICS. CRVS birth registration completeness was calculated as birth registrations reported by a national authority divided by estimates of live births published in the United Nations (UN) World Population Prospects or the Global Burden of Disease (GBD) Study. Summary measures of concordance were used to compare completeness estimates. Birth registration completeness (based on ages less than five years) calculated from self-reported data is higher than that estimated from CRVS data in most of the 57 countries (31 countries according to UN estimated births, average six percentage points (p.p.) higher; 43 countries according to GBD, average eight p.p. higher). For countries with CRVS completeness less than 95%, self-reported completeness was higher in 26 of 28 countries, an average 13 p.p. and median 9-10 p.p. higher. Self-reported completeness is at least 30 p.p. higher than CRVS completeness in three countries. Self-reported birth certification completeness exhibits closer concordance with CRVS completeness. Similar results are found for self-reported completeness at 12-23 months. These findings suggest that self-reported completeness figures over-estimate completeness when compared with CRVS data, especially at lower levels of completeness, partly due to over-reporting of registration by respondents. Estimates published by UNICEF should be viewed cautiously, especially given their wide usage.

Many countries have used the new ANACONDA (Analysis of Causes of National Death for Action) tool to assess the quality of their cause of death data (COD), but no cross-country analysis has been done to verify how different or similar patterns of diagnostic errors and data quality are in countries or how they are related to the local cultural or epidemiological environment or to levels of development. Our objective is to measure whether the usability of COD data and the patterns of unusable codes are related to a country's level of socio-economic development. We have assessed the quality of 20 national COD datasets from the WHO Mortality Database by assessing their completeness of COD reporting and the extent, pattern and severity of garbage codes, i.e. codes that provide little or no information about the true underlying COD. Garbage codes were classified into four groups based on the severity of the error in the code. The Vital Statistics Performance Index for Quality (VSPI(Q)) was used to measure the overall quality of each country's mortality surveillance system. The proportion of 'garbage codes' varied from 7 to 66% across the 20 countries. Countries with a high SDI generally had a lower proportion of high impact (i.e. more severe) garbage codes than countries with low SDI. While the magnitude and pattern of garbage codes differed among countries, the specific codes commonly used did not. There is an inverse relationship between a country's socio-demographic development and the overall quality of its cause of death data, but with important exceptions. In particular, some low SDI countries have vital statistics systems that are as reliable as more developed countries. However, in low-income countries, where most people die at home, the proportion of unusable codes often exceeds 50%, implying that half of all cause-specific mortality data collected is of little or no use in guiding public policy. Moreover, the cause of death pattern identified from the data is likely to seriously under-represent the true extent of the leading causes of death in the population, with very significant consequences for health priority setting. Garbage codes are prevalent at all ages, contrary to expectations. Further research into effective strategies deployed in these countries to improve data quality can inform efforts elsewhere to improve COD reporting systems.

Background Death registration completeness has never been assessed at the county level in China. Such analyses would provide critical intelligence to monitor the performance of the vital registration system and yield adjustment factors to correct death registration data, thereby increasing their policy utility. Methods We estimated the completeness of death registration for 31 provinces and 2844 counties of China in 2018 based on death data from the China Cause of Death Reporting System (CDRS) by using the empirical completeness method. We computed the root mean square difference (RMSD) of county-level completeness compared with provincial-level completeness to study intra-provincial variations. A two-level (province and county) logistic regression model was fitted to explore the association between county-level registration completeness and a set of covariates reflecting socioeconomic status, healthcare quality, and specific strategies and regulations designed to improve registration. Results In 2018, the overall death registration completeness for the CDRS in China was 74.2% (95% uncertainty interval [UI] 66.2–80.4), with very little difference for males and females. Geographical differences in completeness were higher across counties than across provinces. The county-level completeness ranged from 2.4% (95% UI 1.0–5.0%) in Burang County, Tibet, to 100.0% (95% UI 99.9–100.0%) in Guandu District, Yunnan. The coastal provinces of Jiangsu, Guangdong, and Fujian, with higher overall completeness, contained counties with low completeness; conversely, the underdeveloped provinces of Guangxi and Guizhou, with lower overall completeness, included some counties with high completeness. GDP, education, population density, minority population, healthcare access, and registration strategies were important drivers of the geographical differences in registration completeness. Conclusions There are marked inequalities in registration completeness at the county level and within provinces in China. The socioeconomic condition, the implementation of specific registration-enhancing initiatives, and the availability and quality of medical care were the primary drivers of the observed geographical variation. A more strategic approach, with more research, is required to identify the main reasons for death under-reporting, especially in the poorer performing counties, to guide remedial action.