Evaluation of methods for assigning causes of death from verbal autopsies in India.

Background: Physician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (COD) in countries where medical certification of death is low. Computer-coded verbal autopsy (CCVA), an alternative method to PCVA for assigning the COD is considered to be efficient and cost-effective. However, the performance of CCVA as compared to PCVA is yet to be established in the Indian context. Methods: We evaluated the performance of PCVA and three CCVA methods i.e., InterVA 5, InSilico, and Tariff 2.0 on verbal autopsies done using the WHO 2016 VA tool on 2,120 reference standard cases developed from five tertiary care hospitals of Delhi. PCVA methodology involved dual independent review with adjudication, where required. Metrics to assess performance were Cause Specific Mortality Fraction (CSMF), sensitivity, positive predictive value (PPV), CSMF Accuracy, and Kappa statistic. Results: In terms of the measures of the overall performance of COD assignment methods, for CSMF Accuracy, the PCVA method achieved the highest score of 0.79, followed by 0.67 for Tariff_2.0, 0.66 for Inter-VA and 0.62 for InSilicoVA. The PCVA method also achieved the highest agreement (57%) and Kappa scores (0.54). The PCVA method showed the highest sensitivity for 15 out of 20 causes of death. Conclusion: Our study found that the PCVA method had the best performance out of all the four COD assignment methods that were tested in our study sample. In order to improve the performance of CCVA methods, multicentric studies with larger sample sizes need to be conducted using the WHO VA tool.

Implementation research for developing Civil Registration and Vital Statistics (CRVS) Systems: lessons from Indonesia.

Civil Registration and Vital Statistics (CRVS) systems are the optimal source for data on births, deaths and causes of death for health policy, programme evaluation and research. In Indonesia, indicators such as life expectancy at birth, childhood and maternal mortality rates and cause-specific death rates need to be routinely monitored for national health policy. However, the CRVS system is not yet producing reliable vital statistics, which creates a challenge for evidence-based health action. In 2019, the Indonesian government released a national strategy for the CRVS system, with targets for improved coverage and data quality by 2024. This article describes findings from a programme of formative and implementation research to guide the application of the national strategy. At first, a detailed CRVS assessment and gap analysis were undertaken using an international framework. The assessment findings were used to develop a revised business process model for reporting deaths and their causes at village, subdistrict and district level. In addition, a field instruction manual was also developed to guide personnel in implementation. Two field sites in Java-Malang District and Kudus Regency were selected for pilot testing the reporting procedures, and relevant site preparation and training were carried out. Data compilations for Malang in 2019 and Kudus in 2020 were analysed to derive mortality indicators. High levels of death reporting completeness (83% to 89%) were reported from both districts, along with plausible cause-specific mortality profiles, although the latter need further validation. The study findings establish the feasibility of implementing revised death reporting procedures at the local level, as well as demonstrate sustainability through institutionalisation and capacity building, and can be used to accelerate further development of the CRVS system in Indonesia.

Analysis of Multiple Causes of Death: A Review of Methods and Practices.

BACKGROUND: Research and reporting of mortality indicators typically focus on a single underlying cause of death selected from multiple causes recorded on a death certificate. The need to incorporate the multiple causes in mortality statistics-reflecting increasing multimorbidity and complex causation patterns-is recognized internationally. This review aims to identify and appraise relevant analytical methods and practices related to multiple causes. METHODS: We searched Medline, PubMed, Scopus, and Web of Science from their incept ion to December 2020 without language restrictions, supplemented by consultation with international experts. Eligible articles analyzed multiple causes of death from death certificates. The process identified 4,080 items of which we reviewed 434 full-text articles. RESULTS: Most articles we reviewed (76%, n = 332) were published since 2001. The majority of articles examined mortality by "any- mention" of the cause of death (87%, n = 377) and assessed pairwise combinations of causes (57%, n = 245). Since 2001, applications of methods emerged to group deaths based on common cause patterns using, for example, cluster analysis (2%, n = 9), and application of multiple-cause weights to re-evaluate mortality burden (1%, n = 5). We describe multiple-cause methods applied to specific research objectives for approaches emerging recently. CONCLUSION: This review confirms rapidly increasing international interest in the analysis of multiple causes of death and provides the most comprehensive overview, to our knowledge, of methods and practices to date. Available multiple-cause methods are diverse but suit a range of research objectives. With greater availability of data and technology, these could be further developed and applied across a range of settings.

Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations.

BACKGROUND: Mortality statistics using a single underlying cause of death (UC) are key health indicators. Rising multimorbidity and chronic disease mean that deaths increasingly involve multiple conditions. However, additional causes reported on death certificates are rarely integrated into mortality indicators, partly due to complexities in data and methods. This study aimed to assess trends and patterns in cause-related mortality in Australia, integrating multiple causes (MC) of death. METHODS: Deaths (n = 1 773 399) in Australia (2006-17) were mapped to 136 ICD-10-based groups and MC indicators applied. Age-standardized cause-related rates (deaths/100 000) based on the UC (ASRUC) were compared with rates based on any mention of the cause (ASRAM) using rate ratios (RR = ASRAM/ASRUC) and to rates based on weighting multiple contributing causes (ASRW). RESULTS: Deaths involved on average 3.4 causes in 2017; the percentage with >4 causes increased from 20.9 (2006) to 24.4 (2017). Ischaemic heart disease (ASRUC = 73.3, ASRAM = 135.8, ASRW = 63.5), dementia (ASRUC = 51.1, ASRAM = 98.1, ASRW = 52.1) and cerebrovascular diseases (ASRUC = 39.9, ASRAM = 76.7, ASRW = 33.5) ranked as leading causes by all methods. Causes with high RR included hypertension (ASRUC = 2.2, RR = 35.5), atrial fibrillation (ASRUC = 8.0, RR = 6.5) and diabetes (ASRUC = 18.5, RR = 3.5); the corresponding ASRW were 12.5, 12.6 and 24.0, respectively. Renal failure, atrial fibrillation and hypertension ranked among the 10 leading causes by ASRAM and ASRW but not by ASRUC. Practical considerations in working with MC data are discussed. CONCLUSIONS: Despite the similarities in leading causes under the three methods, with integration of MC several preventable diseases emerged as leading causes. MC analyses offer a richer additional perspective for population health monitoring and policy development.

Tuberculosis and HIV/AIDS-attributed mortalities and associated sociodemographic factors in Papua New Guinea: evidence from the comprehensive health and epidemiological surveillance system.

OBJECTIVE: Tuberculosis (TB) and HIV/AIDS are public health concerns in Papua New Guinea (PNG). This study examines TB and HIV/AIDS mortalities and associated sociodemographic factors in PNG. METHOD: As part of a longitudinal study, verbal autopsy (VA) interviews were conducted using the WHO 2016 VA Instrument to collect data of 926 deaths occurred in the communities within the catchment areas of the Comprehensive Health and Epidemiological Surveillance System from 2018 to 2020.InterVA-5 cause of deaths analytical tool was used to assign specific causes of death (COD). Multinomial logistic regression analyses were conducted to identify associated sociodemographic factors, estimate adjusted ORs (AOR), 95% CIs and p values. RESULT: TB and HIV/AIDS were the leading CODs from infectious diseases, attributed to 9% and 8% of the total deaths, respectively.Young adults (25-34 years) had the highest proportion of deaths from TB (20%) and the risk of dying from TB among this age group was five times more likely than those aged 75+ years (AOR: 5.5 (95% CI 1.4 to 21.7)). Urban populations were 46% less likely to die from this disease compared rural ones although the difference was not significant (AOR: 0.54 (95% CI 0.3 to 1.0)). People from middle household wealth quintile were three times more likely to die from TB than those in the richest quintile (AOR: 3.0 (95% CI 1.3 to 7.4)).Young adults also had the highest proportion of deaths to HIV/AIDS (18%) and were nearly seven times more likely to die from this disease compared with those aged 75+years (AOR: 6.7 (95% CI 1.7 to 25.4)). Males were 48% less likely to die from HIV/AIDS than females (AOR: 0.52 (95% CI 0.3 to 0.9)). The risk of dying from HIV/AIDS in urban population was 54% less likely than their rural counterparts (AOR: 0.46 (95% CI 0.2 to 0.9)). CONCLUSION: TB and HIV/AIDS interventions are needed to target vulnerable populations to reduce premature mortality from these diseases in PNG.

Mortality estimates for WHO SEAR countries: problems and prospects.

Cause-specific mortality estimates for 11 countries located in the WHO's South East Asia Region (WHO SEAR) are generated periodically by the Global Burden of Disease (GBD) and the WHO Global Health Estimates (GHE) analyses. A comparison of GBD and GHE estimates for 2019 for 11 specific causes of epidemiological importance to South East Asia was undertaken. An index of relative difference (RD) between the estimated numbers of deaths by sex for each cause from the two sources for each country was calculated, and categorised as marginal (RD=±0%-9%), moderate (RD=±10%-19%), high (RD=±20%-39%) and extreme (RD>±40%). The comparison identified that the RD was >10% in two-thirds of all instances. The RD was 'high' or 'extreme' for deaths from tuberculosis, diarrhoea, road injuries and suicide for most SEAR countries, and for deaths from most of the 11 causes in Bangladesh, DPR Korea, Myanmar, Nepal and Sri Lanka. For all WHO SEAR countries, mortality estimates from both sources are based on statistical models developed from an international historical cause-specific mortality data series that included very limited empirical data from the region. Also, there is no scientific rationale available to justify the reliability of one set of estimates over the other. The characteristics of national mortality statistics systems for each WHO SEAR country were analysed, to understand the reasons for weaknesses in empirical data. The systems analysis identified specific limitations in structure, organisation and implementation that affect data completeness, validity of causes of death and vital statistics production, which vary across countries. Therefore, customised national strategies are required to strengthen mortality statistics systems to meet immediate and long-term data needs for health policy and research, and reduce dependence on current unreliable modelled estimates.

Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic.

BACKGROUND: Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civil Registration System (CRS) is affected by incompleteness of death recording that varies by sex, age and location. METHODS: Under-reporting of CRS 2019 deaths was assessed for three age groups (< 5 years, 15-59 years and ≥60 years) at subnational level, through comparison with age-specific death rates from alternate sources. Age-specific corrections for under-reporting were applied to derive adjusted death counts by sex for each location. These were used to compute life expectancy (LE) at birth by sex in 2019, which were compared with subnational LEs from the Global Burden of Disease (GBD) 2019 Study. RESULTS: A total of 9.92 million deaths (95% UI 9.70 to 10.02) were estimated across India in 2019, about 2.28 million more than CRS reports. Adjustments to under-five and elderly mortality accounted for 30% and 56% of additional deaths, respectively. Adjustments in Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh accounted for 75% of all additional deaths. Adjusted LEs were below corresponding GBD estimates by ≥2 years for males at national level and in 20 states, and by ≥1 year for females in 12 states. CONCLUSIONS: These results represent the first-ever subnational mortality estimates for India derived from CRS reported deaths, and serve as a baseline for assessing excess mortality from the COVID-19 pandemic. Adjusted life expectancies indicate higher mortality patterns in India than previously perceived. Under-reporting of infant deaths and those among women and the elderly is evident in many locations. Further CRS strengthening is required to improve the empirical basis for local mortality measurement across the country.

Lessons Learnt and Pathways forward for National Civil Registration and Vital Statistics Systems after the COVID-19 Pandemic.

The COVID-19 pandemic has had a substantial impact on government services in many areas, including Civil Registration and Vital Statistics (CRVS). However, the pandemic has also highlighted the importance of recording of mortality and causes of death, with some potentially positive impacts for longer term CRVS strengthening, including: (1) increasing online provision of registration services (2) reporting of mortality statistics from settings which had not previously done so (3) improved intersectoral cooperation, particularly with the health sector, improving the ability to record deaths and (4) increased awareness among governments and public of the importance of mortality statistics. Now, it is pressing for national governments, and international organizations working to strengthen CRVS systems, to evaluate the effectiveness of strategies adopted over the last year, and use lessons learnt to catalyse broader sustainable CRVS improvement strategies, providing governments with essential data on mortality and causes of death into the future.

Premature adult mortality in India: what is the size of the matter?

BACKGROUND: Reducing adult mortality by 2030 is a key component of the United Nations Sustainable Development Goals (UNSDGs). Monitoring progress towards these goals requires timely and reliable information on deaths by age, sex and cause. To estimate baseline measures for UNSDGs, this study aimed to use several different data sources to estimate subnational measures of premature adult mortality (between 30 and 70 years) for India in 2017. METHODS: Age-specific population and mortality data were accessed for India and its 21 larger states from the Civil Registration System and Sample Registration System for 2017, and the most recent National Family and Health Survey. Similar data on population and deaths were also procured from the Global Burden of Disease Study 2016 and the National Burden of Disease Estimates Study for 2017. Life table methods were used to estimate life expectancy and age-specific mortality at national and state level from each source. An additional set of life tables were estimated using an international two-parameter model life table system. Three indicators of premature adult mortality were derived by sex for each location and from each data source, for comparative analysis RESULTS: Marked variations in mortality estimates from different sources were noted for each state. Assuming the highest mortality level from all sources as the potentially true value, premature adult mortality was estimated to cause a national total of 2.6 million male and 1.8 million female deaths in 2017, with Bihar, Maharashtra, Tamil Nadu, Uttar Pradesh and West Bengal accounting for half of these deaths. There was marked heterogeneity in risk of premature adult mortality, ranging from 351 per 1000 in Kerala to 558 per 1000 in Chhattisgarh among men, and from 198 per 1000 in Himachal Pradesh to 409 per 1000 in Assam among women. CONCLUSIONS: Available data and estimates for mortality measurement in India are riddled with uncertainty. While the findings from this analysis may be useful for initial subnational health policy to address UNSDGs, more reliable empirical data is required for monitoring and evaluation. For this, strengthening death registration, improving methods for cause of death ascertainment and establishment of robust mortality statistics programs are a priority.

Comparative performance of verbal autopsy methods in identifying causes of adult mortality: A case study in India.

Background & objectives: Cause of death assignment from verbal autopsy (VA) questionnaires is conventionally accomplished through physician review. However, since recently, computer softwares have been developed to assign the cause of death. The present study evaluated the performance of computer software in assigning the cause of death from the VA, as compared to physician review. Methods: VA of 600 adult deaths was conducted using open- and close-ended questionnaires in Nandpur Kalour Block of Punjab, India. Entire VA forms were used by two physicians independently to assign the cause of death using the International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes. In case of disagreement between them, reconciliation was done, and in cases of persistent disagreements finally, adjudication was done by a third physician. InterVA-4-generated causes from close-ended questionnaires were compared using Kappa statistics with causes assigned by physicians using a questionnaire having both open- and close-ended questions. At the population level, Cause-Specific Mortality Fraction (CSMF) accuracy and P-value from McNemar's paired Chi-square were calculated. CSMF accuracy indicates the absolute deviation of a set of proportions of causes of death out of the total number of deaths between the two methods. Results: The overall agreement between InterVA-4 and physician coding was 'fair' (κ=0.42; 95% confidence interval 0.38, 0.46). CSMF accuracy was found to be 0.71. The differences in proportions from the two methods were statistically different as per McNemar's paired Chi-square test for ischaemic heart diseases, liver cirrhosis and maternal deaths. Interpretation & conclusions: In comparison to physicians, assignment of causes of death by InterVA- 4 was only 'fair'. Hence, it may be appropriate to continue with physician review as the optimal option available in the current scenario.

Empiricism in non-communicable disease mortality measurement for the Asia-Pacific: lost in translation.

Control of non-communicable diseases (NCDs) is a key target for the United Nations Sustainable Development Goals (SDGs) for 2030. Available information indicates that countries in the Asia-Pacific Region accounted for 63% of the global NCD mortality burden in 2016. The United Nations Economic and Social Commission for the Asia Pacific (UNESCAP) Regional SDG progress report for 2020 included estimates of trends in NCD mortality rates from 2000 to 2016, which showed considerable variation in national NCD mortality by sex and location.However, while the UNESCAP report states that there was sufficient primary data to derive these NCD mortality estimates for all countries, the critical gaps in availability of national data on causes of death in the Asia-Pacific region are well known. A closer review identified that the UNESCAP obtained these estimates from the United Nations Statistics Division, which in turn obtained the same estimates from WHO. Further analysis revealed that these organisations used varying and often inconsistent terms to describe estimation methodology as well as primary data availability for different countries, with substantial potential for misinterpretation.The analysis also found that for countries without primary data, WHO reported NCD mortality estimates were based on complex epidemiological models developed for the Global Burden of Disease (GBD) Study, and this contradicts the UNESCAP rating of primary data sufficiency. The GBD Study also derives modelled cause of death estimates for countries with national data, but these were different from WHO estimates for these countries. This article discusses prevailing international practices in using modelled estimates as a substitute for empirical data, and the implications of these practices for health policy. In conclusion, a strategic approach to strengthen national mortality statistics programmes in data deficient countries is presented, to improve NCD mortality measurement in the Asia-Pacific Region.

The civil registration system is a potentially viable data source for reliable subnational mortality measurement in India.

INTRODUCTION: The Indian national Civil Registration System (CRS) is the optimal data source for subnational 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 comparison of mortality measures from the SRS and CRS in 2017, and explores the potential of the CRS to meet these subnational data needs. METHODS: Data on population and deaths by age and sex for 2017 from each source were used to compute national-level 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) 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. RESULTS: The CRS operates through an extensive infrastructure with high reporting coverage, but child deaths are uniformly under-reported, as are female deaths in many states. However, at ages 30-69 years, CRS death probabilities are higher than the SRS values in 15 states for males and 10 states for females. SRS death probabilities are of limited precision for measuring mortality trends and differentials. Data on medically certified causes of death are of limited use due to low hospital reporting coverage. CONCLUSIONS: The 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 reporting and quality of medically certified causes of death, and to promote use of verbal autopsy methods can establish the CRS as a reliable source of subnational mortality statistics in the near future.

Evaluating the quality of evidence for diagnosing ischemic heart disease from verbal autopsy in Indonesia.

BACKGROUND: Mortality and cause of death data are fundamental to health policy development. Civil Registration and Vital Statistics systems are the ideal data source, but the system is still under development in Indonesia. A national Sample Registration System (SRS) has provided nationally representative mortality data from 128 sub-districts since 2014. Verbal autopsy (VA) is used in the SRS to obtain causes of death. The quality of VA data must be evaluated as part of the SRS data quality assessment. AIM: To assess the strength of evidence used in the assignment of Ischaemic Heart Disease (IHD) as causes of death from VA. METHODS: The sample frame for this study is the 4,070 deaths that had IHD assigned as the underlying cause in the SRS 2016 database. From these, 400 cases were randomly selected. A data extraction form and data entry template were designed to collect relevant data about IHD from VA questionnaires. A standardised categorisation was designed to assess the strength of evidence used to infer IHD as a cause of death. A pilot test of 50 cases was carried out. IBM SPSS software was used in this study. RESULTS: Strong evidence of IHD as a cause of death was assigned based on surgery for coronary heart disease, chest pain and two out of: sudden death, history of heart disease, medical diagnosis of heart disease, or terminal shortness of breath. More than half (53%) of the questionnaires contained strong evidence. For deaths outside health facilities, VA questionnaires for male deaths contained acceptable evidence in significantly higher proportions as compared to those for female deaths. (P < 0.001). Nearly half of all IHD deaths were concentrated in the 50-69 year age group (48.40%), and a further 36.10% were aged 70 years or more. Nearly two-thirds of the deceased were male (58.40%). Smoking behaviour was found in 44.11% of IHD deaths, but this figure was 73.82% among males. CONCLUSION: More than half of the VA questionnaires from the study sample were found to contain strong evidence to infer IHD as the cause of death. Results from medical records such as electrocardiograms, coronary angiographies, and load tests could have improved the strength of evidence and contributed to IHD cause of death diagnosis.

Elements of a strategic approach for strengthening national mortality statistics programmes.

Information on cause-specific mortality from civil registration and vital statistics (CRVS) systems is essential for health policy and epidemiological research. Currently, there are critical gaps in the international availability of timely and reliable mortality data, which limits planned progress towards the UN Sustainable Development Goals. This article describes an evidence-based strategic approach for strengthening mortality data from CRVS systems. National mortality data availability scores from the Global Burden of Disease study were used to group countries into those with adequate, partial or negligible mortality data. These were further categorised by geographical region and population size, which showed that there were shortcomings in availability of mortality data in approximately two-thirds of all countries. Existing frameworks for evaluating design and functional status of mortality components of CRVS systems were reviewed to identify themes and topics for assessment. Detailed national programme assessments can be used to investigate systemic issues that are likely to affect death reporting, cause of death ascertainment and data management. Assessment findings can guide interventions to strengthen system performance. The strategic national approach should be customised according to data availability and population size and supported by human and institutional capacity building. Countries with larger populations should use an incremental sampling approach to strengthen CRVS systems and use interim data for mortality estimation. Periodic data quality evaluation is required to monitor system performance and scale up interventions. A comprehensive implementation and operations research programme should be concurrently launched to evaluate the feasibility, success and sustainability of system strengthening activities.

Building Capacity for Mortality Statistics Programs: Perspectives from the Indonesian Experience.

Information on deaths by age, sex, and cause are primary inputs for health policy and epidemiological research. Currently, most developing countries lack efficient death registration systems that generate these data on a routine and timely basis. The global community is promoting initiatives to establish and strengthen national mortality statistics programs across the developing world. Building human, technical, and institutional capacity to operate these programs are essential elements for the program. In Indonesia, the government has established a national Sample Registration System (SRS) covering a population of 9 million and is looking toward further scaling up of operations of the mortality statistics program in conjunction with expansion of the national Civil Registration and Vital Statistics (CRVS) systems. This article reports the theoretical and practical perspectives gained from experiences in developing human capacity in the Indonesian context. These perspectives are described in terms of the institutional, personnel, and functional components of the program for collection, compilation, analysis, and utilisation of mortality and cause of death data. The article also describes the challenges and potential solutions for implementing capacity building activities at national and subnational level. In conclusion, the need for and availability of training resources are discussed, including the potential for involvement of public health academia and international collaborations within a research framework on program management, quality evaluation, and data utilisation. Adequate attention to capacity building is essential to ensure the success and sustainability of national mortality statistics programs.

Changes in proportional mortality from diabetes and circulatory disease in Mauritius and Fiji: possible effects of coding and certification.

BACKGROUND: Many developing countries are experiencing the epidemiological transition, with the majority of deaths attributed to cardiovascular disease, cancer, Type 2 diabetes (T2DM) and others. In some countries, large proportional mortality attributed to diabetes is evident in official mortality statistics, with Mauritius and Fiji rated as the highest in the world. METHODS: This study investigates trends in recorded diabetes and cardiovascular disease mortality in Mauritius and Fiji under coding from the International Classification of Diseases (ICD) versions 9 and 10, using mortality data reported from these countries to the World Health Organization (WHO). RESULTS: In Mauritius over 1981-2004, T2DM proportional mortality varied between 4% and 7% in males (M) and 5% and 9% in females (F). In 2005 there was a sudden increase to M 20% and F 25%, which continued to M 25% and F 30% by 2012. Over 1981-2004 the proportion of circulatory disease mortality rose from 44% to 49% in males, and from 46% to 57% in females. In 2005, circulatory disease mortality proportions fell precipitously to 34% in males and 37% in females, and declined to 31% and 34% by 2013. ICD-10 coding was introduced in 2005. In Fiji, sharp rises in proportional T2DM mortality from 3% in both sexes in 2001 to M 15% and F 20% in 2002 were followed by more gradual trend increases to M 20% and F 26% by 2012-13. Circulatory disease proportions fell steeply from M 57% and F 53% in 2001 to M 44% and M 38% by 2004, with subsequent less steep declines to M 39% and F 30% by 2012. ICD-10 coding was introduced in 2001. CONCLUSIONS: Large, abrupt changes in diabetes and circulatory disease proportional mortality in Fiji and Mauritius coincided with the local introduction of ICD-10 coding in different years. There is also evidence for diabetes-related misclassification of underlying cause of death in Australia and the USA. These artefacts can undermine accurate monitoring of cause of death for evaluation of effectiveness of prevention and control, especially of circulatory disease mortality which is demonstrably reversible in populations.

Cause-specific mortality estimates for Malaysia in 2013: results from a national sample verification study using medical record review and verbal autopsy.

BACKGROUND: Mortality indicators are essential for monitoring population health. Although Malaysia has a functional death registration system, the quality of information on causes of death still needs improvement, since approximately 30% of deaths are classified to poorly defined causes. This study was conducted to verify registered causes in a sample of deaths in 2013 and utilise the findings to estimate cause-specific mortality indicators for Malaysia in 2013. METHODS: This is a cross-sectional study involving a nationally representative sample of 14,497 deaths distributed across 19 districts. Registered causes of deaths were verified using standard medical record review protocols for hospital deaths, and locally adapted international standard verbal autopsy procedures for deaths outside hospitals. The findings were used to measure the validity and reliability of the registration data, as well as to establish plausible cause-specific mortality fractions for hospital and non-hospital deaths, which were subsequently used as the basis for estimating national cause-specific mortality indicators. RESULTS: The overall response rate for the study was 67%. Verified causes of 5041 hospital deaths and 3724 deaths outside hospitals were used to derive national mortality estimates for 2013 by age, sex and cause. The study was able to reclassify most of the ill-defined deaths to a specific cause. The leading causes of deaths for males were Ischaemic Heart Disease (15.4%), Cerebrovascular diseases (13.7%), Chronic Obstructive Pulmonary Disease (8.5%) and Road Traffic Accident (8.0%). Among females, the leading causes were Cerebrovascular diseases (18.3%), Ischaemic Heart Disease (12.7%), Lower Respiratory Infections (11.5%) and Diabetes Mellitus (7.2%). CONCLUSIONS: Investigation of registered causes of death using verbal autopsy and medical record review yielded adequate information to enable estimation of cause-specific mortality indicators in Malaysia. Strengthening the national mortality statistics system must be made a priority as it is a core data source for policy and evaluation of the public health and healthcare sectors in Malaysia.