Generating age-specific mortality statistics from incomplete death registration data: two applications of the empirical completeness method

Abstract Background The study aims to assess two approaches that apply the empirical completeness method to generate age-specific mortality statistics from incomplete death registration systems. Methods We use the empirical completeness method to calculate all-age death registration completeness, which is used with a model life table to generate mortality statistics and age-specific completeness using (1) the conventional method and (2) the equivalent deaths method. The results are compared with a capture-recapture (C-RC) study and three alternative mortality estimates for Brazilian states, and C-RC studies in Thailand, Oman and Vietnam, which independently estimate the level and age pattern of mortality or completeness. Results The empirical completeness method produces similar estimates of all-age completeness of registration to the C-RC studies. Compared with C-RC studies, at 15-59 years, the conventional method’s estimates of mortality and completeness are more concordant, while at 60-84 years the equivalent death method’s estimates are closer. Estimates of life expectancy from the two approaches each have similar concordance with the C-RC studies. For male adult mortality in Brazilian states, there is relatively strong average correlation of this study's estimates with three alternative estimates. Conclusions The two approaches produce mortality statistics from incomplete data that are mostly concordant with C-RC studies, and can be most usefully applied to subnational populations.

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Examining sex differences in the completeness of Peruvian CRVS data and adult mortality estimates

Genus ◽

10.1186/s41118-021-00151-5 ◽

2022 ◽

Vol 78 (1) ◽

Author(s):

Helena Cruz Castanheira ◽

José Henrique Costa Monteiro da Silva

Keyword(s):

Sex Differences ◽

Sex Difference ◽

Health Surveys ◽

Adult Mortality ◽

Data Sources ◽

Demographic And Health Surveys ◽

Death Registration ◽

Male And Female ◽

Health Related ◽

Mortality Estimates

AbstractThe production, compilation, and publication of death registration records is complex and usually involves many institutions. Assessing available data and the evolution of the completeness of the data compiled based on demographic techniques and other available data sources is of great importance for countries and for having timely and disaggregated mortality estimates. In this paper, we assess whether it is reasonable, based on the available data, to assume that there is a sex difference in the completeness of male and female death records in Peru in the last 30 years. In addition, we assess how the gap may have evolved with time by applying two-census death distribution methods on health-related registries and analyzing the information from the Demographic and Health Surveys and civil registries. Our findings suggest that there is no significant sex difference in the completeness of male and female health-related registries and, consequently, the sex gap currently observed in adult mortality estimates might be overestimated.

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Mortality estimates for WHO SEAR countries: problems and prospects

BMJ Global Health ◽

10.1136/bmjgh-2021-007177 ◽

2021 ◽

Vol 6 (11) ◽

pp. e007177

Author(s):

Chalapati Rao ◽

Kanitta Bundhamcharoen ◽

Matthew Kelly ◽

Viroj Tangcharoensathien

Keyword(s):

East Asia ◽

Empirical Data ◽

Relative Difference ◽

Vital Statistics ◽

Mortality Data ◽

Data Series ◽

South East Asia ◽

Mortality Statistics ◽

Specific Mortality ◽

Mortality Estimates

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.

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National, regional and global mortality due to alcoholic cardiomyopathy in 2015

Heart ◽

10.1136/heartjnl-2017-312384 ◽

2018 ◽

Vol 104 (20) ◽

pp. 1663-1669 ◽

Cited By ~ 18

Author(s):

Jakob Manthey ◽

Charlotte Probst ◽

Margaret Rylett ◽

Jürgen Rehm

Keyword(s):

Input Data ◽

Alcohol Use Disorders ◽

Mortality Rates ◽

Vital Statistics ◽

Alcoholic Cardiomyopathy ◽

Civil Registration ◽

Registration Data ◽

Mortality Burden ◽

Specific Mortality ◽

Mortality Estimates

Objectives(1) A comprehensive mortality assessment of alcoholic cardiomyopathy (ACM) and (2) examination of under-reporting using vital statistics data.MethodsA modelling study estimated sex-specific mortality rates for each country, which were subsequently aggregated by region and globally. Input data on ACM mortality were obtained from death registries for n=91 countries. For n=99 countries, mortality estimates were predicted using aggregate alcohol data from WHO publications. Descriptive additional analyses illustrated the scope of under-reporting.ResultsIn 2015, there were an estimated 25 997 (95% CI 17 385 to 49 096) global deaths from ACM. This translates into 6.3% (95% CI 4.2% to 11.9%) of all global deaths from cardiomyopathy being caused by alcohol. There were large regional variations with regard to mortality burden. While the majority of ACM deaths were found in Russia (19 749 deaths, 76.0% of all ACM deaths), for about one-third of countries (n=57) less than one ACM death was found. Under-reporting was identified for nearly every second country with civil registration data. Overall, two out of three global ACM deaths might be misclassified.ConclusionsThe variation of ACM mortality burden is greater than for other alcohol-attributable diseases, and partly may be the result of stigma and lack of detection. Misclassification of ACM fatalities is a systematic phenomenon, which may be caused by low resources, lacking standards and stigma associated with alcohol-use disorders. Clinical management may be improved by including routine alcohol assessments. This could contribute to decrease misclassifications and to provide the best available treatment for affected patients.

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Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data

BMJ Global Health ◽

10.1136/bmjgh-2021-005387 ◽

2021 ◽

Vol 6 (5) ◽

pp. e005387

Author(s):

Tim Adair ◽

Sonja Firth ◽

Tint Pa Pa Phyo ◽

Khin Sandar Bo ◽

Alan D Lopez

Keyword(s):

Cause Of Death ◽

Verbal Autopsy ◽

Integration Method ◽

Mortality Rates ◽

Vital Statistics ◽

Death Registration ◽

Chronic Respiratory Diseases ◽

Health Goals ◽

Specific Mortality ◽

Four Causes

IntroductionThe measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.MethodsThe integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.ResultsIn Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.ConclusionThis integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

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Self-reported health and adult mortality risk: An analysis of cause-specific mortality

Social Science & Medicine ◽

10.1016/j.socscimed.2003.01.001 ◽

2004 ◽

Vol 59 (6) ◽

pp. 1297-1306 ◽

Cited By ~ 198

Author(s):

Maureen Reindl Benjamins ◽

Robert A Hummer ◽

Isaac W Eberstein ◽

Charles B Nam

Keyword(s):

Mortality Risk ◽

Adult Mortality ◽

Specific Mortality ◽

Reported Health

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What are the implications of using individual and combined sources of routinely collected data to identify and characterise incident site-specific cancers? a concordance and validation study using linked English electronic health records data

BMJ Open ◽

10.1136/bmjopen-2020-037719 ◽

2020 ◽

Vol 10 (8) ◽

pp. e037719

Author(s):

Helen Strongman ◽

Rachael Williams ◽

Krishnan Bhaskaran

Keyword(s):

Primary Care ◽

Gold Standard ◽

Cancer Registration ◽

Data Sets ◽

Death Registration ◽

Case Definitions ◽

Predictive Values ◽

Site Specific ◽

Registration Data ◽

Electronic Health

ObjectivesTo describe the benefits and limitations of using individual and combinations of linked English electronic health data to identify incident cancers.Design and settingOur descriptive study uses linked English Clinical Practice Research Datalink primary care; cancer registration; hospitalisation and death registration data.Participants and measuresWe implemented case definitions to identify first site-specific cancers at the 20 most common sites, based on the first ever cancer diagnosis recorded in each individual or commonly used combination of data sources between 2000 and 2014. We calculated positive predictive values and sensitivities of each definition, compared with a gold standard algorithm that used information from all linked data sets to identify first cancers. We described completeness of grade and stage information in the cancer registration data set.Results165 953 gold standard cancers were identified. Positive predictive values of all case definitions were ≥80% and ≥94% for the four most common cancers (breast, lung, colorectal and prostate). Sensitivity for case definitions that used cancer registration alone or in combination was ≥92% for the four most common cancers and ≥80% across all cancer sites except bladder cancer (65% using cancer registration alone). For case definitions using linked primary care, hospitalisation and death registration data, sensitivity was ≥89% for the four most common cancers, and ≥80% for all cancer sites except kidney (69%), oral cavity (76%) and ovarian cancer (78%). When primary care or hospitalisation data were used alone, sensitivities were generally lower and diagnosis dates were delayed. Completeness of staging data in cancer registration data was high from 2012 (minimum 76.0% in 2012 and 86.4% in 2014 for the four most common cancers).ConclusionsAscertainment of incident cancers was good when using cancer registration data alone or in combination with other data sets, and for the majority of cancers when using a combination of primary care, hospitalisation and death registration data.

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