Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

Expanding japanese encephalitis vaccination to selected endemic indonesia provinces: A cost-effectiveness analysis

Introduction

A Markov model was used to evaluate the potential health and economic impact of introducing JE vaccine nationally and in selected endemic areas of Indonesia compared to no vaccination from government and societal perspectives over a child’s lifetime horizon.

Methods

Costs were obtained from hospitalized JE suspected patient billing data from 2014 to 2019 in seven provinces. Local data burden data were derived from the literature. Analysis considered several scenarios, including national and sub-regional introduction in seven provinces via a one-time vaccination campaign in all children 1–15 years old followed by routine immunization among infants (RI), or RI alone without vaccination campaign.

Results and discussions

Across scenarios, JE vaccination was projected to range from cost-saving to cost-effective compared to no vaccination at a willingness-to-pay threshold of 0.5x gross domestic product per capita. Including a one-time campaign would avert nearly three times as many JE cases and deaths compared to RI alone while still providing good value for money.

Performance of the tariff method and physicians in determining stroke as the cause of deaths using verbal autopsy in areas with a limited number of physicians: cases in Indonesia

Background: Physician-certified verbal autopsy (PCVA) is the primary method used to determine the cause of death in Indonesia, although it is very costly and problematic to use in areas where physicians are not widely available with most deaths occur at home. The Tariff method has been piloted to obtain an alternative approach that does not require a physician to determine the cause of death. This validation study presents how the Tariff captures the correctness and distinctiveness of stroke symptoms to the PCVA. Methods: Medical records of 298 adult deaths that occured in four teaching hospitals in the Jakarta from  January 1, 2015 to March 2017 were collected prospectively. Verbal Autopsy (VA) was applied using the 2014 WHO instrument diagnosed by a trained physician (PCVA) and by Tariff method. The validity of the VA was assessed by comparing the PCVA diagnoses with the Tariff diagnoses, referring to the best standard. Results. Sensitivity, specificity and positive predictive value (PPV) of VAs using physician’s diagnosis (PCVA) for stroke were 73.9%, 73.5% and 93.4% respectively. The corresponding sensitivity, specificity and positive predictive value (PPV) of VAs diagnosed by the Tariff method were 75%, 61% and 91%. The negative predictive values (NPV) of both techniques were low, 35.6% and 32.6% respectively. Conclusion: The performance of the Tariff method for stroke was almost similar with  PCVA, and with a narrower variation, or more consistent than PCVA. Therefore, the Tariff method is a potential alternative to be used on a large scale, because the difficult geographical conditions where physician are not widely available for causes of deaths with distinct signs and symptoms. Keywords: verbal autopsy, sensitivity, specificity, determining cause of death, physician, tariff method   Abstrak Latar Belakang: Autopsi verbal yang disertifikasi oleh dokter (PCVA) merupakan metode utama yang digunakan untuk memastikan penyebab kematian di Indonesia. Meskipun sangat mahal dan bermasalah untuk digunakan di daerah di mana dokter tidak banyak tersedia dan sebagian besar kematian terjadi di rumah. Metode Tarif telah diujicobakan untuk mendapatkan pendekatan alternatif yang tidak memerlukan dokter untuk menentukan penyebab kematian. Studi validasi ini menyajikan bagaimana Tarif menangkap kebenaran dan kekhasan gejala stroke dibandingkan dengan PCVA. Metode: Rekam medis dari 298 kematian orang dewasa yang terjadi di empat rumah sakit studi di wilayah Jakarta pada 1 Januari 2015 hingga Maret 2017 dikumpulkan secara prospektif. Autopsi verbal (AV) dilakukan dengan menggunakan instrumen WHO 2014 yang didiagnosis oleh dokter terlatih (PCVA) dan metode Tarif. Validitas AV dinilai dengan membandingkan diagnosis PCVA dengan diagnosis metode Tarif, mengacu pada baku mutu. Hasil. Sensitivitas, spesifisitas dan nilai prediksi positif (PPV) dari AV dengan diagnosis dokter (PCVA) untuk stroke adalah 73,9%, 73,5% dan 93,4%. Sensitivitas, spesifisitas, dan nilai prediksi positif (PPV) yang sesuai dari AV yang didiagnosis dengan metode Tariff adalah 75%, 61% dan 91%. Nilai prediksi negatif (NPV) dari kedua teknik itu rendah, masing-masing 35,6% dan 32,6%. Kesimpulan: Untuk stroke, kinerja metode Tarif hampir sama dengan PCVA, dan dengan variasi yang lebih sempit, atau lebih konsisten dibandingkan PCVA. Oleh karena itu, untuk penyebab kematian dengan tanda dan gejala yang berbeda, metode Tarif merupakan alternatif potensial untuk digunakan dalam skala besar, di Indonesia dimana banyak wilayah dengan geografis sulit dan dokter tidak selalu tersedia. Kata kunci: autopsi verbal, sensitifitas, spesifisitas, penentuan penyebab kematian, dokter, metode tariff  

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

Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017

BACKGROUND

Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries.

METHODS

We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).

FINDINGS

In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).

INTERPRETATION

Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.