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Record W6991413919

Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017.

2018· other· en· W6991413919 on OpenAlexfundno aff

Bibliographic record

VenueChalmers Research (Chalmers University of Technology) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteUniversité de LimogesCenter for International HealthEconomic and Social Research CouncilMedical Research CouncilWeill Cornell Medicine - QatarAbbott DiagnosticsInjury Prevention Research CenterCochrane South AfricaUniwersytet OpolskiDebre Markos UniversityGeorge Institute for Global HealthFrankfurt University of Applied SciencesKurdistan University Of Medical SciencesH. Lundbeck A/SServierUniversitas HasanuddinSavitribai Phule Pune UniversityUniversity of ThessalyUniversity of ZanjanUniversity of HailPomorski Uniwersytet Medyczny W SzczecinieZanjan University of Medical SciencesTarbiat Modares UniversityResearch Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesUniversity of GondarCollege of Engineering, Michigan State UniversityTartu ÜlikoolUniversitatea de Medicină şi Farmacie "Carol Davila" BucureştiUniversity of South AfricaUniversity of the PhilippinesArak University of Medical SciencesQazvin University of Medical SciencesI.M. Sechenov First Moscow State Medical UniversityHospital for Sick ChildrenDebre Tabor UniversityShahid Beheshti University of Medical SciencesBaqiyatallah University of Medical SciencesUniversity of HaifaKermanshah University of Medical SciencesShiraz UniversityUnited Arab Emirates UniversityAhvaz Jundishapur University of Medical SciencesAstellas PharmaNational Institutes of HealthChinese University of Hong KongSyddansk UniversitetJimma UniversityZahedan University of Medical SciencesHaramaya UniversitySichuan UniversityInyuvesi Yakwazulu-NataliUniversiti Sains MalaysiaUniversiti Kebangsaan MalaysiaTehran University of Medical Sciences and Health ServicesIsfahan University of Medical SciencesUniversiti MalayaAin Shams UniversityShiraz University of Medical SciencesKing Abdulaziz UniversitySanjay Gandhi Postgraduate Institute of Medical SciencesUniversity of TorontoLunds UniversitetSouth African Medical Research CouncilBundesministerium für GesundheitNational and Kapodistrian University of AthensCairo UniversitySimmons CollegeKing Saud UniversityFriedrich-Schiller-Universität JenaQueensland University of TechnologyUniversity of Technology SydneyUniversity College CorkMekelle UniversityUniversiteit StellenboschPublic Health EnglandUniversité de BordeauxPublic Health Foundation of IndiaIndian Council of Medical ResearchNational Health and Medical Research CouncilHebrew University of JerusalemUniversidad de ExtremaduraKwame Nkrumah University of Science and TechnologySwansea UniversityNational University of SingaporeLa Trobe UniversityAmerican University of BeirutCardiff UniversityMcMaster UniversityUniversity of LeicesterNational Institute for Health and Care ResearchMinistry of Health and Medical EducationMazandaran University of Medical SciencesUniversity of GlasgowKorea Health Industry Development InstituteYork UniversityKorea UniversityKeimyung UniversityUniversity of CanberraDilla UniversityMaragheh University of Medical SciencesAmgenPublic Health Agency of CanadaChinese Center for Disease Control and PreventionNew York University Abu DhabiNovavaxUniwersytet Jagielloński Collegium MedicumKarl-Franzens-Universität GrazSeattle Children's Research InstituteU.S. Department of Veterans AffairsRafsanjan University of Medical SciencesAhmadu Bello UniversitySamara UniversityNational Cerebral and Cardiovascular CenterJordan University of Science and TechnologyUniversity of OxfordPublic Health AgencyMcGill UniversityUniversity of Cape TownHorizon PharmaceuticalsBirzeit UniversityNational Cancer InstituteSeoul National UniversityBurnet InstituteInternational Centre for Diarrhoeal Disease Research, BangladeshWashington University in St. LouisUniversidad de ChileUniversity of PittsburghIran University of Medical SciencesUniversidad de la República UruguayTulane UniversityJohns Hopkins UniversityAddis Ababa UniversityDanoneUniversità degli Studi di FirenzeBill and Melinda Gates FoundationMadras Diabetes Research FoundationPfizerHögskolan DalarnaUniversity of WashingtonUniversität UlmChalmers Tekniska HögskolaAlzheimer's AssociationNorwegian Institute of Public HealthMichigan State UniversityWeill Cornell Medical CollegeUniversity of PennsylvaniaBirmingham City UniversityUniwersytet ŁódzkiHelsingin YliopistoBall State UniversityKarolinska InstitutetUnited Nations Population FundVital StrategiesDamon Runyon Cancer Research FoundationChildren's Hospital of PhiladelphiaUniversity of West FloridaStudent Research Committee, Tabriz University of Medical SciencesMedizinische Universität GrazBahir Dar UniversityBayerMashhad University of Medical SciencesGilead SciencesGlaxoSmithKlineMansoura UniversityAstraZenecaUniversita degli Studi di Bari Aldo MoroHamadan University of Medical SciencesSouth Australian Health and Medical Research InstituteDamietta UniversitySanofiHawassa UniversityKuwait UniversityVetenskapsrådetOklahoma State UniversityUniversitat Pompeu FabraNorthwestern UniversityUnited States Agency for International Development
KeywordsLife expectancyCensusDemographic analysisPopulationLife tableMortality rateInfant mortalityBirth rateFertility
DOInot available

Abstract

fetched live from OpenAlex

Background: Assessments of age-specifc mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Afairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specifc mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in diferent components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings: Globally, 18·7% (95% uncertainty interval 18·4-19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2-59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5-49·6) to 70·5 years (70·1-70·8) for men and from 52·9 years (51·7-54·0) to 75·6 years (75·3-75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5-51·7) for men in the Central African Republic to 87·6 years (86·9-88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3-238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6-42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2-5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation: This analysis of age-sex-specifc mortality shows that there are remarkably complex patterns in population mortality across countries. The fndings of this study highlight global successes, such as the large decline in under-5 mortality, which refects signifcant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0010.009
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.137
GPT teacher head0.371
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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