Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019
Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensiv...
- Autores:
-
Wang, Haidong
alcalde rabanal, jacqueline elizabeth
Antonio, Carl Abelardo
Alvis-Guzmán, Nelson
Amini-Rarani, Mostafa
Andrei, Catalina Liliana
Babaee, Ebrahim
Barker-Collo, Lyn
Bisignano, Catherine
Nikolaevich Briko, Andrey
Dahlawi, Saad
Daryani, Ahmad
Gallus, Silvano
Gitimoghaddam, Mojgan
Hassankhani, Hadi
Househ, Mowafa
kamiab, zahra
Khazaei, Salman
Kosen, Soewarta
Linn, Shai
Mahasha, Phetole
Moghadaszadeh Ahrabi, Masoud
Mohammadpourhodki, Reza
Samad, Zainab
Santric Milicevic, Milena
Shaheen, Amira A
Sharma, Rajesh
Topouzis, Fotis
Unnikrishnan, Bhaskaran
Valli, Alessandro
Wiangkham, Taweewat
Yoon, Seok-Jun
yusefzadeh, hasan
Ziapour, Arash
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
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- Acceso en línea:
- https://hdl.handle.net/11323/8115
https://doi.org/10.1016/S0140-6736(20)30977-6
https://repositorio.cuc.edu.co/
- Palabra clave:
- HIV
Fertility
Mortality
- Rights
- openAccess
- License
- CC0 1.0 Universal
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dc.title.spa.fl_str_mv |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
title |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
spellingShingle |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 HIV Fertility Mortality |
title_short |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
title_full |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
title_fullStr |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
title_full_unstemmed |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
title_sort |
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019 |
dc.creator.fl_str_mv |
Wang, Haidong alcalde rabanal, jacqueline elizabeth Antonio, Carl Abelardo Alvis-Guzmán, Nelson Amini-Rarani, Mostafa Andrei, Catalina Liliana Babaee, Ebrahim Barker-Collo, Lyn Bisignano, Catherine Nikolaevich Briko, Andrey Dahlawi, Saad Daryani, Ahmad Gallus, Silvano Gitimoghaddam, Mojgan Hassankhani, Hadi Househ, Mowafa kamiab, zahra Khazaei, Salman Kosen, Soewarta Linn, Shai Mahasha, Phetole Moghadaszadeh Ahrabi, Masoud Mohammadpourhodki, Reza Samad, Zainab Santric Milicevic, Milena Shaheen, Amira A Sharma, Rajesh Topouzis, Fotis Unnikrishnan, Bhaskaran Valli, Alessandro Wiangkham, Taweewat Yoon, Seok-Jun yusefzadeh, hasan Ziapour, Arash |
dc.contributor.author.spa.fl_str_mv |
Wang, Haidong alcalde rabanal, jacqueline elizabeth Antonio, Carl Abelardo Alvis-Guzmán, Nelson Amini-Rarani, Mostafa Andrei, Catalina Liliana Babaee, Ebrahim Barker-Collo, Lyn Bisignano, Catherine Nikolaevich Briko, Andrey Dahlawi, Saad Daryani, Ahmad Gallus, Silvano Gitimoghaddam, Mojgan Hassankhani, Hadi Househ, Mowafa kamiab, zahra Khazaei, Salman Kosen, Soewarta Linn, Shai Mahasha, Phetole Moghadaszadeh Ahrabi, Masoud Mohammadpourhodki, Reza Samad, Zainab Santric Milicevic, Milena Shaheen, Amira A Sharma, Rajesh Topouzis, Fotis Unnikrishnan, Bhaskaran Valli, Alessandro Wiangkham, Taweewat Yoon, Seok-Jun yusefzadeh, hasan Ziapour, Arash |
dc.subject.spa.fl_str_mv |
HIV Fertility Mortality |
topic |
HIV Fertility Mortality |
description |
Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed agespecific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring |
publishDate |
2020 |
dc.date.issued.none.fl_str_mv |
2020-10-17 |
dc.date.accessioned.none.fl_str_mv |
2021-04-09T15:00:43Z |
dc.date.available.none.fl_str_mv |
2021-04-09T15:00:43Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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acceptedVersion |
dc.identifier.issn.spa.fl_str_mv |
01406736 1474547X |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/8115 |
dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/S0140-6736(20)30977-6 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
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01406736 1474547X Corporación Universidad de la Costa REDICUC - Repositorio CUC |
url |
https://hdl.handle.net/11323/8115 https://doi.org/10.1016/S0140-6736(20)30977-6 https://repositorio.cuc.edu.co/ |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.references.spa.fl_str_mv |
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Lancet 2016; 388: 1459–544. 19 Stevens GA, Alkema L, Black RE, et al. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Lancet 2016; 388: e19–23. 20 Obermeyer Z, Rajaratnam JK, Park CH, et al. Measuring adult mortality using sibling survival: a new analytical method and new results for 44 countries, 1974–2006. PLoS Med 2010; 7: e1000260. 21 Coale AJ. Demeny, Paul George. Regional model life tables and stable populations. Princeton, NJ: Princeton University Press, 1966. 22 UN. Model life tables for developing countries. 1982. https://www. un.org/en/development/desa/population/publications/manual/ model/life-tables.asp (accessed Jan 24, 2020) 23 Wilmoth J, Zureick S, Canudas-Romo V, Inoue M, Sawyer C. A flexible two-dimensional mortality model for use in indirect estimation. Popul Stud (Camb) 2012; 66: 1–28. 24 Wang H, Dwyer-Lindgren L, Lofgren KT, et al. 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Reconstructing past populations with uncertainty from fragmentary data. J Am Stat Assoc 2013; 108: 96–110. 29 Murray CJL, Ferguson BD, Lopez AD, Guillot M, Salomon JA, Ahmad O. Modified logit life table system: principles, empirical validation, and application. Popul Stud 2003; 57: 165–82. 30 UNHCR. Global report 2018. Geneva, Switzerland: The UN Refugee Agency, 2018. 31 Kyu HH, Abate D, Abate KH, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018; 392: 1859–922. 32 Zheng P, Aravkin AY, Barber R, Sorensen RJD, Murray CJL. Trimmed constrained mixed effects models: formulations and algorithms. arXiv 2019; published online Sept 24. http://arxiv.org/ abs/1909.10700 (preprint). 33 Zaidi B, Morgan SP. The second demographic transition theory: a review and appraisal. Annu Rev Sociol 2017; 43: 473–92. 34 Gakidou E, Cowling K, Lozano R, Murray CJ. Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: a systematic analysis. Lancet 2010; 376: 959–74. 35 Cutler DM, Lleras-Muney A. Understanding differences in health behaviors by education. J Health Econ 2010; 29: 1–28. 36 Baird S, Friedman J, Schady N. Aggregate income shocks and infant mortality in the developing world. Rev Econ Stat 2010; 93: 847–56. 37 Brinda EM, Rajkumar AP, Enemark U. Association between gender inequality index and child mortality rates: a cross-national study of 138 countries. BMC Public Health 2015; 15: 97 38 Marphatia AA, Cole TJ, Grijalva-Eternod C, Wells JCK. Associations of gender inequality with child malnutrition and mortality across 96 countries. Glob Health Epidemiol Genom 2016; 1: e6. 39 Anderson S, Ray D. Missing women: age and disease. Rev Econ Stud 2010; 77: 1262–300. 40 Wynes S, Nicholas KA. The climate mitigation gap: education and government recommendations miss the most effective individual actions. Environ Res Lett 2017; 12: 074024. 41 Scutchfield FD, Keck CW. Deaths of despair: why? What to do? Am J Public Health 2017; 107: 1564–65. 42 Bloom DE, Chatterji S, Kowal P, et al. Macroeconomic implications of population ageing and selected policy responses. Lancet 2015; 385: 649–57. 43 Bloom DE, Canning D, Fink G. Implications of population ageing for economic growth. Oxf Rev Econ Policy 2010; 26: 583–612. 44 Bloom DE, Williamson JG. Demographic transitions and economic miracles in emerging Asia. World Bank Econ Rev 1998; 12: 419–55. 45 UN. Global compact for migration. United Nations, 2018. https://refugeesmigrants.un.org/migration-compact (accessed Sept 28, 2019). 46 Malak N, Rahman MM, Yip TA. Baby bonus, anyone? Examining heterogeneous responses to a pro-natalist policy. J Popul Econ 2019; 32: 1205–46. 47 UN Department of Economic and Social Affairs. Population Division. United Nations expert group meeting on policy responses to low fertility. New York; Nov 2–3, 2015. https://www.un.org/en/ development/desa/population/events/expert-group/24/index.asp (accessed Jan 28, 2020). 48 Feng W, Gu B, Cai Y. The end of China’s one-child policy. Stud Fam Plann 2016; 47: 83–86 49 Caldwell JC. Routes to low mortality in poor countries. Popul Dev Rev 1986; 12: 171–220. 50 Palloni A. Fertility and mortality decline in Latin America. Ann Am Acad Pol Soc Sci 1990; 510: 126–44. 51 UNICEF. Under-five mortality. UNICEF data. September, 2019. https://data.unicef.org/topic/child-survival/under-five-mortality (accessed Jan 28, 2020). 52 UN Department of Economic and Social Affairs. Population Division. World Population Prospects 2019: data booklet. New York, NY: United Nations, 2019. |
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Wang, Haidongalcalde rabanal, jacqueline elizabethAntonio, Carl AbelardoAlvis-Guzmán, NelsonAmini-Rarani, MostafaAndrei, Catalina LilianaBabaee, EbrahimBarker-Collo, LynBisignano, CatherineNikolaevich Briko, AndreyDahlawi, SaadDaryani, AhmadGallus, SilvanoGitimoghaddam, MojganHassankhani, HadiHouseh, Mowafakamiab, zahraKhazaei, SalmanKosen, SoewartaLinn, ShaiMahasha, PhetoleMoghadaszadeh Ahrabi, MasoudMohammadpourhodki, RezaSamad, ZainabSantric Milicevic, MilenaShaheen, Amira ASharma, RajeshTopouzis, FotisUnnikrishnan, BhaskaranValli, AlessandroWiangkham, TaweewatYoon, Seok-Junyusefzadeh, hasanZiapour, Arash2021-04-09T15:00:43Z2021-04-09T15:00:43Z2020-10-17014067361474547Xhttps://hdl.handle.net/11323/8115https://doi.org/10.1016/S0140-6736(20)30977-6Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed agespecific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoringWang, Haidongalcalde rabanal, jacqueline elizabeth-will be generated-orcid-0000-0002-9172-2302-600Antonio, Carl Abelardo-will be generated-orcid-0000-0001-7476-0553-600Alvis-Guzmán, Nelson-will be generated-orcid-0000-0001-9458-864X-600Amini-Rarani, MostafaAndrei, Catalina Liliana-will be generated-orcid-0000-0003-4990-0205-600Babaee, Ebrahim-will be generated-orcid-0000-0001-7969-9122-600Barker-Collo, LynBisignano, CatherineNikolaevich Briko, AndreyDahlawi, Saad-will be generated-orcid-0000-0001-6178-9306-600Daryani, Ahmad-will be generated-orcid-0000-0001-8571-5803-600Gallus, Silvano-will be generated-orcid-0000-0002-8967-0400-600Gitimoghaddam, MojganHassankhani, HadiHouseh, Mowafa-will be generated-orcid-0000-0002-3648-6271-600kamiab, zahra-will be generated-orcid-0000-0001-6670-1828-600Khazaei, Salman-will be generated-orcid-0000-0001-5918-2310-600Kosen, Soewarta-will be generated-orcid-0000-0002-2517-8118-600Linn, ShaiMahasha, Phetole-will be generated-orcid-0000-0002-5750-3595-600Moghadaszadeh Ahrabi, Masoud-will be generated-orcid-0000-0002-3946-0325-600Mohammadpourhodki, Reza-will be generated-orcid-0000-0001-5677-0133-600Samad, Zainab-will be generated-orcid-0000-0003-2422-3199-600Santric Milicevic, Milena-will be generated-orcid-0000-0002-0684-359X-600Shaheen, Amira ASharma, RajeshTopouzis, Fotis-will be generated-orcid-0000-0002-8966-537X-600Unnikrishnan, BhaskaranValli, Alessandro-will be generated-orcid-0000-0003-2547-3181-600Wiangkham, Taweewat-will be generated-orcid-0000-0003-4115-704X-600Yoon, Seok-Junyusefzadeh, hasan-will be generated-orcid-0000-0001-9919-0235-600Ziapour, Arashapplication/pdfengCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2The Lancethttps://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30977-6/fulltextHIVFertilityMortalityGlobal age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019Artículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion1 UN Statistics Division. 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New York, NY: United Nations, 2019.PublicationORIGINALGlobal age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories.pdfGlobal age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories.pdfapplication/pdf3517835https://repositorio.cuc.edu.co/bitstreams/407d1024-cd82-4cff-9215-81814718f0e7/downloadd47039be650bde98afef9c3651e528b1MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstreams/decc55bb-e7dd-476a-82d9-8a40c3c33595/download42fd4ad1e89814f5e4a476b409eb708cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/c5a5b759-6a4d-4141-9264-9d99d985ecdb/downloade30e9215131d99561d40d6b0abbe9badMD53THUMBNAILGlobal age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and 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