Show simple item record

dc.creatorDicker, Daniel
dc.creatorNguyen, Grant
dc.creatorAbate, Degu
dc.creatorAbate, Kalkidan Hassen
dc.creatorAbay, Solomon M
dc.creatorAbbafati, Cristiana
dc.creatorAbbasi, Nooshin
dc.creatorAbbastabar, Hedayat
dc.creatorAbd-Allah, Foad
dc.creatorAbdela, Jemal
dc.description.abstractBackground Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (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-specific 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 different 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-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant 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.es_ES
dc.publisherThe Lancetes_ES
dc.rightsCC0 1.0 Universal*
dc.subjectStatistical methodses_ES
dc.subjectMortality patternses_ES
dc.titleGlobal, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017es_ES
dcterms.references1 Harkness AG. Age at marriage and at death in the Roman Empire. Trans Am Philol Assoc 1896; 27: 35–72. 2 Scheidel W. Disease and death in the ancient city of Rome. Rochester: Social Science Research Network, 2009. (accessed July 13, 2018). 3 UN. Sustainable development knowledge platform. (accessed July 13, 2018). 4 GBD 2016 Mortality Collaborators. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017; 390: 1084–150. 5 Ahmad OB, Lopez AD, Inoue M. The decline in child mortality: a reappraisal. Bull World Health Organ 2000; 78: 1175–91. 6 You D, Jin NR, Wardlaw T. Levels & trends in child mortality. 2012. (accessed July 13, 2018). 7 Centers for Disease Control and Prevention (CDC). Trends in aging—United States and worldwide. MMWR Morb Mortal Wkly Rep 2003; 52: 101–04, 106. 8 Roser M. Life expectancy. Our World in Data, 2018. (accessed July 13, 2018). 9 US Burden of Disease Collaborators. The State of US health, 1990–2016: burden of disease, injuries, and risk factors among US States. JAMA 2018; 319: 1444–72. 10 Dwyer-Lindgren L, Bertozzi-Villa A, Stubbs RW, et al. Inequalities in life expectancy among US counties, 1980 to 2014: temporal trends and key drivers. JAMA Intern Med 2017; 177: 1003–11. 11 Kochanek KD, Murphy SL, Xu J, Arias E. Mortality in the United States, 2016. NCHS Data Brief No. 293, December 2017. (accessed April 9, 2018). 12 Newton JN, Briggs ADM, Wolfe CDA. Changes in health in England, with analysis by English regions and areas of deprivation, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015; 386: 2257–74. 13 Fransham M, Dorling D. Have mortality improvements stalled in England? BMJ 2017; 357: j1946. 14 Wang H, Abajobir AA, Abate KH, et al. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017; 390: 1084–150. 15 Mokdad AH, Forouzanfar MH, Daoud F, et al. Health in times of uncertainty in the eastern Mediterranean region, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet Glob Health 2016; 4: e704–13. 16 Gómez-Dantés H, Fullman N, Lamadrid-Figueroa H, et al. Dissonant health transition in the states of Mexico, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2016; 388: 2386–402. 17 Preston SH, Vierboom YC, Stokes A. The role of obesity in exceptionally slow US mortality improvement. Proc Natl Acad Sci USA 2018; 115: 957–61. 18 Walls HL, Backholer K, Proietto J, McNeil JJ. Obesity and trends in life expectancy. J Obesity 2012; 2012: 107989. 19 Angelantonio ED, Bhupathiraju SN, Wormser D, et al. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet 2016; 388: 776–86. 20 Groenewald P, Nannan N, Bourne D, Laubscher R, Bradshaw D. Identifying deaths from AIDS in South Africa. AIDS 2005; 19: 193–201. 21 Kahn K, Garenne ML, Collinson MA, Tollman SM. Mortality trends in a new South Africa: hard to make a fresh start. Scand J Public Health Suppl 2007; 69: 26–34. 22 National Research Council (US) Committee on Population. Bobadilla JL, Costello CA, and Mitchell F, eds. Premature death in the new independent states. Washington: National Academies Press (US), 1997. 23 National Research Council (US) Committee on Population, Bobadilla JL, Costello CA, Mitchell F, eds. Epidemiological transitions in the formerly socialist economies: divergent patterns of mortality and causes of death. National Academies Press (US), 1997. 24 UN Department of Economic and Social Affairs. World population prospects: the 2017 revision. publications/world-population-prospects-the-2017-revision.html (accessed April 7, 2018). 25 United States Census Bureau. International data base. https://www. html (accessed April 8, 2018). 26 WHO. WHO methods and data sources for global burden of disease estimates 2000–2011. GlobalDALYmethods_2000_2011.pdf (accessed April 8, 2018). 27 National Bureau of Statistics of China. National data. http://data. (accessed April 8, 2018). 28 Government of India. Mortality. Open government data (OGD) platform India. (accessed April 8, 2018). 29 National Bureau of statistics (Nigeria). Population and vital statistics. pdf.[search]=vital (accessed April 8, 2018). 30 GBD 2015 Mortality and Causes of Death Collaborators. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388: 1459–544. 31 GBD 2017 Population and Fertility collaborators. Population and fertility by age and sex for 195 countries and territories 1950–2017: a systematic analysis for the Global Burden of Disease 2017. Lancet 2018; 392: 1995–2051. 32 Stevens GA, Alkema L, Black RE, et al. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Lancet 2016; 388: e19–23. 33 Murray CJ, Rajaratnam JK, Marcus J, Laakso T, Lopez AD. What can we conclude from death registration? Improved methods for evaluating completeness. PLoS Med 2010; 7: e1000262. 34 Brass W. Demographic data analysis in less developed countries: 1946–1996. Pop Stud 1996; 50: 451–67. 35 Hill K. Estimating census and death registration completeness. Asian Pac Popul Forum 1987; 1: 8–13, 23–4. 36 Vincent P. La mortalité des vieillards. Population 1951; 6: 181–204. 37 Bennett NG, Horiuch S. Estimating the completeness of death registration in a closed population. Popul Index 1981; 47: 207–21. 38 Hill K, You D, Choi Y. Death distribution methods for estimating adult mortality: Sensitivity analysis with simulated data errors. Demogr Res 2009; 21: 235–54. 39 Rajaratnam JK, Tran LN, Lopez AD, Murray CJL. Measuring under-five mortality: validation of new low-cost methods. PLoS Med 2010; 7: e1000253. 40 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. 41 Department of International Economic and Social Affairs. Manual X. Indirect techniques for demographic estimation: a collaboration of the Population Division of the Department of International Economic and Social Affairs of the United Nations Secretariat with the Committee on Population and Demography of the National Research Council, United States National Academy of Sciences. New York: United Nations, 1983. 42 Global Burden of Disease Health Financing Collaborator Network. Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40. Lancet 2018; 391: 1783–98. 43 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. 44 Murray CJL, Ortblad KF, Guinovart C, et al. Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384: 1005–70. 45 Ghys PD, Brown T, Grassly NC, et al. The UNAIDS Estimation and Projection Package: a software package to estimate and project national HIV epidemics. Sex Transm Infect 2004; 80 (suppl 1): i5–9. 46 McKeown T. The role of medicine: dream, mirage, or nemesis? Princeton: Princeton University Press, 2014. 47 Preston SH. The changing relation between mortality and level of economic development. Int J Epidemiol 2007; 36: 484–90. 48 EM-DAT. The international disasters database. https://www.emdat. be/index.php (accessed July 13, 2018). 49 Grangereau P. La Chine creuse ses trous de mémoire. Libération. June 17, 2011. (accessed July 13, 2018). 50 Emslie C, Hunt K. The weaker sex? Exploring lay understandings of gender differences in life expectancy: a qualitative study. Soc Sci Med 2008; 67: 808–16. 51 Coale AJ, Demeny PG, Vaughan B. Regional model life tables and stable populations. New York: Academic, 1983. 52 United Nations. Age and sex patterns of mortality: model life tables for under-developed countries. Population Studies, No. 22. Department of Social Affairs. Sales No. 1955.XIII.9. New York: United Nations, 1955. 53 Gakidou E, King G. Death by survey: estimating adult mortality without selection bias from sibling survival data. Demography 2006; 43: 569–85. 54 Masquelier B. Adult mortality from sibling survival data: a reappraisal of selection biases. Demography 2013; 50: 207–28.es_ES

Files in this item


This item appears in the following Collection(s)

Show simple item record

CC0 1.0 Universal
Except where otherwise noted, this item's license is described as CC0 1.0 Universal