Ecological deprivation indices at the level of spatial units are often used to measure and monitor inequalities in health despite the possibility of ecological fallacy. For the purpose of this study, the European Deprivation Index (EDI) was used, which is based on Townsend theorization of relative deprivation. The Slovenian version of EDI (SI-EDI) at the aggregated level (SI-EDI-A) was calculated to the level of the national assembly polling stations. The SI-EDI was also calculated at the individual level (SI-EDI-I) by the method that represents a methodological innovation. The degree of ecological fallacy was estimated with the Receiver Operating Characteristics (ROC) curves. By calculating the area under the ROC curve, the ecological fallacy was evaluated numerically. Agreement between measuring deprivation with SI-EDI-A and SI-EDI-I was analysed by graphical methods and formal testing. The association of the socio-economic status and the cancer risk was analysed in all first cancer cases diagnosed in Slovenia at age 16 and older in the period 2011-2013. Analysis was done for each level separately, for SI-EDI-I and for SI-EDI-A. The Poisson regression model was implemented in both settings but adapted specifically for aggregated and individual data. The study clearly shows that ecological fallacy is unavoidable. However, although the association of cancer incidence and socio-economic deprivation at individual and aggregated levels was not the same for all cancer sites, the results were very similar for the majority of investigated cancer sites and especially for cancers associated with unhealthy lifestyles. The results confirm the assumptions from authors' previous research that using the level of the national assembly polling stations would be the acceptable way to aggregate data when explaining inequalities in health in Slovenia in ecological studies.
Intro -- Foreword -- Contents -- About the Editors -- Contributors -- Part I: General Considerations and Methodologic Aspects -- Chapter 1: Social Inequities in Cancer: Why Develop Scientific Research? -- References -- Chapter 2: Population-Based Cancer Registries: A Data Stream to Help Build an Evidence-Based Cancer Policy for Europe and for European Countries -- References -- Chapter 3: The European Deprivation Index: A Tool to Help Build an Evidence-Based Cancer Policy for Europe -- References -- Chapter 4: Social Disparities in Cancer Incidence: Methodological Considerations -- Introduction -- General Context -- Methodological Points -- Context of Spatial Analysis -- Bayesian Model for Smoothing Relative Risks -- Distribution of Hyperparameters σ2v and σ2u -- Regression Models with Covariates -- The Data -- The Results -- SIR, Smoothed SIR and Choice of Bayesian Model -- Regression Coefficients for the Explanatory Variables -- Sensitivity Analysis on the Choice of Hyper-Parameters -- Elements of Discussion -- Conclusion -- References -- Chapter 5: Social Disparities in Cancer Survival: Methodological Considerations -- Introduction -- Relative Survival Approaches -- Net Survival -- The Measure of Interest -- Estimation -- Age-Standardisation for Improving Comparability -- Measuring the Socioeconomic Deprivation -- Illustration - Part 1 -- Quantifying the Association between Socioeconomic Deprivation and Excess Mortality -- The Mortality Hazard -- Illustration - Part 2 -- Some Principles for Defining a Hazard-Based Regression Model -- Illustration - Part 3 -- Discussion -- References -- Part II: Social Disparities in Cancer Incidence and Survival - Reports -- Chapter 6: Social Disparities in Cancer Incidence Among Adults in Europe -- Background -- Cancers Associated with Low Socioeconomic Status.
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BACKGROUND: The COVID-19 pandemic has disrupted the provision and use of healthcare services throughout the world. In Slovenia, an epidemic was officially declared between mid-March and mid-May 2020. Although all non-essential health care services were put on hold by government decree, oncological services were listed as an exception. Nevertheless, as cancer control depends also on other health services and additionally major changes in people's behaviour likely occurred, we aimed to analyse whether cancer diagnosis and management were affected during the COVID-19 epidemic in Slovenia. METHODS: We analysed routine data for the period November 2019 through May 2020 from three sources: (1) from the Slovenian Cancer Registry we analysed data on pathohistological and clinical practice cancer notifications from two major cancer centres in Ljubljana and Maribor; (2) from the e-referral system we analysed data on all referrals in Slovenia issued for oncological services, stratified by type of referral; and (3) from the administrative data of the Institute of Oncology Ljubljana we analysed data on outpatient visits by type as well as on diagnostic imaging performed. RESULTS: Compared to the November 2019 – February 2020 average, the decrease in April 2020 was about 43% and 29% for pathohistological and clinical cancer notifications; 33%, 46% and 85% for first, control and genetic counselling referrals; 19% (53%), 43% (72%) and 20% (21%) for first (and control) outpatient visits at the radiotherapy, surgery and medical oncology sectors at the Institute of Oncology Ljubljana, and 48%, 76%, and 42% for X-rays, mammograms and ultrasounds performed at the Institute, respectively. The number of CT and MRI scans performed was not affected. CONCLUSIONS: Significant drops in first referrals for oncological services, first visits and imaging studies performed at the Institute, as well as cancer notifications in April 2020 point to a possibility of a delayed cancer diagnosis for some patients during the first surge of SARS-CoV-2 ...
Introduction: Ecological deprivation indices belong to essential instruments for monitoring and understanding health inequalities. Our aim was to develop the SI-EDI, a newly derived European Deprivation Index for Slovenia. We intend to provide researchers and policy-makers in our country with a relevant tool for measuring and reducing the socioeconomic inequalities in health, and even at a broader level. Methods: Data from the European survey on Income and Living Conditions and Slovenian national census for the year 2011 were used in the SI-EDI construction. The concept of relative deprivation was used where deprivation refers to unmet need(s), which is caused by lack of all kinds of resources, not only material. The SI-EDI was constructed for 210 Slovenian municipalities. Its geographical distribution was compared to the distribution of two existing deprivation scores previously applied in health inequality research in Slovenia. Results: There were 36% of adults recognized as deprived in Slovenia in 2011. SI-EDI was calculated using 10 census variables that were associated with individual deprivation. A clear east-to-west gradient was detected with the most deprived municipalities in the eastern part of the country. The two existing deprivation scores correlate significantly with the SI-EDI. Conclusions: A new deprivation index, the SI-EDI, is grounded on the internationally established scientific concept, can be replicated over time and, crucially, provides an account of the socioeconomic and cultural particularities of the Slovenian population. The SI-EDI could be used by the stakeholders and the governmental and nongovernmental sectors in Slovenia, with the goal of better understanding health inequalities in Slovenia.
International audience ; Introduction: Ecological deprivation indices belong to essential instruments for monitoring and understanding health inequalities. Our aim was to develop the SI-EDI, a newly derived European Deprivation Index for Slovenia. We intend to provide researchers and policy-makers in our country with a relevant tool for measuring and reducing the socioeconomic inequalities in health, and even at a broader level. Methods: Data from the European survey on Income and Living Conditions and Slovenian national census for the year 2011 were used in the SI-EDI construction. The concept of relative deprivation was used where deprivation refers to unmet need(s), which is caused by lack of all kinds of resources, not only material. The SI-EDI was constructed for 210 Slovenian municipalities. Its geographical distribution was compared to the distribution of two existing deprivation scores previously applied in health inequality research in Slovenia. Results: There were 36% of adults recognized as deprived in Slovenia in 2011. SI-EDI was calculated using 10 census variables that were associated with individual deprivation. A clear east-to-west gradient was detected with the most deprived municipalities in the eastern part of the country. The two existing deprivation scores correlate significantly with the SI-EDI. Conclusions: A new deprivation index, the SI-EDI, is grounded on the internationally established scientific concept, can be replicated over time and, crucially, provides an account of the socioeconomic and cultural particularities of the Slovenian population. The SI-EDI could be used by the stakeholders and the governmental and nongovernmental sectors in Slovenia, with the goal of better understanding health inequalities in Slovenia. ; Uvod: Kazalniki, ki na ravni izbranih geografskih enot prikazujejo socialno-ekonomsko blagostanje oziroma primanjkljaj prebivalstva, so danes temeljno orodje za preučevanje in razumevanje neenakosti v zdravju. V prispevku predstavljamo SI-EDI, novo razvit kazalnik ...
International audience ; Introduction: Ecological deprivation indices belong to essential instruments for monitoring and understanding health inequalities. Our aim was to develop the SI-EDI, a newly derived European Deprivation Index for Slovenia. We intend to provide researchers and policy-makers in our country with a relevant tool for measuring and reducing the socioeconomic inequalities in health, and even at a broader level. Methods: Data from the European survey on Income and Living Conditions and Slovenian national census for the year 2011 were used in the SI-EDI construction. The concept of relative deprivation was used where deprivation refers to unmet need(s), which is caused by lack of all kinds of resources, not only material. The SI-EDI was constructed for 210 Slovenian municipalities. Its geographical distribution was compared to the distribution of two existing deprivation scores previously applied in health inequality research in Slovenia. Results: There were 36% of adults recognized as deprived in Slovenia in 2011. SI-EDI was calculated using 10 census variables that were associated with individual deprivation. A clear east-to-west gradient was detected with the most deprived municipalities in the eastern part of the country. The two existing deprivation scores correlate significantly with the SI-EDI. Conclusions: A new deprivation index, the SI-EDI, is grounded on the internationally established scientific concept, can be replicated over time and, crucially, provides an account of the socioeconomic and cultural particularities of the Slovenian population. The SI-EDI could be used by the stakeholders and the governmental and nongovernmental sectors in Slovenia, with the goal of better understanding health inequalities in Slovenia. ; Uvod: Kazalniki, ki na ravni izbranih geografskih enot prikazujejo socialno-ekonomsko blagostanje oziroma primanjkljaj prebivalstva, so danes temeljno orodje za preučevanje in razumevanje neenakosti v zdravju. V prispevku predstavljamo SI-EDI, novo razvit kazalnik primanjkljaja na ravni slovenskih občin. SI-EDI je slovenska različica evropskega kazalnika primanjkljaja (European Deprivation Index – EDI), ki ga v javnozdravstvenih raziskavah že uspešno uporabljajo v Franciji, Španiji, Italiji, Angliji in na Portugalskem. Namen raziskave je tudi preveriti veljavnost SI-EDI in ga tako kot ustrezno orodje ponuditi raziskovalcem in odločevalcem. Metode: Za izdelavo SI-EDI smo uporabili podatke za leto 2011 iz dveh virov: (1) podatke slovenske različice Ankete o življenjskih pogojih, ki jo na zahtevo Eurostata na reprezentativnem vzorcu posameznikov letno izvaja nacionalni statistični urad, in (2) podatke iz popisa prebivalstva. Izračun temelji na konceptu relativnega primanjkljaja, ki ga je prvi opisal Townsend, danes pa se v nekoliko prilagojeni obliki uporablja tudi v izračunu kazalnikov primanjkljaja na ravni Evropske unije. V konceptu relativnega primanjkljaja so pomanjkanju podvrženi posamezniki, ki jim ni omogočeno zadovoljevanje različnih vrst potreb, ne samo materialnih. SI-EDI za 210 slovenskih občin smo izračunali po enaki metodi, kot se uporablja za EDI. Njegovo veljavnost smo preizkušali s primerjavo z dvema obstoječima kazalnikoma, ki sta se v slovenskem prostoru v zadnjem obdobju uporabljala v raziskavah in prikazih socialno-ekonomske neenakosti v zdravju po občinah: koeficientom razvitosti občin, ki ga uporablja NIJZ, ter kazalnikom primanjkljaja, ki ga je v dosedanjih analizah bremena raka uporabljala naša raziskovalna skupina. Rezultati: Med štirimi temeljnimi življenjskimi potrebami (dostopnost počitnic, zmožnost ogrevati bivališče, osebnega računalnika in avtomobila), ki so se v raziskavi izkazale za povezane z objektivno ali subjektivno revščino, vsaj ene izmed njih ni zadovoljilo 36 % odraslih. Ti so bili opredeljeni kot prikrajšani na individualni ravni. Njihove lastnosti so bile prenesene na populacijsko raven v agregirani obliki, tako da smo za izračun SI-EDI uporabili 10 ustreznih popisnih spremenljivk. Na zemljevidu SI-EDI po občinah je jasno viden trend večanja socialno-ekonomskega primanjkljaja od zahoda proti vzhodu države. Največje vrednosti SI-EDI imajo področja na skrajnem severovzhodu in jugovzhodu države. Povezava SI-EDI z dvema obstoječima kazalnikoma primanjkljaja je bila statistično značilna. Zaključki: Nov kazalnik primanjkljaja SI-EDI je zasnovan na mednarodno priznanem znanstvenem konceptu, lahko se replicira v času in prostoru, ter kar je najpomembnejše, odraža socialno-ekonomske in kulturne posebnosti populacije. Prepričani smo, da lahko služi kot ustrezno orodje pri razumevanju socialno-ekonomskih razlik v zdravju, zagotovo pa je lahko uporaben tudi drugod, ne samo na javnozdravstvenem področju.
International audience ; Introduction: Ecological deprivation indices belong to essential instruments for monitoring and understanding health inequalities. Our aim was to develop the SI-EDI, a newly derived European Deprivation Index for Slovenia. We intend to provide researchers and policy-makers in our country with a relevant tool for measuring and reducing the socioeconomic inequalities in health, and even at a broader level. Methods: Data from the European survey on Income and Living Conditions and Slovenian national census for the year 2011 were used in the SI-EDI construction. The concept of relative deprivation was used where deprivation refers to unmet need(s), which is caused by lack of all kinds of resources, not only material. The SI-EDI was constructed for 210 Slovenian municipalities. Its geographical distribution was compared to the distribution of two existing deprivation scores previously applied in health inequality research in Slovenia. Results: There were 36% of adults recognized as deprived in Slovenia in 2011. SI-EDI was calculated using 10 census variables that were associated with individual deprivation. A clear east-to-west gradient was detected with the most deprived municipalities in the eastern part of the country. The two existing deprivation scores correlate significantly with the SI-EDI. Conclusions: A new deprivation index, the SI-EDI, is grounded on the internationally established scientific concept, can be replicated over time and, crucially, provides an account of the socioeconomic and cultural particularities of the Slovenian population. The SI-EDI could be used by the stakeholders and the governmental and nongovernmental sectors in Slovenia, with the goal of better understanding health inequalities in Slovenia. ; Uvod: Kazalniki, ki na ravni izbranih geografskih enot prikazujejo socialno-ekonomsko blagostanje oziroma primanjkljaj prebivalstva, so danes temeljno orodje za preučevanje in razumevanje neenakosti v zdravju. V prispevku predstavljamo SI-EDI, novo razvit kazalnik ...
PURPOSE: With better access to early diagnosis and appropriate treatment, cervical cancer (CC) burden decreased in several European countries. In Eastern European (EE) countries, which accessed European Union in 2004, CC survival was worse than in the rest of Europe. The present study investigates CC survival differences across five European regions, considering stage at diagnosis (local, regional and metastatic), morphology (mainly squamous versus glandular tumours) and patients' age. METHODS: We analysed 101,714 CC women diagnosed in 2000-2007 and followed-up to December 2008. Age-standardised 5-year relative survival (RS) and the excess risks of cancer death in the 5 years after diagnosis were computed. RESULTS: EE women were older and less commonly diagnosed with glandular tumours. Proportions of local stage cancers were similar across Europe, while morphology- and stage-specific RS (especially for non-metastatic disease) were lower in Eastern Europe. Adjusting for age and morphology, excess risk of local stage CC death for EE patients remained higher than that for other European women. CONCLUSION: Stage, age and morphology alone do not explain worse survival in Eastern Europe: less effective care may play a role, probably partly due to fewer or inadequate resources being allocated to health care in this area, compared to the rest of Europe.
Importance Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). Conclusions and Relevance The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer
Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations. ; Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi's work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge's work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia's research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities. ; Peer reviewed
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. ; Background 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. ; Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163). ; Peer reviewed
