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1. Does educational mobility in mid-life affect mortality? A cohort study covering 1.3 million individuals in Sweden

Author: M. Balaj, H. Sjöqvist, L. van der Velde, PA. Allebeck, AN. Shaaban, S. Swartling Peterson, TA. Eikemo, and EE. Agardh
Subjects: Public aspects of medicine, RA1-1270, Social sciences (General), H1-99
Published: 2024
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2. Disease Burden Attributed to Drug use in the Nordic Countries: a Systematic Analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2019

Author: Agardh, Emilie E., Allebeck, Peter, Knudsen, Ann Kristin Skrindo, Aronsson, Amanda E., Flodin, Pär, Eikemo, Terje A., Bangah, Paul R., Skogen, Jens Christoffer, Gissler, Mika, Rönkä, Sanna, McGrath, John J., Sigurvinsdóttir, Rannveig, Dadras, Omid, Deuba, Keshab, Hedna, Khedidja, Mentis, Alexios-Fotios A., Sagoe, Dominic, Shiri, Rahman, Weye, Nanna, Hay, Simon I., Murray, Christopher J. L., Naghavi, Mohsen, Pasovic, Maja, Vos, Theo, Wennberg, Peter, and Danielsson, Anna-Karin
Published: 2023
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3. Educational level and the risk of mental disorders, substance use disorders and self‐harm in different age‐groups: A cohort study covering 1,6 million subjects in the Stockholm region

Author: Baojing Li, Peter Allebeck, Bo Burstöm, Anna‐Karin Danielsson, Louisa Degenhardt, Terje A. Eikemo, Alize Ferrari, Ann Kristin Knudsen, Andreas Lundin, Hélio Manhica, John Newton, Harvey Whiteford, Pär Flodin, Hugo Sjöqvist, and Emilie E. Agardh
Subjects: educational level, mental disorders, self‐harm, substance use disorders, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Objective To investigate the associations between low education and risk of mental disorders, substance use disorders and self‐harm in different age‐groups. Methods All subjects in Stockholm born between 1931 and 1990 were linked to their own or their parent's highest education in 2000 and followed‐up for these disorders in health care registers 2001–2016. Subjects were stratified into four age‐groups: 10–18, 19–27, 28–50, and 51–70 years. Hazard Ratios with 95% Confidence Intervals (CIs) were estimated with Cox proportional hazard models. Results Low education increased the risk of substance use disorders and self‐harm in all age‐groups. Males aged 10–18 with low education had increased risks of ADHD and conduct disorders, and females a decreased risk of anorexia, bulimia and autism. Those aged 19–27 years had increased risks of anxiety and depression, and those aged 28–50 had increased risks of all mental disorders except anorexia and bulimia in males with Hazard Ratios ranging from 1.2 (95% CIs 1.0–1.3) for bipolar disorder to 5.4 (95% CIs 5.1–5.7) for drug use disorder. Females aged 51–70 years had increased risks of schizophrenia and autism. Conclusion Low education is associated with risk of most mental disorders, substance use disorders and self‐harm in all age‐groups, but especially among those aged 28–50 years.
Published: 2023
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4. Income-based differences in healthcare utilization in relation to mortality in the Swedish population between 2004-2017: A nationwide register study.

Author: Pär Flodin, Peter Allebeck, Ester Gubi, Bo Burström, and Emilie E Agardh
Subjects: Medicine
Abstract: BackgroundDespite universal healthcare, socioeconomic differences in healthcare utilization (HCU) persist in modern welfare states. However, little is known of how HCU inequalities has developed over time. The aim of this study is to assess time trends of differences in utilization of primary and specialized care for the lowest (Q1) and highest (Q5) income quantiles and compare these to mortality.Methods and findingsUsing a repeated cross-sectional register-based study design, data on utilization of (i) primary; (ii) specialized outpatient; and (iii) inpatient care, as well as (iv) cause of death, were linked to family income and sociodemographic control variables (for instance, country of origin and marital status). The study sample comprised all individuals 16 years or older residing in Sweden any year during the study period and ranged from 7.1 million in year 2004 to 8.0 million year 2017. HCU and mortality for all disease as well as for the 5 disease groups causing most deaths were compared for the Q1 and Q5 using logistic regression, adjusting for sex, age, marital status, and birth country. The primary outcome measures were adjusted odds ratios (ORs), and regression coefficients of annual changes in these ORs log-transformed. Additionally, we conducted negative binominal regression to calculate adjusted rate ratios (RRs) comparing Q1 and Q5 with regard to number of disease specific healthcare encounters ≤5 years prior to death. In 2017, for all diseases combined, Q1 utilized marginally more primary and specialized outpatient care than Q5 (OR 1.07, 95% CI [1.07, 1.08]; p < 0.001, and OR 1.04, 95% CI [1.04, 1.05]; p < 0.001, respectively), and considerably more inpatient care (OR 1.44, 95% CI [1.43, 1.45]; p < 0.001). The largest relative inequality was observed for mortality (OR 1.78, 95% CI [1.74, 1.82]; p < 0.001). This pattern was broadly reproduced for each of the 5 disease groups. Time trends in HCU inequality varied by level of care. Each year, Q1 (versus Q5) used more inpatient care and suffered increasing mortality rates. However, utilization of primary and specialized outpatient care increased more among Q5 than in Q1. Finally, group differences in number of healthcare encounters ≤5 years prior to death demonstrated a similar pattern. For each disease group, primary and outpatient care encounters were fewer in Q1 than in Q5, while inpatient encounters were similar or higher in Q1. A main limitation of this study is the absence of data on self-reported need for care, which impedes quantifications of HCU inequalities each year.ConclusionsIncome-related differences in the utilization of primary and specialized outpatient care were considerably smaller than for mortality, and this discrepancy widened with time. Facilitating motivated use of primary and outpatient care among low-income groups could help mitigate the growing health inequalities.
Published: 2023
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5. Five insights from the Global Burden of Disease Study 2019

Author: Collaborators, GBD 2019 Viewpoint, Murray, Christopher JL, Abbafati, Cristiana, Abbas, Kaja M, Abbasi, Mohammad, Abbasi-Kangevari, Mohsen, Abd-Allah, Foad, Abdollahi, Mohammad, Abedi, Parisa, Abedi, Aidin, Abolhassani, Hassan, Aboyans, Victor, Abreu, Lucas Guimarães, Abrigo, Michael RM, Abu-Gharbieh, Eman, Abu Haimed, Abdulaziz Khalid, Abushouk, Abdelrahman I, Acebedo, Alyssa, Ackerman, Ilana N, Adabi, Maryam, Adamu, Abdu A, Adebayo, Oladimeji M, Adelson, Jaimie D, Adetokunboh, Olatunji O, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agrawal, Anurag, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Aji, Budi, Akinyemiju, Tomi, Akombi, Blessing, Alahdab, Fares, Alam, Khurshid, Alanezi, Fahad Mashhour, Alanzi, Turki M, Albertson, Samuel B, Alemu, Biresaw Wassihun, Alemu, Yihun Mulugeta, Alhabib, Khalid F, Ali, Muhammad, Ali, Saqib, Alicandro, Gianfranco, Alipour, Vahid, Alizade, Hesam, Aljunid, Syed Mohamed, Alla, François, Allebeck, Peter, Almadi, Majid Abdulrahman Hamad, Almasi-Hashiani, Amir, Al-Mekhlafi, Hesham M, Almulhim, Abdulaziz M, Alonso, Jordi, Al-Raddadi, Rajaa M, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Bekalu, Amare, Azmeraw T, Amini, Saeed, Amit, Arianna Maever L, Amugsi, Dickson A, Anbesu, Etsay Woldu, Ancuceanu, Robert, Anderlini, Deanna, Anderson, Jason A, Andrei, Tudorel, Andrei, Catalina Liliana, Anjomshoa, Mina, Ansari, Fereshteh, Ansari-Moghaddam, Alireza, Antonio, Carl Abelardo T, Antony, Catherine M, Anvari, Davood, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Arab-Zozani, Morteza, Aravkin, Aleksandr Y, Arba, Aseb Arba Kinfe, Aripov, Timur, Ärnlöv, Johan, Arowosegbe, Oluwaseyi Olalekan, Asaad, Malke, Asadi-Aliabadi, Mehran, Asadi-Pooya, Ali A, Ashbaugh, Charlie, Assmus, Michael, Atout, Maha Moh'd Wahbi, Ausloos, Marcel, Ausloos, Floriane, Quintanilla, Beatriz Paulina Ayala, Ayano, Getinet, Ayanore, Martin Amogre, Azari, Samad, Azene, Zelalem Nigussie, Darshan, BB, Babaee, Ebrahim, and Badawi, Alaa
Subjects: Prevention, 2.4 Surveillance and distribution, Aetiology, Good Health and Well Being, Birth Rate, Delivery of Health Care, Female, Global Burden of Disease, Global Health, Humans, Male, Noncommunicable Diseases, Outcome Assessment, Health Care, Risk Factors, Socioeconomic Factors, Wounds and Injuries, GBD 2019 Viewpoint Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.
Published: 2020

6. Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: Murray, Christopher JL, Callender, Charlton SKH, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, and Atique, Suleman
Subjects: Health Sciences, Behavioral and Social Science, Contraception/Reproduction, Basic Behavioral and Social Science, Aging, Aetiology, 2.4 Surveillance and distribution, Reproductive health and childbirth, Good Health and Well Being, Adolescent, Adult, Aged, Birth Rate, Child, Child, Preschool, Female, Global Burden of Disease, Global Health, Humans, Infant, Infant, Newborn, Male, Maternal Age, Middle Aged, Mortality, Population Density, Population Growth, Young Adult, GBD 2017 Population and Fertility Collaborators, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundPopulation estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods.MethodsWe estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories.FindingsFrom 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4-52·0). The TFR decreased from 4·7 livebirths (4·5-4·9) to 2·4 livebirths (2·2-2·5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3-200·8) since 1950, from 2·6 billion (2·5-2·6) to 7·6 billion (7·4-7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9-1·2) in Cyprus to a high of 7·1 livebirths (6·8-7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07-0·09) in South Korea to 2·4 livebirths (2·2-2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3-0·4) in Puerto Rico to a high of 3·1 livebirths (3·0-3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger.InterpretationPopulation trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress.FundingBill & Melinda Gates Foundation.
Published: 2018

7. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: Collaborators, GBD 2017 Causes of Death, Roth, Gregory A, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adib, Mina G, Admasie, Amha, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemi, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Aremu, Olatunde, Ärnlöv, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Ausloos, Marcel, Avokpaho, Euripide FGA, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, and Badawi, Alaa
Subjects: Brain Disorders, Pediatric, Prevention, Aetiology, 2.4 Surveillance and distribution, Infection, Good Health and Well Being, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Cause of Death, Child, Child, Preschool, Female, Global Burden of Disease, Global Health, Humans, Infant, Infant, Newborn, Life Expectancy, Male, Middle Aged, Sex Distribution, Socioeconomic Factors, Young Adult, GBD 2017 Causes of Death Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundGlobal development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017.MethodsThe causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised.FindingsAt the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5-74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 18·6% (17·9-19·6), and injuries 8·0% (7·7-8·2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22·7% (21·5-23·9), representing an additional 7·61 million (7·20-8·01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7·9% (7·0-8·8). The number of deaths for CMNN causes decreased by 22·2% (20·0-24·0) and the death rate by 31·8% (30·1-33·3). Total deaths from injuries increased by 2·3% (0·5-4·0) between 2007 and 2017, and the death rate from injuries decreased by 13·7% (12·2-15·1) to 57·9 deaths (55·9-59·2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118·0% (88·8-148·6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36·4% (32·2-40·6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33·6% (31·2-36·1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respiratory infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990-neonatal disorders, lower respiratory infections, and diarrhoeal diseases-were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases.InterpretationImprovements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade.FundingBill & Melinda Gates Foundation.
Published: 2018

8. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: James, Spencer L, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N, Adamu, Abdu A, Adebayo, Oladimeji M, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adib, Mina G, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alouani, Mohamed ML, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arabloo, Jalal, Arauz, Antonio, Aremu, Olatunde, Ariani, Filippo, Armoon, Bahroom, Ärnlöv, Johan, Arora, Amit, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asghar, Rana Jawad, Ataro, Zerihun, Atre, Sachin R, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide FGA, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, and Bali, Ayele Geleto
Subjects: Prevention, 2.4 Surveillance and distribution, Aetiology, Good Health and Well Being, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Child, Child, Preschool, Disabled Persons, Female, Global Burden of Disease, Global Health, Humans, Incidence, Infant, Infant, Newborn, Life Expectancy, Male, Middle Aged, Morbidity, Prevalence, Sex Distribution, Socioeconomic Factors, Wounds and Injuries, Young Adult, GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data.MethodsWe estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting.FindingsGlobally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs s1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]).InterpretationGlobal all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury.FundingBill & Melinda Gates Foundation.
Published: 2018

9. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author: Collaborators, GBD 2017 SDG, Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, and Anwari, Palwasha
Subjects: Prevention, Pediatric, Good Health and Well Being, Peace, Justice and Strong Institutions, Female, Global Burden of Disease, Global Health, Goals, Health Status, Health Status Indicators, Humans, Male, Mortality, Risk Factors, Sex Offenses, Sustainable Development, United Nations, GBD 2017 SDG Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundEfforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment.MethodsWe measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator.FindingsThe global median health-related SDG index in 2017 was 59·4 (IQR 35·4-67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6-14·0) to a high of 84·9 (83·1-86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030.InterpretationThe GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains-curative interventions in the case of NCDs-towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions-or inaction-today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.FundingBill & Melinda Gates Foundation.
Published: 2018

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

Author: Collaborators, GBD 2017 Mortality, Dicker, Daniel, Nguyen, Grant, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abdurahman, Ahmed Abdulahi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Agrawal, Anurag, Ahmadi, Mehdi, Ahmadi, Alireza, Ahmadieh, Hamid, Ahmed, Mohamed Lemine Cheikh brahim, Ahmed, Sayem, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Anlay, Degefaye Zelalem, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Megha, and Artaman, Al
Subjects: Behavioral and Social Science, Pediatric, Prevention, Basic Behavioral and Social Science, 2.4 Surveillance and distribution, Aetiology, Good Health and Well Being, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Global Burden of Disease, Global Health, Humans, Infant, Infant, Newborn, Life Expectancy, Male, Middle Aged, Mortality, Sex Distribution, Socioeconomic Factors, Young Adult, GBD 2017 Mortality Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundAssessments 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.MethodsThe 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.FindingsGlobally, 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.InterpretationThis 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.FundingBill & Melinda Gates Foundation.
Published: 2018

11. 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

Author: Kyu, Hmwe Hmwe, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abil, Olifan Zewdie, Aboyans, Victor, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N, Adamu, Abdu A, Adebayo, Oladimeji M, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Anurag, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alonso, Jordi, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Aminde, Leopold N, Amini, Erfan, Amiresmaili, Mohammadreza, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Arora, Amit, Arora, Megha, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide FGA, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, and Balakrishnan, Kalpana
Subjects: Prevention, Aging, Good Health and Well Being, Aged, Communicable Diseases, Disabled Persons, Female, Global Burden of Disease, Health Status, Healthy Lifestyle, Humans, Life Expectancy, Male, Mortality, Mortality, Premature, Prevalence, Quality-Adjusted Life Years, Risk Factors, Socioeconomic Factors, Wounds and Injuries, GBD 2017 DALYs and HALE Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundHow long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years.MethodsWe used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males.FindingsGlobally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2).InterpretationWith increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health.FundingBill & Melinda Gates Foundation.
Published: 2018

12. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Griswold, Max G, Fullman, Nancy, Hawley, Caitlin, Arian, Nicholas, Zimsen, Stephanie RM, Tymeson, Hayley D, Venkateswaran, Vidhya, Tapp, Austin Douglas, Forouzanfar, Mohammad H, Salama, Joseph S, Abate, Kalkidan Hassen, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Aboyans, Victor, Abrar, Mohammed Mehdi, Acharya, Pawan, Adetokunboh, Olatunji O, Adhikari, Tara Ballav, Adsuar, Jose C, Afarideh, Mohsen, Agardh, Emilie Elisabet, Agarwal, Gina, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmed, Muktar Beshir, Akibu, Mohammed, Akinyemiju, Tomi, Akseer, Nadia, Asfoor, Deena H Al, Al-Aly, Ziyad, Alahdab, Fares, Alam, Khurshid, Albujeer, Ammar, Alene, Kefyalew Addis, Ali, Raghib, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Allebeck, Peter, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Ammar, Walid, Amoako, Yaw Ampem, Amul, Gianna Gayle Herrera, Andrei, Catalina Liliana, Angus, Colin, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Assadi, Reza, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F, Awasthi, Ashish, Ayele, Henok Tadesse, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Badali, Hamid, Badawi, Alaa, Banach, Maciej, Barker-Collo, Suzanne Lyn, Barrero, Lope H, Basaleem, Huda, Baye, Estifanos, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Béjot, Yannick, Belachew, Abate Bekele, Belay, Saba Abraham, Bennett, Derrick A, Bensenor, Isabela M, Bernabe, Eduardo, Bernstein, Robert S, Beyene, Addisu Shunu, Beyranvand, Tina, Bhaumik, Soumyadeeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bililign, Nigus, Birlik, Sait Mentes, Birungi, Charles, Bizuneh, Hailemichael, Bjerregaard, Peter, Bjørge, Tone, Borges, Guilherme, Bosetti, Cristina, Boufous, Soufiane, Bragazzi, Nicola Luigi, Brenner, Hermann, and Butt, Zahid A
Subjects: Epidemiology, Public Health, Health Sciences, Women's Health, Alcoholism, Alcohol Use and Health, Substance Misuse, Prevention, Behavioral and Social Science, Aging, 2.4 Surveillance and distribution, Stroke, Cancer, Oral and gastrointestinal, Good Health and Well Being, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Alcohol Drinking, Cause of Death, Commerce, Female, Global Burden of Disease, Global Health, Humans, Male, Middle Aged, Observational Studies as Topic, Population Surveillance, Prevalence, Prospective Studies, Quality-Adjusted Life Years, Retrospective Studies, Risk Assessment, Risk Factors, Sex Distribution, Young Adult, GBD 2016 Alcohol Collaborators, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundAlcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older.MethodsUsing 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health.FindingsGlobally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2·2% (95% uncertainty interval [UI] 1·5-3·0) of age-standardised female deaths and 6·8% (5·8-8·0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3·8% (95% UI 3·2-4·3) of female deaths and 12·2% (10·8-13·6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2·3% (95% UI 2·0-2·6) and male attributable DALYs were 8·9% (7·8-9·9). The three leading causes of attributable deaths in this age group were tuberculosis (1·4% [95% UI 1·0-1·7] of total deaths), road injuries (1·2% [0·7-1·9]), and self-harm (1·1% [0·6-1·5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27·1% (95% UI 21·2-33·3) of total alcohol-attributable female deaths and 18·9% (15·3-22·6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0·0-0·8) standard drinks per week.InterpretationAlcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.FundingBill & Melinda Gates Foundation.
Published: 2018

13. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 Healthcare Access and Quality, Fullman, Nancy, Yearwood, Jamal, Abay, Solomon M, Abbafati, Cristiana, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy MX, Abu-Raddad, Laith J, Adane, Akilew Awoke, Adedoyin, Rufus Adesoji, Adetokunboh, Olatunji, Adhikari, Tara Ballav, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Kiadaliri, Aliasghar Ahmad, Aichour, Miloud Taki Eddine, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi F, Akseer, Nadia, Lami, Faris Hasan Al, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Alasfoor, Deena, Albittar, Mohammed I, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed M, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Alomari, Mahmoud A, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andrei, Catalina Liliana, Androudi, Sofia, Antonio, Carl Abelardo T, Araújo, Valdelaine EM, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Ashebir, Mengistu Mitiku, Asseffa, Netsanet Abera, Atey, Tesfay Mehari, Atre, Sachin R, Atteraya, Madhu S, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayalew, Animut Alebel, Ayele, Henok Tadesse, Ayer, Rakesh, Ayuk, Tambe Betrand, Azzopardi, Peter, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Badali, Hamid, Badawi, Alaa, Banach, Maciej, Banerjee, Amitava, Banstola, Amrit, Barber, Ryan M, Barboza, Miguel A, Barker-Collo, Suzanne L, Bärnighausen, Till, Barquera, Simon, Barrero, Lope H, Bassat, Quique, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, and Bedi, Neeraj
Subjects: Health Services and Systems, Public Health, Health Sciences, Clinical Research, Biodefense, Prevention, Vaccine Related, Good Health and Well Being, Communicable Diseases, Global Burden of Disease, Health Services Accessibility, Humans, Noncommunicable Diseases, Quality of Health Care, Wounds and Injuries, GBD 2016 Healthcare Access and Quality Collaborators, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundA 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.MethodsDrawing 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.FindingsIn 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 (89·1-93·6) 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.InterpretationGBD 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 hinges 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.FundingBill & Melinda Gates Foundation.
Published: 2018

14. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 Risk Factors, Gakidou, Emmanuela, Afshin, Ashkan, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulle, Abdishakur M, Abera, Semaw Ferede, Aboyans, Victor, Abu-Raddad, Laith J, Abu-Rmeileh, Niveen ME, Abyu, Gebre Yitayih, Adedeji, Isaac Akinkunmi, Adetokunboh, Olatunji, Afarideh, Mohsen, Agrawal, Anurag, Agrawal, Sutapa, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Miloud Taki Eddine, Aichour, Amani Nidhal, Aichour, Ibtihel, Akinyemi, Rufus Olusola, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alasfoor, Deena, Alene, Kefyalew Addis, Ali, Komal, Alizadeh-Navaei, Reza, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Ansari, Hossein, Antó, Josep M, Antonio, Carl Abelardo T, Anwari, Palwasha, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon Weldegebreal, Atey, Tesfay Mehari, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Azzopardi, Peter, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Ballew, Shoshana H, Barac, Aleksandra, Barber, Ryan M, Barker-Collo, Suzanne L, Bärnighausen, Till, Barquera, Simon, Barregard, Lars, Barrero, Lope H, Batis, Carolina, Battle, Katherine E, Baumgarner, Blair R, Baune, Bernhard T, Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Bell, Michelle L, Bennett, Derrick A, Bennett, James R, Bensenor, Isabela M, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Beyene, Addisu Shunu, Bhansali, Anil, Bhutta, Zulfiqar A, Bicer, Burcu Kucuk, Bikbov, Boris, Birungi, Charles, Biryukov, Stan, Blosser, Christopher D, Boneya, Dube Jara, Bou-Orm, Ibrahim R, Brauer, Michael, and Breitborde, Nicholas JK
Subjects: Epidemiology, Health Sciences, Prevention, Aetiology, 2.2 Factors relating to the physical environment, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, Air Pollution, Body Mass Index, Cause of Death, Child, Child, Preschool, Communicable Diseases, Disabled Persons, Environmental Health, Female, Global Burden of Disease, Humans, Infant, Infant, Newborn, Life Expectancy, Male, Metabolic Diseases, Middle Aged, Noncommunicable Diseases, Occupational Diseases, Quality-Adjusted Life Years, Risk Assessment, Sex Distribution, Smoking, Water Supply, Young Adult, GBD 2016 Risk Factors Collaborators, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context.MethodsWe used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined.FindingsSince 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124·1 million DALYs [95% UI 111·2 million to 137·0 million]), high systolic blood pressure (122·2 million DALYs [110·3 million to 133·3 million], and low birthweight and short gestation (83·0 million DALYs [78·3 million to 87·7 million]), and for women, were high systolic blood pressure (89·9 million DALYs [80·9 million to 98·2 million]), high body-mass index (64·8 million DALYs [44·4 million to 87·6 million]), and high fasting plasma glucose (63·8 million DALYs [53·2 million to 76·3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9·3% (6·9-11·6) decline in deaths and a 10·8% (8·3-13·1) decrease in DALYs at the global level, while population ageing accounts for 14·9% (12·7-17·5) of deaths and 6·2% (3·9-8·7) of DALYs, and population growth for 12·4% (10·1-14·9) of deaths and 12·4% (10·1-14·9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27·3% (24·9-29·7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks.InterpretationIncreasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade.FundingThe Bill & Melinda Gates Foundation, Bloomberg Philanthropies.
Published: 2017

15. Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 DALYs and HALE, Hay, Simon I, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulkader, Rizwan Suliankatchi, Abdulle, Abdishakur M, Abebo, Teshome Abuka, Abera, Semaw Ferede, Aboyans, Victor, Abu-Raddad, Laith J, Ackerman, Ilana N, Adedeji, Isaac A, Adetokunboh, Olatunji, Afshin, Ashkan, Aggarwal, Rakesh, Agrawal, Sutapa, Agrawal, Anurag, Ahmed, Muktar Beshir, Aichour, Miloud Taki Eddine, Aichour, Amani Nidhal, Aichour, Ibtihel, Aiyar, Sneha, Akinyemiju, Tomi F, Akseer, Nadia, Al Lami, Faris Hasan, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alasfoor, Deena, Alene, Kefyalew Addis, Ali, Raghib, Alizadeh-Navaei, Reza, Alkaabi, Juma M, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Al-Maskari, Fatma, AlMazroa, Mohammad AbdulAziz, Al-Raddadi, Rajaa, Alsharif, Ubai, Alsowaidi, Shirina, Althouse, Benjamin M, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asgedom, Solomon W, Atey, Tesfay Mehari, Atnafu, Niguse Tadele, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Awasthi, Shally, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter, Babalola, Tesleem Kayode, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Bannick, Marlena S, Barac, Aleksandra, Barker-Collo, Suzanne L, Bärnighausen, Till, Barquera, Simon, Barrero, Lope H, Basu, Sanjay, Battista, Robert, Battle, Katherine E, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Beardsley, Justin, Bedi, Neeraj, Béjot, Yannick, Bekele, Bayu Begashaw, Bell, Michelle L, Bennett, Derrick A, Bennett, James R, Bensenor, Isabela M, Benson, Jennifer, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, and Beyene, Addisu Shunu
Subjects: Epidemiology, Public Health, Health Sciences, Clinical Research, Behavioral and Social Science, Prevention, Social Determinants of Health, Burden of Illness, 2.4 Surveillance and distribution, Good Health and Well Being, Adult, Age Distribution, Aged, Aged, 80 and over, Cause of Death, Communicable Diseases, Disabled Persons, Female, Global Burden of Disease, Global Health, Humans, Life Expectancy, Male, Middle Aged, Noncommunicable Diseases, Quality-Adjusted Life Years, Residence Characteristics, Sex Distribution, Wounds and Injuries, GBD 2016 DALYs and HALE Collaborators, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundMeasurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI).MethodsWe used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate.FindingsThe highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally.InterpretationAt a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support.FundingBill & Melinda Gates Foundation.
Published: 2017

16. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 Causes of Death, Naghavi, Mohsen, Abajobir, Amanuel Alemu, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abera, Semaw Ferede, Aboyans, Victor, Adetokunboh, Olatunji, Afshin, Ashkan, Agrawal, Anurag, Ahmadi, Alireza, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Miloud Taki Eddine, Aichour, Ibtihel, Aiyar, Sneha, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Syed Danish, Alizadeh-Navaei, Reza, Alkaabi, Juma M, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andersen, Hjalte H, Andrei, Catalina Liliana, Androudi, Sofia, Ansari, Hossein, Antonio, Carl Abelardo T, Anwari, Palwasha, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon W, Atey, Tesfay Mehari, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G, Awasthi, Ashish, Babalola, Tesleem Kayode, Bacha, Umar, Balakrishnan, Kalpana, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne L, Barquera, Simon, Barregard, Lars, Barrero, Lope H, Baune, Bernhard T, Bedi, Neeraj, Beghi, Ettore, Béjot, Yannick, Bekele, Bayu Begashaw, Bell, Michelle L, Bennett, James R, Bensenor, Isabela M, Berhane, Adugnaw, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Bhatt, Samir, Biadgilign, Sibhatu, Bienhoff, Kelly, Bikbov, Boris, Bisanzio, Donal, Bourne, Rupert RA, Breitborde, Nicholas JK, Bulto, Lemma Negesa Bulto, Bumgarner, Blair R, Butt, Zahid A, Cahuana-Hurtado, Lucero, Cameron, Ewan, Campuzano, Julio Cesar, Car, Josip, Cárdenas, Rosario, Carrero, Juan Jesus, Carter, Austin, Casey, Daniel C, Castañeda-Orjuela, Carlos A, Catalá-López, Ferrán, Charlson, Fiona J, Chibueze, Chioma Ezinne, and Chimed-Ochir, Odgerel
Subjects: Pediatric, Clinical Research, Infant Mortality, Infectious Diseases, 2.4 Surveillance and distribution, Aetiology, Infection, Cardiovascular, Good Health and Well Being, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Cause of Death, Child, Child, Preschool, Communicable Diseases, Disasters, Female, Global Burden of Disease, Global Health, Humans, Infant, Infant, Newborn, Male, Middle Aged, Noncommunicable Diseases, Nutrition Disorders, Pregnancy, Pregnancy Complications, Socioeconomic Factors, Wounds and Injuries, Young Adult, GBD 2016 Causes of Death Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundMonitoring levels and trends in premature mortality is crucial to understanding how societies can address prominent sources of early death. The Global Burden of Disease 2016 Study (GBD 2016) provides a comprehensive assessment of cause-specific mortality for 264 causes in 195 locations from 1980 to 2016. This assessment includes evaluation of the expected epidemiological transition with changes in development and where local patterns deviate from these trends.MethodsWe estimated cause-specific deaths and years of life lost (YLLs) by age, sex, geography, and year. YLLs were calculated from the sum of each death multiplied by the standard life expectancy at each age. We used the GBD cause of death database composed of: vital registration (VR) data corrected for under-registration and garbage coding; national and subnational verbal autopsy (VA) studies corrected for garbage coding; and other sources including surveys and surveillance systems for specific causes such as maternal mortality. To facilitate assessment of quality, we reported on the fraction of deaths assigned to GBD Level 1 or Level 2 causes that cannot be underlying causes of death (major garbage codes) by location and year. Based on completeness, garbage coding, cause list detail, and time periods covered, we provided an overall data quality rating for each location with scores ranging from 0 stars (worst) to 5 stars (best). We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to generate estimates for each location, year, age, and sex. We assessed observed and expected levels and trends of cause-specific deaths in relation to the Socio-demographic Index (SDI), a summary indicator derived from measures of average income per capita, educational attainment, and total fertility, with locations grouped into quintiles by SDI. Relative to GBD 2015, we expanded the GBD cause hierarchy by 18 causes of death for GBD 2016.FindingsThe quality of available data varied by location. Data quality in 25 countries rated in the highest category (5 stars), while 48, 30, 21, and 44 countries were rated at each of the succeeding data quality levels. Vital registration or verbal autopsy data were not available in 27 countries, resulting in the assignment of a zero value for data quality. Deaths from non-communicable diseases (NCDs) represented 72·3% (95% uncertainty interval [UI] 71·2-73·2) of deaths in 2016 with 19·3% (18·5-20·4) of deaths in that year occurring from communicable, maternal, neonatal, and nutritional (CMNN) diseases and a further 8·43% (8·00-8·67) from injuries. Although age-standardised rates of death from NCDs decreased globally between 2006 and 2016, total numbers of these deaths increased; both numbers and age-standardised rates of death from CMNN causes decreased in the decade 2006-16-age-standardised rates of deaths from injuries decreased but total numbers varied little. In 2016, the three leading global causes of death in children under-5 were lower respiratory infections, neonatal preterm birth complications, and neonatal encephalopathy due to birth asphyxia and trauma, combined resulting in 1·80 million deaths (95% UI 1·59 million to 1·89 million). Between 1990 and 2016, a profound shift toward deaths at older ages occurred with a 178% (95% UI 176-181) increase in deaths in ages 90-94 years and a 210% (208-212) increase in deaths older than age 95 years. The ten leading causes by rates of age-standardised YLL significantly decreased from 2006 to 2016 (median annualised rate of change was a decrease of 2·89%); the median annualised rate of change for all other causes was lower (a decrease of 1·59%) during the same interval. Globally, the five leading causes of total YLLs in 2016 were cardiovascular diseases; diarrhoea, lower respiratory infections, and other common infectious diseases; neoplasms; neonatal disorders; and HIV/AIDS and tuberculosis. At a finer level of disaggregation within cause groupings, the ten leading causes of total YLLs in 2016 were ischaemic heart disease, cerebrovascular disease, lower respiratory infections, diarrhoeal diseases, road injuries, malaria, neonatal preterm birth complications, HIV/AIDS, chronic obstructive pulmonary disease, and neonatal encephalopathy due to birth asphyxia and trauma. Ischaemic heart disease was the leading cause of total YLLs in 113 countries for men and 97 countries for women. Comparisons of observed levels of YLLs by countries, relative to the level of YLLs expected on the basis of SDI alone, highlighted distinct regional patterns including the greater than expected level of YLLs from malaria and from HIV/AIDS across sub-Saharan Africa; diabetes mellitus, especially in Oceania; interpersonal violence, notably within Latin America and the Caribbean; and cardiomyopathy and myocarditis, particularly in eastern and central Europe. The level of YLLs from ischaemic heart disease was less than expected in 117 of 195 locations. Other leading causes of YLLs for which YLLs were notably lower than expected included neonatal preterm birth complications in many locations in both south Asia and southeast Asia, and cerebrovascular disease in western Europe.InterpretationThe past 37 years have featured declining rates of communicable, maternal, neonatal, and nutritional diseases across all quintiles of SDI, with faster than expected gains for many locations relative to their SDI. A global shift towards deaths at older ages suggests success in reducing many causes of early death. YLLs have increased globally for causes such as diabetes mellitus or some neoplasms, and in some locations for causes such as drug use disorders, and conflict and terrorism. Increasing levels of YLLs might reflect outcomes from conditions that required high levels of care but for which effective treatments remain elusive, potentially increasing costs to health systems.FundingBill & Melinda Gates Foundation.
Published: 2017

17. Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 SDG, Fullman, Nancy, Barber, Ryan M, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulkader, Rizwan Suliankatchi, Abdulle, Abdishakur M, Abera, Semaw Ferede, Aboyans, Victor, Abu-Raddad, Laith J, Abu-Rmeileh, Niveen ME, Adedeji, Isaac Akinkunmi, Adetokunboh, Olatunji, Afshin, Ashkan, Agrawal, Anurag, Agrawal, Sutapa, Kiadaliri, Aliasghar Ahmad, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Miloud Taki Eddine, Aichour, Amani Nidhal, Aichour, Ibtihel, Aiyar, Sneha, Akinyemi, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alasfoor, Deena, Alene, Kefyalew Addis, Alizadeh-Navaei, Reza, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Ansari, Hossein, Antonio, Carl Abelardo T, Anwari, Palwasha, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari, Atre, Sachin R, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Azzopardi, Peter, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Bannick, Marlena S, Barac, Aleksandra, Barker-Collo, Suzanne L, Bärnighausen, Till, Barrero, Lope H, Basu, Sanjay, Battle, Katherine E, Baune, Bernhard T, Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Béjot, Yannick, Bell, Michelle L, Bennett, Derrick A, Bennett, James R, Bensenor, Isabela M, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Beyene, Addisu Shunu, Bhala, Neeraj, Bhansali, Anil, Bhatt, Samir, Bhutta, Zulfiqar A, Bicer, Burcu Kucuk, Bidgoli, Hassan Haghparast, Bikbov, Boris, Bilal, Arebu I, Birungi, Charles, Biryukov, Stan, Bizuayehu, Habtamu Mellie, Blosser, Christopher D, Boneya, Dube Jara, Bose, Dipan, and Bou-Orm, Ibrahim R
Subjects: Infectious Diseases, Pediatric, Prevention, Rare Diseases, Good Health and Well Being, Adolescent, Adult, Child, Child Abuse, Sexual, Child, Preschool, Conservation of Natural Resources, Female, Global Burden of Disease, Global Health, Health Status, Health Status Indicators, Humans, Infant, Infant Mortality, Infant, Newborn, Male, Middle Aged, Noncommunicable Diseases, Quality-Adjusted Life Years, Sex Offenses, Young Adult, GBD 2016 SDG Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundThe UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of "leaving no one behind". Understanding today's gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990-2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030.MethodsWe used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0-100, with 0 as the 2·5th percentile estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment.FindingsGlobally, the median health-related SDG index was 56·7 (IQR 31·9-66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6-88·9), Iceland (86·0, 84·1-87·6), and Sweden (85·6, 81·8-87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6-11·9), the Central African Republic (11·0, 8·8-13·8), and Somalia (11·3, 9·5-13·1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2-8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past.InterpretationGBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations.FundingBill & Melinda Gates Foundation.
Published: 2017

18. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 Disease and Injury Incidence and Prevalence, Vos, Theo, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulkader, Rizwan Suliankatchi, Abdulle, Abdishakur M, Abebo, Teshome Abuka, Abera, Semaw Ferede, Aboyans, Victor, Abu-Raddad, Laith J, Ackerman, Ilana N, Adamu, Abdu Abdullahi, Adetokunboh, Olatunji, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Sanjay Kumar, Aggarwal, Rakesh, Agrawal, Anurag, Agrawal, Sutapa, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Miloud Taki Eddine, Aichour, Amani Nidhal, Aichour, Ibtihel, Aiyar, Sneha, Akinyemi, Rufus Olusola, Akseer, Nadia, Al Lami, Faris Hasan, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alasfoor, Deena, Alene, Kefyalew Addis, Ali, Raghib, Alizadeh-Navaei, Reza, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Al-Maskari, Fatma, Al-Raddadi, Rajaa, Alsharif, Ubai, Alsowaidi, Shirina, Altirkawi, Khalid A, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Andersen, Hjalte H, Antonio, Carl Abelardo T, Anwari, Palwasha, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon W, Assadi, Reza, Atey, Tesfay Mehari, Atnafu, Niguse Tadele, Atre, Sachin R, Avila-Burgos, Leticia, Avokphako, Euripide Frinel G Arthur, Awasthi, Ashish, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Banerjee, Amitava, Bannick, Marlena S, Barac, Aleksandra, Barber, Ryan M, Barker-Collo, Suzanne L, Bärnighausen, Till, Barquera, Simon, Barregard, Lars, Barrero, Lope H, Basu, Sanjay, Battista, Bob, Battle, Katherine E, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Béjot, Yannick, Bekele, Bayu Begashaw, Bell, Michelle L, Bennett, Derrick A, Bensenor, Isabela M, Benson, Jennifer, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, and Beyene, Addisu Shunu
Subjects: Biomedical and Clinical Sciences, Epidemiology, Public Health, Clinical Sciences, Health Sciences, Neurosciences, Women's Health, Behavioral and Social Science, Mental Health, Burden of Illness, Aging, Brain Disorders, 2.4 Surveillance and distribution, Good Health and Well Being, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Cause of Death, Child, Child, Preschool, Communicable Diseases, Disabled Persons, Female, Global Burden of Disease, Global Health, Humans, Incidence, Infant, Infant, Newborn, Male, Middle Aged, Noncommunicable Diseases, Prevalence, Sex Distribution, Wounds and Injuries, Young Adult, GBD 2016 Disease and Injury Incidence and Prevalence Collaborators, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundAs mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.MethodsWe estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).FindingsGlobally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8-75·9 million [7·2%, 6·0-8·3]), 45·1 million (29·0-62·8 million [5·6%, 4·0-7·2]), 36·3 million (25·3-50·9 million [4·5%, 3·8-5·3]), 34·7 million (23·0-49·6 million [4·3%, 3·5-5·2]), and 34·1 million (23·5-46·0 million [4·2%, 3·2-5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3-3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0-11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer's disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862-11943) and highest rate (Yemen, 14 774 YLDs per 100 000, 11 018-19 228).InterpretationThe decrease in death rates since 1990 for most causes has not been matched by a similar decline in age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases steeply with age, health systems will face increasing demand for services that are generally costlier than the interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-to-date information about the trends of disease and how this varies between countries is essential to plan for an adequate health-system response.FundingBill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.
Published: 2017

19. 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

Author: Naghavi, M, Ong, K, Aali, A, Ababneh, H, Abate, Y, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbasi-Kangevari, M, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdelwahab, A, Abdollahi, M, Abdollahifar, M, Abdoun, M, Abdulah, D, Abdullahi, A, Abebe, M, Abebe, S, Abedi, A, Abegaz, K, Abhilash, E, Abidi, H, Abiodun, O, Aboagye, R, Abolhassani, H, Abolmaali, M, Abouzid, M, Aboye, G, Abreu, L, Abrha, W, Abtahi, D, Abu Rumeileh, S, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abu-Rmeileh, N, Aburuz, S, Abu-Zaid, A, Accrombessi, M, Adal, T, Adamu, A, Addo, I, Addolorato, G, Adebiyi, A, Adekanmbi, V, Adepoju, A, Adetunji, C, Adetunji, J, Adeyeoluwa, T, Adeyinka, D, Adeyomoye, O, Admass, B, Adnani, Q, Adra, S, Afolabi, A, Afzal, M, Afzal, S, Agampodi, S, Agasthi, P, Aggarwal, M, Aghamiri, S, Agide, F, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, M, Ahmad, S, Ahmad, T, Ahmadi, K, Ahmadzade, A, Ahmed, A, Ahmed, H, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Akara, E, Akbarialiabad, H, Akinosoglou, K, Akinyemiju, T, Akkaif, M, Akyirem, S, Al Hamad, H, Al Hasan, S, Alahdab, F, Alalalmeh, S, Alalwan, T, Al-Aly, Z, Alam, K, Alam, M, Alam, N, Al-amer, R, Alanezi, F, Alanzi, T, Al-Azzam, S, Albakri, A, Albashtawy, M, Albataineh, M, Alcalde-Rabanal, J, Aldawsari, K, Aldhaleei, W, Aldridge, R, Alema, H, Alemayohu, M, Alemi, S, Alemu, Y, Al-Gheethi, A, Alhabib, K, Alhalaiqa, F, Al-Hanawi, M, Ali, A, Ali, L, Ali, M, Ali, R, Ali, S, Alicandro, G, Alif, S, Alikhani, R, Alimohamadi, Y, Aliyi, A, Aljasir, M, Aljunid, S, Alla, F, Allebeck, P, Al-Marwani, S, Al-Maweri, S, Almazan, J, Al-Mekhlafi, H, Almidani, L, Almidani, O, Alomari, M, Al-Omari, B, Alonso, J, Alqahtani, J, Alqalyoobi, S, Alqutaibi, A, Al-Sabah, S, Altaany, Z, Altaf, A, Al-Tawfiq, J, Altirkawi, K, Aluh, D, Alvis-Guzman, N, Alwafi, H, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Amani, R, Amare, A, Amegbor, P, Ameyaw, E, Amin, T, Amindarolzarbi, A, 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Ekundayo, T, El Sayed, I, Elbarazi, I, Elema, T, Elemam, N, Elgar, F, Elgendy, I, Elgohary, G, Elhabashy, H, Elhadi, M, El-Huneidi, W, Elilo, L, Elmeligy, O, Elmonem, M, Elshaer, M, Elsohaby, I, Emeto, T, Engelbert Bain, L, Erkhembayar, R, Esezobor, C, Eshrati, B, Eskandarieh, S, Espinosa-Montero, J, Esubalew, H, Etaee, F, Fabin, N, Fadaka, A, Fagbamigbe, A, Fahim, A, Fahimi, S, Fakhri-Demeshghieh, A, Falzone, L, Fareed, M, Farinha, C, Faris, M, Faris, P, Faro, A, Fasanmi, A, Fatehizadeh, A, Fattahi, H, Fauk, N, Fazeli, P, Feigin, V, Feizkhah, A, Fekadu, G, Feng, X, Fereshtehnejad, S, Feroze, A, Ferrante, D, Ferrari, A, Ferreira, N, Fetensa, G, Feyisa, B, Filip, I, Fischer, F, Flavel, J, Flood, D, Florin, B, Foigt, N, Folayan, M, Fomenkov, A, Foroutan, B, Foroutan, M, Forthun, I, Fortuna, D, Foschi, M, Fowobaje, K, Francis, K, Franklin, R, Freitas, A, Friedman, J, Friedman, S, Fukumoto, T, Fuller, J, Fux, B, Gaal, P, Gadanya, M, Gaidhane, A, Gaihre, S, Gakidou, E, Galali, Y, Galles, N, Gallus, S, Ganbat, M, Gandhi, A, Ganesan, B, Ganiyani, M, Garcia-Gordillo, M, Gardner, W, Garg, J, Garg, N, Gautam, R, Gbadamosi, S, Gebi, T, Gebregergis, M, Gebrehiwot, M, Gebremeskel, T, Georgescu, S, Getachew, T, Gething, P, Getie, M, Ghadiri, K, Ghahramani, S, Ghailan, K, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghashghaee, A, Ghassemi, F, Ghazy, R, Ghimire, A, Ghoba, S, Gholamalizadeh, M, Gholamian, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Ghorbani Vajargah, P, Ghoshal, A, Gill, P, Gill, T, Gillum, R, Ginindza, T, Girmay, A, Glasbey, J, Gnedovskaya, E, Göbölös, L, Godinho, M, Goel, A, Golchin, A, Goldust, M, Golechha, M, Goleij, P, Gomes, N, Gona, P, Gopalani, S, Gorini, G, Goudarzi, H, Goulart, A, Goulart, B, Goyal, A, Grada, A, Graham, S, Grivna, M, Grosso, G, Guan, S, Guarducci, G, Gubari, M, Gudeta, M, Guha, A, Guicciardi, S, Guimarães, R, Gulati, S, Gunawardane, D, Gunturu, S, Guo, C, Gupta, A, Gupta, B, Gupta, M, Gupta, R, Gupta, S, Gupta, V, Gurmessa, L, Gutiérrez, R, Habibzadeh, F, Habibzadeh, P, Haddadi, R, Hadei, M, Hadi, N, Haep, N, Hafezi-Nejad, N, Hailu, A, Haj-Mirzaian, A, Halboub, E, Hall, B, Haller, S, Halwani, R, Hamadeh, R, Hameed, S, Hamidi, S, Hamilton, E, Han, C, Han, Q, Hanif, A, Hanifi, N, Hankey, G, Hanna, F, Hannan, M, Haque, M, Harapan, H, Hargono, A, Haro, J, Hasaballah, A, Hasan, I, Hasan, M, Hasani, H, Hasanian, M, Hashi, A, Hasnain, M, Hassan, I, Hassanipour, S, Hassankhani, H, Haubold, J, Havmoeller, R, Hay, S, He, J, Hebert, J, Hegazi, O, Heidari, G, Heidari, M, Heidari-Foroozan, M, Helfer, B, Hendrie, D, Herrera-Serna, B, Herteliu, C, Hesami, H, Hezam, K, Hill, C, Hiraike, Y, Holla, R, Horita, N, Hossain, M, Hossain, S, Hosseini, M, Hosseinzadeh, H, Hosseinzadeh, M, Hosseinzadeh Adli, A, Hostiuc, M, Hostiuc, S, Hsairi, M, Hsieh, V, Hsu, R, Hu, C, Huang, J, Hultström, M, Humayun, A, Hundie, T, Hussain, J, Hussain, M, Hussein, N, Hussien, F, Huynh, H, Hwang, B, Ibitoye, S, Ibrahim, K, Iftikhar, P, Ijo, D, Ikiroma, A, Ikuta, K, Ikwegbue, P, Ilesanmi, O, Ilic, I, Ilic, M, Imam, M, Immurana, M, Inamdar, S, Indriasih, E, Iqhrammullah, M, Iradukunda, A, Iregbu, K, Islam, M, Islam, S, Islami, F, Ismail, F, Ismail, N, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iyamu, I, Iyer, M, J, L, Jaafari, J, Jacob, L, Jacobsen, K, Jadidi-Niaragh, F, Jafarinia, M, Jafarzadeh, A, Jaggi, K, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jain, N, Jairoun, A, Jaiswal, A, Jamshidi, E, Janko, M, Jatau, A, Javadov, S, Javaheri, T, Jayapal, S, Jayaram, S, Jebai, R, Jee, S, Jeganathan, J, Jha, A, Jha, R, Jiang, H, Jin, Y, Johnson, O, Jokar, M, Jonas, J, Joo, T, Joseph, A, Joseph, N, Joshua, C, Joshy, G, Jozwiak, J, Jürisson, M, K, V, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kadir, D, Kalani, R, Kalankesh, L, Kaliyadan, F, Kalra, S, Kamal, V, Kamarajah, S, Kamath, R, Kamiab, Z, Kamyari, N, Kanagasabai, T, Kanchan, T, Kandel, H, Kanmanthareddy, A, Kanmiki, E, Kanmodi, K, Kannan S, S, Kansal, S, Kantar, R, Kapoor, N, Karajizadeh, M, Karanth, S, Karasneh, R, Karaye, I, Karch, A, Karim, A, Karimi, S, Karimi Behnagh, A, Kashoo, F, Kasnazani, Q, Kasraei, H, Kassebaum, N, Kassel, M, Kauppila, J, Kaur, N, Kawakami, N, Kayode, G, Kazemi, F, Kazemian, S, Kazmi, T, Kebebew, G, Kebede, A, Kebede, F, Keflie, T, Keiyoro, P, Keller, C, Kelly, J, Kempen, J, Kerr, J, Kesse-Guyot, E, Khajuria, H, Khalaji, A, Khalid, N, Khalil, A, Khalilian, A, Khamesipour, F, Khan, A, Khan, G, Khan, I, Khan, M, Khan, Z, Khan suheb, M, Khanmohammadi, S, Khatab, K, Khatami, F, Khatatbeh, H, Khatatbeh, M, Khavandegar, A, Khayat Kashani, H, Khidri, F, Khodadoust, E, Khorgamphar, M, Khormali, M, Khorrami, Z, Khosravi, A, Khosravi, M, Kifle, Z, Kim, G, Kim, J, Kim, K, Kim, M, Kim, Y, Kimokoti, R, Kinzel, K, Kisa, A, Kisa, S, Klu, D, Knudsen, A, Kocarnik, J, Kochhar, S, Kocsis, T, Koh, D, Kolahi, A, Kolves, K, Kompani, F, Koren, G, Kosen, S, Kostev, K, Koul, P, Koulmane Laxminarayana, S, Krishan, K, Krishna, H, Krishna, V, Krishnamoorthy, V, Krishnamoorthy, Y, Krohn, K, Kuate Defo, B, Kucuk Bicer, B, Kuddus, M, Kuitunen, I, Kulimbet, M, Kulkarni, V, Kumar, A, Kumar, H, Kumar, M, Kumar, R, Kumari, M, Kumie, F, Kundu, S, Kurmi, O, Kusnali, A, Kusuma, D, Kwarteng, A, Kyriopoulos, I, Kyu, H, La Vecchia, C, Lacey, B, Ladan, M, Laflamme, L, Lagat, A, Lager, A, Lahmar, A, Lai, D, Lal, D, Lalloo, R, Lallukka, T, Lam, H, Lám, J, Landrum, K, Lanfranchi, F, Lang, J, Langguth, B, Lansingh, V, Laplante-Lévesque, A, Larijani, B, Larsson, A, Lasrado, S, Lassi, Z, Latief, K, Latifinaibin, K, Lauriola, P, Le, N, Le, T, Ledda, C, Ledesma, J, Lee, M, Lee, P, Lee, S, Lee, W, Lee, Y, Legrand, K, Leigh, J, Leong, E, Lerango, T, Li, M, Li, W, Li, X, Li, Y, Li, Z, Ligade, V, Likaka, A, Lim, L, Lim, S, Lindstrom, M, Linehan, C, Liu, C, Liu, G, Liu, J, Liu, R, Liu, S, Liu, X, Llanaj, E, Loftus, M, López-Bueno, R, Lopukhov, P, Loreche, A, Lorkowski, S, Lotufo, P, Lozano, R, Lubinda, J, Lucchetti, G, Lugo, A, Lunevicius, R, Ma, Z, Maass, K, Machairas, N, Machoy, M, Madadizadeh, F, Madsen, C, Madureira-Carvalho, Á, Maghazachi, A, Maharaj, S, Mahjoub, S, Mahmoud, M, Mahmoudi, A, Mahmoudi, E, Mahmoudi, R, Majeed, A, Makhdoom, I, Malakan Rad, E, Maled, V, Malekzadeh, R, Malhotra, A, Malhotra, K, Malik, A, Malik, I, Malta, D, Mamun, A, Mansouri, P, Mansournia, M, Mantovani, L, Maqsood, S, Marasini, B, Marateb, H, Maravilla, J, Marconi, A, Mardi, P, Marino, M, Marjani, A, Martinez, G, Martinez-Guerra, B, Martinez-Piedra, R, Martini, D, Martini, S, Martins-Melo, F, Martorell, M, Marx, W, Maryam, S, Marzo, R, Masaka, A, Masrie, A, Mathieson, S, Mathioudakis, A, Mathur, M, Mattumpuram, J, Matzopoulos, R, Maude, R, Maugeri, A, Maulik, P, Mayeli, M, Mazaheri, M, Mazidi, M, Mcgrath, J, Mckee, M, Mckowen, A, Mclaughlin, S, Mcphail, S, Mechili, E, Medina, J, Mediratta, R, Meena, J, Mehra, R, Mehrabani-Zeinabad, K, Mehrabi Nasab, E, Mekene Meto, T, Meles, G, Mendez-Lopez, M, Mendoza, W, Menezes, R, Mengist, B, Mentis, A, 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Francesca, Santomauro, Damian Francesco, Santos, Itamar S, Santric-Milicevic, Milena M, Sao Jose, Bruno Piassi, Sarasmita, Made Ary, Saraswathy, Sivan Yegnanarayana Iyer, Saravanan, Aswini, Saravi, Babak, Sarikhani, Yaser, Sarkar, Tanmay, Sarmiento-Suárez, Rodrigo, Sarode, Gargi Sachin, Sarode, Sachin C, Sarveazad, Arash, Sathian, Brijesh, Sathish, Thirunavukkarasu, Satpathy, Maheswar, Sayeed, Abu, Sayeed, Md Abu, Saylan, Mete, Sayyah, Mehdi, Scarmeas, Nikolaos, Schaarschmidt, Benedikt Michael, Schlaich, Markus P, Schlee, Winfried, Schmidt, Maria Inês, Schneider, Ione Jayce Ceola, Schuermans, Art, Schumacher, Austin E, Schutte, Aletta Elisabeth, Schwarzinger, Michaël, Schwebel, David C, Schwendicke, Falk, Šekerija, Mario, Selvaraj, Siddharthan, Senapati, Sabyasachi, Senthilkumaran, Subramanian, Sepanlou, Sadaf G, Serban, Dragos, Sethi, Yashendra, Sha, Feng, Shabany, Maryam, Shafaat, Amir, Shafie, Mahan, Shah, Nilay S, Shah, Pritik A, Shah, Syed Mahboob, Shahabi, Saeed, Shahbandi, Ataollah, Shahid, Izza, Shahid, Samiah, Shahid, Wajeehah, Shahsavari, Hamid R, Shahwan, Moyad Jamal, Shaikh, Ahmed, Shaikh, Masood Ali, Shakeri, Alireza, Shalash, Ali S, Sham, Sunder, Shamim, Muhammad Aaqib, Shams-Beyranvand, Mehran, Shamshad, Hina, Shamsi, Mohammad Anas, Shanawaz, Mohd, Shankar, Abhishek, Sharfaei, Sadaf, Sharifan, Amin, Sharifi-Rad, Javad, Sharma, Rajesh, Sharma, Saurab, Sharma, Ujjawal, Sharma, Vishal, Shastry, Rajesh P, Shavandi, Amin, Shayan, Maryam, Shehabeldine, Amr Mohamed Elsayed, Sheikh, Aziz, Sheikhi, Rahim Ali, Shen, Jiabin, Shetty, Adithi, Shetty, B Suresh Kumar, Shetty, Pavanchand H, Shi, Peilin, Shibuya, Kenji, Shiferaw, Desalegn, Shigematsu, Mika, Shin, Min-Jeong, Shin, Youn Ho, Shiri, Rahman, Shirkoohi, Reza, Shitaye, Nebiyu Aniley, Shittu, Aminu, Shiue, Ivy, Shivakumar, K M, Shivarov, Velizar, Shokraneh, Farhad, Shokri, Azad, Shool, Sina, Shorofi, Seyed Afshin, Shrestha, Sunil, Shuval, Kerem, Siddig, Emmanuel Edwar, Silva, João Pedro, Silva, Luís Manuel Lopes Rodrigues, Silva, Soraia, Simpson, Colin R, Singal, Anjali, Singh, Abhinav, Singh, Balbir Bagicha, Singh, Garima, Singh, Jasbir, Singh, Narinder Pal, Singh, Paramdeep, Singh, Surjit, Sinha, Dhirendra Narain, Sinto, Robert, Siraj, Md Shahjahan, Sirota, Sarah Brooke, Sitas, Freddy, Sivakumar, Shravan, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Sleet, David A, Socea, Bogdan, Sokhan, Anton, Solanki, Ranjan, Solanki, Shipra, Soleimani, Hamidreza, Soliman, Sameh S M, Song, Suhang, Song, Yimeng, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Spartalis, Michael, Spearman, Sandra, Sreeramareddy, Chandrashekhar T, Srivastava, Vijay Kumar, Stanaway, Jeffrey D, Stanikzai, Muhammad Haroon, Stark, Benjamin A, Starnes, Joseph R, Starodubova, Antonina V, Stein, Caroline, Stein, Dan J, Steinbeis, Fridolin, Steiner, Caitlyn, Steinmetz, Jaimie D, Steiropoulos, Paschalis, Stevanović, Aleksandar, Stockfelt, Leo, Stokes, Mark A, Stortecky, Stefan, Subramaniyan, 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Pugazhenthan, Thankappan, Kavumpurathu Raman, Tharwat, Samar, Thayakaran, Rasiah, Thomas, Nihal, Thomas, Nikhil Kenny, Thomson, Azalea M, Thrift, Amanda G, Thum, Chern Choong Chern, Thygesen, Lau Caspar, Tian, Jing, Tichopad, Ales, Ticoalu, Jansje Henny Vera, Tillawi, Tala, Tiruye, Tenaw Yimer, Titova, Mariya Vladimirovna, Tonelli, Marcello, Topor-Madry, Roman, Toriola, Adetunji T, Torre, Anna E, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Tran, Jasmine T, Tran, Nghia Minh, Trico, Domenico, Tromans, Samuel Joseph, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsegay, Guesh Mebrahtom, Tsermpini, Evangelia Eirini, Tumurkhuu, Munkhtuya, Tung, Kang, Tyrovolas, Stefanos, Uddin, Sayed Mohammad Nazim, Udoakang, Aniefiok John, Udoh, Arit, Ullah, Atta, Ullah, Irfan, Ullah, Saeed, Ullah, Sana, Umakanthan, Srikanth, Umeokonkwo, Chukwuma David, Unim, Brigid, Unnikrishnan, Bhaskaran, Unsworth, Carolyn Anne, Upadhyay, Era, Urso, Daniele, Usman, Jibrin Sammani, Vahabi, Seyed Mohammad, 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Taweewat, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Wilandika, Angga, Wilkerson, Caroline, Willeit, Peter, Wilson, Shadrach, Wojewodzic, Marcin W, Woldegebreal, Demewoz H, Wolf, Axel Walter, Wolfe, Charles D A, Wondimagegene, Yohannes Addisu, Wong, Yen Jun, Wongsin, Utoomporn, Wu, Ai-Min, Wu, Chenkai, Wu, Felicia, Wu, Xinsheng, Wu, Zenghong, Xia, Juan, Xiao, Hong, Xie, Yang, Xu, Suowen, Xu, Wang-Dong, Xu, Xiaoyue, Xu, Yvonne Yiru, Yadollahpour, Ali, Yamagishi, Kazumasa, Yang, Danting, Yang, Lin, Yano, Yuichiro, Yao, Yao, Yaribeygi, Habib, Ye, Pengpeng, Yehualashet, Sisay Shewasinad, Yesiltepe, Metin, Yesuf, Subah Abderehim, Yezli, Saber, Yi, Siyan, Yigezu, Amanuel, Yiğit, Arzu, Yiğit, Vahit, Yip, Paul, Yismaw, Malede Berihun, Yismaw, Yazachew, Yon, Dong Keon, Yonemoto, Naohiro, Yoon, Seok-Jun, You, Yuyi, Younis, Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Yuh, Faith H, Zadey, Siddhesh, Zadnik, Vesna, Zafari, Nima, Zakham, Fathiah, Zaki, Nazar, Zaman, Sojib Bin, Zamora, Nelson, Zand, Ramin, Zangiabadian, Moein, Zar, Heather J, Zare, Iman, Zarrintan, Armin, Zeariya, Mohammed G M, Zeinali, Zahra, Zhang, Haijun, Zhang, Jianrong, Zhang, Jingya, Zhang, Liqun, Zhang, Yunquan, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhong, Chenwen, Zhou, Juexiao, Zhu, Bin, Zhu, Lei, Ziafati, Makan, Zielińska, Magdalena, Zitoun, Osama A, Zoladl, Mohammad, Zou, Zhiyong, Zuhlke, Liesl J, Zumla, Alimuddin, Zweck, Elric, Zyoud, Samer H, Wool, Eve E, and Murray, Christopher J L
Published: 2024

20. The burden of mental disorders, substance use disorders and self-harm among young people in Europe, 1990–2019: Findings from the Global Burden of Disease Study 2019

Author: Giulio Castelpietra, Ann Kristin Skrindo Knudsen, Emilie E. Agardh, Benedetta Armocida, Massimiliano Beghi, Kim Moesgaard Iburg, Giancarlo Logroscino, Rui Ma, Fabrizio Starace, Nicholas Steel, Giovanni Addolorato, Catalina Liliana Andrei, Tudorel Andrei, Jose L Ayuso-Mateos, Maciej Banach, Till Winfried Bärnighausen, Francesco Barone-Adesi, Akshaya Srikanth Bhagavathula, Felix Carvalho, Márcia Carvalho, Joht Singh Chandan, Vijay Kumar Chattu, Rosa A.S. Couto, Natália Cruz-Martins, Paul I. Dargan, Keshab Deuba, Diana Dias da Silva, Adeniyi Francis Fagbamigbe, Eduarda Fernandes, Pietro Ferrara, Florian Fischer, Peter Andras Gaal, Alessandro Gialluisi, Juanita A. Haagsma, Josep Maria Haro, M. Tasdik Hasan, Syed Shahzad Hasan, Sorin Hostiuc, Licia Iacoviello, Ivo Iavicoli, Elham Jamshidi, Jost B. Jonas, Tamas Joo, Jacek Jerzy Jozwiak, Srinivasa Vittal Katikireddi, Joonas H. Kauppila, Moien A.B. Khan, Adnan Kisa, Sezer Kisa, Mika Kivimäki, Kamrun Nahar Koly, Ai Koyanagi, Manasi Kumar, Tea Lallukka, Berthold Langguth, Caterina Ledda, Paul H. Lee, Ilaria Lega, Christine Linehan, Joana A. Loureiro, Áurea M Madureira-Carvalho, Jose Martinez-Raga, Manu Raj Mathur, John J. McGrath, Enkeleint A. Mechili, Alexios-Fotios A. Mentis, Tomislav Mestrovic, Bartosz Miazgowski, Andreea Mirica, Antonio Mirijello, Babak Moazen, Shafiu Mohammed, Francesk Mulita, Gabriele Nagel, Ionut Negoi, Ruxandra Irina Negoi, Vincent Ebuka Nwatah, Alicia Padron-Monedero, Songhomitra Panda-Jonas, Shahina Pardhan, Maja Pasovic, Jay Patel, Ionela-Roxana Petcu, Marina Pinheiro, Richard Charles G. Pollok, Maarten J. Postma, David Laith Rawaf, Salman Rawaf, Esperanza Romero-Rodríguez, Luca Ronfani, Dominic Sagoe, Francesco Sanmarchi, Michael P Schaub, Nigussie Tadesse Sharew, Rahman Shiri, Farhad Shokraneh, Inga Dora Sigfusdottir, João Pedro Silva, Renata Silva, Bogdan Socea, Miklós Szócska, Rafael Tabarés-Seisdedos, Marco Torrado, Marcos Roberto Tovani-Palone, Tommi Juhani Vasankari, Massimiliano Veroux, Russell M. Viner, Andrea Werdecker, Andrea Sylvia Winkler, Simon I. Hay, Alize J. Ferrari, Mohsen Naghavi, Peter Allebeck, and Lorenzo Monasta
Subjects: Young people, Mental health, Mental disorders, Self-harm, Substance use, Europe, Public aspects of medicine, RA1-1270
Abstract: Summary: Background: Mental health is a public health issue for European young people, with great heterogeneity in resource allocation. Representative population-based studies are needed. The Global Burden of Disease (GBD) Study 2019 provides internationally comparable information on trends in the health status of populations and changes in the leading causes of disease burden over time. Methods: Prevalence, incidence, Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) from mental disorders (MDs), substance use disorders (SUDs) and self-harm were estimated for young people aged 10-24 years in 31 European countries. Rates per 100,000 population, percentage changes in 1990-2019, 95% Uncertainty Intervals (UIs), and correlations with Sociodemographic Index (SDI), were estimated. Findings: In 2019, rates per 100,000 population were 16,983 (95% UI 12,823 – 21,630) for MDs, 3,891 (3,020 - 4,905) for SUDs, and 89·1 (63·8 - 123·1) for self-harm. In terms of disability, anxiety contributed to 647·3 (432–912·3) YLDs, while in terms of premature death, self-harm contributed to 319·6 (248·9–412·8) YLLs, per 100,000 population. Over the 30 years studied, YLDs increased in eating disorders (14·9%;9·4-20·1) and drug use disorders (16·9%;8·9-26·3), and decreased in idiopathic developmental intellectual disability (–29·1%;23·8-38·5). YLLs decreased in self-harm (–27·9%;38·3-18·7). Variations were found by sex, age-group and country. The burden of SUDs and self-harm was higher in countries with lower SDI, MDs were associated with SUDs. Interpretation: Mental health conditions represent an important burden among young people living in Europe. National policies should strengthen mental health, with a specific focus on young people. Funding: The Bill and Melinda Gates Foundation
Published: 2022
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21. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Author: Collaborators, GBD 2015 Risk Factors, Forouzanfar, Mohammad H, Afshin, Ashkan, Alexander, Lily T, Anderson, H Ross, Bhutta, Zulfiqar A, Biryukov, Stan, Brauer, Michael, Burnett, Richard, Cercy, Kelly, Charlson, Fiona J, Cohen, Aaron J, Dandona, Lalit, Estep, Kara, Ferrari, Alize J, Frostad, Joseph J, Fullman, Nancy, Gething, Peter W, Godwin, William W, Griswold, Max, Hay, Simon I, Kinfu, Yohannes, Kyu, Hmwe H, Larson, Heidi J, Liang, Xiaofeng, Lim, Stephen S, Liu, Patrick Y, Lopez, Alan D, Lozano, Rafael, Marczak, Laurie, Mensah, George A, Mokdad, Ali H, Moradi-Lakeh, Maziar, Naghavi, Mohsen, Neal, Bruce, Reitsma, Marissa B, Roth, Gregory A, Salomon, Joshua A, Sur, Patrick J, Vos, Theo, Wagner, Joseph A, Wang, Haidong, Zhao, Yi, Zhou, Maigeng, Aasvang, Gunn Marit, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulle, Abdishakur M, Abera, Semaw Ferede, Abraham, Biju, Abu-Raddad, Laith J, Abyu, Gebre Yitayih, Adebiyi, Akindele Olupelumi, Adedeji, Isaac Akinkunmi, Ademi, Zanfina, Adou, Arsène Kouablan, Adsuar, José C, Agardh, Emilie Elisabet, Agarwal, Arnav, Agrawal, Anurag, Kiadaliri, Aliasghar Ahmad, Ajala, Oluremi N, Akinyemiju, Tomi F, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore KM, Aldhahri, Saleh Fahed, Aldridge, Robert William, Alemu, Zewdie Aderaw, Ali, Raghib, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alsharif, Ubai, Altirkawi, Khalid A, Martin, Elena Alvarez, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amberbir, Alemayehu, Amegah, Adeladza Kofi, Amini, Heresh, Ammar, Walid, Amrock, Stephen Marc, Andersen, Hjalte H, Anderson, Benjamin O, Antonio, Carl Abelardo T, Anwari, Palwasha, Ärnlöv, Johan, Artaman, Al, Asayesh, Hamid, Asghar, Rana Jawad, Assadi, Reza, Atique, Suleman, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, and Azzopardi, Peter
Subjects: Prevention, Pediatric, Climate-Related Exposures and Conditions, 2.2 Factors relating to the physical environment, Aetiology, Generic health relevance, Good Health and Well Being, Africa South of the Sahara, Africa, Northern, Air Pollution, Indoor, Alcohol Drinking, Biomarkers, Blood Glucose, Body Mass Index, Cholesterol, Cost of Illness, Disabled Persons, Environmental Exposure, Global Health, Humans, Hypertension, Life Expectancy, Malnutrition, Middle East, Occupational Exposure, Quality-Adjusted Life Years, Risk Assessment, Risk Factors, Risk-Taking, Smoking, Sodium, Dietary, Substance-Related Disorders, Unsafe Sex, GBD 2015 Risk Factors Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context.MethodsWe used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI).FindingsBetween 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6-58·8) of global deaths and 41·2% (39·8-42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa.InterpretationDeclines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden.FundingBill & Melinda Gates Foundation.
Published: 2016

22. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Author: Collaborators, GBD 2013 Risk Factors, Forouzanfar, Mohammad H, Alexander, Lily, Anderson, H Ross, Bachman, Victoria F, Biryukov, Stan, Brauer, Michael, Burnett, Richard, Casey, Daniel, Coates, Matthew M, Cohen, Aaron, Delwiche, Kristen, Estep, Kara, Frostad, Joseph J, Astha, KC, Kyu, Hmwe H, Moradi-Lakeh, Maziar, Ng, Marie, Slepak, Erica Leigh, Thomas, Bernadette A, Wagner, Joseph, Aasvang, Gunn Marit, Abbafati, Cristiana, Ozgoren, Ayse Abbasoglu, Abd-Allah, Foad, Abera, Semaw F, Aboyans, Victor, Abraham, Biju, Abraham, Jerry Puthenpurakal, Abubakar, Ibrahim, Abu-Rmeileh, Niveen ME, Aburto, Tania C, Achoki, Tom, Adelekan, Ademola, Adofo, Koranteng, Adou, Arsène K, Adsuar, José C, Afshin, Ashkan, Agardh, Emilie E, Khabouri, Mazin J Al, Lami, Faris H Al, Alam, Sayed Saidul, Alasfoor, Deena, Albittar, Mohammed I, Alegretti, Miguel A, Aleman, Alicia V, Alemu, Zewdie A, Alfonso-Cristancho, Rafael, Alhabib, Samia, Ali, Raghib, Ali, Mohammed K, Alla, François, Allebeck, Peter, Allen, Peter J, Alsharif, Ubai, Alvarez, Elena, Alvis-Guzman, Nelson, Amankwaa, Adansi A, Amare, Azmeraw T, Ameh, Emmanuel A, Ameli, Omid, Amini, Heresh, Ammar, Walid, Anderson, Benjamin O, Antonio, Carl Abelardo T, Anwari, Palwasha, Cunningham, Solveig Argeseanu, Arnlöv, Johan, Arsenijevic, Valentina S Arsic, Artaman, Al, Asghar, Rana J, Assadi, Reza, Atkins, Lydia S, Atkinson, Charles, Avila, Marco A, Awuah, Baffour, Badawi, Alaa, Bahit, Maria C, Bakfalouni, Talal, Balakrishnan, Kalpana, Balalla, Shivanthi, Balu, Ravi Kumar, Banerjee, Amitava, Barber, Ryan M, Barker-Collo, Suzanne L, Barquera, Simon, Barregard, Lars, Barrero, Lope H, Barrientos-Gutierrez, Tonatiuh, Basto-Abreu, Ana C, Basu, Arindam, Basu, Sanjay, Basulaiman, Mohammed O, Ruvalcaba, Carolina Batis, Beardsley, Justin, Bedi, Neeraj, Bekele, Tolesa, Bell, Michelle L, Benjet, Corina, and Bennett, Derrick A
Subjects: Nutrition, Prevention, Clinical Research, 2.2 Factors relating to the physical environment, Aetiology, Good Health and Well Being, Environmental Exposure, Female, Global Health, Health Behavior, Humans, Male, Metabolic Diseases, Nutritional Status, Occupational Diseases, Occupational Exposure, Risk Assessment, Risk Factors, Sanitation, GBD 2013 Risk Factors Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundThe Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.MethodsAttributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol.FindingsAll risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa.InterpretationBehavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.FundingBill & Melinda Gates Foundation.
Published: 2015

23. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Author: Collaborators, Global Burden of Disease Study 2013, Vos, Theo, Barber, Ryan M, Bell, Brad, Bertozzi-Villa, Amelia, Biryukov, Stan, Bolliger, Ian, Charlson, Fiona, Davis, Adrian, Degenhardt, Louisa, Dicker, Daniel, Duan, Leilei, Erskine, Holly, Feigin, Valery L, Ferrari, Alize J, Fitzmaurice, Christina, Fleming, Thomas, Graetz, Nicholas, Guinovart, Caterina, Haagsma, Juanita, Hansen, Gillian M, Hanson, Sarah Wulf, Heuton, Kyle R, Higashi, Hideki, Kassebaum, Nicholas, Kyu, Hmwe, Laurie, Evan, Liang, Xiofeng, Lofgren, Katherine, Lozano, Rafael, MacIntyre, Michael F, Moradi-Lakeh, Maziar, Naghavi, Mohsen, Nguyen, Grant, Odell, Shaun, Ortblad, Katrina, Roberts, David Allen, Roth, Gregory A, Sandar, Logan, Serina, Peter T, Stanaway, Jeffrey D, Steiner, Caitlyn, Thomas, Bernadette, Vollset, Stein Emil, Whiteford, Harvey, Wolock, Timothy M, Ye, Pengpeng, Zhou, Maigeng, Ãvila, Marco A, Aasvang, Gunn Marit, Abbafati, Cristiana, Ozgoren, Ayse Abbasoglu, Abd-Allah, Foad, Aziz, Muna I Abdel, Abera, Semaw F, Aboyans, Victor, Abraham, Jerry P, Abraham, Biju, Abubakar, Ibrahim, Abu-Raddad, Laith J, Abu-Rmeileh, Niveen ME, Aburto, Tania C, Achoki, Tom, Ackerman, Ilana N, Adelekan, Ademola, Ademi, Zanfina, Adou, Arsène K, Adsuar, Josef C, Arnlov, Johan, Agardh, Emilie E, Khabouri, Mazin J Al, Alam, Sayed Saidul, Alasfoor, Deena, Albittar, Mohammed I, Alegretti, Miguel A, Aleman, Alicia V, Alemu, Zewdie A, Alfonso-Cristancho, Rafael, Alhabib, Samia, Ali, Raghib, Alla, Francois, Allebeck, Peter, Allen, Peter J, AlMazroa, Mohammad AbdulAziz, Alsharif, Ubai, Alvarez, Elena, Alvis-Guzman, Nelson, Ameli, Omid, Amini, Heresh, Ammar, Walid, Anderson, Benjamin O, Anderson, H Ross, Antonio, Carl Abelardo T, Anwari, Palwasha, Apfel, Henry, Arsenijevic, Valentain S Arsic, Artaman, Al, Asghar, Rana J, Assadi, Reza, and Atkins, Lydia S
Subjects: Burden of Illness, Infectious Diseases, Brain Disorders, Pain Research, Mental Health, 2.4 Surveillance and distribution, Aetiology, 2.1 Biological and endogenous factors, 2.2 Factors relating to the physical environment, Good Health and Well Being, Acute Disease, Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Child, Child, Preschool, Chronic Disease, Cost of Illness, Developed Countries, Developing Countries, Disabled Persons, Female, Global Health, Humans, Incidence, Infant, Infant, Newborn, Male, Middle Aged, Neglected Diseases, Prevalence, Residence Characteristics, Sex Distribution, Wounds and Injuries, Young Adult, Global Burden of Disease Study 2013 Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundUp-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013.MethodsEstimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries.FindingsDisease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013.InterpretationAgeing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries.FundingBill & Melinda Gates Foundation.
Published: 2015

24. Conducting a multi‐country online alcohol survey in the time of the COVID‐19 pandemic: Opportunities and challenges

Author: Carolin Kilian, Jürgen Rehm, Peter Allebeck, Miroslav Barták, Fleur Braddick, Antoni Gual, Silvia Matrai, Benjamin Petruželka, Vladimir Rogalewicz, Ingeborg Rossow, Bernd Schulte, Mindaugas Štelemėkas, and Jakob Manthey
Subjects: epidemiology, methodology, representativeness, substance use, surveys, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Objectives This contribution provides insights into the methodology of a pan‐European population‐based online survey, performed without external funding during the COVID‐19 pandemic. We present the impact of different dissemination strategies to collect data from a non‐probabilistic convenience sample and outline post‐stratification weighting schemes, to provide guidance for future multi‐country survey studies. Methods Description and comparison of dissemination strategies for five exemplary countries (Czechia, Germany, Lithuania, Norway, Spain) participating in the Alcohol Use and COVID‐19 Survey. Comparison of the sample distribution with the country's actual population distribution according to sociodemographics, and development of weighting schemes. Results The dissemination of online surveys through national newspapers, paid social media adverts and dissemination with the support of national health ministries turned out to be the most effective strategies. Monitoring the responses and adapting dissemination strategies to reach under‐represented groups, and the application of sample weights were helpful to achieve an analytic sample matching the respective general population profiles. Conclusion Reaching a large pan‐European convenience sample, including most European countries, in a short time was feasible, with the support of a broad scientific network.
Published: 2021
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25. Life expectancy and disease burden in the Nordic countries: results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

Author: Ann Kristin Knudsen, Peter Allebeck, Mette C Tollånes, Jens Christoffer Skogen, Kim Moesgaard Iburg, John J. McGrath, Knud Juel, Emilie Elisabet Agardh, Johan Ärnlöv, Tone Bjørge, Juan J Carrero, Christopher R. Cederroth, Anne Elise Eggen, Ziad El-Khatib, Christian Lycke Ellingsen, Seyed-Mohammad Fereshtehnejad, Mika Gissler, Kishor Hadkhale, Rasmus Havmoeller, Lars Johansson, Peter Benedikt Juliusson, Aliasghar A Kiadaliri, Sezer Kisa, Adnan Kisa, Tea Lallukka, Teferi Mekonnen, Tuomo J Meretoja, Atte Meretoja, Mohsen Naghavi, Subas Neupane, Truc Trung Nguyen, Max Petzold, Oleguer Plana-Ripoll, Rahman Shiri, Rannveig Sigurvinsdottir, Vegard Skirbekk, Søren T Skou, Inga Dora Sigfusdottir, Timothy J Steiner, Gerhard Sulo, Thomas Clement Truelsen, Tommi Juhani Vasankari, Elisabete Weiderpass, Stein Emil Vollset, Theo Vos, and Simon Øverland
Subjects: Public aspects of medicine, RA1-1270
Abstract: Summary: Background: The Nordic countries have commonalities in gender equality, economy, welfare, and health care, but differ in culture and lifestyle, which might create country-wise health differences. This study compared life expectancy, disease burden, and risk factors in the Nordic region. Methods: Life expectancy in years and age-standardised rates of overall, cause-specific, and risk factor-specific estimates of disability-adjusted life-years (DALYs) were analysed in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. Data were extracted for Denmark, Finland, Iceland, Norway, and Sweden (ie, the Nordic countries), and Greenland, an autonomous area of Denmark. Estimates were compared with global, high-income region, and Nordic regional estimates, including Greenland. Findings: All Nordic countries exceeded the global life expectancy; in 2017, the highest life expectancy was in Iceland among females (85·9 years [95% uncertainty interval [UI] 85·5–86·4] vs 75·6 years [75·3–75·9] globally) and Sweden among males (80·8 years [80·2–81·4] vs 70·5 years [70·1–70·8] globally). Females (82·7 years [81·9–83·4]) and males (78·8 years [78·1–79·5]) in Denmark and males in Finland (78·6 years [77·8–79·2]) had lower life expectancy than in the other Nordic countries. The lowest life expectancy in the Nordic region was in Greenland (females 77·2 years [76·2–78·0], males 70·8 years [70·3–71·4]). Overall disease burden was lower in the Nordic countries than globally, with the lowest age-standardised DALY rates among Swedish males (18 555·7 DALYs [95% UI 15 968·6–21 426·8] per 100 000 population vs 35 834·3 DALYs [33 218·2–38 740·7] globally) and Icelandic females (16 074·1 DALYs [13 216·4–19 240·8] vs 29 934·6 DALYs [26 981·9–33 211·2] globally). Greenland had substantially higher DALY rates (26 666·6 DALYs [23 478·4–30 218·8] among females, 33 101·3 DALYs [30 182·3–36 218·6] among males) than the Nordic countries. Country variation was primarily due to differences in causes that largely contributed to DALYs through mortality, such as ischaemic heart disease. These causes dominated male disease burden, whereas non-fatal causes such as low back pain were important for female disease burden. Smoking and metabolic risk factors were high-ranking risk factors across all countries. DALYs attributable to alcohol use and smoking were particularly high among the Danes, as was alcohol use among Finnish males. Interpretation: Risk factor differences might drive differences in life expectancy and disease burden that merit attention also in high-income settings such as the Nordic countries. Special attention should be given to the high disease burden in Greenland. Funding: Bill & Melinda Gates Foundation. The work on this paper was supported by the Research Council of Norway through FRIPRO (project number 262030) and by the Norwegian Institute of Public Health.
Published: 2019
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26. 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

Author: Naghavi, Mohsen, Ong, Kanyin Liane, Aali, Amirali, Ababneh, Hazim S, Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbasgholizadeh, Rouzbeh, Abbasian, Mohammadreza, Abbasi-Kangevari, Mohsen, Abbastabar, Hedayat, Abd ElHafeez, Samar, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdelwahab, Ahmed, Abdollahi, Mohammad, Abdollahifar, Mohammad-Amin, Abdoun, Meriem, Abdulah, Deldar Morad, Abdullahi, Auwal, Abebe, Mesfin, Abebe, Samrawit Shawel, Abedi, Aidin, Abegaz, Kedir Hussein, Abhilash, E S, Abidi, Hassan, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Abolmaali, Meysam, Abouzid, Mohamed, Aboye, Girma Beressa, Abreu, Lucas Guimarães, Abrha, Woldu Aberhe, Abtahi, Dariush, Abu Rumeileh, Samir, Abualruz, Hasan, Abubakar, Bilyaminu, Abu-Gharbieh, Eman, Abu-Rmeileh, Niveen ME, Aburuz, Salahdein, Abu-Zaid, Ahmed, Accrombessi, Manfred Mario Kokou, Adal, Tadele Girum, Adamu, Abdu A, Addo, Isaac Yeboah, Addolorato, Giovanni, Adebiyi, Akindele Olupelumi, Adekanmbi, Victor, Adepoju, Abiola Victor, Adetunji, Charles Oluwaseun, Adetunji, Juliana Bunmi, Adeyeoluwa, Temitayo Esther, Adeyinka, Daniel Adedayo, Adeyomoye, Olorunsola Israel, Admass, Biruk Adie Adie, Adnani, Qorinah Estiningtyas Sakilah, Adra, Saryia, Afolabi, Aanuoluwapo Adeyimika, Afzal, Muhammad Sohail, Afzal, Saira, Agampodi, Suneth Buddhika, Agasthi, Pradyumna, Aggarwal, Manik, Aghamiri, Shahin, Agide, Feleke Doyore, Agodi, Antonella, Agrawal, Anurag, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Firdos, Ahmad, Muayyad M, Ahmad, Sajjad, Ahmad, Shahzaib, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadzade, Amir Mahmoud, Ahmed, Ali, Ahmed, Ayman, Ahmed, Haroon, Ahmed, Luai A, Ahmed, Mehrunnisha Sharif, Ahmed, Meqdad Saleh, Ahmed, Muktar Beshir, Ahmed, Syed Anees, Ajami, Marjan, Aji, Budi, Akara, Essona Matatom, Akbarialiabad, Hossein, Akinosoglou, Karolina, Akinyemiju, Tomi, Akkaif, Mohammed Ahmed, Akyirem, Samuel, Al Hamad, Hanadi, Al Hasan, Syed Mahfuz, Alahdab, Fares, Alalalmeh, Samer O, Alalwan, Tariq A, Al-Aly, Ziyad, Alam, Khurshid, Alam, Manjurul, Alam, Noore, Al-amer, Rasmieh Mustafa, Alanezi, Fahad Mashhour, Alanzi, Turki M, Al-Azzam, Sayer, Albakri, Almaza, Albashtawy, Mohammed, AlBataineh, Mohammad T, Alcalde-Rabanal, Jacqueline Elizabeth, Aldawsari, Khalifah A, Aldhaleei, Wafa A, Aldridge, Robert W, Alema, Haileselasie Berhane, Alemayohu, Mulubirhan Assefa, Alemi, Sharifullah, Alemu, Yihun Mulugeta, Al-Gheethi, Adel Ali Saeed, Alhabib, Khalid F, Alhalaiqa, Fadwa Alhalaiqa Naji, Al-Hanawi, Mohammed Khaled, Ali, Abid, Ali, Amjad, Ali, Liaqat, Ali, Mohammed Usman, Ali, Rafat, Ali, Shahid, Ali, Syed Shujait Shujait, Alicandro, Gianfranco, Alif, Sheikh Mohammad, Alikhani, Reyhaneh, Alimohamadi, Yousef, Aliyi, Ahmednur Adem, Aljasir, Mohammad A M, Aljunid, Syed Mohamed, Alla, François, Allebeck, Peter, Al-Marwani, Sabah, Al-Maweri, Sadeq Ali Ali, Almazan, Joseph Uy, Al-Mekhlafi, Hesham M, Almidani, Louay, Almidani, Omar, Alomari, 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Ales, Ticoalu, Jansje Henny Vera, Tillawi, Tala, Tiruye, Tenaw Yimer, Titova, Mariya Vladimirovna, Tonelli, Marcello, Topor-Madry, Roman, Toriola, Adetunji T, Torre, Anna E, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Tran, Jasmine T, Tran, Nghia Minh, Trico, Domenico, Tromans, Samuel Joseph, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsegay, Guesh Mebrahtom, Tsermpini, Evangelia Eirini, Tumurkhuu, Munkhtuya, Tung, Kang, Tyrovolas, Stefanos, Uddin, Sayed Mohammad Nazim, Udoakang, Aniefiok John, Udoh, Arit, Ullah, Atta, Ullah, Irfan, Ullah, Saeed, Ullah, Sana, Umakanthan, Srikanth, Umeokonkwo, Chukwuma David, Unim, Brigid, Unnikrishnan, Bhaskaran, Unsworth, Carolyn Anne, Upadhyay, Era, Urso, Daniele, Usman, Jibrin Sammani, Vahabi, Seyed Mohammad, Vaithinathan, Asokan Govindaraj, Valizadeh, Rohollah, Van de Velde, Sarah M, Van den Eynde, Jef, Varga, Orsolya, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vasic, Milena, Vaziri, Siavash, Vellingiri, Balachandar, Venketasubramanian, Narayanaswamy, Verghese, Nicholas Alexander, Verma, Madhur, Veroux, Massimiliano, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafañe, Jorge Hugo, Villanueva, Gabriela Ines, Vinayak, Manish, Violante, Francesco S, Viskadourou, Maria, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vo, Bay, Vollset, Stein Emil, Vongpradith, Avina, Vos, Theo, Vujcic, Isidora S, Vukovic, Rade, Wafa, Hatem A, Waheed, Yasir, Wamai, Richard G, Wang, Cong, Wang, Ning, Wang, Shu, Wang, Song, Wang, Yanzhong, Wang, Yuan-Pang, Waqas, Muhammad, Ward, Paul, Wassie, Emebet Gashaw, Watson, Stefanie, Watson, Stephanie Louise Watson, Weerakoon, Kosala Gayan, Wei, Melissa Y, Weintraub, Robert G, Weiss, Daniel J, Westerman, Ronny, Whisnant, Joanna L, Wiangkham, Taweewat, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Wilandika, Angga, Wilkerson, Caroline, Willeit, Peter, Wilson, Shadrach, Wojewodzic, Marcin W, Woldegebreal, Demewoz H, Wolf, Axel Walter, Wolfe, Charles D A, Wondimagegene, Yohannes Addisu, Wong, Yen Jun, Wongsin, Utoomporn, Wu, Ai-Min, Wu, Chenkai, Wu, Felicia, Wu, Xinsheng, Wu, Zenghong, Xia, Juan, Xiao, Hong, Xie, Yang, Xu, Suowen, Xu, Wang-Dong, Xu, Xiaoyue, Xu, Yvonne Yiru, Yadollahpour, Ali, Yamagishi, Kazumasa, Yang, Danting, Yang, Lin, Yano, Yuichiro, Yao, Yao, Yaribeygi, Habib, Ye, Pengpeng, Yehualashet, Sisay Shewasinad, Yesiltepe, Metin, Yesuf, Subah Abderehim, Yezli, Saber, Yi, Siyan, Yigezu, Amanuel, Yiğit, Arzu, Yiğit, Vahit, Yip, Paul, Yismaw, Malede Berihun, Yismaw, Yazachew, Yon, Dong Keon, Yonemoto, Naohiro, Yoon, Seok-Jun, You, Yuyi, Younis, Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Yuh, Faith H, Zadey, Siddhesh, Zadnik, Vesna, Zafari, Nima, Zakham, Fathiah, Zaki, Nazar, Zaman, Sojib Bin, Zamora, Nelson, Zand, Ramin, Zangiabadian, Moein, Zar, Heather J, Zare, Iman, Zarrintan, Armin, Zeariya, Mohammed G M, Zeinali, Zahra, Zhang, Haijun, Zhang, Jianrong, Zhang, Jingya, Zhang, Liqun, Zhang, Yunquan, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhong, Chenwen, Zhou, Juexiao, Zhu, Bin, Zhu, Lei, Ziafati, Makan, Zielińska, Magdalena, Zitoun, Osama A, Zoladl, Mohammad, Zou, Zhiyong, Zuhlke, Liesl J, Zumla, Alimuddin, Zweck, Elric, Zyoud, Samer H, Wool, Eve E, and Murray, Christopher J L
Abstract: 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.
Published: 2024
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27. The burden of mental disorders, substance use disorders and self-harm among young people in Europe, 1990–2019: Findings from the Global Burden of Disease Study 2019

Author: Castelpietra, G, Knudsen, A, Agardh, E, Armocida, B, Beghi, M, Iburg, K, Logroscino, G, Ma, R, Starace, F, Steel, N, Addolorato, G, Andrei, C, Andrei, T, Ayuso-Mateos, J, Banach, M, Barnighausen, T, Barone-Adesi, F, Bhagavathula, A, Carvalho, F, Carvalho, M, Chandan, J, Chattu, V, Couto, R, Cruz-Martins, N, Dargan, P, Deuba, K, da Silva, D, Fagbamigbe, A, Fernandes, E, Ferrara, P, Fischer, F, Gaal, P, Gialluisi, A, Haagsma, J, Haro, J, Hasan, M, Hasan, S, Hostiuc, S, Iacoviello, L, Iavicoli, I, Jamshidi, E, Jonas, J, Joo, T, Jozwiak, J, Katikireddi, S, Kauppila, J, Khan, M, Kisa, A, Kisa, S, Kivimaki, M, Koly, K, Koyanagi, A, Kumar, M, Lallukka, T, Langguth, B, Ledda, C, Lee, P, Lega, I, Linehan, C, Loureiro, J, Madureira-Carvalho, A, Martinez-Raga, J, Mathur, M, Mcgrath, J, Mechili, E, Mentis, A, Mestrovic, T, Miazgowski, B, Mirica, A, Mirijello, A, Moazen, B, Mohammed, S, Mulita, F, Nagel, G, Negoi, I, Negoi, R, Nwatah, V, Padron-Monedero, A, Panda-Jonas, S, Pardhan, S, Pasovic, M, Patel, J, Petcu, I, Pinheiro, M, Pollok, R, Postma, M, Rawaf, D, Rawaf, S, Romero-Rodriguez, E, Ronfani, L, Sagoe, D, Sanmarchi, F, Schaub, M, Sharew, N, Shiri, R, Shokraneh, F, Sigfusdottir, I, Silva, J, Silva, R, Socea, B, Szocska, M, Tabares-Seisdedos, R, Torrado, M, Tovani-Palone, M, Vasankari, T, Veroux, M, Viner, R, Werdecker, A, Winkler, A, Hay, S, Ferrari, A, Naghavi, M, Allebeck, P, Monasta, L, Castelpietra G., Knudsen A. K. S., Agardh E. E., Armocida B., Beghi M., Iburg K. M., Logroscino G., Ma R., Starace F., Steel N., Addolorato G., Andrei C. L., Andrei T., Ayuso-Mateos J. L., Banach M., Barnighausen T. W., Barone-Adesi F., Bhagavathula A. S., Carvalho F., Carvalho M., Chandan J. S., Chattu V. K., Couto R. A. S., Cruz-Martins N., Dargan P. I., Deuba K., da Silva D. D., Fagbamigbe A. F., Fernandes E., Ferrara P., Fischer F., Gaal P. A., Gialluisi A., Haagsma J. A., Haro J. M., Hasan M. T., Hasan S. S., Hostiuc S., Iacoviello L., Iavicoli I., Jamshidi E., Jonas J. B., Joo T., Jozwiak J. J., Katikireddi S. V., Kauppila J. H., Khan M. A. B., Kisa A., Kisa S., Kivimaki M., Koly K. N., Koyanagi A., Kumar M., Lallukka T., Langguth B., Ledda C., Lee P. H., Lega I., Linehan C., Loureiro J. A., Madureira-Carvalho A. M., Martinez-Raga J., Mathur M. R., McGrath J. J., Mechili E. A., Mentis A. -F. A., Mestrovic T., Miazgowski B., Mirica A., Mirijello A., Moazen B., Mohammed S., Mulita F., Nagel G., Negoi I., Negoi R. I., Nwatah V. E., Padron-Monedero A., Panda-Jonas S., Pardhan S., Pasovic M., Patel J., Petcu I. -R., Pinheiro M., Pollok R. C. G., Postma M. J., Rawaf D. L., Rawaf S., Romero-Rodriguez E., Ronfani L., Sagoe D., Sanmarchi F., Schaub M. P., Sharew N. T., Shiri R., Shokraneh F., Sigfusdottir I. D., Silva J. P., Silva R., Socea B., Szocska M., Tabares-Seisdedos R., Torrado M., Tovani-Palone M. R., Vasankari T. J., Veroux M., Viner R. M., Werdecker A., Winkler A. S., Hay S. I., Ferrari A. J., Naghavi M., Allebeck P., Monasta L., Castelpietra, G, Knudsen, A, Agardh, E, Armocida, B, Beghi, M, Iburg, K, Logroscino, G, Ma, R, Starace, F, Steel, N, Addolorato, G, Andrei, C, Andrei, T, Ayuso-Mateos, J, Banach, M, Barnighausen, T, Barone-Adesi, F, Bhagavathula, A, Carvalho, F, Carvalho, M, Chandan, J, Chattu, V, Couto, R, Cruz-Martins, N, Dargan, P, Deuba, K, da Silva, D, Fagbamigbe, A, Fernandes, E, Ferrara, P, Fischer, F, Gaal, P, Gialluisi, A, Haagsma, J, Haro, J, Hasan, M, Hasan, S, Hostiuc, S, Iacoviello, L, Iavicoli, I, Jamshidi, E, Jonas, J, Joo, T, Jozwiak, J, Katikireddi, S, Kauppila, J, Khan, M, Kisa, A, Kisa, S, Kivimaki, M, Koly, K, Koyanagi, A, Kumar, M, Lallukka, T, Langguth, B, Ledda, C, Lee, P, Lega, I, Linehan, C, Loureiro, J, Madureira-Carvalho, A, Martinez-Raga, J, Mathur, M, Mcgrath, J, Mechili, E, Mentis, A, Mestrovic, T, Miazgowski, B, Mirica, A, Mirijello, A, Moazen, B, Mohammed, S, Mulita, F, Nagel, G, Negoi, I, Negoi, R, Nwatah, V, Padron-Monedero, A, Panda-Jonas, S, Pardhan, S, Pasovic, M, Patel, J, Petcu, I, Pinheiro, M, Pollok, R, Postma, M, Rawaf, D, Rawaf, S, Romero-Rodriguez, E, Ronfani, L, Sagoe, D, Sanmarchi, F, Schaub, M, Sharew, N, Shiri, R, Shokraneh, F, Sigfusdottir, I, Silva, J, Silva, R, Socea, B, Szocska, M, Tabares-Seisdedos, R, Torrado, M, Tovani-Palone, M, Vasankari, T, Veroux, M, Viner, R, Werdecker, A, Winkler, A, Hay, S, Ferrari, A, Naghavi, M, Allebeck, P, Monasta, L, Castelpietra G., Knudsen A. K. S., Agardh E. E., Armocida B., Beghi M., Iburg K. M., Logroscino G., Ma R., Starace F., Steel N., Addolorato G., Andrei C. L., Andrei T., Ayuso-Mateos J. L., Banach M., Barnighausen T. W., Barone-Adesi F., Bhagavathula A. S., Carvalho F., Carvalho M., Chandan J. S., Chattu V. K., Couto R. A. S., Cruz-Martins N., Dargan P. I., Deuba K., da Silva D. D., Fagbamigbe A. F., Fernandes E., Ferrara P., Fischer F., Gaal P. A., Gialluisi A., Haagsma J. A., Haro J. M., Hasan M. T., Hasan S. S., Hostiuc S., Iacoviello L., Iavicoli I., Jamshidi E., Jonas J. B., Joo T., Jozwiak J. J., Katikireddi S. V., Kauppila J. H., Khan M. A. B., Kisa A., Kisa S., Kivimaki M., Koly K. N., Koyanagi A., Kumar M., Lallukka T., Langguth B., Ledda C., Lee P. H., Lega I., Linehan C., Loureiro J. A., Madureira-Carvalho A. M., Martinez-Raga J., Mathur M. R., McGrath J. J., Mechili E. A., Mentis A. -F. A., Mestrovic T., Miazgowski B., Mirica A., Mirijello A., Moazen B., Mohammed S., Mulita F., Nagel G., Negoi I., Negoi R. I., Nwatah V. E., Padron-Monedero A., Panda-Jonas S., Pardhan S., Pasovic M., Patel J., Petcu I. -R., Pinheiro M., Pollok R. C. G., Postma M. J., Rawaf D. L., Rawaf S., Romero-Rodriguez E., Ronfani L., Sagoe D., Sanmarchi F., Schaub M. P., Sharew N. T., Shiri R., Shokraneh F., Sigfusdottir I. D., Silva J. P., Silva R., Socea B., Szocska M., Tabares-Seisdedos R., Torrado M., Tovani-Palone M. R., Vasankari T. J., Veroux M., Viner R. M., Werdecker A., Winkler A. S., Hay S. I., Ferrari A. J., Naghavi M., Allebeck P., and Monasta L.
Abstract: Background: Mental health is a public health issue for European young people, with great heterogeneity in resource allocation. Representative population-based studies are needed. The Global Burden of Disease (GBD) Study 2019 provides internationally comparable information on trends in the health status of populations and changes in the leading causes of disease burden over time. Methods: Prevalence, incidence, Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) from mental disorders (MDs), substance use disorders (SUDs) and self-harm were estimated for young people aged 10-24 years in 31 European countries. Rates per 100,000 population, percentage changes in 1990-2019, 95% Uncertainty Intervals (UIs), and correlations with Sociodemographic Index (SDI), were estimated. Findings: In 2019, rates per 100,000 population were 16,983 (95% UI 12,823 – 21,630) for MDs, 3,891 (3,020 - 4,905) for SUDs, and 89·1 (63·8 - 123·1) for self-harm. In terms of disability, anxiety contributed to 647·3 (432–912·3) YLDs, while in terms of premature death, self-harm contributed to 319·6 (248·9–412·8) YLLs, per 100,000 population. Over the 30 years studied, YLDs increased in eating disorders (14·9%;9·4-20·1) and drug use disorders (16·9%;8·9-26·3), and decreased in idiopathic developmental intellectual disability (–29·1%;23·8-38·5). YLLs decreased in self-harm (–27·9%;38·3-18·7). Variations were found by sex, age-group and country. The burden of SUDs and self-harm was higher in countries with lower SDI, MDs were associated with SUDs. Interpretation: Mental health conditions represent an important burden among young people living in Europe. National policies should strengthen mental health, with a specific focus on young people.
Published: 2022

28. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Author: Ferrari, AJ, Santomauro, DF, Herrera, AMM, Shadid, J, Ashbaugh, C, Erskine, HE, Charlson, FJ, Degenhardt, L, Scott, JG, McGrath, JJ, Allebeck, P, Benjet, C, Breitborde, NJK, Brugha, T, Dai, X, Dandona, L, Dandona, R, Fischer, F, Haagsma, JA, Maria Haro, J, Kieling, C, Knudsen, AKS, Kumar, GA, Leung, J, Majeed, A, Mitchell, PB, Moitra, M, Mokdad, AH, Molokhia, M, Patten, SB, Patton, GC, Phillips, MR, Soriano, JB, Stein, DJ, Stein, MB, Szoeke, CE, Naghavi, M, Hay, S, Murray, CJL, Vos, T, and Whiteford, HA
Subjects: Adult, Male, Adolescent, Substance-Related Disorders, Mental Disorders, Disability-Adjusted Life Years, Infant, Articles, Middle Aged, Global Health, Severity of Illness Index, Global Burden of Disease, Psychiatry and Mental health, Epidemiologic Studies, Young Adult, Age Distribution, Risk Factors, Child, Preschool, Prevalence, Humans, Female, Child, Biological Psychiatry, Aged
Abstract: Summary Background The mental disorders included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 were depressive disorders, anxiety disorders, bipolar disorder, schizophrenia, autism spectrum disorders, conduct disorder, attention-deficit hyperactivity disorder, eating disorders, idiopathic developmental intellectual disability, and a residual category of other mental disorders. We aimed to measure the global, regional, and national prevalence, disability-adjusted life-years (DALYS), years lived with disability (YLDs), and years of life lost (YLLs) for mental disorders from 1990 to 2019. Methods In this study, we assessed prevalence and burden estimates from GBD 2019 for 12 mental disorders, males and females, 23 age groups, 204 countries and territories, between 1990 and 2019. DALYs were estimated as the sum of YLDs and YLLs to premature mortality. We systematically reviewed PsycINFO, Embase, PubMed, and the Global Health Data Exchange to obtain data on prevalence, incidence, remission, duration, severity, and excess mortality for each mental disorder. These data informed a Bayesian meta-regression analysis to estimate prevalence by disorder, age, sex, year, and location. Prevalence was multiplied by corresponding disability weights to estimate YLDs. Cause-specific deaths were compiled from mortality surveillance databases. The Cause of Death Ensemble modelling strategy was used to estimate death rate by age, sex, year, and location. The death rates were multiplied by the years of life expected to be remaining at death based on a normative life expectancy to estimate YLLs. Deaths and YLLs could be calculated only for anorexia nervosa and bulimia nervosa, since these were the only mental disorders identified as underlying causes of death in GBD 2019. Findings Between 1990 and 2019, the global number of DALYs due to mental disorders increased from 80·8 million (95% uncertainty interval [UI] 59·5–105·9) to 125·3 million (93·0–163·2), and the proportion of global DALYs attributed to mental disorders increased from 3·1% (95% UI 2·4–3·9) to 4·9% (3·9–6·1). Age-standardised DALY rates remained largely consistent between 1990 (1581·2 DALYs [1170·9–2061·4] per 100 000 people) and 2019 (1566·2 DALYs [1160·1–2042·8] per 100 000 people). YLDs contributed to most of the mental disorder burden, with 125·3 million YLDs (95% UI 93·0–163·2; 14·6% [12·2–16·8] of global YLDs) in 2019 attributable to mental disorders. Eating disorders accounted for 17 361·5 YLLs (95% UI 15 518·5–21 459·8). Globally, the age-standardised DALY rate for mental disorders was 1426·5 (95% UI 1056·4–1869·5) per 100 000 population among males and 1703·3 (1261·5–2237·8) per 100 000 population among females. Age-standardised DALY rates were highest in Australasia, Tropical Latin America, and high-income North America. Interpretation GBD 2019 showed that mental disorders remained among the top ten leading causes of burden worldwide, with no evidence of global reduction in the burden since 1990. The estimated YLLs for mental disorders were extremely low and do not reflect premature mortality in individuals with mental disorders. Research to establish causal pathways between mental disorders and other fatal health outcomes is recommended so that this may be addressed within the GBD study. To reduce the burden of mental disorders, coordinated delivery of effective prevention and treatment programmes by governments and the global health community is imperative. Funding Bill & Melinda Gates Foundation, Australian National Health and Medical Research Council, Queensland Department of Health, Australia.
Published: 2022

29. 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

Author: Abbafati, C., Machado, D.B., Cislaghi, B., Salman, O.M., Karanikolos, M., McKee, M., Abbas, K.M., Brady, O.J., Larson, H.J., Trias-Llimós, S., Cummins, S., Langan, S.M., Sartorius, B., Hafiz, A., Jenabi, E., Mohammad Gholi Mezerji, N., Borzouei, S., Azarian, G., Khazaei, S., Abbasi, M., Asghari, B., Masoumi, S., Komaki, H., Taherkhani, A., Adabi, M., Abbasifard, M., Bazmandegan, G., Kamiab, Z., Vakilian, A., Anjomshoa, M., Mokari, A., Sabour, S., Shahbaz, M., Saeedi, R., Ahmadieh, H., Yousefinezhadi, T., Haj-Mirzaian, A., Nikbakhsh, R., Safi, S., Asgari, S., Irvani, S.N., Jahanmehr, N., Ramezanzadeh, K., Abbasi-Kangevari, M., Khayamzadeh, M., Abbastabar, H., Shirkoohi, R., Fazlzadeh, M., Janjani, H., Hosseini, M., Mansournia, M., Tohidinik, H., Bakhtiari, A., Fazaeli, A., Mousavi, S., Hasanzadeh, A., Nabavizadeh, B., Malekzadeh, R., Hashemian, M., Pourshams, A., Salimzadeh, H., Sepanlou, S.G., Afarideh, M., Esteghamati, A., Esteghamati, S., Ghajar, A., Heidari, B., Rezaei, N., Mohamadi, E., Rahimi-Movaghar, A., Rahim, F., Eskandarieh, S., Sahraian, M., Mohebi, F., Aminorroaya, A., Ebrahimi, H., Farzadfar, F., Mohajer, B., Pishgar, F., Saeedi Moghaddam, S., Shabani, M., Zarafshan, H., Abolhassani, H., Hafezi-Nejad, N., Heidari-Soureshjani, R., Abdollahi, M., Farahmand, M., Salamati, P., Mehrabi Nasab, E., Tajdini, M., Aghamir, S., Mirzaei, R., Dibaji Forooshani, Z., Khater, M.M., Abd-Allah, F., Abdelalim, A., Abualhasan, A., El-Jaafary, S.I., Hassan, A., Elsharkawy, A., Khater, A.M., Elhabashy, H.R., Salem, M.R.R., Salem, H., Sadeghi, M., Jafarinia, M., Amini-Rarani, M., Mohammadifard, N., Sarrafzadegan, N., Abdollahpour, I., Sarveazad, A., Tehrani-Banihashemi, A., Yoosefi Lebni, J., Manafi, N., Pazoki Toroudi, H., Dorostkar, F., Alipour, V., Sheikhtaheri, A., Arabloo, J., Azari, S., Ghashghaee, A., Rezapour, A., Naserbakht, M., Kabir, A., Mehri, F., Yousefifard, M., Asadi-Aliabadi, M., Babaee, E., Eshrati, B., Goharinezhad, S., Moradi-Lakeh, M., Abedi, P., Rashedi, V., Kumar, V., Elgendy, I.Y., Basu, S., Park, J., Pereira, A., Norheim, O.F., Eagan, A.W., Cahill, L.E., Sheikh, A., Abushouk, A.I., Kraemer, M.U.G., Thakur, B., Bärnighausen, T.W., Shrime, M.G., Abedi, A., Doshi, C.P., Abegaz, K.H., Geberemariyam, B.S., Aynalem, Y.A., Shiferaw, W.S., Abosetugn, A.E., Aboyans, V., Abrams, E.M., Gitimoghaddam, M., Kissoon, N., Stubbs, J.L., Brauer, M., Iyamu, I.O., Kopec, J.A., Pourmalek, F., Ribeiro, A.P., Malta, D.C., Gomez, R.S., Abreu, L.G., Abrigo, M.R.M., Almulhim, A.M., Dahlawi, S.M.A., Pottoo, F.H., Menezes, R.G., Alanzi, T.M., Alumran, A.K., Abu Haimed, A.K., Madadin, M., Alanezi, F.M., Abu-Gharbieh, E., Saddik, B., Abu-Raddad, L.J., Samy, A.M., El Nahas, N., Shalash, A.S., Nabhan, A.F., Kamath, A.M., Kassebaum, N.J., Aravkin, A.Y., Kochhar, S., Sorensen, R.J.D., Afshin, A., Burkart, K., Cromwell, E.A., Dandona, L., Dharmaratne, S.D., Gakidou, E., Hay, S.I., Kyu, H.H., Lopez, A.D., Lozano, R., Misganaw, A.T., Mokdad, A.H., Naghavi, M., Pigott, D.M., Reiner Jr, R.C., Roth, G.A., Stanaway, J.D., Vollset, S., Vos, T., Wang, H., Lim, S.S., Murray, C.J.L., Kalani, R., Ikuta, K.S., Cho, D.Y., Kneib, C.J., Crowe, C.S., Massenburg, B.B., Morrison, S.D., Acebedo, A., Adelson, J.D., Agesa, K.M., Alam, T., Albertson, S.B., Anderson, J.A., Antony, C.M., Ashbaugh, C., Assmus, M., Azhar, G., Balassyano, S., Bannick, M.S., Barthelemy, C.M., Bender, R.G., Bennitt, F.B., Bertolacci, G.J., Biehl, M.H., Bisignano, C., Boon-Dooley, A.S., Briant, P.S., Bryazka, D., Bumgarner, B.R., Callender, C.S., Cao, J., Castle, C.D., Castro, E., Causey, K., Cercy, K.M., Chalek, J., Charlson, F.J., Cohen, A.J., Comfort, H., Compton, K., Croneberger, A.J., Cruz, J.A., Cunningham, M., Dandona, R., Dangel, W.J., Dean, F.E., DeCleene, N.K., Deen, A., Degenhardt, L., Dingels, Z.V., Dippenaar, I.N., Dirac, M.A., Dolgert, A.J., Emmons-Bell, S., Estep, K., Farag, T., Feigin, V.L., Feldman, R., Ferrara, G., Ferrari, A.J., Fitzgerald, R., Force, L.M., Fox, 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Maria, Borzouei, Shiva, Brady, Oliver J, Braithwaite, Dejana, Brauer, Michael, Briko, Andrey Nikolaevich, Briko, Nikolay Ivanovich, Bumgarner, Blair R, Burugina Nagaraja, Sharath, Butt, Zahid A, Caetano dos Santos, Florentino Luciano, Cai, Tianji, Callender, Charlton SKH, Cámera, Luis LA Alberto, Campos-Nonato, Ismael R, Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J, Carvalho, Felix, Castaldelli-Maia, Joao Mauricio, Castelpietra, Giulio, Castro, Franz, Catalá-López, Ferrán, Cederroth, Christopher R, Cerin, Ester, Chattu, Vijay Kumar, Chin, Ken Lee, Chu, Dinh-Toi, Ciobanu, Liliana G, Cirillo, Massimo, Comfort, Haley, Costa, Vera Marisa, Cowden, Richard G, Cromwell, Elizabeth A, Croneberger, Andrew J, Cunningham, Matthew, Dahlawi, Saad M A, Damiani, Giovanni, D'Amico, Emanuele, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, Darwesh, Aso Mohammad, Daryani, Ahmad, Das Gupta, Rajat, das Neves, José, Davletov, Kairat, De Leo, Diego, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolao, Desai, Rupak, Dhungana, Govinda Prasad, Dias da Silva, Diana, Diaz, Daniel, Dippenaar, Ilse N, Djalalinia, Shirin, Do, Hoa Thi, Dokova, Klara, Doku, David Teye, Dorostkar, Fariba, Doshi, Chirag P, Doshmangir, Leila, Doyle, Kerrie E, Dubljanin, Eleonora, Duraes, Andre Rodrigue, Edvardsson, David, Effiong, Andem, El Sayed, Iman, El Tantawi, Maha, Elbarazi, Iffat, El-Jaafary, Shaimaa I, Emamian, Mohammad Hassan, Eskandarieh, Sharareh, Esmaeilzadeh, Firooz, Estep, Kara, Farahmand, Mohammad, Faraj, Anwar, Fareed, Mohammad, Faridnia, Roghiyeh, Faro, Andre, Farzadfar, Farshad, Fattahi, Nazir, Fazaeli, Ali Akbar, Fazlzadeh, Mehdi, Feigin, Valery L, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Ferreira, Manuela L, Filip, Irina, Fischer, Florian, Flohr, Carsten, Foigt, Nataliya A, Folayan, Morenike Oluwatoyin, Fomenkov, Artem Alekseevich, Freitas, Marisa, Fukumoto, Takeshi, Fuller, John E, Furtado, João M, Gad, Mohamed M, Gakidou, Emmanuela, Gallus, Silvano, Gebrehiwot, Abiyu Mekonnen, Gebremedhin, Ketema Bizuwork, Gething, Peter W, Ghamari, Farhad, Ghashghaee, Ahmad, Gholamian, Asadollah, Gilani, Syed Amir, Gitimoghaddam, Mojgan, Glushkova, Ekaterina Vladimirovna, Gnedovskaya, Elena V, Gopalani, Sameer Vali, Goulart, Alessandra C, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rajeev, Gupta, Subodh Sharan, Haagsma, Juanita A, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Halvaei, Iman, Hamadeh, Randah R, Hamagharib Abdullah, Kanaan, Han, Chieh, Handiso, Demelash Woldeyohanne, Hankey, Graeme J, Haririan, Hamidreza, Haro, Josep Maria, Hasaballah, Ahmed I, Hassanipour, Soheil, Hassankhani, Hadi, Hay, Simon I, Heibati, Behzad, Heidari-Soureshjani, Reza, Henny, Kiana, Henry, Nathaniel J, Herteliu, Claudiu, Heydarpour, Fatemeh, Hole, Michael K, Hoogar, Praveen, Hosgood, H Dean, Hossain, Naznin, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Househ, Mowafa, Hoy, Damian G, Hu, Guoqing, Huda, Tanvir M, Ibitoye, Segun Emmanuel, Ikuta, Kevin S, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Imani-Nasab, Mohammad Hasan, Islam, Mdmohaimenul, Iso, Hiroyasu, Iwu, Chinwe Juliana, Jaafari, Jalil, Jacobsen, Kathryn H, Jahagirdar, Deepa, Jahanmehr, Nader, Jalali, Amir, Jalilian, Farzad, James, Spencer L, Janjani, Hosna, Jenabi, Ensiyeh, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Jonas, Jost B, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Zubair, Kalani, Hamed, Kalankesh, Leila R, Kamiab, Zahra, Kanchan, Tanuj, Kapoor, Neeti, Karch, André, Karimi, Salah Eddin, Karimi, Seyed Asaad, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kawakami, Norito, Kayode, Gbenga A, Keiyoro, Peter Njenga, Keller, Cathleen, Khader, Yousef Saleh, Khalid, Nauman, Khan, Ejaz Ahmad, Khan, Maseer, Khang, Young-Ho, Khater, Amir M, Khater, Mona M, Khazaei, Salman, Khazaie, Habibolah, Khodayari, Mohammad Taghi, Khubchandani, Jagdish, Kianipour, Neda, Kim, Cho-il, Kim, Young-Eun, Kim, Yun Jin, Kinfu, Yohanne, Kisa, Adnan, Kisa, Sezer, Kissimova-Skarbek, Katarzyna, Kivimäki, Mika, Komaki, Hamidreza, Kopec, Jacek A, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kris J, Kuate Defo, Barthelemy, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kumar, Vivek, Kusuma, Dian, Kyu, Hmwe Hmwe, La Vecchia, Carlo, Lacey, Ben, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lami, Faris Hasan, Lansky, Sonia, Larson, Samantha Leigh, Larsson, Anders O, Lasrado, Savita, Lassi, Zohra S, Lazarus, Jeffrey V, Lee, Paul H, Lee, Shaun Wen Huey, Leever, Andrew T, Legrand, Kate E, Leonardi, Matilde, Li, Shanshan, Lim, Lee-Ling, Lim, Stephen S, Linn, Shai, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lopukhov, Platon D, Lotufo, Paulo A, Lozano, Rafael, Lu, Alton, Lunevicius, Raimunda, Madadin, Mohammed, Maddison, Emilie R, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Muhammed, Mahasha, Phetole Walter, Mahdavi, Mokhtar Mahdavi, Malekzadeh, Reza, Mamun, Abdullah A, Manafi, Navid, Mansour-Ghanaei, Fariborz, Mansouri, Borhan, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Martini, Santi, Martins-Melo, Francisco Rogerlândio, Masaka, Anthony, Mastrogiacomo, Claudia I, Mathur, Manu Raj, May, Erin A, Mcalinden, Colm, Mcgrath, John J, Mckee, Martin, Mehndiratta, Man Mohan, Mehri, Fereshteh, Mehta, Kala M, Meitei, Wahengbam Bigyananda, Memiah, Peter T N, Mendoza, Walter, Menezes, Ritesh G, Mengesha, Endalkachew Worku, Mensah, George A, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Michalek, Irmina Maria, Mihretie, Kebadnew Mulatu, Miller, Ted R, Mills, Edward J, Milne, George J, Mirrakhimov, Erkin M, Mirzaei, Hamed, Mirzaei, Maryam, Mirzaei-Alavijeh, Mehdi, Misganaw, Awoke Temesgen, Moazen, Babak, Moghadaszadeh, Masoud, Mohamadi, Efat, Mohammad, Dara K, Mohammad, Yousef, Mohammad Gholi Mezerji, Naser, Mohammadbeigi, Abolfazl, Mohammadian-Hafshejani, Abdollah, Mohammadpourhodki, Reza, Mohammed, Hussen, Mohammed, Shafiu, Mohebi, Farnam, Mohseni Bandpei, Mohammad A, Mokari, Amin, Mokdad, Ali H, Momen, Natalie C, Monasta, Lorenzo, Mooney, Meghan D, Moradi, Ghobad, Moradi, Masoud, Moradi-Joo, Mohammad, Moradi-Lakeh, Maziar, Moradzadeh, Rahmatollah, Moraga, Paula, Moreno Velásquez, Ilai, Morgado-da-Costa, Joana, Morrison, Shane Dougla, Mosser, Jonathan F, Mouodi, Simin, Mousavi, Seyyed Meysam, Mousavi Khaneghah, Amin, Mueller, Ulrich Otto, Musa, Kamarul Imran, Muthupandian, Saravanan, Nabavizadeh, Behnam, Naderi, Mehdi, Nagarajan, Ahamarshan Jayaraman, Naghavi, Mohsen, Naghshtabrizi, Behshad, Naik, Gurudatta, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Ndwandwe, Duduzile Edith, Negoi, Ionut, Negoi, Ruxandra Irina, Ngunjiri, Josephine W, Nguyen, Huong Lan Thi, Nguyen, Trang Huyen, Nigatu, Yeshambel T, Nikbakhsh, Rajan, Nikpoor, Amin Reza, Nixon, Molly R, Nnaji, Chukwudi A, Nomura, Shuhei, Noubiap, Jean Jacque, Nouraei Motlagh, Soraya, Nowak, Christoph, Oţoiu, Adrian, Odell, Christopher M, Oh, In-Hwan, Oladnabi, Morteza, Olagunju, Andrew T, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Omar Bali, Ahmed, Ong, Kanyin L, Onwujekwe, Obinna E, Ortiz, Alberto, Otstavnov, Nikita, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa O, P A, Mahesh, Padubidri, Jagadish Rao, Pakshir, Keyvan, Palladino, Raffaele, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Jame, Pasupula, Deepak Kumar, Patel, Jenil R, Patel, Sangram Kishor, Patton, George C, Paulson, Katherine R, Pazoki Toroudi, Hamidreza, Pease, Spencer A, Peden, Amy E, Pepito, Veincent Christian Filipino, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pigott, David M, Pilgrim, Thoma, Pilz, Tessa M, Piradov, Michael A, Pirsaheb, Meghdad, Pokhrel, Khem Narayan, Postma, Maarten J, Pourjafar, Hadi, Pourmalek, Farshad, Pourshams, Akram, Poznańska, Anna, Prada, Sergio I, Prakash, Sanjay, Preotescu, Liliana, Quazi Syed, Zahiruddin, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Rafiei, Alireza, Raggi, Alberto, Rahman, Muhammad Aziz, Rajabpour-Sanati, Ali, Ram, Pradhum, Ranabhat, Chhabi Lal, Rao, Sowmya J, Rasella, Davide, Rashedi, Vahid, Rastogi, Prateek, Rathi, Priya, Rawal, Lal, Remuzzi, Giuseppe, Renjith, Vishnu, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Nima, Rezai, Mohammad sadegh, Rezapour, Aziz, Rickard, Jennifer, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostamian, Morteza, Rubagotti, Enrico, Rwegerera, Godfrey M, Sabour, Siamak, Saddik, Basema, Sadeghi, Ehsan, Sadeghi, Masoumeh, Saeedi Moghaddam, Sahar, Safari, Yahya, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, S Mohammad, Salahshoor, Mohammad Reza, Salama, Joseph S, Salamati, Payman, Salem, Marwa R Rashad, Salimi, Yahya, Salomon, Joshua A, Salz, Inbal, Samad, Zainab, Samy, Abdallah M, Sanabria, Juan, Santric-Milicevic, Milena M, Saraswathy, Sivan Yegnanarayana Iyer, Sartorius, Benn, Sarveazad, Arash, Sathian, Brijesh, Sathish, Thirunavukkarasu, Sattin, Davide, Saylan, Mete, Schaeffer, Lauren E, Schiavolin, Silvia, Schwebel, David C, Schwendicke, Falk, Sekerija, Mario, Senbeta, Anbissa Muleta, Senthilkumaran, Subramanian, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabani, Mahsima, Shahabi, Saeed, Shahbaz, Mohammad, Shaheen, Amira A, Shaikh, Masood Ali, Shalash, Ali S, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Shamsizadeh, Morteza, Shannawaz, Mohammed, Sharafi, Kiomar, Sharafi, Zeinab, Sharara, Fablina, Sharma, Rajesh, Shaw, David H, Sheikh, Aziz, Shin, Jae Il, Shiri, Rahman, Shrime, Mark G, Shuval, Kerem, Siabani, Soraya, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Simonetti, Biagio, Simpson, Kyle E, Singh, Jasvinder A, Skiadaresi, Eirini, Skryabin, Valentin Yurievich, Soheili, Amin, Sokhan, Anton, Sorensen, Reed J D, Soriano, Joan B, Sorrie, Muluken Bekele, Soyiri, Ireneous N, Spurlock, Emma Elizabeth, Sreeramareddy, Chandrashekhar T, Stockfelt, Leo, Stokes, Mark A, Stubbs, Jacob L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Suliankatchi Abdulkader, Rizwan, Sykes, Bryan L, Tabarés-Seisdedos, Rafael, Tabb, Karen M, Tadakamadla, Santosh Kumar, Taherkhani, Amir, Tang, Muming, Taveira, Nuno, Taylor, Heather Jean, Teagle, Whitney L, Tehrani-Banihashemi, Arash, Teklehaimanot, Berhane Fseha, Tessema, Zemenu Tadesse, Thankappan, Kavumpurathu Raman, Thomas, Nihal, Thrift, Amanda G, Titova, Mariya Vladimirovna, Tohidinik, Hamid Reza, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Tovani-Palone, Marcos Roberto Roberto, Traini, Eugenio, Tran, Bach Xuan, Travillian, Ravensara, Trias-Llimós, Sergi, Truelsen, Thomas Clement, Tudor Car, Lorainne, Unnikrishnan, Bhaskaran, Upadhyay, Era, Vacante, Marco, Vakilian, Alireza, Valdez, Pascual R, Valli, Alessandro, Vardavas, Constantine, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Vasseghian, Yasser, Veisani, Yousef, Venketasubramanian, Narayanaswamy, Vidale, Simone, Violante, Francesco S, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vujcic, Isidora S, Vukovic, Ana, Vukovic, Rade, Waheed, Yasir, Wallin, Mitchell Taylor, Walters, Magdalene K, Wang, Hongbo, Wang, Yuan-Pang, Watson, Stefanie, Wei, Jingkai, Weiss, Jordan, Weldesamuel, Girmay Teklay, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Wiangkham, Taweewat, Wiens, Kirsten E, Wijeratne, Tissa, Wiysonge, Charles Shey, Wojtyniak, Bogdan, Wolfe, Charles D A, Wondmieneh, Adam Belay, Wool, Eve E, Wu, Ai-Min, Wu, Junjie, Xu, Gelin, Yamada, Tomohide, Yamagishi, Kazumasa, Yano, Yuichiro, Yaya, Sanni, Yazdi-Feyzabadi, Vahid, Yearwood, Jamal A, Yeheyis, Tomas Y, Yilgwan, Christopher Sabo, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yoosefi Lebni, Javad, York, Hunter W, Younis, Mustafa Z, Younker, Theodore Patrick, Yousefi, Zabihollah, Yousefinezhadi, Taraneh, Yousuf, Abdilahi Yousuf, Yusefzadeh, Hasan, Zahirian Moghadam, Telma, Zakzuk, Josefina, Zaman, Sojib Bin, Zamani, Mohammad, Zamanian, Maryam, Zandian, Hamed, Zhang, Zhi-Jiang, Zheng, Peng, Zhou, Maigeng, Ziapour, Arash, Murray, Christopher J L, Collaborators, GBD 2019 Demographics, GBD 2019 Demographics Collaborator, Violante FS, Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), Department of Earth Systems Analysis, Biomechanical Engineering, TechMed Centre, Biomolecular Nanotechnology, Research Methodology, Measurement and Data Analysis, Materials Science and Technology of Polymers, Inorganic Materials Science, MESA+ Institute, Biomedical and Environmental Sensorsystems, Mesoscale Chemical Systems, Faculty of Engineering Technology, Nonlinear Solid Mechanics, Digital Society Institute, Pervasive Systems, Nanobiophysics, Faculty of Geo-Information Science and Earth Observation, Multi Scale Mechanics, Engineering Fluid Dynamics, Physics of Complex Fluids, Developmental BioEngineering, Physics of Fluids, Elastomer Technology and Engineering, Medical Cell Biophysics, European Membrane Institute, Department of Earth Observation Science, Biomaterials Science and Technology, Sustainable Process Technology, Department of Urban and Regional Planning and Geo-Information Management, Department of Natural Resources, XUV Optics, Databases (Former), Department of Water Resources, Psychology, Health & Technology, Membrane Science & Technology, Department of Public Health, Clinicum, HUS Neurocenter, HUS Comprehensive Cancer Center, and Environmental Sciences
Subjects: Male, very elderly, Demographic transition, HALE, 030204 cardiovascular system & hematology, preschool child, Global Burden of Disease, Carga Global de Enfermedades, 0302 clinical medicine, newborn, Risk Factors, Surveys and Questionnaires, and Risk Factors Study, 80 and over, 030212 general & internal medicine, Birth Rate, Child, Migration, 11 Medical and Health Sciences, Aged, 80 and over, education.field_of_study, Injuries, Geography, Mortality rate, 1. No poverty, DEATH, Censuses, General Medicine, SDG 10 - Reduced Inequalities, Middle Aged, Demographic analysis, 3142 Public health care science, environmental and occupational health, 3. Good health, demographic analysis, Estilo de Vida Saludable, risk factor, Child, Preschool, Demography/statistics & numerical data, Global Burden of Diseases, Injuries, Risk Factors, Fertility, Mortality, Migration, Population, epidemiology, Female, A990 Medicine and Dentistry not elsewhere classified, CHILD-MORTALITY, Live Birth, Global Health Metrics, TRANSITION, demographics, GBD, fertility, mortality, hale, Adult, Adolescent, Total fertility rate, Population, Global Burden of Diseases, Injuries, and Risk Factors Study, Birth rate, 03 medical and health sciences, Young Adult, Life Expectancy, SDG 3 - Good Health and Well-being, General & Internal Medicine, SYSTEMATIC ANALYSIS, Demografía, Humans, Global Burden of Disease Study, human, Mortality, education, Preschool, Aged, Demography, Spatial Analysis, questionnaire, Infant, Newborn, Klinisk medicin, HIV, Infant, Global Burden of Diseases, sex-specific fertility, Live Birth/epidemiology, purl.org/pe-repo/ocde/ford#3.02.00 [https], MODEL, Fertilidad, Fertility, Demographic change, Life expectancy, NA, global disease burden, Clinical Medicine, population research
Abstract: 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 age-specific 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. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.
Published: 2020

30. Long-term physical workload in middle age and disability pension in men and women: a follow-up study of Swedish cohorts

Author: Kjellberg, Katarina, Lundin, Andreas, Falkstedt, Daniel, Allebeck, Peter, and Hemmingsson, Tomas
Published: 2016
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31. Do working conditions explain the increased risks of disability pension among men and women with low education? A follow-up of Swedish cohorts

Author: Daniel Falkstedt, Mona Backhans, Andreas Lundin, Peter Allebeck, and Tomas Hemmingsson
Subjects: women, study ambition, cohort study, intellectual performance, psychiatric diagnosis, education, disability, job control, confounding, sweden, men, job exposure matrix, musculoskeletal diagnosis, physical strain, jem, working condition, disability pension, musculoskeletal disorder, swedish cohort, Public aspects of medicine, RA1-1270
Abstract: OBJECTIVES: Rates of disability pension are greatly increased among people with low education. This study examines the extent to which associations between education and disability pensions might be explained by differences in working conditions. Information on individuals at age 13 years was used to assess confounding of associations. METHOD: Two nationally representative samples of men and women born in 1948 and 1953 in Sweden (22 889 participants in total) were linked to information from social insurance records on cause (musculoskeletal, psychiatric, and other) and date (from 1986–2008) of disability pension. Education data were obtained from administrative records. Occupation data were used for measurement of physical strain at work and job control. Data on paternal education, ambition to study, and intellectual performance were collected in school. RESULTS: Women were found to have higher rates of disability pension than men, regardless of diagnosis, whereas men had a steeper increase in disability pension by declining educational level. Adjustment of associations for paternal education, ambition to study, and intellectual performance at age 13 had a considerable attenuating effect, also when disability pension with a musculoskeletal diagnosis was the outcome. Despite this, high physical strain at work and low job control both contributed to explain the associations between low education and disability pensions in multivariable models. CONCLUSION: Working conditions seem to partly explain the increased rate of disability pension among men and women with lower education even though this association does reflect considerable selection effects based on factors already present in late childhood.
Published: 2014
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32. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Author: Vos, T, Lim, S, Abbafati, C, Abbas, K, Abbasi, M, Abbasifard, M, Abbasi-Kangevari, M, Abbastabar, H, Abd-Allah, F, Abdelalim, A, Abdollahi, M, Abdollahpour, I, Abolhassani, H, Aboyans, V, Abrams, E, Abreu, L, Abrigo, M, Abu-Raddad, L, Abushouk, A, Acebedo, A, Ackerman, I, Adabi, M, Adamu, A, Adebayo, O, Adekanmbi, V, Adelson, J, Adetokunboh, O, Adham, D, Afshari, M, Afshin, A, Agardh, E, Agarwal, G, Agesa, K, Aghaali, M, Aghamir, S, Agrawal, A, Ahmad, T, Ahmadi, A, Ahmadi, M, Ahmadieh, H, Ahmadpour, E, Akalu, T, Akinyemi, R, Akinyemiju, T, Akombi, B, Al-Aly, Z, Alam, K, Alam, N, Alam, S, Alam, T, Alanzi, T, Albertson, S, Alcalde-Rabanal, J, Alema, N, Ali, M, Ali, S, Alicandro, G, Alijanzadeh, M, Alinia, C, Alipour, V, Aljunid, S, Alla, F, Allebeck, P, Almasi-Hashiani, A, Alonso, J, Al-Raddadi, R, Altirkawi, K, Alvis-Guzman, N, Alvis-Zakzuk, N, Amini, S, Amini-Rarani, M, Aminorroaya, A, Amiri, F, Amit, A, Amugsi, D, Amul, G, Anderlini, D, Andrei, C, Andrei, T, Anjomshoa, M, Ansari, F, Ansari, I, Ansari-Moghaddam, A, Antonio, C, Antony, C, Antriyandarti, E, Anvari, D, Anwer, R, Arabloo, J, Arab-Zozani, M, Aravkin, A, Ariani, F, Arnlov, J, Aryal, K, Arzani, A, Asadi-Aliabadi, M, Asadi-Pooya, A, Asghari, B, Ashbaugh, C, Atnafu, D, Atre, S, Ausloos, F, Ausloos, M, Ayala Quintanilla, B, Ayano, G, Ayanore, M, Aynalem, Y, Azari, S, Azarian, G, Azene, Z, Babaee, E, Badawi, A, Bagherzadeh, M, Bakhshaei, M, Bakhtiari, A, Balakrishnan, S, Balalla, S, Balassyano, S, Banach, M, Banik, P, Bannick, M, Bante, A, Baraki, A, Barboza, M, Barker-Collo, S, Barthelemy, C, Barua, L, Barzegar, A, Basu, S, Baune, B, Bayati, M, Bazmandegan, G, Bedi, N, Beghi, E, Bejot, Y, Bello, A, Bender, R, Bennett, D, Bennitt, F, Bensenor, I, Benziger, C, Berhe, K, Bernabe, E, Bertolacci, G, Bhageerathy, R, Bhala, N, Bhandari, D, Bhardwaj, P, Bhattacharyya, K, Bhutta, Z, Bibi, S, Biehl, M, Bikbov, B, Bin Sayeed, M, Biondi, A, Birihane, B, Bisanzio, D, Bisignano, C, Biswas, R, Bohlouli, S, Bohluli, M, Bolla, S, Boloor, A, Boon-Dooley, A, Borges, G, Borzi, A, Bourne, R, Brady, O, Brauer, M, Brayne, C, Breitborde, N, Brenner, H, Briant, P, Briggs, A, Briko, N, Britton, G, Bryazka, D, Buchbinder, R, Bumgarner, B, Busse, R, Butt, Z, Caetano dos Santos, F, Camera, L, Campos-Nonato, I, Car, J, Cardenas, R, Carreras, G, Carrero, J, Carvalho, F, Castaldelli-Maia, J, Castaneda-Orjuela, C, Castelpietra, G, Castle, C, Castro, F, Catala-Lopez, F, Causey, K, Cederroth, C, Cercy, K, Cerin, E, Chandan, J, Chang, A, Charlson, F, Chattu, V, Chaturvedi, S, Chimed-Ochir, O, Chin, K, Cho, D, Christensen, H, Chu, D, Chung, M, Cicuttini, F, Ciobanu, L, Cirillo, M, Collins, E, Compton, K, Conti, S, Cortesi, P, Costa, V, Cousin, E, Cowden, R, Cowie, B, Cromwell, E, Cross, D, Crowe, C, Cruz, J, Cunningham, M, Dahlawi, S, Damiani, G, Dandona, L, Dandona, R, Darwesh, A, Daryani, A, Das, J, Das Gupta, R, das Neves, J, Davila-Cervantes, C, Davletov, K, De Leo, D, Dean, F, Decleene, N, Deen, A, Degenhardt, L, Dellavalle, R, Demeke, F, Demsie, D, Denova-Gutierrez, E, Dereje, N, Dervenis, N, Desai, R, Desalew, A, Dessie, G, Dharmaratne, S, Dhungana, G, Dianatinasab, M, Diaz, D, Dibaji Forooshani, Z, Dingels, Z, Dirac, M, Djalalinia, S, Do, H, Dokova, K, Dorostkar, F, Doshi, C, Doshmangir, L, Douiri, A, Doxey, M, Driscoll, T, Dunachie, S, Duncan, B, Duraes, A, Eagan, A, Ebrahimi Kalan, M, Edvardsson, D, Ehrlich, J, El Nahas, N, El Sayed, I, El Tantawi, M, Elbarazi, I, Elgendy, I, Elhabashy, H, El-Jaafary, S, Elyazar, I, Emamian, M, Emmons-Bell, S, Erskine, H, Eshrati, B, Eskandarieh, S, Esmaeilnejad, S, Esmaeilzadeh, F, Esteghamati, A, Estep, K, Etemadi, A, Etisso, A, Farahmand, M, Faraj, A, Fareed, M, Faridnia, R, Farinha, C, Farioli, A, Faro, A, Faruque, M, Farzadfar, F, Fattahi, N, Fazlzadeh, M, Feigin, V, Feldman, R, Fereshtehnejad, S, Fernandes, E, Ferrari, A, Ferreira, M, Filip, I, Fischer, F, Fisher, J, Fitzgerald, R, Flohr, C, Flor, L, Foigt, N, Folayan, M, Force, L, Fornari, C, Foroutan, M, Fox, J, Freitas, M, Fu, W, Fukumoto, T, Furtado, J, Gad, M, Gakidou, E, Galles, N, Gallus, S, Gamkrelidze, A, Garcia-Basteiro, A, Gardner, W, Geberemariyam, B, Gebrehiwot, A, Gebremedhin, K, Gebreslassie, A, Gershberg Hayoon, A, Gething, P, Ghadimi, M, Ghadiri, K, Ghafourifard, M, Ghajar, A, Ghamari, F, Ghashghaee, A, Ghiasvand, H, Ghith, N, Gholamian, A, Gilani, S, Gill, P, Gitimoghaddam, M, Giussani, G, Goli, S, Gomez, R, Gopalani, S, Gorini, G, Gorman, T, Gottlich, H, Goudarzi, H, Goulart, A, Goulart, B, Grada, A, Grivna, M, Grosso, G, Gubari, M, Gugnani, H, Guimaraes, A, Guimaraes, R, Guled, R, Guo, G, Guo, Y, Gupta, R, Haagsma, J, Haddock, B, Hafezi-Nejad, N, Hafiz, A, Hagins, H, Haile, L, Hall, B, Halvaei, I, Hamadeh, R, Hamagharib Abdullah, K, Hamilton, E, Han, C, Han, H, Hankey, G, Haro, J, Harvey, J, Hasaballah, A, Hasanzadeh, A, Hashemian, M, Hassanipour, S, Hassankhani, H, Havmoeller, R, Hay, R, Hay, S, Hayat, K, Heidari, B, Heidari, G, 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B., Remuzzi G., Renjith V., Renzaho A. M. N., Resnikoff S., Rezaei N., Rezai M. S., Rezapour A., Rhinehart P. -A., Riahi S. M., Ribeiro A. L. P., Ribeiro D. C., Ribeiro D., Rickard J., Roberts N. L. S., Roberts S., Robinson S. R., Roever L., Rolfe S., Ronfani L., Roshandel G., Roth G. A., Rubagotti E., Rumisha S. F., Sabour S., Sachdev P. S., Saddik B., Sadeghi E., Sadeghi M., Saeidi S., Safi S., Safiri S., Sagar R., Sahebkar A., Sahraian M. A., Sajadi S. M., Salahshoor M. R., Salamati P., Salehi Zahabi S., Salem H., Salem M. R. R., Salimzadeh H., Salomon J. A., Salz I., Samad Z., Samy A. M., Sanabria J., Santomauro D. F., Santos I. S., Santos J. V., Santric-Milicevic M. M., Saraswathy S. Y. I., Sarmiento-Suarez R., Sarrafzadegan N., Sartorius B., Sarveazad A., Sathian B., Sathish T., Sattin D., Sbarra A. N., Schaeffer L. E., Schiavolin S., Schmidt M. I., Schutte A. E., Schwebel D. C., Schwendicke F., Senbeta A. M., Senthilkumaran S., Sepanlou S. G., Shackelford K. 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G., Yip P., Yonemoto N., Yoon S. -J., Yoosefi Lebni J., Younis M. Z., Younker T. P., Yousefi Z., Yousefifard M., Yousefinezhadi T., Yousuf A. Y., Yu C., Yusefzadeh H., Zahirian Moghadam T., Zaki L., Zaman S. B., Zamani M., Zamanian M., Zandian H., Zangeneh A., Zastrozhin M. S., Zewdie K. A., Zhang Y., Zhang Z. -J., Zhao J. T., Zhao Y., Zheng P., Zhou M., Ziapour A., Zimsen S. R. M., Naghavi M., and Murray C. J. L.
Abstract: Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value
Published: 2020

33. Five insights from the Global Burden of Disease Study 2019

Author: Murray, C, Abbafati, C, Abbas, K, Abbasi, M, Abbasi-Kangevari, M, Abd-Allah, F, Abdollahi, M, Abedi, P, Abedi, A, Abolhassani, H, Aboyans, V, Abreu, L, Abrigo, M, Abu-Gharbieh, E, Abu Haimed, A, Abushouk, A, Acebedo, A, Ackerman, I, Adabi, M, Adamu, A, Adebayo, O, Adelson, J, Adetokunboh, O, Afarideh, M, Afshin, A, Agarwal, G, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmadi, M, Ahmed, M, Aji, B, Akinyemiju, T, Akombi, B, Alahdab, F, Alam, K, Alanezi, F, Alanzi, T, Albertson, S, Alemu, B, Alemu, Y, Alhabib, K, Ali, M, Ali, S, Alicandro, G, Alipour, V, Alizade, H, Aljunid, S, Alla, F, Allebeck, P, Almadi, M, Almasi-Hashiani, A, Al-Mekhlafi, H, Almulhim, A, Alonso, J, Al-Raddadi, R, Altirkawi, K, Alvis-Guzman, N, Amare, B, Amare, A, Amini, S, Amit, A, Amugsi, D, Anbesu, E, Ancuceanu, R, Anderlini, D, Anderson, J, Andrei, T, Andrei, C, Anjomshoa, M, Ansari, F, Ansari-Moghaddam, A, Antonio, C, Antony, C, Anvari, D, Appiah, S, Arabloo, J, Arab-Zozani, M, Aravkin, A, Arba, A, Aripov, T, 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Abstract: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.
Published: 2020

34. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Author: Abbafati, C, Abbas, K, Abbasi-Kangevari, M, Abd-Allah, F, Abdelalim, A, Abdollahi, M, Abdollahpour, I, Abegaz, K, Abolhassani, H, Aboyans, V, Abreu, L, Abrigo, M, Abualhasan, A, Abu-Raddad, L, Abushouk, A, Adabi, M, Adekanmbi, V, Adeoye, A, Adetokunboh, O, Adham, D, Advani, S, Afshin, A, Agarwal, G, Aghamir, S, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmadi, M, Ahmadieh, H, Ahmed, M, Akalu, T, Akinyemi, R, Akinyemiju, T, Akombi, B, Akunna, C, Alahdab, F, Al-Aly, Z, Alam, K, Alam, S, Alam, T, Alanezi, F, Alanzi, T, Alemu, B, Alhabib, K, Ali, M, Ali, S, Alicandro, G, Alinia, C, Alipour, V, Alizade, H, Aljunid, S, Alla, F, Allebeck, P, Almasi-Hashiani, A, Al-Mekhlafi, H, Alonso, J, Altirkawi, K, Amini-Rarani, M, Amiri, F, Amugsi, D, Ancuceanu, R, Anderlini, D, Anderson, J, Andrei, C, Andrei, T, Angus, C, Anjomshoa, M, Ansari, F, Ansari-Moghaddam, A, Antonazzo, I, Antonio, C, Antony, C, Antriyandarti, E, Anvari, D, Anwer, R, Appiah, S, Arabloo, J, Arab-Zozani, M, Aravkin, A, Ariani, F, 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E., Leigh J., Leonardi M., Lescinsky H., Leung J., Levi M., Li S., Lim L. -L., Linn S., Liu S., Liu Y., Lo J., Lopez A. D., Lopez J. C. F., Lopukhov P. D., Lorkowski S., Lotufo P. A., Lu A., Lugo A., Maddison E. R., Mahasha P. W., Mahdavi M. M., Mahmoudi M., Majeed A., Maleki A., Maleki S., Malekzadeh R., Malta D. C., Mamun A. A., Manda A. L., Manguerra H., Mansour-Ghanaei F., Mansouri B., Mansournia M. A., Mantilla Herrera A. M., Maravilla J. C., Marks A., Martin R. V., Martini S., Martins-Melo F. R., Masaka A., Masoumi S. Z., Mathur M. R., Matsushita K., Maulik P. K., McAlinden C., McGrath J. J., McKee M., Mehndiratta M. M., Mehri F., Mehta K. M., Memish Z. A., Mendoza W., Menezes R. G., Mengesha E. W., Mereke A., Mereta S. T., Meretoja A., Meretoja T. J., Mestrovic T., Miazgowski B., Miazgowski T., Michalek I. M., Miller T. R., Mills E. J., Mini G. K., Miri M., Mirica A., Mirrakhimov E. M., Mirzaei H., Mirzaei M., Mirzaei R., Mirzaei-Alavijeh M., Misganaw A. T., Mithra P., Moazen B., Mohammad D. K., Mohammad Y., Mohammad Gholi Mezerji N., Mohammadian-Hafshejani A., Mohammadifard N., Mohammadpourhodki R., Mohammed A. S., Mohammed H., Mohammed J. A., Mohammed S., Mokdad A. H., Molokhia M., Monasta L., Mooney M. D., Moradi G., Moradi M., Moradi-Lakeh M., Moradzadeh R., Moraga P., Morawska L., Morgado-Da-Costa J., Morrison S. D., Mosapour A., Mosser J. F., Mouodi S., Mousavi S. M., Khaneghah A. M., Mueller U. O., Mukhopadhyay S., Mullany E. C., Musa K. I., Muthupandian S., Nabhan A. F., Naderi M., Nagarajan A. J., Nagel G., Naghavi M., Naghshtabrizi B., Naimzada M. D., Najafi F., Nangia V., Nansseu J. R., Naserbakht M., Nayak V. C., Negoi I., Ngunjiri J. W., Nguyen C. T., Nguyen H. L. T., Nguyen M., Nigatu Y. T., Nikbakhsh R., Nixon M. R., Nnaji C. A., Nomura S., Norrving B., Noubiap J. J., Nowak C., Nunez-Samudio V., Oancea B., Odell C. M., Ogbo F. A., Oh I. -H., Okunga E. W., Oladnabi M., Olagunju A. T., Olusanya B. O., Olusanya J. O., Omer M. O., Ong K. L., Onwujekwe O. E., Orpana H. M., Ortiz A., Osarenotor O., Osei F. B., Ostroff S. M., Otoiu A., Otstavnov N., Otstavnov S. S., Overland S., Owolabi M. O., Mahesh P. A., Padubidri J. R., Palladino R., Panda-Jonas S., Pandey A., Parry C. D. H., Pasovic M., Pasupula D. K., Patel S. K., Pathak M., Patten S. B., Patton G. C., Toroudi H. P., Peden A. E., Pennini A., Pepito V. C. F., Peprah E. K., Pereira D. M., Pesudovs K., Pham H. Q., Phillips M. R., Piccinelli C., Pilz T. M., Piradov M. A., Pirsaheb M., Plass D., Polinder S., Polkinghorne K. R., Pond C. D., Postma M. J., Pourjafar H., Pourmalek F., Poznanska A., Prada S. I., Prakash V., Pribadi D. R. A., Pupillo E., Syed Z. Q., Rabiee M., Rabiee N., Radfar A., Rafiee A., Raggi A., Rahman M. A., Rajabpour-Sanati A., Rajati F., Rakovac I., Ram P., Ramezanzadeh K., Ranabhat C. L., Rao P. C., Rao S. J., Rashedi V., Rathi P., Rawaf D. L., Rawaf S., Rawal L., Rawassizadeh R., Rawat R., Razo C., Redford S. B., Reiner R. C., Reitsma M. B., Remuzzi G., Renjith V., Renzaho A. M. N., Resnikoff S., Rezaei N., Rezapour A., Rhinehart P. -A., Riahi S. M., Ribeiro D. C., Ribeiro D., Rickard J., Rivera J. A., Roberts N. L. S., Rodriguez-Ramirez S., Roever L., Ronfani L., Room R., Roshandel G., Roth G. A., Rothenbacher D., Rubagotti E., Rwegerera G. M., Sabour S., Sachdev P. S., Saddik B., Sadeghi E., Sadeghi M., Saeedi R., Saeedi Moghaddam S., Safari Y., Safi S., Safiri S., Sagar R., Sahebkar A., Sajadi S. M., Salam N., Salamati P., Salem H., Salem M. R., Salimzadeh H., Salman O. M., Salomon J. A., Samad Z., Samadi Kafil H., Sambala E. Z., Samy A. M., Sanabria J., Sanchez-Pimienta T. G., Santomauro D. F., Santos I. S., Santos J. V., Santric-Milicevic M. M., Saraswathy S. Y. I., Sarmiento-Suarez R., Sarrafzadegan N., Sartorius B., Sarveazad A., Sathian B., Sathish T., Sattin D., Saxena S., Schaeffer L. E., Schiavolin S., Schlaich M. P., Schmidt M. I., Schutte A. E., Schwebel D. C., Schwendicke F., Senbeta A. M., Senthilkumaran S., Sepanlou S. G., Serdar B., Serre M. L., Shadid J., Shafaat O., Shahabi S., Shaheen A. A., Shaikh M. A., Shalash A. S., Shams-Beyranvand M., Shamsizadeh M., Sharafi K., Sheikh A., Sheikhtaheri A., Shibuya K., Shield K. D., Shigematsu M., Shin J. I., Shin M. -J., Shiri R., Shirkoohi R., Shuval K., Siabani S., Sierpinski R., Sigfusdottir I. D., Sigurvinsdottir R., Silva J. P., Simpson K. E., Singh J. A., Singh P., Skiadaresi E., Skou S. T., Skryabin V. Y., Smith E. U. R., Soheili A., Soltani S., Soofi M., Sorensen R. J. D., Soriano J. B., Sorrie M. B., Soshnikov S., Soyiri I. N., Spencer C. N., Spotin A., Sreeramareddy C. T., Srinivasan V., Stanaway J. D., Stein C., Stein D. J., Steiner C., Stockfelt L., Stokes M. A., Straif K., Stubbs J. L., Sufiyan M. B., Suleria H. A. R., Suliankatchi Abdulkader R., Sulo G., Sultan I., Tabares-Seisdedos R., Tabb K. M., Tabuchi T., Taherkhani A., Tajdini M., Takahashi K., Takala J. S., Tamiru A. T., Taveira N., Tehrani-Banihashemi A., Temsah M. -H., Tesema G. A., Tessema Z. T., Thurston G. D., Titova M. V., Tohidinik H. R., Tonelli M., Topor-Madry R., Topouzis F., Torre A. E., Touvier M., Tovani-Palone M. R., Tran B. X., Travillian R., Tsatsakis A., Tudor Car L. T., Tyrovolas S., Uddin R., Umeokonkwo C. D., Unnikrishnan B., Upadhyay E., Vacante M., Valdez P. R., van Donkelaar A., Vasankari T. J., Vasseghian Y., Veisani Y., Venketasubramanian N., Violante F. S., Vlassov V., Vollset S. E., Vos T., Vukovic R., Waheed Y., Wallin M. T., Wang Y., Wang Y. -P., Watson A., Wei J., Wei M. Y. W., Weintraub R. G., Weiss J., Werdecker A., West J. J., Westerman R., Whisnant J. L., Whiteford H. A., Wiens K. E., Wolfe C. D. A., Wozniak S. S., Wu A. -M., Wu J., Wulf Hanson S., Xu G., Xu R., Yadgir S., Yahyazadeh Jabbari S. H., Yamagishi K., Yaminfirooz M., Yano Y., Yaya S., Yazdi-Feyzabadi V., Yeheyis T. Y., Yilgwan C. S., Yilma M. T., Yip P., Yonemoto N., Younis M. Z., Younker T. P., Yousefi B., Yousefi Z., Yousefinezhadi T., Yousuf A. Y., Yu C., Yusefzadeh H., Moghadam T. Z., Zamani M., Zamanian M., Zandian H., Zastrozhin M. S., Zhang Y., Zhang Z. -J., Zhao J. T., Zhao X. -J. G., Zhao Y., Zheng P., Zhou M., Ziapour A., Zimsen S. R. M., Lim S. S., and Murray C. J. L.
Abstract: Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each
Published: 2020

35. Predictors of a favourable socio-economic situation in middle age for Swedish conscripts with self-reported drug use

Author: Davstad, I., Leifman, A., Allebeck, P., and Romelsjö, A.
Published: 2013
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36. The burden of mental disorders, substance use disorders and self-harm among young people in Europe, 1990–2019:Findings from the Global Burden of Disease Study 2019

Author: Castelpietra, G. (Giulio), Knudsen, A. K. (Ann Kristin Skrindo), Agardh, E. E. (Emilie E.), Armocida, B. (Benedetta), Beghi, M. (Massimiliano), Iburg, K. M. (Kim Moesgaard), Logroscino, G. (Giancarlo), Ma, R. (Rui), Starace, F. (Fabrizio), Steel, N. (Nicholas), Addolorato, G. (Giovanni), Andrei, C. L. (Catalina Liliana), Andrei, T. (Tudorel), Ayuso-Mateos, J. L. (Jose L.), Banach, M. (Maciej), Barnighausen, T. W. (Till Winfried), Barone-Adesi, F. (Francesco), Bhagavathula, A. S. (Akshaya Srikanth), Carvalho, F. (Felix), Carvalho, M. (Marcia), Chandan, J. S. (Joht Singh), Chattu, V. K. (Vijay Kumar), Couto, R. A. (Rosa A. S.), Cruz-Martins, N. (Natalia), Dargan, P. I. (Paul, I), Deuba, K. (Keshab), da Silva, D. D. (Diana Dias), Fagbamigbe, A. F. (Adeniyi Francis), Fernandes, E. (Eduarda), Ferrara, P. (Pietro), Fischer, F. (Florian), Gaal, P. A. (Peter Andras), Gialluisi, A. (Alessandro), Haagsma, J. A. (Juanita A.), Haro, J. M. (Josep Maria), Hasan, M. T. (M. Tasdik), Hasan, S. S. (Syed Shahzad), Hostiuc, S. (Sorin), Iacoviello, L. (Licia), Iavicoli, I. (Ivo), Jamshidi, E. (Elham), Jonas, J. B. (Jost B.), Joo, T. (Tamas), Jozwiak, J. J. (Jacek Jerzy), Katikireddi, S. V. (Srinivasa Vittal), Kauppila, J. H. (Joonas H.), Khan, M. A. (Moien A. B.), Kisa, A. (Adnan), Kisa, S. (Sezer), Kivimaki, M. (Mika), Koly, K. N. (Kamrun Nahar), Koyanagi, A. (Ai), Kumar, M. (Manasi), Lallukka, T. (Tea), Langguth, B. (Berthold), Ledda, C. (Caterina), Lee, P. H. (Paul H.), Lega, I. (Ilaria), Linehan, C. (Christine), Loureiro, J. A. (Joana A.), Madureira-Carvalho, A. M. (Aurea M.), Martinez-Raga, J. (Jose), Mathur, M. R. (Manu Raj), McGrath, J. J. (John J.), Mechili, E. A. (Enkeleint A.), Mentis, A. A. (Alexios-Fotios A.), Mestrovic, T. (Tomislav), Miazgowski, B. (Bartosz), Mirica, A. (Andreea), Mirijello, A. (Antonio), Moazen, B. (Babak), Mohammed, S. (Shafiu), Mulita, F. (Francesk), Nagel, G. (Gabriele), Negoi, I. (Ionut), Negoi, R. I. (Ruxandra Irina), Nwatah, V. E. (Vincent Ebuka), Padron-Monedero, A. (Alicia), Panda-Jonas, S. (Songhomitra), Pardhan, S. (Shahina), Pasovic, M. (Maja), Patel, J. (Jay), Petcu, I.-R. (Ionela-Roxana), Pinheiro, M. (Marina), Pollok, R. C. (Richard Charles G.), Postma, M. J. (Maarten J.), Rawaf, D. L. (David Laith), Rawaf, S. (Salman), Romero-Rodriguez, E. (Esperanza), Ronfani, L. (Luca), Sagoe, D. (Dominic), Sanmarchi, F. (Francesco), Schaub, M. P. (Michael P.), Sharew, N. T. (Nigussie Tadesse), Shiri, R. (Rahman), Shokraneh, F. (Farhad), Sigfusdottir, I. D. (Inga Dora), Silva, J. P. (Joao Pedro), Silva, R. (Renata), Socea, B. (Bogdan), Szocska, M. (Miklos), Tabares-Seisdedos, R. (Rafael), Torrado, M. (Marco), Tovani-Palone, M. R. (Marcos Roberto), Vasankari, T. J. (Tommi Juhani), Veroux, M. (Massimiliano), Viner, R. M. (Russell M.), Werdecker, A. (Andrea), Winkler, A. S. (Andrea Sylvia), Hay, S. I. (Simon, I), Ferrari, A. J. (Alize J.), Naghavi, M. (Mohsen), Allebeck, P. (Peter), Monasta, L. (Lorenzo), Castelpietra, G. (Giulio), Knudsen, A. K. (Ann Kristin Skrindo), Agardh, E. E. (Emilie E.), Armocida, B. (Benedetta), Beghi, M. (Massimiliano), Iburg, K. M. (Kim Moesgaard), Logroscino, G. (Giancarlo), Ma, R. (Rui), Starace, F. (Fabrizio), Steel, N. (Nicholas), Addolorato, G. (Giovanni), Andrei, C. L. (Catalina Liliana), Andrei, T. (Tudorel), Ayuso-Mateos, J. L. (Jose L.), Banach, M. (Maciej), Barnighausen, T. W. (Till Winfried), Barone-Adesi, F. (Francesco), Bhagavathula, A. S. (Akshaya Srikanth), Carvalho, F. (Felix), Carvalho, M. (Marcia), Chandan, J. S. (Joht Singh), Chattu, V. K. (Vijay Kumar), Couto, R. A. (Rosa A. S.), Cruz-Martins, N. (Natalia), Dargan, P. I. (Paul, I), Deuba, K. (Keshab), da Silva, D. D. (Diana Dias), Fagbamigbe, A. F. (Adeniyi Francis), Fernandes, E. (Eduarda), Ferrara, P. (Pietro), Fischer, F. (Florian), Gaal, P. A. (Peter Andras), Gialluisi, A. (Alessandro), Haagsma, J. A. (Juanita A.), Haro, J. M. (Josep Maria), Hasan, M. T. (M. Tasdik), Hasan, S. S. (Syed Shahzad), Hostiuc, S. (Sorin), Iacoviello, L. (Licia), Iavicoli, I. (Ivo), Jamshidi, E. (Elham), Jonas, J. B. (Jost B.), Joo, T. (Tamas), Jozwiak, J. J. (Jacek Jerzy), Katikireddi, S. V. (Srinivasa Vittal), Kauppila, J. H. (Joonas H.), Khan, M. A. (Moien A. B.), Kisa, A. (Adnan), Kisa, S. (Sezer), Kivimaki, M. (Mika), Koly, K. N. (Kamrun Nahar), Koyanagi, A. (Ai), Kumar, M. (Manasi), Lallukka, T. (Tea), Langguth, B. (Berthold), Ledda, C. (Caterina), Lee, P. H. (Paul H.), Lega, I. (Ilaria), Linehan, C. (Christine), Loureiro, J. A. (Joana A.), Madureira-Carvalho, A. M. (Aurea M.), Martinez-Raga, J. (Jose), Mathur, M. R. (Manu Raj), McGrath, J. J. (John J.), Mechili, E. A. (Enkeleint A.), Mentis, A. A. (Alexios-Fotios A.), Mestrovic, T. (Tomislav), Miazgowski, B. (Bartosz), Mirica, A. (Andreea), Mirijello, A. (Antonio), Moazen, B. (Babak), Mohammed, S. (Shafiu), Mulita, F. (Francesk), Nagel, G. (Gabriele), Negoi, I. (Ionut), Negoi, R. I. (Ruxandra Irina), Nwatah, V. E. (Vincent Ebuka), Padron-Monedero, A. (Alicia), Panda-Jonas, S. (Songhomitra), Pardhan, S. (Shahina), Pasovic, M. (Maja), Patel, J. (Jay), Petcu, I.-R. (Ionela-Roxana), Pinheiro, M. (Marina), Pollok, R. C. (Richard Charles G.), Postma, M. J. (Maarten J.), Rawaf, D. L. (David Laith), Rawaf, S. (Salman), Romero-Rodriguez, E. (Esperanza), Ronfani, L. (Luca), Sagoe, D. (Dominic), Sanmarchi, F. (Francesco), Schaub, M. P. (Michael P.), Sharew, N. T. (Nigussie Tadesse), Shiri, R. (Rahman), Shokraneh, F. (Farhad), Sigfusdottir, I. D. (Inga Dora), Silva, J. P. (Joao Pedro), Silva, R. (Renata), Socea, B. (Bogdan), Szocska, M. (Miklos), Tabares-Seisdedos, R. (Rafael), Torrado, M. (Marco), Tovani-Palone, M. R. (Marcos Roberto), Vasankari, T. J. (Tommi Juhani), Veroux, M. (Massimiliano), Viner, R. M. (Russell M.), Werdecker, A. (Andrea), Winkler, A. S. (Andrea Sylvia), Hay, S. I. (Simon, I), Ferrari, A. J. (Alize J.), Naghavi, M. (Mohsen), Allebeck, P. (Peter), and Monasta, L. (Lorenzo)
Abstract: Background: Mental health is a public health issue for European young people, with great heterogeneity in resource allocation. Representative population-based studies are needed. The Global Burden of Disease (GBD) Study 2019 provides internationally comparable information on trends in the health status of populations and changes in the leading causes of disease burden over time. Methods: Prevalence, incidence, Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) from mental disorders (MDs), substance use disorders (SUDs) and self-harm were estimated for young people aged 10–24 years in 31 European countries. Rates per 100,000 population, percentage changes in 1990–2019, 95% Uncertainty Intervals (UIs), and correlations with Sociodemographic Index (SDI), were estimated. Findings: In 2019, rates per 100,000 population were 16,983 (95% UI 12,823–21,630) for MDs, 3,891 (3,020–4,905) for SUDs, and 89·1 (63·8–123·1) for self-harm. In terms of disability, anxiety contributed to 647·3 (432–912·3) YLDs, while in terms of premature death, self-harm contributed to 319·6 (248·9–412·8) YLLs, per 100,000 population. Over the 30 years studied, YLDs increased in eating disorders (14·9%;9·4–20·1) and drug use disorders (16·9%;8·9–26·3), and decreased in idiopathic developmental intellectual disability (–29·1%;23·8-38·5). YLLs decreased in self-harm (–27·9%;38·3–18·7). Variations were found by sex, age-group and country. The burden of SUDs and self-harm was higher in countries with lower SDI, MDs were associated with SUDs. Interpretation: Mental health conditions represent an important burden among young people living in Europe. National policies should strengthen mental health, with a specific focus on young people.
Published: 2022

37. Alcohol consumption and household expenditure on alcohol in a rural district in Vietnam

Author: Peter Allebeck, Kim Bao Giang, and Hoang Van Minh
Subjects: alcohol consumption, alcohol problems, alcohol expenditure, Vietnam, Public aspects of medicine, RA1-1270
Abstract: Introduction: Alcohol use and alcohol-related problems are on the rise in low- and middle-income countries. Expenditure on alcohol is an important problem for families and communities and needs to be assessed. Aim: This study examines level of alcohol consumption and expenditure on alcohol in a district in Vietnam. Methods: A cross-sectional survey was conducted in a rural district in northern Vietnam. Multi-stage sampling was employed to randomly select participants from 20 communities and a town in the same district. One thousand five hundred and sixty-four adults (765 males and 799 females) aged 18–60 years were interviewed. Information about alcohol use as well as expenditure on alcohol consumption four weeks prior to the interview was gathered. Non-parametric tests and log-linear regression were employed to compare expenditure on alcohol consumption across socioeconomic groups. Results: The prevalence of alcohol use one month prior to interview was 35% (66% among men and 5% among women). The median alcohol consumption among those who reported use of alcohol in the week prior to the interview was 7.9 standard drinks. Excessive drinking (more than 14 standard drinks per week for men and more than seven standard drinks per week for women) occurred among 35% of those who used alcohol. Median expenditure for alcohol consumption during one month by those who drank alcohol was USD 3.5, accounting for 4.6% of household food expenditure, 2.7% of total household expenditure, and 1.8% of household income. The differences in alcohol consumption and expenditure between sexes and between socioeconomic groups are also presented. Conclusion: Our study confirms that alcohol consumption and alcohol-related problems are common among men in Vietnam. The share of alcohol expenditure in total household expenditure is substantial, especially among poor households. This should be considered an important public health issue, which needs to be taken into account in the alcohol policy debate.
Published: 2013
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38. Unemployment and suicide in the Stockholm population: A register-based study on 771,068 men and women

Author: Lundin, A., Lundberg, I., Allebeck, P., and Hemmingsson, T.
Published: 2012
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39. Cannabis Use as Risk or Protection for Type 2 Diabetes: A Longitudinal Study of 18 000 Swedish Men and Women

Author: A. K. Danielsson, A. Lundin, A. Yaregal, C. G. Östenson, P. Allebeck, and E. E. Agardh
Subjects: Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract: Aims. Whether or not cannabis use may increase or decrease the risk of type 2 diabetes is not clear. We analyzed the association between cannabis and subsequent type 2 diabetes and if a potential positive or reverse association persisted after controlling for potential confounders. Methods. In this population-based cohort study, 17,967 Swedish men and women (aged 18–84 years), who answered an extensive questionnaire in 2002 (including questions on cannabis use), were followed up for new cases of type 2 diabetes (n=608) by questionnaire (in 2010) and in health registers during 2003–2011. Odds ratios (ORs) with 95% CIs were estimated in a multiple logistic regression analysis. Potential confounders included age, sex, BMI, physical inactivity, smoking, alcohol use, and occupational position. Results. The crude association showed that cannabis users had a reduced risk of type 2 diabetes OR = 0.68 (95% CIs: 0.47–0.99). However, this inverse association attenuated to OR = 0.94 (95% CIs: 0.63–1.39) after adjusting for age. Conclusions. The present study suggests that there is no association between cannabis use and subsequent type 2 diabetes after controlling for age. To make more robust conclusions prospective studies, with longer periods of follow-up and more detailed information about cannabis use, are needed.
Published: 2016
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40. The burden of mental disorders, substance use disorders and self-harm among young people in Europe, 1990–2019: Findings from the Global Burden of Disease Study 2019

Author: Castelpietra, G. Knudsen, A.K.S. Agardh, E.E. Armocida, B. Beghi, M. Iburg, K.M. Logroscino, G. Ma, R. Starace, F. Steel, N. Addolorato, G. Andrei, C.L. Andrei, T. Ayuso-Mateos, J.L. Banach, M. Bärnighausen, T.W. Barone-Adesi, F. Bhagavathula, A.S. Carvalho, F. Carvalho, M. Chandan, J.S. Chattu, V.K. Couto, R.A.S. Cruz-Martins, N. Dargan, P.I. Deuba, K. da Silva, D.D. Fagbamigbe, A.F. Fernandes, E. Ferrara, P. Fischer, F. Gaal, P.A. Gialluisi, A. Haagsma, J.A. Haro, J.M. Hasan, M.T. Hasan, S.S. Hostiuc, S. Iacoviello, L. Iavicoli, I. Jamshidi, E. Jonas, J.B. Joo, T. Jozwiak, J.J. Katikireddi, S.V. Kauppila, J.H. Khan, M.A.B. Kisa, A. Kisa, S. Kivimäki, M. Koly, K.N. Koyanagi, A. Kumar, M. Lallukka, T. Langguth, B. Ledda, C. Lee, P.H. Lega, I. Linehan, C. Loureiro, J.A. Madureira-Carvalho, Á.M. Martinez-Raga, J. Mathur, M.R. McGrath, J.J. Mechili, E.A. Mentis, A.-F.A. Mestrovic, T. Miazgowski, B. Mirica, A. Mirijello, A. Moazen, B. Mohammed, S. Mulita, F. Nagel, G. Negoi, I. Negoi, R.I. Nwatah, V.E. Padron-Monedero, A. Panda-Jonas, S. Pardhan, S. Pasovic, M. Patel, J. Petcu, I.-R. Pinheiro, M. Pollok, R.C.G. Postma, M.J. Rawaf, D.L. Rawaf, S. Romero-Rodríguez, E. Ronfani, L. Sagoe, D. Sanmarchi, F. Schaub, M.P. Sharew, N.T. Shiri, R. Shokraneh, F. Sigfusdottir, I.D. Silva, J.P. Silva, R. Socea, B. Szócska, M. Tabarés-Seisdedos, R. Torrado, M. Tovani-Palone, M.R. Vasankari, T.J. Veroux, M. Viner, R.M. Werdecker, A. Winkler, A.S. Hay, S.I. Ferrari, A.J. Naghavi, M. Allebeck, P. Monasta, L.
Abstract: Background: Mental health is a public health issue for European young people, with great heterogeneity in resource allocation. Representative population-based studies are needed. The Global Burden of Disease (GBD) Study 2019 provides internationally comparable information on trends in the health status of populations and changes in the leading causes of disease burden over time. Methods: Prevalence, incidence, Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) from mental disorders (MDs), substance use disorders (SUDs) and self-harm were estimated for young people aged 10-24 years in 31 European countries. Rates per 100,000 population, percentage changes in 1990-2019, 95% Uncertainty Intervals (UIs), and correlations with Sociodemographic Index (SDI), were estimated. Findings: In 2019, rates per 100,000 population were 16,983 (95% UI 12,823 – 21,630) for MDs, 3,891 (3,020 - 4,905) for SUDs, and 89·1 (63·8 - 123·1) for self-harm. In terms of disability, anxiety contributed to 647·3 (432–912·3) YLDs, while in terms of premature death, self-harm contributed to 319·6 (248·9–412·8) YLLs, per 100,000 population. Over the 30 years studied, YLDs increased in eating disorders (14·9%;9·4-20·1) and drug use disorders (16·9%;8·9-26·3), and decreased in idiopathic developmental intellectual disability (–29·1%;23·8-38·5). YLLs decreased in self-harm (–27·9%;38·3-18·7). Variations were found by sex, age-group and country. The burden of SUDs and self-harm was higher in countries with lower SDI, MDs were associated with SUDs. Interpretation: Mental health conditions represent an important burden among young people living in Europe. National policies should strengthen mental health, with a specific focus on young people. Funding: The Bill and Melinda Gates Foundation © 2022 The Author(s)
Published: 2022

41. Drug use and self-medication among children with respiratory illness or diarrhea in a rural district in Vietnam: a qualitative study

Author: Le TH, Ottosson E, Nguyen TKC, Kim BG, and Allebeck P
Subjects: Medicine (General), R5-920
Abstract: Thi Hoan Le1,2, Ellinor Ottosson3, Thi Kim Chuc Nguyen4, Bao Giang Kim5, Peter Allebeck11Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden; 2Department of Environmental Health, Hanoi Medical University, Hanoi, Vietnam; 3Department of Medicine, Gothenburg University, Gothenburg, Sweden; 4Department of Family Medicine, Hanoi Medical University, Hanoi, Vietnam; 5Department of Health Education, Hanoi Medical University, Hanoi, VietnamAims: To explore the knowledge, attitudes, and behaviors of parents in their use of drugs for respiratory illness or diarrhea among children under 5 years of age, and to understand factors influencing self-medication.Methods: A qualitative study was conducted, using in-depth interviews with two drug sellers and three health care providers, and four focus-group discussions with mothers of children under 5 years of age. Verbatim transcriptions were analyzed, and emerging themes and categories identified, using content analysis.Results: Use of a number of different drugs was reported, including broad-spectrum antibiotics and corticosteroids. There was poor awareness of side-effects, antibiotic resistance, and drug efficacy. Factors influencing self-medication were perceptions of the illness in the child, waiting time, and convenience, the attitudes of public health medical staff, insufficient drug supply in public health facilities, and poor control of prescribed drugs on the market.Conclusion: Misuse and misconceptions regarding drug use gave rise to considerable problems. Mothers' knowledge and attitudes to illness and health care services played an important role in determining the nature of self-medication. Financial barriers were not the only obstacle to adequate treatment. Health services should be more accessible and responsive to the needs of the population.Keywords: health services, parental attitudes, education
Published: 2011

42. Cognitive ability in adolescence and mortality in middle age: a prospective life course study

Author: Hemmingsson, T, Melin, B, Allebeck, P, and Lundberg, I
Published: 2009

43. School performance and risk of suicide in early adulthood: Follow-up of two national cohorts of Swedish schoolchildren

Author: Gunnell, D., Löfving, S., Gustafsson, J.-E., and Allebeck, P.
Published: 2011
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44. Diarrhoea case management in low- and middle-income countries: an unfinished agenda

Author: Birger Carl Forsberg, Max G Petzold, Göran Tomson, and Peter Allebeck
Subjects: Public aspects of medicine, RA1-1270
Abstract: OBJECTIVE: To ascertain whether diarrhoea management improved during 1986-2003, a period when significant efforts were made to promote effective case management in children. METHODS: We analysed household data from 107 Demographic and Health Surveys in 40 low- and middle-income countries from 1986 to 2003 and assessed trends in indicators of rehydration, fluid quantity and food intake in children with diarrhoea. A statistical analysis was made of the overall trend for each indicator. FINDINGS: Modest progress was made with regard to the use of oral rehydration therapy (ORT) (0.39% per year) and increased fluid intake (1.02% per year), and use rates remained low in 2003, when compared with desired full coverage. Although use rates improved in the majority of countries, no progress was made in several countries. We estimate that, annually, 307 million children in low- and middle-income countries did not receive ORT, 356 million did not get increased amounts of fluids, and at the beginning of the 21st century, 227 million children got neither ORT nor increased amounts of fluids. CONCLUSION: The finding that many children in low- and middle-income countries do not receive proper treatment for diarrhoea points to the urgency in addressing this unfinished agenda in child survival. The effectiveness of diarrhoea control needs to be improved after critical review of established approaches and activities to reach caregivers of children at risk of dying from diarrhoeal diseases. Significant efforts must be made to scale up activities to improve case management and reduce childhood deaths from diarrhoea.
Published: 2007

45. Intelligence and Disability Pension in Swedish Men and Women Followed from Childhood to Late Middle Age.

Author: Andreas Lundin, Alma Sörberg Wallin, Daniel Falkstedt, Peter Allebeck, and Tomas Hemmingsson
Subjects: Medicine, Science
Abstract: ObjectiveTo investigate the association between intelligence and disability pension due to mental, musculoskeletal, cardiovascular, and substance-use disorders among men and women, and to assess the role of childhood social factors and adulthood work characteristics.MethodsTwo random samples of men and women born 1948 and 1953 (n = 10 563 and 9 434), and tested for general intelligence at age 13, were followed in registers for disability pension until 2009. Physical and psychological strains in adulthood were assessed using job exposure matrices. Associations were examined using Cox proportional hazard regression models, with increases in rates reported as hazard ratios (HRs) with 95% confidence intervals (95%CI) per decrease in stanine intelligence.ResultsIn both men and women increased risks were found for disability pension due to all causes, musculoskeletal disorder, mental disorder other than substance use, and cardiovascular disease as intelligence decreased. Increased risk was also found for substance use disorder in men. In multivariate models, HRs were attenuated after controlling for pre-school plans in adolescence, and low job control and high physical strain in adulthood. In the fully adjusted model, increased HRs remained for all causes (male HR 1.11, 95%CI 1.07-1.15, female HR 1.06, 95%CI 1.02-1.09) and musculoskeletal disorder (male HR 1.16, 95%CI 1.09-1.24, female HR 1.08, 95%CI 1.03-1.14) during 1986 to 2009.ConclusionRelatively low childhood intelligence is associated with increased risk of disability pension due to musculoskeletal disorder in both men and women, even after adjustment for risk factors for disability pension measured over the life course.
Published: 2015
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46. Burden Of Illness And Suicide In Elderly People: Case-Control Study

Author: Waern, Margda, Rubenowitz, E., Runeson, B., Skoog, I., Wilhelmson, K., and Allebeck, P.
Published: 2002

47. Testing Ødegaardʼs selective migration hypothesis: a longitudinal cohort study of risk factors for non-affective psychotic disorders among prospective emigrants

Author: van der Ven, E., Dalman, C., Wicks, S., Allebeck, P., Magnusson, C., van Os, J., and Selten, J. P.
Published: 2015

48. Body mass index in young adulthood and suicidal behavior up to age 59 in a cohort of Swedish men.

Author: Alma Sörberg, David Gunnell, Daniel Falkstedt, Peter Allebeck, Maria Åberg, and Tomas Hemmingsson
Subjects: Medicine, Science
Abstract: An association of higher body mass index (BMI) with lower risk of attempted and completed suicide has been reported. In contrast, increasing BMI has been found to be associated with depression and other risk factors for suicidal behavior. We aimed to investigate this possible paradox in a cohort comprising 49 000 Swedish men. BMI, mental health, lifestyle and socioeconomic measures were recorded at conscription in 1969-70, at ages 18-20. Information on attempted suicide 1973-2008 and completed suicide 1971-2008 was obtained from national records. Hazard ratios (HR) were estimated by Cox proportional hazard models. We found that each standard deviation (SD) increase in BMI was associated with a 12% lower risk of later suicide attempt (HR 0.88, 95% CI 0.83-0.94). Associations were somewhat weaker for completed suicide and did not reach conventional levels of statistical significance (HR 0.93, 95% CI 0.85-1.01). Adjustment for a wide range of possible confounding factors had little effect on the associations. Lower BMI at conscription was also associated with higher prevalence of psychiatric diagnoses, low emotional control and depressed mood. Our results confirm previous findings regarding the association of higher BMI with a reduced risk of suicide, extending them to show similar findings in relation to suicide attempts. The associations were little affected by adjustment for a range of possible confounding factors. However, we found no evidence that high BMI was associated with an increased risk of depression cross-sectionally or longitudinally.
Published: 2014
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49. Marijuana use and risk of lung cancer: a 40-year cohort study

Author: Callaghan, Russell C., Allebeck, Peter, and Sidorchuk, Anna
Published: 2013
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50. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019

Author: Reitsma, MB, Kendrick, PJ, Ababneh, E, Abbafati, C, Abbasi-Kangevari, M, Abdoli, A, Abedi, A, Abhilash, ES, Abila, DB, Aboyans, V, Abu-Rmeileh, NME, Adebayo, OM, Advani, SM, Aghaali, M, Ahinkorah, BO, Ahmad, S, Ahmadi, K, Ahmed, H, Aji, B, Akunna, CJ, Al-Aly, Z, Alanzi, TM, Alhabib, KF, Ali, L, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Allebeck, P, Alvis-Guzman, N, Amin, TT, Amini, S, Amu, H, Amul, GGH, Ancuceanu, R, Anderson, JA, Ansari-Moghaddam, A, Antonio, CAT, Antony, B, Anvari, D, Arabloo, J, Arian, ND, Arora, M, Asaad, M, Ausloos, M, Awan, AT, Ayano, G, Aynalem, GL, Azari, S, Darshan, BB, Badiye, AD, Baig, AA, Bakhshaei, MH, Banach, M, Banik, PC, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Basu, S, Bayati, M, Bazargan-Hejazi, S, Behzadifar, M, Bekuma, TT, Bennett, DA, Bensenor, IM, Berfield, KSS, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bibi, S, Bijani, A, Bintoro, BS, Biondi, A, Birara, S, Braithwaite, D, Brenner, H, Brunoni, AR, Burkart, K, Butt, ZA, Caetano dos Santos, FL, Alberto Camera, L, Car, J, Cardenas, R, Carreras, G, Carrero, JJ, Castaldelli-Maia, JM, Cattaruzza, MSS, Chang, J-C, Chen, S, Chu, D-T, Chung, S-C, Cirillo, M, Costa, VM, Couto, RAS, Dadras, O, Dai, X, Damasceno, AAM, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Gela, JD, Davletov, K, Molla, MD, Dessie, GA, Desta, AA, Dharmaratne, SD, Dianatinasab, M, Diaz, D, Hoa, TD, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Kalan, ME, Edvardsson, K, Elbarazi, I, El Tantawi, M, Esmaeilnejad, S, Fadhil, I, Faraon, EJA, Farinha, CSES, Farwati, M, Farzadfar, F, Fazlzadeh, M, Feigin, VL, Feldman, R, Prendes, CF, Ferrara, P, Filip, I, Filippidis, F, Fischer, F, Flor, LS, Foigt, NA, Folayan, MO, Foroutan, M, Gad, MM, Gaidhane, AM, Gallus, S, Geberemariyam, BS, Ghafourifard, M, Ghajar, A, Ghashghaee, A, Giampaoli, S, Gill, PS, Glozah, FN, Gnedovskaya, EV, Golechha, M, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Greaves, F, Guha, A, Guo, Y, Gupta, B, Das Gupta, R, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Haider, MR, Hamadeh, RR, Hankey, GJ, Hargono, A, Hartono, RK, Hassankhani, H, Hay, SI, Heidari, G, Herteliu, C, Hezam, K, Hird, TR, Hole, MK, Holla, R, Hosseinzadeh, M, Hostiuc, S, Househ, M, Hsiao, T, Huang, J, Iannucci, VC, Ibitoye, SE, Idrisov, B, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Irvani, SSN, Islam, JY, Islam, RM, Shariful Islam, Sheikh, Islami, F, Iso, H, Itumalla, R, Iwagami, M, Jaafari, J, Jain, V, Jakovljevic, M, Jang, S-I, Janjani, H, Jayaram, S, Jeemon, P, Jha, RP, Jonas, JB, Joo, T, Jurisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kanchan, T, Kandel, H, Kapoor, N, Karimi, SE, Katikireddi, SV, Kebede, HK, Kelkay, B, Kennedy, RD, Khoja, AT, Khubchandani, J, Kim, GR, Kim, Y-E, Kimokoti, RW, Kivimaki, M, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Lacey, B, Lam, JO, Landires, I, Lasrado, S, Lauriola, P, Lee, DW, Lee, YH, Leung, J, Li, S, Lin, H, Linn, S, Liu, W, Lopez, AD, Lopukhov, PD, Lorkowski, S, Lugo, A, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Manjunatha, N, Mansouri, B, Mansournia, MA, Martinez-Raga, J, Martini, S, Mathur, MR, Medina-Solis, CE, Mehata, S, Mendoza, W, Menezes, RG, Meretoja, A, Meretoja, TJ, Miazgowski, B, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Mirzaei-Alavijeh, M, Misra, S, Moghadaszadeh, M, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Monasta, L, Moni, MA, Moradi, G, Moradi-Lakeh, M, Moradzadeh, R, Morrison, SD, Mossie, TB, Mubarik, S, Mullany, EC, Murray, CJL, Naghavi, M, Naghshtabrizi, B, Nair, S, Nalini, M, Nangia, V, Naqvi, AA, Swamy, SN, Naveed, M, Nayak, S, Nayak, VC, Nazari, J, Nduaguba, SO, Kandel, SN, Cuong, TN, Huong, LTN, Son, HN, Trang, HN, Nixon, MR, Nnaji, CA, Norrving, B, Noubiap, JJ, Nowak, C, Ogbo, FA, Oguntade, AS, Oh, I-H, Olagunju, AT, Oren, E, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Pakhale, MPAS, Pakshir, K, Palladino, R, Pana, A, Panda-Jonas, S, Pandey, A, Parekh, U, Park, E-C, Park, E-K, Kan, FP, Patton, GC, Pawar, S, Pestell, RG, Pinheiro, M, Piradov, MA, Pirouzpanah, S, Pokhrel, KN, Polibin, RV, Prashant, A, Pribadi, DRA, Radfar, A, Rahimi-Movaghar, V, Rahman, A, Rahman, MHU, Rahman, Muhammad, Rahmani, AM, Rajai, N, Ram, P, Ranabhat, CL, Rathi, P, Rawal, L, Renzaho, AMN, Myriam Reynales-Shigematsu, L, Rezapour, A, Riahi, SM, Riaz, MA, Roever, L, Ronfani, L, Roshandel, G, Roy, A, Roy, B, Sacco, S, Saddik, B, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sathian, B, Sawhney, M, Saylan, M, Schaub, MP, Schmidt, MI, Ceola Schneider, IJ, Schutte, AE, Schwendicke, F, Seidu, A-A, Kumar, NS, Sepanlou, SG, Seylani, A, Shafaat, O, Shah, SM, Shaikh, MA, Shalash, AS, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shigematsu, M, Shiri, R, Shishani, K, Shivakumar, KM, Shivalli, S, Shrestha, R, Siabani, S, Sidemo, NB, Sigfusdottir, ID, Sigurvinsdottir, R, Santos Silva, DA, Silva, JP, Singh, A, Singh, JA, Singh, V, Sinha, DN, Sitas, F, Skryabin, VY, Skryabina, AA, Soboka, M, Soriano, JB, Soroush, A, Soshnikov, S, Soyiri, IN, Spurlock, EE, Sreeramareddy, CT, Stein, DJ, Steiropoulos, P, Stortecky, S, Straif, K, Abdulkader, RS, Sulo, G, Sundstrom, J, Tabuchi, T, Tadakamadla, SK, Taddele, BW, Tadesse, EG, Tamiru, AT, Tareke, M, Tareque, MI, Tarigan, IU, Temsah, M-H, Thankappan, KR, Thapar, R, Tichopad, A, Tolani, MA, Topouzis, F, Tovani-Palone, MR, Bach, XT, Tripathy, JP, Tsegaye, GW, Tsilimparis, N, Tymeson, HD, Ullah, A, Ullah, S, Unim, B, Updike, RL, Vacante, M, Valdez, PR, Vardavas, C, Varona Perez, P, Vasankari, TJ, Venketasubramanian, N, Verma, M, Vetrova, MV, Bay, V, Giang, TV, Waheed, Y, Wang, Y, Welding, K, Werdecker, A, Whisnant, JL, Wickramasinghe, ND, Yamagishi, K, Yandrapalli, S, Yatsuya, H, Yazdi-Feyzabadi, V, Yeshaw, Y, Yimmer, MZ, Yonemoto, N, Yu, C, Yunusa, I, Yusefzadeh, H, Moghadam, TZ, Zaman, MS, Zamanian, M, Zandian, H, Zar, HJ, Zastrozhin, MS, Zastrozhina, A, Zavala-Arciniega, L, Zhang, J, Zhang, Z-J, Zhong, C, Zuniga, YMH, Gakidou, E, Reitsma, MB, Kendrick, PJ, Ababneh, E, Abbafati, C, Abbasi-Kangevari, M, Abdoli, A, Abedi, A, Abhilash, ES, Abila, DB, Aboyans, V, Abu-Rmeileh, NME, Adebayo, OM, Advani, SM, Aghaali, M, Ahinkorah, BO, Ahmad, S, Ahmadi, K, Ahmed, H, Aji, B, Akunna, CJ, Al-Aly, Z, Alanzi, TM, Alhabib, KF, Ali, L, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Allebeck, P, Alvis-Guzman, N, Amin, TT, Amini, S, Amu, H, Amul, GGH, Ancuceanu, R, Anderson, JA, Ansari-Moghaddam, A, Antonio, CAT, Antony, B, Anvari, D, Arabloo, J, Arian, ND, Arora, M, Asaad, M, Ausloos, M, Awan, AT, Ayano, G, Aynalem, GL, Azari, S, Darshan, BB, Badiye, AD, Baig, AA, Bakhshaei, MH, Banach, M, Banik, PC, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Basu, S, Bayati, M, Bazargan-Hejazi, S, Behzadifar, M, Bekuma, TT, Bennett, DA, Bensenor, IM, Berfield, KSS, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bibi, S, Bijani, A, Bintoro, BS, Biondi, A, Birara, S, Braithwaite, D, Brenner, H, Brunoni, AR, Burkart, K, Butt, ZA, Caetano dos Santos, FL, Alberto Camera, L, Car, J, Cardenas, R, Carreras, G, Carrero, JJ, Castaldelli-Maia, JM, Cattaruzza, MSS, Chang, J-C, Chen, S, Chu, D-T, Chung, S-C, Cirillo, M, Costa, VM, Couto, RAS, Dadras, O, Dai, X, Damasceno, AAM, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Gela, JD, Davletov, K, Molla, MD, Dessie, GA, Desta, AA, Dharmaratne, SD, Dianatinasab, M, Diaz, D, Hoa, TD, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Kalan, ME, Edvardsson, K, Elbarazi, I, El Tantawi, M, Esmaeilnejad, S, Fadhil, I, Faraon, EJA, Farinha, CSES, Farwati, M, Farzadfar, F, Fazlzadeh, M, Feigin, VL, Feldman, R, Prendes, CF, Ferrara, P, Filip, I, Filippidis, F, Fischer, F, Flor, LS, Foigt, NA, Folayan, MO, Foroutan, M, Gad, MM, Gaidhane, AM, Gallus, S, Geberemariyam, BS, Ghafourifard, M, Ghajar, A, Ghashghaee, A, Giampaoli, S, Gill, PS, Glozah, FN, Gnedovskaya, EV, Golechha, M, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Greaves, F, Guha, A, Guo, Y, Gupta, B, Das Gupta, R, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Haider, MR, Hamadeh, RR, Hankey, GJ, Hargono, A, Hartono, RK, Hassankhani, H, Hay, SI, Heidari, G, Herteliu, C, Hezam, K, Hird, TR, Hole, MK, Holla, R, Hosseinzadeh, M, Hostiuc, S, Househ, M, Hsiao, T, Huang, J, Iannucci, VC, Ibitoye, SE, Idrisov, B, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Irvani, SSN, Islam, JY, Islam, RM, Shariful Islam, Sheikh, Islami, F, Iso, H, Itumalla, R, Iwagami, M, Jaafari, J, Jain, V, Jakovljevic, M, Jang, S-I, Janjani, H, Jayaram, S, Jeemon, P, Jha, RP, Jonas, JB, Joo, T, Jurisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kanchan, T, Kandel, H, Kapoor, N, Karimi, SE, Katikireddi, SV, Kebede, HK, Kelkay, B, Kennedy, RD, Khoja, AT, Khubchandani, J, Kim, GR, Kim, Y-E, Kimokoti, RW, Kivimaki, M, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Lacey, B, Lam, JO, Landires, I, Lasrado, S, Lauriola, P, Lee, DW, Lee, YH, Leung, J, Li, S, Lin, H, Linn, S, Liu, W, Lopez, AD, Lopukhov, PD, Lorkowski, S, Lugo, A, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Manjunatha, N, Mansouri, B, Mansournia, MA, Martinez-Raga, J, Martini, S, Mathur, MR, Medina-Solis, CE, Mehata, S, Mendoza, W, Menezes, RG, Meretoja, A, Meretoja, TJ, Miazgowski, B, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Mirzaei-Alavijeh, M, Misra, S, Moghadaszadeh, M, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Monasta, L, Moni, MA, Moradi, G, Moradi-Lakeh, M, Moradzadeh, R, Morrison, SD, Mossie, TB, Mubarik, S, Mullany, EC, Murray, CJL, Naghavi, M, Naghshtabrizi, B, Nair, S, Nalini, M, Nangia, V, Naqvi, AA, Swamy, SN, Naveed, M, Nayak, S, Nayak, VC, Nazari, J, Nduaguba, SO, Kandel, SN, Cuong, TN, Huong, LTN, Son, HN, Trang, HN, Nixon, MR, Nnaji, CA, Norrving, B, Noubiap, JJ, Nowak, 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