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1. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Collaborators, GBD 2016 Neurology, Feigin, Valery L, Nichols, Emma, Alam, Tahiya, Bannick, Marlena S, Beghi, Ettore, Blake, Natacha, Culpepper, William J, Dorsey, E Ray, Elbaz, Alexis, Ellenbogen, Richard G, Fisher, James L, Fitzmaurice, Christina, Giussani, Giorgia, Glennie, Linda, James, Spencer L, Johnson, Catherine Owens, Kassebaum, Nicholas J, Logroscino, Giancarlo, Marin, Benoît, Mountjoy-Venning, W Cliff, Nguyen, Minh, Ofori-Asenso, Richard, Patel, Anoop P, Piccininni, Marco, Roth, Gregory A, Steiner, Timothy J, Stovner, Lars Jacob, Szoeke, Cassandra EI, Theadom, Alice, Vollset, Stein Emil, Wallin, Mitchell Taylor, Wright, Claire, Zunt, Joseph Raymond, Abbasi, Nooshin, Abd-Allah, Foad, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Aboyans, Victor, Abraha, Haftom Niguse, Acharya, Dilaram, Adamu, Abdu A, Adebayo, Oladimeji M, Adeoye, Abiodun Moshood, Adsuar, Jose C, Afarideh, Mohsen, Agrawal, Sutapa, Ahmadi, Alireza, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemi, Rufus Olusola, Akseer, Nadia, Al-Eyadhy, Ayman, Salman, Rustam Al-Shahi, Alahdab, Fares, Alene, Kefyalew Addis, Aljunid, Syed Mohamed, Altirkawi, Khalid, Alvis-Guzman, Nelson, Anber, Nahla Hamed, Antonio, Carl Abelardo T, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Asayesh, Hamid, Asghar, Rana Jawad, Atalay, Hagos Tasew, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayuk, Tambe B, Badawi, Alaa, Banach, Maciej, Banoub, Joseph Adel Mattar, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Baune, Bernhard T, Bedi, Neeraj, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Bennett, Derrick A, Bensenor, Isabela M, Berhane, Adugnaw, Beuran, Mircea, Bhattacharyya, Krittika, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Blazes, Christopher Kynrint, Brayne, Carol, Butt, Zahid A, Campos-Nonato, Ismael R, and Cantu-Brito, Carlos
Subjects: Neurosciences, Headaches, Pain Research, Aging, Brain Disorders, Prevention, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Neurological, Good Health and Well Being, Adult, Age Factors, Aged, Aged, 80 and over, Cause of Death, Dementia, Disability Evaluation, Female, Global Burden of Disease, Humans, Incidence, Male, Middle Aged, Nervous System Diseases, Prevalence, Quality-Adjusted Life Years, Risk Factors, Sex Factors, Socioeconomic Factors, GBD 2016 Neurology Collaborators, Clinical Sciences, Neurology & Neurosurgery
Abstract: BackgroundNeurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders.MethodsWe estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach.FindingsGlobally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247-308]) and second leading cause of deaths (9·0 million [8·8-9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34-44] and DALYs by 15% [9-21]) whereas their age-standardised rates decreased (deaths by 28% [26-30] and DALYs by 27% [24-31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6-46·1]), migraine (16·3% [11·7-20·8]), Alzheimer's and other dementias (10·4% [9·0-12·1]), and meningitis (7·9% [6·6-10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05-1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5-90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8-35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8-17·5] of DALYs are risk attributable).InterpretationGlobally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies.FundingBill & Melinda Gates Foundation.
Published: 2019

2. 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, Social Determinants of Health, Prevention, 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, Persons with Disabilities, 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, Disabled Persons, 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

3. 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

4. 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, Behavioral and Social Science, Women's Health, Mental Health, Brain Disorders, Burden of Illness, Neurosciences, Aging, 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, Persons with Disabilities, 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, Disabled Persons, 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

5. The Effect of the COVID-19 Pandemic on the Social Inequalities of Health Care Use in Hungary: A Nationally Representative Cross-Sectional Study

Author: Bayu Begashaw, Bekele, Bahaa Aldin, Alhaffar, Rahul Naresh, Wasnik, and János, Sándor
Subjects: Adult, Hungary, Cross-Sectional Studies, Socioeconomic Factors, SARS-CoV-2, COVID-19, Humans, Delivery of Health Care, Pandemics
Abstract: The social representation of restricted health care use during the COVID-19 pandemic has not been evaluated properly yet in Hungary.Our study aimed to quantify the effect of COVID-19 pandemic measures on general practitioner (GP) visits, specialist care, hospitalization, and cost-related prescription nonredemption (CRPNR) among adults, and to identify the social strata susceptible to the pandemic effect.This cross-sectional study was based on nationally representative data of 6611 (NWhile the CRPNR did not change, the frequency of GP visits, specialist care, and hospitalization rates was remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic. Roma proved to be not specifically affected by the pandemic in any studied aspect, and the pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (iORPrimary educated and widowed adults did not follow the general trend, and their prepandemic health care use was not reduced during the pandemic. This shows that although the management of pandemic health care use restrictions was implemented by not increasing social inequity, the drug availability for primary educated individuals could require more support.
Published: 2021

6. Exclusive breastfeeding cessation and associated factors among employed mothers in Dukem town, Central Ethiopia

Author: Habtemu Jarso, Tolossa Kebede, Bayu Begashaw Bekele, and Kifle Woldemichael
Subjects: Adult, Employment, Cessation, Time Factors, Full-time, Breastfeeding, Dukem town, Breast milk, Logistic regression, Young Adult, Work time, Pregnancy, Surveys and Questionnaires, Prevalence, Humans, Medicine, Cities, Employed women, business.industry, Research, lcsh:Public aspects of medicine, Infant, Newborn, lcsh:RJ1-570, Obstetrics and Gynecology, lcsh:Pediatrics, lcsh:RA1-1270, Odds ratio, Exclusive breastfeeding, Confidence interval, Breast Feeding, Cross-Sectional Studies, Socioeconomic Factors, Private organization, Pediatrics, Perinatology and Child Health, Female, Ethiopia, business, Demography
Abstract: Background Employed women tend to exclusively breastfeed less than non-employed women. Early returning to work has been major reason why employed women stop exclusive breastfeeding. The aim of this study was to investigate exclusive breastfeeding (EBF) cessation and associated factors among employed mothers in Dukem town, Central Ethiopia. Methods A cross-sectional study was conducted from February to March 2015 using total sample of 313 randomly selected permanently employed women. Information regarding participants’ work-related factors, health service and sociodemographic factors were collected by face to face interview using structured questionnaire. Data were checked for completeness, entered and analyzed by SPSS version 20. Binary logistic regression was done to identify factors associated with exclusive breastfeeding cessation. The strength of association was measured using odds ratio with 95% confidence intervals. Results Prevalence of exclusive breastfeeding cessation was 75.7% (95% CI 71.0, 80.5%). Having a short duration of maternity leave (AOR 9.3; 95% CI 3.8, 23), being a full time employee (AOR 3.5; 95% CI 1.7, 11), being private organization employee (AOR=2.1, 95% CI(1, 4.3)), lack of flexible work time (AOR 3.0; 95% CI 1.2, 7.5), not pumping breast milk (AOR 4.3; 95% CI 1.7, 11), lack of a lactation break (AOR 6.7; 95% CI 3,14.5) and work place far away from her child (AOR 3.1; 95% CI 3.1, 6.3), were significantly associated with cessation of EBF among employed mothers. Conclusion Prevalence of exclusive breastfeeding cessation was much higher than the international and national expectation. The concerned governmental bodies should consider improving the legislation of the 3 months postpartum maternity leave to reduce employed mother’s exclusive breastfeeding cessation.
Published: 2020

7. Prevalence of poor sleep quality in the Ethiopian population: a systematic review and meta-analysis

Author: David Warren Spence, Seithikurippu R. Pandi-Perumal, Dilshad Manzar, Ahmed S. BaHammam, Abdulrhman Albougami, Mohammed Salahuddin, Bayu Begashaw Bekele, and Majumi M Noohu
Subjects: Adult, Sleep Wake Disorders, medicine.medical_specialty, media_common.quotation_subject, Population, Developing country, Scientific literature, 03 medical and health sciences, 0302 clinical medicine, Surveys and Questionnaires, Environmental health, Epidemiology, medicine, Humans, Quality (business), education, Developing Countries, Poverty, Aged, media_common, education.field_of_study, business.industry, Age Factors, Middle Aged, Sleep in non-human animals, Cross-Sectional Studies, 030228 respiratory system, Otorhinolaryngology, Meta-analysis, Ethiopia, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract: Only a limited amount of data is available from lower-income countries regarding the prevalence of poor quality of sleep. This meta-analysis of the scientific literature was performed to estimate the pooled prevalence of poor sleep quality in the Ethiopian population. The study protocol followed was the Preferred Reporting of Items for Systematic Review and meta-analysis (PRISMA) statement. The nine studies which met the inclusion criteria provided data based on a total of 9103 participants who were studied at various health and academic institutions. The incidences of self-reported poor sleep quality ranged from 26 to 66.2%. The pooled estimate of poor sleep quality was 53%.There was a high prevalence of reported poor quality of sleep among younger subjects and among those who were studied in community (noninstitutional) settings. The pooled prevalence of poor sleep quality is quite high among Ethiopians.
Published: 2019
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8. 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: 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, Beyene, Addisu Shunu, Bhansali, Anil, Bhatt, Samir, Bhutta, Zulfiqar A, Biadgilign, Sibhatu, Bicer, Burcu Kucuk, Bienhoff, Kelly, Bikbov, Boris, Birungi, Charles, Biryukov, Stan, Bisanzio, Donal, Bizuayehu, Habtamu Mellie, Blyth, Fiona M, Boneya, Dube Jara, Bose, Dipan, Bou-Orm, Ibrahim R, Bourne, Rupert R A, Brainin, Michael, Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul S, Britton, Gabrielle, Brugha, Traolach S, Buchbinder, Rachelle, Bulto, Lemma Negesa Bulto, Bumgarner, Blair R, Butt, Zahid A, Cahuana-Hurtado, Lucero, Cameron, Ewan, Campos-Nonato, Ismael Ricardo, Carabin, Hélène, Cárdenas, Rosario, Carpenter, David O, Carrero, Juan Jesus, Carter, Austin, Carvalho, Felix, Casey, Daniel, Castañeda-Orjuela, Carlos A, Castle, Chris D, Catalá-López, Ferrán, Chang, Jung-Chen, Charlson, Fiona J, Chaturvedi, Pankaj, Chen, Honglei, Chibalabala, Mirriam, Chibueze, Chioma Ezinne, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A, Chowdhury, Rajiv, Christopher, Devasahayam Jesudas, Ciobanu, Liliana G, Cirillo, Massimo, Colombara, Danny, Cooper, Leslie Trumbull, 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Subjects: Male, Dánarmein, AUSTRALIA, GBD, disability-adjusted life-years (DALYs), Heilsufar, Lífslíkur, Epidemiology, Life expectancy, Diseases, Global Health, THERAPY, Global Burden of Disease, Residence Characteristics, Fullorðnir, Cause of Death, Medicine and Health Sciences, Psychology, Konur, Aged, 80 and over, Tölfræði, PLASMODIUM-FALCIPARUM, Aldraðir, Sjúkdómar, Medicine (all), Fatlaðir, Men, Þjóðir, 11 Medical And Health Sciences, ASSOCIATION, Middle Aged, Health policy, PREVALENCE, Sálfræði, disability-adjusted life-years (DALYs), Female, Lýðheilsa, Quality-Adjusted Life Years, Life Sciences & Biomedicine, Global Health Metrics, Adult, AFRICA, Quality of life, People with disabilities, GBD, WEIGHTS, Social ecology, Lífsgæði, Communicable Diseases, World health/statistics, Age Distribution, Life Expectancy, Medicine, General & Internal, SDG 3 - Good Health and Well-being, General & Internal Medicine, Heilbrigðisstefna, Humans, Adults, Disabled Persons, Women, Sex Distribution, Mortality, Noncommunicable Diseases, Aged, Science & Technology, Faraldsfræði, MORTALITY, Wounds and injuries, EPIDEMIOLOGIC TRANSITION, HIV, Áverkar, Karlar, Wounds and Injuries, Félagshagfræði, Older people
Abstract: Correction in: LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017, Background Measurement 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). Methods We 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. Findings The 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. Interpretation At 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., Bill & Melinda Gates Foundation
Published: 2017

9. 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: Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, 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, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. G. A., Awasthi, Ashish, Quintattilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S., Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Ballesteros, Katherine E., Banach, Maciej, Banerjee, Kajori, Bannick, Marlena S., Banoub, Joseph Adel Mattar, Barboza, Miguel A., Barker-Collo, Suzanne Lyu, Barnighausen, Till Winfried, Barquera, Simon, Barrero, Lope, Bassat, Quique, Base, Sanjay, Baune, Bernhard T., Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Beth, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Mcysam, Bejot, Yannick, Bekele, Bayu Begashaw, Belacliew, Abate Bekele, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Berman, Adam F., Bernabe, Eduardo, Bernstein, Robert S., Bertolacci, Gregory J., Beuran, Mircea, Beyranvand, Tina, Bhalla, Ashish, Bhattarai, Suraj, Bhaumik, Sounayadeeep, Bhutta, Zulfiqar A., Biadgo, Belete, Biehl, Molly H., Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shandaat, Bisanzio, Donal, Biswas, Tuhin, Blacker, Brigitte F., Basara, Berrak Bora, Borschmann, Rohan, Bosetti, Cristina, Bozorgmehr, Kayvan, Brady, Oliver J., Brant, Luisa C., Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J. K., Brenner, Hermann, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Busse, Reinhard, Butt, Zahid A., Callender, Charlton S. K. H., Campos-Nonato, Ismael R., Rincon, Julio Cesar Canapuzano, Cano, Jorge, Car, Mate, Cardenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carter, Austin, Carvalho, Felix, Castaneda-Orjuela, Carlos A., Rivas, Jacqueline Castillo, Castle, Chris D., Castro, Clara, Castro, Franz, Catala-Lopez, Ferran, Cerin, Ester, Chaiah, Yazan, Chang, Jung -Chen, Chanson, Fiona J., Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheet, Abdulaal, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chiang, Sheng-Chia, Cicuttini, Flavia M., Ciobanu, Liliana G., Cirillo, Massimo, Cohen, Aaron J., Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Cowie, Benjamin C., Criqui, Michael H., Cromwell, Elizabeth A., Crowe, Christopher Stephen, Crump, John A., Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I., Daryani, Ahmad, Das, Siddharth K., Das Gupta, Rajat, Das Neves, Jose, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C., Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De La Hoz, Fernando Pio, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T., Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Baleen Betsu, Denova-Gutierrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Jarlais, Don C. 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Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J., Kuzin, Igor, Kyu, Hmwe Hmwe, Lad, Deepesh P., Lad, Sheetal D., Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lam, Jennifer O., Lami, Faris Hasan, Van Lansingh, C., Lansky, Sonia, Larson, Heidi J., Latifi, Amman, Lau, Kathryn Mei-Ming, Lazarus, Jeffrey V., Lebedev, Georgy, Lee, Paul H., Leigh, James, Leili, Mostafa, Leshargie, Cheru Tesema, Li, Shanshan, Li, Yichong, Liang, Juan, Lim, Lee-Ling, Lim, Stephen S., Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Lansdale, Chris, Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lunevicius, Raimundas, Ma, Stefan, Macarayan, Erlyn Rachelle King, Mackay, Mark T., MacLachlan, Jennifer H., Maddison, Emilie R., Nadotto, Fabiana, Abd El Razek, Hassan Magdy, Abd El Razek, Muhammed Magdy, Maghavani, Dhaval P., Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C., Marcenes, Wagner, Marczak, Laurie, Marks, Ashley, Marks, Guy B., Martinez, Gabriel, Martins-Melo, Francisco Rogerlandio, Martopullo, Ira, Marz, Winfried, Marron, Melvin B., Masci, Joseph R., Lylassenburg, Benjamin Ballard, Mathur, Manu Raj, Mathur, Prashant, Matzopoulos, Richard, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Cohn, McGrath, John J., McKee, Martin, McMahon, Brian J., Mehata, Suiiesh, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Mekonnen, Tefera C., Melese, Addisu, Melku, Mulugeta, Memiah, Peter T. N., Memish, Ziad A., Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Mensah, George A., Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J., Meshovic, Tbmislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I., Miller, Ted R., Katherine, Molly, Petrie, Miller, Mini, G. K., Mirabi, Parvaneh, Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke Temesgen, Mitiku, Habtamu, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammad, Moslem, Mohammadifard, Noushin, Mohammed, A. 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J., Ngalesoni, Frida N., Ngunjiri, Josephine W., Anh Quynh Nguyen, Nguyen, Grant, Ha Thu Nguyen, Luong Thanh Nguyen, Long Hoang Nguyen, Nguyen, Minh, Trang Huyen Nguyen, Nichols, Emma, Ningnun, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nixon, Molly R., Nolutshungu, Nomonde, Nomura, Shhhei, Norhelin, Ole F., Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Shiadeh, Malihe Nourollahpour, Nowroozi, Mohammad Reza, Nyasulu, Peter S., Odell, Christopher M., Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T., Olivares, Pedro R., Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L., Ong, Sok King Sk, Oren, Eyal, Orpana, Heather M., Ortiz, Alberto, Ortiz, Justin R., Otstavnov, Stanislav S., Overland, Simon, Owolabi, Mayowa Ojo, Ozdemir, Raziye, Mahesh, P. A., Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P., Pakpour, Amir H., Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D. H., Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patton, George C., Paturi, Vishnupriya Rao, Paulson, Katherine R., Pereira, Alexandre, Pereira, David M., Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael R., Piel, Frederic B., Pigott, David M., Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Polinder, Suzanne, Postma, Maarten J., Pourshams, Akram, Poustchi, Hossein, Pujar, Ashwini, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A., Qorbani, Mostafa, Quintana, Hedley, Quistberg, D. 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Bensenor, Im, Berman, Ae, Bertolacci, Gj, Bhutta, Za, Biehl, Mh, Blacker, Bf, Basara, Bb, Brady, Oj, Brant, Lc, Breitborde, Njk, Butt, Za, Callender, Cskh, Campos-Nonato, Ir, Campuzano Rincon, Jc, Cárdenas, R, Carrero, Jj, Castañeda-Orjuela, Ca, Castle, Cd, Catalá-López, F, Chang, Jc, Charlson, Fj, Chiang, Pp, Chisumpa, Vh, Christopher, Dj, Chung, Sc, Cicuttini, Fm, Ciobanu, Lg, Cohen, Aj, Cooper, Lt, Cortesi, Pa, Cowie, Bc, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dadi, Af, Dang, Ak, Dargan, Pi, Das, Sk, Gupta, Rd, Neves, Jd, Dasa, Tt, Dash, Ap, Davis, Ac, Davitoiu, Dv, De La Hoz, Fp, De Neve, Jw, Degefa, Mg, Degfie, Tt, Demoz, Gt, Demtsu, Bb, Denova-Gutiérrez, E, Des Jarlais, Dc, Dessie, Ga, Dharmaratne, Sd, Dinberu, Mt, Ding, El, Dirac, Ma, Doku, Dt, Donnelly, Ca, Dorsey, Er, Doshi, Pp, Doyle, Ke, Driscoll, Tr, Duken, Ee, Duncan, Bb, Duraes, Ar, Eggen, Ae, Ellingsen, Cl, Endries, Ay, Erskine, He, Farinha, Cse, Farzaei, Mh, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Ferrari, Aj, Feyissa, Gt, Foigt, Na, Foreman, Kj, Frank, Td, Fuller, Je, Fürst, T, Furtado, Jm, Futran, Nd, Garcia-Basteiro, Al, Garcia-Gordillo, Ma, Gardner, Wm, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gebremichael, Tg, Gelano, Tf, Geleijnse, Jm, Geramo, Ycd, Gething, Pw, Gezae, Ke, Ghadami, Mr, Gibney, Kb, Gill, Tk, Gillum, Rf, Ginawi, Ia, Goldberg, Em, Gómez-Dantés, H, Gona, Pn, Gopalani, Sv, Gorman, Tm, Goulart, Ac, Gnedovskaya, Ev, Gugnani, Hc, Guimaraes, Al, Gupta, Pc, Gutiérrez, Ra, Haagsma, Ja, Hagos, Tb, Hailegiyorgis, Tt, Hailu, Gb, Hamadeh, Rr, Handal, Aj, Hankey, Gj, Harb, Hl, Haro, Jm, Hassen, Hy, Hay, Rj, Hay, Si, Hegazy, Mi, Henry, Nj, Hibstu, Dt, Hoek, Hw, Hole, Mk, Hosgood, Hd, Hosseini, Sm, Hotez, Pj, Hoy, Dg, Huang, Jj, Hussen, Mm, Irvani, Ssn, Irvine, Cm, Islam, Sm, Jacobsen, Kh, Jain, Sk, Jalu, Mt, James, Sl, Jayatilleke, Au, Jenkins, Kj, Jha, Rp, Johnson, Co, Johnson, Sc, Jonas, Jb, Jozwiak, Jj, Jungari, Sb, Jürisson, M, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Karyani, Ak, Kefale, At, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Kesavachandran, Cn, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Ma, Khang, Yh, Khater, Mm, Khoja, At, Khosravi, Mh, Kiadaliri, Aa, Kibret, Gd, Kidanemariam, Zt, Kiirithio, Dn, Kim, Ye, Kim, Yj, Kimokoti, Rw, Kivimäki, M, Knudsen, Ak, Kocarnik, Jm, Kopec, Ja, Koul, Pa, Kravchenko, Ma, Kumar, Ga, Kutz, Mj, Kyu, Hh, Lad, Dp, Lad, Sd, Lal, Dk, Lam, Jo, Lami, Fh, Lansingh, Vc, Larson, Hj, Lau, Km, Lazarus, Jv, Lee, Ph, Leshargie, Ct, Lim, Ll, Limenih, Ma, Lopez, Ad, Lotufo, Pa, Macarayan, Erk, Mackay, Mt, Maclachlan, Jh, Maddison, Er, Maghavani, Dp, Malta, Dc, Manda, Al, Mandarano-Filho, Lg, Mansournia, Ma, Mapoma, Cc, Maravilla, Jc, Marks, Gb, Martins-Melo, Fr, März, W, Marzan, Mb, Masci, Jr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mcmahon, Bj, Mehndiratta, Mm, Mehta, Km, Mekonnen, Tc, Memiah, Ptn, Memish, Za, Mengistu, Dt, Mensah, Ga, Mereta, St, Meretoja, Tj, Mezgebe, Hb, Millear, Ai, Miller, Tr, Miller-Petrie, Mk, Mini, Gk, Mirrakhimov, Em, Misganaw, At, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Moreno Velásquez, I, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Muchie, Kf, Mueller, Uo, Mumford, Je, Musa, Ki, Nachega, Jb, Nansseu, Jr, Nascimento, Br, Negoi, Ri, Newton, Crj, Ngalesoni, Fn, Ngunjiri, Jw, Nguyen, Aq, Nguyen, Ht, Nguyen, Lh, Nguyen, Th, Ningrum, Dna, Nirayo, Yl, Nixon, Mr, Norheim, Of, Noubiap, Jj, Nouri, Hr, Nourollahpour Shiadeh, M, Nowroozi, Mr, Odell, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Orpana, Hm, Ortiz, Jr, Øverland, S, Owolabi, Mo, Özdemir, R, P A, M, Pakhare, Ap, Pakpour, Ah, Pandian, Jd, Park, Ek, Parry, Cdh, Patton, Gc, Paturi, Vr, Paulson, Kr, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Postma, Mj, Purcell, Ca, Quistberg, Da, Rade, Kw, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahman, Mhu, Rahman, Ma, Rai, Rk, Ranabhat, Cl, Rao, Pc, Rawaf, Dl, Razo-García, C, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Robinson, Sr, Sahraian, Ma, Saldanha, Rf, Sambala, Ez, Samy, Am, Sanchez-Niño, Md, Santomauro, Df, Santos, Jv, Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sarmiento-Suárez, R, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serván-Mori, E, Shackelford, Ka, Shaheen, Aa, Shaikh, Ma, Shrime, Mg, Siddiqi, Tj, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Pk, Sinha, Dn, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Starodubov, Vi, Stein, Dj, Stewart, Lg, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sur, Pj, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekle, Mg, Temsah, Mh, Teshale, My, Tessema, Ga, Thankappan, Kr, Thrift, Ag, Thurston, Gd, To, Qg, Torre, Ae, Tortajada-Girbés, M, Tovani-Palone, Mr, Tran, Bx, Tran, Kb, Troeger, Ce, Truelsen, Tc, Truong, Nt, Tsadik, Ag, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Updike, Rl, Uthman, Oa, Uzun, Sb, Valdez, Pr, Vasankari, Tj, Vladimirov, Sk, Vollset, Se, Wagner, Gr, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weintraub, Rg, Weldegwergs, Kg, Werkneh, Aa, West, Te, Whiteford, Ha, Wilner, Lb, Wolfe, Cda, Wu, Yc, Wyper, Gma, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yentür, Gk, Yimer, Em, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaman, Sb, Zeleke, Aj, Zenebe, Zm, Zhang, Al, Zuhlke, Lj, and Murray, Cjl.
Subjects: Adult, Male, Adolescent, national age-sex-specific mortality, UNITED-STATES, Global Health, Socioeconomic Factor, Global Burden of Disease, GBD, causes of death, Young Adult, Age Distribution, Life Expectancy, General & Internal Medicine, Cause of Death, PUBLIC-HEALTH PROBLEM, mortality, 282 causes global burden of disease, Sex Distribution, Child, Aged, Aged, 80 and over, BARRIERS, DEMENTIA, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, TRENDS, PREVENTION, PREVALENCE, ALZHEIMERS-DISEASE, INDIVIDUALS, 3121 General medicine, internal medicine and other clinical medicine, Child, Preschool, REGISTRATION, Female, Human medicine, Human
Abstract: Background Global 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. Methods The 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 (CODErn), 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. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) 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 186% (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% (7.08.8). The number of deaths for CMNN causes decreased by 222% (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, respirator}, 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. Interpretation Improvements 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. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

10. The Effect of Haplotypes in the CETP and LIPC Genes on the Triglycerides to HDL-C Ratio and Its Components in the Roma and Hungarian General Populations

Author: Peter Piko, Szilvia Fiatal, Nardos Abebe Werissa, Bayu Begashaw Bekele, Gabor Racz, Zsigmond Kosa, Janos Sandor, and Roza Adany
Subjects: Adult, Male, haplotype, Roma, lcsh:QH426-470, Genotype, TG/HDL-C ratio, LIPC, Polymorphism, Single Nucleotide, Article, Gene Frequency, single nucleotide polymorphism, high-density lipoprotein cholesterol, cardiometabolic risk, CETP, Ethnicity, Humans, Genetic Predisposition to Disease, triglyceride, Alleles, Triglycerides, Hungary, Cholesterol, HDL, cetp, Lipase, Middle Aged, Cholesterol Ester Transfer Proteins, lcsh:Genetics, Hungarian general, Haplotypes, lipids (amino acids, peptides, and proteins), Female, Lipoproteins, HDL, lipc
Abstract: Background: The triglycerides (TG) to high-density lipoprotein (HDL)-cholesterol (HDL-C) ratio (TG/HDL-C) is a well-known predictor for cardiovascular diseases (CVDs) with great heritability background. The cholesteryl ester transfer protein (CETP) and hepatic lipase (LIPC) gene affect TG/HDL-C ratio. This study aims to explore the association between haplotypes (H) in CETP (based on 5 single nucleotide polymorphisms (SNPs)) and LIPC (based on 6 SNPs) genes and the TG/HDL-C ratio and its components, among Roma and Hungarian general populations. Methods: The prevalence of haplotypes and their effect on HDL-C, TG and TG/HDL-C ratio were calculated in both populations and compared. Results: Ten haplotypes in CETP and 6 in LIPC gene were identified. Three haplotypes in CETP and 3 in LIPC have significant effect on HDL-C level, whereas two in CETP and 3 in LIPC on TG level. The H6 in CETP (β = 0.52, p = 0.015; odds ratio (OR) = 1.87, p = 0.009) and H5 in LIPC (β = 0.56, p < 0.001; OR = 1.51, p = 0.002) have a significant increasing effect on TG/HDL-C ratio and have shown higher prevalence among the Roma, as compared to Hungarian general population. The H2 in the CETP gene has a decreasing effect on the TG/HDL-C ratio (OR = 0.58, p = 0.019) and is significantly less frequent among the Roma. Conclusions: Accumulation of harmful haplotypes in CETP and LIPC genes might have a role in the elevated TG/HDL-C ratio in the Roma population, which contributes to a higher risk in the development of cardiovascular diseases.
Published: 2020

11. 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 J L, Callender, Charlton S K H, 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 M E, 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, Atique, Suleman, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Banach, Maciej, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gilles, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Biswas, Tuhin, Bizuneh, Hailemichael, Bleyer, Archie, Basara, Berrak Bora, Bosetti, Cristina, Boufous, Soufiane, Brady, Oliver J, Bragazzi, Nicola Luigi, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Brewer, Jerry D, Briant, Paul Svitil, Britton, Gabrielle, Burstein, Roy, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christopher, Devasahayam J, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Collado-Mateo, Daniel, Constantin, Maria-Magdalena, Conti, Sara, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cromwell, Elizabeth, Crowe, Christopher Stephen, Cukelj, Petra, Cunningham, Matthew, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De Leo, Diego, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Dessie, Getenet Ayalew, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Ding, Eric L, Dinsa, Girmaye Deye, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dolan, Kate A, Doyle, Kerrie E, Driscoll, Tim R, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, El-Khatib, Ziad, Elyazar, Iqbal Rf, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhim, Hamed, Farag, Tamer, Faramarzi, Mahbobeh, Fareed, Mohammad, Farinha, Carla Sofia E Sá, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Fay, Kairsten A, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Feizy, Fariba, Fenny, Ama P, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Feyissa, Garumma Tolu, Filip, Irina, Finegold, Samuel, Fischer, Florian, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Fornari, Carla, Fürst, Thomas, Fukumoto, Takeshi, Fuller, John E, Fullman, Nancy, Gakidou, Emmanuela, Gallus, Silvano, Gamkrelidze, Amiran, Ganji, Morsaleh, Gankpe, Fortune Gbetoho, 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Subjects: Adult, Male, Population Density, GBD, population, fertility, Adolescent, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, Global Health, Global Burden of Disease, Young Adult, Child, Preschool, General & Internal Medicine, Female, Human medicine, Mortality, Child, Population Growth, Birth Rate, Aged, Human, Maternal Age
Abstract: Background Population 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. Methods We 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-cotnponent 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. Findings From 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 O7% 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 (I F030; 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. TF030 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. Interpretation Population 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. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

12. Health Care Seeking Behavior in Southwest Ethiopia

Author: Fasil Tessema, Bayu Begashaw, and Hailay Abrha Gesesew
Subjects: Male, Rural Population, Urban Population, Cross-sectional study, lcsh:Medicine, Logistic regression, Severity of Illness Index, Health Services Accessibility, Geographical Locations, 0302 clinical medicine, Environmental protection, Surveys and Questionnaires, Health care, Medicine and Health Sciences, Medicine, Public and Occupational Health, 030212 general & internal medicine, Young adult, lcsh:Science, Multidisciplinary, Ecology, Middle Aged, Socioeconomic Aspects of Health, Urban ecology, Research Design, Income, Marital status, Female, 0305 other medical science, Research Article, Adult, Census, Adolescent, Research and Analysis Methods, Interviews as Topic, Young Adult, 03 medical and health sciences, Environmental health, Severity of illness, Humans, Urban Ecology, Social determinants of health, Behavior, Health Care Policy, Survey Research, 030505 public health, Marital Status, business.industry, lcsh:R, Ecology and Environmental Sciences, Biology and Life Sciences, Patient Acceptance of Health Care, Health Care, Cross-Sectional Studies, Health Care Facilities, People and Places, Africa, lcsh:Q, Ethiopia, Health Statistics, Morbidity, business
Abstract: Background Rural and urban populations have disparate socio-demographic and economic characteristics, which have an influence on equity and their health seeking behavior. We examined and compared the health care seeking behavior for perceived morbidity between urban and rural households in Southwest Ethiopia. Methods Analytic cross-sectional study was conducted among urban and rural households living in Esera district of Southwest Ethiopia. A random sample of 388 head of households (126 urban and 262 rural) were selected. A pretested and structured questionnaire was used for data collection with face-to-face interview. In addition to descriptive methods, binary logistic regression was used to identify factors associated with health seeking behavior at p value of less than 0.05. Results Of the sample household heads, 377 (97.2%) (119 urban and 258 rural) were successfully interviewed. Among these, 58.4% (95% CI, 53.3-63.3%) of the households sought care from modern health care that was lower among rural (48.1%) than urban (80.7%) households. The prevalence of self-treatment was 35.3% in urban and 46.1% in rural households. Among the factors considered for modern health care utilization, higher monthly income (AOR, 5.6; 95% CI, 2.04-15.4), perceived severity of disease (AOR, 2.5; 95% CI, 1.1-5.8), acute duration of disease (AOR, 8.9; 95% CI, 2.4-33.3) and short distance from health facilities (AOR, 3; 95% CI, 1.2-8.4) among rural and being married (AOR, 11.3; 95% CI, 1.2-110.2) and perceived severity of disease (AOR, 6.6; 95% CI, 1.1-10.9) among urban households showed statistically significant association. Conclusions The general health seeking behavior of households on perceived morbidity was satisfactory but lower in rural compared to urban households. Self-medication was also widely practiced in the study area. The findings signal the need to work more on accessibility and promotion of healthcare seeking behavior especially among rural households.
Published: 2016
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13. 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: Naghavi, Mohsen, Abajobir, Amanuel Alemu, Abbafati, Cristiana, Abbas, Kaja M., Abd-Allah, Foad, Abera, Semaw Ferede, Aboyans, Victor, Adetokunboh, Olatunji, Arnlov, Johan, Afshin, Ashkan, Agrawal, Anurag, Kiadaliri, Aliasghar Ahmad, Ahmadi, Alireza, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Aiyar, Sneha, Al-Eyadhy, Ayman, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alene, Kefyalew Addis, Ali, Syed Danish, Alizadeh-Navaei, Reza, Alkaabi, Juma M., Alkerwi, Ala'a, Alla, Francois, 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, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon W., Atey, Tesfay Mehari, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G. Arthur, Awasthi, Ashish, Paulina, Beatriz, Quintanilla, Ayala, Bejot, Yannick, 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, Bekele, Bayu Begashaw, Bell, Michelle L., Bennett, James R., Bensenor, Isabela M., Berhane, Adugnaw, Bernabe, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Bhatt, Samir, Biadgilign, Sibhatu, Bienhoff, Kelly, Bikbov, Boris, Bisanzio, Donal, Bourne, Rupert R. A., Breitborde, Nicholas J. K., Negesa, Lemma, Bulto, Bulto, Bumgarner, Blair R., Butt, Zahid A., Cardenas, Rosario, Cahuana-Hurtado, Lucero, Cameron, Ewan, Cesar Campuzano, Julio, Car, Josip, Jesus Carrero, Juan, Carter, Austin, Casey, Daniel C., Castaneda-Orjuela, Carlos A., Catala-Lopez, Ferran, Charlson, Fiona J., Chibueze, Chioma Ezinne, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A., Christopher, Devasahayam Jesudas, Ciobanu, Liliana G., Cirillo, Massimo, Cohen, Aaron J., Colombara, Danny, Cooper, Cyrus, Cowie, Benjamin C., Criqui, Michael H., Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I., das Neves, Jose, Davitoiu, Dragos V., Davletov, Kairat, de Courten, Barbora, Degenhardt, Louisa, Deiparine, Selina, Deribe, Kebede, Deribew, Amare, Dey, Subhojit, Dicker, Daniel, Ding, Eric L., Djalalinia, Shirin, Huyen Phuc Do, Huyen Phuc Do, Doku, David Teye, Douwes-Schultz, Dirk, Driscoll, Tim R., Dubey, Manisha, Duncan, Bruce Bartholow, Echko, Michelle, El-Khatib, Ziad Ziad, Ellingsen, Christian Lycke, Enayati, Ahmadali, Erskine, Holly E., Eskandarieh, Sharareh, Esteghamati, Alireza, Ermakov, Sergey P., Estep, Kara, E Sa Farinha, Carla Sofia, Faro, Andre, Farzadfar, Farshad, Feigin, Valery L., Fereshtehnejad, Seyed-Mohammad, Fernandes, Joao C., Ferrari, Alize J., Feyissa, Tesfaye Regassa, Filip, Irina, Finegold, Samuel, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Foigt, Nataliya, Frank, Tahvi, Fraser, Maya, Fullman, Nancy, Furst, Thomas, Furtado, Joao M., Gakidou, Emmanuela, Garcia-Basteiro, Alberto L., Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremichael, Delelegn Yilma, Geleijnse, Johanna M., Genova-Maleras, Ricard, Gesesew, Hailay Abrha, Gething, Peter W., Gillum, Richard F., Ginawi, Ibrahim Abdelmageem Mohamed, Giref, Ababi Zergaw, Giroud, Maurice, Giussani, Giorgia, Godwin, William W., Gold, Audra L., Goldberg, Ellen M., Gona, Philimon N., Gopalani, Sameer Vali, Gouda, Hebe N., Goulart, Alessandra Carvalho, Griswold, Max, Gupta, Prakash C., Gupta, Rajeev, Gupta, Tanush, Gupta, Vipin, Haagsma, Juanita A., Hafezi-Nejad, Nima, Hailu, Alemayehu Desalegne, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hambisa, Mitiku Teshome, Hamidi, Samer, Hammami, Mouhanad, Hancock, Jamie, Handal, Alexis J., Hankey, Graeme J., Hao, Yuantao, Harb, Hilda L., Hareri, Habtamu Abera, Hassanvand, Mohammad Sadegh, Havmoeller, Rasmus, Hay, Simon I., He, Fei, Hedayati, Mohammad T., Henry, Nathaniel J., Beatriz Heredia-Pi, Ileana, Herteliu, Claudiu, Hoek, Hans W., Horino, Masako, Horita, Nobuyuki, Hosgood, H. Dean, Hostiuc, Sorin, Hotez, Peter J., Hoy, Damian G., Huynh, Chantal, Iburg, Kim Moesgaard, Ikeda, Chad, Ileanu, Bogdan Vasile, Irenso, Asnake Ararsa, Irvine, Caleb Mackay Salpeter, Jurisson, Mikk, Jacobsen, Kathryn H., Jahanmehr, Nader, Jakovljevic, Mihajlo B., Javanbakht, Mehdi, Jayaraman, Sudha P., Jeemon, Panniyammakal, Jha, Vivekanand, John, Denny, Johnson, Catherine O., Johnson, Sarah Charlotte, Jonas, Jost B., Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Karch, Andre, Karimi, Seyed M., Karimkhani, Chante, Kasaeian, Amir, Kassaw, Nigussie Assefa, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kawakami, Norito, Keiyoro, Peter Njenga, Kemmer, Laura, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khan, Ejaz Ahmad, Khang, Young-Ho, Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kieling, Christian, Kievlan, Daniel, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kissoon, Niranjan, Kivimaki, Mika, Knudsen, Ann Kristin, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Defo, Barthelemy Kuate, Kulikoff, Xie Rachel, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kyu, Hmwe H., Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lambert, Nkurunziza, Lan, Qing, Lansingh, Van C., Larsson, Anders, Lee, Paul H., Leigh, James, Leung, Janni, Levi, Miriam, Li, Yongmei, Kappe, Darya Li, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Stephen S., Liu, Angela, Liu, Patrick Y., Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lucas, Timothy C. D., Ma, Stefan, Macarayan, Erlyn Rachelle King, Maddison, Emilie R., Abd el Razek, Mohammed Magdy, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Manguerra, Helena, Manyazewal, Tsegahun, Mapoma, Chabila C., Marczak, Laurie B., Markos, Desalegn, Martinez-Raga, Jose, Martins-Melo, Francisco Rogerlandio, Martopullo, Ira, McAlinden, Colm, McGaughey, Madeline, McGrath, John J., Mehata, Suresh, Meier, Toni, Meles, Kidanu Gebremariam, Memiah, Peter, Memish, Ziad A., Mengesha, Melkamu Merid, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Millear, Anoushka, Miller, Ted R., Minnig, Shawn, Mirarefin, Mojde, Mirrakhimov, Erkin M., Misganaw, Awoke, Mishra, Shiva Raj, Mohammad, Karzan Abdulmuhsin, Mohammadi, Alireza, Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Mollenkopf, Sarah K., Molokhia, Mariam, Monasta, Lorenzo, Montanez Hernandez, Julio C., Montico, Marcella, Mooney, Meghan D., Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Morrison, Shane D., Morozoff, Chloe, Mountjoy-Venning, Cliff, Mruts, Kalayu Birhane, Muller, Kate, Murthy, Gudlavalleti Venkata Satyanarayana, Musa, Kamarul Imran, Nachega, Jean B., Naheed, Aliya, Naldi, Luigi, Nangia, Vinay, Nascimento, Bruno Ramos, Nasher, Jamal T., Natarajan, Gopalakrishnan, Negoi, Ionut, Ngunjiri, Josephine Wanjiku, Cuong Tat Nguyen, Cuong Tat Nguyen, Grant Nguyen, Grant Nguyen, Minh Nguyen, Minh Nguyen, Quyen Le Nguyen, Quyen Le Nguyen, Trang Huyen Nguyen, Trang Huyen Nguyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Vuong Minh Nong, Vuong Minh Nong, Noubiap, Jean Jacques N., Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Olagunju, Andrew Toyin, Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortiz, Alberto, Osman, Majdi, Ota, Erika, Pa, Mahesh, Pacella, Rosana E., Pakhale, Smita, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Papachristou, Christina, Park, Eun-Kee, Patten, Scott B., Patton, George C., Paudel, Deepak, Paulson, Katherine, Pereira, David M., Perez-Ruiz, Fernando, Perico, Norberto, Pervaiz, Aslam, Petzold, Max, Phillips, Michael Robert, Pigott, David M., Pinho, Christine, Plass, Dietrich, Pletcher, Martin A., Polinder, Suzanne, Postma, Maarten J., Pourmalek, Farshad, Purcell, Caroline, Qorbani, Mostafa, Radfar, Amir, Rafay, Anwar, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rai, Rajesh Kumar, Ranabhat, Chhabi Lal, Rankin, Zane, Rao, Puja C., Rath, Goura Kishor, Rawaf, Salman, Ray, Sarah E., Rehm, Jurgen, Reiner, Robert C., Reitsma, Marissa B., Remuzzi, Giuseppe, Rezaei, Satar, Rezai, Mohammad Sadegh, Rokni, Mohammad Bagher, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A., Rothenbacher, Dietrich, Ruhago, George Mugambage, Saadat, Rizwan S. A. Soheil, Sachdev, Perminder S., Sadat, Nafis, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahathevan, Ramesh, Salama, Joseph, Salamati, Payman, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Dolores Sanchez-Nino, Maria, Santomauro, Damian, Santos, Itamar S., Milicevic, Milena M. Santric, Sartorius, Benn, Satpathy, Maheswar, Shahraz, Saeid, Schmidt, Maria Ines, Schneider, Ione J. C., Schulhofer-Wohl, Sam, Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shackelford, Katya Anne, Shaikh, Masood Ali, Shamsipour, Mansour, Shamsizadeh, Morteza, Islam, Sheikh Mohammed Shariful, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikhbahaei, Sara, Shey, Muki, Shi, Peilin, Shields, Chloe, Shigematsu, Mika, Shiri, Rahman, Shirude, Shreya, Shiue, Ivy, Shoman, Haitham, Shrime, Mark G., Sigfusdottir, Inga Dora, Silpakit, Naris, Silva, Joao Pedro, Singh, Abhishek, Singh, Jasvinder A., Skiadaresi, Eirini, Sligar, Amber, Smith, Alison, Smith, David L., Smith, Mari, Sobaih, Badr H. A., Soneji, Samir, Sorensen, Reed J. D., Soriano, Joan B., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., Stathopoulou, Vasiliki, Steel, Nicholas, Stein, Dan J., Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Strong, Mark, Strub, Bryan, Subart, Michelle, Sufiyan, Muawiyyah Babale, Sunguya, Bruno F., Sur, Patrick J., Swaminathan, Soumya, Sykes, Bryan L., Tabares-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Takahashi, Ken, Takala, Jukka S., Talongwa, Roberto Tchio, Tarawneh, Mohammed Rasoul, Tavakkoli, Mohammad, Taveira, Nuno, Tegegne, Teketo Kassaw, Tehrani-Banihashemi, Arash, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Thakur, J. 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A., Woodbrook, Rachel, Workicho, Abdulhalik, Xavier, Denis, Xiao, Qingyang, Xu, Gelin, Yaghoubi, Mohsen, Yakob, Bereket, Yano, Yuichiro, Yaseri, Mehdi, Yimam, Hassen Hamid, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zegeye, Elias Asfaw, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Anthony Lin, Zhang, Xueying, Zipkin, Ben, Zodpey, Sanjay, Lopez, Alan D., Murray, Christopher J. L., 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, Fare, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alene, Kefyalew Addi, Al-Eyadhy, Ayman, Ali, Syed Danish, Alizadeh-Navaei, Reza, Alkaabi, Juma M, Alkerwi, Ala'a, Alla, Françoi, 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, Lar, 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, Bori, Bisanzio, Donal, Bourne, Rupert R A, Breitborde, Nicholas J K, Bulto, Lemma Negesa Bulto, Bumgarner, Blair R, Butt, Zahid A, Cahuana-Hurtado, Lucero, Cameron, Ewan, Campuzano, Julio Cesar, Car, Josip, Cárdenas, Rosario, Carrero, Juan Jesu, Carter, Austin, Casey, Daniel C, Castañeda-Orjuela, Carlos A, Catalá-López, Ferrán, Charlson, Fiona J, Chibueze, Chioma Ezinne, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A, Christopher, Devasahayam Jesuda, Ciobanu, Liliana G, Cirillo, Massimo, Cohen, Aaron J, 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Qorbani, Mostafa, Quintanilla, Beatriz Paulina Ayala, Radfar, Amir, Rahimi-Movaghar, Vafa, Rahman, Mohammad Hifz Ur, Rahman, Mahfuzar, Rai, Rajesh Kumar, Ranabhat, Chhabi Lal, Rankin, Zane, Rao, Puja C, Rath, Goura Kishor, Rawaf, Salman, Ray, Sarah E, Rehm, Jürgen, Reiner, Robert C, Reitsma, Marissa B, Remuzzi, Giuseppe, Rezaei, Satar, Rezai, Mohammad Sadegh, Rokni, Mohammad Bagher, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rothenbacher, Dietrich, Ruhago, George Mugambage, SA, Rizwan, Saadat, Soheil, Sachdev, Perminder S, Sadat, Nafi, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahathevan, Ramesh, Salama, Joseph, Salamati, Payman, Salomon, Joshua A, Samy, Abdallah M, Sanabria, Juan Ramon, Sanchez-Niño, Maria Dolore, Santomauro, Damian, Santos, Itamar S, Santric Milicevic, Milena M, Sartorius, Benn, Satpathy, Maheswar, Schmidt, Maria Inê, Schneider, Ione J C, Schulhofer-Wohl, Sam, Schutte, Aletta E, Schwebel, David C, Schwendicke, Falk, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shackelford, Katya Anne, Shahraz, Saeid, Shaikh, Masood Ali, Shamsipour, Mansour, Shamsizadeh, Morteza, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikhbahaei, Sara, Shey, Muki, Shields, Chloe, Shigematsu, Mika, Shiri, Rahman, Shirude, Shreya, Shiue, Ivy, Shoman, Haitham, Shrime, Mark G, Sigfusdottir, Inga Dora, Silpakit, Nari, Silva, João Pedro, Singh, Jasvinder A, Singh, Abhishek, Skiadaresi, Eirini, Sligar, Amber, Smith, David L, Smith, Alison, Smith, Mari, Sobaih, Badr H A, Soneji, Samir, Sorensen, Reed J D, Soriano, Joan B, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Stanaway, Jeffrey D, Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J, Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Strong, Mark, Strub, Bryan, Subart, Michelle, Sufiyan, Muawiyyah Babale, Sunguya, Bruno F, Sur, Patrick J, Swaminathan, Soumya, Sykes, Bryan L, Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Takahashi, Ken, Takala, Jukka S, Talongwa, Roberto Tchio, 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Getahun, Wolfe, Charles D A, Woodbrook, Rachel, Workicho, Abdulhalik, Xavier, Deni, Xiao, Qingyang, Xu, Gelin, Yaghoubi, Mohsen, Yakob, Bereket, Yano, Yuichiro, Yaseri, Mehdi, Yimam, Hassen Hamid, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zegeye, Elias Asfaw, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Anthony Lin, Zhang, Xueying, Zipkin, Ben, Zodpey, Sanjay, Giref, Ababi Zergaw, Rafay, Anwar, Tuzcu, Emin Murat, Ermakov, Sergey Petrovich, Shi, Peilin, Gupta, Parkash C, Erasmus MC other, Public Health, Neurosciences, Viðskiptadeild (HR), School of Business (RU), Háskólinn í Reykjavík, Reykjavik University, Mohsen, Naghavi, Amanuel, Alemu, Abajobir, Cristiana, Abbafati, Kaja, M, Abbas, Foad, Abd Allah, Semaw, Ferede, Abera, Victor, Aboyan, Olatunji, Adetokunboh, Johan, Ärnlöv, Ashkan, Afshin, Anurag, Agrawal, Aliasghar, Ahmad, Kiadaliri, Alireza, Ahmadi, Muktar, Beshir, Ahmed, Amani, Nidhal, Aichour, Ibtihel, Aichour, Miloud, Taki, Eddine, Aichour, Sneha, Aiyar, Ayman, Al Eyadhy, Fares, Alahdab, Ziyad, Al Aly, Khurshid, Alam, Noore, Alam, Tahiya, Alam, Kefyalew, Addi, Alene, Syed, Danish, Ali, Reza, Alizadeh Navaei, Juma, M, Alkaabi, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Rajaa, Al Raddadi, Ubai, Alsharif, Khalid, A, Altirkawi, Nelson, Alvis Guzman, Azmeraw, T, Amare, Erfan, Amini, Walid, Ammar, Yaw, Ampem, Amoako, Nahla, Anber, Hjalte, H, Andersen, Catalina, Liliana, Andrei, Sofia, Androudi, Hossein, Ansari, Carl, Abelardo, T, Antonio, Palwasha, Anwari, Megha, Arora, Al, Artaman, Krishna, Kumar, Aryal, Hamid, Asayesh, Solomon, W, Asgedom, Tesfay, Mehari, Atey, Leticia, Avila Burgo, Euripide, Frinel, G, Arthur, Avokpaho, Ashish, Awasthi, Beatriz, Paulina, Ayala, Quintanilla, Yannick, Béjot, Tesleem, Kayode, Babalola, Umar, Bacha, Kalpana, Balakrishnan, Aleksandra, Barac, Miguel, A, Barboza, Suzanne, L, Barker, Collo, Simon, Barquera, Lars, Barregard, Lope, H, Barrero, Bernhard, T, Baune, Neeraj, Bedi, Ettore, Beghi, Bayu, Begashaw, Bekele, Michelle, L, Bell, James, R, Bennett, Isabela, M, Bensenor, Adugnaw, Berhane, Eduardo, Bernabé, Balem, Demtsu, Betsu, Mircea, Beuran, Samir, Bhatt, Sibhatu, Biadgilign, Kelly, Bienhoff, Boris, Bikbov, Donal, Bisanzio, Rupert, R, A, Bourne, Nicholas, J, K, Breitborde, Lemma, Negesa, Bulto, Bulto, Blair, R, Bumgarner, Zahid, A, Butt, Rosario, Cárdena, Lucero, Cahuana Hurtado, Ewan, Cameron, Julio, Cesar, Campuzano, Josip, Car, Juan, Jesu, Carrero, Austin, Carter, Daniel, C, Casey, Carlo, A, Castañeda, Orjuela, Ferrán, Catalá López, Fiona, J, Charlson, Chioma, Ezinne, Chibueze, Odgerel, Chimed Ochir, Vesper, Hichilombwe, Chisumpa, Abdulaal, A, Chitheer, Devasahayam, Jesuda, Christopher, Liliana, G, Ciobanu, Aaron, J, and Cohen
Subjects: Dánarmein, Male, Heilsufar, Dánartíðni, Newborn infants, Lífslíkur, Life expectancy, Communicable diseases, Global Health, Global Burden of Disease, Disasters, Pregnancy, Cause of Death, Psychology, Child, Konur, Aged, 80 and over, Ungbörn, CLIMATE-CHANGE, PLASMODIUM-FALCIPARUM, Kransæðasjúkdómar, Global burden of disease/statistics and numerical data, Medicine (all), Men, Þjóðir, Öndunarfærasjúkdómar, 11 Medical And Health Sciences, Middle Aged, Nutrition Disorders, PREVALENCE, Coronary heart disease, Smitsjúkdómar, Death, Suicide, Cardiovascular diseases, Sálfræði, World health, Child, Preschool, Nýburar, Female, GBD, mortality, Infants, Life Sciences & Biomedicine, Age distribution, Global Health Metrics, Adult, Diarrhea, AFRICA, HUMAN HEALTH, Adolescent, GBD, UNITED-STATES, Socioeconomic factors, Communicable Diseases, Young Adult, Age Distribution, Heilbrigðisvísindi, Medicine, General & Internal, General & Internal Medicine, Humans, QUALITY, Women, Nutrition disorders, INCOME COUNTRIES, Mortality, Noncommunicable Diseases, Aged, Science & Technology, Infant, Newborn, Infant, Respiratory infections, Næringarskortur, ALCOHOL POLICY, mortality, Malaria, Pregnancy Complications, Socioeconomic Factors, Áverkar, Karlar, Wounds and Injuries, Félagshagfræði, Accidental Falls, Cause of death/trends, RESISTANCE
Abstract: Correction: Group Author(s): GBD 2016 Causes Death LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017 Group Author(s): GBD 2016 Dis Injury Incidence LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017, Background Monitoring 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. Methods We 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. Findings The 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. Interpretation The 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., Bill & Melinda Gates Foundation.
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14. 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: Hay, Simon I, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, 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, Kiadaliri, Aliasghar Ahmad, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, 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, Francois, 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, Ampem, Yaw Amoako, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arnlov, 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, Quintanilla, Beatriz Paulina Ayala, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter, Babalola, Tesleem Kayode, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Bannick, Marlena S, Barac, Aleksandra, Barker-Collo, Suzanne L, Barnighausen, Till, Barquera, Simon, Barrero, Lope H, Basu, Sanjay, Battista, Robert, Battle, Katherine E, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Beardsley, Justin, Bedi, Neeraj, Bejot, Yannick, Bekele, Bayu Begashaw, Bell, Michelle L, Bennett, Derrick A, Bennett, James R, Bensenor, Isabela M, Benson, Jennifer, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabe, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Beyene, Addisu Shunu, Bhansali, Anil, Bhatt, Samir, Bhutta, Zulfiqar A, Biadgilign, Sibhatu, Bienhoff, Kelly, Bikbov, Boris, Birungi, Charles, Biryukov, Stan, Bisanzio, Donal, Bizuayehu, Habtamu Mellie, Blyth, Fiona M, Boneya, Dube Jara, Bose, Dipan, Bou-Orm, Ibrahim R, Bourne, Rupert RA, Brainin, Michael, Brayne, Carol EG, Brazinova, Alexandra, Breitborde, Nicholas JK, Briant, Paul S, Britton, Gabrielle, Brugha, Traolach S, Buchbinder, Rachelle, Bulto, Lemma Negesa Bulto, Bumgarner, Blair, Butt, Zahid A, Cahuana-Hurtado, Lucero, Cameron, Ewan, Ricardo Campos-Nonato, Ismael, Carabin, Helene, Cardenas, Rosario, Carpenter, David O, Carrero, Juan Jesus, Carter, Austin, Carvalho, Felix, Casey, Daniel, Castaneda-Orjuela, Carlos A, Rivas, Jacqueline Castillo, Castle, Chris D, Catala-Lopez, Ferran, Chang, Jung-Chen, Charlson, Fiona J, Chaturvedi, Pankaj, Chen, Honglei, Chibalabala, Mirriam, Chibueze, Chioma Ezinne, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A, Chowdhury, Rajiv, Christopher, Devasahayam Jesudas, Ciobanu, Liliana G, Cirillo, Massimo, Colombara, Danny, Cooper, Leslie Trumbull, Cooper, Cyrus, Cortesi, Paolo Angelo, Cortinovis, Monica, Criqui, Michael H, Cromwell, Elizabeth A, Cross, Marita, Crump, John A, Dadi, Abel Fekadu, Dalal, Koustuv, Damasceno, Albertino, Dandona, Lalit, Dandona, Rakhi, Das Neves, Jose, Davitoiu, Dragos V, Davletov, Kairat, De Courten, Barbora, De Leo, Diego, De Steur, Hans, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P, Deribe, Kebede, Deribew, Amare, Des Jarlais, Don C, Dey, Subhojit, Dharmaratne, Samath D, Dhillon, Preet K, Dicker, Daniel, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dorsey, E Ray, Bender Dos Santos, Kadine Priscila, Driscoll, Tim R, Dubey, Manisha, Duncan, Bruce Bartholow, Ebel, Beth E, Echko, Michelle, El-Khatib, Ziad Ziad, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Erskine, Holly E, Eshetie, Setegn, Eshrati, Babak, Esteghamati, Alireza, Estep, Kara, Fanuel, Fanuel Belayneh Bekele, Farag, Tamer, Sofia, Carla, Farinha, Sa, Faro, Andre, Farzadfar, Farshad, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fereshtehnejad, Seyed-Mohammad, Fernandes, Joao C, Ferrari, Alize J, Feyissa, Tesfaye Regassa, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D, Foigt, Nataliya, Foreman, Kyle J, Franklin, Richard C, Frostad, Joseph J, Fullman, Nancy, Furst, Thomas, Furtado, Joao M, Futran, Neal D, Gakidou, Emmanuela, Garcia-Basteiro, Alberto L, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Geleijnse, Johanna M, Geleto, Ayele, Gemechu, Bikila Lencha, Gesesew, Hailay Abrha, Gething, Peter W, Ghajar, Alireza, Gibney, Katherine B, Gillum, Richard F, Ginawi, Ibrahim Abdelmageem Mohamed, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W, Goel, Kashish, Goenka, Shifalika, Goldberg, Ellen M, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gosselin, Richard A, Gotay, Carolyn C, Goto, Atsushi, Goulart, Alessandra Carvalho, Graetz, Nicholas, Gugnani, Harish Chander, Gupta, Rajeev, Gupta, Prakash C, Gupta, Tanush, Gupta, Vipin, Gupta, Rahul, Gutierrez, Reyna A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Alemayehu Desalegne, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hammami, Mouhanad, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Hareri, Habtamu Abera, Haro, Josep Maria, Harun, Kimani M, Harvey, James, Hassanvand, Mohammad Sadegh, Havmoeller, Rasmus, Hay, Roderick J, Hedayati, Mohammad T, Hendrie, Delia, Henry, Nathaniel J, Heredia-Pi, Ileana Beatriz, Heydarpour, Pouria, Hoek, Hans W, Hoffman, Howard J, Horino, Masako, Horita, Nobuyuki, Hosgood, H Dean, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Htet, Aung Soe, Hu, Guoqing, Huang, John J, Huynh, Chantal, Iburg, Kim Moesgaard, Igumbor, Ehimario Uche, Ikeda, Chad, Irvine, Caleb Mackay Salpeter, Jacobsen, Kathryn H, Jahanmehr, Nader, Jakovljevic, Mihajlo B, James, Peter, Jassal, Simerjot K, Javanbakht, Mehdi, Jayaraman, Sudha P, Jeemon, Panniyammakal, Jensen, Paul N, Jha, Vivekanand, Jiang, Guohong, John, Denny, Johnson, Catherine O, Johnson, Sarah Charlotte, Jonas, Jost B, Jurisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Kar, Chittaranjan, Karam, Nadim E, Karch, Andre, Karema, Corine Kakizi, Karimi, Seyed M, Karimkhani, Chante, Kasaeian, Amir, Kassa, Getachew Mullu, Kassebaum, Nicholas J, Kassaw, Nigussie Assefa, Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Keiyoro, Peter Njenga, Kemmer, Laura, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khang, Young-Ho, Khoja, Abdullah T, Khosravi, Ardeshir, Khubchandani, Jagdish, Kieling, Christian, Kim, Yun Jin, Kim, Daniel, Kimokoti, Ruth W, Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna A, Kissoon, Niranjan, Kivimaki, Mika, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kotsakis, Georgios A, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael, Krohn, Kristopher J, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kumar, G Anil, Kumar, Pushpendra, Kyu, Hmwe H, Lager, Anton Carl Jonas, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lambert, Nkurunziza, Lan, Qing, Lansingh, Van C, Larsson, Anders, Leasher, Janet L, Lee, Paul H, Leigh, James, Leshargie, Cheru Tesema, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Stephen S, Linn, Shai, Liu, Angela, Liu, Patrick Y, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Looker, Katharine J, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Timothy CD, Lunevicius, Raimundas, Lyons, Ronan A, Macarayan, Erlyn Rachelle King, Maddison, Emilie R, Abd El Razek, Hassan Magdy, Magis-Rodriguez, Carlos, Mahdavi, Mahdi, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A, Manguerra, Helena, Manhertz, Treh, Mantovani, Lorenzo G, Mapoma, Chabila C, March, Lyn M, Marczak, Laurie B, Martinez-Raga, Jose, Henrique, Paulo, Martins, Viegas, Martins-Melo, Francisco Rogerlndio, Martopullo, Ira, Marz, Winfried, Mathur, Manu Raj, Mazidi, Mohsen, McAlinden, Colm, McGaughey, Madeline, McGrath, John J, Mckee, Martin, Mehata, Suresh, Meier, Toni, Meles, Kidanu Gebremariam, Memiah, Peter, Memish, Ziad A, Mendoza, Walter, Mengesha, Melkamu Merid, Mengistie, Mubarek Abera, Mengistu, Desalegn Tadese, Mensah, George A, Meretoja, Atte, Meretoja, Tuomo J, Mezgebe, Haftay Berhane, Micha, Renata, Millear, Anoushka, Miller, Ted R, Minnig, Shawn, Mirarefin, Mojde, Mirrakhimov, Erkin M, Misganaw, Awoke, Mishra, Shiva Raj, Mitchell, Philip B, Mohammad, Karzan Abdulmuhsin, Mohammadi, Alireza, Mohammed, Shafiu, Mohammed, Kedir Endris, Mohammed, Muktar Sano Kedir, Mohan, Murali BV, Mokdad, Ali H, Mollenkopf, Sarah K, Monasta, Lorenzo, Montanez Hernandez, Julio Cesar, Montico, Marcella, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Mori, Rintaro, Morrison, Shane D, Moses, Mark, Mountjoy-Venning, Cliff, Mruts, Kalayu Birhane, Mueller, Ulrich O, Muller, Kate, Mudoch, Michele E, Murthy, Srinivas, Murthy, Gudlavalleti Venkata Satyanarayana, Musa, Kamarul Imran, Nachega, Jean B, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naidoo, Kovin S, Nangia, Vinay, Nasher, Jamal T, Natarajan, Gopalakrishnan, Negasa, Dumessa Edessa, Negoi, Ionut, Negoi, Ruxandra Irina, Newton, Charles R, Ngunjiri, Josephine Wanjiku, Nguyen, Cuong Tat, Nguyen, Quyen Le, Nguyen, Grant, Nguyen, Trang Huyen, Nguyen, Minh, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nong, Vuong Minh, Norheim, Ole F, Norrving, Bo, Noubiap, Jean Jacques N, Nyandwi, Alypio, Obermeyer, Carla Makhlouf, O'Donnell, Martin J, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olsen, Helen E, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortiz, Alberto, Osborne, Richard H, Osgood-Zimmerman, Aaron, Osman, Majdi, Ota, Erika, Owolabi, Mayowa O, Pa, Mahesh, Pacella, Rosana E, Panda, Basant Kumar, Pandian, Jeyaraj D, Papachristou, Christina, Park, Eun-Kee, Parry, Charles D, Parsaeian, Mahboubeh, Patil, Snehal T, Patten, Scott B, Patton, George C, Paudel, Deepak, Paulson, Katherine, Pearce, Neil, Pereira, David M, Perez, Krystle Marie, Perico, Norberto, Pesudovs, Konrad, Peterson, Carrie Beth, Petri, William Arthur, Petzold, Max, Phillips, Michael Robert, Phipps, Geoffrey, Pigott, David M, Pillay, Julian David, Pinho, Christine, Piradov, Michael A, Plass, Dietrich, Pletcher, Martin A, Popova, Svetlana, Poulton, Richie G, Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Narayan, Purcell, Carrie, Purwar, Manorama, Qorbani, Mostafa, Rabiee, Rynaz HS, Radfar, Amir, Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Mohammad Hifz Ur, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Ranabhat, Chhabi Lal, Rangaswamy, Thara, Rankin, Zane, Rao, Paturi Vishnupriya, Rao, Puja C, Rawaf, Salman, Ray, Sarah E, Reiner, Robert C, Reinig, Nikolas, Reitsma, Marissa, Remuzzi, Giuseppe, Renzaho, Andre MN, Resnikoff, Serge, Rezaei, Satar, Ribeiro, Antonio L, Roba, Hirbo Shore, Robinson, Stephen R, Rojas-Rueda, David, Rokni, Mohammad Bagher, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rothenbacher, Dietrich, Roy, Ambuj, Rubagotti, Enrico, Ruhago, George Mugambage, Saadat, Soheil, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahathevan, Ramesh, Sahraian, Mohammad Ali, Salama, Joseph, Saleh, Muhammad Muhammad, Salomon, Joshua A, Salvi, Sundeep Santosh, Samy, Abdallah M, Sanabria, Juan Ramon, Dolores Sanchez-Nino, Maria, Santomauro, Damian, Santos, Joao Vasco, Santos, Itamar S, Milicevic, Milena M Santric, Sartorius, Benn, Satpathy, Maheswar, Sawhney, Monika, Saxena, Sonia, Schelonka, Kathryn, Schmidt, Maria Ines, Schneider, Ione JC, Schottker, Ben, Schutte, Aletta E, Schwebel, David C, Schwendicke, Falk, Seedat, Soraya, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shaheen, Amira, Shaikh, Masood Ali, Shamsipour, Mansour, Islam, Sheikh Mohammed Shariful, Sharma, Rajesh, Sharma, Jayendra, She, Jun, Shi, Peilin, Shibuya, Kenji, Shields, Chloe, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shirude, Shreya, Shishani, Kawkab, Shoman, Haitham, Siabani, Soraya, Sibai, Abla Mehio, Sigfusdottir, Inga Dora, Silberberg, Donald H, Silva, Joao Pedro, Santos Silva, Diego Augusto, Alves Silveira, Dayane Gabriele, Singh, Jasvinder A, Singh, Virendra, Singh, Om Prakash, Singh, Narinder Pal, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Slepak, Erica Leigh, Smith, David L, Smith, Mari, Sobaih, Badr HA, Sobngwi, Eugene, Soljak, Michael, Sorensen, Reed JD, Moraes Sousa, Tatiane Cristina, Sposato, Luciano A, Sufiyan, Muawiyyah Babale, Abdulkader, Rizwan Suliankatchi, Sunguya, Bruno F, Sur, Patrick J, Swaminathan, Soumya, Sykes, Bryan L, Sylte, Dillon, Szoeke, Cassandra EI, Tabares-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Taffere, Getachew Redae, Takala, Jukka S, Tandon, Nikhil, Tanne, David, Tarekegn, Yihunie L, Tavakkoli, Mohammad, Taveira, Nuno, Taylor, Hugh R, Tegegne, Teketo Kassaw, Tehrani-Banihashemi, Arash, Tekelab, Tesfalidet, Shifa, Girma Temam, Terkawi, Abdullah Sulieman, Tesfaye, Dawit Jember, Tesssema, Belay, Thakur, JS, Thamsuwan, Ornwipa, Theadom, Alice M, Theis, Andrew M, Thomas, Katie E, Thomas, Nihal, Thompson, Robert, Thrift, Amanda G, Tobe-Gai, Ruoyan, Tobollik, Myriam, Tonelli, Marcello, Topor-Madry, Roman, Tortajada, Miguel, Touvier, Mathilde, Traebert, Jefferson, Tran, Bach Xuan, Troeger, Christopher, Truelsen, Thomas, Tsoi, Derrick, Tuzcu, Emin Murat, Tymeson, Hayley, Tyrovolas, Stefanos, Ukwaja, Kingsley Nnanna, Undurraga, Eduardo A, Uneke, Chigozie Jesse, Updike, Rachel, Uthman, Olalekan A, Uzochukwu, Benjamin S Chudi, Van Boven, Job FM, Varughese, Santosh, Vasankari, Tommi, Veerman, Lennert J, Venkatesh, S, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Vijayakumar, Lakshmi, Violante, Francesco S, Vishnu, Abhishek, Vladimirov, Sergey K, Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wadilo, Fiseha, Wakayo, Tolassa, Wallin, Mitchell T, Wang, Yuan-Pang, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Wijeratne, Tissa, Williams, Hywel C, Wiysonge, Charles Shey, Woldeyes, Belete Getahun, Wolfe, Charles DA, Woodbrook, Rachel, Woolf, Anthony D, Workicho, Abdulhalik, Xavier, Denis, Xu, Gelin, Yadgir, Simon, Yaghoubi, Mohsen, Yakob, Bereket, Yan, Lijing L, Yano, Yuichiro, Ye, Pengpeng, Yihdego, Mahari Gidey, Yimam, Hassen Hamid, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yu, Chuanhua, Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zegeye, Elias Asfaw, Zenebe, Zerihun Menlkalew, Zhang, Xueying, Zheng, Yingfeng, Zhou, Maigeng, Zipkin, Ben, Zodpey, Sanjay, Zoeckler, Leo, Zuhlke, Liesl Joanna, Murray, Christopher JL, and Collaborators, GBD DALYs HALE
Subjects: Adult, Aged, 80 and over, Male, 1. No poverty, Middle Aged, Global Health, Communicable Diseases, 3. Good health, Global Burden of Disease, Age Distribution, Life Expectancy, Residence Characteristics, Cause of Death, Humans, Wounds and Injuries, Disabled Persons, Female, sense organs, Quality-Adjusted Life Years, Sex Distribution, Noncommunicable Diseases, Aged
Abstract: Measurement 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).

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14 results on '"Bayu, Begashaw"'

1. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

2. 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

3. 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

4. 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

5. The Effect of the COVID-19 Pandemic on the Social Inequalities of Health Care Use in Hungary: A Nationally Representative Cross-Sectional Study

6. Exclusive breastfeeding cessation and associated factors among employed mothers in Dukem town, Central Ethiopia

7. Prevalence of poor sleep quality in the Ethiopian population: a systematic review and meta-analysis

8. 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

9. 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

10. The Effect of Haplotypes in the CETP and LIPC Genes on the Triglycerides to HDL-C Ratio and Its Components in the Roma and Hungarian General Populations

11. 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

12. Health Care Seeking Behavior in Southwest Ethiopia

13. 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

14. 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

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14 results on '"Bayu, Begashaw"'

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