173 results on '"Aghayan, Sargis A."'
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2. Phylogenomics revealed migration routes and adaptive radiation timing of Holarctic malaria mosquito species of the Maculipennis Group
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Yurchenko, Andrey A., Naumenko, Anastasia N., Artemov, Gleb N., Karagodin, Dmitry A., Hodge, James M., Velichevskaya, Alena I., Kokhanenko, Alina A., Bondarenko, Semen M., Abai, Mohammad R., Kamali, Maryam, Gordeev, Mikhail I., Moskaev, Anton V., Caputo, Beniamino, Aghayan, Sargis A., Baricheva, Elina M., Stegniy, Vladimir N., Sharakhova, Maria V., and Sharakhov, Igor V.
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- 2023
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3. 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
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Murray, Christopher JL, Callender, Charlton SKH, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, and Atique, Suleman
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Health Sciences ,Behavioral and Social Science ,Contraception/Reproduction ,Basic Behavioral and Social Science ,Aging ,Aetiology ,2.4 Surveillance and distribution ,Reproductive health and childbirth ,Good Health and Well Being ,Adolescent ,Adult ,Aged ,Birth Rate ,Child ,Child ,Preschool ,Female ,Global Burden of Disease ,Global Health ,Humans ,Infant ,Infant ,Newborn ,Male ,Maternal Age ,Middle Aged ,Mortality ,Population Density ,Population Growth ,Young Adult ,GBD 2017 Population and Fertility Collaborators ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundPopulation estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods.MethodsWe estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories.FindingsFrom 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4-52·0). The TFR decreased from 4·7 livebirths (4·5-4·9) to 2·4 livebirths (2·2-2·5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3-200·8) since 1950, from 2·6 billion (2·5-2·6) to 7·6 billion (7·4-7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9-1·2) in Cyprus to a high of 7·1 livebirths (6·8-7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07-0·09) in South Korea to 2·4 livebirths (2·2-2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3-0·4) in Puerto Rico to a high of 3·1 livebirths (3·0-3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger.InterpretationPopulation trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress.FundingBill & Melinda Gates Foundation.
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- 2018
4. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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James, Spencer L, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N, Adamu, Abdu A, Adebayo, Oladimeji M, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adib, Mina G, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alouani, Mohamed ML, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arabloo, Jalal, Arauz, Antonio, Aremu, Olatunde, Ariani, Filippo, Armoon, Bahroom, Ärnlöv, Johan, Arora, Amit, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asghar, Rana Jawad, Ataro, Zerihun, Atre, Sachin R, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide FGA, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, and Bali, Ayele Geleto
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Prevention ,2.4 Surveillance and distribution ,Aetiology ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Child ,Child ,Preschool ,Disabled Persons ,Female ,Global Burden of Disease ,Global Health ,Humans ,Incidence ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Middle Aged ,Morbidity ,Prevalence ,Sex Distribution ,Socioeconomic Factors ,Wounds and Injuries ,Young Adult ,GBD 2017 Disease and Injury Incidence and Prevalence Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data.MethodsWe estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting.FindingsGlobally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs s1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]).InterpretationGlobal all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury.FundingBill & Melinda Gates Foundation.
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- 2018
5. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 SDG, Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, and Anwari, Palwasha
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Prevention ,Pediatric ,Good Health and Well Being ,Peace ,Justice and Strong Institutions ,Female ,Global Burden of Disease ,Global Health ,Goals ,Health Status ,Health Status Indicators ,Humans ,Male ,Mortality ,Risk Factors ,Sex Offenses ,Sustainable Development ,United Nations ,GBD 2017 SDG Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundEfforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment.MethodsWe measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator.FindingsThe global median health-related SDG index in 2017 was 59·4 (IQR 35·4-67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6-14·0) to a high of 84·9 (83·1-86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030.InterpretationThe GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains-curative interventions in the case of NCDs-towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions-or inaction-today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.FundingBill & Melinda Gates Foundation.
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- 2018
6. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 Risk Factor, Stanaway, Jeffrey D, Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S, Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adane, Akilew Awoke, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Admasie, Amha, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Agarwal, Gina, Aggarwal, Anju, Aghayan, Sargis Aghasi, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Alahdab, Fares, Alam, Khurshid, Alam, Samiah, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Ali, Komal, Ali, Syed Mustafa, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antó, Josep M, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avokpaho, Euripide FGA, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayer, Rakesh, and Ayuk, Tambe B
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Prevention ,Aetiology ,2.2 Factors relating to the physical environment ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Child ,Child ,Preschool ,Disabled Persons ,Environmental Exposure ,Female ,Global Burden of Disease ,Global Health ,Health Risk Behaviors ,Humans ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Metabolic Diseases ,Middle Aged ,Occupational Diseases ,Occupational Exposure ,Quality-Adjusted Life Years ,Risk Assessment ,Sex Distribution ,Socioeconomic Factors ,Young Adult ,GBD 2017 Risk Factor Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk-outcome associations.MethodsWe used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.FindingsIn 2017, 34·1 million (95% uncertainty interval [UI] 33·3-35·0) deaths and 1·21 billion (1·14-1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6-62·4) of deaths and 48·3% (46·3-50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39-11·5) deaths and 218 million (198-237) DALYs, followed by smoking (7·10 million [6·83-7·37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6·53 million [5·23-8·23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4·72 million [2·99-6·70] deaths and 148 million [98·6-202] DALYs), and short gestation for birthweight (1·43 million [1·36-1·51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3-6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low.InterpretationBy quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.FundingBill & Melinda Gates Foundation.
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- 2018
7. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 Mortality, Dicker, Daniel, Nguyen, Grant, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abdurahman, Ahmed Abdulahi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Agrawal, Anurag, Ahmadi, Mehdi, Ahmadi, Alireza, Ahmadieh, Hamid, Ahmed, Mohamed Lemine Cheikh brahim, Ahmed, Sayem, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Anlay, Degefaye Zelalem, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Megha, and Artaman, Al
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Behavioral and Social Science ,Pediatric ,Prevention ,Basic Behavioral and Social Science ,2.4 Surveillance and distribution ,Aetiology ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Child ,Child ,Preschool ,Female ,Global Burden of Disease ,Global Health ,Humans ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Middle Aged ,Mortality ,Sex Distribution ,Socioeconomic Factors ,Young Adult ,GBD 2017 Mortality Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundAssessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally.MethodsThe GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950.FindingsGlobally, 18·7% (95% uncertainty interval 18·4-19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2-59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5-49·6) to 70·5 years (70·1-70·8) for men and from 52·9 years (51·7-54·0) to 75·6 years (75·3-75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5-51·7) for men in the Central African Republic to 87·6 years (86·9-88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3-238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6-42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2-5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development.InterpretationThis analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing.FundingBill & Melinda Gates Foundation.
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- 2018
8. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Kyu, Hmwe Hmwe, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abil, Olifan Zewdie, Aboyans, Victor, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N, Adamu, Abdu A, Adebayo, Oladimeji M, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Anurag, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alonso, Jordi, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Aminde, Leopold N, Amini, Erfan, Amiresmaili, Mohammadreza, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Arora, Amit, Arora, Megha, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide FGA, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, and Balakrishnan, Kalpana
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Prevention ,Aging ,Good Health and Well Being ,Aged ,Communicable Diseases ,Disabled Persons ,Female ,Global Burden of Disease ,Health Status ,Healthy Lifestyle ,Humans ,Life Expectancy ,Male ,Mortality ,Mortality ,Premature ,Prevalence ,Quality-Adjusted Life Years ,Risk Factors ,Socioeconomic Factors ,Wounds and Injuries ,GBD 2017 DALYs and HALE Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundHow long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years.MethodsWe used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males.FindingsGlobally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2).InterpretationWith increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health.FundingBill & Melinda Gates Foundation.
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- 2018
9. Chromosome-scale Echinococcus granulosus (genotype G1) genome reveals the Eg95 gene family and conservation of the EG95-vaccine molecule
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Korhonen, Pasi K., Kinkar, Liina, Young, Neil D., Cai, Huimin, Lightowlers, Marshall W., Gauci, Charles, Jabbar, Abdul, Chang, Bill C. H., Wang, Tao, Hofmann, Andreas, Koehler, Anson V., Li, Junhua, Li, Jiandong, Wang, Daxi, Yin, Jiefang, Yang, Huanming, Jenkins, David J., Saarma, Urmas, Laurimäe, Teivi, Rostami-Nejad, Mohammad, Irshadullah, Malik, Mirhendi, Hossein, Sharbatkhori, Mitra, Ponce-Gordo, Francisco, Simsek, Sami, Casulli, Adriano, Zait, Houria, Atoyan, Hripsime, de la Rue, Mario Luiz, Romig, Thomas, Wassermann, Marion, Aghayan, Sargis A., Gevorgyan, Hasmik, Yang, Bicheng, and Gasser, Robin B.
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- 2022
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10. The era of reference genomes in conservation genomics
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Formenti, Giulio, Theissinger, Kathrin, Fernandes, Carlos, Bista, Iliana, Bombarely, Aureliano, Bleidorn, Christoph, Čiampor, Fedor, Ciofi, Claudio, Crottini, Angelica, Godoy, José A., Hoglund, Jacob, Malukiewicz, Joanna, Mouton, Alice, Oomen, Rebekah A., Paez, Sadye, Palsbøll, Per, Pampoulie, Christophe, Ruiz-López, María José, Svardal, Hannes, Theofanopoulou, Constantina, de Vries, Jan, Waldvogel, Ann-Marie, Zhang, Goujie, Mazzoni, Camila J., Jarvis, Erich, Bálint, Miklós, Aghayan, Sargis A., Alioto, Tyler S., Almudi, Isabel, Alvarez, Nadir, Alves, Paulo C., Amorim, Isabel R., Antunes, Agostinho, Arribas, Paula, Baldrian, Petr, Berg, Paul R., Bertorelle, Giorgio, Böhne, Astrid, Bonisoli-Alquati, Andrea, Boštjančić, Ljudevit L., Boussau, Bastien, Breton, Catherine M., Buzan, Elena, Campos, Paula F., Carreras, Carlos, Castro, L. FIlipe, Chueca, Luis J., Conti, Elena, Cook-Deegan, Robert, Croll, Daniel, Cunha, Mónica V., Delsuc, Frédéric, Dennis, Alice B., Dimitrov, Dimitar, Faria, Rui, Favre, Adrien, Fedrigo, Olivier D., Fernández, Rosa, Ficetola, Gentile Francesco, Flot, Jean-François, Gabaldón, Toni, Galea Agius, Dolores R., Gallo, Guido R., Giani, Alice M., Gilbert, M. Thomas P., Grebenc, Tine, Guschanski, Katerina, Guyot, Romain, Hausdorf, Bernhard, Hawlitschek, Oliver, Heintzman, Peter D., Heinze, Berthold, Hiller, Michael, Husemann, Martin, Iannucci, Alessio, Irisarri, Iker, Jakobsen, Kjetill S., Jentoft, Sissel, Klinga, Peter, Kloch, Agnieszka, Kratochwil, Claudius F., Kusche, Henrik, Layton, Kara K.S., Leonard, Jennifer A., Lerat, Emmanuelle, Liti, Gianni, Manousaki, Tereza, Marques-Bonet, Tomas, Matos-Maraví, Pável, Matschiner, Michael, Maumus, Florian, Mc Cartney, Ann M., Meiri, Shai, Melo-Ferreira, José, Mengual, Ximo, Monaghan, Michael T., Montagna, Matteo, Mysłajek, Robert W., Neiber, Marco T., Nicolas, Violaine, Novo, Marta, Ozretić, Petar, Palero, Ferran, Pârvulescu, Lucian, Pascual, Marta, Paulo, Octávio S., Pavlek, Martina, Pegueroles, Cinta, Pellissier, Loïc, Pesole, Graziano, Primmer, Craig R., Riesgo, Ana, Rüber, Lukas, Rubolini, Diego, Salvi, Daniele, Seehausen, Ole, Seidel, Matthias, Secomandi, Simona, Studer, Bruno, Theodoridis, Spyros, Thines, Marco, Urban, Lara, Vasemägi, Anti, Vella, Adriana, Vella, Noel, Vernes, Sonja C., Vernesi, Cristiano, Vieites, David R., Waterhouse, Robert M., Wheat, Christopher W., Wörheide, Gert, Wurm, Yannick, Zammit, Gabrielle, Höglund, Jacob, Palsbøll, Per J., Ruiz-López, María J., Zhang, Guojie, and Jarvis, Erich D.
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- 2022
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11. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016
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Griswold, Max G, Fullman, Nancy, Hawley, Caitlin, Arian, Nicholas, Zimsen, Stephanie RM, Tymeson, Hayley D, Venkateswaran, Vidhya, Tapp, Austin Douglas, Forouzanfar, Mohammad H, Salama, Joseph S, Abate, Kalkidan Hassen, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Aboyans, Victor, Abrar, Mohammed Mehdi, Acharya, Pawan, Adetokunboh, Olatunji O, Adhikari, Tara Ballav, Adsuar, Jose C, Afarideh, Mohsen, Agardh, Emilie Elisabet, Agarwal, Gina, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmed, Muktar Beshir, Akibu, Mohammed, Akinyemiju, Tomi, Akseer, Nadia, Asfoor, Deena H Al, Al-Aly, Ziyad, Alahdab, Fares, Alam, Khurshid, Albujeer, Ammar, Alene, Kefyalew Addis, Ali, Raghib, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Allebeck, Peter, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Ammar, Walid, Amoako, Yaw Ampem, Amul, Gianna Gayle Herrera, Andrei, Catalina Liliana, Angus, Colin, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Assadi, Reza, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F, Awasthi, Ashish, Ayele, Henok Tadesse, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Badali, Hamid, Badawi, Alaa, Banach, Maciej, Barker-Collo, Suzanne Lyn, Barrero, Lope H, Basaleem, Huda, Baye, Estifanos, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Béjot, Yannick, Belachew, Abate Bekele, Belay, Saba Abraham, Bennett, Derrick A, Bensenor, Isabela M, Bernabe, Eduardo, Bernstein, Robert S, Beyene, Addisu Shunu, Beyranvand, Tina, Bhaumik, Soumyadeeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bililign, Nigus, Birlik, Sait Mentes, Birungi, Charles, Bizuneh, Hailemichael, Bjerregaard, Peter, Bjørge, Tone, Borges, Guilherme, Bosetti, Cristina, Boufous, Soufiane, Bragazzi, Nicola Luigi, Brenner, Hermann, and Butt, Zahid A
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Epidemiology ,Public Health ,Health Sciences ,Women's Health ,Alcoholism ,Alcohol Use and Health ,Substance Misuse ,Prevention ,Behavioral and Social Science ,Aging ,2.4 Surveillance and distribution ,Stroke ,Cancer ,Oral and gastrointestinal ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Alcohol Drinking ,Cause of Death ,Commerce ,Female ,Global Burden of Disease ,Global Health ,Humans ,Male ,Middle Aged ,Observational Studies as Topic ,Population Surveillance ,Prevalence ,Prospective Studies ,Quality-Adjusted Life Years ,Retrospective Studies ,Risk Assessment ,Risk Factors ,Sex Distribution ,Young Adult ,GBD 2016 Alcohol Collaborators ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundAlcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older.MethodsUsing 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health.FindingsGlobally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2·2% (95% uncertainty interval [UI] 1·5-3·0) of age-standardised female deaths and 6·8% (5·8-8·0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3·8% (95% UI 3·2-4·3) of female deaths and 12·2% (10·8-13·6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2·3% (95% UI 2·0-2·6) and male attributable DALYs were 8·9% (7·8-9·9). The three leading causes of attributable deaths in this age group were tuberculosis (1·4% [95% UI 1·0-1·7] of total deaths), road injuries (1·2% [0·7-1·9]), and self-harm (1·1% [0·6-1·5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27·1% (95% UI 21·2-33·3) of total alcohol-attributable female deaths and 18·9% (15·3-22·6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0·0-0·8) standard drinks per week.InterpretationAlcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.FundingBill & Melinda Gates Foundation.
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- 2018
12. Preliminary investigations of parasite contamination of water sources in Armenia
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Shcherbakov, Oleg V., primary, Aghayan, Sargis A., additional, Gevorgyan, Hasmik S., additional, Abgaryan, Tigran A., additional, Gevorgyan, Ruzanna H., additional, Jiménez-Meléndez, Alejandro, additional, and Robertson, Lucy J., additional
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- 2024
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13. A test of the European Pleistocene refugial paradigm, using a Western Palaearctic endemic bird species
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Drovetski, Sergei V., Fadeev, Igor V., Raković, Marko, Lopes, Ricardo J., Boano, Giovanni, Pavia, Marco, Koblik, Evgeniy A., Lohman, Yuriy V., Red’kin, Yaroslav A., Aghayan, Sargis A., Reis, Sandra, Drovetskaya, Sofya S., and Voelker, Gary
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- 2018
14. Low MSP-1 haplotype diversity in the West Palearctic population of the avian malaria parasite Plasmodium relictum
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Hellgren, Olof, Kelbskopf, Victor, Ellis, Vincenzo A., Ciloglu, Arif, Duc, Mélanie, Huang, Xi, Lopes, Ricardo J., Mata, Vanessa A., Aghayan, Sargis A., Inci, Abdullah, and Drovetski, Sergei V.
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- 2021
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15. Is Toxoplasma gondii a potential risk factor for Alzheimer's disease? A systematic review and meta-analysis
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Nayeri Chegeni, Tooran, Sarvi, Shahabeddin, Moosazadeh, Mahmood, Sharif, Mehdi, Aghayan, Sargis A., Amouei, Afsaneh, Hosseininejad, Zahra, and Daryani, Ahmad
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- 2019
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16. Seroprevalence of Toxoplasma gondii infection in cancer patients: A systematic review and meta-analysis
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Anvari, Davood, Sharif, Mehdi, Sarvi, Shahabeddin, Aghayan, Sargis A., Gholami, Shirzad, Pagheh, Abdol Sattar, Hosseini, Seyed Abdollah, Saberi, Reza, Chegeni, Tooran Nayeri, Hosseininejad, Zahra, and Daryani, Ahmad
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- 2019
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17. A systematic review of Toxoplasma gondii antigens to find the best vaccine candidates for immunization
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Rezaei, Fatemeh, Sarvi, Shahabeddin, Sharif, Mahdi, Hejazi, Seyed Hossein, Pagheh, Abdol sattar, Aghayan, Sargis A., and Daryani, Ahmad
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- 2019
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18. Mortality, morbidity, and hospitalisations due to influenza lower respiratory tract infections, 2017: an analysis for the Global Burden of Disease Study 2017
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Troeger, Christopher E, Blacker, Brigette F., Khalil, Ibrahim A., Zimsen, Stephanie R M, Albertson, Samuel B., Abate, Degu, Abdela, Jemal, Adhikari, Tara Ballav, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M, Alahdab, Fares, Alene, Kefyalew Addis, Aljunid, Syed Mohamed, Alvis-Guzman, Nelson, Anber, Nahla Hamed, Anjomshoa, Mina, Antonio, Carl Abelardo T., Aremu, Olatunde, Atalay, Hagos Tasew, Atique, Suleman, Attia, Engi F., Avokpaho, Euripide F G A, Awasthi, Ashish, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Banoub, Joseph Adel Mattar, Barac, Aleksandra, Bassat, Quique, Bedi, Neeraj, Belachew, Abate Bekele, Bennett, Derrick A., Bhattacharyya, Krittika, Bhutta, Zulfiqar A, Bijani, Ali, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Christopher, Devasahayam J, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Daryani, Ahmad, Degefa, Meaza Girma, Demeke, Feleke Mekonnen, Dhimal, Meghnath, Djalalinia, Shirin, Doku, David Teye, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Edessa, Dumessa, El Sayed Zaki, Maysaa, Fakhim, Hamed, Fernandes, Eduarda, Fischer, Florian, Flor, Luisa Sorio, Foreman, Kyle J., Gebremichael, Teklu Gebrehiwo, Geremew, Demeke, Ghadiri, Keyghobad, Goulart, Alessandra C, Guo, Jingwen, Ha, Giang Hai, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamidi, Samer, Hassen, Hamid Yimam, Hoang, Chi Linh, Horita, Nobuyuki, Hostiuc, Mihaela, Irvani, Seyed Sina Naghibi, Jha, Ravi Prakash, Jonas, Jost B., Kahsay, Amaha, Karch, André, Kasaeian, Amir, Kassa, Tesfaye Dessale, Kefale, Adane Teshome, Khader, Yousef Saleh, Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khang, Young-Ho, Khoja, Abdullah T, Khubchandani, Jagdish, Kimokoti, Ruth W, Kisa, Adnan, Knibbs, Luke D, Kochhar, Sonali, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kuate Defo, Barthelemy, Kumar, G Anil, Lal, Dharmesh Kumar, Lamichhane, Prabhat, Leshargie, Cheru Tesema, Levi, Miriam, Li, Shanshan, Macarayan, Erlyn Rachelle King, Majdan, Marek, Mehta, Varshil, Melese, Addisu, Memish, Ziad A, Mengistu, Desalegn Tadese, Meretoja, Tuomo J, Mestrovic, Tomislav, Miazgowski, Bartosz, Milne, George J, Milosevic, Branko, Mirrakhimov, Erkin M, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammed, Shafiu, Monasta, Lorenzo, Morawska, Lidia, Mousavi, Seyyed Meysam, Muhammed, Oumer Sada S, Murthy, Srinivas, Mustafa, Ghulam, Naheed, Aliya, Nguyen, Huong Lan Thi, Nguyen, Nam Ba, Nguyen, Son Hoang, Nguyen, Trang Huyen, Nisar, Muhammad Imran, Nixon, Molly R, Ogbo, Felix Akpojene, Olagunju, Andrew T, Olagunju, Tinuke O, Oren, Eyal, Ortiz, Justin R, P A, Mahesh, Pakhale, Smita, Patel, Shanti, Paudel, Deepak, Pigott, David M, Postma, Maarten J, Qorbani, Mostafa, Rafay, Anwar, Rafiei, Alireza, Rahimi-Movaghar, Vafa, Rai, Rajesh Kumar, Rezai, Mohammad Sadegh, Roberts, Nicholas L S, Ronfani, Luca, Rubino, Salvatore, Safari, Saeed, Safiri, Saeid, Saleem, Zikria, Sambala, Evanson Zondani, Samy, Abdallah M., Santric Milicevic, Milena M, Sartorius, Benn, Sarvi, Shahabeddin, Savic, Miloje, Sawhney, Monika, Saxena, Sonia, Seyedmousavi, Seyedmojtaba, Shaikh, Masood Ali, Sharif, Mehdi, Sheikh, Aziz, Shigematsu, Mika, Smith, David L, Somayaji, Ranjani, Soriano, Joan B, Sreeramareddy, Chandrashekhar T, Sufiyan, Mu'awiyyah Babale, Temsah, Mohamad-Hani, Tessema, Belay, Teweldemedhin, Mebrahtu, Tortajada-Girbés, Miguel, Tran, Bach Xuan, Tran, Khanh Bao, Tsadik, Afewerki Gebremeskel, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Vasankari, Tommi Juhani, Vu, Giang Thu, Wada, Fiseha Wadilo, Waheed, Yasir, West, T. Eoin, Wiysonge, Charles Shey, Yimer, Ebrahim M, Yonemoto, Naohiro, Zaidi, Zoubida, Vos, Theo, Lim, Stephen S, Murray, Christopher J L, Mokdad, Ali H, Hay, Simon I., and Reiner, Robert C
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- 2019
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19. How genomics can help biodiversity conservation
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Theissinger, Kathrin, primary, Fernandes, Carlos, additional, Formenti, Giulio, additional, Bista, Iliana, additional, Berg, Paul R., additional, Bleidorn, Christoph, additional, Bombarely, Aureliano, additional, Crottini, Angelica, additional, Gallo, Guido R., additional, Godoy, José A., additional, Jentoft, Sissel, additional, Malukiewicz, Joanna, additional, Mouton, Alice, additional, Oomen, Rebekah A., additional, Paez, Sadye, additional, Palsbøll, Per J., additional, Pampoulie, Christophe, additional, Ruiz-López, María J., additional, Secomandi, Simona, additional, Svardal, Hannes, additional, Theofanopoulou, Constantina, additional, de Vries, Jan, additional, Waldvogel, Ann-Marie, additional, Zhang, Guojie, additional, Jarvis, Erich D., additional, Bálint, Miklós, additional, Ciofi, Claudio, additional, Waterhouse, Robert M., additional, Mazzoni, Camila J., additional, Höglund, Jacob, additional, Aghayan, Sargis A., additional, Alioto, Tyler S., additional, Almudi, Isabel, additional, Alvarez, Nadir, additional, Alves, Paulo C., additional, Amorim do Rosario, Isabel R., additional, Antunes, Agostinho, additional, Arribas, Paula, additional, Baldrian, Petr, additional, Bertorelle, Giorgio, additional, Böhne, Astrid, additional, Bonisoli-Alquati, Andrea, additional, Boštjančić, Ljudevit L., additional, Boussau, Bastien, additional, Breton, Catherine M., additional, Buzan, Elena, additional, Campos, Paula F., additional, Carreras, Carlos, additional, Castro, L. FIlipe C., additional, Chueca, Luis J., additional, Čiampor, Fedor, additional, Conti, Elena, additional, Cook-Deegan, Robert, additional, Croll, Daniel, additional, Cunha, Mónica V., additional, Delsuc, Frédéric, additional, Dennis, Alice B., additional, Dimitrov, Dimitar, additional, Faria, Rui, additional, Favre, Adrien, additional, Fedrigo, Olivier D., additional, Fernández, Rosa, additional, Ficetola, Gentile Francesco, additional, Flot, Jean-François, additional, Gabaldón, Toni, additional, Agius, Dolores R., additional, Giani, Alice M., additional, Gilbert, M. Thomas P., additional, Grebenc, Tine, additional, Guschanski, Katerina, additional, Guyot, Romain, additional, Hausdorf, Bernhard, additional, Hawlitschek, Oliver, additional, Heintzman, Peter D., additional, Heinze, Berthold, additional, Hiller, Michael, additional, Husemann, Martin, additional, Iannucci, Alessio, additional, Irisarri, Iker, additional, Jakobsen, Kjetill S., additional, Klinga, Peter, additional, Kloch, Agnieszka, additional, Kratochwil, Claudius F., additional, Kusche, Henrik, additional, Layton, Kara K.S., additional, Leonard, Jennifer A., additional, Lerat, Emmanuelle, additional, Liti, Gianni, additional, Manousaki, Tereza, additional, Marques-Bonet, Tomas, additional, Matos-Maraví, Pável, additional, Matschiner, Michael, additional, Maumus, Florian, additional, Mc Cartney, Ann M., additional, Meiri, Shai, additional, Melo-Ferreira, José, additional, Mengual, Ximo, additional, Monaghan, Michael T., additional, Montagna, Matteo, additional, Mysłajek, Robert W., additional, Neiber, Marco T., additional, Nicolas, Violaine, additional, Novo, Marta, additional, Ozretić, Petar, additional, Palero, Ferran, additional, Pârvulescu, Lucian, additional, Pascual, Marta, additional, Paulo, Octávio S., additional, Pavlek, Martina, additional, Pegueroles, Cinta, additional, Pellissier, Loïc, additional, Pesole, Graziano, additional, Primmer, Craig R., additional, Riesgo, Ana, additional, Rüber, Lukas, additional, Rubolini, Diego, additional, Salvi, Daniele, additional, Seehausen, Ole, additional, Seidel, Matthias, additional, Studer, Bruno, additional, Theodoridis, Spyros, additional, Thines, Marco, additional, Urban, Lara, additional, Vasemägi, Anti, additional, Vella, Adriana, additional, Vella, Noel, additional, Vernes, Sonja C., additional, Vernesi, Cristiano, additional, Vieites, David R., additional, Wheat, Christopher W., additional, Wörheide, Gert, additional, Wurm, Yannick, additional, and Zammit, Gabrielle, additional
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- 2023
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20. A systematic review on efficiency of microneme proteins to induce protective immunity against Toxoplasma gondii
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Dodangeh, Samira, Daryani, Ahmad, Sharif, Mehdi, Aghayan, Sargis A., Pagheh, Abdol Satar, Sarvi, Shahabeddin, and Rezaei, Fatemeh
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- 2019
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21. Determinants of avian malaria prevalence in mountainous Transcaucasia
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Atoyan, Hripsime A., Sargsyan, Mariam, Gevorgyan, Hasmik, Raković, Marko, Fadeev, Igor, Muradyan, Vahagn, Daryani, Ahmad, Sharif, Mehdi, and Aghayan, Sargis A.
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- 2018
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22. Global epidemiology and spatial distribution of Toxoplasma gondii in goats: Protocol for a systematic review and Bayesian hierarchical meta-analysis.
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Amouei, Afsaneh, Mizani, Azadeh, Hanafi-Bojd, Ahmad Ali, Jafari-Koshki, Tohid, Sarvi, Shahabeddin, Aghayan, Sargis A., Amuei, Fateme, Nayeri Chegeni, Tooran, and Daryani, Ahmad
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TOXOPLASMA gondii ,GEOGRAPHIC information systems ,RESEARCH protocols ,GOATS ,AGENESIS of corpus callosum ,GOAT farming ,GEOGRAPHIC information system software - Abstract
Background: Toxoplasma gondii, a cosmopolitan protozoan parasite causes toxoplasmosis in humans and many species of domestic and wild animals. T. gondii instigates significant economic losses in sheep and goat farming industry and can lead to abortion, stillbirth, congenital malformations and neonatal losses. The objective of this protocol is to evaluate worldwide seroprevalence of T. gondii exposure in goats using Bayesian hierarchical meta-analysis and geographic information system (GIS). Methods: A comprehensive literature search will be conducted using search engines, including Web of Science, ScienceDirect, Scopus, PubMed, ProQuest, EMBASE, PROSPERO Register and, Google Scholar without date and language restrictions. The authors search for cross-sectional studies that determine the seroprevalence of T. gondii in goats. Two reviewers will independently screen, selected studies; also, they will extract data, and assess the risk of bias. In case(s) of disagreement, a consensus will be reached with the help of a third author. The Bayesian hierarchical meta-analysis will use to estimate country and worldwide true seroprevalence of T. gondii, which is consist of the sensitivity and specificity of the applied serological assays. The obtained data will be used to identify country-level risk factors associated with T. gondii exposure using GIS in the ArcGIS software. Discussion: The systematic review produced from this protocol will provide the true prevalence rate and spatial distribution T. gondii exposure in goats both regionally and globally using Bayesian hierarchical and GIS analysis. Systematic review registration: PROSPERO registration number: CRD42020107928. [ABSTRACT FROM AUTHOR]
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- 2023
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23. An updated list of mosquito species in Armenia and Transcaucasian region responsible for Dirofilaria transmission: A review.
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Shcherbakov, Oleg V., Aghayan, Sargis A., Gevorgyan, Hasmik Sh, Burlak, Vladimir A., Fedorova, Valentina S., and Artemov, Gleb N.
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- 2023
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24. Additional file 1 of Phylogenomics revealed migration routes and adaptive radiation timing of Holarctic malaria mosquito species of the Maculipennis Group
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Yurchenko, Andrey A., Naumenko, Anastasia N., Artemov, Gleb N., Karagodin, Dmitry A., Hodge, James M., Velichevskaya, Alena I., Kokhanenko, Alina A., Bondarenko, Semen M., Abai, Mohammad R., Kamali, Maryam, Gordeev, Mikhail I., Moskaev, Anton V., Caputo, Beniamino, Aghayan, Sargis A., Baricheva, Elina M., Stegniy, Vladimir N., Sharakhova, Maria V., and Sharakhov, Igor V.
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Additional file 1: Table S1. Statistics of the transcriptome assemblies for species of the Maculipennis Group. Table S2. Genes of An. atroparvus used as markers for detection of interspecies chromosome rearrangements on the X chromosome in five species of the Maculipennis Subgroup. Table S3. Mosquito species and sampling sites. Figure S1. A phylogenetic analysis of ortholog groups split into 4 equally-sized datasets based on the length of the alignments after trimal filtration. Figure S2. A phylogenetic analysis using whole-genome datasets from six Anopheles species.
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- 2023
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25. Phylogenomics revealed migration routes and adaptive radiation timing of Holarctic malaria vectors of the Maculipennis group
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Yurchenko, Andrey A., primary, Naumenko, Anastasia N., additional, Artemov, Gleb N., additional, Karagodin, Dmitry A., additional, Hodge, James M., additional, Velichevskaya, Alena I., additional, Kokhanenko, Alina A., additional, Bondarenko, Semen M., additional, Abai, Mohammad R., additional, Kamali, Maryam, additional, Gordeev, Mikhail I., additional, Moskaev, Anton V., additional, Caputo, Beniamino, additional, Aghayan, Sargis A., additional, Baricheva, Elina M., additional, Stegniy, Vladimir N., additional, Sharakhova, Maria V., additional, and Sharakhov, Igor V., additional
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- 2022
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26. A standard photomap of the ovarian nurse cell chromosomes for the dominant malaria vector in Europe and Middle East Anopheles sacharovi
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Artemov, Gleb N., Velichevskaya, Alena I., Bondarenko, Semen M., Karagyan, Gayane H., Aghayan, Sargis A., Arakelyan, Marine S., Stegniy, Vladimir N., Sharakhov, Igor V., and Sharakhova, Maria V.
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- 2018
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27. Deep genome‐wide phylogeographic structure indicates cryptic diversity in the Middle Spotted Woodpecker ( Dendrocoptes medius )
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Schweizer, Manuel, primary, Tang, Qindong, additional, Burri, Reto, additional, Drovetski, Sergei V., additional, Robles, Hugo, additional, Zyskowski, Kristof, additional, Aghayan, Sargis, additional, Rakovic, Marko, additional, and Pasinelli, Gilberto, additional
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- 2022
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28. Burden of Ischemic Heart Disease in Central Asian Countries, 1990–2017
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Lui, Michelle, primary, Safiri, Saeid, additional, Mereke, Alibek, additional, Davletov, Kairat, additional, Mebonia, Nana, additional, Myrkassymova, Akbope, additional, Aripov, Timur, additional, Mirrakhimov, Erkin, additional, Aghayan, Sargis A., additional, Gamkrelidze, Amiran, additional, Naghavi, Mohsen, additional, Kopec, Jacek A., additional, and Sarrafzadegan, Nizal, additional
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- 2021
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29. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
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Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu 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Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Madotto, F, Maghavani, Dp, Magis-Rodriguez, C, Mahotra, Nb, Majdan, M, Majdzadeh, R, Majeed, A, Malekzadeh, R, Malta, Dc, Mamun, Aa, Manda, Al, Mandarano-Filho, Lg, Mangalam, S, Manguerra, H, Mansournia, Ma, Mapoma, Cc, Maravilla, Jc, Marcenes, W, Marks, A, Martin, Rv, Martins, Sco, Martins-Melo, Fr, Martopullo, I, Mashamba-Thompson, Tp, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mazidi, M, Mcalinden, C, Mcgrath, Jj, Mckee, M, Mcmahon, Bj, Mehata, S, Mehndiratta, Mm, Mehrotra, R, Mehta, Km, Mehta, V, Mejia-Rodriguez, F, Mekonen, T, Mekonnen, Tcc, Meles, Hg, Melese, A, Melku, M, Memiah, Ptn, Memish, Za, Mendoza, W, Mengistu, Dt, Mengistu, G, Mensah, Ga, Mensink, Gbm, Mereta, St, Meretoja, A, Meretoja, Tj, Mestrovic, T, Mezgebe, Hb, Miazgowski, B, Miazgowski, T, Millear, Ai, Miller, Tr, Miller-Petrie, Mk, Milne, Gj, Mini, Gk, Minnig, Sp, Mirabi, P, Mirarefin, M, Mirrakhimov, Em, Misganaw, At, Mitchell, Pb, Moazen, B, Moghadamnia, Aa, Mohajer, B, Mohammad, Ka, Mohammadi, M, Mohammadifard, N, Mohammadnia-Afrouzi, M, Mohammed, Ma, Mohammed, S, Mohan, Mbv, Mohan, V, Mohebi, F, Moitra, M, Mokdad, Ah, Molokhia, M, Monasta, L, Montañez, Jc, Moosazadeh, M, Moradi, G, Moradi, M, Moradi-Lakeh, M, Moradinazar, M, Moraga, P, Morawska, L, Morgado-da-Costa, J, Morisaki, N, Morrison, Sd, Mosapour, A, Moschos, Mm, Mountjoy-Venning, Wc, Mouodi, S, Mousavi, Sm, Muche, Aa, Muchie, Kf, Mueller, Uo, Muhammed, O, Mukhopadhyay, S, Mullany, Ec, Muller, K, Mumford, Je, Murhekar, M, Murthy, Gv, Murthy, S, Musa, J, Musa, Ki, Mustafa, G, Muthupandian, S, Nabhan, Af, Nachega, Jb, Nagarajan, Aj, Nagel, G, Naghavi, M, Naheed, A, Nahvijou, A, Naidoo, K, Naik, G, Naik, N, Najafi, F, Naldi, L, Nam, H, Nangia, V, Nansseu, Jr, Nascimento, Br, Nawaz, H, Neamati, N, Negoi, I, Negoi, Ri, Neupane, S, Newton, Crj, Ngalesoni, Fn, Ngunjiri, Jw, Nguyen, A, Nguyen, G, Nguyen, H, Nguyen, Hlt, Nguyen, Ht, Nguyen, M, Nichols, E, Nigatu, Sg, Ningrum, Dna, Nirayo, Yl, Nisar, Mi, Nixon, Mr, Nolutshungu, N, Nomura, M, Norheim, Of, Noroozi, M, Norrving, B, Noubiap, Jj, Nouri, Hr, Nourollahpour Shiadeh, M, Nowroozi, Mr, Nyasulu, P, Obermeyer, Cm, Ofori-Asenso, R, Ogah, O, Ogbo, Fa, Oh, Ih, Okoro, A, Oladimeji, Ke, Oladimeji, O, Olagunju, At, Olagunju, To, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Oommen, Am, Opio, Jn, Oren, E, Oros, A, Ortega-Altamirano, Ddv, Ortiz, A, Ortiz, Jr, Ortiz-Panozo, E, Ota, E, Otstavnov, S, Owolabi, Mo, P A, M, Pakhale, S, Pakhare, Ap, Pan, Wh, Pana, A, Panda, Bk, Panda-Jonas, S, Pandian, Jd, Papantoniou, N, Park, Ek, Parry, Cdh, Parsian, H, Patel, S, Pati, S, Patle, A, Patton, Gc, Paturi, Vr, Paudel, D, Paulson, Kr, Pearce, N, Peprah, Ek, Pereira, Dm, Perico, N, Pervaiz, A, Pesudovs, K, Petri, Wa, Petzold, M, Phillips, Mr, Pigott, Dm, Pillay, Jd, Pirsaheb, M, Pletcher, M, Pond, Cd, Postma, Mj, Pourshams, A, Poustchi, H, Prabhakaran, D, Prakash, S, Prasad, N, Purcell, Ca, Pyakurel, M, Qorbani, M, Quansah, R, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahimi, K, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rahman, M, Rahman, Mhu, Rahman, Ma, Rahman, Su, Rai, Rk, Rajati, F, Rajsic, S, Ram, U, Rana, Sm, Ranabhat, Cl, Ranjan, P, Rasella, D, Rawaf, Dl, Rawaf, S, Razo-García, C, Reddy, K, Reiner, Rc, Reis, C, Reitsma, Mb, Remuzzi, G, Renzaho, Amn, Resnikoff, S, Reynales-Shigematsu, Lm, Rezaei, S, Rezaeian, S, Rezai, M, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Roever, L, Ronfani, L, Roshandel, G, Rostami, A, Roth, Ga, Roy, A, Rubagotti, E, Ruhago, Gm, Sabde, Yd, Sachdev, P, Saddik, B, Sadeghi, E, Safari, H, Safari, Y, Safari-Faramani, R, Safdarian, M, Safi, S, Safiri, S, Sagar, R, Sahebkar, A, Sahraian, Ma, Sajadi, H, Salam, N, Salama, J, Salamati, P, Saldanha, Rf, Saleem, Z, Salimi, Y, Salimzadeh, H, Salomon, Ja, Salvi, S, Salz, I, Sambala, Ez, Samy, Am, Sanabria, J, Sanchez-Niño, Md, Santos, I, Santric Milicevic, Mm, Sao Jose, Bp, Sardana, M, Sarker, Ar, Sarrafzadegan, N, Sartorius, B, Sarvi, S, Sathian, B, Satpathy, M, Savic, M, Sawant, Ar, Sawhney, M, Saxena, S, Saylan, M, Sayyah, M, Schaeffner, E, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Schwendicke, F, Seedat, S, Sekerija, M, Sepanlou, Sg, Serván-Mori, E, Seyedmousavi, S, Shabaninejad, H, Shackelford, Ka, Shafieesabet, A, Shaheen, Aa, Shaikh, Ma, Shams-Beyranvand, M, Shamsi, Mb, Shamsizadeh, M, Sharafi, H, Sharafi, K, Sharif, M, Sharif-Alhoseini, M, Sharma, J, Sharma, R, Sharma, Sk, She, J, Sheikh, A, Shey, M, Shi, P, Shibuya, K, Shields, C, Shifa, Gt, Shiferaw, M, Shigematsu, M, Shiri, R, Shirkoohi, R, Shirude, S, Shishani, K, Shiue, I, Shokraneh, F, Shoman, H, Shrime, Mg, Shukla, Sr, Si, S, Siabani, S, Sibai, Am, Siddiqi, Tj, Sigfusdottir, Id, Silpakit, N, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Op, Singh, Pk, Singh, V, Sinha, Dn, Skiadaresi, E, Sliwa, K, Smith, Ae, Smith, M, Soares Filho, Am, Sobaih, Bh, Sobhani, S, Soljak, M, Soofi, M, Soosaraei, M, Sorensen, Rjd, Soriano, Jb, Soshnikov, S, Soyiri, In, Spinelli, A, Sposato, La, Sreeramareddy, Ct, Srinivasan, Rg, Srinivasan, V, Stanaway, Jd, Starodubov, Vi, Stathopoulou, V, Steckling, N, Stein, Dj, Stewart, Lg, Stockfelt, L, Stokes, Ma, Straif, K, Sudaryanto, A, Sufiyan, Mb, Sunguya, Bf, Sur, Pj, Sutradhar, I, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tabuchi, T, Tadakamadla, Sk, Tamirat, K, Tandon, N, Tanser, Fc, Tassew, Aa, Tassew, Sg, Tavakkoli, M, Taveira, N, Tawye, Ny, Tehrani-Banihashemi, A, Tekalign, Tg, Tekle, Mg, Temesgen, H, Temsah, Mh, Temsah, O, Terkawi, A, Teshale, My, Teshome, Df, Tessema, B, Teweldemedhin, M, Thakur, J, Thankappan, Kr, Theis, A, Thirunavukkarasu, S, Thomas, La, Thomas, N, Thomson, Aj, Thrift, Ag, Tilahun, B, To, Qg, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Torre, Ae, Tortajada-Girbés, M, Tovani-Palone, Mr, Towbin, Ja, Tran, Bx, Tran, Kb, Tran, Tt, Tripathy, Sp, Troeger, Ce, Truelsen, Tc, Tsadik, Ag, Tudor Car, L, Tuzcu, Em, Tymeson, Hd, Ukwaja, Kn, Ullah, I, Updike, Rl, Usman, M, Uthman, Oa, Vaduganathan, M, Vaezi, A, Vaidya, G, Valdez, Pr, van Donkelaar, A, Varavikova, E, Vasankari, Tj, Venketasubramanian, N, Vidavalur, R, Villafaina, S, Violante, F, Vladimirov, Sk, Vlassov, V, Vollmer, S, Vollset, Se, Vos, T, Vosoughi, K, Vujcic, I, Wagner, Gr, Wagnew, F, Waheed, Y, Walson, Jl, Wang, Y, Wang, Yp, Wassie, Mm, Weiderpass, E, Weintraub, Rg, Weiss, J, Weldegebreal, F, Weldegwergs, Kg, Werdecker, A, Werkneh, Aa, West, Te, Westerman, R, Whisnant, Jl, Whiteford, Ha, Widecka, J, Widecka, K, Wijeratne, T, Wilner, Lb, Winkler, A, Wiyeh, Ab, Wiysonge, C, Wolde, Hf, Wolfe, Cda, Wu, S, Xavier, D, Xu, G, Xu, R, Yadollahpour, A, Yahyazadeh Jabbari, Sh, Yakob, B, Yamada, T, Yan, Ll, Yano, Y, Yaseri, M, Yasin, Yj, Ye, P, Yearwood, Ja, Yeshaneh, A, Yimer, Em, Yip, P, Yirsaw, Bd, Yisma, E, Yonemoto, N, Yonga, G, Yoon, Sj, Yotebieng, M, Younis, Mz, Yousefifard, M, Yu, C, Zaman, Sb, Zamani, M, Zare, Z, Zavala-Arciniega, L, Zegeye, Dt, Zegeye, Ea, Zeleke, Aj, Zendehdel, K, Zerfu, Ta, Zhang, Al, Zhang, X, Zhou, M, Zhu, J, Zimsen, Srm, Zodpey, S, Zoeckler, L, Zucker, I, Zuhlke, Ljj, Lim, S, and Murray, Cjl.
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GENDER-DIFFERENCES ,SUICIDE ,Medicine (all) ,Burden of Disease Study 2017 ,SDG ,CONSUMPTION ,11 Medical And Health Sciences ,GBD, Sustainable Development Goals ,PREVENTION ,ALCOHOL-USE ,CARDIOVASCULAR-DISEASE ,SMOKING PREVALENCE ,General & Internal Medicine ,factors risk ,Medicine and Health Sciences ,Human medicine ,CESSATION ,PERSPECTIVE ,TRANSITION - Abstract
Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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30. Mortality, morbidity, and hospitalisations due to influenza lower respiratory tract infections, 2017: an analysis for the Global Burden of Disease Study 2017
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Alvis-Guzmán, Nelson, Troeger, Christopher E, Blacker, Brigette F, Khalil, Ibrahim A, Zimsen, Stephanie R M, Albertson, Samuel B, Abate, Degu, Abdela, Jemal, Ballav Adhikari, Tara, and Aghasi Aghayan, Sargis
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Mortality ,Morbidity ,Lower respiratory tract infections - Abstract
Background Although the burden of influenza is often discussed in the context of historical pandemics and the threat of future pandemics, every year a substantial burden of lower respiratory tract infections (LRTIs) and other respiratory conditions (like chronic obstructive pulmonary disease) are attributable to seasonal influenza. The Global Burden of Disease Study (GBD) 2017 is a systematic scientific effort to quantify the health loss associated with a comprehensive set of diseases and disabilities. In this Article, we focus on LRTIs that can be attributed to influenza. Methods We modelled the LRTI incidence, hospitalisations, and mortality attributable to influenza for every country and selected subnational locations by age and year from 1990 to 2017 as part of GBD 2017. We used a counterfactual approach that first estimated the LRTI incidence, hospitalisations, and mortality and then attributed a fraction of those outcomes to influenza. Findings Influenza LRTI was responsible for an estimated 145 000 (95% uncertainty interval [UI] 99 000–200 000) deaths among all ages in 2017. The influenza LRTI mortality rate was highest among adults older than 70 years (16·4 deaths per 100 000 [95% UI 11·6–21·9]), and the highest rate among all ages was in eastern Europe (5·2 per 100 000 population [95% UI 3·5–7·2]). We estimated that influenza LRTIs accounted for 9 459000 (95% UI 3 709000–22 935000) hospitalisations due to LRTIs and 81 536 000 hospital days (24 330 000–259851 000). We estimated that 11·5% (95% UI 10·0–12·9) of LRTI episodes were attributable to influenza, corresponding to 54481 000 (38465000–73864000) episodes and 8172000 severe episodes (5 000 000–13 296000). Interpretation This comprehensive assessment of the burden of influenza LRTIs shows the substantial annual effect of influenza on global health. Although preparedness planning will be important for potential pandemics, health loss due to seasonal influenza LRTIs should not be overlooked, and vaccine use should be considered. Efforts to improve influenza prevention measures are needed.
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31. Malaria Journal
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Velichevskaya, Alena I., Bondarenko, Semen M., Karagyan, Gayane H., Aghayan, Sargis A., Arakelyan, Marine S., Stegniy, Vladimir N., Sharakhov, Igor V., Sharakhova, Maria V., Artemov, Gleb N., Entomology, and Fralin Life Sciences Institute
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lcsh:Arctic medicine. Tropical medicine ,lcsh:RC955-962 ,Research ,Fluorescence in situ hybridization ,Chromosome Mapping ,флуоресцентная гибридизация in situ ,Mosquito Vectors ,Salivary Glands ,цитогенетическая карта ,Malaria ,lcsh:Infectious and parasitic diseases ,Mosquito ,Anopheles ,Anopheles sacharovi ,Animals ,lcsh:RC109-216 ,комары ,Gytogenetic map ,In Situ Hybridization, Fluorescence ,Polytene Chromosomes - Abstract
Background Anopheles sacharovi is a dominant malaria vector species in South Europe and the Middle East which has a highly plastic behaviour at both adult and larval stages. Such plasticity has prevented this species from eradication by several anti-vector campaigns. The development of new genome-based strategies for vector control will benefit from genome sequencing and physical chromosome mapping of this mosquito. Although a cytogenetic photomap for chromosomes from salivary glands of An. sacharovi has been developed, no cytogenetic map suitable for physical genome mapping is available. Methods Mosquitoes for this study were collected at adult stage in animal shelters in Armenia. Polytene chromosome preparations were prepared from ovarian nurse cells. Fluorescent in situ hybridization (FISH) was performed using PCR amplified probes. Results This study constructed a high-quality standard photomap for polytene chromosomes from ovarian nurse cells of An. sacharovi. Following the previous nomenclature, chromosomes were sub-divided into 39 numbered and 119 lettered sub-divisions. Chromosomal landmarks for the chromosome recognition were described. Using FISH, 4 PCR-amplified genic probes were mapped to the chromosomes. The positions of the probes demonstrated gene order reshuffling between An. sacharovi and Anopheles atroparvus which has not been seen cytologically. In addition, this study described specific chromosomal landmarks that can be used for the cytotaxonomic diagnostics of An. sacharovi based on the banding pattern of its polytene chromosomes. Conclusions This study constructed a high-quality standard photomap for ovarian nurse cell chromosomes of An. sacharovi and validated its utility for physical genome mapping. Based on the map, cytotaxonomic features for identification of An. sacharovi have been described. The cytogenetic map constructed in this study will assist in creating a chromosome-based genome assembly for this mosquito and in developing cytotaxonomic tools for identification of other species from the Maculipennis group. Published version
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32. The First Report of Trichinella britovi in Armenia
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GRIGORYAN, Gohar, primary, A. AGHAYAN, Sargis, additional, GEVORGYAN, Hasmik, additional, MALKHASYAN, Alexander, additional, VALLEE, Isabelle, additional, and KARADJIAN, Grégory, additional
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- 2020
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33. First report about toxic cyanobacterial bloom occurrence in Lake Sevan, Armenia
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Gevorgyan, Gor, primary, Rinke, Karsten, additional, Schultze, Martin, additional, Mamyan, Armine, additional, Kuzmin, Anton, additional, Belykh, Olga, additional, Sorokovikova, Ekaterina, additional, Hayrapetyan, Armine, additional, Hovsepyan, Anahit, additional, Khachikyan, Termine, additional, Aghayan, Sargis, additional, Fedorova, Galina, additional, Krasnopeev, Andrey, additional, Potapov, Sergey, additional, and Tikhonova, Irina, additional
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34. Cover Image
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Amouei, Afsaneh, primary, Sarvi, Shahabeddin, additional, Sharif, Mehdi, additional, Aghayan, Sargis A., additional, Javidnia, Javad, additional, Mizani, Azadeh, additional, Moosazadeh, Mahmood, additional, Shams, Nemat, additional, Hosseini, Seyed Abdollah, additional, Hosseininejad, Zahra, additional, Nayeri Chegeni, Tooran, additional, Badali, Hamid, additional, and Daryani, Ahmad, additional
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- 2020
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35. Genetic characterization of Toxoplasma gondii in Iranian HIV positive patients using multilocus nested-PCR-RFLP method
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Hosseini, Seyed Abdollah, primary, Sharif, Mehdi, additional, Sarvi, Shahabeddin, additional, Abediankenari, Saeid, additional, Hashemi-Soteh, Mohammad Bagher, additional, Amouei, Afsaneh, additional, Montazeri, Mahboobeh, additional, Aghayan, Sargis A., additional, Gholami, Sara, additional, Shaker, Davoud, additional, Mizani, Azadeh, additional, Shabanzadeh, Shafigheh, additional, and Daryani, Ahmad, additional
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36. Infection of parthenogenetic lizards by blood parasites does not support the “Red Queen hypothesis” but reveals the costs of sex
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Arakelyan, Marine, primary, Harutyunyan, Tehmine, additional, Aghayan, Sargis A., additional, and Carretero, Miguel A., additional
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37. A systematic review on the role of GRA proteins of Toxoplasma gondii in host immunization
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Rezaei, Fatemeh, primary, Sharif, Mahdi, additional, Sarvi, Shahabeddin, additional, Hejazi, Seyed Hossein, additional, Aghayan, Sargis, additional, Pagheh, Abdol Sattar, additional, Dodangeh, Samira, additional, and Daryani, Ahmad, additional
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38. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Stanaway, Jeffrey D., Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S., Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A., Adane, Akilew Awoke, Adebayo, Oladimeji M., Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O., Adib, Mina G., Admasie, Amha, Adsuar, Jose C., Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Agarwal, Gina, Aggarwal, Anju, Aghayan, Sargis Aghasi, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M., Alahdab, Fares, Alam, Khurshid, Alam, Samiah, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Ali, Komal, Ali, Syed Mustafa, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A., Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antó, Josep M., Antonio, Carl Abelardo T., Anwari, Palwasha, Appiah, Lambert Tetteh, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avokpaho, Euripide F.G.A., Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Ayuk, Tambe B., Azzopardi, Peter S., Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Ball, Kylie, Ballew, Shoshana H., Banach, Maciej, Banoub, Joseph Adel Mattar, Barac, Aleksandra, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H., Basu, Sanjay, Baune, Bernhard T., Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Bekru, Eyasu Tamru, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Bergeron, Gilles, Berhane, Adugnaw, Bernabe, Eduardo, Bernstein, Robert S., Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhattarai, Suraj, Bhutta, Zulfiqar A., Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Bisanzio, Donal, Biswas, Tuhin, Bjørge, Tone, Blacker, Brigette F., Bleyer, Archie, Borschmann, Rohan, Bou-Orm, Ibrahim R., Boufous, Soufiane, Bourne, Rupert, Brady, Oliver J., Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J.K., Brenner, Hermann, Briko, Andrey Nikolaevich, Britton, Gabrielle, Brugha, Traolach, Buchbinder, Rachelle, Burnett, Richard T., Busse, Reinhard, Butt, Zahid A., Cahill, Leah E., Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R., Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carvalho, Félix, Castañeda-Orjuela, Carlos A., Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Causey, Kate, Cercy, Kelly M., Cerin, Ester, Chaiah, Yazan, Chang, Hsing Yi, Chang, Jung Chen, Chang, Kai Lan, Charlson, Fiona J., Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chee, Miao Li, Cheng, Ching Yu, Chew, Adrienne, Chiang, Peggy Pei Chia, Chimed-Ochir, Odgerel, Chin, Ken Lee, Chitheer, Abdulaal, Choi, Jee Young J., Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chung, Sheng Chia, Cicuttini, Flavia M., Cirillo, Massimo, Cohen, Aaron J., Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Owen R., Coresh, Josef, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Criqui, Michael H., Cromwell, Elizabeth A., Cundiff, David K., Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dadi, Abel Fekadu, Damasceno, Albertino Antonio Moura, Dandona, Lalit, Dandona, Rakhi, Darby, Sarah C., Dargan, Paul I., Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davitoiu, Dragos Virgil, Davletov, Kairat, De la Cruz-Góngora, Vanessa, De La Hoz, Fernando Pio, De Leo, Diego, De Neve, Jan Walter, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P., Demoz, Gebre Teklemariam, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Deshpande, Aniruddha, Des Jarlais, Don C., Dessie, Getenet Ayalew, Deveber, Gabrielle Aline, Dey, Subhojit, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dinberu, Mesfin Tadese, Ding, Eric L., Diro, Helen Derara, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B., Duraes, Andre R., Ebert, Natalie, Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edvardsson, David, Effiong, Andem, Eggen, Anne Elise, El Bcheraoui, Charbel, El-Khatib, Ziad, Elyazar, Iqbal Rf, Enayati, Ahmadali, Endries, Aman Yesuf, Er, Benjamin, Erskine, Holly E., Eskandarieh, Sharareh, Esteghamati, Alireza, Estep, Kara, Fakhim, Hamed, Faramarzi, Mahbobeh, Fareed, Mohammad, Farid, Talha A., Farinha, Carla Sofia E.sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S., Farzaei, Mohammad Hosein, Fatima, Batool, Fay, Kairsten A., Fazaeli, Ali Akbar, Feigin, Valery L., Feigl, Andrea B., Fereshtehnejad, Seyed Mohammad, Fernandes, Eduarda, Fernandes, Joao C., Ferrara, Giannina, Ferrari, Alize J., Ferreira, Manuela L., Filip, Irina, Finger, Jonas David, Fischer, Florian, Foigt, Nataliya A., Foreman, Kyle J., Fukumoto, Takeshi, Fullman, Nancy, Fürst, Thomas, Furtado, João M., Futran, Neal D., Gall, Seana, Gallus, Silvano, Gamkrelidze, Amiran, Ganji, Morsaleh, Garcia-Basteiro, Alberto L., Gardner, William M., Gebre, Abadi Kahsu, Gebremedhin, Amanuel Tesfay, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M., Geramo, Yilma Chisha Dea, Gething, Peter W., Gezae, Kebede Embaye, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghimire, Mamata, Ghosh, Rakesh, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K., Gillum, Richard F., Ginawi, Ibrahim Abdelmageed, Giussani, Giorgia, Gnedovskaya, Elena V., Godwin, William W., Goli, Srinivas, Gómez-Dantés, Hector, Gona, Philimon N., Gopalani, Sameer Vali, Goulart, Alessandra C., Grada, Ayman, Grams, Morgan E., Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gutiérrez, Reyna Alma, Gutiérrez-Torres, Daniela S., Haagsma, Juanita A., Habtewold, Tesfa Dejenie, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hagos, Tekleberhan B., Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R., Hamidi, Samer, Handal, Alexis J., Hankey, Graeme J., Hao, Yuantao, Harb, Hilda L., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N., Hay, Simon I., Hedayatizadeh-Omran, Akbar, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T., Higazi, Tarig B., Hilawe, Esayas Haregot, Hoek, Hans W., Hoffman, Howard J., Hole, Michael K., Homaie Rad, Enayatollah, Hoogar, Praveen, Hosgood, H. Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Hu, Howard, Huang, John J., Hussen, Mamusha Aman, Huynh, Chantal K., Iburg, Kim Moesgaard, Ikeda, Nayu, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jackson, Maria D., Jacobsen, Kathryn H., Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, James, Spencer L., Jassal, Simerjot K., Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S., Jonas, Jost B., Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Zubair, Kahsay, Amaha, Kalani, Rizwan, Kanchan, Tanuj, Kant, Surya, Kar, Chittaranjan, Karami, Manoochehr, Karami Matin, Behzad, Karch, André, Karema, Corine, Karimi, Narges, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn H., Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kefale, Adane Teshome, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A., Khan, Gulfaraz, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young Ho, Khater, Mona M., Khazaei, Mohammad, Khazaie, Habibolah, Khoja, Abdullah T., Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Kiadaliri, Aliasghar A., Kiirithio, Daniel N., Kim, Cho Il, Kim, Daniel, Kim, Young Eun, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kivimäki, Mika, Knibbs, Luke D., Knudsen, Ann Kristin Skrindo, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael A., Krishan, Kewal, Krohn, Kristopher J., Kromhout, Hans, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kumar, G. Anil, Kumar, Manasi, Kuzin, Igor, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P., Lad, Sheetal D., Lafranconi, Alessandra, Lalloo, Ratilal, Lallukka, Tea, Lami, Faris Hasan, Lang, Justin J., Lansingh, Van C., Larson, Samantha Leigh, Latifi, Arman, Lazarus, Jeffrey V., Lee, Paul H., Leigh, James, Leili, Mostafa, Leshargie, Cheru Tesema, Leung, Janni, Levi, Miriam, Lewycka, Sonia, Li, Shanshan, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liao, Yu, Liben, Misgan Legesse, Lim, Lee Ling, Linn, Shai, Liu, Shiwei, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lucas, Tim C.D., Lunevicius, Raimundas, Ma, Stefan, Macarayan, Erlyn Rachelle King, Machado, Ísis Eloah, Madotto, Fabiana, Mai, Hue Thi, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A., Manda, Ana Laura, Manguerra, Helena, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Maravilla, Joemer C., Marcenes, Wagner, Marks, Ashley, Martin, Randall V., Martins, Sheila C.O., Martins-Melo, Francisco Rogerlândio, März, Winfried, Marzan, Melvin B., Massenburg, Benjamin Ballard, Mathur, Manu Raj, Mathur, Prashant, Matsushita, Kunihiro, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mekonnen, Fantahun Ayenew, Melaku, Yohannes A., Melese, Addisu, Melku, Mulugeta, Memiah, Peter T.N., Memish, Ziad A., Mendoza, Walter, Mengistu, Desalegn Tadese, Mensah, George A., Mensink, Gert B.M., Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J., Mestrovic, Tomislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I., Miller, Ted R., Miller-Petrie, Molly Katherine, Mini, G. K., Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke Temesgen, Mitiku, Habtamu, Moazen, Babak, Mohajer, Bahram, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadnia-Afrouzi, Mousa, Mohammed, Shafiu, Mohebi, Farnam, Mokdad, Ali H., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Moodley, Yoshan, Moradi, Ghobad, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Morgado-Da-Costa, Joana, Morrison, Shane Douglas, Moschos, Marilita M., Mouodi, Simin, Mousavi, Seyyed Meysam, Mozaffarian, Dariush, Mruts, Kalayu Brhane, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada, Mukhopadhyay, Satinath, Muller, Kate, Musa, Kamarul Imran, Mustafa, Ghulam, Nabhan, Ashraf F., Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Naik, Nitish, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramos, Neal, Bruce, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Subas, Newton, Charles Richard James, Ngunjiri, Josephine W., Nguyen, Anh Quynh, Nguyen, Grant, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Minh, Nguyen, Nam Ba, Nichols, Emma, Nie, Jing, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nishi, Nobuo, Nixon, Molly R., Nojomi, Marzieh, Nomura, Shuhei, Norheim, Ole F., Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, Elaine O., Nyasulu, Peter S., Obermeyer, Carla M., Odell, Christopher M., Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T., Olagunju, Tinuke O., Olivares, Pedro R., Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L., Ong, Sok King, Oren, Eyal, Orpana, Heather M., Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S., Øverland, Simon, Owolabi, Mayowa Ojo, P A, Mahesh, Pacella, Rosana, Pakhare, Abhijit P., Pakpour, Amir H., Pana, Adrian, Panda-Jonas, Songhomitra, Park, Eun Kee, Parry, Charles D.H., Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patil, Snehal T., Patle, Ajay, Patton, George C., Paudel, Deepak, Paulson, Katherine R., Paz Ballesteros, Wayra Citlali, Pearce, Neil, Pereira, Alexandre, Pereira, David M., Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Pham, Hai Quang, Phillips, Michael R., Pillay, Julian David, Piradov, Michael A., Pirsaheb, Meghdad, Pischon, Tobias, Pishgar, Farhad, Plana-Ripoll, Oleguer, Plass, Dietrich, Polinder, Suzanne, Polkinghorne, Kevan R., Postma, Maarten J., Poulton, Richie, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A., Purwar, Manorama B., Qorbani, Mostafa, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Zohreh, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz ur, Rahman, Muhammad Aziz, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Raju, Sree Bhushan, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Rath, Goura Kishor, Rawaf, David Laith, Rawaf, Salman, Reddy, K. Srinath, Rehm, Colin D., Rehm, Jürgen, Reiner, Robert C., Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Reynales-Shigematsu, Luz Myriam, Rezaei, Satar, Ribeiro, Antonio Luiz P., Rivera, Juan A., Roba, Kedir Teji, Rodríguez-Ramírez, Sonia, Roever, Leonardo, Román, Yesenia, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A., Rothenbacher, Dietrich, Roy, Ambuj, Rubagotti, Enrico, Rushton, Lesley, Sabanayagam, Charumathi, Sachdev, Perminder S., Saddik, Basema, Sadeghi, Ehsan, Saeedi Moghaddam, Sahar, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salam, Nasir, Salamati, Payman, Saleem, Zikria, Salimi, Yahya, Salimzadeh, Hamideh, Salomon, Joshua A., Salvi, Devashri Digvijay, Salz, Inbal, Samy, Abdallah M., Sanabria, Juan, Sanchez-Niño, Maria Dolores, Sánchez-Pimienta, Tania G., Sanders, Taren, Sang, Yingying, Santomauro, Damian Francesco, Santos, Itamar S., Santos, João Vasco, Santric Milicevic, Milena M., Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarmiento-Suárez, Rodrigo, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R., Sawhney, Monika, Saylan, Mete, Sayyah, Mehdi, Schaeffner, Elke, Schmidt, Maria Inês, Schneider, Ione J.C., Schöttker, Ben, Schutte, Aletta Elisabeth, Schwebel, David C., Schwendicke, Falk, Scott, James G., Seedat, Soraya, Sekerija, Mario, Sepanlou, Sadaf G., Serre, Marc L., Serván-Mori, Edson, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shaddick, Gavin, Shafieesabet, Azadeh, Shahbazi, Mehdi, Shaheen, Amira A., Shaikh, Masood Ali, Shamah Levy, Teresa, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Sharafi, Heidar, Sharafi, Kiomars, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharifi, Hamid, Sharma, Jayendra, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shibuya, Kenji, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shin, Min Jeong, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shoman, Haitham, Shrime, Mark G., Shupler, Matthew S., Si, Si, Siabani, Soraya, Sibai, Abla Mehio, Siddiqi, Tariq J., Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santos, Silva, João Pedro, Silveira, Dayane Gabriele Alves, Singh, Jasvinder A., Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Smith, David L., Smith, Mari, Sobaih, Badr Hasan, Sobhani, Soheila, Somayaji, Ranjani, Soofi, Moslem, Sorensen, Reed J.D., Soriano, Joan B., Soyiri, Ireneous N., Spinelli, Angela, Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Starodubov, Vladimir I., Steckling, Nadine, Stein, Dan J., Stein, Murray B., Stevanovic, Goran, Stockfelt, Leo, Stokes, Mark A., Sturua, Lela, Subart, Michelle L., Sudaryanto, Agus, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F., Sur, Patrick John, Sykes, Bryan L., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Takahashi, Ken, Tandon, Nikhil, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekelemedhin, Shishay Wahdey, Tekle, Merhawi Gebremedhin, Temesgen, Habtamu, Temsah, Mohamad Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Tessema, Belay, Teweldemedhin, Mebrahtu, Thankappan, Kavumpurathu Raman, Theis, Andrew, Thirunavukkarasu, Sathish, Thomas, Hannah J., Thomas, Matthew Lloyd, Thomas, Nihal, Thurston, George D., Tilahun, Binyam, Tillmann, Taavi, To, Quyen G., Tobollik, Myriam, Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna E., Tortajada-Girbés, Miguel, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A., Tran, Bach Xuan, Tran, Khanh Bao, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tudor Car, Lorainne, Tuzcu, E. Murat, Tymeson, Hayley D., Tyrovolas, Stefanos, Ukwaja, Kingsley N., Ullah, Irfan, Updike, Rachel L., Usman, Muhammad Shariq, Uthman, Olalekan A., Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R., Van Donkelaar, Aaron, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venkateswaran, Vidhya, Venketasubramanian, Narayanaswamy, Villafaina, Santos, Violante, Francesco S., Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vu, Giang Thu, Vujcic, Isidora S., Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G., Walson, Judd L., Wang, Yafeng, Wang, Yanping, Wang, Yuan Pang, Weiderpass, Elisabete, Weintraub, Robert G., Weldegebreal, Fitsum, Werdecker, Andrea, Werkneh, Adhena Ayaliew, West, J. 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Hsiao, Thoma, Hu, Guoqing, Hu, Howard, Huang, John J, Hussen, Mamusha Aman, Huynh, Chantal K, Iburg, Kim Moesgaard, Ikeda, Nayu, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jackson, Maria D, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, James, Spencer L, Jassal, Simerjot K, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Zubair, Kahsay, Amaha, Kalani, Rizwan, Kanchan, Tanuj, Kant, Surya, Kar, Chittaranjan, Karami, Manoochehr, Karami Matin, Behzad, Karch, André, Karema, Corine, Karimi, Narge, Karimi, Seyed M, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, 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Anil, Kumar, Manasi, Kuzin, Igor, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lalloo, Ratilal, Lallukka, Tea, Lami, Faris Hasan, Lang, Justin J, Lansingh, Van C, Larson, Samantha Leigh, Latifi, Arman, Lazarus, Jeffrey V, Lee, Paul H, Leigh, Jame, Leili, Mostafa, Leshargie, Cheru Tesema, Leung, Janni, Levi, Miriam, Lewycka, Sonia, Li, Shanshan, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liao, Yu, Liben, Misgan Legesse, Lim, Lee-Ling, Linn, Shai, Liu, Shiwei, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Tim C D, Lunevicius, Raimunda, Ma, Stefan, Macarayan, Erlyn Rachelle King, Machado, Ísis Eloah, Madotto, Fabiana, Mai, Hue Thi, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Manguerra, Helena, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, 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Mohammed, Shafiu, Mohebi, Farnam, Mokdad, Ali H, Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Moodley, Yoshan, Moradi, Ghobad, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Morgado-Da-Costa, Joana, Morrison, Shane Dougla, Moschos, Marilita M, Mouodi, Simin, Mousavi, Seyyed Meysam, Mozaffarian, Dariush, Mruts, Kalayu Brhane, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada, Mukhopadhyay, Satinath, Muller, Kate, Musa, Kamarul Imran, Mustafa, Ghulam, Nabhan, Ashraf F, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Naik, Nitish, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramo, Neal, Bruce, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Suba, Newton, Charles Richard Jame, Ngunjiri, Josephine W, Nguyen, Anh Quynh, Nguyen, Grant, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Minh, Nguyen, Nam Ba, Nichols, Emma, Nie, Jing, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nishi, Nobuo, Nixon, Molly R, Nojomi, Marzieh, Nomura, Shuhei, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacque, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Obermeyer, Carla M, Odell, Christopher M, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L, Ong, Sok King, Oren, Eyal, Orpana, Heather M, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, P A, Mahesh, Pacella, Rosana, Pakhare, Abhijit P, Pakpour, Amir H, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patil, Snehal T, Patle, Ajay, Patton, George C, Paudel, Deepak, Paulson, Katherine R, Paz Ballesteros, Wayra Citlali, Pearce, Neil, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Pham, Hai Quang, Phillips, Michael R, Pillay, Julian David, Piradov, Michael A, Pirsaheb, Meghdad, Pischon, Tobia, Pishgar, Farhad, Plana-Ripoll, Oleguer, Plass, Dietrich, Polinder, Suzanne, Polkinghorne, Kevan R, Postma, Maarten J, Poulton, Richie, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A, Purwar, Manorama B, Qorbani, Mostafa, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Zohreh, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz ur, Rahman, Muhammad Aziz, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Raju, Sree Bhushan, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Rath, Goura Kishor, Rawaf, David Laith, Rawaf, Salman, Reddy, K Srinath, Rehm, Colin D, Rehm, Jürgen, Reiner, Robert C, Reitsma, Marissa B, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Reynales-Shigematsu, Luz Myriam, Rezaei, Satar, Ribeiro, Antonio Luiz P, Rivera, Juan A, Roba, Kedir Teji, Rodríguez-Ramírez, Sonia, Roever, Leonardo, Román, Yesenia, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A, Rothenbacher, Dietrich, Roy, Ambuj, Rubagotti, Enrico, Rushton, Lesley, Sabanayagam, Charumathi, Sachdev, Perminder S, Saddik, Basema, Sadeghi, Ehsan, Saeedi Moghaddam, Sahar, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salam, Nasir, Salamati, Payman, Saleem, Zikria, Salimi, Yahya, Salimzadeh, Hamideh, Salomon, Joshua A, Salvi, Devashri Digvijay, Salz, Inbal, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolore, Sánchez-Pimienta, Tania G, Sanders, Taren, Sang, Yingying, Santomauro, Damian Francesco, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarmiento-Suárez, Rodrigo, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R, Sawhney, Monika, Saylan, Mete, Sayyah, Mehdi, Schaeffner, Elke, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schutte, Aletta Elisabeth, Schwebel, David C, Schwendicke, Falk, Scott, James G, Seedat, Soraya, Sekerija, Mario, Sepanlou, Sadaf G, Serre, Marc L, Serván-Mori, Edson, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shaddick, Gavin, Shafieesabet, Azadeh, Shahbazi, Mehdi, Shaheen, Amira A, Shaikh, Masood Ali, Shamah Levy, Teresa, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Sharafi, Heidar, Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharifi, Hamid, Sharma, Jayendra, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shibuya, Kenji, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shin, Min-Jeong, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shoman, Haitham, Shrime, Mark G, Shupler, Matthew S, Si, Si, Siabani, Soraya, Sibai, Abla Mehio, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Smith, David L, Smith, Mari, Sobaih, Badr Hasan, Sobhani, Soheila, Somayaji, Ranjani, Soofi, Moslem, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Spinelli, Angela, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Starodubov, Vladimir I, Steckling, Nadine, Stein, Dan J, Stein, Murray B, Stevanovic, Goran, Stockfelt, Leo, Stokes, Mark A, Sturua, Lela, Subart, Michelle L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sykes, Bryan L, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh 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Muthiah, Vaezi, Afsane, Valdez, Pascual R, Van Donkelaar, Aaron, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venkateswaran, Vidhya, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vu, Giang Thu, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G, Walson, Judd L, Wang, Yafeng, Wang, Yanping, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weldegebreal, Fitsum, Werdecker, Andrea, Werkneh, Adhena Ayaliew, West, J Jason, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Wong, Tien Yin, Wu, Shouling, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zavala-Arciniega, Lui, Zhang, Anthony Lin, Zhang, Hao, Zhang, Kai, Zhou, Maigeng, Zimsen, Stephanie R M, Zodpey, Sanjay, and Murray, Christopher J L
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Science & Technology ,GBD, risks ,risk factors ,comparative risk assesment ,Dalys ,Medicine (all) ,CHOLESTEROL ,BLOOD-PRESSURE ,11 Medical And Health Sciences ,ILLNESS ,TRENDS ,humanities ,Medicine, General & Internal ,TOBACCO CONTROL ,General & Internal Medicine ,parasitic diseases ,Medicine and Health Sciences ,CARDIOVASCULAR-DISEASES ,TRIAL ,Human medicine ,Life Sciences & Biomedicine ,METAANALYSIS - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk– outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Lancet 2018; 392: 1923–94 *Collaborators listed at the end of the paper Correspondence to: Prof Christopher J L Murray, Institute for Health Metrics and Evalution, Seattle, WA 98121, USA cjlm@uw.edu Global Health Metrics 1924 www.thelancet.com Vol 392 November 10, 2018 Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.
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39. 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
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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, 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Vasconcelos, A, Vladimirov, S, Vollset, S, Walson, J, Weintraub, R, Weldegwergs, K, Wolfe, C, Wyper, G, Yasin, Y, Yentür, G, Yimer, E, Yoon, S, Younis, M, Zaman, S, Zeleke, M, Zenebe, Z, Zerfu, T, Zhao, X, Zimsen, S, Lopez, A, and Lim, S
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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.
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40. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Crispin, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Maddison, Ralph, Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Muhammed, Maghavani, Dhaval P, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malik, Manzoor Ahmad, Malta, Deborah Carvalho, Mamun, Abdullah A, Manamo, Wondimu Ayele, Manda, Ana-Laura, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C, Marcenes, Wagner, Marina, Shakhnazarova, Martinez-Raga, Jose, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, März, Winfried, Marzan, Melvin B, Mashamba-Thompson, Tivani Phosa, Masiye, Felix, Massenburg, Benjamin Ballard, Maulik, Pallab K, Mazidi, Mohsen, McGrath, John J, McKee, Martin, Mehata, Suresh, Mehendale, Sanjay Madhav, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Mekonen, Tesfa, Mekonnen, Tefera Chane, Meles, Hagazi Gebre, Meles, Kidanu Gebremariam, 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, Mestrovic, Tomislav, Mezgebe, Haftay Berhane, Miangotar, Yode, Miazgowski, Bartosz, Miazgowski, Tomasz, Miller, Ted R, Mini, G.K., Mirica, Andreea, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Moazen, Babak, Moges, Nurilign Abebe, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadi-Khanaposhtani, Maryam, Mohammadnia-Afrouzi, Mousa, Mohammed, Shafiu, Mohammed, Mohammed A, Mohan, Viswanathan, Mokdad, Ali H, Molokhia, Mariam, Monasta, Lorenzo, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Moreno Velásquez, Ilai, Morgado-da-Costa, Joana, Morrison, Shane Dougla, Mosapour, Abba, Moschos, Marilita M, Mousavi, Seyyed Meysam, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Mukhopadhyay, Satinath, Mullany, Erin C, Muller, Kate, Murhekar, Manoj, Murphy, Tasha B, Murthy, G.V.S., Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nachega, Jean B, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Nair, Sanjeev, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramo, Nawaz, Haseeb, Ncama, Busisiwe P, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Suba, Newton, Charles Richard Jame, Ngalesoni, Frida N, Ngunjiri, Josephine W, Nguyen, Ha Thu, Nguyen, Huong Thanh, Nguyen, Long Hoang, Nguyen, Michele, Nguyen, Trang Huyen, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nisar, Muhammad Imran, Nixon, Molly R, Nolutshungu, Nomonde, Nomura, Shuhei, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacque, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Ofori-Asenso, Richard, Ogah, Okechukwu Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Sok King, Opio, John Nelson, Oren, Eyal, Ortiz, Justin R, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, Oyekale, Abayomi Samuel, P A, Mahesh, Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandey, Achyut Raj, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Patle, Ajay, Patten, Scott B, Patton, George C, Paudel, Deepak, Pearce, Neil, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perez, Krystle M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Plass, Dietrich, Polinder, Suzanne, Pond, Constance Dimity, Popova, Svetlana, Postma, Maarten J, Pourmalek, Farshad, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, V., Prakash, Swayam, Prasad, Narayan, Qorbani, Mostafa, Quistberg, D Alex, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Raju, Sree Bhushan, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Ranta, Anna, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E, Razo-García, Christian, Rego, Maria Albertina Santiago, Rehm, Jürgen, Reiner, Robert C, Reinig, Nickola, Reis, Cesar, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Ribeiro, Antonio Luiz P, Riojas, Horacio, Rios-Blancas, Maria Jesu, Roba, Kedir Teji, Robinson, Stephen R, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Roshchin, Denis O, Rostami, Ali, Rothenbacher, Dietrich, Rubagotti, Enrico, Ruhago, George Mugambage, Saadat, Soheil, Sabde, Yogesh Damodar, Sachdev, Perminder S, Saddik, Basema, Sadeghi, Ehsan, Moghaddam, Sahar Saeedi, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salahshoor, Mohamadreza, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saldanha, Raphael de Freita, Salimi, Yahya, Salimzadeh, Hamideh, Salz, Inbal, Sambala, Evanson Zondani, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolore, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Savic, Miloje, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Sayyah, Mehdi, Scaria, Vinod, Schaeffner, Elke, Schelonka, Kathryn, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schutte, Aletta Elisabeth, Schwebel, David C, Schwendicke, Falk, Scott, James G, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabaninejad, Hosein, Shackelford, Katya Anne, Shafieesabet, Azadeh, Shaheen, Amira A, Shaikh, Masood Ali, Shakir, Raad A, Shams-Beyranvand, Mehran, Shamsi, MohammadBagher, Shamsizadeh, Morteza, Sharafi, Heidar, Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Meenakshi, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Sheth, Kevin N, Shi, Peilin, Shibuya, Kenji, Shifa, Girma Temam, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shrime, Mark G, Shukla, Sharvari Rahul, Si, Si, Siabani, Soraya, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silpakit, Nari, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Virendra, Sinha, Anju Pradhan, Sinha, Dhirendra Narain, Sitas, Freddy, Skirbekk, Vegard, Sliwa, Karen, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Soriano, Joan B, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Srivastava, Rakesh Kumar, Starodubov, Vladimir I, Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J, Steiner, Caitlyn, Stewart, Leo G, Stokes, Mark A, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sutradhar, Ipsita, Sykes, Bryan L, Sylaja, P.N., Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Takahashi, Ken, Tandon, Nikhil, Tassew, Aberash Abay, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Tawye, Nega Yimer, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekle, Merhawi Gebremedhin, Temesgen, Habtamu, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Teshale, Manaye Yihune, Tessema, Belay, Teweldemedhin, Mebrahtu, Thakur, Jarnail Singh, Thankappan, Kavumpurathu Raman, Thirunavukkarasu, Sathish, Thomas, Laura Anne, Thomas, Nihal, Thrift, Amanda G, Tilahun, Binyam, To, Quyen G, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna E, Tortajada-Girbés, Miguel, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Suryakant, Tripathy, Srikanth Prasad, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tsilimparis, Nikolao, Tudor Car, Lorainne, Tuzcu, E Murat, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Usman, Muhammad Shariq, Uthman, Olalekan A, Uzun, Selen Begüm, Vaduganathan, Muthiah, Vaezi, Afsane, Vaidya, Gaurang, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagner, Gregory R, Wagnew, Fasil Wagnew Shiferaw, Waheed, Yasir, Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weiss, Jordan, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wondemagegn, Sintayehu Ambachew, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yadav, Rajaram, Yakob, Bereket, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yearwood, Jamal A, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, York, Hunter W, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zachariah, Geevar, Zadnik, Vesna, Zafar, Shamsa, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeeb, Hajo, Zeleke, Mulugeta Molla, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Kai, Zhang, Xueying, Zhou, Maigeng, Zhu, Jun, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna J, Lopez, Alan D, Gakidou, Emmanuela, and Murray, Christopher J L
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Child mortality ,Alnæmi ,Dánartíðni ,Heilsufar ,GBD ,Börn ,Dauði ,Almennar lyflækningar ,Fullorðnir ,General & Internal Medicine ,parasitic diseases ,Psychology ,age-specific mortality ,Estimating adult mortality ,Medicine (all) ,HIV ,11 Medical And Health Sciences ,General Medicine ,All-cause mortality ,humanities ,Countries ,Death ,mortality, national ,Sálfræði ,Health ,GBD, mortality ,Human medicine ,Trends - Abstract
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data., Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing., Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163).
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- 2018
41. Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Stanaway, Jeffrey D., Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S., Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M.E., Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A., Adane, Akilew Awoke, Adebayo, Oladimeji M., Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O., Adib, Mina G., Admasie, Amha, Adsuar, Jose C., Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Agarwal, Gina, Aggarwal, Anju, Aghayan, Sargis Aghasi, Geleijnse, Johanna M., Hoek, Hans W., Khan, Muhammad Shahzeb, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Vos, Theo, Zhang, Hao, and Zhang, Kai
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Nutrition and Disease ,Voeding en Ziekte ,Life Science ,VLAG - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.
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- 2019
42. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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James, Spencer L. G., Abate, Degu, Abate, Kalkidan Hessen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M. E., Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N., Adamu, Abdu A., Adebayo, Oladimeji M., Adekanmbi, Victor, Adetokunboh, Olatunji O., Adib, Mina G., Adsuar, Jose C., Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M., Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Amare, Azmeraw T., Hoek, Hans W., Khan, Muhammad Shahzeb, Kim, Young-Eun, Leigh, James, Postma, Maarten J., Zhao, Zheng, PharmacoTherapy, -Epidemiology and -Economics, Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), and Methods in Medicines evaluation & Outcomes research (M2O)
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CHINESE POPULATION ,MATERNAL MORTALITY ,ECONOMIC BURDEN ,TERM OXYGEN-THERAPY ,HOSPITAL CARDIAC-ARREST ,UNITED-STATES ,VISION IMPAIRMENT ,SECONDARY PREVENTION ,INFLUENZA VACCINATION ,OBSTRUCTIVE PULMONARY-DISEASE - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 39% (95% uncertainty interval [UI] 3.1-4. 6) from 1990 to 2017; however, the all-age YLD rate increased by 7.2% (6.0-8.4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7.9% (6 6-9. 2) for males and 6.5% (5.4-7.7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-hatin and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
43. Alcohol use and burden for 195 countries and territories, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
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Griswold, Max G., Fullman, Nancy, Hawley, Caitlin, Arian, Nicholas, Zimsen, Stephanie R. M., Tymeson, Hayley D., Venkateswaran, Vidhya, Tapp, Austin Douglas, Forouzanfar, Mohammad H., Salama, Joseph S., Abate, Kalkidan Hassen, Abate, Degu, Abay, Solomon M., Abbafati, Cristiana, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Aboyans, Victor, Abrar, Mohammed Mehdi, Acharya, Pawan, Adetokunboh, Olatunji O., Adhikari, Tara Ballav, Adsuar, Jose C., Afarideh, Mohsen, Agardh, Emilie Elisabet, Agarwal, Gina, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmed, Muktar Beshir, Akibu, Mohammed, Akinyemiju, Tomi, Akseer, Nadia, Al Asfoor, Deena H., Al-Aly, Ziyad, Alahdab, Fares, Alam, Khurshid, Albujeer, Ammar, Alene, Kefyalew Addis, Ali, Raghib, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Allebeck, Peter, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Ammar, Walid, Leigh, James, Postma, Maarten J., Van Boven, Job F. M., PharmacoTherapy, -Epidemiology and -Economics, Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), Methods in Medicines evaluation & Outcomes research (M2O), and Groningen Research Institute for Asthma and COPD (GRIAC)
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DRINKING ,DEPENDENCE ,RISK-FACTORS ,CONSUMPTION ,REDUCED MORTALITY ,METAANALYSIS ,ALL-CAUSE MORTALITY - Abstract
Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.
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- 2018
44. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Stanaway, Jeffrey D, Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S, Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adane, Akilew Awoke, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Admasie, Amha, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Agarwal, Gina, Aggarwal, Anju, Aghayan, Sargis Aghasi, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Alahdab, Fares, Alam, Khurshid, Alam, Samiah, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Ali, Komal, Ali, Syed Mustafa, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antó, Josep M, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Ball, Kylie, Ballew, Shoshana H, Banach, Maciej, Banoub, Joseph Adel Mattar, Barac, Aleksandra, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Bekru, Eyasu Tamru, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gilles, Berhane, Adugnaw, Bernabe, Eduardo, Bernstein, Robert S, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhattarai, Suraj, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Bisanzio, Donal, Biswas, Tuhin, Bjørge, Tone, Blacker, Brigette F, Bleyer, Archie, Borschmann, Rohan, Bou-Orm, Ibrahim R, Boufous, Soufiane, Bourne, Rupert, Brady, Oliver J, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Briko, Andrey Nikolaevich, Britton, Gabrielle, Brugha, Traolach, Buchbinder, Rachelle, Burnett, Richard T, Busse, Reinhard, Butt, Zahid A, Cahill, Leah E, Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R, Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Causey, Kate, Cercy, Kelly M, Cerin, Ester, Chaiah, Yazan, Chang, Hsing-Yi, Chang, Jung-Chen, Chang, Kai-Lan, Charlson, Fiona J, Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chee, Miao Li, Cheng, Ching-Yu, Chew, Adrienne, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chin, Ken Lee, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Cirillo, Massimo, Cohen, Aaron J, Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Owen R, Coresh, Josef, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Criqui, Michael H, Cromwell, Elizabeth A, Cundiff, David K, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dadi, Abel Fekadu, Damasceno, Albertino Antonio Moura, Dandona, Lalit, Dandona, Rakhi, Darby, Sarah C, Dargan, Paul I, Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davitoiu, Dragos Virgil, Davletov, Kairat, De la Cruz-Góngora, Vanessa, De La Hoz, Fernando Pio, De Leo, Diego, De Neve, Jan-Walter, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Deshpande, Aniruddha, Des Jarlais, Don C, Dessie, Getenet Ayalew, Deveber, Gabrielle Aline, Dey, Subhojit, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dinberu, Mesfin Tadese, Ding, Eric L, Diro, Helen Derara, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Doyle, Kerrie E, Driscoll, Tim R, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebert, Natalie, Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edvardsson, David, Effiong, Andem, Eggen, Anne Elise, El Bcheraoui, Charbel, El-Khatib, Ziad, Elyazar, Iqbal Rf, Enayati, Ahmadali, Endries, Aman Yesuf, Er, Benjamin, Erskine, Holly E, Eskandarieh, Sharareh, Esteghamati, Alireza, Estep, Kara, Fakhim, Hamed, Faramarzi, Mahbobeh, Fareed, Mohammad, Farid, Talha A, Farinha, Carla Sofia E sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzaei, Mohammad Hosein, Fatima, Batool, Fay, Kairsten A, Fazaeli, Ali Akbar, Feigin, Valery L, Feigl, Andrea B, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Ferrara, Giannina, Ferrari, Alize J, Ferreira, Manuela L, Filip, Irina, Finger, Jonas David, Fischer, Florian, Foigt, Nataliya A, Foreman, Kyle J, Fukumoto, Takeshi, Fullman, Nancy, Fürst, Thomas, Furtado, João M, Futran, Neal D, Gall, Seana, Gallus, Silvano, Gamkrelidze, Amiran, Ganji, Morsaleh, Garcia-Basteiro, Alberto L, Gardner, William M, Gebre, Abadi Kahsu, Gebremedhin, Amanuel Tesfay, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M, Geramo, Yilma Chisha Dea, Gething, Peter W, Gezae, Kebede Embaye, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghimire, Mamata, Ghosh, Rakesh, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K, Gillum, Richard F, Ginawi, Ibrahim Abdelmageed, Giussani, Giorgia, Gnedovskaya, Elena V, Godwin, William W, Goli, Srinivas, Gómez-Dantés, Hector, Gona, Philimon N, Gopalani, Sameer Vali, Goulart, Alessandra C, Grada, Ayman, Grams, Morgan E, Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gutiérrez, Reyna Alma, Gutiérrez-Torres, Daniela S, Haagsma, Juanita A, Habtewold, Tesfa Dejenie, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hagos, Tekleberhan B, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N, Hay, Simon I, Hedayatizadeh-Omran, Akbar, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T, Higazi, Tarig B, Hilawe, Esayas Haregot, Hoek, Hans W, Hoffman, Howard J, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Hu, Howard, Huang, John J, Hussen, Mamusha Aman, Huynh, Chantal K, Iburg, Kim Moesgaard, Ikeda, Nayu, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jackson, Maria D, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, James, Spencer L, Jassal, Simerjot K, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Zubair, Kahsay, Amaha, Kalani, Rizwan, Kanchan, Tanuj, Kant, Surya, Kar, Chittaranjan, Karami, Manoochehr, Karami Matin, Behzad, Karch, André, Karema, Corine, Karimi, Narges, Karimi, Seyed M, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kefale, Adane Teshome, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Gulfaraz, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khater, Mona M, Khazaei, Mohammad, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Kiadaliri, Aliasghar A, Kiirithio, Daniel N, Kim, Cho-Il, Kim, Daniel, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W, Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kivimäki, Mika, Knibbs, Luke D, Knudsen, Ann Kristin Skrindo, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kristopher J, Kromhout, Hans, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kumar, G Anil, Kumar, Manasi, Kuzin, Igor, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lalloo, Ratilal, Lallukka, Tea, Lami, Faris Hasan, Lang, Justin J, Lansingh, Van C, Larson, Samantha Leigh, Latifi, Arman, Lazarus, Jeffrey V, Lee, Paul H, Leigh, James, Leili, Mostafa, Leshargie, Cheru Tesema, Leung, Janni, Levi, Miriam, Lewycka, Sonia, Li, Shanshan, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liao, Yu, Liben, Misgan Legesse, Lim, Lee-Ling, Linn, Shai, Liu, Shiwei, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Tim C D, Lunevicius, Raimundas, Ma, Stefan, Macarayan, Erlyn Rachelle King, Machado, Ísis Eloah, Madotto, Fabiana, Mai, Hue Thi, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Manguerra, Helena, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, Martin, Randall V, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, März, Winfried, Marzan, Melvin B, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Mathur, Prashant, Matsushita, Kunihiro, Maulik, Pallab K, Mazidi, Mohsen, McAlinden, Colm, McGrath, John J, McKee, Martin, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Meier, Toni, Mekonnen, Fantahun Ayenew, Melaku, Yohannes A, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengistu, Desalegn Tadese, Mensah, George A, Mensink, Gert B M, Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I, Miller, Ted R, Miller-Petrie, Molly Katherine, Mini, G K, Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Mitiku, Habtamu, Moazen, Babak, Mohajer, Bahram, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadnia-Afrouzi, Mousa, Mohammed, Shafiu, Mohebi, Farnam, Mokdad, Ali H, Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Moodley, Yoshan, Moradi, Ghobad, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Morgado-Da-Costa, Joana, Morrison, Shane Douglas, Moschos, Marilita M, Mouodi, Simin, Mousavi, Seyyed Meysam, Mozaffarian, Dariush, Mruts, Kalayu Brhane, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada, Mukhopadhyay, Satinath, Muller, Kate, Musa, Kamarul Imran, Mustafa, Ghulam, Nabhan, Ashraf F, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Naik, Nitish, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramos, Neal, Bruce, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Subas, Newton, Charles Richard James, Ngunjiri, Josephine W, Nguyen, Anh Quynh, Nguyen, Grant, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Minh, Nguyen, Nam Ba, Nichols, Emma, Nie, Jing, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nishi, Nobuo, Nixon, Molly R, Nojomi, Marzieh, Nomura, Shuhei, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Obermeyer, Carla M, Odell, Christopher M, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L, Ong, Sok King, Oren, Eyal, Orpana, Heather M, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, P A, Mahesh, Pacella, Rosana, Pakhare, Abhijit P, Pakpour, Amir H, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patil, Snehal T, Patle, Ajay, Patton, George C, Paudel, Deepak, Paulson, Katherine R, Paz Ballesteros, Wayra Citlali, Pearce, Neil, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Pham, Hai Quang, Phillips, Michael R, Pillay, Julian David, Piradov, Michael A, Pirsaheb, Meghdad, Pischon, 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- Subjects
ddc - Published
- 2018
45. A systematic review of Toxoplasma gondii genotypes and feline: Geographical distribution trends
- Author
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Amouei, Afsaneh, primary, Sarvi, Shahabeddin, additional, Sharif, Mehdi, additional, Aghayan, Sargis A., additional, Javidnia, Javad, additional, Mizani, Azadeh, additional, Moosazadeh, Mahmood, additional, Shams, Nemat, additional, Hosseini, Seyed Abdollah, additional, Hosseininejad, Zahra, additional, Nayeri Chegeni, Tooran, additional, Badali, Hamid, additional, and Daryani, Ahmad, additional
- Published
- 2019
- Full Text
- View/download PDF
46. Is there any association between Toxoplasma gondii infection and depression? A systematic review and meta-analysis
- Author
-
Nayeri Chegeni, Tooran, primary, Sharif, Mehdi, additional, Sarvi, Shahabeddin, additional, Moosazadeh, Mahmood, additional, Montazeri, Mahbobeh, additional, Aghayan, Sargis A., additional, Balalami, Nader Jafari, additional, Gholami, Shirzad, additional, Hosseininejad, Zahra, additional, Saberi, Reza, additional, Anvari, Davood, additional, Gohardehi, Shaban, additional, and Daryani, Ahmad, additional
- Published
- 2019
- Full Text
- View/download PDF
47. Evidence of Crimean-Congo Haemorrhagic Fever Virus Occurrence in Ixodi¬dae Ticks of Armenia
- Author
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Gevorgyan, Hasmik, primary, Grigoryan, Gohar G., additional, A. Atoyan, Hripsime, additional, Rukhkyan, Martin, additional, Hakobyan, Astghik, additional, Zakaryan, Hovakim, additional, and A. Aghayan, Sargis, additional
- Published
- 2019
- Full Text
- View/download PDF
48. Relationship between toxoplasmosis and obsessive compulsive disorder: A systematic review and meta-analysis
- Author
-
Nayeri Chegeni, Tooran, primary, Sarvi, Shahabeddin, additional, Amouei, Afsaneh, additional, Moosazadeh, Mahmood, additional, Hosseininejad, Zahra, additional, A. Aghayan, Sargis, additional, and Daryani, Ahmad, additional
- Published
- 2019
- Full Text
- View/download PDF
49. Fasciola spp. in Armenia: Genetic diversity in a global context
- Author
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Aghayan, Sargis, primary, Gevorgian, Hasmik, additional, Ebi, Dennis, additional, Atoyan, Hripsime A., additional, Addy, Francis, additional, Mackenstedt, Ute, additional, Romig, Thomas, additional, and Wassermann, Marion, additional
- Published
- 2019
- Full Text
- View/download PDF
50. Aetiology of livestock fetal mortality in Mazandaran province, Iran
- Author
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Amouei, Afsaneh, primary, Sharif, Mehdi, additional, Sarvi, Shahabeddin, additional, Bagheri Nejad, Ramin, additional, Aghayan, Sargis A., additional, Hashemi-Soteh, Mohammad Bagher, additional, Mizani, Azadeh, additional, Hosseini, Seyed Abdollah, additional, Gholami, Sara, additional, Sadeghi, Alireza, additional, Sarafrazi, Mohammad, additional, and Daryani, Ahmad, additional
- Published
- 2019
- Full Text
- View/download PDF
Catalog
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