Maqola

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

Spencer L JamesInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USADegu AbateInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKalkidan Hassen AbateInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASolomón Mequanente AbayInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USACristiana AbbafatiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USANooshin AbbasiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAHedayat AbbastabarInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAFoad Abd-AllahInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAJemal AbdelaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAhmed AbdelalimInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAIbrahim AbdollahpourInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USARizwan Suliankatchi AbdulkaderInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAbebe ZegeyeInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASemaw Ferede AberaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAOlifan Zewdie AbilHaftom Niguse AbrahaLaith J. Abu‐RaddadInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USANiveen M. E. Abu-RmeilehInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAManfred AccrombessiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USADilaram AcharyaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAPawan AcharyaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAIlana N. AckermanInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAbdu A. AdamuInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAOladimeji AdebayoInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAVictor AdekanmbiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAOlatunji AdetokunbohInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMina G AdibInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAJosé Carmelo AdsuarInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKossivi Agbélénko AfanviInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMohsen AfaridehInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAshkan AfshinInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAGina AgarwalInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKareha M AgesaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USARakesh AggarwalInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASargis A. AghayanInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASutapa AgrawalInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAlireza AhmadiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMehdi AhmadiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAHamid AhmadiehInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMuktar Beshir AhmedInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAmani Nidhal AichourInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAIbtihel AichourInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMiloud Taki Eddine AichourInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USATomi AkinyemijuInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USANadia AkseerInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAZiyad Al‐AlyInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAyman Al‐EyadhyInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAHesham M. Al‐MekhlafiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USARajaa Al‐RaddadiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAFares AlahdabInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKhurshid AlamInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAShazia AlamInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAlaa AlashiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASeyed Moayed AlavianInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKefyalew Addis AleneInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMehran AlijanzadehInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAReza Alizadeh‐NavaeiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASyed Mohamed AljunidAla’a AlkerwiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAFrançois AllaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAPeter AllebeckInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMohamed M L AlouaniInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKhalid A AltirkawiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USANelson Alvis‐GuzmánInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAzmeraw T. AmareInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USALéopold Ndemnge AmindeInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAWalid AmmarInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAYaw Ampem AmoakoInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USANahla AnberInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USACătălina Liliana AndreiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASofia AndroudiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMegbaru Debalkie AnimutInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMina AnjomshoaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMustafa Geleto AnshaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USACarl Abelardo T. AntonioInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAPalwasha AnwariInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAJalal ArablooInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAntonio AraúzInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAOlatunde AremuInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAFilippo ArianiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USABahroom ArmoonInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAJohan ÄrnlövInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAmit AroraInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAl ArtamanInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAKrishna K AryalInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAHamid AsayeshInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USARana Jawad AsgharInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAZerihun AtaroInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USASachin AtreInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAMarcel AusloosInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USALeticia Ávila‐BurgosInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAEuripide AvokpahoInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAshish AwasthiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USABeatriz Paulina Ayala QuintanillaInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USARakesh AyerInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAPeter AzzopardiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAArefeh BabazadehInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAHamid BadaliInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAlaa BadawiInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USAAyele GeletoInstitute for Health Metrics Evaluation, University of Washington, Seattle, WA 98121, USA

2018en

ABI

Annotatsiya

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 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]). 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. FUNDING: Bill & Melinda Gates Foundation.

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DOI: 10.1016/s0140-6736(18)32279-7

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