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1. Sensitivity and Specificity of Central Vein Sign as a Diagnostic Biomarker in Egyptian Patients with Multiple Sclerosis

Author: Abdel Ghany H, Karam-Allah A, Edward R, Abdel Naseer M, and Hegazy MI
Subjects: multiple sclerosis, central vein, mimics, cutoff, gradient-echo, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Hend Abdel Ghany,1 Ahmed Karam-Allah,1 Ramy Edward,2 Maged Abdel Naseer,1 Mohamed I Hegazy1 1Neurology Department, Faculty of Medicine, Cairo University, Cairo, Egypt; 2Radiology Department, Faculty of Medicine, Cairo University, Cairo, EgyptCorrespondence: Mohamed I Hegazy, Neurology Department, Cairo University, 108 Al Manial street, Degla, Maadi, Cairo, 11435, Egypt, Tel +20 1223130686, Email mhegazy@kasralainy.edu.egPurpose: Magnetic resonance imaging (MRI) findings in multiple sclerosis (MS) overlap with numerous MS mimics. The central vein sign (CVS) can help to differentiate MS from other mimics. This study aimed to determine the value of CVS as a diagnostic biomarker for distinguishing MS from its mimics.Patients and Methods: Patients were prospectively recruited into two groups: a typical clinical (TC) MS presentation with an atypical MRI for MS and an atypical clinical (ATC) MS presentation with a typical MRI for MS. Patients underwent a 1.5T MRI brain scan with a T2&ast;-weighted gradient-echo sequence. The presence of the central vein was assessed by a radiologist blinded to patients’ clinical presentation. The MS consultant made the final diagnosis without reviewing the T2&ast;-weighted gradient-echo sequence or the CVS analysis results.Results: Forty-two patients were included. Ten (40%) out of 25 TC patients were diagnosed with clinically definite MS (CDMS), with a mean percentage of CV-positive lesions of 65.5% among CDMS patients. Four (23.5%) out of 17 ATC patients were diagnosed with CDMS with a mean CV-positive lesions percentage of 68.25% among CDMS patients. TC patients who were not diagnosed as CDMS had a mean CV-positive lesions percentage of 10.13%, while ATC patients who were not diagnosed as CDMS had a mean CV-positive lesions percentage of 16.38%. The CVS showed 85.7% sensitivity and 100% specificity (95% confidence interval: 0.919– 1.018) for diagnosis of MS at a cut off value of 45% (p < 0.001). The percentage of CV-positive lesions was significantly higher in oligoclonal bands (OCBs) positive patients compared to OCBs negative patients (p < 0.001) and those with spinal cord lesions compared to patients with no spinal cord lesions (p = 0.017).Conclusion: The CVS has 85.7% sensitivity and 100% specificity for the diagnosis of MS at a cutoff value of 45%.Keywords: multiple sclerosis, central vein, mimics, cutoff, gradient-echo
Published: 2022

2. Management Strategies of Patients with Neuromyelitis Optica Spectrum Disorder During the COVID-19 Pandemic Era

Author: Hamdy SM, Abdel-Naseer M, Shehata HS, Shalaby NM, Hassan A, Elmazny A, Shaker E, Nada MAF, Ahmed SM, Hegazy MI, Mourad HS, Abdelalim A, Magdy R, Othman AS, Mekkawy DA, and Kishk NA
Subjects: neuromyelitis optica spectrum disorder, covid19, pandemic, Therapeutics. Pharmacology, RM1-950
Abstract: Sherif M Hamdy, Maged Abdel-Naseer, Hatem S Shehata, Nevin M Shalaby, Amr Hassan, Alaa Elmazny, Ehab Shaker, Mona AF Nada, Sandra M Ahmed, Mohamed I Hegazy, Husam S Mourad, Ahmed Abdelalim, Rehab Magdy, Alshimaa S Othman, Doaa A Mekkawy, Nirmeen A Kishk Neurology Department, Faculty of Medicine, Cairo University, Cairo, EgyptCorrespondence: Alaa Elmazny 66-Manial-Street, Cairo, EgyptTel +966536012237Email alaa_elmazny@kasralainy.edu.egAbstract: The ongoing coronavirus (COVID-19) pandemic is a global health emergency of international concern and has affected management plans of many autoimmune disorders. Immunosuppressive and immunomodulatory therapies are pivotal in the management of neuromyelitis optica spectrum disorder (NMOSD), potentially placing patients at an increased risk of contracting infections such as COVID-19. The optimal management strategy of NMOSD during the COVID-19 era remains unclear. Here, however, we examined the evidence of NMOSD disease-modifying therapies (DMTs) use during the present period and highlighted different scenarios including treatment of relapses as well as initiation and maintenance of DMTs in order to optimize care of NMOSD patients in the COVID-19 era.Keywords: neuromyelitis optica spectrum disorder, COVID-19, pandemic
Published: 2020

3. Managing Disease-Modifying Therapies and Breakthrough Activity in Multiple Sclerosis Patients During the COVID-19 Pandemic: Toward an Optimized Approach

Author: Hamdy SM, Abdel-Naseer M, Shehata HS, Hassan A, Elmazny A, Shalaby NM, Abokrysha NT, Kishk NA, Nada MAF, Ahmed SM, Hegazy MI, Mekkawy D, Mourad HS, Abdelalim A, and Berger T
Subjects: covid-19, multiple sclerosis, disease-modifying therapies, Therapeutics. Pharmacology, RM1-950
Abstract: Sherif M Hamdy,1 Maged Abdel-Naseer,1 Hatem S Shehata,1 Amr Hassan,1 Alaa Elmazny,1 Nevin M Shalaby,1 Noha T Abokrysha,1 Nirmeen A Kishk,1 Mona AF Nada,1 Sandra M Ahmed,1 Mohamed I Hegazy,1 Doaa Mekkawy,1 Husam S Mourad,1 Ahmed Abdelalim,1 Thomas Berger2 1Neurology Department, Faculty of Medicine, Cairo University, Cairo, Egypt; 2Neurology Department, Medical University of Vienna, Vienna, AustriaCorrespondence: Amr HassanKasr Al Ainy Faculty of Medicine, Cairo University, P.O.11553, Cairo, EgyptTel +201006060809Email amrhasanneuro@kasralainy.edu.egAbstract: The emergence of the novel coronavirus disease 2019 (COVID-19) pandemic has become a major public health challenge of global concern since December 2019, when the virus was recognized in Wuhan, the capital city of Hubei province in China and epicenter of the COVID-19 epidemic. Given the novelty of COVID-19 and the lack of specific anti-virus therapies, the current management is essentially supportive. There is an absence of consensus on guidelines or treatment strategies for complex disorders such as multiple sclerosis (MS), in which the risk of infections is higher than in the general population. This is due to the overall impairment of the immune system typical of autoimmune diseases, in addition to accumulation of disabilities, and the iatrogenic effect generated by corticosteroids and the recommended disease-modifying therapies (DMTs). DMTs have different modes of action, but all modulate and interfere with the patient’s immune response, thereby raising concerns about adverse effects, such as an increased susceptibility to infections. In this review, we analyze the evidence for use of DMTs during the current critical period and ratify an algorithmic approach for management to optimize care between keeping DMTs, with their infection hazards, or coming off them, with the risk of disease activation. We also provide an algorithmic approach to the management of breakthrough activity during the COVID-19 pandemic.Keywords: COVID-19, multiple sclerosis, disease-modifying therapies
Published: 2020

4. Interferon-Beta-Induced Headache in Patients with Multiple Sclerosis: Frequency and Characterization

Author: Elmazny A, Hamdy SM, Abdel-Naseer M, Shalaby NM, Shehata HS, Kishk NA, Nada MA, Mourad HS, Hegazy MI, Abdelalim A, Ahmed SM, Hatem G, Fouad AM, Mahmoud H, and Hassan A
Subjects: headache, interferon beta, multiple sclerosis, Medicine (General), R5-920
Abstract: Alaa Elmazny, Sherif M Hamdy, Maged Abdel-Naseer, Nevin M Shalaby, Hatem S Shehata, Nirmeen A Kishk, Mona A Nada, Husam S Mourad, Mohamed I Hegazy, Ahmed Abdelalim, Sandra M Ahmed, Ghada Hatem, Amr M Fouad, Hadel Mahmoud, Amr Hassan Neurology Department, Faculty of Medicine, Cairo University, Cairo, EgyptCorrespondence: Hatem S ShehataNeurology Department, Cairo University, 23 Amin Samy Street – Kasr Alaini Street, Cairo, EgyptTel +2011124444179Fax +20227927795Email samirhatem@kasralainy.edu.egBackground: Studies have shown that interferon-beta (IFN-β) treatment is associated with headaches in patients with multiple sclerosis (MS). Headaches can affect quality of life and overall function of patients with MS. We examined the frequency, relationships, patterns, and characteristics of headaches in response to IFN-β in patients with relapsing-remitting multiple sclerosis (RRMS).Patients and Methods: This study was a prospective, longitudinal analysis with 1-year follow-up. The study comprised 796 patients with RRMS treated with IFN-β (mean age 30.84± 8.98 years) at 5 tertiary referral center outpatient clinics in Egypt between January 2015 and December 2017. Headaches were diagnosed according to the International Classification of Headache Disorders ICHD-3 (beta version), and data were collected through an interviewer-administered Arabic-language-validated questionnaire with an addendum specifically designed to investigate the temporal relationship between commencement of interferon treatment, and headache onset and characteristics.Results: Two hundred seventy-six patients had pre-existing headaches, and 356 experienced de novo headaches. Of 122 patients who experienced headaches before IFN-β treatment, 55 reported headaches that worsened following onset of IFN-β treatment. In patients with post-IFN-β headaches, 329 had headaches that persisted for > 3 months, 51 had chronic headaches, and 278 had episodic headaches, and 216 of these patients required preventive therapies. Univariate analysis showed a > 6- and an approximately 5-fold increased risk of headache among those treated with intramuscular (IM) INF-β-1a (OR 6.51; 95% CI: 3.73– 10.01; P-value < 0.0001) and 44 μg of SC INF-β-1a (OR 5.44; 95% CI: 3.15– 9.37; P-value < 0.0001), respectively, compared with that in patients who received 22 μg of SC INF-β-1a.Conclusion: Interferon-β therapy aggravated pre-existing headaches and caused primary headaches in patients with MS. Headache risk was greater following treatment with IM INF-β-1a and 44 μg SC INF-β-1a.Keywords: headache, interferon-beta, multiple sclerosis
Published: 2020

5. Pediatric-onset multiple sclerosis in Egypt: a multi-center registry of 186 patients

Author: Hamdy SM, Abdel-Naseer M, Shalaby NM, Elmazny A, Girgis M, Nada MA, Hassan A, Mourad HS, Hegazy MI, Abdelalim A, Kishk NA, Abokrysha NT, Genedy SA, Essawy EA, and Shehata HS
Subjects: multiple sclerosis, pediatric onset, early onset, registry, Egypt., Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Sherif M Hamdy,1 Maged Abdel-Naseer,1 Nevin M Shalaby,1 Alaa Elmazny,1 Marian Girgis,2 Mona A Nada,1 Amr Hassan,1 Husam S Mourad,1 Mohamed I Hegazy,1 Ahmed Abdelalim,1 Nirmeen A Kishk,1 Noha T Abokrysha,1 Shaimaa A Genedy,1 Ehab A Essawy,3 Hatem S Shehata1 1Neurology Department, Cairo University, Cairo, Egypt; 2Pediatric Department, Cairo University, Cairo, Egypt; 3Division of Biochemistry, Chemistry Department, Faculty of Science, Helwan University, Helwan, Egypt Introduction: Although the frequency of pediatric-onset multiple sclerosis (POMS) has increased in recent decades, it is still highly uncommon, which creates a need for the involvement of more registries from various clinical centers.Objective: To characterize the demographic, clinical, and paraclinical features of Egyptian patients with POMS.Patients and methods: A retrospective chart review study was undertaken on 237 Egyptian patients with demyelinating events which started before the age of 18 years who attended one of five tertiary referral centers in Cairo, Egypt.Results: Multiple sclerosis was diagnosed in 186 patients, 47 (25.27%) patients had disease onset before the age of 12 years; “early-onset pediatric multiple sclerosis (EOPMS)”. The mean age of disease onset was (14.13±2.49 years), with a female:male ratio of 1.62:1, none of the enrolled patients had a primary progressive course (PPMS), whereas 10 patients (5.38%) had a secondary progressive form. Approximately two-thirds of the patients had monofocal disease onset, and less than 10% presented with encephalopathy; most of them had EOPMS. Motor weakness was the presenting symptom in half of the patients, whereas cerebellar presentation was detected in 34.95%, mainly in EOPMS. Seizures (not related to encephalopathy) were more frequent in those with EOPMS. Initial brain magnetic resonance images were positive in all patients, with detected atypical lesions in 29.03%, enhanced lesions in 35.48%, black holes in 13.98%, and infratentorial in 34.41%. Cervical cord involvement was found in 68.28%. More than two-thirds of the patients received either immunomodulatory or immunosuppressant (IS) treatment throughout their disease course, and about half of them received their treatment within the first year from symptoms onset, with a more favorable outcome, and patients with highly active disease received natalizumab, fingolimod, or other IS.Conclusion: The results from this registry – the largest for MS in the Arab region to date – are comparable to other registries. Immunomodulatory therapies in POMS are well tolerated and efficacious and they can improve the long-term outcome in children. Keywords: multiple sclerosis, pediatric onset, early onset, registry, Egypt
Published: 2018

6. Characteristics and predictors of progression in an Egyptian multiple sclerosis cohort: a multicenter registry study

Author: Hamdy SM, Abdel-Naseer M, Shalaby NM, Elmazny AN, Nemr AA, Hassan A, Hegazy MI, Mourad HS, Kishk NA, Nada MA, Abdelalim A, Fouad AM, and Shehata HS
Subjects: Multiple sclerosis, MS registry, Epidemiology, Middle East, North Africa, Egypt., Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Sherif M Hamdy,1 Maged Abdel-Naseer,1 Nevin M Shalaby,1 Alaa N Elmazny,1 Ahmed A Nemr,2 Amr Hassan,1 Mohamed I Hegazy,1 Husam S Mourad,1 Nirmeen A Kishk,1 Mona A Nada,1 Ahmed Abdelalim,1 Amr M Fouad,1 Hatem S Shehata1 1Neurology Department, Cairo University, 2Neurology Department, Maadi Military Hospital, Cairo, Egypt Background: Multiple sclerosis (MS) is a complex autoimmune disease with a heterogeneous presentation and diverse disease course. Recent studies indicate a rising prevalence of MS in the Middle East.Objective: To characterize the demographics and disease features of Egyptian patients attending four tertiary referral MS centers in Cairo.Materials and methods: This was a retrospective, observational study on 1,581 patients between 2001 and 2015. Medical records were reviewed and data were identified and extracted in a standardized electronic registry.Results: The mean age of disease onset was 26.6±7.8 years, with the majority being female (2.11:1). Relapsing–remitting MS was the most common type (75.1%). The main presenting symptom was motor weakness (43.9%), which was also the most frequent symptom during the disease course. Family history of MS was found in 2.28%. Higher initial Expanded Disability Status Scale score, black holes, and infratentorial lesions on initial magnetic resonance imaging were independent factors for disease progression by univariate analysis (OR 3.87 [95% CI 1.84–6.51], 4.14 [95% CI 3.08–5.58], 4.07 [95% CI 3.21–4.99], respectively); however, in multivariate analysis, only infratentorial lesions were an independent risk for disease progression (OR 6, 95% CI 2.99–12.02; P=0.0005).Conclusion: The results from this registry – the largest for MS in the Arab region to date – are comparable to other registries with slight differences. Keywords: multiple sclerosis, MS registry, epidemiology, Middle East, North Africa, Egypt
Published: 2017

7. Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Dorsey, ER, Elbaz, A, Nichols, E, Abd-Allah, F, Abdelalim, A, Adsuar, JC, Ansha, MG, Brayne, C, Choi, J-YJ, Collado-Mateo, D, Dahodwala, N, Huyen, PD, Edessa, D, Endres, M, Fereshtehnejad, S-M, Foreman, KJ, Gbetoho Gankpe, F, Gupta, R, Hankey, GJ, Hay, SI, Hegazy, MI, Hibstu, DT, Kasaeian, A, Khader, Y, Khalil, I, Khang, Y-H, Kim, YJ, Kokubo, Y, Logroscino, G, Massano, J, Ibrahim, NM, Mohammed, AM, Mohammadi, A, Moradi-Lakeh, M, Naghavi, M, Binh, TN, Nirayo, YL, Ogbo, FA, Owolabi, MO, Pereira, DM, Postma, MJ, Qorbani, M, Rahman, MA, Roba, KT, Safari, H, Safiri, S, Satpathy, M, Sawhney, M, Shafieesabet, A, Shiferaw, MS, Smith, M, Szoeke, CEI, Tabares-Seisdedos, R, Nu, TT, Ukwaja, KN, Venketasubramanian, N, Villafaina, S, Weldegwergs, KG, Westerman, R, Wijeratne, T, Winkler, AS, Bach, TX, Yonemoto, N, Feigin, VL, Vos, T, and Murray, CJL
Subjects: Uncategorized
Abstract: [Background] Neurological disorders are now the leading source of disability globally, and ageing is increasing the burden of neurodegenerative disorders, including Parkinson's disease. We aimed to determine the global burden of Parkinson's disease between 1990 and 2016 to identify trends and to enable appropriate public health, medical, and scientific responses. [Methods] Through a systematic analysis of epidemiological studies, we estimated global, regional, and country-specific prevalence and years of life lived with disability for Parkinson's disease from 1990 to 2016. We estimated the proportion of mild, moderate, and severe Parkinson's disease on the basis of studies that used the Hoehn and Yahr scale and assigned disability weights to each level. We jointly modelled prevalence and excess mortality risk in a natural history model to derive estimates of deaths due to Parkinson's disease. Death counts were multiplied by values from the Global Burden of Disease study's standard life expectancy to compute years of life lost. Disability-adjusted life-years (DALYs) were computed as the sum of years lived with disability and years of life lost. We also analysed results based on the Socio-demographic Index, a compound measure of income per capita, education, and fertility. [Findings] In 2016, 6·1 million (95% uncertainty interval [UI] 5·0–7·3) individuals had Parkinson's disease globally, compared with 2·5 million (2·0–3·0) in 1990. This increase was not solely due to increasing numbers of older people, because age-standardised prevalence rates increased by 21·7% (95% UI 18·1–25·3) over the same period (compared with an increase of 74·3%, 95% UI 69·2–79·6, for crude prevalence rates). Parkinson's disease caused 3·2 million (95% UI 2·6–4·0) DALYs and 211 296 deaths (95% UI 167 771–265 160) in 2016. The male-to-female ratios of age-standardised prevalence rates were similar in 2016 (1·40, 95% UI 1·36–1·43) and 1990 (1·37, 1·34–1·40). From 1990 to 2016, age-standardised prevalence, DALY rates, and death rates increased for all global burden of disease regions except for southern Latin America, eastern Europe, and Oceania. In addition, age-standardised DALY rates generally increased across the Socio-demographic Index. [Interpretation] Over the past generation, the global burden of Parkinson's disease has more than doubled as a result of increasing numbers of older people, with potential contributions from longer disease duration and environmental factors. Demographic and potentially other factors are poised to increase the future burden of Parkinson's disease substantially. [Finding] Bill & Melinda Gates Foundation.
Published: 2023
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8. Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000-2018

Author: Bhattacharjee, NV, Schaeffer, LE, Hay, SI, Lu, D, Schipp, MF, Lazzar-Atwood, A, Donkers, KM, Abady, GG, Abd-Allah, F, Abdelalim, A, Abebo, ZH, Abejie, AN, Abosetugn, AE, Abreu, LG, Abrigo, MRM, Abu-Gharbieh, E, Abushouk, AI, Adamu, AL, Adedeji, IA, Adegbosin, AE, Adekanmbi, V, Adetokunboh, OO, Agudelo-Botero, M, Aji, B, Akinyemi, OO, Alamneh, AA, Alanezi, FM, Alanzi, TM, Albright, J, Alcalde-Rabanal, JE, Alemu, BW, Alhassan, RK, Ali, BA, Ali, S, Alinia, C, Alipour, V, Amit, AML, Amugsi, DA, Anbesu, EW, Ancuceanu, R, Anjomshoa, M, Ansari, F, Antonio, CAT, Anvari, D, Arabloo, J, Arora, A, Artanti, KD, Asemahagn, MA, Asmare, WN, Atout, MMW, Ausloos, M, Awoke, N, Quintanilla, BPA, Ayanore, MA, Aynalem, YA, Ayza, MA, Azene, ZN, Darshan, BB, Badiye, AD, Baig, AA, Bakkannavar, SM, Banach, M, Banik, PC, Bärnighausen, TW, Basaleem, H, Bayati, M, Baye, BA, Bedi, N, Belay, SA, Bhagavathula, AS, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhutta, ZA, Bijani, A, Birhan, TA, Birihane, BM, Bitew, ZW, Bohlouli, S, Bohluli, M, Bojia, HA, Boloor, A, Brady, OJ, Bragazzi, NL, Brunoni, AR, Budhathoki, SS, Nagaraja, SB, Butt, ZA, Cárdenas, R, Castaldelli-Maia, JM, Castro, F, Cernigliaro, A, Charan, J, Chatterjee, P, Chatterjee, S, Chattu, VK, Chaturvedi, S, Chowdhury, MAK, Chu, D-T, Collison, ML, Cook, AJ, Cork, MA, Couto, RAS, Dagnew, B, Dai, H, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Darwesh, AM, Darwish, AH, Daryani, A, Das, JK, Gupta, RD, Dávila-Cervantes, CA, Davis, AC, Weaver, ND, Denova-Gutiérrez, E, Deribe, K, Desalew, A, Deshpande, A, Dessie, A, Deuba, K, Dharmaratne, SD, Dhimal, M, Dhungana, GP, Diaz, D, Didarloo, A, Dipeolu, IO, Doan, LP, Duko, B, Duraes, AR, Dwyer-Lindgren, L, Earl, L, Zaki, MES, Tantawi, ME, Elema, TB, Elhabashy, HR, El-Jaafary, SI, Faris, PS, Faro, A, Farzadfar, F, Feigin, VL, Feleke, BE, Ferede, TY, Fischer, F, Foigt, NA, Folayan, MO, Franklin, RC, Gad, MM, Gaidhane, S, Gardner, WM, Geberemariyam, BS, Gebregiorgis, BG, Gebremedhin, KB, Gebremichael, B, Ghaffarpasand, F, Gilani, SA, Ginindza, TG, Glagn, M, Golechha, M, Gonfa, KB, Goulart, BNG, Gudi, N, Guido, D, Guled, RA, Guo, Y, Hamidi, S, Handiso, DW, Hasaballah, AI, Hassan, A, Hayat, K, Hegazy, MI, Heidari, B, Henry, NJ, Herteliu, C, de, Hidru, HD, Ho, HC, Hoang, CL, Holla, R, Hon, J, Hosseini, M, Hosseinzadeh, M, Househ, M, Hsairi, M, Hu, G, Huda, TM, Hwang, B-F, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Iqbal, U, Irvani, SSN, Islam, MM, Iwu, CCD, Iwu, CJ, Jain, A, Janodia, MD, Javaheri, T, John-Akinola, YO, Johnson, KB, Joukar, F, Jozwiak, JJ, Kabir, A, Kalankesh, LR, Kalhor, R, Kamath, A, Kamyari, N, Kanchan, OT, Kapoor, N, Matin, BK, Karimi, SE, Kasaye, HK, Kassahun, G, Kassebaum, NJ, Kayode, GA, Karyani, AK, Keiyoro, PN, Kelkay, B, Khalid, N, Khan, MN, Khatab, K, Khater, AM, Khater, MM, Khatib, MN, Kim, YJ, Kimokoti, RW, Kinyoki, DK, Kisa, A, Kisa, S, Kosen, S, Krishan, K, Kulkarni, V, Kumar, GA, Kumar, M, Kumar, N, Kumar, P, Kurmi, OP, Kusuma, D, Vecchia, CL, Lad, SD, Lami, FH, Landires, I, Lansingh, VC, Lasrado, S, Lee, PH, LeGrand, KE, Letourneau, ID, Lewycka, S, Li, B, Li, M-C, Li, S, Liu, X, Lodha, R, Lopez, JCF, Louie, C, Machado, DB, Maled, V, Maleki, S, Malta, DC, Mamun, AA, Manafi, N, Mansournia, MA, Mapoma, CC, Marczak, LB, Martins-Melo, FR, Mehndiratta, MM, Mejia-Rodriguez, F, Mekonnen, TC, Mendoza, W, Menezes, RG, Mengesha, EW, Mersha, AM, Miller, TR, Mini, GK, Mirrakhimov, EM, Misra, S, Moghadaszadeh, M, Mohammad, DK, Mohammadian-Hafshejani, A, Mohammed, JA, Mohammed, S, Mokdad, AH, Montero-Zamora, PA, Moradi, M, Moradzadeh, R, Moraga, P, Mosser, JF, Mousavi, SM, Khaneghah, AM, Munro, SB, Muriithi, MK, Mustafa, G, Muthupandian, S, Nagarajan, AJ, Naik, G, Naimzada, MD, Nangia, V, Nascimento, BR, Nayak, VC, Ndejjo, R, Ndwandwe, DE, Negoi, I, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, CT, Nguyen, DN, Nguyen, HLT, Nigussie, SN, Nigussie, TTN, Nikbakhsh, R, Nnaji, CA, Nunez-Samudio, V, Oancea, B, Oghenetega, OB, Olagunju, AT, Olusanya, BO, Olusanya, JO, Omer, MO, Onwujekwe, OE, Ortega-Altamirano, DV, Osgood-Zimmerman, AE, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Mahesh, PA, Padubidri, JR, Pana, A, Pandey, A, Pandi-Perumal, SR, Pangaribuan, HU, Parsekar, SS, Pasupula, DK, Patel, UK, Pathak, A, Pathak, M, Pattanshetty, SM, Patton, GC, Paulos, K, Pepito, VCF, Pickering, BV, Pinheiro, M, Piwoz, EG, Pokhrel, KN, Pourjafar, H, Prada, SI, Pribadi, DRA, Syed, ZQ, Rabiee, M, Rabiee, N, Rahim, F, Rahimzadeh, S, Rahman, A, Rahman, MHU, Rahmani, AM, Rai, RK, Ranabhat, CL, Rao, SJ, Rastogi, P, Rathi, P, Rawaf, DL, Rawaf, S, Rawassizadeh, R, Rawat, R, Regassa, LD, Rego, MAS, Reiner, RC, Reshmi, B, Rezapour, A, Ribeiro, AI, Rickard, J, Roever, L, Rumisha, SF, Rwegerera, GM, Sagar, R, Sajadi, SM, Salem, MR, Samy, AM, Santric-Milicevic, MM, Saraswathy, SYI, Sarker, AR, Sartorius, B, Sathian, B, Saxena, D, Sbarra, AN, Sengupta, D, Senthilkumaran, S, Sha, F, Shafaat, O, Shaheen, AA, Shaikh, MA, Shalash, AS, Shannawaz, M, Sheikh, A, Shetty, BSK, Shetty, RS, Shibuya, K, Shiferaw, WS, Shin, JI, Silva, DAS, Singh, NP, Singh, P, Singh, S, Sintayehu, Y, Skryabin, VY, Skryabina, AA, Soheili, A, Soltani, S, Sorrie, MB, Spurlock, EE, Steuben, KM, Sudaryanto, A, Sufiyan, MB, Swartz, SJ, Tadesse, EG, Tamiru, AT, Tapak, L, Tareque, MI, Tarigan, IU, Tesema, GA, Tesfay, FH, Teshome, A, Tessema, ZT, Thankappan, KR, Thapar, R, Thomas, N, Topor-Madry, R, Tovani-Palone, MR, Traini, E, Tran, BX, Truong, PN, Tsegaye, BTBT, Ullah, I, Umeokonkwo, CD, Unnikrishnan, B, Upadhyay, E, Uzochukwu, BSC, VanderHeide, JD, Violante, FS, Vo, B, Wado, YD, Waheed, Y, Wamai, RG, Wang, F, Wang, Y, Wang, Y-P, Wickramasinghe, ND, Wiens, KE, Wiysonge, CS, Woyczynski, L, Wu, A-M, Wu, C, Yamada, T, Yaya, S, Yeshaneh, A, Yeshaw, Y, Yeshitila, YG, Yilma, MT, Yip, P, Yonemoto, N, Yosef, T, Younis, MZ, Yousuf, AY, Yu, C, Yu, Y, Yuce, D, Zafar, S, Zaidi, SS, Zaki, L, Zakzuk, J, Zamanian, M, Zar, HJ, Zastrozhin, MS, Zastrozhina, A, Zelellw, DA, Zhang, Y, Zhang, Z-J, Zhao, X-JG, Zodpey, S, Zuniga, YMH, Local Burden of Disease Exclusive Breastfeeding Collaborators, Bhattacharjee, Natalia V, Schaeffer, Lauren E, Hay, Simon I, Duko, Bereket, Yeshaw, Yigizie, Local Burden of Disease Exclusive Breastfeeding Collaborators, Bhattacharjee N.V., Schaeffer L.E., Hay S.I., Lu D., Schipp M.F., Lazzar-Atwood A., Donkers K.M., Abady G.G., Abd-Allah F., Abdelalim A., Abebo Z.H., Abejie A.N., Abosetugn A.E., Abreu L.G., Abrigo M.R.M., Abu-Gharbieh E., Abushouk A.I., Adamu A.L., Adedeji I.A., Adegbosin A.E., Adekanmbi V., Adetokunboh O.O., Agudelo-Botero M., Aji B., Akinyemi O.O., Alamneh A.A., Alanezi F.M., Alanzi T.M., Albright J., Alcalde-Rabanal J.E., Alemu B.W., Alhassan R.K., Ali B.A., Ali S., Alinia C., Alipour V., Amit A.M.L., Amugsi D.A., Anbesu E.W., Ancuceanu R., Anjomshoa M., Ansari F., Antonio C.A.T., Anvari D., Arabloo J., Arora A., Artanti K.D., Asemahagn M.A., Asmare W.N., Atout M.M.W., Ausloos M., Awoke N., Quintanilla B.P.A., Ayanore M.A., Aynalem Y.A., Ayza M.A., Azene Z.N., Darshan B.B., Badiye A.D., Baig A.A., Bakkannavar S.M., Banach M., Banik P.C., Barnighausen T.W., Basaleem H., Bayati M., Baye B.A., Bedi N., Belay S.A., Bhagavathula A.S., Bhandari D., Bhardwaj N., Bhardwaj P., Bhutta Z.A., Bijani A., Birhan T.A., Birihane B.M., Bitew Z.W., Bohlouli S., Bohluli M., Bojia H.A., Boloor A., Brady O.J., Bragazzi N.L., Brunoni A.R., Budhathoki S.S., Nagaraja S.B., Butt Z.A., Cardenas R., Castaldelli-Maia J.M., Castro F., Cernigliaro A., Charan J., Chatterjee P., Chatterjee S., Chattu V.K., Chaturvedi S., Chowdhury M.A.K., Chu D.-T., Collison M.L., Cook A.J., Cork M.A., Couto R.A.S., Dagnew B., Dai H., Dandona L., Dandona R., Daneshpajouhnejad P., Darwesh A.M., Darwish A.H., Daryani A., Das J.K., Gupta R.D., Davila-Cervantes C.A., Davis A.C., Weaver N.D., Denova-Gutierrez E., Deribe K., Desalew A., Deshpande A., Dessie A., Deuba K., Dharmaratne S.D., Dhimal M., Dhungana G.P., Diaz D., Didarloo A., Dipeolu I.O., Doan L.P., Duko B., Duraes A.R., Dwyer-Lindgren L., Earl L., Zaki M.E.S., Tantawi M.E., Elema T.B., Elhabashy H.R., El-Jaafary S.I., Faris P.S., Faro A., Farzadfar F., Feigin V.L., Feleke B.E., Ferede T.Y., Fischer F., Foigt N.A., Folayan M.O., Franklin R.C., Gad M.M., Gaidhane S., Gardner W.M., Geberemariyam B.S., Gebregiorgis B.G., Gebremedhin K.B., Gebremichael B., Ghaffarpasand F., Gilani S.A., Ginindza T.G., Glagn M., Golechha M., Gonfa K.B., Goulart B.N.G., Gudi N., Guido D., Guled R.A., Guo Y., Hamidi S., Handiso D.W., Hasaballah A.I., Hassan A., Hayat K., Hegazy M.I., Heidari B., Henry N.J., Herteliu C., de Hidru H.D., Ho H.C., Hoang C.L., Holla R., Hon J., Hosseini M., Hosseinzadeh M., Househ M., Hsairi M., Hu G., Huda T.M., Hwang B.-F., Ibitoye S.E., Ilesanmi O.S., Ilic I.M., Ilic M.D., Inbaraj L.R., Iqbal U., Irvani S.S.N., Islam M.M., Iwu C.C.D., Iwu C.J., Jain A., Janodia M.D., Javaheri T., John-Akinola Y.O., Johnson K.B., Joukar F., Jozwiak J.J., Kabir A., Kalankesh L.R., Kalhor R., Kamath A., Kamyari N., Kanchan O.T., Kapoor N., Matin B.K., Karimi S.E., Kasaye H.K., Kassahun G., Kassebaum N.J., Kayode G.A., Karyani A.K., Keiyoro P.N., Kelkay B., Khalid N., Khan M.N., Khatab K., Khater A.M., Khater M.M., Khatib M.N., Kim Y.J., Kimokoti R.W., Kinyoki D.K., Kisa A., Kisa S., Kosen S., Krishan K., Kulkarni V., Kumar G.A., Kumar M., Kumar N., Kumar P., Kurmi O.P., Kusuma D., Vecchia C.L., Lad S.D., Lami F.H., Landires I., Lansingh V.C., Lasrado S., Lee P.H., LeGrand K.E., Letourneau I.D., Lewycka S., Li B., Li M.-C., Li S., Liu X., Lodha R., Lopez J.C.F., Louie C., Machado D.B., Maled V., Maleki S., Malta D.C., Mamun A.A., Manafi N., Mansournia M.A., Mapoma C.C., Marczak L.B., Martins-Melo F.R., Mehndiratta M.M., Mejia-Rodriguez F., Mekonnen T.C., Mendoza W., Menezes R.G., Mengesha E.W., Mersha A.M., Miller T.R., Mini G.K., Mirrakhimov E.M., Misra S., Moghadaszadeh M., Mohammad D.K., Mohammadian-Hafshejani A., Mohammed J.A., Mohammed S., Mokdad A.H., Montero-Zamora P.A., Moradi M., Moradzadeh R., Moraga P., Mosser J.F., Mousavi S.M., Khaneghah A.M., Munro S.B., Muriithi M.K., Mustafa G., Muthupandian S., Nagarajan A.J., Naik G., Naimzada M.D., Nangia V., Nascimento B.R., Nayak V.C., Ndejjo R., Ndwandwe D.E., Negoi I., Nguefack-Tsague G., Ngunjiri J.W., Nguyen C.T., Nguyen D.N., Nguyen H.L.T., Nigussie S.N., Nigussie T.T.N., Nikbakhsh R., Nnaji C.A., Nunez-Samudio V., Oancea B., Oghenetega O.B., Olagunju A.T., Olusanya B.O., Olusanya J.O., Omer M.O., Onwujekwe O.E., Ortega-Altamirano D.V., Osgood-Zimmerman A.E., Otstavnov N., Otstavnov S.S., Owolabi M.O., Mahesh P.A., Padubidri J.R., Pana A., Pandey A., Pandi-Perumal S.R., Pangaribuan H.U., Parsekar S.S., Pasupula D.K., Patel U.K., Pathak A., Pathak M., Pattanshetty S.M., Patton G.C., Paulos K., Pepito V.C.F., Pickering B.V., Pinheiro M., Piwoz E.G., Pokhrel K.N., Pourjafar H., Prada S.I., Pribadi D.R.A., Syed Z.Q., Rabiee M., Rabiee N., Rahim F., Rahimzadeh S., Rahman A., Rahman M.H.U., Rahmani A.M., Rai R.K., Ranabhat C.L., Rao S.J., Rastogi P., Rathi P., Rawaf D.L., Rawaf S., Rawassizadeh R., Rawat R., Regassa L.D., Rego M.A.S., Reiner R.C., Reshmi B., Rezapour A., Ribeiro A.I., Rickard J., Roever L., Rumisha S.F., Rwegerera G.M., Sagar R., Sajadi S.M., Salem M.R., Samy A.M., Santric-Milicevic M.M., Saraswathy S.Y.I., Sarker A.R., Sartorius B., Sathian B., Saxena D., Sbarra A.N., Sengupta D., Senthilkumaran S., Sha F., Shafaat O., Shaheen A.A., Shaikh M.A., Shalash A.S., Shannawaz M., Sheikh A., Shetty B.S.K., Shetty R.S., Shibuya K., Shiferaw W.S., Shin J.I., Silva D.A.S., Singh N.P., Singh P., Singh S., Sintayehu Y., Skryabin V.Y., Skryabina A.A., Soheili A., Soltani S., Sorrie M.B., Spurlock E.E., Steuben K.M., Sudaryanto A., Sufiyan M.B., Swartz S.J., Tadesse E.G., Tamiru A.T., Tapak L., Tareque M.I., Tarigan I.U., Tesema G.A., Tesfay F.H., Teshome A., Tessema Z.T., Thankappan K.R., Thapar R., Thomas N., Topor-Madry R., Tovani-Palone M.R., Traini E., Tran B.X., Truong P.N., Tsegaye B.T.B.T., Ullah I., Umeokonkwo C.D., Unnikrishnan B., Upadhyay E., Uzochukwu B.S.C., VanderHeide J.D., Violante F.S., Vo B., Wado Y.D., Waheed Y., Wamai R.G., Wang F., Wang Y., Wang Y.-P., Wickramasinghe N.D., Wiens K.E., Wiysonge C.S., Woyczynski L., Wu A.-M., Wu C., Yamada T., Yaya S., Yeshaneh A., Yeshaw Y., Yeshitila Y.G., Yilma M.T., Yip P., Yonemoto N., Yosef T., Younis M.Z., Yousuf A.Y., Yu C., Yu Y., Yuce D., Zafar S., Zaidi S.S., Zaki L., Zakzuk J., Zamanian M., Zar H.J., Zastrozhin M.S., Zastrozhina A., Zelellw D.A., Zhang Y., Zhang Z.-J., Zhao X.-J.G., Zodpey S., Zuniga Y.M.H., Collaborators, Local Burden of Disease Exclusive Breastfeeding, and Instituto de Saúde Pública da Universidade do Porto
Subjects: RJ101, Psychological intervention, Breastfeeding, Social Sciences, geography, Behavioral Neuroscience, 0302 clinical medicine, RA0421, Prevalence, Psychology, policy making, 030212 general & internal medicine, Policy Making, humans, media_common, CHILD GROWTH FAILURE, Developing world, 0303 health sciences, education.field_of_study, Psychology, Biological, Geography, Psychology, Experimental, Health Status Disparitie, Multidisciplinary Sciences, Breast Feeding, breast feeding, Scale (social sciences), Science & Technology - Other Topics, Life Sciences & Biomedicine, Human, AFRICA, Social Psychology, Inequality, spatial analysis, media_common.quotation_subject, public policy, Population, prevalence, Public policy, Developing country, Experimental and Cognitive Psychology, Public Policy, Local Burden of Disease Exclusive Breastfeeding Collaborators, Article, Developing Countrie, 03 medical and health sciences, Environmental health, Humans, Nutrition disorders, education, Developing Countries, 030304 developmental biology, Spatial Analysis, Science & Technology, Neurosciences, Health Status Disparities, developing countries, health status disparities, Risk factors, Neurosciences & Neurology, Breast feeding
Abstract: Exclusive breastfeeding (EBF)—giving infants only breast-milk for the first 6 months of life—is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization’s Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030., Bhattacharjee and Schaeffer et al. map exclusive breastfeeding (EBF) in 94 low- and middle-income countries (LMICs), finding increased EBF practice and reduced subnational variation across the majority of LMICs from 2000 to 2018. However, only six LMICs will meet WHO’s target of ≥70% EBF by 2030 nationally, and only three will achieve this in all districts.
Published: 2021

9. Neurological Manifestations in a Cohort of Egyptian Patients with COVID-19: A Prospective, Multicenter, Observational Study

Author: Mekkawy, DA, Hamdy, S, Abdel-Naseer, M, Shehata, HS, Halfawy, AA, Shalaby, NM, Shehata, GA, Ali, AM, Elmazny, A, Ahmed, SM, Ismail, JH, Ibraheim, A, Abdel-Hamid, HM, Magdy, R, Kabara Ayoub, Y, Taha, AE, Merghany, N, Soliman, NM, Elshebawy, H, Abdelal, SES, El-Ghoneimy, L, Al-Athwari, A, Kishk, NA, Nada, MAF, Farghaly, M, Hassan, A, Hegazy, MI, Abdelalim, A, Mourad, HS, Hassouna, A, Othman, AS, Wijeratne, T, Mekkawy, DA, Hamdy, S, Abdel-Naseer, M, Shehata, HS, Halfawy, AA, Shalaby, NM, Shehata, GA, Ali, AM, Elmazny, A, Ahmed, SM, Ismail, JH, Ibraheim, A, Abdel-Hamid, HM, Magdy, R, Kabara Ayoub, Y, Taha, AE, Merghany, N, Soliman, NM, Elshebawy, H, Abdelal, SES, El-Ghoneimy, L, Al-Athwari, A, Kishk, NA, Nada, MAF, Farghaly, M, Hassan, A, Hegazy, MI, Abdelalim, A, Mourad, HS, Hassouna, A, Othman, AS, and Wijeratne, T
Abstract: BACKGROUND: The COVID-19 pandemic has reached over 276 million people globally with 5.3 million deaths as of 22nd December 2021. COVID-19-associated acute and long-term neurological manifestations are well recognized. The exact profile and the timing of neurological events in relation to the onset of infection are worth exploring. The aim of the current body of work was to determine the frequency, pattern, and temporal profile of neurological manifestations in a cohort of Egyptian patients with confirmed COVID-19 infection. METHODS: This was a prospective study conducted on 582 hospitalized COVID-19 patients within the first two weeks of the diagnosis of COVID-19 to detect any specific or non-specific neurological events. RESULTS: The patients' mean (SD) age was 46.74 (17.26) years, and 340 (58.42%) patients were females. The most commonly encountered COVID-19 symptoms were fever (90.72%), cough (82.99%), and fatigue (76.98%). Neurological events (NE) detected in 283 patients (48.63%) and were significantly associated with a severe COVID-19 at the onset (OR: 3.13; 95% CI: 2.18-4.51; p < 0.0001) and with a higher mortality (OR: 2.56; 95% CI: 1.48-5.46; p = 0.019). The most frequently reported NEs were headaches (n = 167) and myalgias (n = 126). Neurological syndromes included stroke (n = 14), encephalitis (n = 12), encephalopathy (n = 11), transverse myelitis (n = 6) and Guillain-Barré syndrome (n = 4). CONCLUSIONS: Neurological involvement is common (48.63%) in COVID-19 patients within the first two weeks of the illness. This includes neurological symptoms such as anosmia, headaches, as well as a constellation of neurological syndromes such as stroke, encephalitis, transverse myelitis, and Guillain-Barré syndrome. Severity of acute COVID-19 illness and older age are the main risk factors.
Published: 2022

10. Global and regional burden of disease and injury in 2016 arising from occupational exposures: a systematic analysis for the Global Burden of Disease Study 2016

Author: Driscoll, T, Rushton, L, Hutchings, SJ, Straif, K, Steenland, K, Abate, D, Abbafat, C, Acharya, D, Adebayo, OM, Afshari, M, Akinyemiju, T, Alahdab, F, Anjomshoa, M, Antonio, CAT, Aremu, O, Ataro, Z, Quintanilla, BPA, Banoub, JAM, Barker-Collo, SL, Barnighausen, TW, Barrero, LH, Bedi, N, Behzadifar, M, Benavides, FG, Beuran, M, Bhattacharyya, K, Bijani, A, Cardenas, R, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Cerin, E, Cooper, C, Dandona, L, Dandona, R, Dang, AK, Daryani, A, Desalegn, BB, Dharmaratne, SD, Dubljanin, E, El-Khatib, Z, Eskandarieh, S, Fareed, M, Faro, A, Fereshtehnejad, S-M, Fernandes, E, Filip, I, Fischer, F, Fukumoto, T, Gallus, S, Gebremichael, TG, Gezae, KE, Gill, TK, Goulart, BNG, Grada, A, Guo, Y, Gupta, R, Haj-Mirzaian, A, Hamadeh, RR, Hamidi, S, Hamzeh, B, Hassankhani, H, Hawkins, DM, Hay, SI, Hegazy, MI, Henok, A, Hoang, CL, Hole, MK, Rad, EH, Hossain, N, Hosseini, M, Hostiuc, S, Hu, G, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Jakovljevic, M, Jha, RP, Jonas, JB, Shushtar, ZJ, Jozwiak, JJ, Jurisson, M, Kahsay, A, Karami, M, Karimi, N, Kasaeian, A, Kawakami, N, Khader, YS, Khan, EA, Khubchandani, J, Kim, YJ, Kisa, A, Defo, BK, Kumar, GA, Kumar, M, Lami, FH, Latif, A, Leigh, J, Levi, M, Li, S, Linn, S, Lopez, JCF, Lunevicius, R, Mahotra, NB, Majdan, M, Malekzadeh, R, Mansournia, MA, Massenburg, BB, Mehta, V, Melese, A, Memish, ZA, Mendoza, W, Mengistu, G, Meretoja, TJ, Mestrovic, T, Miazgowski, T, Miller, TR, Mini, GK, Mirrakhimov, EM, Moazen, B, Mezerji, NMG, Mohammed, S, Mohebi, F, Mokdad, AH, Molokhia, M, Monasta, L, Moodley, Y, Moosazadeh, M, Morad, G, Moradi-Lakeh, M, Morawska, L, Morrison, SD, Mousav, SM, Mustafa, G, Najaf, F, Nangia, V, Negoi, I, Negoi, RI, Neupane, S, Nguyen, CT, Nguyen, TH, Nixon, MR, Ofori-Asenso, R, Ogbo, FA, Olagunju, AT, Olusanya, BO, Otstavnov, SS, Mahesh, PA, Panda-Jonas, S, Park, E-K, Prakash, S, Qorbani, M, Radfar, A, Rafay, A, Rahim, F, Reiner, RC, Renzaho, AMN, Roever, L, Ronfani, L, Saddik, B, Safari-Faramani, R, Safi, S, Safiri, S, Salamati, P, Salimi, Y, Samy, AM, Schwebel, DC, Sepanlou, SG, Serdar, B, Shaikh, MA, Shams-Beyranvand, M, Sharif-Alhoseini, M, She, J, Shigematsu, M, Shiri, R, Shirkoohi, R, Si, S, Sinha, DN, Stanaway, JD, Soofi, M, Stokes, MA, Sufiyan, MB, Tabares-Seisdedos, R, Takahashi, K, Tassew, SG, Tehrani-Banihashemi, A, Tran, M-HTBX, Tran, KB, Car, LT, Ullah, I, Valdez, PR, Vasankari, TJ, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, V, Vu, GT, Wagner, GR, Waheed, Y, Wang, Y-P, Werdecker, A, Winkler, AS, Yimer, EM, Yip, P, Yirsaw, BD, Yisma, E, Yonemoto, N, Yousefifard, M, Bin Zaman, S, Zamani, M, Zandian, H, Zhang, Y, Zodpey, S, Lim, SS, Driscoll, Tim, Rushton, Lesley, Hutchings, Sally J, Straif, Kurt, Kumar, Manasi, Yisma, Engida, Lim, Stephen S, GBD 2016 Occupational Risk Factors Collaborators, Collaborators, GBD 2016 Occupational Risk Factors, Institute for Molecular Medicine Finland, Clinicum, HUS Comprehensive Cancer Center, GBD 2016 Occupational Risk Factors Collaborator, and Violante FS
Subjects: Male, exposure assessment, Global Health, medicine.disease_cause, Global Burden of Disease, ergonomic, GBD 2016 Occupational Risk Factors Collaborators, 0302 clinical medicine, Risk Factors, 1599 Other Commerce, Management, Tourism and Services, Neoplasms, METABOLIC RISKS, Per capita, Medicine, 030212 general & internal medicine, Public, Environmental & Occupational Health, Aged, 80 and over, education.field_of_study, Human factors and ergonomics, Middle Aged, 030210 environmental & occupational health, 3142 Public health care science, environmental and occupational health, 3. Good health, Occupational Diseases, COMPARATIVE RISK-ASSESSMENT, Female, Quality-Adjusted Life Years, Risk assessment, Life Sciences & Biomedicine, Adult, COUNTRIES, noise, Adolescent, Population, cancer, respiratory tract diseases, workplace, Risk Assessment, Environmental & Occupational Health, Asbestos, respiratory tract disease, 1117 Public Health and Health Services, Young Adult, 03 medical and health sciences, Age Distribution, Life Expectancy, Occupational Exposure, Environmental health, Humans, Disabled Persons, Sex Distribution, education, Aged, Science & Technology, business.industry, Public Health, Environmental and Occupational Health, 1103 Clinical Sciences, TRENDS, Quality-adjusted life year, Socioeconomic Factors, Attributable risk, Commentary, Life expectancy, Wounds and Injuries, CLUSTERS, business, Low Back Pain
Abstract: ObjectivesThis study provides an overview of the influence of occupational risk factors on the global burden of disease as estimated by the occupational component of the Global Burden of Disease (GBD) 2016 study.MethodsThe GBD 2016 study estimated the burden in terms of deaths and disability-adjusted life years (DALYs) arising from the effects of occupational risk factors (carcinogens; asthmagens; particulate matter, gases and fumes (PMGF); secondhand smoke (SHS); noise; ergonomic risk factors for low back pain; risk factors for injury). A population attributable fraction (PAF) approach was used for most risk factors.ResultsIn 2016, globally, an estimated 1.53 (95% uncertainty interval 1.39–1.68) million deaths and 76.1 (66.3–86.3) million DALYs were attributable to the included occupational risk factors, accounting for 2.8% of deaths and 3.2% of DALYs from all causes. Most deaths were attributable to PMGF, carcinogens (particularly asbestos), injury risk factors and SHS. Most DALYs were attributable to injury risk factors and ergonomic exposures. Men and persons 55 years or older were most affected. PAFs ranged from 26.8% for low back pain from ergonomic risk factors and 19.6% for hearing loss from noise to 3.4% for carcinogens. DALYs per capita were highest in Oceania, Southeast Asia and Central sub-Saharan Africa. On a per capita basis, between 1990 and 2016 there was an overall decrease of about 31% in deaths and 25% in DALYs.ConclusionsOccupational exposures continue to cause an important health burden worldwide, justifying the need for ongoing prevention and control initiatives.
Published: 2020

11. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Author: Micah, AE, Cogswell, IE, Cunningham, B, Ezoe, S, Harle, AC, Maddison, ER, McCracken, D, Nomura, S, Simpson, KE, Stutzman, HN, Tsakalos, G, Wallace, LE, Zhao, Y, Zende, RR, Abbafati, C, Abdelmasseh, M, Abedi, A, Abegaz, KH, Abhilash, ES, Abolhassani, H, Abrigo, MRM, Adhikari, TB, Afzal, S, Ahinkorah, BO, Ahmadi, S, Ahmed, H, Ahmed, MB, Rashid, TA, Ajami, M, Aji, B, Akalu, Y, Akunna, CJ, Al Hamad, H, Alam, K, Alanezi, FM, Alanzi, TM, Alemayehu, Y, Alhassan, RK, Alinia, C, Aljunid, SM, Almustanyir, SA, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amini, S, Amini-Rarani, M, Amu, H, Ancuceanu, R, Andrei, CL, Andrei, T, Angell, B, Anjomshoa, M, Antonio, CAT, Antony, CM, Aqeel, M, Arabloo, J, Arab-Zozani, M, Aripov, T, Arrigo, A, Ashraf, T, Atnafu, DD, Ausloos, M, Avila-Burgos, L, Awan, AT, Ayano, G, Ayanore, MA, Azari, S, Azhar, GS, Babalola, TK, Bahrami, MA, Baig, AA, Banach, M, Barati, N, Barnighausen, TW, Barrow, A, Basu, S, Baune, BT, Bayati, M, Benzian, H, Berman, AE, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bibi, S, Bijani, A, Bodolica, V, Bragazzi, NL, Braithwaite, D, Breitborde, NJK, Breusov, AV, Briko, NI, Busse, R, Cahuana-Hurtado, L, Callander, EJ, Camera, LA, Castaneda-Orjuela, CA, Catala-Lopez, F, Charan, J, Chatterjee, S, Chattu, SK, Chattu, VK, Chen, S, Cicero, AFG, Dadras, O, Dahlawi, SMA, Dai, X, Dalal, K, Dandona, L, Dandona, R, Davitoiu, DV, De Neve, J-W, de Sa-Junior, AR, Denova-Gutierrez, E, Dhamnetiya, D, Dharmaratne, SD, Doshmangir, L, Dube, J, Ehsani-Chimeh, E, Zaki, MES, El Tantawi, M, Eskandarieh, S, Farzadfar, F, Ferede, TY, Fischer, F, Foigt, NA, Freitas, A, Friedman, SD, Fukumoto, T, Fullman, N, Gaal, PA, Gad, MM, Garcia-Gordillo, MA, Garg, T, Ghafourifard, M, Ghashghaee, A, Gholamian, A, Gholamrezanezhad, A, Ghozali, G, Gilani, SA, Glavan, I-R, Glushkova, EV, Goharinezhad, S, Golechha, M, Goli, S, Guha, A, Gupta, VB, Gupta, VK, Haakenstad, A, Haider, MR, Hailu, A, Hamidi, S, Hanif, A, Harapan, H, Hartono, RK, Hasaballah, AI, Hassan, S, Hassanein, MH, Hayat, K, Hegazy, MI, Heidari, G, Hendrie, D, Heredia-Pi, I, Herteliu, C, Hezam, K, Holla, R, Hossain, SJ, Hosseinzadeh, M, Hostiuc, S, Huda, TM, Hwang, B-F, Iavicoli, I, Idrisov, B, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Ismail, NE, Isola, G, Jahani, MA, Jahanmehr, N, Jakovljevic, M, Janodia, MD, Javaheri, T, Jayapal, SK, Jayawardena, R, Jazayeri, SB, Jha, RP, Jonas, JB, Joo, T, Joukar, F, Jurisson, M, Kaambwa, B, Kalhor, R, Kanchan, T, Kandel, H, Matin, BK, Karimi, SE, Kassahun, G, Kayode, GA, Karyani, AK, Keikavoosi-Arani, L, Khader, YS, Khajuria, H, Khalilov, R, Khammarnia, M, Khan, J, Khubchandani, J, Kianipour, N, Kim, GR, Kim, YJ, Kisa, A, Kisa, S, Kohler, S, Kosen, S, Koteeswaran, R, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kumar, GA, Kusuma, D, Lamnisos, D, Lansingh, VC, Larsson, AO, Lasrado, S, Le, LKD, Lee, SWH, Lee, YY, Lim, SS, Lobo, SW, Lozano, R, Abd El Razek, HM, Abd El Razek, MM, Mahdavi, MM, Majeed, A, Makki, A, Maleki, A, Malekzadeh, R, Manda, AL, Mansour-Ghanaei, F, Mansournia, MA, Arnedo, CAM, Martinez-Valle, A, Masoumi, SZ, Maude, RJ, Mckee, M, Medina-Solis, CE, Menezes, RG, Meretoja, A, Meretoja, TJ, Mesregah, MK, Mestrovic, T, Kostova, NM, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Mohajer, B, Mohamed, TA, Mohammadi, M, Mohammadian-Hafshejani, A, Mohammed, S, Moitra, M, Mokdad, AH, Molokhia, M, Moni, MA, Moradi, Y, Morze, J, Mousavi, SM, Mpundu-Kaambwa, C, Muriithi, MK, Muthupandian, S, Nagarajan, AJ, Naimzada, MD, Nangia, V, Naqvi, AA, Narayana, AI, Nascimento, BR, Naveed, M, Nayak, BP, Nazari, J, Ndejjo, R, Negoi, I, Kandel, SN, Trang, HN, Nonvignon, J, Noubiap, JJ, Nwatah, VE, Oancea, B, Ojelabi, FAO, Olagunju, AT, Olakunde, BO, Olgiati, S, Olusanya, JO, Onwujekwe, OE, Otoiu, A, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Padubidri, JR, Palladino, R, Panda-Jonas, S, Park, E-C, Kan, FP, Pawar, S, Toroudi, HP, Pereira, DM, Perianayagam, A, Pesudovs, K, Piccinelli, C, Postma, MJ, Prada, SI, Rabiee, M, Rabiee, N, Rahim, F, Rahimi-Movaghar, V, Rahman, MHU, Rahman, M, Rahmani, AM, Ram, U, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rathi, P, Rawaf, DL, Rawaf, S, Rawal, L, Rawassizadeh, R, Reiner, RC, Renzaho, AMN, Reshmi, B, Riaz, MA, Ripon, RK, Saad, AM, Sahraian, MA, Sahu, M, Salama, JS, Salehi, S, Samy, AM, Sanabria, J, Sanmarchi, F, Santos, JV, Santric-Milicevic, MM, Sathian, B, Savic, M, Saxena, D, Sayyah, M, Schwendicke, F, Senthilkumaran, S, Sepanlou, SG, Seylani, A, Shahabi, S, Shaikh, MA, Sheikh, A, Shetty, A, Shetty, PH, Shibuya, K, Shrime, MG, Shuja, KH, Singh, JA, Skryabin, VY, Skryabina, AA, Soltani, S, Soofi, M, Spurlock, EE, Stefan, SC, Szerencses, V, Szocska, M, Tabares-Seisdedos, R, Taddele, BW, Tefera, YG, Thavamani, A, Tobe-Gai, R, Topor-Madry, R, Tovani-Palone, MR, Bach, XT, Car, LT, Ullah, A, Ullah, S, Umar, N, Undurraga, EA, Valdez, PR, Vasankari, TJ, Villafane, JH, Violante, FS, Vlassov, V, Bay, V, Vollmer, S, Theo, V, Giang, TV, Linh, GV, Wamai, RG, Werdecker, A, Woldekidan, MA, Wubishet, BL, Xu, G, Yaya, S, Yazdi-Feyzabadi, V, Yigit, V, Yip, P, Yirdaw, BW, Yonemoto, N, Younis, MZ, Yu, C, Yunusa, I, Moghadam, TZ, Zandian, H, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Ziapour, A, Zuniga, YMH, Hay, SI, Murray, CJL, Dieleman, JL, Micah, AE, Cogswell, IE, Cunningham, B, Ezoe, S, Harle, AC, Maddison, ER, McCracken, D, Nomura, S, Simpson, KE, Stutzman, HN, Tsakalos, G, Wallace, LE, Zhao, Y, Zende, RR, Abbafati, C, Abdelmasseh, M, Abedi, A, Abegaz, KH, Abhilash, ES, Abolhassani, H, Abrigo, MRM, Adhikari, TB, Afzal, S, Ahinkorah, BO, Ahmadi, S, Ahmed, H, Ahmed, MB, Rashid, TA, Ajami, M, Aji, B, Akalu, Y, Akunna, CJ, Al Hamad, H, Alam, K, Alanezi, FM, Alanzi, TM, Alemayehu, Y, Alhassan, RK, Alinia, C, Aljunid, SM, Almustanyir, SA, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amini, S, Amini-Rarani, M, Amu, H, Ancuceanu, R, Andrei, CL, Andrei, T, Angell, B, Anjomshoa, M, Antonio, CAT, Antony, CM, Aqeel, M, Arabloo, J, Arab-Zozani, M, Aripov, T, Arrigo, A, Ashraf, T, Atnafu, DD, Ausloos, M, Avila-Burgos, L, Awan, AT, Ayano, G, Ayanore, MA, Azari, S, Azhar, GS, Babalola, TK, Bahrami, MA, Baig, AA, Banach, M, Barati, N, Barnighausen, TW, Barrow, A, Basu, S, Baune, BT, Bayati, M, Benzian, H, Berman, AE, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bibi, S, Bijani, A, Bodolica, V, Bragazzi, NL, Braithwaite, D, Breitborde, NJK, Breusov, AV, Briko, NI, Busse, R, Cahuana-Hurtado, L, Callander, EJ, Camera, LA, Castaneda-Orjuela, CA, Catala-Lopez, F, Charan, J, Chatterjee, S, Chattu, SK, Chattu, VK, Chen, S, Cicero, AFG, Dadras, O, Dahlawi, SMA, Dai, X, Dalal, K, Dandona, L, Dandona, R, Davitoiu, DV, De Neve, J-W, de Sa-Junior, AR, Denova-Gutierrez, E, Dhamnetiya, D, Dharmaratne, SD, Doshmangir, L, Dube, J, Ehsani-Chimeh, E, Zaki, MES, El Tantawi, M, Eskandarieh, S, Farzadfar, F, Ferede, TY, Fischer, F, Foigt, NA, Freitas, A, Friedman, SD, Fukumoto, T, Fullman, N, Gaal, PA, Gad, MM, Garcia-Gordillo, MA, Garg, T, Ghafourifard, M, Ghashghaee, A, Gholamian, A, Gholamrezanezhad, A, Ghozali, G, Gilani, SA, Glavan, I-R, Glushkova, EV, Goharinezhad, S, Golechha, M, Goli, S, Guha, A, Gupta, VB, Gupta, VK, Haakenstad, A, Haider, MR, Hailu, A, Hamidi, S, Hanif, A, Harapan, H, Hartono, RK, Hasaballah, AI, Hassan, S, Hassanein, MH, Hayat, K, Hegazy, MI, Heidari, G, Hendrie, D, Heredia-Pi, I, Herteliu, C, Hezam, K, Holla, R, Hossain, SJ, Hosseinzadeh, M, Hostiuc, S, Huda, TM, Hwang, B-F, Iavicoli, I, Idrisov, B, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Ismail, NE, Isola, G, Jahani, MA, Jahanmehr, N, Jakovljevic, M, Janodia, MD, Javaheri, T, Jayapal, SK, Jayawardena, R, Jazayeri, SB, Jha, RP, Jonas, JB, Joo, T, Joukar, F, Jurisson, M, Kaambwa, B, Kalhor, R, Kanchan, T, Kandel, H, Matin, BK, Karimi, SE, Kassahun, G, Kayode, GA, Karyani, AK, Keikavoosi-Arani, L, Khader, YS, Khajuria, H, Khalilov, R, Khammarnia, M, Khan, J, Khubchandani, J, Kianipour, N, Kim, GR, Kim, YJ, Kisa, A, Kisa, S, Kohler, S, Kosen, S, Koteeswaran, R, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kumar, GA, Kusuma, D, Lamnisos, D, Lansingh, VC, Larsson, AO, Lasrado, S, Le, LKD, Lee, SWH, Lee, YY, Lim, SS, Lobo, SW, Lozano, R, Abd El Razek, HM, Abd El Razek, MM, Mahdavi, MM, Majeed, A, Makki, A, Maleki, A, Malekzadeh, R, Manda, AL, Mansour-Ghanaei, F, Mansournia, MA, Arnedo, CAM, Martinez-Valle, A, Masoumi, SZ, Maude, RJ, Mckee, M, Medina-Solis, CE, Menezes, RG, Meretoja, A, Meretoja, TJ, Mesregah, MK, Mestrovic, T, Kostova, NM, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Mohajer, B, Mohamed, TA, Mohammadi, M, Mohammadian-Hafshejani, A, Mohammed, S, Moitra, M, Mokdad, AH, Molokhia, M, Moni, MA, Moradi, Y, Morze, J, Mousavi, SM, Mpundu-Kaambwa, C, Muriithi, MK, Muthupandian, S, Nagarajan, AJ, Naimzada, MD, Nangia, V, Naqvi, AA, Narayana, AI, Nascimento, BR, Naveed, M, Nayak, BP, Nazari, J, Ndejjo, R, Negoi, I, Kandel, SN, Trang, HN, Nonvignon, J, Noubiap, JJ, Nwatah, VE, Oancea, B, Ojelabi, FAO, Olagunju, AT, Olakunde, BO, Olgiati, S, Olusanya, JO, Onwujekwe, OE, Otoiu, A, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Padubidri, JR, Palladino, R, Panda-Jonas, S, Park, E-C, Kan, FP, Pawar, S, Toroudi, HP, Pereira, DM, Perianayagam, A, Pesudovs, K, Piccinelli, C, Postma, MJ, Prada, SI, Rabiee, M, Rabiee, N, Rahim, F, Rahimi-Movaghar, V, Rahman, MHU, Rahman, M, Rahmani, AM, Ram, U, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rathi, P, Rawaf, DL, Rawaf, S, Rawal, L, Rawassizadeh, R, Reiner, RC, Renzaho, AMN, Reshmi, B, Riaz, MA, Ripon, RK, Saad, AM, Sahraian, MA, Sahu, M, Salama, JS, Salehi, S, Samy, AM, Sanabria, J, Sanmarchi, F, Santos, JV, Santric-Milicevic, MM, Sathian, B, Savic, M, Saxena, D, Sayyah, M, Schwendicke, F, Senthilkumaran, S, Sepanlou, SG, Seylani, A, Shahabi, S, Shaikh, MA, Sheikh, A, Shetty, A, Shetty, PH, Shibuya, K, Shrime, MG, Shuja, KH, Singh, JA, Skryabin, VY, Skryabina, AA, Soltani, S, Soofi, M, Spurlock, EE, Stefan, SC, Szerencses, V, Szocska, M, Tabares-Seisdedos, R, Taddele, BW, Tefera, YG, Thavamani, A, Tobe-Gai, R, Topor-Madry, R, Tovani-Palone, MR, Bach, XT, Car, LT, Ullah, A, Ullah, S, Umar, N, Undurraga, EA, Valdez, PR, Vasankari, TJ, Villafane, JH, Violante, FS, Vlassov, V, Bay, V, Vollmer, S, Theo, V, Giang, TV, Linh, GV, Wamai, RG, Werdecker, A, Woldekidan, MA, Wubishet, BL, Xu, G, Yaya, S, Yazdi-Feyzabadi, V, Yigit, V, Yip, P, Yirdaw, BW, Yonemoto, N, Younis, MZ, Yu, C, Yunusa, I, Moghadam, TZ, Zandian, H, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Ziapour, A, Zuniga, YMH, Hay, SI, Murray, CJL, and Dieleman, JL
Abstract: BACKGROUND: The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. METHODS: We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. FINDINGS: In 2019, health spending globally reached $8·8 trillion (95% uncertainty interval [UI] 8·7-8·8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this t
Published: 2021

12. Global and regional burden of cancer in 2016 arising from occupational exposure to selected carcinogens: a systematic analysis for the Global Burden of Disease Study 2016

Author: Driscoll, T, Rushton, L, Steenland, K, Hutchings, S, Straif, K, Abate, D, Abdel-Rahman, O, Acharya, D, Afarideh, M, Alahdab, F, Al-Aly, Z, Anjomshoa, M, Aremu, O, Artaman, A, Ataro, Z, Quintanilla, BPA, Badawi, A, Behzadifar, M, Beuran, M, Bhattacharyya, K, Bijani, A, Bjorge, T, Butt, ZA, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Cerin, E, Chaturvedi, P, Chimed-Ochir, O, Crider, R, Crowe, CS, Dandona, L, Dandona, R, Dang, AK, Daryani, A, Desalegn, BB, Dharmaratne, SD, Djalalinia, S, Effiong, A, El-Khatib, Z, Esteghamati, A, Fareed, M, Fernandes, E, Filip, I, Fischer, F, Fukumoto, T, Gallus, S, Gebremichael, TG, Gezae, KE, Grada, A, Guimaraes, ALS, Gupta, R, Hafezi-Nejad, N, Haj-Mirzaian, A, Hamadeh, RR, Hamidi, S, Hassankhani, H, Hay, SI, Hegazy, MI, Henok, A, Hoang, CL, Hole, MK, Hosgood, HD, Hosseini, M, Hostiuc, M, Hostiuc, S, Irvani, SSN, Islam, SMS, Jakovljevic, M, Jha, RP, Jurisson, M, Kahsay, A, Karim, N, Kasaeian, A, Kassa, ZY, Khader, YS, Khafaie, MA, Khan, EA, Khosravi, MH, Khubchandani, J, Kiadaliri, AA, Kim, YJ, Kogevinas, M, Koh, D, Kosen, S, Koyanagi, A, Kumar, GA, Lad, DP, Lal, DK, Lami, FH, Latifi, A, Leigh, J, Linn, S, Majdan, M, Malekzadeh, R, Malta, DC, Mansournia, MA, Massenburg, BB, Melese, A, Melku, M, Memish, ZA, Mendoza, W, Mengistu, G, Meretoja, TJ, Mestrovic, T, Miazgowski, B, Miazgowski, T, Mirrakhimov, EM, Moazen, B, Mohammed, S, Mohebi, F, Mokdad, AH, Moodley, Y, Moosazadeh, M, Moradi, G, Morawska, L, Morrison, SD, Mousavi, SM, Mustafa, G, Negoi, I, Negoi, RI, Nguyen, CT, Nguyen, TH, Ningrum, DNA, Nixon, MR, Ofori-Asenso, R, Ogbo, FA, Olagunju, AT, Olusanya, BO, Ortega-Altamirano, DDV, Mahesh, PA, Park, E-K, Pereira, DM, Prakash, S, Qorbani, M, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahimi-Movaghar, V, Rajati, F, Reiner, RC, Renzaho, AMN, Rezaei, S, Roever, L, Saadat, M, Saddik, B, Safari, S, Safiri, S, Sahebkar, A, Sahraian, MA, Salimzadeh, H, Samy, AM, Sanabria, J, Sarmiento-Suarez, R, Sathian, B, Schwebel, DC, Sepanlou, SG, Serdar, B, Shaikh, MA, Sharma, R, She, J, Shigematsu, M, Shirkoohi, R, Si, S, Sinha, DN, Soofi, M, Stanaway, JD, Stokes, MA, Tabares-Seisdedos, R, Tabuchi, T, Takahashi, K, Tefera, YM, Temsah, M-H, Tovani-Palone, MR, Tran, BX, Tran, KB, Ullah, I, Valdez, PR, Vasankari, TJ, Violante, FS, Vlassov, V, Vu, GT, Waheed, Y, Wang, Y-P, Yeshaneh, A, Yirsaw, BD, Yisma, E, Yonemoto, N, Yousefifard, M, Yu, C, Zadnik, V, Zamani, M, Zandian, H, Zodpey, S, Lim, SS, Driscoll, Tim, Rushton, Lesley, Steenland, Kyle, Hutchings, Sally, Yisma, Engida, Lim, Stephen S, GBD 2016 Occupational Carcinogens Collaborators, GBD 2016 Occupational Carcinogens Collaborator, and Violante FS
Subjects: AUSTRALIA, medicine.disease_cause, asbesto, mesothelioma incidence, 0302 clinical medicine, 1599 Other Commerce, Management, Tourism and Services, Sílice, 030212 general & internal medicine, clusters, Asbestos-related diseases, asbestos, diesel engine exhaust, epidemiology, occupational exposure, silica, Public, Environmental & Occupational Health, education.field_of_study, Mortality rate, metabolic risks, 030210 environmental & occupational health, 3. Good health, COMPARATIVE RISK-ASSESSMENT, comparative risk-assessment, Exposición Profesional, Life Sciences & Biomedicine, epidemiology occupational exposure, trends, Population, MESOTHELIOMA INCIDENCE, GBD 2016 Occupational Carcinogens Collaborators, Asbestos, Environmental & Occupational Health, 1117 Public Health and Health Services, 03 medical and health sciences, Environmental health, medicine, Epidemiología, education, Disease burden, Motores diesel, Science & Technology, business.industry, Public Health, Environmental and Occupational Health, Cancer, 1103 Clinical Sciences, medicine.disease, TRENDS, ASBESTOS-RELATED DISEASES, asbestos-related diseases, 13. Climate action, Relative risk, Attributable risk, business, CLUSTERS
Abstract: ObjectivesThis study provides a detailed analysis of the global and regional burden of cancer due to occupational carcinogens from the Global Burden of Disease 2016 study.MethodsThe burden of cancer due to 14 International Agency for Research on Cancer Group 1 occupational carcinogens was estimated using the population attributable fraction, based on past population exposure prevalence and relative risks from the literature. The results were used to calculate attributable deaths and disability-adjusted life years (DALYs).ResultsThere were an estimated 349 000 (95% Uncertainty Interval 269 000 to 427 000) deaths and 7.2 (5.8 to 8.6) million DALYs in 2016 due to exposure to the included occupational carcinogens—3.9% (3.2% to 4.6%) of all cancer deaths and 3.4% (2.7% to 4.0%) of all cancer DALYs; 79% of deaths were of males and 88% were of people aged 55 –79 years. Lung cancer accounted for 86% of the deaths, mesothelioma for 7.9% and laryngeal cancer for 2.1%. Asbestos was responsible for the largest number of deaths due to occupational carcinogens (63%); other important risk factors were secondhand smoke (14%), silica (14%) and diesel engine exhaust (5%). The highest mortality rates were in high-income regions, largely due to asbestos-related cancers, whereas in other regions cancer deaths from secondhand smoke, silica and diesel engine exhaust were more prominent. From 1990 to 2016, there was a decrease in the rate for deaths (−10%) and DALYs (−15%) due to exposure to occupational carcinogens.ConclusionsWork-related carcinogens are responsible for considerable disease burden worldwide. The results provide guidance for prevention and control initiatives.
Published: 2020

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

Author: Johnson, CO, Nguyen, M, Roth, GA, Nichols, E, Alam, T, Abate, D, Abd-Allah, F, Abdelalim, A, Abraha, HN, Abu-Rmeileh, NM, Adebayo, OM, Adeoye, AM, Agarwal, G, Agrawal, S, Aichour, AN, Aichour, I, Aichour, MTE, Alahdab, F, Ali, R, Alvis-Guzman, N, Anber, NH, Anjomshoa, M, Arabloo, J, Arauz, A, Ärnlöv, J, Arora, A, Awasthi, A, Banach, M, Barboza, MA, Barker-Collo, SL, Bärnighausen, TW, Basu, S, Belachew, AB, Belayneh, YM, Bennett, DA, Bensenor, IM, Bhattacharyya, K, Biadgo, B, Bijani, A, Bikbov, B, Bin Sayeed, MS, Butt, ZA, Cahuana-Hurtado, L, Carrero, JJ, Carvalho, F, Castañeda-Orjuela, CA, Castro, F, Catalá-López, F, Chaiah, Y, Chiang, PPC, Choi, JYJ, Christensen, H, Chu, DT, Cortinovis, M, Damasceno, AAM, Dandona, L, Dandona, R, Daryani, A, Davletov, K, De Courten, B, De la Cruz-Góngora, V, Degefa, MG, Dharmaratne, SD, Diaz, D, Dubey, M, Duken, EE, Edessa, D, Endres, M, Faraon, EJA, Farzadfar, F, Fernandes, E, Fischer, F, Flor, LS, Ganji, M, Gebre, AK, Gebremichael, TG, Geta, B, Gezae, KE, Gill, PS, Gnedovskaya, EV, Gómez-Dantés, H, Goulart, AC, Grosso, G, Guo, Y, Gupta, R, Haj-Mirzaian, A, Hamidi, S, Hankey, GJ, Hassen, HY, Hay, SI, Hegazy, MI, Heidari, B, Herial, NA, Hosseini, MA, Hostiuc, S, Irvani, SSN, Islam, SMS, Jahanmehr, N, and Javanbakht, M
Subjects: Neurology & Neurosurgery
Abstract: © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Stroke is a leading cause of mortality and disability worldwide and the economic costs of treatment and post-stroke care are substantial. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic, comparable method of quantifying health loss by disease, age, sex, year, and location to provide information to health systems and policy makers on more than 300 causes of disease and injury, including stroke. The results presented here are the estimates of burden due to overall stroke and ischaemic and haemorrhagic stroke from GBD 2016. Methods: We report estimates and corresponding uncertainty intervals (UIs), from 1990 to 2016, for incidence, prevalence, deaths, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs). DALYs were generated by summing YLLs and YLDs. Cause-specific mortality was estimated using an ensemble modelling process with vital registration and verbal autopsy data as inputs. Non-fatal estimates were generated using Bayesian meta-regression incorporating data from registries, scientific literature, administrative records, and surveys. The Socio-demographic Index (SDI), a summary indicator generated using educational attainment, lagged distributed income, and total fertility rate, was used to group countries into quintiles. Findings: In 2016, there were 5·5 million (95% UI 5·3 to 5·7) deaths and 116·4 million (111·4 to 121·4) DALYs due to stroke. The global age-standardised mortality rate decreased by 36·2% (−39·3 to −33·6) from 1990 to 2016, with decreases in all SDI quintiles. Over the same period, the global age-standardised DALY rate declined by 34·2% (−37·2 to −31·5), also with decreases in all SDI quintiles. There were 13·7 million (12·7 to 14·7) new stroke cases in 2016. Global age-standardised incidence declined by 8·1% (−10·7 to −5·5) from 1990 to 2016 and decreased in all SDI quintiles except the middle SDI group. There were 80·1 million (74·1 to 86·3) prevalent cases of stroke globally in 2016; 41·1 million (38·0 to 44·3) in women and 39·0 million (36·1 to 42·1) in men. Interpretation: Although age-standardised mortality rates have decreased sharply from 1990 to 2016, the decrease in age-standardised incidence has been less steep, indicating that the burden of stroke is likely to remain high. Planned updates to future GBD iterations include generating separate estimates for subarachnoid haemorrhage and intracerebral haemorrhage, generating estimates of transient ischaemic attack, and including atrial fibrillation as a risk factor. Funding: Bill & Melinda Gates Foundation
Published: 2019

14. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: James, SL, Theadom, A, Ellenbogen, RG, Bannick, MS, Mountjoy-Venning, WC, Lucchesi, LR, Abbasi, N, Abdulkader, R, Abraha, HN, Adsuar, JC, Afarideh, M, Agrawal, S, Ahmadi, A, Ahmed, MB, Aichour, AN, Aichour, I, Aichour, MTE, Akinyemi, RO, Akseer, N, Alahdab, F, Alebel, A, Alghnam, SA, Ali, BA, Alsharif, U, Altirkawi, K, Andrei, CL, Anjomshoa, M, Ansari, H, Ansha, MG, Antonio, CAT, Appiah, SCY, Ariani, F, Asefa, NG, Asgedom, SW, Atique, S, Awasthi, A, Quintanilla, BPA, Ayuk, TB, Azzopardi, PS, Badali, H, Badawi, A, Balalla, S, Banstola, A, Barker-Collo, SL, Barnighausen, TW, Bedi, N, Behzadifar, M, Bekele, BB, Belachew, AB, Belay, YA, Bennett, DA, Bensenor, IM, Berhane, A, Beuran, M, Bhalla, A, Bhaumik, S, Bhutta, ZA, Biadgo, B, Biffino, M, Bijani, A, Bililign, N, Birungi, C, Boufous, S, Brazinova, A, Brown, AW, Car, M, Cardenas, R, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Catala-Lopez, F, Chaiah, Y, Champs, AP, Chang, J-C, Choi, J-YJ, Christopher, DJ, Cooper, C, Crowe, CS, Dandona, L, Dandona, R, Daryani, A, Davitoiu, DV, Degefa, MG, Demoz, GT, Deribe, K, Djalalinia, S, Huyen, PD, Doku, DT, Drake, TM, Dubey, M, Dubljanin, E, El-Khatib, Z, Eskandarieh, S, Esteghamati, A, Esteghamati, S, Faro, A, Farzadfar, F, Farzaei, MH, Fereshtehnejad, S-M, Fernandes, E, Feyissa, GT, Filip, I, Fischer, F, Fukumoto, T, Ganji, M, Gankpe, FG, Gebre, AK, Gebrehiwot, TT, Gezae, KE, Gopalkrishna, G, Goulart, AC, Haagsma, JA, Haj-Mirzaian, A, Hamadeh, RR, Hamidi, S, Haro, JM, Hassankhani, H, Hassen, HY, Havmoeller, R, Hawley, C, Hay, SI, Hegazy, MI, Hendrie, D, Henok, A, Hibstu, DT, Hoffman, HJ, Hole, MK, Rad, EH, Hosseini, SM, Hostiuc, S, Hu, G, Hussen, MA, Ilesanmi, OS, Irvani, SN, Jakovljevic, M, Jayaraman, S, Jha, RP, Jonas, JB, Jones, KM, Shushtari, ZJ, Jozwiak, JJ, Jurisson, M, Kabir, A, Kahsay, A, Kahssay, M, Kalani, R, Karch, A, Kasaeian, A, Kassa, GM, Kassa, TD, Kassa, ZY, Kengne, AP, Khader, YS, Khafaie, MA, Khalid, N, Khalil, I, Khan, EA, Khan, MS, Khang, Y-H, Khazaie, H, Khoja, AT, Khubchandani, J, Kiadaliri, AA, Kim, D, Kim, Y-E, Kisa, A, Koyanagi, A, Krohn, KJ, Defo, BK, Bicer, BK, Kumar, GA, Kumar, M, Lalloo, R, Lami, FH, Lansingh, VC, Laryea, DO, Latifi, A, Leshargie, CT, Levi, M, Li, S, Liben, ML, Lotufo, PA, Lunevicius, R, Mahotra, NB, Majdan, M, Majeed, A, Malekzadeh, R, Manda, A-L, Mansournia, MA, Massenburg, BB, Mate, KKV, Mehndiratta, MM, Mehta, V, Meles, H, Melese, A, Memiah, PTN, Mendoza, W, Mengistu, G, Meretoja, A, Meretoja, TJ, Mestrovic, T, Miazgowski, T, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Moazen, B, Mohammadi, M, Mokdad, AH, Molokhia, M, Monasta, L, Mondello, S, Moosazadeh, M, Moradi, G, Moradi, M, Moradi-Lakeh, M, Moradinazar, M, Morrison, SD, Moschos, MM, Mousavi, SM, Murthy, S, Musa, KI, Mustafa, G, Naghavi, M, Naik, G, Najafi, F, Nangia, V, Nascimento, BR, Negoi, I, Trang, HN, Nichols, E, Ningrum, DNA, Nirayo, YL, Nyasulu, PS, Ofori-Asenso, R, Ogbo, FA, Oh, I-H, Okoro, A, Olagunju, AT, Olagunju, TO, Olivares, PR, Otstavnov, SS, Owolabi, MO, Mahesh, PA, Pakhale, S, Pandey, AR, Pesudovs, K, Pinilla-Monsalve, GD, Polinder, S, Poustchi, H, Prakash, S, Qorbani, M, Radfar, A, Rafay, A, Rafiei, A, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rahman, M, Rahman, MA, Rai, RK, Rajati, F, Ram, U, Rawaf, DL, Rawaf, S, Reiner, RC, Reis, C, Renzaho, AMN, Resnikoff, S, Rezaei, S, Rezaeian, S, Roever, L, Ronfani, L, Roshandel, G, Roy, N, Ruhago, GM, Saddik, B, Safari, H, Safiri, S, Sahraian, MA, Salamati, P, Saldanha, RDF, Samy, AM, Sanabria, J, Santos, JV, Milicevic, MMMS, Sartorius, B, Satpathy, M, Schneider, IJC, Schwebel, DC, Sepanlou, SG, Shabaninejad, H, Shaikh, MAA, Shams-Beyranvand, M, Sharif, M, Sharif-Alhoseini, M, Islam, SMS, She, J, Sheikh, A, Shen, J, Sheth, KN, Shibuya, K, Shiferaw, MS, Shigematsu, M, Shiri, R, Shiue, I, Shoman, H, Siabani, S, Siddiqi, TJ, Silva, JP, Silveira, DGA, Sinha, DN, Smith, M, Soares Filho, AM, Sobhani, S, Soofi, M, Soriano, JB, Soyiri, IN, Stein, DJ, Stokes, MA, Sufiyan, MB, Sunguya, BF, Sunshine, JE, Sykes, BL, Szoeke, CEI, Tabares-Seisdedos, R, Ao, BJT, Tehrani-Banihashemi, A, Tekle, MG, Temsah, M-H, Temsah, O, Topor-Madry, R, Tortajada-Girbes, M, Bach, XT, Khanh, BT, Car, LT, Ukwaja, KN, Ullah, I, Usman, MS, Uthman, OA, Valdez, PR, Vasankari, TJ, Venketasubramanian, N, Violante, FS, Wagnew, FS, Waheed, Y, Wang, Y-P, Weldegwergs, KG, Werdecker, A, Wijeratne, T, Winkler, AS, Wyper, GMA, Yano, Y, Yaseri, M, Yasin, YJ, Ye, P, Yimer, EM, Yip, P, Yisma, E, Yonemoto, N, Yoon, S-J, Yost, MG, Younis, MZ, Yousefifard, M, Yu, C, Zaidi, Z, Bin Zaman, S, Zamani, M, Zenebe, ZM, Zodpey, S, Feigin, VL, Vos, T, Murray, CJL, James, SL, Theadom, A, Ellenbogen, RG, Bannick, MS, Mountjoy-Venning, WC, Lucchesi, LR, Abbasi, N, Abdulkader, R, Abraha, HN, Adsuar, JC, Afarideh, M, Agrawal, S, Ahmadi, A, Ahmed, MB, Aichour, AN, Aichour, I, Aichour, MTE, Akinyemi, RO, Akseer, N, Alahdab, F, Alebel, A, Alghnam, SA, Ali, BA, Alsharif, U, Altirkawi, K, Andrei, CL, Anjomshoa, M, Ansari, H, Ansha, MG, Antonio, CAT, Appiah, SCY, Ariani, F, Asefa, NG, Asgedom, SW, Atique, S, Awasthi, A, Quintanilla, BPA, Ayuk, TB, Azzopardi, PS, Badali, H, Badawi, A, Balalla, S, Banstola, A, Barker-Collo, SL, Barnighausen, TW, Bedi, N, Behzadifar, M, Bekele, BB, Belachew, AB, Belay, YA, Bennett, DA, Bensenor, IM, Berhane, A, Beuran, M, Bhalla, A, Bhaumik, S, Bhutta, ZA, Biadgo, B, Biffino, M, Bijani, A, Bililign, N, Birungi, C, Boufous, S, Brazinova, A, Brown, AW, Car, M, Cardenas, R, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Catala-Lopez, F, Chaiah, Y, Champs, AP, Chang, J-C, Choi, J-YJ, Christopher, DJ, Cooper, C, Crowe, CS, Dandona, L, Dandona, R, Daryani, A, Davitoiu, DV, Degefa, MG, Demoz, GT, Deribe, K, Djalalinia, S, Huyen, PD, Doku, DT, Drake, TM, Dubey, M, Dubljanin, E, El-Khatib, Z, Eskandarieh, S, Esteghamati, A, Esteghamati, S, Faro, A, Farzadfar, F, Farzaei, MH, Fereshtehnejad, S-M, Fernandes, E, Feyissa, GT, Filip, I, Fischer, F, Fukumoto, T, Ganji, M, Gankpe, FG, Gebre, AK, Gebrehiwot, TT, Gezae, KE, Gopalkrishna, G, Goulart, AC, Haagsma, JA, Haj-Mirzaian, A, Hamadeh, RR, Hamidi, S, Haro, JM, Hassankhani, H, Hassen, HY, Havmoeller, R, Hawley, C, Hay, SI, Hegazy, MI, Hendrie, D, Henok, A, Hibstu, DT, Hoffman, HJ, Hole, MK, Rad, EH, Hosseini, SM, Hostiuc, S, Hu, G, Hussen, MA, Ilesanmi, OS, Irvani, SN, Jakovljevic, M, Jayaraman, S, Jha, RP, Jonas, JB, Jones, KM, Shushtari, ZJ, Jozwiak, JJ, Jurisson, M, Kabir, A, Kahsay, A, Kahssay, M, Kalani, R, Karch, A, Kasaeian, A, Kassa, GM, Kassa, TD, Kassa, ZY, Kengne, AP, Khader, YS, Khafaie, MA, Khalid, N, Khalil, I, Khan, EA, Khan, MS, Khang, Y-H, Khazaie, H, Khoja, AT, Khubchandani, J, Kiadaliri, AA, Kim, D, Kim, Y-E, Kisa, A, Koyanagi, A, Krohn, KJ, Defo, BK, Bicer, BK, Kumar, GA, Kumar, M, Lalloo, R, Lami, FH, Lansingh, VC, Laryea, DO, Latifi, A, Leshargie, CT, Levi, M, Li, S, Liben, ML, Lotufo, PA, Lunevicius, R, Mahotra, NB, Majdan, M, Majeed, A, Malekzadeh, R, Manda, A-L, Mansournia, MA, Massenburg, BB, Mate, KKV, Mehndiratta, MM, Mehta, V, Meles, H, Melese, A, Memiah, PTN, Mendoza, W, Mengistu, G, Meretoja, A, Meretoja, TJ, Mestrovic, T, Miazgowski, T, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Moazen, B, Mohammadi, M, Mokdad, AH, Molokhia, M, Monasta, L, Mondello, S, Moosazadeh, M, Moradi, G, Moradi, M, Moradi-Lakeh, M, Moradinazar, M, Morrison, SD, Moschos, MM, Mousavi, SM, Murthy, S, Musa, KI, Mustafa, G, Naghavi, M, Naik, G, Najafi, F, Nangia, V, Nascimento, BR, Negoi, I, Trang, HN, Nichols, E, Ningrum, DNA, Nirayo, YL, Nyasulu, PS, Ofori-Asenso, R, Ogbo, FA, Oh, I-H, Okoro, A, Olagunju, AT, Olagunju, TO, Olivares, PR, Otstavnov, SS, Owolabi, MO, Mahesh, PA, Pakhale, S, Pandey, AR, Pesudovs, K, Pinilla-Monsalve, GD, Polinder, S, Poustchi, H, Prakash, S, Qorbani, M, Radfar, A, Rafay, A, Rafiei, A, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rahman, M, Rahman, MA, Rai, RK, Rajati, F, Ram, U, Rawaf, DL, Rawaf, S, Reiner, RC, Reis, C, Renzaho, AMN, Resnikoff, S, Rezaei, S, Rezaeian, S, Roever, L, Ronfani, L, Roshandel, G, Roy, N, Ruhago, GM, Saddik, B, Safari, H, Safiri, S, Sahraian, MA, Salamati, P, Saldanha, RDF, Samy, AM, Sanabria, J, Santos, JV, Milicevic, MMMS, Sartorius, B, Satpathy, M, Schneider, IJC, Schwebel, DC, Sepanlou, SG, Shabaninejad, H, Shaikh, MAA, Shams-Beyranvand, M, Sharif, M, Sharif-Alhoseini, M, Islam, SMS, She, J, Sheikh, A, Shen, J, Sheth, KN, Shibuya, K, Shiferaw, MS, Shigematsu, M, Shiri, R, Shiue, I, Shoman, H, Siabani, S, Siddiqi, TJ, Silva, JP, Silveira, DGA, Sinha, DN, Smith, M, Soares Filho, AM, Sobhani, S, Soofi, M, Soriano, JB, Soyiri, IN, Stein, DJ, Stokes, MA, Sufiyan, MB, Sunguya, BF, Sunshine, JE, Sykes, BL, Szoeke, CEI, Tabares-Seisdedos, R, Ao, BJT, Tehrani-Banihashemi, A, Tekle, MG, Temsah, M-H, Temsah, O, Topor-Madry, R, Tortajada-Girbes, M, Bach, XT, Khanh, BT, Car, LT, Ukwaja, KN, Ullah, I, Usman, MS, Uthman, OA, Valdez, PR, Vasankari, TJ, Venketasubramanian, N, Violante, FS, Wagnew, FS, Waheed, Y, Wang, Y-P, Weldegwergs, KG, Werdecker, A, Wijeratne, T, Winkler, AS, Wyper, GMA, Yano, Y, Yaseri, M, Yasin, YJ, Ye, P, Yimer, EM, Yip, P, Yisma, E, Yonemoto, N, Yoon, S-J, Yost, MG, Younis, MZ, Yousefifard, M, Yu, C, Zaidi, Z, Bin Zaman, S, Zamani, M, Zenebe, ZM, Zodpey, S, Feigin, VL, Vos, T, and Murray, CJL
Abstract: BACKGROUND: Traumatic brain injury (TBI) and spinal cord injury (SCI) are increasingly recognised as global health priorities in view of the preventability of most injuries and the complex and expensive medical care they necessitate. We aimed to measure the incidence, prevalence, and years of life lived with disability (YLDs) for TBI and SCI from all causes of injury in every country, to describe how these measures have changed between 1990 and 2016, and to estimate the proportion of TBI and SCI cases caused by different types of injury. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 to measure the global, regional, and national burden of TBI and SCI by age and sex. We measured the incidence and prevalence of all causes of injury requiring medical care in inpatient and outpatient records, literature studies, and survey data. By use of clinical record data, we estimated the proportion of each cause of injury that required medical care that would result in TBI or SCI being considered as the nature of injury. We used literature studies to establish standardised mortality ratios and applied differential equations to convert incidence to prevalence of long-term disability. Finally, we applied GBD disability weights to calculate YLDs. We used a Bayesian meta-regression tool for epidemiological modelling, used cause-specific mortality rates for non-fatal estimation, and adjusted our results for disability experienced with comorbid conditions. We also analysed results on the basis of the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, there were 27·08 million (95% uncertainty interval [UI] 24·30-30·30 million) new cases of TBI and 0·93 million (0·78-1·16 million) new cases of SCI, with age-standardised incidence rates of 369 (331-412) per 100 000 population for TBI and 13 (11-16) per 100 000 for SCI. In 2016, the number of prevalent cases of TBI was 55·50
Published: 2019

15. Global, regional, and national burden of Parkinson's disease, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Dorsey, ER, Elbaz, Alexis, Nichols, E, Abd-Allah, F, Abdelalim, A, Adsuar, JC, Ansha, MG, Brayne, C, Choi, JJ, Collado-Mateo, D, Dahodwala, N, Do, HP, Edessa, D, Endres, M, Fereshtehnejad, SM, Foreman, KJ, Gankpe, FG, Gupta, R, Hankey, GJ, Hay, SI, Hegazy, MI, Hibstu, DT, Kasaeian, A, Khader, Y, Khalil, I, Khang, YH, Kim, YJ, Kokubo, Y, Logroscino, G, Massano, J, Mohamed Ibrahim, N, Mohammed, MA, Mohammadi, A, Moradi-Lakeh, M, Naghavi, M, Nguyen, BT, Nirayo, YL, Ogbo, FA, Owolabi, MO, and Pereira, DM
Subjects: Mortalitat, Malalties mentals
Abstract: BACKGROUND: Neurological disorders are now the leading source of disability globally, and ageing is increasing the burden of neurodegenerative disorders, including Parkinson's disease. We aimed to determine the global burden of Parkinson's disease between 1990 and 2016 to identify trends and to enable appropriate public health, medical, and scientific responses. METHODS: Through a systematic analysis of epidemiological studies, we estimated global, regional, and country-specific prevalence and years of life lived with disability for Parkinson's disease from 1990 to 2016. We estimated the proportion of mild, moderate, and severe Parkinson's disease on the basis of studies that used the Hoehn and Yahr scale and assigned disability weights to each level. We jointly modelled prevalence and excess mortality risk in a natural history model to derive estimates of deaths due to Parkinson's disease. Death counts were multiplied by values from the Global Burden of Disease study's standard life expectancy to compute years of life lost. Disability-adjusted life-years (DALYs) were computed as the sum of years lived with disability and years of life lost. We also analysed results based on the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, 6·1 million (95% uncertainty interval [UI] 5·0-7·3) individuals had Parkinson's disease globally, compared with 2·5 million (2·0-3·0) in 1990. This increase was not solely due to increasing numbers of older people, because age-standardised prevalence rates increased by 21·7% (95% UI 18·1-25·3) over the same period (compared with an increase of 74·3%, 95% UI 69·2-79·6, for crude prevalence rates). Parkinson's disease caused 3·2 million (95% UI 2·6-4·0) DALYs and 211 296 deaths (95% UI 167 771-265 160) in 2016. The male-to-female ratios of age-standardised prevalence rates were similar in 2016 (1·40, 95% UI 1·36-1·43) and 1990 (1·37, 1·34-1·40). From 1990 to 2016, age-standardised prevalence, DALY rates, and death rates increased for all global burden of disease regions except for southern Latin America, eastern Europe, and Oceania. In addition, age-standardised DALY rates generally increased across the Socio-demographic Index. INTERPRETATION: Over the past generation, the global burden of Parkinson's disease has more than doubled as a result of increasing numbers of older people, with potential contributions from longer disease duration and environmental factors. Demographic and potentially other factors are poised to increase the future burden of Parkinson's disease substantially.
Published: 2018

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

Author: 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 Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton SKH, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Josip, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carter, Austin, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Causey, Kate, Çavlin, Alanur, Cercy, Kelly M, Cerin, Ester, Chaiah, Yazan, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Claßen, Thomas Khaled Dwayne, Cohen, Aaron J, Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I, Daryani, Ahmad, Das, Siddharth K, Das Gupta, Rajat, das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, de Courten, Barbora, De Leo, Diego, De Neve, Jan-Walter, De Steur, Hans, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Douwes-Schultz, Dirk, Driscoll, Tim Robert, Duan, Leilei, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, Eldrenkamp, Erika, El-Khatib, Ziad, Elyazar, Iqbal RF, Enayati, Ahmadali, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhar, Mahdi, Fakhim, Hamed, Fanzo, Jessica, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Farid, Talha A, Farinha, Carla Sofia e Sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Farzam, Hossein, Fazaeli, Ali Akbar, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fekadu, Wubalem, Feldman, Rachel, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Finger, Jonas David, Fischer, Florian, Fitzmaurice, Christina, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fukutaki, Kai, Fuller, John E, Fürst, Thomas, Furtado, João M, Gakidou, Emmanuela, Gallus, Silvano, Gankpe, Fortune Gbetoho, Gansevoort, Ron T, Garcia, Ana Cristina, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gardner, William M, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M, Geramo, Yilma Chisha Dea, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goldberg, Ellen M, Goli, Srinivas, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gorman, Taren M, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Griswold, Max G, Grosso, Giuseppe, Gugnani, Harish Chander C, Guillemin, Francis, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Ha, Giang Hai, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Haghparast Bidgoli, Hassan, Hagos, Tekleberhan B, Haile, Michael Tamene, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Hankey, Graeme J, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Behzad, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T, Híjar, Martha, Hoek, Hans W, Hoffman, Daniel J, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Horita, Nobuyuki, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Huang, John J, Hughes, Caitlyn, Huynh, Chantal K, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ivers, Rebecca Q, Izadi, Neda, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, Jalu, Moti Tolera, Jamal, Amr A, James, Spencer L, Jassal, Simerjot K, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Johnson, Catherine O, Johnson, Sarah C, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, K, Madhanraj, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kahssay, Molla, Kalani, Rizwan, Kapil, Umesh, Karami, Manoochehr, Karami Matin, Behzad, Karanikolos, Marina, Karimi, Narges, Karimi, Seyed M, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, KC, Prakash, Kebede, Seifu, Keiyoro, Peter Njenga, Kemmer, Laura, 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, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, Khatony, Alireza, Khazaeipour, Zahra, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A, Kiarie, Helen W, Kibret, Getiye D, Kiirithio, Daniel N, Kim, Daniel, Kim, Jun Y, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W, Kinfu, Yohannes, Kinra, Sanjay, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kissoon, Niranjan, Kivimäki, Mika, Kocarnik, Jonathan M, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A, Kosek, Margaret N, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kristopher J, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kudom, Andreas A, Kulikoff, Xie Rachel, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lagat, Abraham K, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lami, Faris Hasan, Lamichhane, Prabhat, Lan, Qing, Lang, Justin J, Lansingh, Van C, Lansky, Sonia, Larson, Heidi J, Larsson, Anders O, Laryea, Dennis Odai, Lassi, Zohra S, Latifi, Arman, Lau, Kathryn Mei-Ming, Laxmaiah, Avula, Lazarus, Jeffrey V, Leasher, Janet L, Lebedev, Georgy, Ledesma, Jorge R, Lee, James B, Lee, Paul H, Leever, Andrew T, Leigh, James, Leinsalu, Mall, Leshargie, Cheru Tesema, Leung, Janni, Lewycka, Sonia, Li, Shanshan, Li, Xiaohong, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Lee-Ling, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lucchesi, Lydia R, Lyons, Ronan A, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Madotto, Fabiana, Maghavani, Dhaval P, Magis-Rodriguez, Carlos, Mahotra, Narayan Bahadur, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Mangalam, Srikanth, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, Martin, Randall V, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, Mashamba-Thompson, Tivani Phosa, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K, Mazidi, Mohsen, McAlinden, Colm, McGrath, John J, McKee, Martin, McMahon, Brian J, Mehata, Suresh, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Mejia-Rodriguez, Fabiola, Mekonen, Tesfa, Mekonnen, Tefera C Chane, Meles, Hagazi Gebre, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, 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, Milne, George J, Mini, G K, Minnig, Shawn P, Mirabi, Parvaneh, Mirarefin, Mojde, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Mitchell, Philip B, Moazen, Babak, Moghadamnia, Ali Akbar, Mohajer, Bahram, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadnia-Afrouzi, Mousa, Mohammed, Mohammed A, Mohammed, Shafiu, Mohan, Murali B V, Mohan, Viswanathan, Mohebi, Farnam, Moitra, Modhurima, Mokdad, Ali H, Molokhia, Mariam, Monasta, Lorenzo, Montañez, Julio Cesar, Moosazadeh, Mahmood, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Morgado-da-Costa, Joana, Morisaki, Naho, Morrison, Shane Douglas, Mosapour, Abbas, Moschos, Marilita M, Mountjoy-Venning, W Cliff, Mouodi, Simin, Mousavi, Seyyed Meysam, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada S, Mukhopadhyay, Satinath, Mullany, Erin C, Muller, Kate, Mumford, John Everett, Murhekar, Manoj, Murthy, G V S, Murthy, Srinivas, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nabhan, Ashraf F, Nachega, Jean B, Nagarajan, Ahamarshan Jayaraman, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naidoo, Kovin, Naik, Gurudatta, Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nam, Hae Sung, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramos, Nawaz, Haseeb, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Subas, Newton, Charles Richard James, Ngalesoni, Frida N, Ngunjiri, Josephine W, Nguyen, Anh, Nguyen, Grant, Nguyen, Ha, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Minh, Nichols, Emma, Nigatu, Solomon Gedlu, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nisar, Muhammad Imran, Nixon, Molly R, Nolutshungu, Nomonde, Nomura, Marika, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nyasulu, Peter S, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogah, Okechukwu Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Kelechi E, 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, Oommen, Anu Mary, Opio, John Nelson, Oren, Eyal, Oros, Andrei, Ortega-Altamirano, Doris D V, Ortiz, Alberto, Ortiz, Justin R, Ortiz-Panozo, Eduardo, Ota, Erika, Otstavnov, Stanislav S, Owolabi, Mayowa Ojo, P A, Mahesh, Pakhale, Smita, Pakhare, Abhijit P, Pan, Wen-Harn, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandian, Jeyaraj Durai, Papantoniou, Nikolaos, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patle, Ajay, Patton, George C, Paturi, Vishnupriya Rao, Paudel, Deepak, Paulson, Katherine R, Pearce, Neil, Peprah, Emmanuel K, Pereira, David M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pletcher, Martin, Pond, Constance Dimity, Postma, Maarten J, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A, Pyakurel, Manita, Qorbani, Mostafa, Quansah, Reginald, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Md Shafiur, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Ram, Usha, Rana, Saleem M, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Razo-García, Christian, Reddy, K Srinath, Reiner, Robert C, Reis, Cesar, Reitsma, Marissa B, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Reynales-Shigematsu, Luz Myriam, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Ribeiro, Antonio Luiz P, Rios-Blancas, Maria Jesus, Roba, Kedir Teji, Roberts, Nicholas L S, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A, Roy, Ambuj, Rubagotti, Enrico, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S, Saddik, Basema, Sadeghi, Ehsan, Safari, 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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.
Subjects: 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.
Published: 2018

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

Author: Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A., Adebayo, Oladimeji, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. 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K., Brenner, Hermann, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Busse, Reinhard, Butt, Zahid A., Callender, Charlton S. K. H., Campos-Nonato, Ismael R., Rincon, Julio Cesar Canapuzano, Cano, Jorge, Car, Mate, Cardenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carter, Austin, Carvalho, Felix, Castaneda-Orjuela, Carlos A., Rivas, Jacqueline Castillo, Castle, Chris D., Castro, Clara, Castro, Franz, Catala-Lopez, Ferran, Cerin, Ester, Chaiah, Yazan, Chang, Jung -Chen, Chanson, Fiona J., Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheet, Abdulaal, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chiang, Sheng-Chia, Cicuttini, Flavia M., Ciobanu, Liliana G., Cirillo, Massimo, Cohen, Aaron J., Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Cowie, Benjamin C., Criqui, Michael H., Cromwell, Elizabeth A., Crowe, Christopher Stephen, Crump, John A., Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I., Daryani, Ahmad, Das, Siddharth K., Das Gupta, Rajat, Das Neves, Jose, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C., Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De La Hoz, Fernando Pio, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T., Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Baleen Betsu, Denova-Gutierrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Jarlais, Don C. 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Jc, Ferrari, Aj, Feyissa, Gt, Foigt, Na, Foreman, Kj, Frank, Td, Fuller, Je, Fürst, T, Furtado, Jm, Futran, Nd, Garcia-Basteiro, Al, Garcia-Gordillo, Ma, Gardner, Wm, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gebremichael, Tg, Gelano, Tf, Geleijnse, Jm, Geramo, Ycd, Gething, Pw, Gezae, Ke, Ghadami, Mr, Gibney, Kb, Gill, Tk, Gillum, Rf, Ginawi, Ia, Goldberg, Em, Gómez-Dantés, H, Gona, Pn, Gopalani, Sv, Gorman, Tm, Goulart, Ac, Gnedovskaya, Ev, Gugnani, Hc, Guimaraes, Al, Gupta, Pc, Gutiérrez, Ra, Haagsma, Ja, Hagos, Tb, Hailegiyorgis, Tt, Hailu, Gb, Hamadeh, Rr, Handal, Aj, Hankey, Gj, Harb, Hl, Haro, Jm, Hassen, Hy, Hay, Rj, Hay, Si, Hegazy, Mi, Henry, Nj, Hibstu, Dt, Hoek, Hw, Hole, Mk, Hosgood, Hd, Hosseini, Sm, Hotez, Pj, Hoy, Dg, Huang, Jj, Hussen, Mm, Irvani, Ssn, Irvine, Cm, Islam, Sm, Jacobsen, Kh, Jain, Sk, Jalu, Mt, James, Sl, Jayatilleke, Au, Jenkins, Kj, Jha, Rp, Johnson, Co, Johnson, Sc, Jonas, Jb, Jozwiak, Jj, Jungari, Sb, Jürisson, M, Kassa, Dh, Kassa, Gm, Kassa, Td, 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Miller, Tr, Miller-Petrie, Mk, Mini, Gk, Mirrakhimov, Em, Misganaw, At, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Moreno Velásquez, I, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Muchie, Kf, Mueller, Uo, Mumford, Je, Musa, Ki, Nachega, Jb, Nansseu, Jr, Nascimento, Br, Negoi, Ri, Newton, Crj, Ngalesoni, Fn, Ngunjiri, Jw, Nguyen, Aq, Nguyen, Ht, Nguyen, Lh, Nguyen, Th, Ningrum, Dna, Nirayo, Yl, Nixon, Mr, Norheim, Of, Noubiap, Jj, Nouri, Hr, Nourollahpour Shiadeh, M, Nowroozi, Mr, Odell, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Orpana, Hm, Ortiz, Jr, Øverland, S, Owolabi, Mo, Özdemir, R, P A, M, Pakhare, Ap, Pakpour, Ah, Pandian, Jd, Park, Ek, Parry, Cdh, Patton, Gc, Paturi, Vr, Paulson, Kr, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Postma, Mj, Purcell, Ca, Quistberg, Da, Rade, Kw, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahman, Mhu, Rahman, Ma, Rai, Rk, Ranabhat, Cl, Rao, Pc, Rawaf, Dl, Razo-García, C, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Robinson, Sr, Sahraian, Ma, Saldanha, Rf, Sambala, Ez, Samy, Am, Sanchez-Niño, Md, Santomauro, Df, Santos, Jv, Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sarmiento-Suárez, R, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serván-Mori, E, Shackelford, Ka, Shaheen, Aa, Shaikh, Ma, Shrime, Mg, Siddiqi, Tj, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Pk, Sinha, Dn, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Starodubov, Vi, Stein, Dj, Stewart, Lg, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sur, Pj, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekle, Mg, Temsah, Mh, Teshale, My, Tessema, Ga, Thankappan, Kr, Thrift, Ag, Thurston, Gd, To, Qg, Torre, Ae, Tortajada-Girbés, M, Tovani-Palone, Mr, Tran, Bx, Tran, Kb, Troeger, Ce, Truelsen, Tc, Truong, Nt, Tsadik, Ag, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Updike, Rl, Uthman, Oa, Uzun, Sb, Valdez, Pr, Vasankari, Tj, Vladimirov, Sk, Vollset, Se, Wagner, Gr, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weintraub, Rg, Weldegwergs, Kg, Werkneh, Aa, West, Te, Whiteford, Ha, Wilner, Lb, Wolfe, Cda, Wu, Yc, Wyper, Gma, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yentür, Gk, Yimer, Em, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaman, Sb, Zeleke, Aj, Zenebe, Zm, Zhang, Al, Zuhlke, Lj, and Murray, Cjl.
Subjects: Adult, Male, Adolescent, national age-sex-specific mortality, UNITED-STATES, Global Health, Socioeconomic Factor, Global Burden of Disease, GBD, causes of death, Young Adult, Age Distribution, Life Expectancy, General & Internal Medicine, Cause of Death, PUBLIC-HEALTH PROBLEM, mortality, 282 causes global burden of disease, Sex Distribution, Child, Aged, Aged, 80 and over, BARRIERS, DEMENTIA, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, TRENDS, PREVENTION, PREVALENCE, ALZHEIMERS-DISEASE, INDIVIDUALS, 3121 General medicine, internal medicine and other clinical medicine, Child, Preschool, REGISTRATION, Female, Human medicine, Human
Abstract: Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

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

Author: Murray, Christopher J L, Callender, Charlton S K H, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M E, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, Atique, Suleman, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Banach, Maciej, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gilles, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Biswas, Tuhin, Bizuneh, Hailemichael, Bleyer, Archie, Basara, Berrak Bora, Bosetti, Cristina, Boufous, Soufiane, Brady, Oliver J, Bragazzi, Nicola Luigi, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Brewer, Jerry D, Briant, Paul Svitil, Britton, Gabrielle, Burstein, Roy, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christopher, Devasahayam J, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, 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Subjects: Adult, Male, Population Density, GBD, population, fertility, Adolescent, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, Global Health, Global Burden of Disease, Young Adult, Child, Preschool, General & Internal Medicine, Female, Human medicine, Mortality, Child, Population Growth, Birth Rate, Aged, Human, Maternal Age
Abstract: Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-cotnponent method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49.4% (95% uncertainty interval [UI] 46.4-52.0). The TFR decreased from 4.7 livebirths (4.5-4.9) to 2.4 livebirths (2.2-2.5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83.8 million people per year since 1985. The global population increased by 197-2% (193.3-200.8) since 1950, from 2.6 billion (2.5-2.6) to 7.6 billion (7.4-7.9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2.0%; this rate then remained nearly constant until 1970 and then decreased to 1.1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2.5% in 1963 to O7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2.7%. The global average age increased from 26.6 years in 1950 to 32.1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59.9% to 65.3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1.0 livebirths (95% UI 0. 9-1.2) in Cyprus to a high of 7.1 livebirths (6.8-7.4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0.08 livebirths (0.07-0.09) in South Korea to 2.4 livebirths (2.2-2.6) in Niger, and the TFR over age 30 years (I F030; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0.3 livebirths (0.3-0-4) in Puerto Rico to a high of 3.1 livebirths (3.0-3.2) in Niger. TF030 was higher than TFU25 in 145 countries and territories in 2017.33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2.0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

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

Author: Nancy, Fullman, Jamal, Yearwood, Solomon, M, Abay, Cristiana, Abbafati, Foad, Abd-Allah, Jemal, Abdela, Ahmed, Abdelalim, Zegeye, Abebe, Teshome, Abuka, Abebo, Victor, Aboyans, Haftom, Niguse, Abraha, Daisy, M, X, Abreu, Laith, Abu-Raddad, J, Akilew, Awoke, Adane, Rufus, Adesoji, Adedoyin, Olatunji, Adetokunboh, Tara, Ballav, Adhikari, Mohsen, Afarideh, Ashkan, Afshin, Gina, Agarwal, Dominic, Agius, Anurag, Agrawal, Sutapa, Agrawal, Aliasghar, Ahmad, Kiadaliri, Miloud, Taki, Eddine, Aichour, Mohammed, Akibu, Rufus, Olusola, Akinyemi, Tomi, Akinyemiju, F, Nadia, Akseer, Faris, Hasan, Lami, Al, Fares, Alahdab, Ziyad, Al-Aly, Khurshid, Alam, Tahiya, Alam, Deena, Alasfoor, Mohammed, I, Albittar, Kefyalew, Addis, Alene, Ayman, Al-Eyadhy, Syed, Danish, Ali, Mehran, Alijanzadeh, Syed, M, Aljunid, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Mahmoud, A, Alomari, Rajaa, Al-Raddadi, Ubai, Alsharif, Khalid, A, Altirkawi, Nelson, Alvis-Guzman, Azmeraw, T, Amare, Kebede, Amenu, Walid, Ammar, Yaw, Ampem, Amoako, Nahla, Anber, Catalina, Liliana, Andrei, Sofia, Androudi, Carl, Abelardo, Antonio, T, Valdelaine, E, Araújo, M, Olatunde, Aremu, Johan, Ärnlöv, Artaman, Al, Krishna, Kumar, Aryal, Hamid, Asayesh, Ephrem, Tsegay, Asfaw, Solomon, Weldegebreal, Asgedom, Rana, Jawad, Asghar, Mengistu, Mitiku, Ashebir, Netsanet, Abera, Asseffa, Tesfay, Mehari, Atey, Sachin, R, Atre, Madhu, Atteraya, S, Leticia, Avila-Burgos, Euripide, Frinel, Arthur, G, Avokpaho, Ashish, Awasthi, Beatriz, Paulina, Ayala, Quintanilla, Animut, Alebel, Ayalew, Henok, Tadesse, Ayele, Rakesh, Ayer, Tambe, Betrand, Ayuk, Peter, Azzopardi, Natasha, Azzopardi-Muscat, Tesleem, Kayode, Babalola, Hamid, Badali, Alaa, Badawi, Maciej, Banach, Amitava, Banerjee, Amrit, Banstola, Ryan, M, Barber, Miguel, Barboza, A, Suzanne, L, Barker-Collo, Till, Bärnighausen, Simon, Barquera, Lope, H, Barrero, Quique, Bassat, Sanjay, Basu, Bernhard, T, Baune, Shahrzad, Bazargan-Hejazi, Neeraj, Bedi, Ettore, Beghi, Masoud, Behzadifar, Meysam, Behzadifar, Bayu, Begashaw, Bekele, Abate, Bekele, Belachew, Saba, Abraham, Belay, Yihalem, Abebe, Belay, Michelle, L, Bell, Aminu, Bello, K, Derrick, A, Bennett, James, Bennett, R, Isabela, M, Bensenor, Derbew, Fikadu, Berhe, Eduardo, Bernabé, Robert, Steven, Bernstein, Mircea, Beuran, Ashish, Bhalla, Paurvi, Bhatt, Soumyadeep, Bhaumik, Zulfiqar, A, Bhutta, Belete, Biadgo, Ali, Bijani, Boris, Bikbov, Charles, Birungi, Stan, Biryukov, Hailemichael, Bizuneh, Ian, W, Bolliger, Kaylin, Bolt, Ibrahim, R, Bou-Orm, Kayvan, Bozorgmehr, Oliver, Jerome, Brady, Alexandra, Brazinova, Nicholas, J, Breitborde, K, Hermann, Brenner, Gabrielle, Britton, Traolach, S, Brugha, Zahid, Butt, A, Lucero, Cahuana-Hurtado, Ismael, Ricardo, Campos-Nonato, Julio, Cesar, Campuzano, Josip, Car, Mate, Car, Rosario, Cárdenas, Juan, Jesus, Carrero, Felix, Carvalho, Carlos, A, Castañeda-Orjuela, Jacqueline, Castillo, Rivas, Ferrán, Catalá-López, Kelly, Cercy, Julian, Chalek, Hsing-Yi, Chang, Jung-Chen, Chang, Aparajita, Chattopadhyay, Pankaj, Chaturvedi, Peggy, Pei-Chia, Chiang, Vesper, Hichilombwe, Chisumpa, Jee-Young, J, Choi, Hanne, Christensen, Devasahayam, Jesudas, Christopher, Sheng-Chia, Chung, Liliana, G, Ciobanu, Cirillo, Massimo, Danny, Colombara, Sara, Conti, Cyrus, Cooper, Leslie, Cornaby, Paolo, Angelo, Cortesi, Monica, Cortinovis, Alexandre, Costa, Pereira, Ewerton, Cousin, Michael, H, Criqui, Elizabeth, Cromwell, A, Christopher, Stephen, Crowe, John, Crump, A, Alemneh, Kabeta, Daba, Berihun, Assefa, Dachew, Abel, Fekadu, Dadi, Lalit, Dandona, Rakhi, Dandona, Paul, I, Dargan, Ahmad, Daryani, Maryam, Daryani, Jai, Das, Siddharth, Kumar, Das, José, Das, Neves, Nicole, Davis, Weaver, Kairat, Davletov, Barbora, De, Courten, Diego, Leo, De, Jan-Walter, De, Neve, Robert, Dellavalle, P, Gebre, Demoz, Kebede, Deribe, Don, C, Des, Jarlais, Subhojit, Dey, Samath, D, Dharmaratne, Meghnath, Dhimal, Shirin, Djalalinia, David, Teye, Doku, Kate, Dolan, Ray, E, Dorsey, Kadine, Priscila, Bender, Dos, Santos, Kerrie, E, Doyle, Tim, Driscoll, R, Manisha, Dubey, Eleonora, Dubljanin, Bruce, Bartholow, Duncan, Michelle, Echko, Dumessa, Edessa, David, Edvardsson, Joshua, R, Ehrlich, Erika, Eldrenkamp, Ziad, El-Khatib, Matthias, Endres, Aman, Yesuf, Endries, Babak, Eshrati, Sharareh, Eskandarieh, Alireza, Esteghamati, Mahdi, Fakhar, Tamer, Farag, Mahbobeh, Faramarzi, Emerito, Jose, Aquino, Faraon, André, Faro, Farshad, Farzadfar, Adesegun, Fatusi, Mir, Sohail, Fazeli, Valery, Feigin, L, Andrea, B, Feigl, Netsanet, Fentahun, Seyed-Mohammad, Fereshtehnejad, Eduarda, Fernandes, João, C, Fernandes, Daniel, Obadare, Fijabi, Irina, Filip, Florian, Fischer, Christina, Fitzmaurice, Abraham, D, Flaxman, Luisa, Sorio, Flor, Nataliya, Foigt, Kyle, J, Foreman, Joseph, Frostad, J, Thomas, Fürst, Neal, D, Futran, Emmanuela, Gakidou, Silvano, Gallus, Ketevan, Gambashidze, Amiran, Gamkrelidze, Morsaleh, Ganji, Abadi, Kahsu, Gebre, Tsegaye, Tewelde, Gebrehiwot, Amanuel, Tesfay, Gebremedhin, Yalemzewod, Assefa, Gelaw, Johanna, M, Geleijnse, Demeke, Geremew, Peter, W, Gething, Reza, Ghadimi, Khalil, Ghasemi, Falavarjani, Maryam, Ghasemi-Kasman, Paramjit, Singh, Gill, Ababi, Zergaw, Giref, Maurice, Giroud, Melkamu, Dedefo, Gishu, Giorgia, Giussani, William, W, Godwin, Srinivas, Goli, Hector, Gomez-Dantes, Philimon, N, Gona, Amador, Goodridge, Sameer, Vali, Gopalani, Yevgeniy, Goryakin, Alessandra, Carvalho, Goulart, Ayman, Grada, Max, Griswold, Giuseppe, Grosso, Harish, Chander, Gugnani, Yuming, Guo, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Gupta, Juanita, A, Haagsma, Vladimir, Hachinski, Nima, Hafezi-Nejad, Gessessew, Bugssa, Hailu, Randah, Ribhi, Hamadeh, Samer, Hamidi, Graeme, J, Hankey, Hilda, Harb, L, Heather, C, Harewood, Sivadasanpillai, Harikrishnan, Josep, Maria, Haro, Hamid, Yimam, Hassen, Rasmus, Havmoeller, Caitlin, Hawley, Simon, I, Hay, Jiawei, He, Stephen, J, Hearps, C, Mohamed, I, Hegazy, Behzad, Heibati, Mohsen, Heidari, Delia, Hendrie, Nathaniel, J, Henry, Victor, Hugo, Herrera, Ballesteros, Claudiu, Herteliu, Desalegn, Tsegaw, Hibstu, Molla, Kahssay, Hiluf, Hans, W, Hoek, Enayatollah, Homaie, Rad, Nobuyuki, Horita, Dean, H, Hosgood, Mostafa, Hosseini, Seyed, Reza, Hosseini, Mihaela, Hostiuc, Sorin, Hostiuc, Damian, G, Hoy, Mohamed, Hsairi, Aung, Soe, Htet, Guoqing, Hu, John, J, Huang, Kim, Moesgaard, Iburg, Fachmi, Idris, Ehimario, Uche, Igumbor, Chad, Ikeda, Bogdan, Vasile, Ileanu, Olayinka, Ilesanmi, S, Kaire, Innos, Seyed, Sina, Naghibi, Irvani, Caleb, M, Irvine, S, Farhad, Islami, Troy, A, Jacobs, Kathryn, Jacobsen, H, Nader, Jahanmehr, Rajesh, Jain, Sudhir, Kumar, Jain, Mihajlo, Jakovljevic, M, Moti, Tolera, Jalu, Amr, Jamal, A, Mehdi, Javanbakht, Achala, Upendra, Jayatilleke, Panniyammakal, Jeemon, Ravi, Prakash, Jha, Vivekanand, Jha, Jacek, Józwiak, Oommen, John, Sarah, Charlotte, Johnson, Jost, Jonas, B, Vasna, Joshua, Mikk, Jürisson, Zubair, Kabir, Rajendra, Kadel, Amaha, Kahsay, Rizwan, Kalani, Chittaranjan, Kar, Marina, Karanikolos, André, Karch, Corine, Kakizi, Karema, Seyed, Karimi, M, Amir, Kasaeian, Dessalegn, Haile, Kassa, Getachew, Mullu, Kassa, Tesfaye, Dessale, Kassa, Nicholas, Kassebaum, J, Srinivasa, Vittal, Katikireddi, Anil, Kaul, Norito, Kawakami, Konstantin, Kazanjan, Seifu, Kebede, Peter, Njenga, Keiyoro, Grant, Rodgers, Kemp, Andre, Pascal, Kengne, Maia, Kereselidze, Ezra, Belay, Ketema, Yousef, Saleh, Khader, Morteza, Abdullatif, Khafaie, Alireza, Khajavi, Ibrahim, A, Khalil, Ejaz, Ahmad, Khan, Gulfaraz, Khan, Nuruzzaman, Md, Khan, Muhammad, Ali, Khan, Mukti, Nath, Khanal, Young-Ho, Khang, Mona, M, Khater, Abdullah, Tawfih, Abdullah, Khoja, Ardeshir, Khosravi, Jagdish, Khubchandani, Getiye, Dejenu, Kibret, Daniel, Ngari, Kiirithio, Daniel, Kim, Yun, Jin, Kim, Ruth, Kimokoti, W, Yohannes, Kinfu, Sanjay, Kinra, Adnan, Kisa, Niranjan, Kissoon, Sonali, Kochhar, Yoshihiro, Kokubo, Jacek, A, Kopec, Soewarta, Kosen, Parvaiz, A, Koul, Koyanagi, Ai, Michael, Kravchenko, Kewal, Krishan, Kristopher, J, Krohn, Barthelemy, Kuate, Defo, Anil, G, Kumar, Pushpendra, Kumar, Michael, Kutz, Igor, Kuzin, Hmwe, H, Kyu, Deepesh, Pravinkumar, Lad, Alessandra, Lafranconi, Dharmesh, Kumar, Lal, Ratilal, Lalloo, Hilton, Lam, Qing, Lan, Justin, J, Lang, Van, Lansingh, C, Sonia, Lansky, Anders, Larsson, Arman, Latifi, Jeffrey, Victor, Lazarus, Janet, Leasher, L, Paul, H, Lee, Yirga, Legesse, James, Leigh, Cheru, Tesema, Leshargie, Samson, Leta, Janni, Leung, Ricky, Leung, Miriam, Levi, Yongmei, Li, Juan, Liang, Misgan, Legesse, Liben, Lee-Ling, Lim, Stephen, S, Lim, Margaret, Lind, Shai, Linn, Stefan, Listl, Patrick, Y, Liu, Shiwei, Liu, Rakesh, Lodha, Alan, D, Lopez, Scott, Lorch, A, Stefan, Lorkowski, Paulo, A, Lotufo, Timothy, C, D, Lucas, Raimundas, Lunevicius, Grégoire, Lurton, Ronan, A, Lyons, Fadi, Maalouf, Erlyn, Rachelle, King, Macarayan, Mark, T, Mackay, Emilie, Maddison, R, Fabiana, Madotto, Hassan, Magdy, Abd, El, Razek, Mohammed, Magdy, Abd, Razek, El, Marek, Majdan, Reza, Majdzadeh, Azeem, Majeed, Reza, Malekzadeh, Rajesh, Malhotra, Deborah, Carvalho, Malta, Abdullah, Mamun, A, Helena, Manguerra, Treh, Manhertz, Mohammad, Ali, Mansournia, Lorenzo, Mantovani, G, Tsegahun, Manyazewal, Chabila, C, Mapoma, Christopher, Margono, Jose, Martinez-Raga, Sheila, Cristina, Ouriques, Martins, Francisco, Rogerlândio, Martins-Melo, Ira, Martopullo, Winfried, März, Benjamin, Ballard, Massenburg, Manu, Raj, Mathur, Pallab, K, Maulik, Mohsen, Mazidi, Colm, Mcalinden, Mcgrath, Martin, Mckee, Suresh, Mehata, Ravi, Mehrotra, Kala, M, Mehta, Varshil, Mehta, Toni, Meier, Fabiola, Mejia-Rodriguez, Kidanu, Gebremariam, Meles, Mulugeta, Melku, Peter, Memiah, Ziad, A, Memish, Walter, Mendoza, Degu, Abate, Mengiste, Desalegn, Tadese, Mengistu, Bereket, Gebremichael, Menota, George, Mensah, A, Atte, Meretoja, Tuomo, J, Meretoja, Haftay, Berhane, Mezgebe, Tomasz, Miazgowski, Renata, Micha, Robert, Milam, Anoushka, Millear, Ted, R, Miller, Mini, Gk, Shawn, Minnig, Andreea, Mirica, Erkin, M, Mirrakhimov, Awoke, Misganaw, Philip, B, Mitchell, Fitsum, Weldegebreal, Mlashu, Babak, Moazen, Karzan, Abdulmuhsin, Mohammad, Roghayeh, Mohammadibakhsh, Ebrahim, Mohammed, Mohammed, A, Mohammed, Shafiu, Mohammed, Ali, H, Mokdad, Glen, Liddell, D, Mola, Mariam, Molokhia, Fatemeh, Momeniha, Lorenzo, Monasta, Julio, Cesar, Montañez, Hernandez, Mahmood, Moosazadeh, Maziar, Moradi-Lakeh, Paula, Moraga, Lidia, Morawska, Ilais, Moreno, Velasquez, Rintaro, Mori, Shane, D, Morrison, Mark, Moses, Seyyed, Meysam, Mousavi, Ulrich, Mueller, O, Manoj, Murhekar, Gudlavalleti, Venkata, Satyanarayana, Murthy, Srinivas, Murthy, Jonah, Musa, Kamarul, Imran, Musa, Ghulam, Mustafa, Saravanan, Muthupandian, Chie, Nagata, Gabriele, Nagel, Mohsen, Naghavi, Aliya, Naheed, Gurudatta, A, Naik, Nitish, Naik, Farid, Najafi, Luigi, Naldi, Vinay, Nangia, Jobert, Richie, Njingang, Nansseu, K, M, Venkat, Narayan, Bruno, Ramos, Nascimento, Ionut, Negoi, Ruxandra, Irina, Negoi, Charles, Newton, R, Josephine, Wanjiku, Ngunjiri, Grant, Nguyen, Long, Nguyen, Trang, Huyen, Nguyen, Emma, Nichols, Dina, Nur, Anggraini, Ningrum, Ellen, Nolte, Vuong, Minh, Nong, Ole, Norheim, F, Norrving, Bo, Jean, Jacques, Noubiap, N, Alypio, Nyandwi, Carla, Makhlouf, Obermeyer, Richard, Ofori-Asenso, Felix, Akpojene, Ogbo, In-Hwan, Oh, Olanrewaju, Oladimeji, Andrew, Toyin, Olagunju, Tinuke, Oluwasefunmi, Olagunju, Pedro, R, Olivares, Patricia, Pereira, Vasconcelos, Oliveira, De, Helen, E, Olsen, Bolajoko, Olubukunola, Olusanya, Jacob, Olusegun, Olusanya, Kanyin, Ong, John, Nelson, Opio, Eyal, Oren, Doris, V, Ortega-Altamirano, Alberto, Ortiz, Raziye, Ozdemir, Mahesh, Pa, Amanda, W, Pain, Marcos, Roberto, Tovani, Palone, Adrian, Pana, Songhomitra, Panda-Jonas, Jeyaraj, D, Pandian, Eun-Kee, Park, Hadi, Parsian, Tejas, Patel, Sanghamitra, Pati, Snehal, T, Patil, Ajay, Patle, George, C, Patton, Vishnupriya, Rao, Paturi, Deepak, Paudel, Marcel, De, Moares, Pedroso, Sandra, P, Pedroza, David, Pereira, M, Norberto, Perico, Hannah, Peterson, Max, Petzold, Niloofar, Peykari, Michael, Robert, Phillips, Frédéric, Piel, B, David, M, Pigott, Julian, David, Pillay, Michael, A, Piradov, Suzanne, Polinder, Constance, D, Pond, Maarten, Postma, J, Farshad, Pourmalek, Swayam, Prakash, Prakash, V, Narayan, Prasad, Noela, Marie, Prasad, Caroline, Purcell, Mostafa, Qorbani, Hedley, Knewjen, Quintana, Amir, Radfar, Anwar, Rafay, Alireza, Rafiei, Kazem, Rahimi, Afarin, Rahimi-Movaghar, Vafa, Rahimi-Movaghar, Mahfuzar, Rahman, Muhammad, Aziz, Rahman, Sajjad, Rahman, Ur, Rajesh, Kumar, Rai, Sree, Bhushan, Raju, Usha, Ram, Saleem, M, Rana, Zane, Rankin, Davide, Rasella, David, Laith, Rawaf, Salman, Rawaf, Sarah, E, Ray, Christian, Aspacia, Razo-García, Priscilla, Reddy, Robert, C, Reiner, Cesar, Reis, Marissa, B, Reitsma, Giuseppe, Remuzzi, Andre, M, Renzaho, N, Serge, Resnikoff, Satar, Rezaei, Mohammad, Sadegh, Rezai, Antonio, Ribeiro, L, Maria, Jesus, Rios, Blancas, Juan, A, Rivera, Leonardo, Roever, Luca, Ronfani, Gholamreza, Roshandel, Ali, Rostami, Gregory, A, Roth, Dietrich, Rothenbacher, Ambuj, Roy, Nobhojit, Roy, George, Mugambage, Ruhago, Yogesh, Damodar, Sabde, Perminder, S, Sachdev, Nafis, Sadat, Mahdi, Safdarian, Saeid, Safiri, Rajesh, Sagar, Amirhossein, Sahebkar, Sahraian, Haniye, Sadat, Sajadi, Joseph, Salama, Payman, Salamati, Raphael, De, Freitas, Saldanha, Hamideh, Salimzadeh, Joshua, A, Salomon, Abdallah, Samy, M, Juan, Ramon, Sanabria, Parag, Sancheti, K, Maria, Dolores, Sanchez-Niño, Damian, Santomauro, Itamar, S, Santos, Milena, Santric, M, Milicevic, Abdur, Razzaque, Sarker, Nizal, Sarrafzadegan, Benn, Sartorius, Maheswar, Satpathy, Miloje, Savic, Monika, Sawhney, Sonia, Saxena, Mete, I, Saylan, Elke, Schaeffner, Josef, Schmidhuber, Maria, Inês, Schmidt, Ione, J, C, Schneider, Austin, Schumacher, E, Aletta, E, Schutte, David, Schwebel, C, Falk, Schwendicke, Mario, Sekerija, Sadaf, G, Sepanlou, Edson, Servan-Mori, E, Azadeh, Shafieesabet, Masood, Ali, Shaikh, Marina, Shakh-Nazarova, Mehran, Shams-Beyranvand, Heidar, Sharafi, Mahdi, Sharif-Alhoseini, Sheikh, Mohammed, Shariful, Islam, Meenakshi, Sharma, Rajesh, Sharma, Jun, She, Aziz, Sheikh, Mebrahtu, Teweldemedhin, Shfare, Peilin, Shi, Chloe, Shields, Mika, Shigematsu, Yukito, Shinohara, Rahman, Shiri, Reza, Shirkoohi, Ivy, Shiue, Mark, G, Shrime, Sharvari, Rahul, Shukla, Soraya, Siabani, Inga, Dora, Sigfusdottir, Donald, Silberberg, H, Diego, Augusto, Santos, Silva, João, Pedro, Silva, Dayane, Gabriele, Alves, Silveira, Jasvinder, Singh, A, Lavanya, Singh, Narinder, Pal, Singh, Virendra, Singh, Dhirendra, Narain, Sinha, Abiy, Hiruye, Sinke, Mekonnen, Sisay, Vegard, Skirbekk, Karen, Sliwa, Alison, Smith, Adauto, Martins, Soares, Filho, Badr, H, Sobaih, A, Melek, Somai, Samir, Soneji, Moslem, Soofi, Reed, J, Sorensen, D, Joan, B, Soriano, Ireneous, Soyiri, N, Luciano, A, Sposato, Chandrashekhar, Sreeramareddy, T, Vinay, Srinivasan, Jeffrey, D, Stanaway, Vasiliki, Stathopoulou, Nicholas, Steel, Dan, J, Stein, Mark, Andrew, Stokes, Lela, Sturua, Muawiyyah, Babale, Sufiyan, Rizwan, Abdulkader, Suliankatchi, Bruno, F, Sunguya, Patrick, Sur, J, Bryan, L, Sykes, P, Sylaja, N, Cassandra, E, Szoeke, I, Rafael, Tabarés-Seisdedos, Santosh, Kumar, Tadakamadla, Andualem, Henok, Tadesse, Getachew, Redae, Taffere, Nikhil, Tandon, Amare, Tariku, Tariku, Nuno, Taveira, Arash, Tehrani-Banihashemi, Girma, Temam, Shifa, Mohamad-Hani, Temsah, Abdullah, Sulieman, Terkawi, Azeb, Gebresilassie, Tesema, Dawit, Jember, Tesfaye, Belay, Tessema, Thakur, Js, Nihal, Thomas, Matthew, J, Thompson, Taavi, Tillmann, Quyen, G, Ruoyan, Tobe-Gai, Marcello, Tonelli, Roman, Topor-Madry, Fotis, Topouzis, Anna, Torre, Miguel, Tortajada, Bach, Xuan, Tran, Khanh, Bao, Tran, Avnish, Tripathi, Srikanth, Prasad, Tripathy, Christopher, Troeger, Thomas, Truelsen, Derrick, Tsoi, Lorainne, Tudor, Car, Kald, Beshir, Tuem, Stefanos, Tyrovolas, Uche, S, Uchendu, Kingsley, Nnanna, Ukwaja, Irfan, Ullah, Rachel, Updike, Olalekan, A, Uthman, Benjamin, Chudi, S, Uzochukwu, Pascual, Rubén, Valdez, Job, F, Van, M, Boven, Santosh, Varughese, Tommi, Vasankari, Narayanaswamy, Venketasubramanian, Francesco, S, Violante, Sergey, Vladimirov, K, Vasiliy, Victorovich, Vlassov, Stein, Emil, Vollset, Theo, Vos, Fasil, Wagnew, Yasir, Waheed, Mitchell, T, Wallin, Judd, Walson, L, Yafeng, Wang, Yuan-Pang, Wang, Molla, Mesele, Wassie, Marcia, Weaver, R, Elisabete, Weiderpass, Robert, G, Weintraub, Jordan, Weiss, Kidu, Gidey, Weldegwergs, Andrea, Werdecker, Eoin, T, West, Ronny, Westerman, Richard, G, White, Harvey, Whiteford, A, Justyna, Widecka, Andrea, Sylvia, Winkler, Charles, Shey, Wiysonge, Charles, D, Wolfe, A, Yohanes, Ayele, Wondimkun, Abdulhalik, Workicho, Grant, M, Wyper, A, Denis, Xavier, Gelin, Xu, Lijing, L, Yan, Yuichiro, Yano, Mehdi, Yaseri, Nigus, Bililign, Yimer, Peng, Yin, Paul, Yip, Biruck, Desalegn, Yirsaw, Naohiro, Yonemoto, Gerald, Yonga, Seok-Jun, 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Ray, Dos Santos, Kadine Priscila Bender, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duncan, Bruce Bartholow, Echko, Michelle, Edessa, Dumessa, Edvardsson, David, Ehrlich, Joshua R., Eldrenkamp, Erika, El-Khatib, Ziad, Endres, Matthia, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Fakhar, Mahdi, Farag, Tamer, Faramarzi, Mahbobeh, Faraon, Emerito Jose Aquino, Faro, André, Farzadfar, Farshad, Fatusi, Adesegun, Fazeli, Mir Sohail, Feigin, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, João C., Fijabi, Daniel Obadare, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Flor, Luisa Sorio, Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fürst, Thoma, Futran, Neal D., Gakidou, Emmanuela, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Ganji, Morsaleh, Gebre, Abadi Kahsu, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M., Geremew, Demeke, Gething, Peter W., Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Gill, Paramjit Singh, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Goli, Sriniva, Gomez-Dantes, Hector, Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Grada, Ayman, Griswold, Max, Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Haagsma, Juanita A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hankey, Graeme J., Harb, Hilda L., Harewood, Heather C., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassen, Hamid Yimam, Havmoeller, Rasmu, Hawley, Caitlin, Hay, Simon I., He, Jiawei, Hearps, Stephen J.C., Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henry, Nathaniel J., Herrera Ballesteros, Victor Hugo, Herteliu, Claudiu, Hibstu, Desalegn Tsegaw, Hiluf, Molla Kahssay, Hoek, Hans W., Homaie Rad, Enayatollah, Horita, Nobuyuki, Hosgood, H. Dean, Hosseini, Mostafa, Hosseini, Seyed Reza, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J., Iburg, Kim Moesgaard, Idris, Fachmi, Igumbor, Ehimario Uche, Ikeda, Chad, Ileanu, Bogdan Vasile, Ilesanmi, Olayinka S., Innos, Kaire, Irvani, Seyed Sina Naghibi, Irvine, Caleb M.S., Islami, Farhad, Jacobs, Troy A., Jacobsen, Kathryn H., Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo M., Jalu, Moti Tolera, Jamal, Amr A., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Józwiak, Jacek, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Joshua, Vasna, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kar, Chittaranjan, Karanikolos, Marina, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn Haile, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodger, Kengne, Andre Pascal, Kereselidze, Maia, Ketema, Ezra Belay, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Muhammad Ali, Khanal, Mukti Nath, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khubchandani, Jagdish, Kibret, Getiye Dejenu, Kiirithio, Daniel Ngari, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kinra, Sanjay, Kisa, Adnan, Kissoon, Niranjan, Kochhar, Sonali, Kokubo, Yoshihiro, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krishan, Kewal, Krohn, Kristopher J., Kuate Defo, Barthelemy, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kuzin, Igor, Kyu, Hmwe H., Lad, Deepesh Pravinkumar, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lang, Justin J., Lansingh, Van C., Lansky, Sonia, Larsson, Ander, Latifi, Arman, Lazarus, Jeffrey Victor, Leasher, Janet L., Lee, Paul H., Legesse, Yirga, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yongmei, Liang, Juan, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S., Lind, Margaret, Linn, Shai, Listl, Stefan, Liu, Patrick Y., Liu, Shiwei, Lodha, Rakesh, Lopez, Alan D., Lorch, Scott A., Lorkowski, Stefan, Lotufo, Paulo A., Lucas, Timothy C.D., Lunevicius, Raimunda, Lurton, Grégoire, Lyons, Ronan A., Maalouf, Fadi, Macarayan, Erlyn Rachelle King, Mackay, Mark T., Maddison, Emilie R., Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Mohammed, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A., Manguerra, Helena, Manhertz, Treh, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Manyazewal, Tsegahun, Mapoma, Chabila C., Margono, Christopher, Martinez-Raga, Jose, Martins, Sheila Cristina Ourique, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mejia-Rodriguez, Fabiola, Meles, Kidanu Gebremariam, Melku, Mulugeta, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengiste, Degu Abate, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Miazgowski, Tomasz, Micha, Renata, Milam, Robert, Millear, Anoushka, Miller, Ted R., Mini, G.K., Minnig, Shawn, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke, Mitchell, Philip B., Mlashu, Fitsum Weldegebreal, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadibakhsh, Roghayeh, Mohammed, Ebrahim, Mohammed, Mohammed A., Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Moosazadeh, Mahmood, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Moreno Velasquez, Ilai, Mori, Rintaro, Morrison, Shane D., Moses, Mark, Mousavi, Seyyed Meysam, Mueller, Ulrich O., Murhekar, Manoj, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta A., Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nangia, Vinay, Nansseu, Jobert Richie Njingang, Narayan, K.M. Venkat, Nascimento, Bruno Ramo, Negoi, Ionut, Negoi, Ruxandra Irina, Newton, Charles R., Ngunjiri, Josephine Wanjiku, Nguyen, Grant, Nguyen, Long, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nolte, Ellen, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Nyandwi, Alypio, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., De Oliveira, Patricia Pereira Vasconcelo, Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortega-Altamirano, Doris V., Ortiz, Alberto, Ozdemir, Raziye, Pa, Mahesh, Pain, Amanda W., Palone, Marcos Roberto Tovani, Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Park, Eun-Kee, Parsian, Hadi, Patel, Teja, Pati, Sanghamitra, Patil, Snehal T., Patle, Ajay, Patton, George C., Paturi, Vishnupriya Rao, Paudel, Deepak, De Moares Pedroso, Marcel, Pedroza, Sandra P., Pereira, David M., Perico, Norberto, Peterson, Hannah, Petzold, Max, Peykari, Niloofar, Phillips, Michael Robert, Piel, Frédéric B., Pigott, David M., Pillay, Julian David, Piradov, Michael A., Polinder, Suzanne, Pond, Constance D., Postma, Maarten J., Pourmalek, Farshad, Prakash, Swayam, Prakash, V., Prasad, Narayan, Prasad, Noela Marie, Purcell, Caroline, Qorbani, Mostafa, Quintana, Hedley Knewjen, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Raju, Sree Bhushan, Ram, Usha, Rana, Saleem M., Rankin, Zane, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E., Razo-García, Christian Aspacia, Reddy, Priscilla, Reiner, Robert C., Reis, Cesar, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio L., Rios Blancas, Maria Jesu, Rivera, Juan A., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A., Rothenbacher, Dietrich, Roy, Ambuj, Roy, Nobhojit, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S., Sadat, Nafi, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salama, Joseph, Salamati, Payman, De Freitas Saldanha, Raphael, Salimzadeh, Hamideh, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sancheti, Parag K., Sanchez-Niño, Maria Dolore, Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Saxena, Sonia, Saylan, Mete I., Schaeffner, Elke, Schmidhuber, Josef, Schmidt, Maria Inê, Schneider, Ione J.C., Schumacher, Austin E., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Sekerija, Mario, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shafieesabet, Azadeh, Shaikh, Masood Ali, Shakh-Nazarova, Marina, Shams-Beyranvand, Mehran, Sharafi, Heidar, Sharif-Alhoseini, Mahdi, Shariful Islam, Sheikh Mohammed, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shfare, Mebrahtu Teweldemedhin, Shi, Peilin, Shields, Chloe, Shigematsu, Mika, Shinohara, Yukito, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shrime, Mark G., Shukla, Sharvari Rahul, Siabani, Soraya, Sigfusdottir, Inga Dora, Silberberg, Donald H., Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Lavanya, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Sinke, Abiy Hiruye, Sisay, Mekonnen, Skirbekk, Vegard, Sliwa, Karen, Smith, Alison, Soares Filho, Adauto Martin, Sobaih, Badr H.A., Somai, Melek, Soneji, Samir, Soofi, Moslem, Sorensen, Reed J.D., Soriano, Joan B., Soyiri, Ireneous N., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J., Stokes, Mark Andrew, Sturua, Lela, Sufiyan, Muawiyyah Babale, Suliankatchi, Rizwan Abdulkader, Sunguya, Bruno F., Sur, Patrick J., Sykes, Bryan L., Sylaja, P.N., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Tadesse, Andualem Henok, Taffere, Getachew Redae, Tandon, Nikhil, Tariku, Amare Tariku, Taveira, Nuno, Tehrani-Banihashemi, Arash, Temam Shifa, Girma, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Tesema, Azeb Gebresilassie, Tesfaye, Dawit Jember, Tessema, Belay, Thakur, J.S., Thomas, Nihal, Thompson, Matthew J., Tillmann, Taavi, To, Quyen G., Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna, Tortajada, Miguel, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Avnish, Tripathy, Srikanth Prasad, Troeger, Christopher, Truelsen, Thoma, Tsoi, Derrick, Tudor Car, Lorainne, Tuem, Kald Beshir, Tyrovolas, Stefano, Uchendu, Uche S., Ukwaja, Kingsley Nnanna, Ullah, Irfan, Updike, Rachel, Uthman, Olalekan A., Uzochukwu, Benjamin S. Chudi, Valdez, Pascual Rubén, Van Boven, Job F.M., Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wagnew, Fasil, Waheed, Yasir, Wallin, Mitchell T., Walson, Judd L., Wang, Yafeng, Wang, Yuan-Pang, Wassie, Molla Mesele, Weaver, Marcia R., Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Jordan, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T. 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Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, 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Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.
Subjects: Peformance, Coverage, Dánartíðni, Lífslíkur, Life expectancy, GBD, Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best), universal health coverage, Article, access quality health care, health care access and quality index, Nations, Healthcare Acce, Cause-specific mortality, Psychology, Healthcare Access and Quality Index, Mælitæki, States, Medicine (all), Health care, Þjóðir, Public Health, Global Health, Social Medicine and Epidemiology, Quality, Heilbrigðisþjónusta, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Sálfræði, Indicator, Amenable mortality, Transition, we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations, Trends, Inequalities
Abstract: Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.
Published: 2018

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

Author: 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, Artaman, Al, Aryal, Krishna K, Asadi-Lari, Mohsen, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Ataro, Zerihun, Atey, Tesfay Mehari Mehari, Athari, Seyyed Shamsadin, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Attia, Engi F, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Awuah, Baffour, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barquera, Simon, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhatia, Eesh, Bhatt, Samir, Bhattarai, Suraj, Bhaumik, Soumyadeeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bjørge, Tone, Bleyer, Archie, Basara, Berrak Bora, Bose, Dipan, Bosetti, Cristina, Boufous, Soufiane, Bourne, Rupert, Brady, Oliver J, Bragazzi, Nicola Luigi, Brant, Luisa C, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Britton, Gabrielle, Brugha, Traolach, Burke, Kristin E, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton S K H, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J, Carter, Austin, Carvalho, Félix, 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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, 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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
Subjects: 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).
Published: 2018

21. New algorithmic approach for easier and faster extended disability status scale calculation.

Author: Fouad AM, Abdel Naseer M, Farghaly M, and Hegazy MI
Abstract: Background: The traditional paper and pencil method for EDSS calculation (pEDSS) is the cornerstone of multiple sclerosis practice; however, it requires an expert for an accurate calculation, and it takes a lot of time to perform the function scores. A new algorithmic approach (aEDSS) has been developed for easier and faster assessment., Objective: To determine if using aEDSS can achieve good inter-rater agreement and save time compared to pEDSS., Subjects and Methods: This study was conducted on 200 MS patients; EDSS was performed twice for each patient by two neurologists on the same day; one used the pEDSS, and the other used the aEDSS in a random order to test the inter-rater agreement regarding functional system scores and the final EDSS score and to detect the difference in the time needed for calculation between both methods., Results: The new algorithmic approach achieved excellent agreement with the traditional method (Kappa > 0.81) with a shorter calculation time (16 ± 2.67 min for aEDSS vs 31 ± 4.3 min for pEDSS, P < 0.0001)., Conclusion: The new algorithmic approach could represent a suitable alternative to the traditional method, making EDSS calculation easier and faster., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s), 2023.)
Published: 2023
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22. ٍSome biologically active microorganisms have the potential to suppress mosquito larvae ( Culex pipiens , Diptera: Culicidae).

Author: Hegazy MI, Hegazy AM, Saad AM, Salem HM, El-Tahan AM, El-Saadony MT, Soliman SM, Taha AE, Alshehri MA, Ezzat Ahmed A, and Swelum AA
Abstract: Malaria is a disease caused by protozoan species of the genus Plasmodium . It is widespread and becoming a challenge in several African countries in the tropical and subtropical regions. In 2010, a report was published showing that over 1.2 million death cases were occurred globally due to malaria in just one year. The transmission of the disease from one person to another occurs via the bite of the Anopheles female. It is known that Plasmodium ovale, P. vivax , P. malariae , P. falciparum, and P. knowlesi are the highly infective malaria species. The problem of this disease is the absence of any effective medical treatment or vaccine, making the mosquito control is the only feasible way for disease prevention. Pesticides are currently the most widely used method for mosquito control, despite its well-known negative effects, including health hazards on human, the increasing insecticidal resistance, and the negative impact on the environment and beneficial organisms. Biological control (also called: biocontrol) of insects has been a promising method to overcome the negative effects of using chemical insecticides, as it depends on just using the natural enemies of pests to either minimize their populations or eradicate them. This article provides an overview of the recent and effective biological means to control malaria, such as bacteria, fungi, viruses, larvivorous fish, toxorhynchites larva and nematodes. In addition, the importance, advantages, and disadvantages of the biocontrol methods will be discussed in comparison with the traditionally used chemical methods of malaria control with special reference to nanotechnology as a novel method for insects' control., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)
Published: 2022
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23. Neurological Manifestations in a Cohort of Egyptian Patients with COVID-19: A Prospective, Multicenter, Observational Study.

Author: Mekkawy DA, Hamdy S, Abdel-Naseer M, Shehata HS, Halfawy AA, Shalaby NM, Shehata GA, Ali AM, Elmazny A, Ahmed SM, Ismail JH, Ibraheim A, Abdel-Hamid HM, Magdy R, Kabara Ayoub Y, Taha AE, Merghany N, Soliman NM, Elshebawy H, Abdelal SES, El-Ghoneimy L, Al-Athwari A, Kishk NA, Nada MAF, Farghaly M, Hassan A, Hegazy MI, Abdelalim A, Mourad HS, Hassouna A, Othman AS, and Wijeratne T
Abstract: Background: The COVID-19 pandemic has reached over 276 million people globally with 5.3 million deaths as of 22nd December 2021. COVID-19-associated acute and long-term neurological manifestations are well recognized. The exact profile and the timing of neurological events in relation to the onset of infection are worth exploring. The aim of the current body of work was to determine the frequency, pattern, and temporal profile of neurological manifestations in a cohort of Egyptian patients with confirmed COVID-19 infection., Methods: This was a prospective study conducted on 582 hospitalized COVID-19 patients within the first two weeks of the diagnosis of COVID-19 to detect any specific or non-specific neurological events., Results: The patients' mean (SD) age was 46.74 (17.26) years, and 340 (58.42%) patients were females. The most commonly encountered COVID-19 symptoms were fever (90.72%), cough (82.99%), and fatigue (76.98%). Neurological events (NE) detected in 283 patients (48.63%) and were significantly associated with a severe COVID-19 at the onset (OR: 3.13; 95% CI: 2.18-4.51; p < 0.0001) and with a higher mortality (OR: 2.56; 95% CI: 1.48-5.46; p = 0.019). The most frequently reported NEs were headaches ( n = 167) and myalgias ( n = 126). Neurological syndromes included stroke ( n = 14), encephalitis ( n = 12), encephalopathy ( n = 11), transverse myelitis ( n = 6) and Guillain-Barré syndrome ( n = 4)., Conclusions: Neurological involvement is common (48.63%) in COVID-19 patients within the first two weeks of the illness. This includes neurological symptoms such as anosmia, headaches, as well as a constellation of neurological syndromes such as stroke, encephalitis, transverse myelitis, and Guillain-Barré syndrome. Severity of acute COVID-19 illness and older age are the main risk factors.
Published: 2022
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24. Impact of Ramadan fasting on disease activity in patients with multiple sclerosis: a multicenter study.

Author: Hassan A, Merghany N, Ouchkat F, Regragui W, Kedah H, Hamdy SM, Abdel-Naseer M, Shehata HS, Shalaby NM, Kishk NA, Nada MAF, Hegazy MI, Farghaly M, Ahmed SM, and Hussein M
Abstract: Background: The safety of Ramadan fasting for Muslim patients suffering from multiple sclerosis (MS) is still a matter of debate. This work aimed to study the clinical course of MS during Ramadan fasting and to clarify the predictors of relapses and symptoms exacerbation., Methods: This retrospective study included 153 Muslim patients with MS. Data related to the disease course before Ramadan were obtained from patients' files, whereas data related to the disease activity during Ramadan, were collected from patients over the two months following Ramadan., Results: Patients with MS who experienced relapses, exacerbation of symptoms and development of new symptoms during Ramadan had a statistically significant longer disease duration compared to those who did not experience (P < 0.001, <0.001, 0.01 respectively). Also, patients who experienced relapses, exacerbation of symptoms and development of new symptoms during Ramadan had a statistically significant higher expanded disability status scale (EDSS) compared to those who did not experience (P <0.001, <0.001,0.01, respectively). The occurrence of relapses, exacerbation of symptoms and development of new symptoms during Ramadan, were significantly higher in patients who experienced relapses in the preceding year compared to those who did not (P= 0.002, 0.002, 0.01, respectively). Binary logistic regression revealed that each score elevation of EDSS increased the odds of relapse during Ramadan by 1.02 (P-value = 0.04). Also, each month's increase in disease duration increased the odds of relapse during Ramadan by 1.87 (P-value = 0.046)., Conclusion: High EDSS and long disease duration are independent predictors of relapse during Ramadan.
Published: 2021
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25. Rainwater-driven microbial fuel cells for power generation in remote areas.

Author: Amen MT, Yasin AS, Hegazy MI, Jamal MAHM, Hong ST, and Barakat NAM
Abstract: The possibility of using rainwater as a sustainable anolyte in an air-cathode microbial fuel cell (MFC) is investigated in this study. The results indicate that the proposed MFC can work within a wide temperature range (from 0 to 30°C) and under aerobic or anaerobic conditions. However, the rainwater season has a distinct impact. Under anaerobic conditions, the summer rainwater achieves a promised open circuit potential (OCP) of 553 ± 2 mV without addition of nutrients at the ambient temperature, while addition of nutrients leads to an increase in the cell voltage to 763 ± 3 and 588 ± 2 mV at 30°C and ambient temperature, respectively. The maximum OCP for the winter rainwater (492 ± 1.5 mV) is obtained when the reactor is exposed to the air (aerobic conditions) at ambient temperature. Furthermore, the winter rainwater MFC generates a maximum power output of 7 ± 0.1 mWm -2 at a corresponding current density value of 44 ± 0.7 mAm -2 at 30°C. While, at the ambient temperature, the maximum output power is obtained with the summer rainwater (7.2 ± 0.1 mWm -2 at 26 ± 0.5 mAm -2 ). Moreover, investigation of the bacterial diversity indicates that Lactobacillus spp. is the dominant electroactive genus in the summer rainwater, while in the winter rainwater, Staphylococcus spp. is the main electroactive bacteria. The cyclic voltammetry analysis confirms that the electrons are delivered directly from the bacterial biofilm to the anode surface and without mediators. Overall, this study opens a new avenue for using a novel sustainable type of MFC derived from rainwater., (© 2021 The Authors.)
Published: 2021
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26. The aquaporin4-IgG status and how it affects the clinical features and treatment response in NMOSD patients in Egypt.

Author: Kishk NA, Abdelfattah W, Shalaby NM, Shehata HS, Hassan A, Hegazy MI, Abokrysha NT, Abdellatif D, Shawky SM, Abdo SS, Taha N, Fouad AM, Elmazny A, and Ragab AH
Subjects: Adolescent, Adult, Autoantigens immunology, Azathioprine therapeutic use, Egypt, Female, Humans, Immunologic Factors therapeutic use, Immunosuppressive Agents therapeutic use, Male, Middle Aged, Neuromyelitis Optica drug therapy, Retrospective Studies, Rituximab therapeutic use, Treatment Outcome, Young Adult, Aquaporin 4 immunology, Autoantibodies immunology, Neuromyelitis Optica immunology, Neuromyelitis Optica pathology
Abstract: Background: In Egypt, the characterization of Neuromyelitis Optica Spectrum Disorder (NMOSD) is lacking., Objectives: To determine the demographics, clinical features, aquaporin4 antibodies (AQP4-IgG) status, and neuroimaging of Egyptian NMOSD patients., Methods: Retrospective analysis of 70 NMOSD patients' records from the MS clinic, Kasr Alainy hospital, between January 2013 and June 2018., Results: Patients' mean age was 34.9 ± 9.2 years, and the mean at disease onset was 28.9 ± 10.5 years. Fifty-nine patients had an initial monosymptomatic presentation. AQP4-IgG was measured using either enzyme-linked immunosorbent assay (ELISA) (22 patients) or cell-based assay (CBA) (34 patients). Six and 29 patients had positive results, respectively (p < 0.001). 84% had typical NMOSD brain lesions. Longitudinally extensive myelitis was detected in 49 patients, and 9 had either short segments or normal cords. Treatment failure was higher in seropositive patients. Rituximab significantly reduced the annualized relapse rate (ARR) compared to Azathioprine with a percentage reduction of (76.47 ± 13.28) and (10.21 ± 96.07), respectively (p = 0.04). Age at disease onset was the only independent predictor for disability (p < 0.01)., Conclusion: Treatment failure was higher in seropositive patients. However, there was no difference in clinical or radiological parameters between seropositive and seronegative patients. Patients, who are polysymptomatic or with older age of onset, are predicted to have higher future disability regardless of the AQP4-IgG status.
Published: 2021
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27. Mapping 123 million neonatal, infant and child deaths between 2000 and 2017.

Author: Burstein R, Henry NJ, Collison ML, Marczak LB, Sligar A, Watson S, Marquez N, Abbasalizad-Farhangi M, Abbasi M, Abd-Allah F, Abdoli A, Abdollahi M, Abdollahpour I, Abdulkader RS, Abrigo MRM, Acharya D, Adebayo OM, Adekanmbi V, Adham D, Afshari M, Aghaali M, Ahmadi K, Ahmadi M, Ahmadpour E, Ahmed R, Akal CG, Akinyemi JO, Alahdab F, Alam N, Alamene GM, Alene KA, Alijanzadeh M, Alinia C, Alipour V, Aljunid SM, Almalki MJ, Al-Mekhlafi HM, Altirkawi K, Alvis-Guzman N, Amegah AK, Amini S, Amit AML, Anbari Z, Androudi S, Anjomshoa M, Ansari F, Antonio CAT, Arabloo J, Arefi Z, Aremu O, Armoon B, Arora A, Artaman A, Asadi A, Asadi-Aliabadi M, Ashraf-Ganjouei A, Assadi R, Ataeinia B, Atre SR, Quintanilla BPA, Ayanore MA, Azari S, Babaee E, Babazadeh A, Badawi A, Bagheri S, Bagherzadeh M, Baheiraei N, Balouchi A, Barac A, Bassat Q, Baune BT, Bayati M, Bedi N, Beghi E, Behzadifar M, Behzadifar M, Belay YB, Bell B, Bell ML, Berbada DA, Bernstein RS, Bhattacharjee NV, Bhattarai S, Bhutta ZA, Bijani A, Bohlouli S, Breitborde NJK, Britton G, Browne AJ, Nagaraja SB, Busse R, Butt ZA, Car J, Cárdenas R, Castañeda-Orjuela CA, Cerin E, Chanie WF, Chatterjee P, Chu DT, Cooper C, Costa VM, Dalal K, Dandona L, Dandona R, Daoud F, Daryani A, Das Gupta R, Davis I, Davis Weaver N, Davitoiu DV, De Neve JW, Demeke FM, Demoz GT, Deribe K, Desai R, Deshpande A, Desyibelew HD, Dey S, Dharmaratne SD, Dhimal M, Diaz D, Doshmangir L, Duraes AR, Dwyer-Lindgren L, Earl L, Ebrahimi R, Ebrahimpour S, Effiong A, Eftekhari A, Ehsani-Chimeh E, El Sayed I, El Sayed Zaki M, El Tantawi M, El-Khatib Z, Emamian MH, Enany S, Eskandarieh S, Eyawo O, Ezalarab M, Faramarzi M, Fareed M, Faridnia R, Faro A, Fazaeli AA, Fazlzadeh M, Fentahun N, Fereshtehnejad SM, Fernandes JC, Filip I, Fischer F, Foigt NA, Foroutan M, Francis JM, Fukumoto T, Fullman N, Gallus S, Gebre DG, Gebrehiwot TT, Gebremeskel GG, Gessner BD, Geta B, Gething PW, Ghadimi R, Ghadiri K, Ghajarzadeh M, Ghashghaee A, Gill PS, Gill TK, Golding N, Gomes NGM, Gona PN, Gopalani SV, Gorini G, Goulart BNG, Graetz N, Greaves F, Green MS, Guo Y, Haj-Mirzaian A, Haj-Mirzaian A, Hall BJ, Hamidi S, Haririan H, Haro JM, Hasankhani M, Hasanpoor E, Hasanzadeh A, Hassankhani H, Hassen HY, Hegazy MI, Hendrie D, Heydarpour F, Hird TR, Hoang CL, Hollerich G, Rad EH, Hoseini-Ghahfarokhi M, Hossain N, Hosseini M, Hosseinzadeh M, Hostiuc M, Hostiuc S, Househ M, Hsairi M, Ilesanmi OS, Imani-Nasab MH, Iqbal U, Irvani SSN, Islam N, Islam SMS, Jürisson M, Balalami NJ, Jalali A, Javidnia J, Jayatilleke AU, Jenabi E, Ji JS, Jobanputra YB, Johnson K, Jonas JB, Shushtari ZJ, Jozwiak JJ, Kabir A, Kahsay A, Kalani H, Kalhor R, Karami M, Karki S, Kasaeian A, Kassebaum NJ, Keiyoro PN, Kemp GR, Khabiri R, Khader YS, Khafaie MA, Khan EA, Khan J, Khan MS, Khang YH, Khatab K, Khater A, Khater MM, Khatony A, Khazaei M, Khazaei S, Khazaei-Pool M, Khubchandani J, Kianipour N, Kim YJ, Kimokoti RW, Kinyoki DK, Kisa A, Kisa S, Kolola T, Kosen S, Koul PA, Koyanagi A, Kraemer MUG, Krishan K, Krohn KJ, Kugbey N, Kumar GA, Kumar M, Kumar P, Kuupiel D, Lacey B, Lad SD, Lami FH, Larsson AO, Lee PH, Leili M, Levine AJ, Li S, Lim LL, Listl S, Longbottom J, Lopez JCF, Lorkowski S, Magdeldin S, Abd El Razek HM, Abd El Razek MM, Majeed A, Maleki A, Malekzadeh R, Malta DC, Mamun AA, Manafi N, Manda AL, Mansourian M, Martins-Melo FR, Masaka A, Massenburg BB, Maulik PK, Mayala BK, Mazidi M, McKee M, Mehrotra R, Mehta KM, Meles GG, Mendoza W, Menezes RG, Meretoja A, Meretoja TJ, Mestrovic T, Miller TR, Miller-Petrie MK, Mills EJ, Milne GJ, Mini GK, Mir SM, Mirjalali H, Mirrakhimov EM, Mohamadi E, Mohammad DK, Darwesh AM, Mezerji NMG, Mohammed AS, Mohammed S, Mokdad AH, Molokhia M, Monasta L, Moodley Y, Moosazadeh M, Moradi G, Moradi M, Moradi Y, Moradi-Lakeh M, Moradinazar M, Moraga P, Morawska L, Mosapour A, Mousavi SM, Mueller UO, Muluneh AG, Mustafa G, Nabavizadeh B, Naderi M, Nagarajan AJ, Nahvijou A, Najafi F, Nangia V, Ndwandwe DE, Neamati N, Negoi I, Negoi RI, Ngunjiri JW, Thi Nguyen HL, Nguyen LH, Nguyen SH, Nielsen KR, Ningrum DNA, Nirayo YL, Nixon MR, Nnaji CA, Nojomi M, Noroozi M, Nosratnejad S, Noubiap JJ, Motlagh SN, Ofori-Asenso R, Ogbo FA, Oladimeji KE, Olagunju AT, Olfatifar M, Olum S, Olusanya BO, Oluwasanu MM, Onwujekwe OE, Oren E, Ortega-Altamirano DDV, Ortiz A, Osarenotor O, Osei FB, Osgood-Zimmerman AE, Otstavnov SS, Owolabi MO, P A M, Pagheh AS, Pakhale S, Panda-Jonas S, Pandey A, Park EK, Parsian H, Pashaei T, Patel SK, Pepito VCF, Pereira A, Perkins S, Pickering BV, Pilgrim T, Pirestani M, Piroozi B, Pirsaheb M, Plana-Ripoll O, Pourjafar H, Puri P, Qorbani M, Quintana H, Rabiee M, Rabiee N, Radfar A, Rafiei A, Rahim F, Rahimi Z, Rahimi-Movaghar V, Rahimzadeh S, Rajati F, Raju SB, Ramezankhani A, Ranabhat CL, Rasella D, Rashedi V, Rawal L, Reiner RC Jr, Renzaho AMN, Rezaei S, Rezapour A, Riahi SM, Ribeiro AI, Roever L, Roro EM, Roser M, Roshandel G, Roshani D, Rostami A, Rubagotti E, Rubino S, Sabour S, Sadat N, Sadeghi E, Saeedi R, Safari Y, Safari-Faramani R, Safdarian M, Sahebkar A, Salahshoor MR, Salam N, Salamati P, Salehi F, Zahabi SS, Salimi Y, Salimzadeh H, Salomon JA, Sambala EZ, Samy AM, Santric Milicevic MM, Jose BPS, Saraswathy SYI, Sarmiento-Suárez R, Sartorius B, Sathian B, Saxena S, Sbarra AN, Schaeffer LE, Schwebel DC, Sepanlou SG, Seyedmousavi S, Shaahmadi F, Shaikh MA, Shams-Beyranvand M, Shamshirian A, Shamsizadeh M, Sharafi K, Sharif M, Sharif-Alhoseini M, Sharifi H, Sharma J, Sharma R, Sheikh A, Shields C, Shigematsu M, Shiri R, Shiue I, Shuval K, Siddiqi TJ, Silva JP, Singh JA, Sinha DN, Sisay MM, Sisay S, Sliwa K, Smith DL, Somayaji R, Soofi M, Soriano JB, Sreeramareddy CT, Sudaryanto A, Sufiyan MB, Sykes BL, Sylaja PN, Tabarés-Seisdedos R, Tabb KM, Tabuchi T, Taveira N, Temsah MH, Terkawi AS, Tessema ZT, Thankappan KR, Thirunavukkarasu S, To QG, Tovani-Palone MR, Tran BX, Tran KB, Ullah I, Usman MS, Uthman OA, Vahedian-Azimi A, Valdez PR, van Boven JFM, Vasankari TJ, Vasseghian Y, Veisani Y, Venketasubramanian N, Violante FS, Vladimirov SK, Vlassov V, Vos T, Vu GT, Vujcic IS, Waheed Y, Wakefield J, Wang H, Wang Y, Wang YP, Ward JL, Weintraub RG, Weldegwergs KG, Weldesamuel GT, Westerman R, Wiysonge CS, Wondafrash DZ, Woyczynski L, Wu AM, Xu G, Yadegar A, Yamada T, Yazdi-Feyzabadi V, Yilgwan CS, Yip P, Yonemoto N, Lebni JY, Younis MZ, Yousefifard M, Yousof HSA, Yu C, Yusefzadeh H, Zabeh E, Moghadam TZ, Bin Zaman S, Zamani M, Zandian H, Zangeneh A, Zerfu TA, Zhang Y, Ziapour A, Zodpey S, Murray CJL, and Hay SI
Subjects: Child, Geography, Global Health, Humans, Infant, Infant, Newborn, Organizational Objectives, Public Health, Socioeconomic Factors, United Nations, Child Mortality trends, Infant Mortality trends
Abstract: Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.
Published: 2019
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28. The combined effect of IL-17F and CCL20 gene polymorphism in susceptibility to multiple sclerosis in Egypt.

Author: El Sharkawi FZ, Ali SA, Hegazy MI, and Atya HB
Subjects: Alleles, Case-Control Studies, Chemokine CCL20 blood, Egypt, Female, Genotype, Humans, Interleukin-17 blood, Male, Odds Ratio, Chemokine CCL20 genetics, Genetic Association Studies, Genetic Predisposition to Disease, Interleukin-17 genetics, Multiple Sclerosis genetics, Polymorphism, Single Nucleotide
Abstract: Background: Levels of CCL20 and its CCR6 receptor are elevated in many autoimmune diseases which help in the recruitment of T helper (Th17) cells to site of inflammation., Objectives: Determine the value of single nucleotide polymorphism of CCL20 (rs6749704) and IL-17F (rs763780) genes and their concomitant effect on the serum CCL20 level and susceptibility to MS in Egyptian patients., Subjects and Methods: Blood samples were collected from 83 patients and 95 healthy subjects. Serum levels of CCL20 were measured by ELISA. The DNA was analyzed for rs6749704 and rs763780 using Genotyping Taqman assay., Results: The mean serum levels of CCL20 in the MS group were significantly higher than healthy group (P < 0.001). Frequencies of CT genotype of rs6749704 in CCL20 gene and C allele in MS patients were significantly higher compared to controls. Also significant increase of rs763780 in IL-17F gene was detected in MS patients. Concomitant polymorphism in both genes in MS patients showed an increase risk to MS rather than individual locus., Conclusion: CCL20 may play an important role in the pathogenesis of MS. Both allelic variation of (rs6749704) within CCL20 gene and (rs763780) within IL-17F gene can be considered risk factor for development of MS in Egyptian patients., (Copyright © 2018 Elsevier B.V. All rights reserved.)
Published: 2019
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29. Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016.

Author: Feigin VL, Nguyen G, Cercy K, Johnson CO, Alam T, Parmar PG, Abajobir AA, Abate KH, Abd-Allah F, Abejie AN, Abyu GY, Ademi Z, Agarwal G, Ahmed MB, Akinyemi RO, Al-Raddadi R, Aminde LN, Amlie-Lefond C, Ansari H, Asayesh H, Asgedom SW, Atey TM, Ayele HT, Banach M, Banerjee A, Barac A, Barker-Collo SL, Bärnighausen T, Barregard L, Basu S, Bedi N, Behzadifar M, Béjot Y, Bennett DA, Bensenor IM, Berhe DF, Boneya DJ, Brainin M, Campos-Nonato IR, Caso V, Castañeda-Orjuela CA, Rivas JC, Catalá-López F, Christensen H, Criqui MH, Damasceno A, Dandona L, Dandona R, Davletov K, de Courten B, deVeber G, Dokova K, Edessa D, Endres M, Faraon EJA, Farvid MS, Fischer F, Foreman K, Forouzanfar MH, Gall SL, Gebrehiwot TT, Geleijnse JM, Gillum RF, Giroud M, Goulart AC, Gupta R, Gupta R, Hachinski V, Hamadeh RR, Hankey GJ, Hareri HA, Havmoeller R, Hay SI, Hegazy MI, Hibstu DT, James SL, Jeemon P, John D, Jonas JB, Jóźwiak J, Kalani R, Kandel A, Kasaeian A, Kengne AP, Khader YS, Khan AR, Khang YH, Khubchandani J, Kim D, Kim YJ, Kivimaki M, Kokubo Y, Kolte D, Kopec JA, Kosen S, Kravchenko M, Krishnamurthi R, Kumar GA, Lafranconi A, Lavados PM, Legesse Y, Li Y, Liang X, Lo WD, Lorkowski S, Lotufo PA, Loy CT, Mackay MT, Abd El Razek HM, Mahdavi M, Majeed A, Malekzadeh R, Malta DC, Mamun AA, Mantovani LG, Martins SCO, Mate KK, Mazidi M, Mehata S, Meier T, Melaku YA, Mendoza W, Mensah GA, Meretoja A, Mezgebe HB, Miazgowski T, Miller TR, Ibrahim NM, Mohammed S, Mokdad AH, Moosazadeh M, Moran AE, Musa KI, Negoi RI, Nguyen M, Nguyen QL, Nguyen TH, Tran TT, Nguyen TT, Anggraini Ningrum DN, Norrving B, Noubiap JJ, O’Donnell MJ, Olagunju AT, Onuma OK, Owolabi MO, Parsaeian M, Patton GC, Piradov M, Pletcher MA, Pourmalek F, Prakash V, Qorbani M, Rahman M, Rahman MA, Rai RK, Ranta A, Rawaf D, Rawaf S, Renzaho AM, Robinson SR, Sahathevan R, Sahebkar A, Salomon JA, Santalucia P, Santos IS, Sartorius B, Schutte AE, Sepanlou SG, Shafieesabet A, Shaikh MA, Shamsizadeh M, Sheth KN, Sisay M, Shin MJ, Shiue I, Silva DAS, Sobngwi E, Soljak M, Sorensen RJD, Sposato LA, Stranges S, Suliankatchi RA, Tabarés-Seisdedos R, Tanne D, Nguyen CT, Thakur JS, Thrift AG, Tirschwell DL, Topor-Madry R, Tran BX, Nguyen LT, Truelsen T, Tsilimparis N, Tyrovolas S, Ukwaja KN, Uthman OA, Varakin Y, Vasankari T, Venketasubramanian N, Vlassov VV, Wang W, Werdecker A, Wolfe CDA, Xu G, Yano Y, Yonemoto N, Yu C, Zaidi Z, El Sayed Zaki M, Zhou M, Ziaeian B, Zipkin B, Vos T, Naghavi M, Murray CJL, and Roth GA
Subjects: Adult, Age Distribution, Aged, Aged, 80 and over, Cause of Death, Female, Global Burden of Disease, Global Health, Humans, Incidence, Male, Middle Aged, Risk, Sex Distribution, Socioeconomic Factors, Stroke epidemiology
Abstract: Background: The lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases., Methods: We used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate., Results: The estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation., Conclusions: In 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.).
Published: 2018
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30. Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients.

Author: Atya HB, Ali SA, Hegazy MI, and El Sharkawi FZ
Abstract: Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS). The objective was to investigate the level of some urinary metabolites (urea, uric acid and hippuric acid) in patients with MS and correlate their levels to the severity of the disease, MS subtypes and MS treatment. The urine samples were collected from 73 MS patients-48 with RRMS and 25 with SPMS- and age matched 75 healthy controls. The values of urinary urea, uric acid and hippuric acid in MS patients were significantly decreased, and these metabolites in SPMS pattern showed significantly decrease than RRMS pattern. Also showed significant inverse correlation with expanded disability status scale and number of relapses. Accordingly, they may act as a potential urinary biomarkers for MS, and correlate to disease progression., Competing Interests: Compliance with Ethical StandardsThe authors declare that they have no conflict of interests related to the publication of this paper.
Published: 2018
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31. Prediction of Functional Outcome in Ischemic Stroke Patients: An Observational Study on Egyptian Population.

Author: Mahmoud Fouad M, Mohamed Farag S, Hegazy MI, and Abd Elalem Aziz M
Abstract: Introduction Determining the prognosis of ischemic stroke is important for neurologists and patients. The aim is to study the predictors of three months clinical outcome in ischemic stroke patients. Materials and methods A total of 397 patients were classified according to three months modified Rankin Scale score (mRS score) into two groups, favorable and unfavorable outcome. Favorable outcome was assumed if the score was zero or one, or unchanged if the score was ≥ 1 before the onset of the most recent event. Results The variables associated with unfavorable outcome were old age ( P <0.001), presence of cardiac disease ( P <0.001), low ejection fraction ( P =0.008), low levels of total cholesterol and low-density lipoproteins ( P <0.001), large artery atherosclerosis stroke ( P <0.001), early confluent ( P =0.005), high National Institute of Health stroke scale (NIHSS) score on admission ( P <0.001), mRS score before admission ( P <0.001), mRS score on discharge ( P <0.001). Lacunar stroke was associated with favorable outcome ( P <0.001). The regression analysis showed mRS score on discharge ( P <0.001) and the presence of cardiac diseases ( P =0.077) as independent predictors of unfavorable outcome. Conclusion High mRS score on discharge and presence of the cardiac disease independently could predict the unfavorable outcome and mRS score on discharge had a high sensitivity and negative predictive value in predicting the unfavorable outcome. Abbreviations MRS: score modified Rankin scale score, NIHSS: National Institutes of Health Stroke Scale, MRI: Magnetic resonance imaging, LDL: Low-density lipoprotein, MRA: Magnetic resonance of arteries., Competing Interests: The authors have declared that no competing interests exist.
Published: 2017
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32. Evaluation of local varieties of Egyptian rice.

Author: Awadalla MZ, Mekhael KG, and Hegazy MI
Subjects: Amino Acids analysis, Amino Acids, Essential analysis, Egypt, Food Handling, Minerals analysis, Nutritive Value, Species Specificity, Oryza analysis, Plant Proteins analysis
Abstract: The different nutritional ingredients of the Egyptian varieties of rice (Giza 171, Giza 172, and Giza 180) were determined. 1. The nutritive values decreased in polished varieties more than in the hulled ones. 2. A wide variation in the protein content in the different varieties was recognized. 3. Giza 180 could be considered as the best Egyptian variety from the nutritional aspects.
Published: 1981
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33. Metabolism of vicine and convicine in rat tissues: absorption and excretion patterns and sites of hydrolysis.

Author: Hegazy MI and Marquardt RR
Subjects: Animals, Hydrolysis, Intestinal Absorption, Male, Rats, Rats, Inbred Strains, Uracil metabolism, Glucosides metabolism, Glycosides metabolism, Pyrimidinones metabolism, Uracil analogs & derivatives, Uridine analogs & derivatives
Published: 1984
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33 results on '"Hegazy MI"'

1. Sensitivity and Specificity of Central Vein Sign as a Diagnostic Biomarker in Egyptian Patients with Multiple Sclerosis

2. Management Strategies of Patients with Neuromyelitis Optica Spectrum Disorder During the COVID-19 Pandemic Era

3. Managing Disease-Modifying Therapies and Breakthrough Activity in Multiple Sclerosis Patients During the COVID-19 Pandemic: Toward an Optimized Approach

4. Interferon-Beta-Induced Headache in Patients with Multiple Sclerosis: Frequency and Characterization

5. Pediatric-onset multiple sclerosis in Egypt: a multi-center registry of 186 patients

6. Characteristics and predictors of progression in an Egyptian multiple sclerosis cohort: a multicenter registry study

7. Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

8. Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000-2018

9. Neurological Manifestations in a Cohort of Egyptian Patients with COVID-19: A Prospective, Multicenter, Observational Study

10. Global and regional burden of disease and injury in 2016 arising from occupational exposures: a systematic analysis for the Global Burden of Disease Study 2016

11. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

12. Global and regional burden of cancer in 2016 arising from occupational exposure to selected carcinogens: a systematic analysis for the Global Burden of Disease Study 2016

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

14. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

15. Global, regional, and national burden of Parkinson's disease, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

16. 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

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

18. 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

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

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

21. New algorithmic approach for easier and faster extended disability status scale calculation.

22. ٍSome biologically active microorganisms have the potential to suppress mosquito larvae ( Culex pipiens , Diptera: Culicidae).

23. Neurological Manifestations in a Cohort of Egyptian Patients with COVID-19: A Prospective, Multicenter, Observational Study.

24. Impact of Ramadan fasting on disease activity in patients with multiple sclerosis: a multicenter study.

25. Rainwater-driven microbial fuel cells for power generation in remote areas.

26. The aquaporin4-IgG status and how it affects the clinical features and treatment response in NMOSD patients in Egypt.

27. Mapping 123 million neonatal, infant and child deaths between 2000 and 2017.

28. The combined effect of IL-17F and CCL20 gene polymorphism in susceptibility to multiple sclerosis in Egypt.

29. Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016.

30. Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients.

31. Prediction of Functional Outcome in Ischemic Stroke Patients: An Observational Study on Egyptian Population.

32. Evaluation of local varieties of Egyptian rice.

33. Metabolism of vicine and convicine in rat tissues: absorption and excretion patterns and sites of hydrolysis.

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