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1. Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017

Author: James, SL, Castle, CD, Dingels, ZV, Fox, JT, Hamilton, EB, Liu, Z, S Roberts, NL, Sylte, DO, Henry, NJ, LeGrand, KE, Abdelalim, A, Abdoli, A, Abdollahpour, I, Abdulkader, RS, Abedi, A, Abosetugn, AE, Abushouk, AI, Adebayo, OM, Agudelo-Botero, M, Ahmad, T, Ahmed, R, Ahmed, MB, Eddine Aichour, MT, Alahdab, F, Alamene, GM, Alanezi, FM, Alebel, A, Alema, NM, Alghnam, SA, Al-Hajj, S, Ali, BA, Ali, S, Alikhani, M, Alinia, C, Alipour, V, Aljunid, SM, Almasi-Hashiani, A, Almasri, NA, Altirkawi, K, Abdeldayem Amer, YS, Amini, S, Loreche Amit, AM, Andrei, CL, Ansari-Moghaddam, A, T Antonio, CA, Yaw Appiah, SC, Arabloo, J, Arab-Zozani, M, Arefi, Z, Aremu, O, Ariani, F, Arora, A, Asaad, M, Asghari, B, Awoke, N, Ayala Quintanilla, BP, Ayano, G, Ayanore, MA, Azari, S, Azarian, G, Badawi, A, Badiye, AD, Bagli, E, Baig, AA, Bairwa, M, Bakhtiari, A, Balachandran, A, Banach, M, Banerjee, SK, Banik, PC, Banstola, A, Barker-Collo, SL, Bärnighausen, TW, Barrero, LH, Barzegar, A, Bayati, M, Baye, BA, Bedi, N, Behzadifar, M, Bekuma, TT, Belete, H, Benjet, C, Bennett, DA, Bensenor, IM, Berhe, K, Bhardwaj, P, Bhat, AG, Bhattacharyya, K, Bibi, S, Bijani, A, Bin Sayeed, MS, Borges, G, Borzì, AM, Boufous, S, Brazinova, A, Briko, NI, Budhathoki, SS, Car, J, Cárdenas, R, Carvalho, F, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Cerin, E, Chandan, JS, Chanie, WF, Chattu, SK, Chattu, VK, Chatziralli, I, Chaudhary, N, Cho, DY, Kabir Chowdhury, MA, Chu, D-T, Colquhoun, SM, Constantin, M-M, Costa, VM, Damiani, G, Daryani, A, Dávila-Cervantes, CA, Demeke, FM, Demis, AB, Demoz, GT, Demsie, DG, Derakhshani, A, Deribe, K, Desai, R, Nasab, MD, da Silva, DD, Dibaji Forooshani, ZS, Doyle, KE, Driscoll, TR, Dubljanin, E, Adema, BD, Eagan, AW, Eftekhari, A, Ehsani-Chimeh, E, Sayed Zaki, ME, Elemineh, DA, El-Jaafary, SI, El-Khatib, Z, Ellingsen, CL, Emamian, MH, Endalew, DA, Eskandarieh, S, Faris, PS, Faro, A, Farzadfar, F, Fatahi, Y, Fekadu, W, Ferede, TY, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Feyissa, GT, Filip, I, Fischer, F, Folayan, MO, Foroutan, M, Francis, JM, Franklin, RC, Fukumoto, T, Geberemariyam, BS, Gebre, AK, Gebremedhin, KB, Gebremeskel, GG, Gebremichael, B, Gedefaw, GA, Geta, B, Ghafourifard, M, Ghamari, F, Ghashghaee, A, Gholamian, A, Gill, TK, Goulart, AC, Grada, A, Grivna, M, Mohialdeen Gubari, MI, Guimarães, RA, Guo, Y, Gupta, G, Haagsma, JA, Hafezi-Nejad, N, Bidgoli, HH, Hall, BJ, Hamadeh, RR, Hamidi, S, Haro, JM, Hasan, MM, Hasanzadeh, A, Hassanipour, S, Hassankhani, H, Hassen, HY, Havmoeller, R, Hayat, K, Hendrie, D, Heydarpour, F, Híjar, M, Ho, HC, Hoang, CL, Hole, MK, Holla, R, Hossain, N, Hosseinzadeh, M, Hostiuc, S, Hu, G, Ibitoye, SE, Ilesanmi, OS, Ilic, I, Ilic, MD, Inbaraj, LR, Indriasih, E, Naghibi Irvani, SS, Shariful Islam, SM, Islam, MM, Ivers, RQ, Jacobsen, KH, Jahani, MA, Jahanmehr, N, Jakovljevic, M, Jalilian, F, Jayaraman, S, Jayatilleke, AU, Jha, RP, John-Akinola, YO, Jonas, JB, Joseph, N, Joukar, F, Jozwiak, JJ, Jungari, SB, Jürisson, M, Kabir, A, Kadel, R, Kahsay, A, Kalankesh, LR, Kalhor, R, Kamil, TA, Kanchan, T, Kapoor, N, Karami, M, Kasaeian, A, Kassaye, HG, Kavetskyy, T, Kebede, HK, Keiyoro, PN, Kelbore, AG, Kelkay, B, Khader, YS, Khafaie, MA, Khalid, N, Khalil, IA, Khalilov, R, Khammarnia, M, Khan, EA, Khan, M, Khanna, T, Khazaie, H, Shadmani, FK, Khundkar, R, Kiirithio, DN, Kim, Y-E, Kim, D, Kim, YJ, Kisa, A, Kisa, S, Komaki, H, M Kondlahalli, SK, Korshunov, VA, Koyanagi, A, G Kraemer, MU, Krishan, K, Bicer, BK, Kugbey, N, Kumar, V, Kumar, N, Kumar, GA, Kumar, M, Kumaresh, G, Kurmi, OP, Kuti, O, Vecchia, CL, Lami, FH, Lamichhane, P, Lang, JJ, Lansingh, VC, Laryea, DO, Lasrado, S, Latifi, A, Lauriola, P, Leasher, JL, Huey Lee, SW, Lenjebo, TL, Levi, M, Li, S, Linn, S, Liu, X, Lopez, AD, Lotufo, PA, Lunevicius, R, Lyons, RA, Madadin, M, El Razek, MMA, Mahotra, NB, Majdan, M, Majeed, A, Malagon-Rojas, JN, Maled, V, Malekzadeh, R, Malta, DC, Manafi, N, Manafi, A, Manda, A-L, Manjunatha, N, Mansour-Ghanaei, F, Mansouri, B, Mansournia, MA, Maravilla, JC, March, LM, Mason-Jones, AJ, Masoumi, SZ, Massenburg, BB, Maulik, PK, Meles, GG, Melese, A, Melketsedik, ZA, N Memiah, PT, Mendoza, W, Menezes, RG, Mengesha, MB, Mengesha, MM, Meretoja, TJ, Meretoja, A, Merie, HE, Mestrovic, T, Miazgowski, B, Miazgowski, T, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Mirzaei-Alavijeh, M, Mithra, P, Moazen, B, Moghadaszadeh, M, Mohamadi, E, Mohammad, Y, Mohammad, KA, Darwesh, AM, Gholi Mezerji, NM, Mohammadian-Hafshejani, A, Mohammadoo-Khorasani, M, Mohammadpourhodki, R, Mohammed, S, Mohammed, JA, Mohebi, F, Molokhia, M, Monasta, L, Moodley, Y, Moosazadeh, M, Moradi, M, Moradi, G, Moradi-Lakeh, M, Moradpour, F, Morawska, L, Velásquez, IM, Morisaki, N, Morrison, SD, Mossie, TB, Muluneh, AG, Murthy, S, Musa, KI, Mustafa, G, Nabhan, AF, Nagarajan, AJ, Naik, G, Naimzada, MD, Najafi, F, Nangia, V, Nascimento, BR, Naserbakht, M, Nayak, V, Ndwandwe, DE, Negoi, I, Ngunjiri, JW, Nguyen, CT, Thi Nguyen, HL, Nikbakhsh, R, Anggraini Ningrum, DN, Nnaji, CA, Nyasulu, PS, Ogbo, FA, Oghenetega, OB, Oh, I-H, Okunga, EW, Olagunju, AT, Olagunju, TO, Bali, AO, Onwujekwe, OE, Asante, KO, Orpana, HM, Ota, E, Otstavnov, N, Otstavnov, SS, A, MP, Padubidri, JR, Pakhale, S, Pakshir, K, Panda-Jonas, S, Park, E-K, Patel, SK, Pathak, A, Pati, S, Patton, GC, Paulos, K, Peden, AE, Filipino Pepito, VC, Pereira, J, Pham, HQ, Phillips, MR, Pinheiro, M, Polibin, RV, Polinder, S, Poustchi, H, Prakash, S, Angga Pribadi, DR, Puri, P, Syed, ZQ, Rabiee, M, Rabiee, N, Radfar, A, Rafay, A, Rafiee, A, Rafiei, A, Rahim, F, Rahimi, S, Rahimi-Movaghar, V, Rahman, MA, Rajabpour-Sanati, A, Rajati, F, Rakovac, I, Ranganathan, K, Rao, SJ, Rashedi, V, Rastogi, P, Rathi, P, Rawaf, S, Rawal, L, Rawassizadeh, R, Renjith, V, N Renzaho, AM, Resnikoff, S, Rezapour, A, Ribeiro, AI, Rickard, J, Rios González, CM, Ronfani, L, Roshandel, G, Saad, AM, Sabde, YD, Sabour, S, Saddik, B, Safari, S, Safari-Faramani, R, Safarpour, H, Safdarian, M, Sajadi, SM, Salamati, P, Salehi, F, Zahabi, SS, Rashad Salem, MR, Salem, H, Salman, O, Salz, I, Samy, AM, Sanabria, J, Riera, LS, Santric Milicevic, MM, Sarker, AR, Sarveazad, A, Sathian, B, Sawhney, M, Sawyer, SM, Saxena, S, Sayyah, M, Schwebel, DC, Seedat, S, Senthilkumaran, S, Sepanlou, SG, Seyedmousavi, S, Sha, F, Shaahmadi, F, Shahabi, S, Shaikh, MA, Shams-Beyranvand, M, Shamsizadeh, M, Sharif-Alhoseini, M, Sharifi, H, Sheikh, A, Shigematsu, M, Shin, JI, Shiri, R, Siabani, S, Sigfusdottir, ID, Singh, PK, Singh, JA, Sinha, DN, Smarandache, C-G, R Smith, EU, Soheili, A, Soleymani, B, Soltanian, AR, Soriano, JB, Sorrie, MB, Soyiri, IN, Stein, DJ, Stokes, MA, Sufiyan, MB, Rasul Suleria, HA, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taddele, BW, Tadesse, DB, Tamiru, AT, Tarigan, IU, Tefera, YM, Tehrani-Banihashemi, A, Tekle, MG, Tekulu, GH, Tesema, AK, Tesfay, BE, Thapar, R, Tilahune, AB, Tlaye, KG, Tohidinik, HR, Topor-Madry, R, Tran, BX, Tran, KB, Tripathy, JP, Tsai, AC, Car, LT, Ullah, S, Ullah, I, Umar, M, Unnikrishnan, B, Upadhyay, E, Uthman, OA, Valdez, PR, Vasankari, TJ, Venketasubramanian, N, Violante, FS, Vlassov, V, Waheed, Y, Weldesamuel, GT, Werdecker, A, Wiangkham, T, Wolde, HF, Woldeyes, DH, Wondafrash, DZ, Wondmeneh, TG, Wondmieneh, AB, Wu, A-M, Yadav, R, Yadollahpour, A, Yano, Y, Yaya, S, Yazdi-Feyzabadi, V, Yip, P, Yisma, E, Yonemoto, N, Yoon, S-J, Youm, Y, Younis, MZ, Yousefi, Z, Yu, Y, Yu, C, Yusefzadeh, H, Moghadam, TZ, Zaidi, Z, Zaman, SB, Zamani, M, Zamanian, M, Zandian, H, Zarei, A, Zare, F, Zhang, Z-J, Zhang, Y, Zodpey, S, Dandona, L, Dandona, R, Degenhardt, L, Dharmaratne, SD, Hay, SI, Mokdad, AH, Reiner, RC, Sartorius, B, and Vos, T
Subjects: Life Expectancy, Incidence, burden of disease, descriptive epidemiology, global, Humans, Wounds and Injuries, Public Health, Quality-Adjusted Life Years, Morbidity, Global Health, 1106 Human Movement and Sports Sciences, 1117 Public Health and Health Services, 1701 Psychology, Global Burden of Disease
Abstract: BACKGROUND: Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries.; METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).; FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100000. In 1990, there were 354064302 (95% uncertainty interval: 338174876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100000 to 3267 (3058 to 3505).; INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.
Published: 2020

2. Burden of injury along the development spectrum: associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017

Author: Haagsma, JA, James, SL, Castle, CD, Dingels, Z, Fox, JT, Hamilton, EB, Liu, Z, Lucchesi, LR, Roberts, NLS, Sylte, DO, Adebayo, OM, Ahmadi, A, Ahmed, MB, Aichour, MTE, Alahdab, F, Alghnam, SA, Aljunid, SM, Al-Raddadi, RM, Alsharif, U, Altirkawi, K, Anjomshoa, M, Antonio, CAT, Appiah, SCY, Aremu, O, Arora, A, Asayesh, H, Assadi, R, Awasthi, A, Ayala Quintanilla, BP, Balalla, S, Banstola, A, Barker-Collo, SL, Baernighausen, TW, Bazargan-Hejazi, S, Bedi, N, Behzadifar, M, Benjet, C, Bennett, DA, Bensenor, IM, Bhaumik, S, Bhutta, ZA, Bijani, A, Borges, G, Borschmann, R, Bose, D, Boufous, S, Brazinova, A, Rincon, JCC, Cardenas, R, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Catala-Lopez, F, Choi, J-YJ, Christopher, DJ, Crowe, CS, Dalal, K, Daryani, A, Davitoiu, DV, Degenhardt, L, De Leo, D, De Neve, J-W, Deribe, K, Dessie, GA, deVeber, GA, Dharmaratne, SD, Linh, PD, Dolan, KA, Driscoll, TR, Dubey, M, El-Khatib, Z, Ellingsen, CL, Zaki, MES, Endries, AY, Eskandarieh, S, Faro, A, Fereshtehnejad, S-M, Fernandes, E, Filip, I, Fischer, F, Franklin, RC, Fukumoto, T, Gezae, KE, Gill, TK, Goulart, AC, Grada, A, Guo, Y, Gupta, R, Bidgoli, HH, Haj-Mirzaian, A, Hamadeh, RR, Hamidi, S, Maria Haro, J, Hassankhani, H, Hassen, HY, Havmoeller, R, Hendrie, D, Henok, A, Hijar, M, Hole, MK, Rad, EH, Hossain, N, Hostiuc, S, Hu, G, Igumbor, EU, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Ivers, RQ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, M, Jayatilleke, AU, Jha, RP, Jonas, JB, Shushtari, ZJ, Jozwiak, JJ, Jurisson, M, Kabir, A, Kalani, R, Kasaeian, A, Kelbore, AG, Kengne, AP, Khader, YS, Khafaie, MA, Khalid, N, Khan, EA, Khoja, AT, Kiadaliri, AA, Kim, Y-E, Kim, D, Kisa, A, Koyanagi, A, Defo, BK, Bicer, BK, Kumar, M, Lalloo, R, Lam, H, Lami, FH, Lansingh, VC, Leasher, JL, Li, S, Linn, S, Lunevicius, R, Machado, FR, Abd El Razek, HM, Abd El Razek, MM, Mahotra, NB, Majdan, M, Majeed, A, Malekzadeh, R, Malik, MA, Malta, DC, Manda, A-L, Mansournia, MA, Massenburg, BB, Maulik, PK, Meheretu, HAA, Mehndiratta, MM, Melese, A, Mendoza, W, Mengesha, MM, Meretoja, TJ, Meretoja, A, Mestrovic, T, Miazgowski, T, Miller, TR, Mini, GK, Mirrakhimov, EM, Moazen, B, Mezerji, NMG, Mohammadibakhsh, R, Mohammed, S, Molokhia, M, Monasta, L, Mondello, S, Montero-Zamora, PA, Moodley, Y, Moosazadeh, M, Moradi, G, Moradi-Lakeh, M, Morawska, L, Moreno Velasquez, I, Morrison, SD, Moschos, MM, Mousavi, SM, Murthy, S, Musa, KI, Naik, G, Najafi, F, Nangia, V, Nascimento, BR, Ndwandwe, DE, Negoi, I, Trang, HN, Son, HN, Long, HN, Huong, LTN, Ningrum, DNA, Nirayo, YL, Ofori-Asenso, R, Ogbo, FA, Oh, I-H, Oladimeji, O, Olagunju, AT, Olagunju, TO, Olivares, PR, Orpana, HM, Otstavnov, SS, Mahesh, PA, Pakhale, S, Park, E-K, Patton, GC, Pesudovs, K, Phillips, MR, Polinder, S, Prakash, S, Radfar, A, Rafay, A, Rafiei, A, Rahimi, S, Rahimi-Movaghar, V, Rahman, MA, Rai, RK, Ramezanzadeh, K, Rawaf, S, Rawaf, DL, Renzaho, AMN, Resnikoff, S, Rezaeian, S, Roever, L, Ronfani, L, Roshandel, G, Sabde, YD, Saddik, B, Salamati, P, Salimi, Y, Salz, I, Samy, AM, Sanabria, J, Riera, LS, Milicevic, MMS, Satpathy, M, Sawhney, M, Sawyer, SM, Saxena, S, Saylan, M, Schneider, IJC, Schwebel, DC, Seedat, S, Sepanlou, SG, Shaikh, MA, Shams-Beyranvand, M, Shamsizadeh, M, Sharif-Alhoseini, M, Sheikh, A, Shen, J, Shigematsu, M, Shiri, R, Shiue, I, Silva, JP, Singh, JA, Sinha, DN, Soares Filho, AM, Soriano, JB, Soshnikov, S, Soyiri, IN, Starodubov, V, Stein, DJ, Stokes, MA, Sufiyan, MB, Sunshine, JE, Sykes, BL, Tabares-Seisdedos, R, Tabb, KM, Tehrani-Banihashemi, A, Tessema, GA, Thakur, JS, Khanh, BT, Bach, XT, Car, LT, Uthman, OA, Uzochukwu, BSC, Valdez, PR, Varavikova, E, Nogales Vasconcelos, AM, Venketasubramanian, N, Violante, FS, Vlassov, V, Waheed, Y, Wang, Y-P, Wijeratne, T, Winkler, AS, Yadav, P, Yano, Y, Yenesew, MA, Yip, P, Yisma, E, Yonemoto, N, Younis, MZ, Yu, C, Zafar, S, Zaidi, Z, Bin Zaman, S, Zamani, M, Zhao, Y, Zodpey, S, Hay, S, Lopez, AD, Mokdad, AH, Vos, T, Haagsma, JA, James, SL, Castle, CD, Dingels, Z, Fox, JT, Hamilton, EB, Liu, Z, Lucchesi, LR, Roberts, NLS, Sylte, DO, Adebayo, OM, Ahmadi, A, Ahmed, MB, Aichour, MTE, Alahdab, F, Alghnam, SA, Aljunid, SM, Al-Raddadi, RM, Alsharif, U, Altirkawi, K, Anjomshoa, M, Antonio, CAT, Appiah, SCY, Aremu, O, Arora, A, Asayesh, H, Assadi, R, Awasthi, A, Ayala Quintanilla, BP, Balalla, S, Banstola, A, Barker-Collo, SL, Baernighausen, TW, Bazargan-Hejazi, S, Bedi, N, Behzadifar, M, Benjet, C, Bennett, DA, Bensenor, IM, Bhaumik, S, Bhutta, ZA, Bijani, A, Borges, G, Borschmann, R, Bose, D, Boufous, S, Brazinova, A, Rincon, JCC, Cardenas, R, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Catala-Lopez, F, Choi, J-YJ, Christopher, DJ, Crowe, CS, Dalal, K, Daryani, A, Davitoiu, DV, Degenhardt, L, De Leo, D, De Neve, J-W, Deribe, K, Dessie, GA, deVeber, GA, Dharmaratne, SD, Linh, PD, Dolan, KA, Driscoll, TR, Dubey, M, El-Khatib, Z, Ellingsen, CL, Zaki, MES, Endries, AY, Eskandarieh, S, Faro, A, Fereshtehnejad, S-M, Fernandes, E, Filip, I, Fischer, F, Franklin, RC, Fukumoto, T, Gezae, KE, Gill, TK, Goulart, AC, Grada, A, Guo, Y, Gupta, R, Bidgoli, HH, Haj-Mirzaian, A, Hamadeh, RR, Hamidi, S, Maria Haro, J, Hassankhani, H, Hassen, HY, Havmoeller, R, Hendrie, D, Henok, A, Hijar, M, Hole, MK, Rad, EH, Hossain, N, Hostiuc, S, Hu, G, Igumbor, EU, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Ivers, RQ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, M, Jayatilleke, AU, Jha, RP, Jonas, JB, Shushtari, ZJ, Jozwiak, JJ, Jurisson, M, Kabir, A, Kalani, R, Kasaeian, A, Kelbore, AG, Kengne, AP, Khader, YS, Khafaie, MA, Khalid, N, Khan, EA, Khoja, AT, Kiadaliri, AA, Kim, Y-E, Kim, D, Kisa, A, Koyanagi, A, Defo, BK, Bicer, BK, Kumar, M, Lalloo, R, Lam, H, Lami, FH, Lansingh, VC, Leasher, JL, Li, S, Linn, S, Lunevicius, R, Machado, FR, Abd El Razek, HM, Abd El Razek, MM, Mahotra, NB, Majdan, M, Majeed, A, Malekzadeh, R, Malik, MA, Malta, DC, Manda, A-L, Mansournia, MA, Massenburg, BB, Maulik, PK, Meheretu, HAA, Mehndiratta, MM, Melese, A, Mendoza, W, Mengesha, MM, Meretoja, TJ, Meretoja, A, Mestrovic, T, Miazgowski, T, Miller, TR, Mini, GK, Mirrakhimov, EM, Moazen, B, Mezerji, NMG, Mohammadibakhsh, R, Mohammed, S, Molokhia, M, Monasta, L, Mondello, S, Montero-Zamora, PA, Moodley, Y, Moosazadeh, M, Moradi, G, Moradi-Lakeh, M, Morawska, L, Moreno Velasquez, I, Morrison, SD, Moschos, MM, Mousavi, SM, Murthy, S, Musa, KI, Naik, G, Najafi, F, Nangia, V, Nascimento, BR, Ndwandwe, DE, Negoi, I, Trang, HN, Son, HN, Long, HN, Huong, LTN, Ningrum, DNA, Nirayo, YL, Ofori-Asenso, R, Ogbo, FA, Oh, I-H, Oladimeji, O, Olagunju, AT, Olagunju, TO, Olivares, PR, Orpana, HM, Otstavnov, SS, Mahesh, PA, Pakhale, S, Park, E-K, Patton, GC, Pesudovs, K, Phillips, MR, Polinder, S, Prakash, S, Radfar, A, Rafay, A, Rafiei, A, Rahimi, S, Rahimi-Movaghar, V, Rahman, MA, Rai, RK, Ramezanzadeh, K, Rawaf, S, Rawaf, DL, Renzaho, AMN, Resnikoff, S, Rezaeian, S, Roever, L, Ronfani, L, Roshandel, G, Sabde, YD, Saddik, B, Salamati, P, Salimi, Y, Salz, I, Samy, AM, Sanabria, J, Riera, LS, Milicevic, MMS, Satpathy, M, Sawhney, M, Sawyer, SM, Saxena, S, Saylan, M, Schneider, IJC, Schwebel, DC, Seedat, S, Sepanlou, SG, Shaikh, MA, Shams-Beyranvand, M, Shamsizadeh, M, Sharif-Alhoseini, M, Sheikh, A, Shen, J, Shigematsu, M, Shiri, R, Shiue, I, Silva, JP, Singh, JA, Sinha, DN, Soares Filho, AM, Soriano, JB, Soshnikov, S, Soyiri, IN, Starodubov, V, Stein, DJ, Stokes, MA, Sufiyan, MB, Sunshine, JE, Sykes, BL, Tabares-Seisdedos, R, Tabb, KM, Tehrani-Banihashemi, A, Tessema, GA, Thakur, JS, Khanh, BT, Bach, XT, Car, LT, Uthman, OA, Uzochukwu, BSC, Valdez, PR, Varavikova, E, Nogales Vasconcelos, AM, Venketasubramanian, N, Violante, FS, Vlassov, V, Waheed, Y, Wang, Y-P, Wijeratne, T, Winkler, AS, Yadav, P, Yano, Y, Yenesew, MA, Yip, P, Yisma, E, Yonemoto, N, Younis, MZ, Yu, C, Zafar, S, Zaidi, Z, Bin Zaman, S, Zamani, M, Zhao, Y, Zodpey, S, Hay, S, Lopez, AD, Mokdad, AH, and Vos, T
Abstract: BACKGROUND: The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. METHODS: Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. RESULTS: For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. CONCLUSIONS: The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.
Published: 2020

3. Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: Soriano, JB, Kendrick, PJ, Paulson, KR, Gupta, V, Vos, T, Abrams, EM, Adedoyin, RA, Adhikari, TB, Advani, SM, Agrawal, A, Ahmadian, E, Alahdab, F, Aljunid, SM, Altirkawi, KA, Alvis-Guzman, N, Anber, NH, Andrei, CL, Anjomshoa, M, Ansari, F, Anto, JM, Arabloo, J, Athari, SM, Athari, SS, Awoke, N, Badawi, A, Banoub, JAM, Bennett, DA, Bensenor, IM, Berfield, KS, Bernstein, RS, Bhattacharyya, K, Bijani, A, Brauer, M, Bukhman, G, Butt, ZA, Camera, LA, Car, J, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Choi, J-YJ, Christopher, DJ, Cohen, AJ, Dandona, L, Dandona, R, Dang, AK, Daryani, A, de Courten, B, Demeke, FM, Demoz, GT, De Neve, J-W, Desai, R, Dharmaratne, SD, Diaz, D, Douiri, A, Driscoll, TR, Duken, EE, Eftekhari, A, Elkout, H, Endries, AY, Fadhil, I, Faro, A, Farzadfar, F, Fernandes, E, Filip, I, Fischer, F, Foroutan, M, Garcia-Gordillo, MA, Gebre, AK, Gebremedhin, KB, Gebremeskel, GG, Gezae, KE, Ghoshal, AG, Gill, PS, Gillum, RF, Goudarzi, H, Guo, Y, Gupta, R, Hailu, GB, Hasanzadeh, A, Hassen, HY, Hay, SI, Hoang, CL, Hole, MK, Horita, N, Hosgood, HD, Hostiuc, M, Househ, M, Ilesanmi, OS, Ilic, MD, Irvani, SSN, Islam, SMS, Jakovljevic, M, Jamal, AA, Jha, RP, Jonas, JB, Kabir, Z, Kasaeian, A, Kasahun, GG, Kassa, GM, Kefale, AT, Kengne, AP, Khader, YS, Khafaie, MA, Khan, EA, Khan, J, Khubchandani, J, Kim, Y-E, Kim, YJ, Kisa, S, Kisa, A, Knibbs, LD, Komaki, H, Koul, PA, Koyanagi, A, Kumar, GA, Lan, Q, Lasrado, S, Lauriola, P, La Vecchia, C, Tham, TL, Leigh, J, Levi, M, Li, S, Lopez, AD, Lotufo, PA, Madotto, F, Mahotra, NB, Majdan, M, Majeed, A, Malekzadeh, R, Mamun, AA, Manafi, N, Manafi, F, Mantovani, LG, Meharie, BG, Meles, HG, Meles, GG, Menezes, RG, Mestrovic, T, Miller, TR, Mini, GK, Mirrakhimov, EM, Moazen, B, Mohammad, KA, Mohammed, S, Mohebi, F, Mokdad, AH, Molokhia, M, Monasta, L, Moradi, M, Moradi, G, Morawska, L, Mousavi, SM, Musa, KI, Mustafa, G, Naderi, M, Naghavi, M, Naik, G, Nair, S, Nangia, V, Nansseu, JR, Nazari, J, Ndwandwe, DE, Negoi, RI, Trang, HN, Cuong, TN, Huong, LTN, Nixon, MR, Ofori-Asenso, R, Ogbo, FA, Olagunju, AT, Olagunju, TO, Oren, E, Ortiz, JR, Owolabi, MO, Mahesh, PA, Pakhale, S, Pana, A, Panda-Jonas, S, Park, E-K, Hai, QP, Postma, MJ, Pourjafar, H, Poustchi, H, Radfar, A, Rafiei, A, Rahim, F, Rahman, MHU, Rahman, MA, Rawaf, S, Rawaf, DL, Rawal, L, Reiner, RC, Reitsma, MB, Roever, L, Ronfani, L, Roro, EM, Roshandel, G, Rudd, KE, Sabde, YD, Sabour, S, Saddik, B, Safari, S, Saleem, K, Samy, AM, Santric-Milicevic, MM, Jose, BPS, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Sepanlou, SG, Shaikh, MA, Sheikh, A, Shigematsu, M, Shirkoohi, R, Si, S, Siabani, S, Singh, V, Singh, JA, Soljak, M, Somayaji, R, Soofi, M, Soyiri, IN, Tefera, YM, Temsah, M-H, Tesfay, BE, Thakur, JS, Toma, AT, Tortajada-Girbes, M, Khanh, BT, Bach, XT, Car, LT, Ullah, I, Vacante, M, Valdez, PR, van Boven, JFM, Vasankari, TJ, Veisani, Y, Violante, FS, Wagner, GR, Westerman, R, Wolfe, CDA, Wondafrash, DZ, Wondmieneh, AB, Yonemoto, N, Yoon, S-J, Zaidi, Z, Zamani, M, Zar, HJ, Zhang, Y, Soriano, JB, Kendrick, PJ, Paulson, KR, Gupta, V, Vos, T, Abrams, EM, Adedoyin, RA, Adhikari, TB, Advani, SM, Agrawal, A, Ahmadian, E, Alahdab, F, Aljunid, SM, Altirkawi, KA, Alvis-Guzman, N, Anber, NH, Andrei, CL, Anjomshoa, M, Ansari, F, Anto, JM, Arabloo, J, Athari, SM, Athari, SS, Awoke, N, Badawi, A, Banoub, JAM, Bennett, DA, Bensenor, IM, Berfield, KS, Bernstein, RS, Bhattacharyya, K, Bijani, A, Brauer, M, Bukhman, G, Butt, ZA, Camera, LA, Car, J, Carrero, JJ, Carvalho, F, Castaneda-Orjuela, CA, Choi, J-YJ, Christopher, DJ, Cohen, AJ, Dandona, L, Dandona, R, Dang, AK, Daryani, A, de Courten, B, Demeke, FM, Demoz, GT, De Neve, J-W, Desai, R, Dharmaratne, SD, Diaz, D, Douiri, A, Driscoll, TR, Duken, EE, Eftekhari, A, Elkout, H, Endries, AY, Fadhil, I, Faro, A, Farzadfar, F, Fernandes, E, Filip, I, Fischer, F, Foroutan, M, Garcia-Gordillo, MA, Gebre, AK, Gebremedhin, KB, Gebremeskel, GG, Gezae, KE, Ghoshal, AG, Gill, PS, Gillum, RF, Goudarzi, H, Guo, Y, Gupta, R, Hailu, GB, Hasanzadeh, A, Hassen, HY, Hay, SI, Hoang, CL, Hole, MK, Horita, N, Hosgood, HD, Hostiuc, M, Househ, M, Ilesanmi, OS, Ilic, MD, Irvani, SSN, Islam, SMS, Jakovljevic, M, Jamal, AA, Jha, RP, Jonas, JB, Kabir, Z, Kasaeian, A, Kasahun, GG, Kassa, GM, Kefale, AT, Kengne, AP, Khader, YS, Khafaie, MA, Khan, EA, Khan, J, Khubchandani, J, Kim, Y-E, Kim, YJ, Kisa, S, Kisa, A, Knibbs, LD, Komaki, H, Koul, PA, Koyanagi, A, Kumar, GA, Lan, Q, Lasrado, S, Lauriola, P, La Vecchia, C, Tham, TL, Leigh, J, Levi, M, Li, S, Lopez, AD, Lotufo, PA, Madotto, F, Mahotra, NB, Majdan, M, Majeed, A, Malekzadeh, R, Mamun, AA, Manafi, N, Manafi, F, Mantovani, LG, Meharie, BG, Meles, HG, Meles, GG, Menezes, RG, Mestrovic, T, Miller, TR, Mini, GK, Mirrakhimov, EM, Moazen, B, Mohammad, KA, Mohammed, S, Mohebi, F, Mokdad, AH, Molokhia, M, Monasta, L, Moradi, M, Moradi, G, Morawska, L, Mousavi, SM, Musa, KI, Mustafa, G, Naderi, M, Naghavi, M, Naik, G, Nair, S, Nangia, V, Nansseu, JR, Nazari, J, Ndwandwe, DE, Negoi, RI, Trang, HN, Cuong, TN, Huong, LTN, Nixon, MR, Ofori-Asenso, R, Ogbo, FA, Olagunju, AT, Olagunju, TO, Oren, E, Ortiz, JR, Owolabi, MO, Mahesh, PA, Pakhale, S, Pana, A, Panda-Jonas, S, Park, E-K, Hai, QP, Postma, MJ, Pourjafar, H, Poustchi, H, Radfar, A, Rafiei, A, Rahim, F, Rahman, MHU, Rahman, MA, Rawaf, S, Rawaf, DL, Rawal, L, Reiner, RC, Reitsma, MB, Roever, L, Ronfani, L, Roro, EM, Roshandel, G, Rudd, KE, Sabde, YD, Sabour, S, Saddik, B, Safari, S, Saleem, K, Samy, AM, Santric-Milicevic, MM, Jose, BPS, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Sepanlou, SG, Shaikh, MA, Sheikh, A, Shigematsu, M, Shirkoohi, R, Si, S, Siabani, S, Singh, V, Singh, JA, Soljak, M, Somayaji, R, Soofi, M, Soyiri, IN, Tefera, YM, Temsah, M-H, Tesfay, BE, Thakur, JS, Toma, AT, Tortajada-Girbes, M, Khanh, BT, Bach, XT, Car, LT, Ullah, I, Vacante, M, Valdez, PR, van Boven, JFM, Vasankari, TJ, Veisani, Y, Violante, FS, Wagner, GR, Westerman, R, Wolfe, CDA, Wondafrash, DZ, Wondmieneh, AB, Yonemoto, N, Yoon, S-J, Zaidi, Z, Zamani, M, Zar, HJ, and Zhang, Y
Abstract: BACKGROUND: Previous attempts to characterise the burden of chronic respiratory diseases have focused only on specific disease conditions, such as chronic obstructive pulmonary disease (COPD) or asthma. In this study, we aimed to characterise the burden of chronic respiratory diseases globally, providing a comprehensive and up-to-date analysis on geographical and time trends from 1990 to 2017. METHODS: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, we estimated the prevalence, morbidity, and mortality attributable to chronic respiratory diseases through an analysis of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLL) by GBD super-region, from 1990 to 2017, stratified by age and sex. Specific diseases analysed included asthma, COPD, interstitial lung disease and pulmonary sarcoidosis, pneumoconiosis, and other chronic respiratory diseases. We also assessed the contribution of risk factors (smoking, second-hand smoke, ambient particulate matter and ozone pollution, household air pollution from solid fuels, and occupational risks) to chronic respiratory disease-attributable DALYs. FINDINGS: In 2017, 544·9 million people (95% uncertainty interval [UI] 506·9-584·8) worldwide had a chronic respiratory disease, representing an increase of 39·8% compared with 1990. Chronic respiratory disease prevalence showed wide variability across GBD super-regions, with the highest prevalence among both males and females in high-income regions, and the lowest prevalence in sub-Saharan Africa and south Asia. The age-sex-specific prevalence of each chronic respiratory disease in 2017 was also highly variable geographically. Chronic respiratory diseases were the third leading cause of death in 2017 (7·0% [95% UI 6·8-7·2] of all deaths), behind cardiovascular diseases and neoplasms. Deaths due to chronic respiratory diseases numbered 3 914 196 (95% UI 3 790 578-4 044 819) in 2017, an increase of 18·0% since 1990, while
Published: 2020

4. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016

Author: Wang, H, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abera, SF, Abraha, HN, Abu-Raddad, LJ, Abu-Rmeileh, NME, Adedeji, IA, Adedoyin, RA, Adetifa, IMO, Adetokunboh, O, Afshin, A, Aggarwal, R, Agrawal, A, Agrawal, S, Kiadaliri, AA, Ahmed, MB, Aichour, AN, Aichour, I, Aichour, MTE, Aiyar, S, Akanda, S, Akinyemiju, TF, Akseer, N, Al-Eyadhy, A, Al Lami, FH, Alabed, S, Alahdab, F, Al-Aly, Z, Alam, K, Alam, N, Alasfoor, D, Aldridge, RW, Alene, KA, Alhabib, S, Ali, R, Alizadeh-Navaei, R, Aljunid, SM, Alkaabi, JM, Alkerwi, A, Alla, F, Allam, SD, Allebeck, P, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Ameh, EA, Amini, E, Ammar, W, Amoako, YA, Anber, N, Andrei, CL, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Anwari, P, Arnlov, J, Arora, M, Al, A, Aryal, KK, Asayesh, H, Asgedom, SW, Asghar, RJ, Assadi, R, Atey, TM, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Babalola, TK, Bacha, U, Badawi, A, Balakrishnan, K, Balalla, S, Barac, A, Barber, RM, Barboza, MA, Barker-Collo, SL, Barnighausen, T, Barquera, S, Barregard, L, Barrero, LH, Baune, BT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Bejot, Y, Bekele, BB, Bell, ML, Bello, AK, Bennett, DA, Bennett, JR, Bensenor, IM, Benson, J, Berhane, A, Berhe, DF, Bernabe, E, Beuran, M, Beyene, AS, Bhala, N, Bhansali, A, Bhaumik, S, Bhutta, ZA, Bikbov, B, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bjerregaard, P, Blosser, CD, Boneya, DJ, Boufous, S, Bourne, RRA, Brazinova, A, Breitborde, NJK, Brenner, H, Brugha, TS, Bukhman, G, Negesa, L, Bulto, B, Bumgarner, BR, Burch, M, Butt, ZA, Cahill, LE, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Car, M, Crdenas, R, Carpenter, DO, Carrero, JJ, Carter, A, Castaneda-Orjuela, CA, Rivas, JC, Castro, FF, Castro, RE, Catala-Lopez, F, Chen, H, Chiang, PP-C, Chibalabala, M, Chisumpa, VH, Chitheer, AA, Choi, J-YJ, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Cohen, AJ, Colquhoun, SM, Coresh, J, Criqui, MH, Cromwell, EA, Crump, JA, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, de Courten, B, De Leo, D, Degenhardt, L, Deiparine, S, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dherani, MK, Diaz-Torne, C, Ding, EL, Dixit, P, Djalalinia, S, Huyen, PD, Doku, DT, Donnelly, CA, Priscila, K, dos Santos, B, Douwes-Schultz, D, Driscoll, TR, Duan, L, Dubey, M, Duncan, BB, Dwivedi, LK, Ebrahimi, H, El Bcheraoui, C, Ellingsen, CL, Enayati, A, Endries, AY, Ermakov, SP, Eshetie, S, Eshrati, B, Eskandarieh, S, Esteghamati, A, Estep, K, Fanuel, BBF, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Filip, I, Fischer, F, Foigt, N, Foreman, KJ, Frank, T, Franklin, RC, Fraser, M, Friedman, J, Frostad, JJ, Fullman, N, Furst, T, Furtado, JM, Futran, ND, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gankpe, FG, Garcia-Basteiro, AL, Gebregergs, GB, Gebrehiwot, TT, Gebrekidan, KG, Gebremichael, MW, Gelaye, AA, Geleijnse, JM, Gemechu, BL, Gemechu, KS, Genova-Maleras, R, Gesesew, HA, Gething, PW, Gibney, KB, Gill, PS, Gillum, RF, Giref, AZ, Girma, BW, Giussani, G, Goenka, S, Gomez, B, Gona, PN, Gopalani, SV, Goulart, AC, Graetz, N, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Haagsma, JA, Hafezi-Nejad, N, Bidgoli, HH, Hakuzimana, A, Halasa, YA, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hancock, J, Handal, AJ, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Harikrishnan, S, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, He, F, Heredia-Pi, IB, Herteliu, C, Hilawe, EH, Hoek, HW, Horita, N, Hosgood, HD, Hostiuc, S, Hotez, PJ, Hoy, DG, Hsairi, M, Htet, AS, Hu, G, Huang, H, Huang, JJ, Iburg, KM, Igumbor, EU, Ileanu, BV, Inoue, M, Irenso, AA, Irvine, CMS, Islam, N, Jacobsen, KH, Jaenisch, T, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jeemon, P, Jensen, PN, Jha, V, Jin, Y, John, D, John, O, Johnson, SC, Jonas, JB, Jurisson, M, Kabir, Z, Kadel, R, Kahsay, A, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Karthikeyan, G, Kasaeian, A, Kassaw, NA, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kaul, A, Kawakami, N, Kazanjan, K, Keiyoro, PN, Kelbore, SG, Kemp, AH, Kengne, AP, Keren, A, Kereselidze, M, Kesavachandran, CN, Ketema, EB, Khader, YS, Khalil, IA, Khan, EA, Khan, G, Khang, Y-H, Khera, S, Khoja, ATA, Khosravi, MH, Kibret, GD, Kieling, C, Kim, C-I, Kim, D, Kim, P, Kim, S, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kishawi, S, Kissimova-Skarbek, KA, Kissoon, N, Kivimaki, M, Knudsen, AK, Kokubo, Y, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulikoff, XR, Kulkarni, VS, Kumar, GA, Kumar, P, Kumsa, FA, Kutz, M, Lachat, C, Lagat, AK, Lager, ACJ, Lal, DK, Lalloo, R, Lambert, N, Lan, Q, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Lavados, PM, Laxmaiah, A, Lee, PH, Leigh, J, Leung, J, Leung, R, Levi, M, Li, Y, Liao, Y, Liben, ML, Lim, SS, Linn, S, Lipshultz, SE, Liu, S, Lodha, R, Logroscino, G, Lorch, SA, Lorkowski, S, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Ma, S, Macarayan, ERK, Machado, IE, Mackay, MT, Abd el Razek, MM, Magis-Rodriguez, C, Mahdavi, M, Majdan, M, Majdzadeh, R, Majeed, A, Malekzadeh, R, Malhotra, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marczak, LB, Marks, GB, Martinez-Raga, J, Martins-Melo, FR, Massano, J, Maulik, PK, Mayosi, BM, Mazidi, M, McAlinden, C, McGarvey, ST, McGrath, JJ, Mckee, M, Mehata, S, Mehndiratta, MM, Mehta, KM, Meier, T, Mekonnen, TC, Meles, KG, Memiah, P, Memish, ZA, Mendoza, W, Mengesha, MM, Mengistie, MA, Tadese, D, Menon, MGR, Menota, BG, Mensah, GA, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Mikesell, J, Miller, TR, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Misganaw, A, Mishra, SR, Mohammad, KA, Mohammadi, A, Mohammed, KESM, Mohan, MBV, Mohanty, SK, Mokdad, AH, Assaye, AM, Mollenkopf, SK, Molokhia, M, Monasta, L, Hernandez, JCM, Montico, M, Mooney, MD, Moore, AR, Moradi-Lakeh, M, Moraga, P, Morawska, L, Velasquez, IM, Mori, R, Morrison, SD, Mruts, KB, Mueller, UO, Mullany, E, Muller, K, Venkata, G, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naidoo, KS, Nanda, L, Nangia, V, Nascimento, BR, Natarajan, G, Negoi, I, Cuong, TN, Ningrum, DNA, Nisar, MI, Nomura, M, Vuong, MN, Norheim, OF, Norrving, B, Noubiap, JJN, Nyakarahuka, L, Obermeyer, CM, O'Donnell, MJ, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olusanya, BO, Olusanya, JO, Oren, E, Ortiz, A, Osgood-Zimmerman, A, Ota, E, Owolabi, MO, Oyekale, AS, Pa, M, Pacella, RE, Pakhale, S, Pana, A, Panda, BK, Panda-Jonas, S, Park, E-K, Parsaeian, M, Patel, T, Patten, SB, Patton, GC, Paudel, D, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, CB, Petri, WA, Petzold, M, Phillips, MR, Piel, FB, Pigott, DM, Pishgar, F, Plass, D, Polinder, S, Popova, S, Postma, MJ, Poulton, RG, 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Werdecker, A, Wesana, J, Wijeratne, T, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Workicho, A, Workie, SB, Xavier, D, Xu, G, Yaghoubi, M, Yakob, B, Yalew, AZ, Yan, LL, Yano, Y, Yaseri, M, Ye, P, Yimam, HH, Yip, P, Yirsaw, BD, Yonemoto, N, Yoon, S-J, Yotebieng, M, Younis, MZ, Zaidi, Z, Zaki, MES, Zeeb, H, Zenebe, ZM, Zerfu, TA, Zhang, AL, Zhang, X, Zodpey, S, Zuhlke, LJ, Lopez, AD, and Murray, CJL
Published: 2017

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

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, 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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

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

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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, 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Purcell, C, Purwar, M, Rahman, S, Rai, R, Ranabhat, C, Rawaf, D, Ray, S, Reiner, R, Renzaho, A, Riahi, S, Rios-Blancas, M, Roba, K, Roberts, N, Ruhago, G, Sabde, Y, Sahraian, M, Saldanha, R, Salomon, J, Sambala, E, Samy, A, Sanchez-Niño, M, Santric Milicevic, M, Sao Jose, B, Sarker, A, Sawant, A, Schneider, I, Schwebel, D, Sepanlou, S, Shackelford, K, Shaheen, A, Shaikh, M, Shakir, R, Shukla, S, Sibai, A, Siddiqi, T, Sigfusdottir, I, Silva, D, Silva, J, Silveira, D, Singam, N, Singh, J, Singh, N, Sinha, D, Soares Filho, A, Sobaih, B, Soriano, J, Soyiri, I, Sreeramareddy, C, Starodubov, V, Stewart, L, Stokes, M, Subart, M, Sufiyan, M, Sunguya, B, Sur, P, Sykes, B, Sylaja, P, Sylte, D, Szoeke, C, Tabb, K, Tadakamadla, S, Tassew, A, Tassew, S, Tawye, N, Tekalign, T, Tekle, M, Temsah, M, Teshale, M, Thankappan, K, Thomson, A, To, Q, Torre, A, Tovani-Palone, M, Tran, B, Tran, K, Tripathy, S, Truelsen, T, Truong, N, Tsadik, A, Ukwaja, K, Uthman, O, Uzun, S, Valdez, P, Vasankari, T, Vasconcelos, A, Vladimirov, S, Vollset, S, Walson, J, Weintraub, R, Weldegwergs, K, Wolfe, C, Wyper, G, Yasin, Y, Yentür, G, Yimer, E, Yoon, S, Younis, M, Zaman, S, Zeleke, M, Zenebe, Z, Zerfu, T, Zhao, X, Zimsen, S, Lopez, A, and Lim, S
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

7. 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, 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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, Ay, Faraon, Eja, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Fijabi, Do, Flaxman, Ad, Foreman, Kj, Frostad, Jj, Futran, Nd, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gelaw, Ya, Geleijnse, Jm, Gething, Pw, Giref, Az, Gishu, Md, Godwin, Ww, Gona, Pn, Gopalani, Sv, Goulart, Ac, Gugnani, Hc, Haagsma, Ja, Hailu, Gb, Hamadeh, Rr, Hankey, Gj, Harb, Hl, Harewood, Hc, Haro, Jm, Hassen, Hy, Hay, Si, Hearps, Sjc, Hegazy, Mi, Henry, Nj, Herrera Ballesteros, Vh, Hibstu, Dt, Hiluf, Mk, Hoek, Hw, Hosgood, Hd, Hosseini, Sr, Hoy, Dg, Huang, Jj, Iburg, Km, Igumbor, Eu, Ileanu, Bv, Irvani, Ssn, Irvine, Cm, Jacobs, Ta, Jacobsen, Kh, Jain, Sk, Jakovljevic, Mb, Jalu, Mt, Jamal, Aa, Jayatilleke, Au, Jha, Rp, Johnson, Sc, Jonas, Jb, Karema, Ck, Karimi, Sm, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Ketema, Eb, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Mn, Khan, Ma, Khanal, Mn, Khang, Yh, Khater, Mm, Khoja, Ata, Kibret, Gd, Kiirithio, Dn, 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, 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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

8. 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, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chaiah, Yazan, Champs, Ana Paula, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chen, Wanqing, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Cohen, Aaron J, Collado-Mateo, Daniel, Constantin, Maria-Magdalena, Conti, Sara, Cooper, Cyrus, Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Criqui, Michael H, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Crump, John A, Cucu, Alexandra, Cunningham, Matthew, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, 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, Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, Courten, Barbora de, De la Hoz, Fernando Pio, De leo, Diego, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem Betsu, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Ding, Eric L, Djalalinia, Shirin, Doku, David Teye, Dolan, Kate A, Donnelly, Christl A, Dorsey, E Ray, Douwes-Schultz, Dirk, Doyle, Kerrie E, Drake, Thomas M, Driscoll, Tim Robert, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edessa, Dumessa, Edvardsson, David, Eggen, Anne Elise, El Bcheraoui, Charbel, El Sayed Zaki, Maysaa, Elfaramawi, Mohammed, El-Khatib, Ziad, Ellingsen, Christian Lycke, Elyazar, Iqbal R F, Enayati, Ahmadali, Endries, Aman Yesuf Yesuf, Er, Benjamin, Ermakov, Sergey Petrovich, Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Esteghamati, Sadaf, Fakhar, Mahdi, Fakhim, Hamed, Farag, Tamer, 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, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Feizy, Fariba, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Fischer, Florian, Flor, Luisa Sorio, Foigt, Nataliya A, Ford, John A, Foreman, Kyle J, Fornari, Carla, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fuller, John E, Fullman, Nancy, Fürst, Thomas, Furtado, João M, Futran, Neal D, Galan, Adriana, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Gankpe, Fortune Gbetoho, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gebre, Teshome, Gebre, Abadi Kahsu, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelano, Tilayie Feto, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M, Genova-Maleras, Ricard, Gessner, Bradford D, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Gill, Paramjit Singh, Gill, Tiffany K, Gillum, Richard F, Giussani, Giorgia, Goenka, Shifalika, Goli, Srinivas, Gomez, Ricardo Santiago, Gomez-Cabrera, Mari Carmen, Gómez-Dantés, Hector, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Grosso, Giuseppe, Gugnani, Harish Chander, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gyawali, Bishal, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hagos, Tekleberhan B, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arya, Haj-Mirzaian, Arvin, Hamadeh, Randah R, Hamidi, Samer, Handal, Alexis J, Hankey, Graeme J, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hay, Roderick J, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Henry, Nathaniel J, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Fatemeh, Heydarpour, Pouria, Heydarpour, Sousan, Hibstu, Desalegn Tsegaw, Hoek, Hans W, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Horino, Masako, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Sorin, Hostiuc, Mihaela, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J, Husseini, Abdullatif, Hussen, Mohammedaman Mama, Hutfless, Susan, Iburg, Kim Moesgaard, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Isehunwa, Oluwaseyi Oluwakemi, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jahangiry, Leila, Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, James, Spencer L, Javanbakht, Mehdi, Jayaraman, Sudha, Jayatilleke, Achala Upendra, Jee, Sun Ha, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Johnson, Sarah Charlotte, Jonas, Jost B, 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, Karch, André, Karema, Corine, Karimi, Narges, Karimi, Seyed M, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Katibeh, Marzieh, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemeini, Hossein, Kazemi, Zhila, Karyani, Ali Kazemi, K C, Prakash, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kereselidze, Maia, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, Khatony, Alireza, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A, Kibret, Getiye D Dejenu, Kim, Cho-il, Kim, Daniel, Kim, Jun Y, Kim, Young-Eun, Kimokoti, Ruth W, Kinfu, Yohannes, Kinra, Sanjay, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kissoon, Niranjan, Kivimäki, Mika, Kleber, Marcus E, Knibbs, Luke D, Knudsen, Ann Kristin Skrindo, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A, Kosek, Margaret N, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krishnaswami, Sanjay, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kudom, Andreas A, Kuipers, Ernst J, Kulikoff, Xie Rachel, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kumsa, Fekede Asefa, Kutz, Michael J, Lad, Sheetal D, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lami, Faris Hasan, Lan, Qing, Langan, Sinéad M, Lansingh, Van C, Lansky, Sonia, Larson, Heidi Jane, Laryea, Dennis Odai, Lassi, Zohra S, Latifi, Arman, Lavados, Pablo M, Laxmaiah, Avula, Lazarus, Jeffrey V, Lebedev, Georgy, Lee, Paul H, Leigh, James, Leshargie, Cheru Tesema, Leta, Samson, Levi, Miriam, Li, Shanshan, Li, Yichong, Li, Xiaohong, Liang, Juan, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lonsdale, Chris, Lorch, Scott A, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Tim C D, Lunevicius, Raimundas, Lyons, Ronan A, Ma, Stefan, Mabika, Crispin, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Maddison, Ralph, Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Muhammed, Maghavani, Dhaval P, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malik, Manzoor Ahmad, Malta, Deborah Carvalho, Mamun, Abdullah A, Manamo, Wondimu Ayele, Manda, Ana-Laura, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C, Marcenes, Wagner, Marina, Shakhnazarova, Martinez-Raga, Jose, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, März, Winfried, Marzan, Melvin B, Mashamba-Thompson, Tivani Phosa, Masiye, Felix, Massenburg, Benjamin Ballard, Maulik, Pallab K, Mazidi, Mohsen, McGrath, John J, McKee, Martin, Mehata, Suresh, Mehendale, Sanjay Madhav, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Mekonen, Tesfa, Mekonnen, Tefera Chane, Meles, Hagazi Gebre, Meles, Kidanu Gebremariam, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Mensah, George A, Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Mezgebe, Haftay Berhane, Miangotar, Yode, Miazgowski, Bartosz, Miazgowski, Tomasz, Miller, Ted R, Mini, G K, Mirica, Andreea, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Moazen, Babak, Moges, Nurilign Abebe, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadi-Khanaposhtani, Maryam, Mohammadnia-Afrouzi, Mousa, Mohammed, Shafiu, Mohammed, Mohammed A, Mohan, Viswanathan, Mokdad, Ali H, Molokhia, Mariam, Monasta, Lorenzo, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Moreno Velásquez, Ilais, Morgado-da-Costa, Joana, Morrison, Shane Douglas, Mosapour, Abbas, Moschos, Marilita M, Mousavi, Seyyed Meysam, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Mukhopadhyay, Satinath, Mullany, Erin C, Muller, Kate, Murhekar, Manoj, Murphy, Tasha B, Murthy, G V S, Murthy, Srinivas, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nachega, Jean B, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Nair, Sanjeev, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramos, Nawaz, Haseeb, Ncama, Busisiwe P, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Subas, Newton, Charles Richard James, Ngalesoni, Frida N, Ngunjiri, Josephine W, Nguyen, Ha Thu, Nguyen, Huong Thanh, Nguyen, Long Hoang, Nguyen, Michele, Nguyen, Trang Huyen, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nisar, Muhammad Imran, Nixon, Molly R, Nolutshungu, Nomonde, Nomura, Shuhei, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Ofori-Asenso, Richard, Ogah, Okechukwu Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Sok King, Opio, John Nelson, Oren, Eyal, Ortiz, Justin R, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, Oyekale, Abayomi Samuel, P A, Mahesh, Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandey, Achyut Raj, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Patle, Ajay, Patten, Scott B, Patton, George C, Paudel, Deepak, Pearce, Neil, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perez, Krystle M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Plass, Dietrich, Polinder, Suzanne, Pond, Constance Dimity, Popova, Svetlana, Postma, Maarten J, Pourmalek, Farshad, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, V, Prakash, Swayam, Prasad, Narayan, Qorbani, Mostafa, Quistberg, D Alex, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Raju, Sree Bhushan, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Ranta, Anna, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E, Razo-García, Christian, Rego, Maria Albertina Santiago, Rehm, Jürgen, Reiner, Robert C, Reinig, Nickolas, Reis, Cesar, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezaeian, Shahab, Rezai, 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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

9. Association of tobacco use with the tobacco-related built environment: an ecological study from urban slums of Bhopal, India.

Author: Sabde YD, Yadav V, Pakhare AP, Kumar S, Joshi A, and Joshi R
Subjects: Cross-Sectional Studies, Tobacco Use epidemiology, India epidemiology, Poverty Areas, Nicotiana
Abstract: Introduction: Tobacco is one of the biggest public health problems and a major risk factor for various non-communicable diseases (NCDs). An important aspect of tobacco control strategy could include modifications in the tobacco-related built environment. This study investigated the association between tobacco shop density and tobacco use prevalence in the urban slums of Bhopal city, India., Methods: We conducted a cross-sectional survey to obtain the distribution of tobacco-related built environment (tobacco shops) in the neighbourhood (400-m service area) of 32 urban slum clusters of Bhopal. We plotted this distribution using the 'network service area analysis' in ArcMap 10.7.1 software. Then, we used an ecological design to determine the association between tobacco shop density and tobacco use prevalence in these 32 clusters (N = 6214 adult inhabitants). We used multiple linear regression analysis to estimate the regression coefficient (adjusted for socio-demographic variables) between tobacco use and tobacco shop density at the cluster level., Results: The prevalence of tobacco use among all 32 slum clusters ranged from 22.1 to 59.6% (median 40.9% with IQR 31.8-44.2). There were 194 tobacco shops situated in the neighbourhood of all clusters. The median density of tobacco shops was 59.40/km 2 (IQR 39.9-108.1/km 2 ) in the neighbourhoods of slum clusters. Tobacco use prevalence was significantly associated with tobacco shop density (estimate or B = 0.071, p value = 0.002) after adjusting for age, literacy, wealth index, and gender ratio., Conclusions: Tobacco use prevalence is significantly associated with tobacco shop density in the slums of Bhopal city in central India. We need to develop appropriate built environment interventions to control rampant tobacco use., (© 2023. The Author(s).)
Published: 2023
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10. Prevalence of chronic kidney disease among severely gas-exposed survivors in Bhopal, India.

Author: Soni KK, Kalyanasundaram M, Singh S, Shubham S, Sabde YD, Prakash A, and Tiwari R
Subjects: Humans, Prevalence, Cross-Sectional Studies, Glomerular Filtration Rate, Survivors, Risk Factors, Renal Insufficiency, Chronic epidemiology, Renal Insufficiency, Chronic etiology
Abstract: Background The survivors of the 1984 Bhopal gas disaster frequently express concern of them being at higher risk of developing chronic kidney disease (CKD) as a consequence of the long-term health effects of gas exposure. We aimed to estimate the prevalence of CKD among the survivors of severely gas-exposed cohort assembled in 1985 after the Bhopal gas disaster to study the long-term health consequences of gas exposure. Methods We did this cross-sectional study with a sample size of 215 systematically selected participants among the severely gas-exposed survivors in Bhopal to estimate the prevalence of CKD. Sociodemographic and relevant past medical history of the participants was obtained using a semi-structured questionnaire and their blood and urine samples were collected. The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease equation. Those found with reduced e-GFR and proteinuria, suggestive of CKD, were further surveyed after 3 months to differentiate CKD from acute renal damage. Results The prevalence of CKD among the severely gas-exposed cohort survivors in Bhopal was 16.7%. Multiple logistic regression analysis revealed that body mass index and level of education were significant predictors of CKD. Conclusion The prevalence of CKD among the severely exposed survivors of Bhopal was at par with the national prevalence, putting at rest the apprehension of gas-exposed survivors of being at higher risk of developing CKD.
Published: 2023
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11. Evaluation of health impacts of the improved housing conditions on under-five children in the socioeconomically underprivileged families in central India: A 1-year follow-up study protocol.

Author: Sabde YD, Trushna T, Mandal UK, Yadav V, Sarma DK, Aher SB, Singh S, Tiwari RR, and Diwan V
Subjects: Child, Child, Preschool, Follow-Up Studies, Housing, Humans, Infant, Infant, Newborn, Morbidity, Housing Quality, Poverty Areas
Abstract: Unacceptable housing conditions prevalent in Indian urban slums adversely affect the health of residents. The Government of India initiated the Basic Services to the Urban Poor (BSUP) as a sub-mission under the Jawaharlal Nehru National Urban Renewal Mission (JNNURM), to provide basic services to the urban poor. As per the available scientific literature, the health effects of such improved housing schemes for the poor have not been studied so far in India, especially in under-five children (0-5 years old) who spend most of their time indoors. The present paper describes the protocol for a follow-up research study proposed to fill this gap. This study, funded by the Indian Council of Medical Research (Sanction No. 5/8-4/9/Env/2020-NCD-II dated 21.09.2021), will be conducted in Bhopal in the central Indian province of Madhya Pradesh for over 2 years. We will recruit 320 under-five children each from Group 1 (Beneficiary families residing in the houses constructed under BSUP) and Group 2 (Slum dwelling families eligible for improved housing but who did not avail of benefit). Eligible children will be recruited in the first household visit. During the same visit, we will record clinical history, examination findings and take anthropometric measurements of participants. We will also collect data regarding socio-economic-environmental parameters of the house. During subsequent monthly follow-up visits, we will collect primary data on morbidity profile, anthropometric details and medical history over 1 year. Approval for the study was obtained from the Institutional Ethics Committee of the National Institute for Research in Environmental Health (No: NIREH/BPL/IEC/2020-21/198, dated 22/06/2020). This study will evaluate the impact of different housing conditions on the health of under-five children. Finding of this research will be beneficial in guiding future housing-related policy decisions in low- and middle-income countries., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sabde, Trushna, Mandal, Yadav, Sarma, Aher, Singh, Tiwari and Diwan.)
Published: 2022
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12. A mixed-methods community-based participatory research to explore stakeholder's perspectives and to quantify the effect of crop residue burning on air and human health in Central India: study protocol.

Author: Trushna T, Diwan V, Nandi SS, Aher SB, Tiwari RR, and Sabde YD
Subjects: Adult, Community-Based Participatory Research methods, Female, Focus Groups, Humans, India, Male, Qualitative Research, Research Design, Stakeholder Participation psychology, Air Pollution adverse effects, Air Pollution analysis, Crops, Agricultural, Fires
Abstract: Background: Crop residue burning adversely affects air quality and consequently human health. India, being one of the largest agro-economies of the world, produces around 500 Million tonnes of crop residue annually most of which is burnt on-farm. However, integrated studies that simultaneously quantify the effects of crop residue burning while exploring the subjective determinants of the practice are lacking in India. This paper describes the protocol for a longitudinal mixed methods research study employing a community-based participatory approach to fill this gap., Methods: Both quantitative and qualitative data will be collected in a rural setting of the central Indian province of Madhya Pradesh, over 1 year. A steering committee comprising of the research team and community representatives will be formed. The proportion of cultivable land burnt in one crop burning season will be estimated. The association between crop residue burning, level of ambient air pollutants, and pulmonary function of village residents will be determined. Focus groups, interviews, and participatory rural appraisal methods will be used to explore stakeholder perspectives about crop residue burning. Potential barriers and opportunities for substituting burning with an alternative crop residue management technique will be ascertained as the basis for future interventions. Ethics approval has been obtained from the Institutional Ethics Committee of the National Institute for Research in Environmental Health (No: NIREH/BPL/IEC/2019-20/1494, dt 06/01/2020)., Discussion: This manuscript describes the protocol for a novel community-based participatory study to investigate thoroughly the phenomenon of crop residue burning from the perspective of the agricultural community through their active collaboration. The lack of comprehensive evidence regarding the factors responsible for crop residue burning in India underlines the importance of implementing this study protocol to fill in this critical gap in knowledge. While acknowledging that findings of this study will be not generalizable to agricultural communities other than the one studied, it is expected that the study will generate baseline evidence that might be beneficial in developing and implementing an appropriate intervention strategy.
Published: 2020
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13. Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017.

Author: James SL, Castle CD, Dingels ZV, Fox JT, Hamilton EB, Liu Z, S Roberts NL, Sylte DO, Henry NJ, LeGrand KE, Abdelalim A, Abdoli A, Abdollahpour I, Abdulkader RS, Abedi A, Abosetugn AE, Abushouk AI, Adebayo OM, Agudelo-Botero M, Ahmad T, Ahmed R, Ahmed MB, Eddine Aichour MT, Alahdab F, Alamene GM, Alanezi FM, Alebel A, Alema NM, Alghnam SA, Al-Hajj S, Ali BA, Ali S, Alikhani M, Alinia C, Alipour V, Aljunid SM, Almasi-Hashiani A, Almasri NA, Altirkawi K, Abdeldayem Amer YS, Amini S, Loreche Amit AM, Andrei CL, Ansari-Moghaddam A, T Antonio CA, Yaw Appiah SC, Arabloo J, Arab-Zozani M, Arefi Z, Aremu O, Ariani F, Arora A, Asaad M, Asghari B, Awoke N, Ayala Quintanilla BP, Ayano G, Ayanore MA, Azari S, Azarian G, Badawi A, Badiye AD, Bagli E, Baig AA, Bairwa M, Bakhtiari A, Balachandran A, Banach M, Banerjee SK, Banik PC, Banstola A, Barker-Collo SL, Bärnighausen TW, Barrero LH, Barzegar A, Bayati M, Baye BA, Bedi N, Behzadifar M, Bekuma TT, Belete H, Benjet C, Bennett DA, Bensenor IM, Berhe K, Bhardwaj P, Bhat AG, Bhattacharyya K, Bibi S, Bijani A, Bin Sayeed MS, Borges G, Borzì AM, Boufous S, Brazinova A, Briko NI, Budhathoki SS, Car J, Cárdenas R, Carvalho F, Castaldelli-Maia JM, Castañeda-Orjuela CA, Castelpietra G, Catalá-López F, Cerin E, Chandan JS, Chanie WF, Chattu SK, Chattu VK, Chatziralli I, Chaudhary N, Cho DY, Kabir Chowdhury MA, Chu DT, Colquhoun SM, Constantin MM, Costa VM, Damiani G, Daryani A, Dávila-Cervantes CA, Demeke FM, Demis AB, Demoz GT, Demsie DG, Derakhshani A, Deribe K, Desai R, Nasab MD, da Silva DD, Dibaji Forooshani ZS, Doyle KE, Driscoll TR, Dubljanin E, Adema BD, Eagan AW, Eftekhari A, Ehsani-Chimeh E, Sayed Zaki ME, Elemineh DA, El-Jaafary SI, El-Khatib Z, Ellingsen CL, Emamian MH, Endalew DA, Eskandarieh S, Faris PS, Faro A, Farzadfar F, Fatahi Y, Fekadu W, Ferede TY, Fereshtehnejad SM, Fernandes E, Ferrara P, Feyissa GT, Filip I, Fischer F, Folayan MO, Foroutan M, Francis JM, Franklin RC, Fukumoto T, Geberemariyam BS, Gebre AK, Gebremedhin KB, Gebremeskel GG, Gebremichael B, Gedefaw GA, Geta B, Ghafourifard M, Ghamari F, Ghashghaee A, Gholamian A, Gill TK, Goulart AC, Grada A, Grivna M, Mohialdeen Gubari MI, Guimarães RA, Guo Y, Gupta G, Haagsma JA, Hafezi-Nejad N, Bidgoli HH, Hall BJ, Hamadeh RR, Hamidi S, Haro JM, Hasan MM, Hasanzadeh A, Hassanipour S, Hassankhani H, Hassen HY, Havmoeller R, Hayat K, Hendrie D, Heydarpour F, Híjar M, Ho HC, Hoang CL, Hole MK, Holla R, Hossain N, Hosseinzadeh M, Hostiuc S, Hu G, Ibitoye SE, Ilesanmi OS, Ilic I, Ilic MD, Inbaraj LR, Indriasih E, Naghibi Irvani SS, Shariful Islam SM, Islam MM, Ivers RQ, Jacobsen KH, Jahani MA, Jahanmehr N, Jakovljevic M, Jalilian F, Jayaraman S, Jayatilleke AU, Jha RP, John-Akinola YO, Jonas JB, Joseph N, Joukar F, Jozwiak JJ, Jungari SB, Jürisson M, Kabir A, Kadel R, Kahsay A, Kalankesh LR, Kalhor R, Kamil TA, Kanchan T, Kapoor N, Karami M, Kasaeian A, Kassaye HG, Kavetskyy T, Kebede HK, Keiyoro PN, Kelbore AG, Kelkay B, Khader YS, Khafaie MA, Khalid N, Khalil IA, Khalilov R, Khammarnia M, Khan EA, Khan M, Khanna T, Khazaie H, Shadmani FK, Khundkar R, Kiirithio DN, Kim YE, Kim D, Kim YJ, Kisa A, Kisa S, Komaki H, M Kondlahalli SK, Korshunov VA, Koyanagi A, G Kraemer MU, Krishan K, Bicer BK, Kugbey N, Kumar V, Kumar N, Kumar GA, Kumar M, Kumaresh G, Kurmi OP, Kuti O, Vecchia C, Lami FH, Lamichhane P, Lang JJ, Lansingh VC, Laryea DO, Lasrado S, Latifi A, Lauriola P, Leasher JL, Huey Lee SW, Lenjebo TL, Levi M, Li S, Linn S, Liu X, Lopez AD, Lotufo PA, Lunevicius R, Lyons RA, Madadin M, El Razek MMA, Mahotra NB, Majdan M, Majeed A, Malagon-Rojas JN, Maled V, Malekzadeh R, Malta DC, Manafi N, Manafi A, Manda AL, Manjunatha N, Mansour-Ghanaei F, Mansouri B, Mansournia MA, Maravilla JC, March LM, Mason-Jones AJ, Masoumi SZ, Massenburg BB, Maulik PK, Meles GG, Melese A, Melketsedik ZA, N Memiah PT, Mendoza W, Menezes RG, Mengesha MB, Mengesha MM, Meretoja TJ, Meretoja A, Merie HE, Mestrovic T, Miazgowski B, Miazgowski T, Miller TR, Mini GK, Mirica A, Mirrakhimov EM, Mirzaei-Alavijeh M, Mithra P, Moazen B, Moghadaszadeh M, Mohamadi E, Mohammad Y, Mohammad KA, Darwesh AM, Gholi Mezerji NM, Mohammadian-Hafshejani A, Mohammadoo-Khorasani M, Mohammadpourhodki R, Mohammed S, Mohammed JA, Mohebi F, Molokhia M, Monasta L, Moodley Y, Moosazadeh M, Moradi M, Moradi G, Moradi-Lakeh M, Moradpour F, Morawska L, Velásquez IM, Morisaki N, Morrison SD, Mossie TB, Muluneh AG, Murthy S, Musa KI, Mustafa G, Nabhan AF, Nagarajan AJ, Naik G, Naimzada MD, Najafi F, Nangia V, Nascimento BR, Naserbakht M, Nayak V, Ndwandwe DE, Negoi I, Ngunjiri JW, Nguyen CT, Thi Nguyen HL, Nikbakhsh R, Anggraini Ningrum DN, Nnaji CA, Nyasulu PS, Ogbo FA, Oghenetega OB, Oh IH, Okunga EW, Olagunju AT, Olagunju TO, Bali AO, Onwujekwe OE, Asante KO, Orpana HM, Ota E, Otstavnov N, Otstavnov SS, A MP, Padubidri JR, Pakhale S, Pakshir K, Panda-Jonas S, Park EK, Patel SK, Pathak A, Pati S, Patton GC, Paulos K, Peden AE, Filipino Pepito VC, Pereira J, Pham HQ, Phillips MR, Pinheiro M, Polibin RV, Polinder S, Poustchi H, Prakash S, Angga Pribadi DR, Puri P, Syed ZQ, Rabiee M, Rabiee N, Radfar A, Rafay A, Rafiee A, Rafiei A, Rahim F, Rahimi S, Rahimi-Movaghar V, Rahman MA, Rajabpour-Sanati A, Rajati F, Rakovac I, Ranganathan K, Rao SJ, Rashedi V, Rastogi P, Rathi P, Rawaf S, Rawal L, Rawassizadeh R, Renjith V, N Renzaho AM, Resnikoff S, Rezapour A, Ribeiro AI, Rickard J, Rios González CM, Ronfani L, Roshandel G, Saad AM, Sabde YD, Sabour S, Saddik B, Safari S, Safari-Faramani R, Safarpour H, Safdarian M, Sajadi SM, Salamati P, Salehi F, Zahabi SS, Rashad Salem MR, Salem H, Salman O, Salz I, Samy AM, Sanabria J, Riera LS, Santric Milicevic MM, Sarker AR, Sarveazad A, Sathian B, Sawhney M, Sawyer SM, Saxena S, Sayyah M, Schwebel DC, Seedat S, Senthilkumaran S, Sepanlou SG, Seyedmousavi S, Sha F, Shaahmadi F, Shahabi S, Shaikh MA, Shams-Beyranvand M, Shamsizadeh M, Sharif-Alhoseini M, Sharifi H, Sheikh A, Shigematsu M, Shin JI, Shiri R, Siabani S, Sigfusdottir ID, Singh PK, Singh JA, Sinha DN, Smarandache CG, R Smith EU, Soheili A, Soleymani B, Soltanian AR, Soriano JB, Sorrie MB, Soyiri IN, Stein DJ, Stokes MA, Sufiyan MB, Rasul Suleria HA, Sykes BL, Tabarés-Seisdedos R, Tabb KM, Taddele BW, Tadesse DB, Tamiru AT, Tarigan IU, Tefera YM, Tehrani-Banihashemi A, Tekle MG, Tekulu GH, Tesema AK, Tesfay BE, Thapar R, Tilahune AB, Tlaye KG, Tohidinik HR, Topor-Madry R, Tran BX, Tran KB, Tripathy JP, Tsai AC, Car LT, Ullah S, Ullah I, Umar M, Unnikrishnan B, Upadhyay E, Uthman OA, Valdez PR, Vasankari TJ, Venketasubramanian N, Violante FS, Vlassov V, Waheed Y, Weldesamuel GT, Werdecker A, Wiangkham T, Wolde HF, Woldeyes DH, Wondafrash DZ, Wondmeneh TG, Wondmieneh AB, Wu AM, Yadav R, Yadollahpour A, Yano Y, Yaya S, Yazdi-Feyzabadi V, Yip P, Yisma E, Yonemoto N, Yoon SJ, Youm Y, Younis MZ, Yousefi Z, Yu Y, Yu C, Yusefzadeh H, Moghadam TZ, Zaidi Z, Zaman SB, Zamani M, Zamanian M, Zandian H, Zarei A, Zare F, Zhang ZJ, Zhang Y, Zodpey S, Dandona L, Dandona R, Degenhardt L, Dharmaratne SD, Hay SI, Mokdad AH, Reiner RC Jr, Sartorius B, and Vos T
Subjects: Humans, Incidence, Life Expectancy, Morbidity, Quality-Adjusted Life Years, Global Burden of Disease, Global Health, Wounds and Injuries mortality
Abstract: Background: Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries., Methods: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs)., Findings: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505)., Interpretation: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care., Competing Interests: Competing interests: Dr. James reports grants from Sanofi Pasteur, outside the submitted work. Dr. Driscoll reports grants from World Health Organization, during the conduct of the study. Dr. Ivers reports grants from National Health and Medical Research Council of Australia, during the conduct of the study. Dr. Jozwiak reports personal fees from TEVA, personal fees from ALAB, personal fees from BOEHRINGER INGELHEIM, personal fees from SYNEXUS, non-financial support from SERVIER, non-financial support from MICROLIFE, non-financial support from MEDICOVER, outside the submitted work. Dr. Rakovac reports grants from World Health Organization, during the conduct of the study. Dr Shariful Islam is funded by National Heart Foundation of Australia and Institute for Physical Activity and Nutrition, Deakin University. Dr. Sheikh reports grants from Health Data Research UK, outside the submitted work. Dr. Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Trio health, Medscape, WebMD, Clinical Care options, Clearview healthcare partners, Putnam associates, Spherix, Practice Point communications, the National Institutes of Health and the American College of Rheumatology, and Speaker’s bureau of Simply Speaking, owns stock options in Amarin pharmaceuticals and Viking pharmaceuticals, serves on the steering committee of OMERACT, an international organization that develops measures for clinical trials and receives arm’s length funding from 12 pharmaceutical companies, serves on the FDA Arthritis Advisory Committee, is a member of the Veterans Affairs Rheumatology Field Advisory Committee, and is the editor and the Director of the UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis, outside the submitted work. Dr. Stein reports personal fees from Lundbeck, personal fees from Sun, outside the submitted work. Dr. Degenhardt reports grants from Indivior, Seqirus, Reckitt Benckiser, outside the submitted work., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)
Published: 2020
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14. Burden of injury along the development spectrum: associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017.

Author: Haagsma JA, James SL, Castle CD, Dingels ZV, Fox JT, Hamilton EB, Liu Z, Lucchesi LR, Roberts NLS, Sylte DO, Adebayo OM, Ahmadi A, Ahmed MB, Aichour MTE, Alahdab F, Alghnam SA, Aljunid SM, Al-Raddadi RM, Alsharif U, Altirkawi K, Anjomshoa M, Antonio CAT, Appiah SCY, Aremu O, Arora A, Asayesh H, Assadi R, Awasthi A, Ayala Quintanilla BP, Balalla S, Banstola A, Barker-Collo SL, Bärnighausen TW, Bazargan-Hejazi S, Bedi N, Behzadifar M, Behzadifar M, Benjet C, Bennett DA, Bensenor IM, Bhaumik S, Bhutta ZA, Bijani A, Borges G, Borschmann R, Bose D, Boufous S, Brazinova A, Campuzano Rincon JC, Cárdenas R, Carrero JJ, Carvalho F, Castañeda-Orjuela CA, Catalá-López F, Choi JJ, Christopher DJ, Crowe CS, Dalal K, Daryani A, Davitoiu DV, Degenhardt L, De Leo D, De Neve JW, Deribe K, Dessie GA, deVeber GA, Dharmaratne SD, Doan LP, Dolan KA, Driscoll TR, Dubey M, El-Khatib Z, Ellingsen CL, El Sayed Zaki M, Endries AY, Eskandarieh S, Faro A, Fereshtehnejad SM, Fernandes E, Filip I, Fischer F, Franklin RC, Fukumoto T, Gezae KE, Gill TK, Goulart AC, Grada A, Guo Y, Gupta R, Haghparast Bidgoli H, Haj-Mirzaian A, Haj-Mirzaian A, Hamadeh RR, Hamidi S, Haro JM, Hassankhani H, Hassen HY, Havmoeller R, Hendrie D, Henok A, Híjar M, Hole MK, Homaie Rad E, Hossain N, Hostiuc S, Hu G, Igumbor EU, Ilesanmi OS, Irvani SSN, Islam SMS, Ivers RQ, Jacobsen KH, Jahanmehr N, Jakovljevic M, Jayatilleke AU, Jha RP, Jonas JB, Jorjoran Shushtari Z, Jozwiak JJ, Jürisson M, Kabir A, Kalani R, Kasaeian A, Kelbore AG, Kengne AP, Khader YS, Khafaie MA, Khalid N, Khan EA, Khoja AT, Kiadaliri AA, Kim YE, Kim D, Kisa A, Koyanagi A, Kuate Defo B, Kucuk Bicer B, Kumar M, Lalloo R, Lam H, Lami FH, Lansingh VC, Leasher JL, Li S, Linn S, Lunevicius R, Machado FR, Magdy Abd El Razek H, Magdy Abd El Razek M, Mahotra NB, Majdan M, Majeed A, Malekzadeh R, Malik MA, Malta DC, Manda AL, Mansournia MA, Massenburg BB, Maulik PK, Meheretu HAA, Mehndiratta MM, Melese A, Mendoza W, Mengesha MM, Meretoja TJ, Meretoja A, Mestrovic T, Miazgowski T, Miller TR, Mini GK, Mirrakhimov EM, Moazen B, Mohammad Gholi Mezerji N, Mohammadibakhsh R, Mohammed S, Molokhia M, Monasta L, Mondello S, Montero-Zamora PA, Moodley Y, Moosazadeh M, Moradi G, Moradi-Lakeh M, Morawska L, Velásquez IM, Morrison SD, Moschos MM, Mousavi SM, Murthy S, Musa KI, Naik G, Najafi F, Nangia V, Nascimento BR, Ndwandwe DE, Negoi I, Nguyen TH, Nguyen SH, Nguyen LH, Nguyen HLT, Ningrum DNA, Nirayo YL, Ofori-Asenso R, Ogbo FA, Oh IH, Oladimeji O, Olagunju AT, Olagunju TO, Olivares PR, Orpana HM, Otstavnov SS, P A M, Pakhale S, Park EK, Patton GC, Pesudovs K, Phillips MR, Polinder S, Prakash S, Radfar A, Rafay A, Rafiei A, Rahimi S, Rahimi-Movaghar V, Rahman MA, Rai RK, Ramezanzadeh K, Rawaf S, Rawaf DL, Renzaho AMN, Resnikoff S, Rezaeian S, Roever L, Ronfani L, Roshandel G, Sabde YD, Saddik B, Salamati P, Salimi Y, Salz I, Samy AM, Sanabria J, Sanchez Riera L, Santric Milicevic MM, Satpathy M, Sawhney M, Sawyer SM, Saxena S, Saylan M, Schneider IJC, Schwebel DC, Seedat S, Sepanlou SG, Shaikh MA, Shams-Beyranvand M, Shamsizadeh M, Sharif-Alhoseini M, Sheikh A, Shen J, Shigematsu M, Shiri R, Shiue I, Silva JP, Singh JA, Sinha DN, Soares Filho AM, Soriano JB, Soshnikov S, Soyiri IN, Starodubov VI, Stein DJ, Stokes MA, Sufiyan MB, Sunshine JE, Sykes BL, Tabarés-Seisdedos R, Tabb KM, Tehrani-Banihashemi A, Tessema GA, Thakur JS, Tran KB, Tran BX, Tudor Car L, Uthman OA, Uzochukwu BSC, Valdez PR, Varavikova E, Vasconcelos AMN, Venketasubramanian N, Violante FS, Vlassov V, Waheed Y, Wang YP, Wijeratne T, Winkler AS, Yadav P, Yano Y, Yenesew MA, Yip P, Yisma E, Yonemoto N, Younis MZ, Yu C, Zafar S, Zaidi Z, Zaman SB, Zamani M, Zhao Y, Zodpey S, Hay SI, Lopez AD, Mokdad AH, and Vos T
Subjects: Adolescent, Global Health, Humans, Life Expectancy, Disabled Persons, Global Burden of Disease, Quality-Adjusted Life Years, Wounds and Injuries
Abstract: Background: The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates., Methods: Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate., Results: For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced., Conclusions: The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum., Competing Interests: Competing interests: Dr. Carl Abelardo T Antonio reports personal fees from Johnson & Johnson (Philippines), Inc., outside the submitted work. Dr. Jasvinder Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Medscape, WebMD, Clinical Care options, Clearview healthcare partners, Putnam associates, Spherix, the National Institutes of Health and the American College of Rheumatology, stock options in Amarin pharmaceuticals and Viking pharmaceuticals, participating in the steering committee of OMERACT, an international organization that develops measures for clinical trials and receives arm’s length funding from 12 pharmaceutical companies, including Amgen, Janssen, Novartis, Roche, UCB Group, Ardea/Astra Zeneca, Bristol Myers Squibb, Celgene, EliLilly, Horizon Pharma, Pfizer, and Centrexion. Dr. Josep Maria Haro reports personal fees from Roche and Lundbeck, and that the institute for which they work provides services to Eli Lilly and Co., outside the submitted work. Dr. Mete Saylan is an employee of Bayer AG, outside the submitted work. Dr Sheikh Mohammed Shariful Islam is funded by National Heart Foundation of Australia and supported by a senior research fellowship from Deakin University, outside the submitted work. Dr. Spencer James reports grants from Sanofi Pasteur, outside the submitted work., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)
Published: 2020
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15. The need to focus on medical education in rural districts of India.

Author: Brahmapurkar KP, Zodpey SP, Sabde YD, and Brahmapurkar VK
Subjects: Education, Medical statistics & numerical data, India, Schools, Medical organization & administration, Education, Medical organization & administration, Health Workforce statistics & numerical data, Medically Underserved Area, Rural Population statistics & numerical data, Schools, Medical statistics & numerical data
Abstract: Background: . Globally, India has the highest number of medical colleges followed by Brazil and China. The density of physicians in rural India was 3 per 10 000 population against 13 per 10 000 in urban areas. Worldwide, studies show that medical schools play an important role in overcoming the shortage of physicians locally. Hence, we studied the distribution of medical colleges in India and reviewed the shortage of established and new medical colleges in rural districts with the year 2000 as baseline., Methods: . We used the database of the Medical Council of India as on 27 April 2017; and Census 2011 data, based on the percentage of rural/urban population, for the classification of districts (rural/urban). All the 640 districts were included with 1210.9 million population., Results: . Of the 480 rural districts in India, only 132 (27.5%) had a medical college. Jharkhand, Jammu and Kashmir and Arunachal Pradesh had no medical colleges in rural districts. Madhya Pradesh, Uttar Pradesh, Bihar, Assam, Punjab, Uttarakhand, Haryana and Rajasthan had <30% of rural districts with a medical college. Of the 286 new medical colleges established since 2000 in India, 130 (45.5%) were in rural districts with uneven distribution with lower percentage of new medical colleges in states with predominance of rural population., Conclusion: . There is an overall shortage of medical colleges in rural districts of India. Paradoxically, the trend of uneven rural-urban distribution continues among the newly opened medical colleges as well., Competing Interests: None
Published: 2018
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16. Treatment of pediatric diarrhea: a simulated client study at private pharmacies of Ujjain, Madhya Pradesh, India.

Author: Diwan V, Sabde YD, Byström E, and De Costa A
Subjects: Adult, Child, Preschool, Cross-Sectional Studies, Female, Humans, India, Infant, Male, Urban Population, Anti-Bacterial Agents therapeutic use, Diarrhea drug therapy, Drug Utilization, Guideline Adherence, Health Services Research, Pharmacies
Abstract: Introduction: In low- and middle-income countries such as India, private pharmacies play an important role in medical treatments, offering advice for common illnesses such as diarrhea and respiratory tract infections. There is a need to explore the details of the dispensing practices at the private pharmacies in low- and middle-income countries., Methodology: The present study used simulated client methodology to assess the actual dispensing practices for patients with pediatric diarrhea at private pharmacies in an urban setting of an Indian province., Results: This study identified 164 private pharmacies (84.10%) in the study setting that engaged in the practice of dispensing prescription drugs without prescriptions. Only about 40% asked clients if they had a prescription from a doctor. The average duration of consultations at the pharmacies was 1.3 minutes (range, 0.5-6 minutes). The dispensing of drugs was not in compliance with the recommended guidelines and regulations. The most commonly dispensed drugs were antibiotics (40.24%); of these, quinolones either alone or in combination with imidazoles were the most frequently dispensed. The other commonly dispensed drugs were antimotility drugs (31.10%) and Lactobacillus acidophilus (probiotics; 23.17%). The drugs were dispensed in inappropriate doses due to the absence of indications., Conclusions: Overuse and misuse of all these prescription drugs dispensed by pharmacies pose significant issues, such as resistance, dangerous side effects, and high costs. At the same time, the pharmacies did not dispense recommended drugs such as oral rehydration solution and zinc, which they are authorized to dispense without a prescription.
Published: 2015
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17. Mapping private pharmacies and their characteristics in Ujjain district, Central India.

Author: Sabde YD, Diwan V, Saraf VS, Mahadik VK, Diwan VK, and De Costa A
Subjects: Cross-Sectional Studies, Geographic Information Systems, India, Rural Health Services, Urban Health Services, Ownership, Pharmaceutical Services supply & distribution, Private Sector, Professional Practice Location
Abstract: Background: In India, private pharmacies are ubiquitous yet critical establishments that facilitate community access to medicines. These are often the first points of treatment seeking in parts of India and other low income settings around the world. The characteristics of these pharmacies including their location, drug availability, human resources and infrastructure have not been studied before. Given the ubiquity and popularity of private pharmacies in India, such information would be useful to harness the potential of these pharmacies to deliver desirable public health outcomes, to facilitate regulation and to involve in initiatives pertaining to rational drug use. This study was a cross sectional survey that mapped private pharmacies in one district on a geographic information system and described relevant characteristics of these units., Methods: This study of pharmacies was a part of larger cross sectional survey carried out to map all the health care providers in Ujjain district (population 1.9 million), Central India, on a geographic information system. Their location vis-à-vis formal providers of health services were studied. Other characteristics like human resources, infrastructure, clients and availability of tracer drugs were also surveyed., Results: A total 475 private pharmacies were identified in the district. Three-quarter were in urban areas, where they were concentrated around physician practices. In rural areas, pharmacies were located along the main roads. A majority of pharmacies simultaneously retailed medicines from multiple systems of medicine. Tracer parenteral antibiotics and injectable steroids were available in 83.7% and 88.7% pharmacies respectively. The proportion of clients without prescription was 39.04%. Only 11.58% of staff had formal pharmacist qualifications. Power outages were a significant challenge., Conclusion: This is the first mapping of pharmacies & their characteristics in India. It provides evidence of the urban dominance and close relationship between healthcare provider location and pharmacy location. The implications of this relationship are discussed. The study reports a lack of qualified staff in the presence of a high proportion of clients attending without a prescription. The study highlights the need for the better implementation of regulation. Besides facilitating regulation & partnerships, the data also provides a sampling frame for future interventional studies on these pharmacies.
Published: 2011
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18. A Study of Morbidity Pattern in Street Sweepers: A Cross-sectional Study.

Author: Sabde YD and Zodpey SP
Abstract: Background: Street sweepers play an important role in maintaining the health and hygiene within the cities. This job exposes the street sweepers to a variety of risk factors such as dust, toxins and diesel exhaust pollution, which make them vulnerable to develop certain occupational diseases. Therefore, it was thought necessary to study the morbidity profile in this occupational group., Objectives: To study the prevalence of morbidities among street sweepers and comparison group., Study Design: A cross-sectional study with a comparison group., Study Setting: Nagpur Municipal Corporation, Nagpur., Subjects: THE STUDY INCLUDED TWO GROUPS: (1) A study group comprising 273 street sweepers. (2) A comparison group comprising 142 class IV workers working in the office buildings of Nagpur Municipal Corporation, Nagpur., Materials and Methods: A pretested proforma was used to record the necessary information such as clinical history, sociodemographic factors, findings of clinical examination and investigations performed., Results and Conclusions: THE IMPORTANT MORBIDITIES DETECTED AMONG STREET SWEEPERS WERE THE FOLLOWING: anemia (20.5%), hypertension (9.5%), upper respiratory tract infections (URTI) (7.3%) and chronic bronchitis (5.9%). In the comparison group, important morbidities detected were the following: anemia (20.4%), hypertension (11.3%), hyperacidity (9.9%), URTI (7.0%) and refractive error (7.0%). Chronic bronchitis was detected in two subjects (1.4%) of the comparison group. The prevalence of chronic bronchitis was significantly high among street sweepers than that of subjects of the comparison group. Therefore, it is recommended that further studies with a larger sample size be undertaken to identify the factors responsible for higher prevalence of chronic bronchitis among the street sweepers.
Published: 2008
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18 results on '"Sabde, YD"'

1. Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017

2. Burden of injury along the development spectrum: associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017

3. Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

4. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016

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

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

7. 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

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

9. Association of tobacco use with the tobacco-related built environment: an ecological study from urban slums of Bhopal, India.

10. Prevalence of chronic kidney disease among severely gas-exposed survivors in Bhopal, India.

11. Evaluation of health impacts of the improved housing conditions on under-five children in the socioeconomically underprivileged families in central India: A 1-year follow-up study protocol.

12. A mixed-methods community-based participatory research to explore stakeholder's perspectives and to quantify the effect of crop residue burning on air and human health in Central India: study protocol.

13. Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017.

14. Burden of injury along the development spectrum: associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017.

15. The need to focus on medical education in rural districts of India.

16. Treatment of pediatric diarrhea: a simulated client study at private pharmacies of Ujjain, Madhya Pradesh, India.

17. Mapping private pharmacies and their characteristics in Ujjain district, Central India.

18. A Study of Morbidity Pattern in Street Sweepers: A Cross-sectional Study.

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