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2. Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020
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Bryazka, D, Reitsma, MB, Griswold, MG, Abate, KH, Abbafati, C, Kangevari, MA, Kangevari, ZA, Abdoli, A, Abdollahi, M, Abdullah, AYM, Abhilash, ES, Abu Gharbieh, E, Acuna, JM, Addolorato, G, Adebayo, OM, Adekanmbi, V, Adhikari, K, Adhikari, S, Adnani, QES, Afzal, S, Agegnehu, WY, Aggarwal, M, Ahinkorah, BO, Ahmad, AR, Ahmad, S, Ahmad, T, Ahmadi, A, Ahmadi, S, Ahmed, H, Rashid, TA, Akunna, CJ, Al Hamad, H, Alam, MZ, Alem, DT, Alene, KA, Alimohamadi, Y, Alizadeh, A, Allel, K, Alonso, J, Alvand, S, Guzman, NA, Amare, F, Ameyaw, EK, Amiri, S, Ancuceanu, R, Anderson, JA, Andrei, CL, Andrei, T, Arabloo, J, Arshad, M, Artamonov, AA, Aryan, Z, Asaad, M, Asemahagn, MA, Burt, TA, Athari, SS, Atnafu, DD, Atorkey, P, Atreya, A, Ausloos, F, Ausloos, M, Ayano, G, Ayanore, MA, Ayinde, OO, Mateos, JLA, Azadnajafabad, S, Azanaw, MM, Khyavy, MA, Jafari, AA, Azzam, AY, Badiye, AD, Bagheri, N, Bagherieh, S, Bairwa, M, Bakkannavar, SM, Bakshi, RK, Balchut, AH, Null, T, Barra, F, Barrow, A, Baskaran, P, Belo, L, Bennett, DA, Bensenor, IM, Bhagavathula, AS, Bhala, N, Bhalla, A, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhattacharyya, K, Bhojaraja, VS, Bintoro, BS, Blokhina, EAE, Bodicha, BBA, Boloor, A, Bosetti, C, Braithwaite, D, Brenner, H, Briko, NI, Brunoni, AR, Butt, ZA, Cao, C, Cao, Y, Cardenas, R, Carvalho, AF, Carvalho, M, Maia, JMC, Castelpietra, G, de Araujo, LFSC, Cattaruzza, MS, Chakraborty, PA, Charan, J, Chattu, VK, Chaurasia, A, Cherbuin, N, Dinh, TC, Chudal, N, Chung, SC, Churko, C, Ciobanu, LG, Cirillo, M, Claro, RM, Costanzo, S, Cowden, RG, Criqui, MH, Martins, NC, Culbreth, GT, Dachew, BA, Dadras, O, Dai, X, Damiani, G, Dandona, L, Dandona, R, Daniel, BD, Danielewicz, A, Gela, JD, Davletov, K, de Araujo, JAP, de Sa Junior, AR, Debela, SA, Dehghan, A, Demetriades, AK, Molla, MD, Desai, R, Desta, AA, da Silva, DD, Diaz, D, Digesa, LE, Diress, M, Dodangeh, M, Dongarwar, D, Dorostkar, F, Dsouza, HL, Duko, B, Duncan, BB, Edvardsson, K, Ekholuenetale, M, Elgar, FJ, Elhadi, M, Elmonem, MA, Endries, AY, Eskandarieh, S, Etemadimanesh, A, Fagbamigbe, AF, Fakhradiyev, IR, Farahmand, F, Sa Farinha, CSE, Faro, A, Farzadfar, F, Fatehizadeh, A, Fauk, NK, Feigin, VL, Feldman, R, Feng, X, Fentaw, Z, Ferrero, S, Desideri, LF, Filip, I, Fischer, F, Francis, JM, Franklin, RC, Gaal, PA, Gad, MM, Gallus, S, Galvano, F, Ganesan, B, Garg, T, Gebrehiwot, MGD, Gebremeskel, TG, Gebremichael, MA, Gemechu, TR, Getacher, L, Getachew, ME, Obsa, AG, Getie, A, Ghaderi, A, Ghafourifard, M, Ghajar, A, Ghamari, SH, Ghandour, LA, Nour, MG, Ghashghaee, A, Ghozy, S, Glozah, FN, Glushkova, EV, Godos, J, Goel, A, Goharinezhad, S, Golechha, M, Goleij, P, Golitaleb, M, Greaves, F, Grivna, M, Grosso, G, Gudayu, TW, Gupta, B, Gupta, R, Gupta, S, Gupta, VB, Gupta, VK, Nejad, NH, Mirzaian, AH, Hall, BJ, Halwani, R, Handiso, TB, Hankey, GJ, Hariri, S, Haro, JM, Hasaballah, A, Moghaddam, HH, Hay, S, Hayat, K, Heidari, G, Heidari, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hlongwa, MM, Holla, R, Hossain, MM, Hossain, S, Hosseini, SK, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, G, Huang, J, Hussain, S, Ibitoye, SE, Ilic, IM, Ilic, MD, Immurana, M, Irham, LM, Islam, MM, Islam, RM, Islam, SMS, Iso, H, Itumalla, R, Iwagami, M, Jabbarinejad, R, Jacob, L, Jakovljevic, M, Jamalpoor, Z, Jamshidi, E, Jayapal, SK, Jayarajah, UU, Jayawardena, R, Jebai, R, Jeddi, SA, Jema, AT, Jha, RP, Jindal, HA, Jonas, JB, Joo, T, Joseph, N, Joukar, F, Jozwiak, JJ, Jurisson, M, Kabir, A, Kabthymer, RH, Kamble, BD, Kandel, H, Kanno, GG, Kapoor, N, Karaye, IM, Karimi, SE, Kassa, BG, Kaur, RJ, Kayode, GA, Keykhaei, M, Khajuria, H, Khalilov, R, Khan, IA, Ab Khan, M, Kim, H, Kim, J, Kim, MS, Kimokoti, RW, Kivimaki, M, Klymchuk, V, Knudsen, AKS, Kolahi, AA, Korshunov, VA, Koyanagi, A, Krishan, K, Krishnamoorthy, Y, Kumar, GA, Kumar, N, Ben, L, Lallukka, T, Lasrado, S, Lau, J, Lee, SW, Lee, WC, Lee, YH, Lim, LL, Lim, SS, Lobo, SW, Lopukhov, PD, Lorkowski, S, Lozano, R, Lucchetti, G, Madadizadeh, F, Mahjoub, S, Mahmoodpoor, A, Mahumud, RA, Makki, A, Malekpour, MR, Manjunatha, N, Mansouri, B, Mansournia, MA, Raga, JM, Villa, FAM, Matzopoulos, R, Maulik, PK, Mayeli, M, McGrath, JJ, Meena, JK, Nasab, EM, Menezes, RG, Mensink, GBM, Mentis, AFA, Meretoja, A, Merga, BT, Mestrovic, T, Jonasson, JM, Miazgowski, B, de Sa, ACMGN, Miller, TR, Mini, G, Mirica, A, Mirijello, A, Mirmoeeni, S, Mirrakhimov, EM, Misra, S, Moazen, B, Mobarakabadi, M, Moccia, M, Mohammad, Y, Mohammadi, E, Hafshejani, AM, Mohammed, TA, Moka, N, Mokdad, AH, Momtazmanesh, S, Moradi, Y, Mostafavi, E, Mubarik, S, Mullany, EC, Mulugeta, BT, Zamora, EM, Murray, CJL, Mwita, JC, Naghavi, M, Naimzada, MD, Nangia, V, Nayak, BP, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nepal, S, Neupane, SPP, Kandel, SN, Nigatu, YT, Nowroozi, A, Nuruzzaman, KM, Nzoputam, CI, Obamiro, KO, Ogbo, FA, Oguntade, AS, Aliabad, HO, Olakunde, BO, Oliveira, GMM, Bali, AO, Omer, E, Altamirano, DVO, Otoiu, A, Otstavnov, SS, Oumer, B, Mahesh, PA, Monedero, AP, Palladino, R, Pana, A, Jonas, SP, Pandey, A, Pardhan, S, Parekh, T, Park, EK, Parry, CDH, Kan, FP, Patel, J, Pati, S, Patton, GC, Paudel, U, Pawar, S, Peden, AE, Petcu, IR, Phillips, MR, Pinheiro, M, Plotnikov, E, Pradhan, PMS, Prashant, A, Quan, J, Radfar, A, Rafiei, A, Raghav, PR, Movaghar, VR, Rahman, A, Rahman, MM, Rahman, M, Rahmani, AM, Rahmani, S, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rasali, DP, Rashidi, MM, Ratan, ZA, Rawaf, DL, Rawaf, S, Rawal, L, Renzaho, AMN, Rezaei, N, Rezaei, S, Rezaeian, M, Riahi, SM, Rodriguez, ER, Roth, GA, Rwegerera, GM, Saddik, B, Sadeghi, E, Sadeghian, R, Saeed, U, Saeedi, F, Sagar, R, Sahebkar, A, Sahoo, H, Sahraian, MA, Rahman, KSU, Salahi, S, Salimzadeh, H, Samy, AM, Sanmarchi, F, Milicevic, MMS, Sarikhani, Y, Sathian, B, Saya, GK, Sayyah, M, Schmidt, MI, Schutte, AE, Schwarzinger, M, Schwebel, DC, Seidu, AA, Kumar, NS, SeyedAlinaghi, S, Seylani, A, Sha, F, Shahin, S, Sanavi, FS, Shahrokhi, S, Shaikh, MA, Shaker, E, Shakhmardanov, MZ, Beyranvand, MS, Sheikhbahaei, S, Sheikhi, RA, Shetty, A, Shetty, JK, Shiferaw, DS, Shigematsu, M, Shiri, R, Shirkoohi, R, Shivakumar, KM, Shivarov, V, Shobeiri, P, Shrestha, R, Sidemo, NB, Sigfusdottir, ID, Silva, DAS, da Silva, NT, Singh, JA, Singh, S, Skryabin, VY, Skryabina, AA, Sleet, DA, Solmi, M, Solomon, Y, Song, S, Song, Y, Sorensen, RJD, Soshnikov, S, Soyiri, IN, Stein, DJ, Subba, SH, Szocska, M, Seisdedos, RT, Tabuchi, T, Taheri, M, Tan, KK, Tareke, M, Tarkang, EE, Temesgen, G, Temesgen, WA, Temsah, MH, Thankappan, KR, Thapar, R, Thomas, NK, Tiruneh, C, Todorovic, J, Torrado, M, Touvier, M, Palone, MRT, Mai, TNT, Llimos, ST, Tripathy, JP, Vakilian, A, Valizadeh, R, Varmaghani, M, Varthya, SB, Vasankari, TJ, Vos, T, Wagaye, B, Waheed, Y, Walde, MT, Wang, C, Wang, Y, Wang, YP, Westerman, R, Wickramasinghe, ND, Wubetu, AD, Xu, S, Yamagishi, K, Yang, L, Yesera, GEE, Yigit, A, Yigit, V, Yimaw, AE, Yon, DK, Yonemoto, N, Yu, C, Zadey, S, Zahir, M, Zare, I, Zastrozhin, MS, Zastrozhina, A, Zhang, ZJ, Zhong, C, Zmaili, M, Zuniga, YMH, Gakidou, E, Madureira-Carvalho, AM, Bryazka, D, Reitsma, MB, Griswold, MG, Abate, KH, Abbafati, C, Kangevari, MA, Kangevari, ZA, Abdoli, A, Abdollahi, M, Abdullah, AYM, Abhilash, ES, Abu Gharbieh, E, Acuna, JM, Addolorato, G, Adebayo, OM, Adekanmbi, V, Adhikari, K, Adhikari, S, Adnani, QES, Afzal, S, Agegnehu, WY, Aggarwal, M, Ahinkorah, BO, Ahmad, AR, Ahmad, S, Ahmad, T, Ahmadi, A, Ahmadi, S, Ahmed, H, Rashid, TA, Akunna, CJ, Al Hamad, H, Alam, MZ, Alem, DT, Alene, KA, Alimohamadi, Y, Alizadeh, A, Allel, K, Alonso, J, Alvand, S, Guzman, NA, Amare, F, Ameyaw, EK, Amiri, S, Ancuceanu, R, Anderson, JA, Andrei, CL, Andrei, T, Arabloo, J, Arshad, M, Artamonov, AA, Aryan, Z, Asaad, M, Asemahagn, MA, Burt, TA, Athari, SS, Atnafu, DD, Atorkey, P, Atreya, A, Ausloos, F, Ausloos, M, Ayano, G, Ayanore, MA, Ayinde, OO, Mateos, JLA, Azadnajafabad, S, Azanaw, MM, Khyavy, MA, Jafari, AA, Azzam, AY, Badiye, AD, Bagheri, N, Bagherieh, S, Bairwa, M, Bakkannavar, SM, Bakshi, RK, Balchut, AH, Null, T, Barra, F, Barrow, A, Baskaran, P, Belo, L, Bennett, DA, Bensenor, IM, Bhagavathula, AS, Bhala, N, Bhalla, A, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhattacharyya, K, Bhojaraja, VS, Bintoro, BS, Blokhina, EAE, Bodicha, BBA, Boloor, A, Bosetti, C, Braithwaite, D, Brenner, H, Briko, NI, Brunoni, AR, Butt, ZA, Cao, C, Cao, Y, Cardenas, R, Carvalho, AF, Carvalho, M, Maia, JMC, Castelpietra, G, de Araujo, LFSC, Cattaruzza, MS, Chakraborty, PA, Charan, J, Chattu, VK, Chaurasia, A, Cherbuin, N, Dinh, TC, Chudal, N, Chung, SC, Churko, C, Ciobanu, LG, Cirillo, M, Claro, RM, Costanzo, S, Cowden, RG, Criqui, MH, Martins, NC, Culbreth, GT, Dachew, BA, Dadras, O, Dai, X, Damiani, G, Dandona, L, Dandona, R, Daniel, BD, Danielewicz, A, Gela, JD, Davletov, K, de Araujo, JAP, de Sa Junior, AR, Debela, SA, Dehghan, A, Demetriades, AK, Molla, MD, Desai, R, Desta, AA, da Silva, DD, Diaz, D, Digesa, LE, Diress, M, Dodangeh, M, Dongarwar, D, Dorostkar, F, Dsouza, HL, Duko, B, Duncan, BB, Edvardsson, K, Ekholuenetale, M, Elgar, FJ, Elhadi, M, Elmonem, MA, Endries, AY, Eskandarieh, S, Etemadimanesh, A, Fagbamigbe, AF, Fakhradiyev, IR, Farahmand, F, Sa Farinha, CSE, Faro, A, Farzadfar, F, Fatehizadeh, A, Fauk, NK, Feigin, VL, Feldman, R, Feng, X, Fentaw, Z, Ferrero, S, Desideri, LF, Filip, I, Fischer, F, Francis, JM, Franklin, RC, Gaal, PA, Gad, MM, Gallus, S, Galvano, F, Ganesan, B, Garg, T, Gebrehiwot, MGD, Gebremeskel, TG, Gebremichael, MA, Gemechu, TR, Getacher, L, Getachew, ME, Obsa, AG, Getie, A, Ghaderi, A, Ghafourifard, M, Ghajar, A, Ghamari, SH, Ghandour, LA, Nour, MG, Ghashghaee, A, Ghozy, S, Glozah, FN, Glushkova, EV, Godos, J, Goel, A, Goharinezhad, S, Golechha, M, Goleij, P, Golitaleb, M, Greaves, F, Grivna, M, Grosso, G, Gudayu, TW, Gupta, B, Gupta, R, Gupta, S, Gupta, VB, Gupta, VK, Nejad, NH, Mirzaian, AH, Hall, BJ, Halwani, R, Handiso, TB, Hankey, GJ, Hariri, S, Haro, JM, Hasaballah, A, Moghaddam, HH, Hay, S, Hayat, K, Heidari, G, Heidari, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hlongwa, MM, Holla, R, Hossain, MM, Hossain, S, Hosseini, SK, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, G, Huang, J, Hussain, S, Ibitoye, SE, Ilic, IM, Ilic, MD, Immurana, M, Irham, LM, Islam, MM, Islam, RM, Islam, SMS, Iso, H, Itumalla, R, Iwagami, M, Jabbarinejad, R, Jacob, L, Jakovljevic, M, Jamalpoor, Z, Jamshidi, E, Jayapal, SK, Jayarajah, UU, Jayawardena, R, Jebai, R, Jeddi, SA, Jema, AT, Jha, RP, Jindal, HA, Jonas, JB, Joo, T, Joseph, N, Joukar, F, Jozwiak, JJ, Jurisson, M, Kabir, A, Kabthymer, RH, Kamble, BD, Kandel, H, Kanno, GG, Kapoor, N, Karaye, IM, Karimi, SE, Kassa, BG, Kaur, RJ, Kayode, GA, Keykhaei, M, Khajuria, H, Khalilov, R, Khan, IA, Ab Khan, M, Kim, H, Kim, J, Kim, MS, Kimokoti, RW, Kivimaki, M, Klymchuk, V, Knudsen, AKS, Kolahi, AA, Korshunov, VA, Koyanagi, A, Krishan, K, Krishnamoorthy, Y, Kumar, GA, Kumar, N, Ben, L, Lallukka, T, Lasrado, S, Lau, J, Lee, SW, Lee, WC, Lee, YH, Lim, LL, Lim, SS, Lobo, SW, Lopukhov, PD, Lorkowski, S, Lozano, R, Lucchetti, G, Madadizadeh, F, Mahjoub, S, Mahmoodpoor, A, Mahumud, RA, Makki, A, Malekpour, MR, Manjunatha, N, Mansouri, B, Mansournia, MA, Raga, JM, Villa, FAM, Matzopoulos, R, Maulik, PK, Mayeli, M, McGrath, JJ, Meena, JK, Nasab, EM, Menezes, RG, Mensink, GBM, Mentis, AFA, Meretoja, A, Merga, BT, Mestrovic, T, Jonasson, JM, Miazgowski, B, de Sa, ACMGN, Miller, TR, Mini, G, Mirica, A, Mirijello, A, Mirmoeeni, S, Mirrakhimov, EM, Misra, S, Moazen, B, Mobarakabadi, M, Moccia, M, Mohammad, Y, Mohammadi, E, Hafshejani, AM, Mohammed, TA, Moka, N, Mokdad, AH, Momtazmanesh, S, Moradi, Y, Mostafavi, E, Mubarik, S, Mullany, EC, Mulugeta, BT, Zamora, EM, Murray, CJL, Mwita, JC, Naghavi, M, Naimzada, MD, Nangia, V, Nayak, BP, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nepal, S, Neupane, SPP, Kandel, SN, Nigatu, YT, Nowroozi, A, Nuruzzaman, KM, Nzoputam, CI, Obamiro, KO, Ogbo, FA, Oguntade, AS, Aliabad, HO, Olakunde, BO, Oliveira, GMM, Bali, AO, Omer, E, Altamirano, DVO, Otoiu, A, Otstavnov, SS, Oumer, B, Mahesh, PA, Monedero, AP, Palladino, R, Pana, A, Jonas, SP, Pandey, A, Pardhan, S, Parekh, T, Park, EK, Parry, CDH, Kan, FP, Patel, J, Pati, S, Patton, GC, Paudel, U, Pawar, S, Peden, AE, Petcu, IR, Phillips, MR, Pinheiro, M, Plotnikov, E, Pradhan, PMS, Prashant, A, Quan, J, Radfar, A, Rafiei, A, Raghav, PR, Movaghar, VR, Rahman, A, Rahman, MM, Rahman, M, Rahmani, AM, Rahmani, S, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rasali, DP, Rashidi, MM, Ratan, ZA, Rawaf, DL, Rawaf, S, Rawal, L, Renzaho, AMN, Rezaei, N, Rezaei, S, Rezaeian, M, Riahi, SM, Rodriguez, ER, Roth, GA, Rwegerera, GM, Saddik, B, Sadeghi, E, Sadeghian, R, Saeed, U, Saeedi, F, Sagar, R, Sahebkar, A, Sahoo, H, Sahraian, MA, Rahman, KSU, Salahi, S, Salimzadeh, H, Samy, AM, Sanmarchi, F, Milicevic, MMS, Sarikhani, Y, Sathian, B, Saya, GK, Sayyah, M, Schmidt, MI, Schutte, AE, Schwarzinger, M, Schwebel, DC, Seidu, AA, Kumar, NS, SeyedAlinaghi, S, Seylani, A, Sha, F, Shahin, S, Sanavi, FS, Shahrokhi, S, Shaikh, MA, Shaker, E, Shakhmardanov, MZ, Beyranvand, MS, Sheikhbahaei, S, Sheikhi, RA, Shetty, A, Shetty, JK, Shiferaw, DS, Shigematsu, M, Shiri, R, Shirkoohi, R, Shivakumar, KM, Shivarov, V, Shobeiri, P, Shrestha, R, Sidemo, NB, Sigfusdottir, ID, Silva, DAS, da Silva, NT, Singh, JA, Singh, S, Skryabin, VY, Skryabina, AA, Sleet, DA, Solmi, M, Solomon, Y, Song, S, Song, Y, Sorensen, RJD, Soshnikov, S, Soyiri, IN, Stein, DJ, Subba, SH, Szocska, M, Seisdedos, RT, Tabuchi, T, Taheri, M, Tan, KK, Tareke, M, Tarkang, EE, Temesgen, G, Temesgen, WA, Temsah, MH, Thankappan, KR, Thapar, R, Thomas, NK, Tiruneh, C, Todorovic, J, Torrado, M, Touvier, M, Palone, MRT, Mai, TNT, Llimos, ST, Tripathy, JP, Vakilian, A, Valizadeh, R, Varmaghani, M, Varthya, SB, Vasankari, TJ, Vos, T, Wagaye, B, Waheed, Y, Walde, MT, Wang, C, Wang, Y, Wang, YP, Westerman, R, Wickramasinghe, ND, Wubetu, AD, Xu, S, Yamagishi, K, Yang, L, Yesera, GEE, Yigit, A, Yigit, V, Yimaw, AE, Yon, DK, Yonemoto, N, Yu, C, Zadey, S, Zahir, M, Zare, I, Zastrozhin, MS, Zastrozhina, A, Zhang, ZJ, Zhong, C, Zmaili, M, Zuniga, YMH, Gakidou, E, and Madureira-Carvalho, AM
- Abstract
BACKGROUND: The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year. METHODS: For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol. FINDINGS: The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male. INTERPRETATION: There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attribu
- Published
- 2022
3. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
- Author
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Kyu, Hh, Abate, D, Abate, Kh, Abay, Sm, Abbafati, C, Abbasi, N, Abbastabar, H, Abd-Allah, F, Abdela, J, Abdelalim, A, Abdollahpour, I, Abdulkader, Rs, Abebe, M, Abebe, Z, Abil, Oz, Aboyans, V, Abrham, Ar, Abu-Raddad, Lj, Abu-Rmeileh, Nme, Accrombessi, Mmk, Acharya, D, Acharya, P, Ackerman, In, Adamu, Aa, Adebayo, Om, Adekanmbi, V, Ademi, Z, Adetokunboh, Oo, Adib, Mg, Adsuar, Jc, Afanvi, Ka, Afarideh, M, Afshin, A, Agarwal, G, Agesa, Km, Aggarwal, R, Aghayan, Sa, Agrawal, A, Ahmadi, A, Ahmadi, M, Ahmadieh, H, Ahmed, Mb, Ahmed, S, Aichour, An, Aichour, I, Aichour, Mte, Akinyemiju, T, Akseer, N, Al-Aly, Z, Al-Eyadhy, A, Al-Mekhlafi, Hm, Al-Raddadi, Rm, Alahdab, F, Alam, K, Alam, T, Alashi, A, Alavian, Sm, Alene, Ka, Alijanzadeh, M, Alizadeh-Navaei, R, Aljunid, Sm, Alkerwi, A, Alla, F, Allebeck, P, Alonso, J, Alsharif, U, Altirkawi, K, Alvis-Guzman, N, Aminde, Ln, Amini, E, Amiresmaili, M, Ammar, W, Amoako, Ya, Anber, Nh, Andrei, Cl, Androudi, S, Animut, Md, Anjomshoa, M, Ansha, Mg, Antonio, Cat, Anwari, P, Arabloo, J, Aremu, O, Ärnlöv, J, Arora, A, Arora, M, Artaman, A, Aryal, Kk, Asayesh, H, Ataro, Z, Ausloos, M, Avila-Burgos, L, Avokpaho, Efga, Awasthi, A, Ayala, Quintanilla, Ayer, R, Azzopardi, Ps, Babazadeh, A, Badali, H, Balakrishnan, K, Bali, Ag, Banach, M, Banoub, Jam, Barac, A, Barboza, Ma, Barker-Collo, Sl, Bärnighausen, Tw, Barquera, S, Barrero, Lh, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Behzadifar, M, Bekele, Bb, Bekru, Et, Belachew, Ab, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bensenor, Im, Berhane, A, Bernabe, E, Bernstein, Rs, Beuran, M, Beyranvand, T, Bhala, N, Bhatt, S, Bhaumik, S, Bhutta, Za, Biadgo, B, Biehl, Mh, Bijani, A, Bikbov, B, Bilano, V, Bililign, N, Bin, Sayeed, Bisanzio, D, Bjørge, T, Bleyer, A, Bobasa, Em, Bou-Orm, Ir, Boufous, S, Bourne, R, Brady, Oj, Brant, Lc, Brayne, C, Brazinova, A, Breitborde, Njk, Brenner, H, Briant, Ps, Briko, An, Britton, G, Brugha, T, Buchbinder, R, Busse, R, Butt, Za, Cahuana-Hurtado, L, Campuzano, Rincon, Cano, J, Cárdenas, R, Carrero, Jj, Carter, A, Carvalho, F, Castañeda-Orjuela, Ca, Castillo, Rivas, J, Castro, F, Catalá-López, F, Cercy, Km, Cerin, E, Chaiah, Y, Chang, Jc, Charlson, Fj, Chattu, Vk, Chiang, Pp, Chitheer, A, Choi, Jj, Christensen, H, Christopher, Dj, Chung, Sc, Cicuttini, Fm, Cirillo, Massimo, Collado-Mateo, D, Cooper, C, Cortesi, Pa, Cortinovis, M, Cousin, E, Criqui, Mh, Cromwell, Ea, Cross, M, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dandona, L, Dandona, R, Dargan, Pi, Daryani, A, Das, Gupta, Das, R, Neves, J, Dasa, Tt, Davitoiu, Dv, De, La, Hoz, Fp, Leo, De, D, De, Neve, Jw, Steur, De, H, Degefa, Mg, Degenhardt, L, Deiparine, S, Demoz, Gt, Denova-Gutiérrez, E, Deribe, K, Dervenis, N, Des, Jarlais, Dey, S, Dharmaratne, Sd, Dhimal, M, Dinberu, Mt, Dirac, Ma, Djalalinia, S, Doan, L, Dokova, K, Doku, Dt, Dorsey, Er, Doyle, Ke, Driscoll, Tr, Dubey, M, Dubljanin, E, Duken, Ee, Duncan, Bb, Duraes, Ar, Ebrahimi, H, Ebrahimpour, S, Echko, Mm, Edessa, D, Edvardsson, D, Effiong, A, Eggen, Ae, Ehrlich, Jr, Bcheraoui, El, C, El-Khatib, Z, Elyazar, Irf, Enayati, A, Endalifer, Ml, Endries, Ay, Er, B, Erskine, He, Eskandarieh, S, Esteghamati, A, Esteghamati, S, Fakhim, H, Faramarzi, M, Fareed, M, Farhadi, F, Farid, Ta, Farinha, Cses, Farioli, A, Faro, A, Farzadfar, F, Fazaeli, Aa, Feigin, Vl, Fentahun, N, Fereshtehnejad, Sm, Fernandes, E, Fernandes, Jc, Ferrari, Aj, Ferreira, Ml, Filip, I, Fischer, F, Fitzmaurice, C, Foigt, Na, Foreman, Kj, Frank, Td, Fukumoto, T, Fullman, N, Fürst, T, Furtado, Jm, Gakidou, E, Gall, S, Gallus, S, Ganji, M, Garcia-Basteiro, Al, Gardner, Wm, Gebre, Ak, Gebremedhin, At, Gebremichael, Tg, Gelano, Tf, Geleijnse, Jm, Genova-Maleras, R, Geramo, Ycd, Gething, Pw, Gezae, Ke, Ghadami, Mr, Ghadiri, K, Ghasemi-Kasman, M, Ghimire, M, Ghoshal, Ag, Gill, Ps, Gill, Tk, Ginawi, Ia, Giussani, G, Gnedovskaya, Ev, Goldberg, Em, Goli, S, Gómez-Dantés, H, Gona, Pn, Gopalani, Sv, Gorman, Tm, Goulart, Ac, Goulart, Bng, Grada, A, Grosso, G, Gugnani, Hc, Guillemin, F, Guo, Y, Gupta, Pc, Gupta, R, Gupta, T, Gutiérrez, Ra, Gyawali, B, Haagsma, Ja, Hachinski, V, Hafezi-Nejad, N, Haghparast, Bidgoli, Hagos, Tb, Hailegiyorgis, Tt, Haj-Mirzaian, A, Hamadeh, Rr, Hamidi, S, Handal, Aj, Hankey, Gj, Hao, Y, Harb, Hl, Harikrishnan, S, Haririan, H, Haro, Jm, Hassankhani, H, Hassen, Hy, Havmoeller, R, Hay, Rj, Hay, Si, Hedayatizadeh-Omran, A, Heibati, B, Hendrie, D, Henok, A, Heredia-Pi, I, Herteliu, C, Heydarpour, F, Heydarpour, P, Hibstu, Dt, Hoek, Hw, Hoffman, Hj, Hole, Mk, Homaie, Rad, E, Hoogar, P, Hosgood, Hd, Hosseini, Sm, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hotez, Pj, Hoy, Dg, Hsairi, M, Htet, As, Huang, Jj, Iburg, Km, Ikeda, Ct, Ilesanmi, Os, Irvani, Ssn, Irvine, Cms, Islam, Sms, Islami, F, Jacobsen, Kh, Jahangiry, L, Jahanmehr, N, Jain, Sk, Jakovljevic, M, James, Sl, Jayatilleke, Au, Jeemon, P, Jha, Rp, Jha, V, Js, Ji, Johnson, Co, Jonas, Jb, Jonnagaddala, J, Jorjoran, Shushtari, Z, Joshi, A, Jozwiak, Jj, Jungari, Sb, 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Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Sliwa, Karen, Smith, David L, Smith, Mari, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Sorensen, Reed J D, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Stanaway, Jeffrey D, Starodubov, Vladimir I, Stein, Dan J, Steiner, Caitlyn, Steiner, Timothy J, Stokes, Mark A, Stovner, Lars Jacob, Subart, Michelle L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sykes, Bryan L, Sylaja, P.N., Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Tandon, Nikhil, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Taylor, Hugh R, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekelemedhin, Shishay Wahdey, Tekle, Merhawi Gebremedhin, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Tessema, Belay, Teweldemedhin, Mebrahtu, Thankappan, Kavumpurathu Raman, Theis, Andrew, Thirunavukkarasu, Sathish, Thomas, Nihal, Tilahun, Binyam, To, Quyen G, Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna E, Tortajada-Girbés, Miguel, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Troeger, Christopher E, Tsadik, Afewerki Gebremeskel, Tsoi, Derrick, Tudor Car, Lorainne, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Undurraga, Eduardo A, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Wang, Yafeng, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T Eoin, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Williams, Hywel C, Wilner, Lauren B, Wilson, Shadrach, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Woolf, Anthony D, Wyper, Grant M A, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zandian, Hamed, Zar, Heather J, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zipkin, Ben, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna, and Murray, Christopher J L
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Male ,Health Status ,health statu ,HALE ,mortality rate ,communicable disease ,DALYs ,Global Burden of Disease ,Risk Factors ,Prevalence ,Medicine and Health Sciences ,Singapore ,OUTCOMES ,disability-adjusted life year ,international cooperation ,Medicine (all) ,11 Medical And Health Sciences ,Central African Republic ,newborn disease ,IRON-DEFICIENCY ,AIDS ,priority journal ,Bahrain ,disease severity ,Female ,Quality-Adjusted Life Years ,cerebrovascular accident ,Ukraine ,Life Sciences & Biomedicine ,INTERVENTIONS ,Slovakia ,DISORDERS ,Burundi ,WEIGHTS ,GBD 2017 DALYs and HALE Collaborators ,Communicable Diseases ,Article ,STYLE ,Medicine, General & Internal ,Life Expectancy ,General & Internal Medicine ,Humans ,Disabled Persons ,human ,Healthy Lifestyle ,HALE, DALYs, global burden of disease ,Mortality ,Aged ,Science & Technology ,Mortality, Premature ,HIV ,ischemic heart disease ,major clinical study ,PREVENTION ,non communicable disease ,GBD, disability-adjusted life-years ,age ,sex factor ,Socioeconomic Factors ,Algeria ,Federation of Bosnia and Herzegovina ,lower respiratory tract infection ,Wounds and Injuries ,GENDER ,Human medicine ,trend study ,chronic obstructive lung disease - Abstract
Background How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Sociodemographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7.4 years (95% uncertainty interval 74-7.8), from 65.6 years (65.3-65- 8) in 1990 to 73.0 years (72.7-73.3) in 2017. The increase in years of life varied from 5.1 years (5.0-5.3) in high SDI countries to 12.0 years (11.3-12.8) in low SDI countries. Of the additional years of life expected at birth, 26.3% (20.1-33.1) were expected to be spent in poor health in high SDI countries compared with 11.7% (8.8-15.1) in low-middle SDI countries. HALE at birth increased by 6.3 years (5.9-6.7), from 57.0 years (54.6-59.1) in 1990 to 63.3 years (60.5-65.7) in 2017. The increase varied from 3.8 years (3.4-4.1) in high SDI countries to 10.5 years (9.8-11.2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1.0 year (0.4-1.7) in Saint Vincent and the Grenadines (62.4 years [59.9-64.7] in 1990 to 63.5 years [60.9-65.8] in 2017) to 23.7 years (21.9-25.6) in Eritrea (30.7 years [28.9-32.2] in 1990 to 54.4 years [51.5-57.1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1.4 years (0.6-2.3) in Algeria to 11.9 years (10.9-12.9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75.8 years [72.4-78.7]) and males (72.6 years [69 " 8-75.0]) and the lowest estimates were in Central African Republic (47.0 years [43.7-50.2] for females and 42.8 years [40.1-45.6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41.3% (38.8-43.5) for communicable diseases and by 49"8% (47.9-51.6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40.1% (36.8-43.0), although age-standardised DALY rates decreased by 18.1% (16.0-20.2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low S DI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
4. Compliance and persistence with hydroxychloroquine in South Korean patients with systemic lupus erythematosus
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Kim Yk, Park Ek, S-M Kweon, Kim Gt, Seung-Geun Lee, and Park Jh
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Adult ,Male ,Health Knowledge, Attitudes, Practice ,medicine.medical_specialty ,Time Factors ,Adolescent ,Administration, Oral ,Medication adherence ,Severity of Illness Index ,Drug Administration Schedule ,Medication Adherence ,Persistence (computer science) ,Tertiary Care Centers ,Poor adherence ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,Asian People ,Rheumatology ,Risk Factors ,immune system diseases ,Internal medicine ,Republic of Korea ,medicine ,Humans ,Lupus Erythematosus, Systemic ,Longitudinal Studies ,030212 general & internal medicine ,Child ,skin and connective tissue diseases ,Aged ,Retrospective Studies ,030203 arthritis & rheumatology ,business.industry ,Hydroxychloroquine ,Middle Aged ,Compliance (physiology) ,Treatment Outcome ,Physical therapy ,Female ,business ,Immunosuppressive Agents ,medicine.drug - Abstract
We aimed to analyze compliance and persistence with hydroxychloroquine (HCQ) in real practice and identify risk factors for poor adherence in South Korean patients with systemic lupus erythematosus (SLE). This retrospective longitudinal study evaluated 235 SLE patients in whom oral HCQ was newly started from 2002 to 2016 at a tertiary hospital in South Korea. Compliance was assessed using one-year medication possession ratio (MPR) and non-compliance was defined as a one-year MPR 0.8. Persistence was determined as the time from HCQ treatment initiation to discontinuation without interruption for ≥56 days. The mean one-year MPR of HCQ was 0.88 and the frequency of non-compliance was 19.9%. During the study period, 115 (48.9%) patients discontinued HCQ and forgetfulness and/or carelessness (73%) were the most common reason for HCQ non-persistence, followed by adverse events (10.4%), unknown factors (10.4%), and pregnancy (6.1%). Median duration until HCQ discontinuation was 55.1 months and the one-year persistence rate to HCQ was 0.8. SLE Disease Activity Index 2000 (SLEDAI-2K) 6 was a significant risk factor for non-compliance (OR = 2.98, p = 0.001) and non-persistence (HR = 1.55, p = 0.046) with HCQ after adjusting confounding factors. However, HCQ adherence was not associated with the dose of HCQ or concomitant immunosuppressive medications. Our data showed that overall adherence to HCQ in SLE patients was suboptimal in real practice and SLEDAI-2K score 6 was a risk factor for poor adherence, suggesting the need to improve adherence with HCQ treatment in SLE patients, especially in those with low disease activity.
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- 2017
5. iNKT cells prevent obesity-induced hepatic steatosis in mice in a C-C chemokine receptor 7-dependent manner
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Ko Hj, Kwon Be, Kim Hm, Kwon Mh, Chang Sy, Park Ek, Lee Es, Huh Jh, Choon Hee Chung, Lee Br, Mi-Na Kweon, and Kim Ph
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Male ,0301 basic medicine ,Receptors, CCR7 ,Adoptive cell transfer ,medicine.medical_specialty ,Endocrinology, Diabetes and Metabolism ,Mice, Obese ,Medicine (miscellaneous) ,chemical and pharmacologic phenomena ,C-C chemokine receptor type 7 ,Inflammation ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Insulin resistance ,Immune system ,Non-alcoholic Fatty Liver Disease ,Internal medicine ,medicine ,Animals ,Obesity ,Triglycerides ,Nutrition and Dietetics ,Chemistry ,Fatty liver ,hemic and immune systems ,medicine.disease ,Disease Models, Animal ,030104 developmental biology ,Endocrinology ,Liver ,030220 oncology & carcinogenesis ,Natural Killer T-Cells ,Original Article ,Steatohepatitis ,Steatosis ,medicine.symptom - Abstract
Non-alcoholic fatty liver disease and non-alcoholic steatohepatitis are characterized by an increase in hepatic triglyceride content with infiltration of immune cells, which can cause steatohepatitis and hepatic insulin resistance. C-C chemokine receptor 7 (CCR7) is primarily expressed in immune cells, and CCR7 deficiency leads to the development of multi-organ autoimmunity, chronic renal disease and autoimmune diabetes. Here, we investigated the effect of CCR7 on hepatic steatosis in a mouse model and its underlying mechanism. Our results demonstrated that body and liver weights were higher in the CCR7−/− mice than in the wild-type (WT) mice when they were fed a high-fat diet. Further, glucose tolerance and insulin sensitivity were markedly diminished in CCR7−/− mice. The number of invariant natural killer T (iNKT) cells was reduced in the livers of the CCR7−/− mice. Moreover, liver inflammation was detected in obese CCR7−/− mice, which was ameliorated by the adoptive transfer of hepatic mononuclear cells from WT mice, but not through the transfer of hepatic mononuclear cells from CD1d−/− or interleukin-10-deficient (IL-10−/−) mice. Overall, these results suggest that CCR7+ mononuclear cells in the liver could regulate obesity-induced hepatic steatosis via induction of IL-10-expressing iNKT cells.
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- 2017
6. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017: A Systematic Analysis for the Global Burden of Disease Study
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Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Abate D, Abbasi N, Abbastabar H, Abd-Allah F, Abdel-Rahman O, Abdelalim A, Abdoli A, Abdollahpour I, Abdulle ASM, Abebe ND, Abraha HN, Abu-Raddad LJ, Abualhasan A, Adedeji IA, Advani SM, Afarideh M, Afshari M, Aghaali M, Agius D, Agrawal S, Ahmadi A, Ahmadian E, Ahmadpour E, Ahmed MB, Akbari ME, Akinyemiju T, Al-Aly Z, AlAbdulKader AM, Alahdab F, Alam T, Alamene GM, Alemnew BTT, Alene KA, Alinia C, Alipour V, Aljunid SM, Bakeshei FA, Almadi MAH, Almasi-Hashiani A, Alsharif U, Alsowaidi S, Alvis-Guzman N, Amini E, Amini S, Amoako YA, Anbari Z, Anber NH, Andrei CL, Anjomshoa M, Ansari F, Ansariadi A, Appiah SCY, Arab-Zozani M, Arabloo J, Arefi Z, Aremu O, Areri HA, Artaman A, Asayesh H, Asfaw ET, Ashagre AF, Assadi R, Ataeinia B, Atalay HT, Ataro Z, Atique S, Ausloos M, Avila-Burgos L, Avokpaho EFGA, Awasthi A, Awoke N, Ayala Quintanilla BP, Ayanore MA, Ayele HT, Babaee E, Bacha U, Badawi A, Bagherzadeh M, Bagli E, Balakrishnan S, Balouchi A, Bärnighausen TW, Battista RJ, Behzadifar M, Bekele BB, Belay YB, Belayneh YM, Berfield KKS, Berhane A, Bernabe E, Beuran M, Bhakta N, Bhattacharyya K, Biadgo B, Bijani A, Bin Sayeed MS, Birungi C, Bisignano C, Bitew H, Bjørge T, Bleyer A, Bogale KA, Bojia HA, Borzì AM, Bosetti C, Bou-Orm IR, Brenner H, Brewer JD, Briko AN, Briko NI, Bustamante-Teixeira MT, Butt ZA, Carreras G, Carrero JJ, Carvalho F, Castro C, Castro F, Catalá-López F, Cerin E, Chaiah Y, Chanie WF, Chattu VK, Chaturvedi P, Chauhan NS, Chehrazi M, Chiang PP, Chichiabellu TY, Chido-Amajuoyi OG, Chimed-Ochir O, Choi JJ, Christopher DJ, Chu DT, Constantin MM, Costa VM, Crocetti E, Crowe CS, Curado MP, Dahlawi SMA, Damiani G, Darwish AH, Daryani A, das Neves J, Demeke FM, Demis AB, Demissie BW, Demoz GT, Denova-Gutiérrez E, Derakhshani A, Deribe KS, Desai R, Desalegn BB, Desta M, Dey S, Dharmaratne SD, Dhimal M, Diaz D, Dinberu MTT, Djalalinia S, Doku DT, Drake TM, Dubey M, Dubljanin E, Duken EE, Ebrahimi H, Effiong A, Eftekhari A, El Sayed I, Zaki MES, El-Jaafary SI, El-Khatib Z, Elemineh DA, Elkout H, Ellenbogen RG, Elsharkawy A, Emamian MH, Endalew DA, Endries AY, Eshrati B, Fadhil I, Fallah V, Faramarzi M, Farhangi MA, Farioli A, Farzadfar F, Fentahun N, Fernandes E, Feyissa GT, Filip I, Fischer F, Fisher JL, Force LM, Foroutan M, Freitas M, Fukumoto T, Futran ND, Gallus S, Gankpe FG, Gayesa RT, Gebrehiwot TT, Gebremeskel GG, Gedefaw GA, Gelaw BK, Geta B, Getachew S, Gezae KE, Ghafourifard M, Ghajar A, Ghashghaee A, Gholamian A, Gill PS, Ginindza TTG, Girmay A, Gizaw M, Gomez RS, Gopalani SV, Gorini G, Goulart BNG, Grada A, Ribeiro Guerra M, Guimaraes ALS, Gupta PC, Gupta R, Hadkhale K, Haj-Mirzaian A, Hamadeh RR, Hamidi S, Hanfore LK, Haro JM, Hasankhani M, Hasanzadeh A, Hassen HY, Hay RJ, Hay SI, Henok A, Henry NJ, Herteliu C, Hidru HD, Hoang CL, Hole MK, Hoogar P, Horita N, Hosgood HD, Hosseini M, Hosseinzadeh M, Hostiuc M, Hostiuc S, Househ M, Hussen MM, Ileanu B, Ilic MD, Innos K, Irvani SSN, Iseh KR, Islam SMS, Islami F, Jafari Balalami N, Jafarinia M, Jahangiry L, Jahani MA, Jahanmehr N, Jakovljevic M, James SL, Javanbakht M, Jayaraman S, Jee SH, Jenabi E, Jha RP, Jonas JB, Jonnagaddala J, Joo T, Jungari SB, Jürisson M, Kabir A, Kamangar F, Karch A, Karimi N, Karimian A, Kasaeian A, Kasahun GG, Kassa B, Kassa TD, Kassaw MW, Kaul A, Keiyoro PN, Kelbore AG, Kerbo AA, Khader YS, Khalilarjmandi M, Khan EA, Khan G, Khang YH, Khatab K, Khater A, Khayamzadeh M, Khazaee-Pool M, Khazaei S, Khoja AT, Khosravi MH, Khubchandani J, Kianipour N, Kim D, Kim YJ, Kisa A, Kisa S, Kissimova-Skarbek K, Komaki H, Koyanagi A, Krohn KJ, Bicer BK, Kugbey N, Kumar V, Kuupiel D, La Vecchia C, Lad DP, Lake EA, Lakew AM, Lal DK, Lami FH, Lan Q, Lasrado S, Lauriola P, Lazarus JV, Leigh J, Leshargie CT, Liao Y, Limenih MA, Listl S, Lopez AD, Lopukhov PD, Lunevicius R, Madadin M, Magdeldin S, El Razek HMA, Majeed A, Maleki A, Malekzadeh R, Manafi A, Manafi N, Manamo WA, Mansourian M, Mansournia MA, Mantovani LG, Maroufizadeh S, Martini SMS, Mashamba-Thompson TP, Massenburg BB, Maswabi MT, Mathur MR, McAlinden C, McKee M, Meheretu HAA, Mehrotra R, Mehta V, Meier T, Melaku YA, Meles GG, Meles HG, Melese A, Melku M, Memiah PTN, Mendoza W, Menezes RG, Merat S, Meretoja TJ, Mestrovic T, Miazgowski B, Miazgowski T, Mihretie KMM, Miller TR, Mills EJ, Mir SM, Mirzaei H, Mirzaei HR, Mishra R, Moazen B, Mohammad DK, Mohammad KA, Mohammad Y, Darwesh AM, Mohammadbeigi A, Mohammadi H, Mohammadi M, Mohammadian M, Mohammadian-Hafshejani A, Mohammadoo-Khorasani M, Mohammadpourhodki R, Mohammed AS, Mohammed JA, Mohammed S, Mohebi F, Mokdad AH, Monasta L, Moodley Y, Moosazadeh M, Moossavi M, Moradi G, Moradi-Joo M, Moradi-Lakeh M, Moradpour F, Morawska L, Morgado-da-Costa J, Morisaki N, Morrison SD, Mosapour A, Mousavi SM, Muche AA, Muhammed OSS, Musa J, Nabhan AR, Naderi M, Nagarajan AJ, Nagel G, Nahvijou A, Naik G, Najafi F, Naldi L, Nam HS, Nasiri N, Nazari J, Negoi I, Neupane S, Newcomb PA, Nggada HA, Ngunjiri JW, Nguyen CT, Nikniaz L, Ningrum DNA, Nirayo YL, Nixon MR, Nnaji CA, Nojomi M, Nosratnejad S, Shiadeh MN, Obsa MS, Ofori-Asenso R, Ogbo FA, Oh IH, Olagunju AT, Olagunju TO, Oluwasanu MM, Omonisi AE, Onwujekwe OE, Oommen AM, Oren E, Ortega-Altamirano DDV, Ota E, Otstavnov SS, Owolabi MO, P A M, Padubidri JR, Pakhale S, Pakpour AH, Pana A, Park EK, Parsian H, Pashaei T, Patel S, Patil ST, Pennini A, Pereira DM, Piccinelli C, Pillay JD, Pirestani M, Pishgar F, Postma MJ, Pourjafar H, Pourmalek F, Pourshams A, Prakash S, Prasad N, Qorbani M, Rabiee M, Rabiee N, Radfar A, Rafiei A, Rahim F, Rahimi M, Rahman MA, Rajati F, Rana SM, Raoofi S, Rath GK, Rawaf DL, Rawaf S, Reiner RC, Renzaho AMN, Rezaei N, Rezapour A, Ribeiro AI, Ribeiro D, Ronfani L, Roro EM, Roshandel G, Rostami A, Saad RS, Sabbagh P, Sabour S, Saddik B, Safiri S, Sahebkar A, Salahshoor MR, Salehi F, Salem H, Salem MR, Salimzadeh H, Salomon JA, Samy AM, Sanabria J, Santric Milicevic MM, Sartorius B, Sarveazad A, Sathian B, Satpathy M, Savic M, Sawhney M, Sayyah M, Schneider IJC, Schöttker B, Sekerija M, Sepanlou SG, Sepehrimanesh M, Seyedmousavi S, Shaahmadi F, Shabaninejad H, Shahbaz M, Shaikh MA, Shamshirian A, Shamsizadeh M, Sharafi H, Sharafi Z, Sharif M, Sharifi A, Sharifi H, Sharma R, Sheikh A, Shirkoohi R, Shukla SR, Si S, Siabani S, Silva DAS, Silveira DGA, Singh A, Singh JA, Sisay S, Sitas F, Sobngwi E, Soofi M, Soriano JB, Stathopoulou V, Sufiyan MB, Tabarés-Seisdedos R, Tabuchi T, Takahashi K, Tamtaji OR, Tarawneh MR, Tassew SG, Taymoori P, Tehrani-Banihashemi A, Temsah MH, Temsah O, Tesfay BE, Tesfay FH, Teshale MY, Tessema GA, Thapa S, Tlaye KG, Topor-Madry R, Tovani-Palone MR, Traini E, Tran BX, Tran KB, Tsadik AG, Ullah I, Uthman OA, Vacante M, Vaezi M, Varona Pérez P, Veisani Y, Vidale S, Violante FS, Vlassov V, Vollset SE, Vos T, Vosoughi K, Vu GT, Vujcic IS, Wabinga H, Wachamo TM, Wagnew FS, Waheed Y, Weldegebreal F, Weldesamuel GT, Wijeratne T, Wondafrash DZ, Wonde TE, Wondmieneh AB, Workie HM, Yadav R, Yadegar A, Yadollahpour A, Yaseri M, Yazdi-Feyzabadi V, Yeshaneh A, Yimam MA, Yimer EM, Yisma E, Yonemoto N, Younis MZ, Yousefi B, Yousefifard M, Yu C, Zabeh E, Zadnik V, Moghadam TZ, Zaidi Z, Zamani M, Zandian H, Zangeneh A, Zaki L, Zendehdel K, Zenebe ZM, Zewale TA, Ziapour A, Zodpey S, Murray CJL, Fitzmaurice C., Abate D., Abbasi N., Abbastabar H., Abd-Allah F., Abdel-Rahman O., Abdelalim A., Abdoli A., Abdollahpour I., Abdulle A.S.M., Abebe N.D., Abraha H.N., Abu-Raddad L.J., Abualhasan A., Adedeji I.A., Advani S.M., Afarideh M., Afshari M., Aghaali M., Agius D., Agrawal S., Ahmadi A., Ahmadian E., Ahmadpour E., Ahmed M.B., Akbari M.E., Akinyemiju T., Al-Aly Z., Alabdulkader A.M., Alahdab F., Alam T., Alamene G.M., Alemnew B.T.T., Alene K.A., Alinia C., Alipour V., Aljunid S.M., Bakeshei F.A., Almadi M.A.H., Almasi-Hashiani A., Alsharif U., Alsowaidi S., Alvis-Guzman N., Amini E., Amini S., Amoako Y.A., Anbari Z., Anber N.H., Andrei C.L., Anjomshoa M., Ansari F., Ansariadi A., Appiah S.C.Y., Arab-Zozani M., Arabloo J., Arefi Z., Aremu O., Areri H.A., Artaman A., Asayesh H., Asfaw E.T., Ashagre A.F., Assadi R., Ataeinia B., Atalay H.T., Ataro Z., Atique S., Ausloos M., Avila-Burgos L., Avokpaho E.F.G.A., Awasthi A., Awoke N., Ayala Quintanilla B.P., Ayanore M.A., Ayele H.T., Babaee E., Bacha U., Badawi A., Bagherzadeh M., Bagli E., Balakrishnan S., Balouchi A., Barnighausen T.W., Battista R.J., Behzadifar M., Bekele B.B., Belay Y.B., Belayneh Y.M., Berfield K.K.S., Berhane A., Bernabe E., Beuran M., Bhakta N., Bhattacharyya K., Biadgo B., Bijani A., Bin Sayeed M.S., Birungi C., Bisignano C., Bitew H., Bjorge T., Bleyer A., Bogale K.A., Bojia H.A., Borzi A.M., Bosetti C., Bou-Orm I.R., Brenner H., Brewer J.D., Briko A.N., Briko N.I., Bustamante-Teixeira M.T., Butt Z.A., Carreras G., Carrero J.J., Carvalho F., Castro C., Castro F., Catala-Lopez F., Cerin E., Chaiah Y., Chanie W.F., Chattu V.K., Chaturvedi P., Chauhan N.S., Chehrazi M., Chiang P.P.-C., Chichiabellu T.Y., Chido-Amajuoyi O.G., Chimed-Ochir O., Choi J.-Y.J., Christopher D.J., Chu D.-T., Constantin M.-M., Costa V.M., Crocetti E., Crowe C.S., Curado M.P., Dahlawi S.M.A., Damiani G., Darwish A.H., Daryani A., Das Neves J., Demeke F.M., Demis A.B., Demissie B.W., Demoz G.T., Denova-Gutierrez E., Derakhshani A., Deribe K.S., Desai R., Desalegn B.B., Desta M., Dey S., Dharmaratne S.D., Dhimal M., Diaz D., Dinberu M.T.T., Djalalinia S., Doku D.T., Drake T.M., Dubey M., Dubljanin E., Duken E.E., Ebrahimi H., Effiong A., Eftekhari A., El Sayed I., Zaki M.E.S., El-Jaafary S.I., El-Khatib Z., Elemineh D.A., Elkout H., Ellenbogen R.G., Elsharkawy A., Emamian M.H., Endalew D.A., Endries A.Y., Eshrati B., Fadhil I., Fallah V., Faramarzi M., Farhangi M.A., Farioli A., Farzadfar F., Fentahun N., Fernandes E., Feyissa G.T., Filip I., Fischer F., Fisher J.L., Force L.M., Foroutan M., Freitas M., Fukumoto T., Futran N.D., Gallus S., Gankpe F.G., Gayesa R.T., Gebrehiwot T.T., Gebremeskel G.G., Gedefaw G.A., Gelaw B.K., Geta B., Getachew S., Gezae K.E., Ghafourifard M., Ghajar A., Ghashghaee A., Gholamian A., Gill P.S., Ginindza T.T.G., Girmay A., Gizaw M., Gomez R.S., Gopalani S.V., Gorini G., Goulart B.N.G., Grada A., Ribeiro Guerra M., Guimaraes A.L.S., Gupta P.C., Gupta R., Hadkhale K., Haj-Mirzaian A., Hamadeh R.R., Hamidi S., Hanfore L.K., Haro J.M., Hasankhani M., Hasanzadeh A., Hassen H.Y., Hay R.J., Hay S.I., Henok A., Henry N.J., Herteliu C., Hidru H.D., Hoang C.L., Hole M.K., Hoogar P., Horita N., Hosgood H.D., Hosseini M., Hosseinzadeh M., Hostiuc M., Hostiuc S., Househ M., Hussen M.M., Ileanu B., Ilic M.D., Innos K., Irvani S.S.N., Iseh K.R., Islam S.M.S., Islami F., Jafari Balalami N., Jafarinia M., Jahangiry L., Jahani M.A., Jahanmehr N., Jakovljevic M., James S.L., Javanbakht M., Jayaraman S., Jee S.H., Jenabi E., Jha R.P., Jonas J.B., Jonnagaddala J., Joo T., Jungari S.B., Jurisson M., Kabir A., 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El-Jaafary, S, El-Khatib, Z, Elemineh, D, Elkout, H, Ellenbogen, R, Elsharkawy, A, Emamian, M, Endalew, D, Endries, A, Eshrati, B, Fadhil, I, Fallah, V, Faramarzi, M, Farhangi, M, Farioli, A, Farzadfar, F, Fentahun, N, Fernandes, E, Feyissa, G, Filip, I, Fischer, F, Fisher, J, Force, L, Foroutan, M, Freitas, M, Fukumoto, T, Futran, N, Gallus, S, Gankpe, F, Gayesa, R, Gebrehiwot, T, Gebremeskel, G, Gedefaw, G, Gelaw, B, Geta, B, Getachew, S, Gezae, K, Ghafourifard, M, Ghajar, A, Ghashghaee, A, Gholamian, A, Gill, P, Ginindza, T, Girmay, A, Gizaw, M, Gomez, R, Gopalani, S, Gorini, G, Goulart, B, Grada, A, Ribeiro Guerra, M, Guimaraes, A, Gupta, P, Gupta, R, Hadkhale, K, Haj-Mirzaian, A, Hamadeh, R, Hamidi, S, Hanfore, L, Haro, J, Hasankhani, M, Hasanzadeh, A, Hassen, H, Hay, R, Hay, S, Henok, A, Henry, N, Herteliu, C, Hidru, H, Hoang, C, Hole, M, Hoogar, P, Horita, N, Hosgood, H, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Hussen, M, Ileanu, B, Ilic, M, Innos, K, 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Violante, F, Vlassov, V, Vollset, S, Vos, T, Vosoughi, K, Vu, G, Vujcic, I, Wabinga, H, Wachamo, T, Wagnew, F, Waheed, Y, Weldegebreal, F, Weldesamuel, G, Wijeratne, T, Wondafrash, D, Wonde, T, Wondmieneh, A, Workie, H, Yadav, R, Yadegar, A, Yadollahpour, A, Yaseri, M, Yazdi-Feyzabadi, V, Yeshaneh, A, Yimam, M, Yimer, E, Yisma, E, Yonemoto, N, Younis, M, Yousefi, B, Yousefifard, M, Yu, C, Zabeh, E, Zadnik, V, Moghadam, T, Zaidi, Z, Zamani, M, Zandian, H, Zangeneh, A, Zaki, L, Zendehdel, K, Zenebe, Z, Zewale, T, Ziapour, A, Zodpey, S, Murray, C, Fitzmaurice, Christina, Abate, Degu, Abbasi, Naghmeh, Abbastabar, Hedayat, Yisma, Engida, Murray, Christopher JL, and Global Burden of Disease Cancer Collaboration
- Subjects
Cancer Research ,age distribution ,cancer incidence ,Colorectal cancer ,GBD, DALY ,cancer risk ,Global Health ,Global Burden of Disease ,disease burden ,cause of death ,trachea cancer ,0302 clinical medicine ,systematic review ,Neoplasms ,quality adjusted life year ,11. Sustainability ,Epidemiology ,cancer mortality ,030212 general & internal medicine ,years of life lost ,Stomach cancer ,fertility ,disabled person ,stomach cancer ,disability-adjusted life year ,nonhodgkin lymphoma ,Incidence ,1. No poverty ,prostate cancer ,3. Good health ,income ,Oncology ,risk factor ,030220 oncology & carcinogenesis ,bladder cancer ,Quality-Adjusted Life Years ,medicine.medical_specialty ,sex difference ,3122 Cancers ,colorectal cancer ,bronchus cancer ,Article ,educational status ,Causes of cancer ,liver cancer ,03 medical and health sciences ,Breast cancer ,breast cancer ,Environmental health ,geographic distribution ,medicine ,Humans ,Disabled Persons ,human ,business.industry ,Correction ,Cancer ,non melanoma skin cancer ,medicine.disease ,years lived with disability ,lung cancer ,Years of potential life lost ,Skin cancer ,global disease burden ,business ,neoplasm ,RC ,uterine cervix cancer - Abstract
Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-Adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs). Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care. © 2019 American Medical Association. All rights reserved.
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- 2019
7. About a new self–tuning mechanism in string theory
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Park EK and Kwon PS
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Physics ,Classical mechanics ,Rehabilitation ,Self-tuning ,Physical Therapy, Sports Therapy and Rehabilitation ,General Medicine ,String theory ,Mechanism (sociology) - Abstract
We briefly review the main points of a new self-tuning mechanism in string theory which is very distinguished from the existing theories. PACS number: 11.25.-w, 11.25.Uv
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- 2017
8. Special issue on information dissemination and new services in P2P systems
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Song, Min, Shetty, Sachin, Jiang, Wenbin, and Park, EK
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- 2011
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9. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study
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Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Allen C, Barber RM, Barregard L, Bhutta ZA, Brenner H, Dicker DJ, Chimed-Orchir O, Dandona R, Dandona L, Fleming T, Forouzanfar MH, Hancock J, Hay RJ, Hunter-Merrill R, Huynh C, Hosgood HD, Johnson CO, Jonas JB, Khubchandani J, Kumar GA, Kutz M, Lan Q, Larson HJ, Liang X, Lim SS, Lopez AD, MacIntyre MF, Marczak L, Marquez N, Mokdad AH, Pinho C, Pourmalek F, Salomon JA, Sanabria JR, Sandar L, Sartorius B, Schwartz SM, Shackelford KA, Shibuya K, Stanaway J, Steiner C, Sun J, Takahashi K, Vollset SE, Vos T, Wagner JA, Wang H, Westerman R, Zeeb H, Zoeckler L, Abd-Allah F, Ahmed MB, Alabed S, Alam NK, Aldhahri SF, Alem G, Alemayohu MA, Ali R, Al-Raddadi R, Amare A, Amoako Y, Artaman A, Asayesh H, Atnafu N, Awasthi A, Saleem HB, Barac A, Bedi N, Bensenor I, Berhane A, Bernabé E, Betsu B, Binagwaho A, Boneya D, Campos-Nonato I, Castañeda-Orjuela C, Catalá-López F, Chiang P, Chibueze C, Chitheer A, Choi JY, Cowie B, Damtew S, das Neves J, Dey S, Dharmaratne S, Dhillon P, Ding E, Driscoll T, Ekwueme D, Endries AY, Farvid M, Farzadfar F, Fernandes J, Fischer F, G/Hiwot TT, Gebru A, Gopalani S, Hailu A, Horino M, Horita N, Husseini A, Huybrechts I, Inoue M, Islami F, Jakovljevic M, James S, Javanbakht M, Jee SH, Kasaeian A, Kedir MS, Khader YS, Khang YH, Kim D, Leigh J, Linn S, Lunevicius R, El Razek HMA, Malekzadeh R, Malta DC, Marcenes W, Markos D, Melaku YA, Meles KG, Mendoza W, Mengiste DT, Meretoja TJ, Miller TR, Mohammad KA, Mohammadi A, Mohammed S, Moradi-Lakeh M, Nagel G, Nand D, Le Nguyen Q, Nolte S, Ogbo FA, Oladimeji KE, Oren E, Pa M, Park EK, Pereira DM, Plass D, Qorbani M, Radfar A, Rafay A, Rahman M, Rana SM, Søreide K, Satpathy M, Sawhney M, Sepanlou SG, Shaikh MA, She J, Shiue I, Shore HR, Shrime MG, So S, Soneji S, Stathopoulou V, Stroumpoulis K, Sufiyan MB, Sykes BL, Tabarés-Seisdedos R, Tadese F, Tedla BA, Tessema GA, Thakur JS, Tran BX, Ukwaja KN, Uzochukwu BSC, Vlassov VV, Weiderpass E, Wubshet Terefe M, Yebyo HG, Yimam HH, Yonemoto N, Younis MZ, Yu C, Zaidi Z, Zaki MES, Zenebe ZM, Murray CJL, and Naghavi M
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- 2017
10. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
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Vos, T, Barber, Rm, Bell, B, Bertozzi Villa, A, Biryukov, S, Bolliger, I, Charlson, F, Davis, A, Degenhardt, L, Dicker, D, Duan, L, Erskine, H, Feigin, Vl, Ferrari, Aj, Fitzmaurice, C, Fleming, T, Graetz, N, Guinovart, C, Haagsma, J, Hansen, Gm, Hanson, Sw, Heuton, Kr, Higashi, H, Kassebaum, N, Kyu, H, Laurie, E, Liang, X, Lofgren, K, Lozano, R, Macintyre, Mf, Moradi Lakeh, M, Naghavi, M, Nguyen, G, Odell, S, Ortblad, K, Roberts, Da, Roth, Ga, Sandar, L, Serina, Pt, Stanaway, Jd, Steiner, C, Thomas, B, Vollset, Se, Whiteford, H, Wolock, Tm, Ye, P, Zhou, M, Ãvila, Ma, Aasvang, Gm, Abbafati, C, Abbasoglu, Ozgoren, A, Abd Allah, F, Abdel, Aziz, Abera, Sf, Aboyans, V, Abraham, Jp, Abraham, B, Abubakar, I, Abu Raddad, Lj, Abu Rmeileh, Nm, Aburto, Tc, Achoki, T, Ackerman, In, Adelekan, A, Ademi, Z, Adou, Ak, Adsuar, Jc, Arnlov, J, Agardh, Ee, Khabouri, Al, Alam, Ss, Alasfoor, D, Albittar, Mi, Alegretti, Ma, Aleman, Av, Alemu, Za, Alfonso Cristancho, R, Alhabib, S, Ali, R, Alla, F, Allebeck, P, Allen, Pj, Almazroa, Ma, Alsharif, U, Alvarez, E, Alvis, Guzman, Ameli, N, O, Amini, H, Ammar, W, Anderson, Bo, Anderson, Hr, Antonio, Ca, Anwari, P, Apfel, H, Arsenijevic, Vs, Artaman, A, Asghar, Rj, Assadi, R, Atkins, Ls, Atkinson, C, Badawi, A, Bahit, Mc, Bakfalouni, T, Balakrishnan, K, Balalla, S, Banerjee, A, Barker Collo, Sl, Barquera, S, Barregard, L, Barrero, Lh, Basu, S, Basu, A, Baxter, A, Beardsley, J, Bedi, N, Beghi, E, Bekele, T, Bell, Ml, Benjet, C, Bennett, Da, Bensenor, Im, Benzian, H, Bernabe, E, Beyene, Tj, Bhala, N, Bhalla, A, Bhutta, Z, Bienhoff, K, Bikbov, B, Bin, Abdulhak, Blore, Jd, Blyth, Fm, Bohensky, Ma, Bora, Basara, B, Borges, G, Bornstein, Nm, Bose, D, Boufous, S, Bourne, Rr, Boyers, Ln, Brainin, M, Brauer, M, Brayne, Ce, Brazinova, A, Breitborde, Nj, Brenner, H, Briggs, Ad, Brooks, Pm, Brown, J, Brugha, Ts, Buchbinder, R, Buckle, Gc, Bukhman, G, Bulloch, Ag, Burch, M, Burnett, R, Cardenas, R, Cabral, Nl, Campos, Nonato, Campuzano, Ir, Carapetis, Jc, Carpenter, Do, Caso, V, Castaneda Orjuela, Ca, Catala Lopez, F, Chadha, Vk, Chang, Jc, Chen, H, Chen, W, Chiang, Pp, Chimed Ochir, O, Chowdhury, R, Christensen, H, Christophi, Ca, Chugh, Ss, Cirillo, Massimo, Coggeshall, M, Cohen, A, Colistro, V, Colquhoun, Sm, Contreras, Ag, Cooper, Lt, Cooper, C, Cooperrider, K, Coresh, J, Cortinovis, M, Criqui, Mh, Crump, Ja, Cuevas Nasu, L, Dandona, R, Dandona, L, Dansereau, E, Dantes, Hg, Dargan, Pi, Davey, G, Davitoiu, Dv, Dayama, A, La, De, Cruz, Gongora, De, V, Vega, La, De, Sf, Leo, D, Del, Pozo, Cruz, Dellavalle, Rp, Deribe, K, Derrett, S, Des, Jarlais, Dessalegn, M, Deveber, Ga, Dharmaratne, Sd, Diaz Torne, C, Ding, El, Dokova, K, Dorsey, Er, Driscoll, Tr, Duber, H, Durrani, Am, Edmond, Km, Ellenbogen, Rg, Endres, M, Ermakov, Sp, Eshrati, B, Esteghamati, A, Estep, K, Fahimi, S, Farzadfar, F, Fay, Df, Felson, Dt, Fereshtehnejad, Sm, Fernandes, Jg, Ferri, Cp, Flaxman, A, Foigt, N, Foreman, Kj, Fowkes, Fg, Franklin, Rc, Furst, T, Futran, Nd, Gabbe, Bj, Gankpe, Fg, Garcia, Guerra, Geleijnse, Fa, Gessner, Bd, Gibney, Kb, Gillum, Rf, Ginawi, Ia, Giroud, M, Giussani, G, Goenka, S, Goginashvili, K, Gona, P, Gonzalez, De, Cosio, T, Gosselin, Ra, Gotay, Cc, Goto, A, Gouda, Hn, Guerrant, Rl, Gugnani, Hc, Gunnell, D, Gupta, R, Gutierrez, Ra, Hafezi Nejad, N, Hagan, H, Halasa, Y, Hamadeh, Rr, Hamavid, H, Hammami, M, Hankey, Gj, Hao, Y, Harb, Hl, Haro, Jm, Havmoeller, R, Hay, Rj, Hay, S, Hedayati, Mt, Heredia, Pi, Heydarpour, P, Hijar, M, Hoek, Hw, Hoffman, Hj, Hornberger, Jc, Hosgood, Hd, Hossain, M, Hotez, Pj, Hoy, Dg, Hsairi, M, Hu, H, Hu, G, Huang, Jj, Huang, C, Huiart, L, Husseini, A, Iannarone, M, Iburg, Km, Innos, K, Inoue, M, Jacobsen, Kh, Jassal, Sk, Jeemon, P, Jensen, Pn, Jha, V, Jiang, G, Jiang, Y, Jonas, Jb, Joseph, J, Juel, K, Kan, H, Karch, A, Karimkhani, C, Karthikeyan, G, Katz, R, Kaul, A, Kawakami, N, Kazi, Ds, Kemp, Ah, Kengne, Ap, Khader, Ys, Khalifa, Se, Khan, Ea, Khan, G, Khang, Yh, Khonelidze, I, Kieling, C, Kim, D, Kim, S, Kimokoti, Rw, Kinfu, Y, Kinge, Jm, Kissela, Bm, Kivipelto, M, Knibbs, L, Knudsen, Ak, Kokubo, Y, Kosen, S, Kramer, A, Kravchenko, M, Krishnamurthi, Rv, Krishnaswami, S, Kuate, Defo, Kucuk, B, Bicer, B, Kuipers, Ej, Kulkarni, Vs, Kumar, K, Kumar, Ga, Kwan, Gf, Lai, T, Lalloo, R, Lam, H, Lan, Q, Lansingh, Vc, Larson, H, Larsson, A, Lawrynowicz, Ae, Leasher, Jl, Lee, Jt, Leigh, J, Leung, R, Levi, M, Li, B, Li, Y, Liang, J, Lim, S, Lin, Hh, Lind, M, Lindsay, Mp, Lipshultz, Se, Liu, S, Lloyd, Bk, Lockett, Ohno, S, Logroscino, G, Looker, Kj, Lopez, Ad, Lopez Olmedo, N, Lortet Tieulent, J, Lotufo, Pa, Low, N, Lucas, Rm, Lunevicius, R, Lyons, Ra, Ma, J, Ma, S, Mackay, Mt, Majdan, M, Malekzadeh, R, Mapoma, Cc, Marcenes, W, March, Lm, Margono, C, Marks, Gb, Marzan, Mb, Masci, Jr, Mason Jones, Aj, Matzopoulos, Rg, Mayosi, Bm, Mazorodze, Tt, Mcgill, Nw, Mcgrath, Jj, Mckee, M, Mclain, A, Mcmahon, Bj, Meaney, Pa, Mehndiratta, Mm, Mejia Rodriguez, F, Mekonnen, W, Melaku, Ya, Meltzer, M, Memish, Za, Mensah, G, Meretoja, A, Mhimbira, Fa, Micha, R, Miller, Tr, Mills, Ej, Mitchell, Pb, Mock, Cn, Moffitt, Te, Mohamed, Ibrahim, N, Mohammad, Ka, Mokdad, Ah, Mola, Gl, Monasta, L, Montico, M, Montine, Tj, Moore, Ar, Moran, Ae, Morawska, L, Mori, R, Moschandreas, J, Moturi, Wn, Moyer, M, Mozaffarian, D, Mueller, Uo, Mukaigawara, M, Murdoch, Me, Murray, J, Murthy, Ks, Naghavi, P, Nahas, Z, Naheed, A, Naidoo, Ks, Naldi, L, Nand, D, Nangia, V, Narayan, Km, Nash, D, Nejjari, C, Neupane, Sp, Newman, Lm, Newton, Cr, Ng, M, Ngalesoni, Fn, Nhung, Nt, Nisar, Mi, Nolte, S, Norheim, Of, Norman, Re, Norrving, B, Nyakarahuka, L, Ih, Oh, Ohkubo, T, Omer, Sb, Opio, Jn, Ortiz, A, Pandian, Jd, Panelo, Ci, Papachristou, C, Park, Ek, Parry, Cd, Caicedo, Aj, Patten, Sb, Paul, Vk, Pavlin, Bi, Pearce, N, Pedraza, Ls, Pellegrini, Ca, Pereira, Dm, Perez Ruiz, Fp, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, Cb, Petzold, M, Phillips, Mr, Phillips, D, Phillips, B, Piel, Fb, Plass, D, Poenaru, D, Polanczyk, Gv, Polinder, S, Pope, Ca, Popova, S, Poulton, Rg, Pourmalek, F, Prabhakaran, D, Prasad, Nm, Qato, D, Quistberg, Da, Rafay, A, Rahimi, K, Rahimi Movaghar, V, Rahman, Su, Raju, M, Rakovac, I, Rana, Sm, Razavi, H, Refaat, A, Rehm, J, Remuzzi, G, Resnikoff, S, Ribeiro, Al, Riccio, Pm, Richardson, L, Richardus, Jh, Riederer, Am, Robinson, M, Roca, A, Rodriguez, A, Rojas Rueda, D, Ronfani, L, Rothenbacher, D, Roy, N, Ruhago, Gm, Sabin, N, Sacco, Rl, Ksoreide, K, Saha, S, Sahathevan, R, Sahraian, Ma, Sampson, U, Sanabria, Jr, Sanchez Riera, L, Santos, Is, Satpathy, M, Saunders, Je, Sawhney, M, Saylan, Mi, Scarborough, P, Schoettker, B, Schneider, Ij, Schwebel, Dc, Scott, Jg, Seedat, S, Sepanlou, Sg, Serdar, B, Servan Mori, Ee, Shackelford, K, Shaheen, A, Shahraz, S, Shamah, Levy, T, Shangguan, S, She, J, Sheikhbahaei, S, Shepard, Ds, Shi, P, Shibuya, K, Shinohara, Y, Shiri, R, Shishani, K, Shiue, I, Shrime, Mg, Sigfusdottir, Id, Silberberg, Dh, Simard, Ep, Sindi, S, Singh, Ja, 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Weichenthal, S, Weiderpass, E, Weintraub, Rg, Werdecker, A, Wessells, Kr, Westerman, R, Wilkinson, Jd, Williams, Hc, Williams, Tn, Woldeyohannes, Sm, Wolfe, Cd, Wong, Jq, Wong, H, Woolf, Ad, Wright, Jl, Wurtz, B, Xu, G, Yang, G, Yano, Y, Yenesew, Ma, Yentur, Gk, Yip, P, Yonemoto, N, Yoon, Sj, Younis, M, Yu, C, Kim, Ky, Zaki, Mel, Zhang, Y, Zhao, Z, Zhao, Y, Zhu, J, Zonies, D, Zunt, Jr, Salomon, Ja, Murray, C. J., Vos, T, Barber, Rm, Bell, B, Bertozzi-Villa, A, Biryukov, S, Bolliger, I, Charlson, F, Davis, A, Degenhardt, L, Dicker, D, Duan, L, Erskine, H, Feigin, Vl, Ferrari, Aj, Fitzmaurice, C, Fleming, T, Graetz, N, Guinovart, C, Haagsma, J, Hansen, Gm, Hanson, Sw, Heuton, Kr, Higashi, H, Kassebaum, N, Kyu, H, Laurie ELiang, X, Lofgren, K, Lozano, R, Macintyre, Mf, Moradi-Lakeh, M, Naghavi, M, Nguyen, G, Odell, S, Ortblad, K, Roberts, Da, Roth, Ga, Sandar, L, Serina, Pt, Stanaway, Jd, Steiner, C, Thomas, B, Vollset, Se, Whiteford, H, Wolock, Tm, Ye, P, Zhou, M, Ãvila, Ma, Aasvang, Gm, Abbafati, C, Abbasoglu Ozgoren, A, Abd-Allah, F, Abdel Aziz MI, Abera, Sf, Aboyans, V, Abraham, Jp, Abraham, B, Abubakar, I, Abu-Raddad, Lj, Abu-Rmeileh, Nm, Aburto, Tc, Achoki TAckerman IN, Adelekan, A, Ademi, Z, Adou, Ak, Adsuar, Jc, Arnlov, J, Agardh, Ee, Al Khabouri MJ, Alam, S, Alasfoor, D, Albittar, Mi, Alegretti MAAleman AV, Alemu, Za, Alfonso-Cristancho, R, Alhabib, S, Ali, R, Alla, F, Allebeck, P, Allen, Pj, Almazroa, Ma, Alsharif, U, Alvarez, E, Alvis-Guzman NAmeli, O, Amini, H, Ammar, W, Anderson, Bo, Anderson, Hr, Antonio, Ca, Anwari, P, Apfel, H, Arsenijevic, V, Artaman, A, Asghar, Rj, Assadi, R, Atkins, L, Atkinson, C, Badawi, A, Bahit, Mc, Bakfalouni, T, Balakrishnan, K, Balalla, S, Banerjee, A, Barker-Collo, Sl, Barquera, S, Barregard, L, Barrero LHBasu, S, Basu, A, Baxter, A, Beardsley, J, Bedi, N, Beghi, E, Bekele, T, Bell, Ml, Benjet, C, Bennett, Da, Bensenor, Im, Benzian, H, Bernabe, E, Beyene TJBhala, N, Bhalla, A, Bhutta, Z, Bienhoff, K, Bikbov, B, Bin Abdulhak, A, Blore, Jd, Blyth, Fm, Bohensky, Ma, Bora Basara, B, Borges, G, Bornstein, Nm, Bose, D, Boufous, S, Bourne, Rr, Boyers, Ln, Brainin, M, Brauer, M, Brayne, Ce, Brazinova, A, Breitborde, Nj, Brenner, H, Briggs, Ad, Brooks, Pm, Brown JBrugha TS, Buchbinder, R, Buckle, Gc, Bukhman, G, Bulloch, Ag, Burch, M, Burnett, R, Cardenas, R, Cabral, Nl, Campos Nonato IR, Campuzano JCCarapetis JR, Carpenter, Do, Caso, V, Castaneda-Orjuela, Ca, Catala-Lopez, F, Chadha, Vk, Chang, Jc, Chen, H, Chen, W, Chiang, Pp, Chimed-Ochir, O, Chowdhury, R, Christensen, H, Christophi, Ca, Chugh, S, Cirillo, M, Coggeshall, M, Cohen, A, Colistro, V, Colquhoun, Sm, Contreras, Ag, Cooper LTCooper, C, Cooperrider, K, Coresh, J, Cortinovis, M, Criqui, Mh, Crump, Ja, Cuevas-Nasu, L, Dandona, R, Dandona, L, Dansereau, E, Dantes, Hg, Dargan, Pi, Davey, G, Davitoiu, Dv, Dayama, A, De la Cruz-Gongora, V, de la Vega SF, De Leo, D, del Pozo-Cruz, B, Dellavalle, Rp, Deribe, K, Derrett, S, Des Jarlais DC, Dessalegn, M, Deveber, Ga, Dharmaratne, Sd, Diaz-Torne, C, Ding, El, Dokova, K, Dorsey, Er, Driscoll, Tr, Duber, H, Durrani, Am, Edmond, Km, Ellenbogen, Rg, Endres, M, Ermakov, Sp, Eshrati, B, Esteghamati, A, Estep, K, Fahimi, S, Farzadfar, F, Fay, Df, Felson, Dt, Fereshtehnejad SMFernandes JG, Ferri, Cp, Flaxman, A, Foigt, N, Foreman, Kj, Fowkes, Fg, Franklin, Rc, Furst, T, Futran, Nd, Gabbe, Bj, Gankpe, Fg, Garcia-Guerra FAGeleijnse JM, Gessner, Bd, Gibney, Kb, Gillum, Rf, Ginawi, Ia, Giroud, M, Giussani, G, Goenka, S, Goginashvili, K, Gona, P, Gonzalez de Cosio TGosselin RA, Gotay, Cc, Goto, A, Gouda, Hn, Guerrant, Rl, Gugnani, Hc, Gunnell, D, Gupta, R, Gutierrez, Ra, Hafezi-Nejad, N, Hagan HHalasa, Y, Hamadeh, Rr, Hamavid, H, Hammami, M, Hankey, Gj, Hao, Y, Harb, Hl, Haro, Jm, Havmoeller, R, Hay, Rj, Hay, S, Hedayati, Mt, Heredia Pi IB, Heydarpour, P, Hijar, M, Hoek, Hw, Hoffman, Hj, Hornberger, Jc, Hosgood, Hd, Hossain, M, Hotez, Pj, Hoy, Dg, Hsairi, M, Hu, H, Hu, G, Huang JJHuang, C, Huiart, L, Husseini, A, Iannarone, M, Iburg, Km, Innos, K, Inoue, M, Jacobsen, Kh, Jassal, Sk, Jeemon, P, Jensen, Pn, Jha, V, Jiang, G, Jiang YJonas JB, Joseph, J, Juel, K, Kan, H, Karch, A, Karimkhani, C, Karthikeyan, G, Katz, R, Kaul, A, Kawakami, N, Kazi, D, Kemp, Ah, Kengne, Ap, Khader, Y, Khalifa, Se, Khan, Ea, Khan, G, Khang, Yh, Khonelidze, I, Kieling, C, Kim, D, Kim, S, Kimokoti, Rw, Kinfu, Y, Kinge, Jm, Kissela, Bm, Kivipelto MKnibbs, L, Knudsen, Ak, Kokubo, Y, Kosen, S, Kramer, A, Kravchenko, M, Krishnamurthi, Rv, Krishnaswami, S, Kuate Defo, B, Kucuk Bicer, B, Kuipers EJKulkarni VS, Kumar, K, Kumar, Ga, Kwan, Gf, Lai, T, Lalloo, R, Lam, H, Lan, Q, Lansingh, Vc, Larson, H, Larsson, A, Lawrynowicz, Ae, Leasher, Jl, Lee, Jt, Leigh, J, Leung, R, Levi, M, Li, B, Li, Y, Liang, J, Lim, S, Lin, Hh, Lind, M, Lindsay, Mp, Lipshultz, Se, Liu, S, Lloyd, Bk, Lockett Ohno, S, Logroscino, G, Looker, Kj, Lopez, Ad, Lopez-Olmedo, N, Lortet-Tieulent, J, Lotufo, Pa, Low, N, Lucas, Rm, Lunevicius, R, Lyons, Ra, Ma, J, Ma, S, Mackay MTMajdan, M, Malekzadeh, R, Mapoma, Cc, Marcenes, W, March, Lm, Margono, C, Marks, Gb, Marzan, Mb, Masci, Jr, Mason-Jones, Aj, Matzopoulos RGMayosi BM, Mazorodze, Tt, Mcgill, Nw, Mcgrath, Jj, Mckee, M, Mclain, A, Mcmahon, Bj, Meaney, Pa, Mehndiratta, Mm, Mejia-Rodriguez, F, Mekonnen, W, Melaku, Ya, Meltzer, M, Memish, Za, Mensah, G, Meretoja, A, Mhimbira, Fa, Micha, R, Miller, Tr, Mills, Ej, Mitchell, Pb, Mock, Cn, Moffitt TEMohamed Ibrahim, N, Mohammad, Ka, Mokdad, Ah, Mola, Gl, Monasta, L, Montico, M, Montine, Tj, Moore, Ar, Moran, Ae, Morawska, L, Mori RMoschandreas, J, Moturi, Wn, Moyer, M, Mozaffarian, D, Mueller, Uo, Mukaigawara, M, Murdoch, Me, Murray, J, Murthy, K, Naghavi, P, Nahas ZNaheed, A, Naidoo, K, Naldi, L, Nand, D, Nangia, V, Narayan, Km, Nash, D, Nejjari, C, Neupane, Sp, Newman, Lm, Newton, Cr, Ng, M, Ngalesoni FNNhung NT, Nisar, Mi, Nolte, S, Norheim, Of, Norman, Re, Norrving, B, Nyakarahuka, L, Oh, Ih, Ohkubo, T, Omer, Sb, Opio, Jn, Ortiz, A, Pandian JDPanelo CI, Papachristou, C, Park, Ek, Parry, Cd, Caicedo, Aj, Patten, Sb, Paul, Vk, Pavlin, Bi, Pearce, N, Pedraza, L, Pellegrini, Ca, Pereira, Dm, Perez-Ruiz, Fp, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, Cb, Petzold, M, Phillips, Mr, Phillips, D, Phillips, B, Piel, Fb, Plass, D, Poenaru, D, Polanczyk GVPolinder, S, Pope, Ca, Popova, S, Poulton, Rg, Pourmalek, F, Prabhakaran, 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Heredia, Heydarpour, Pouria, Hijar, Martha, Hoek, Hans W., Hoffman, Howard J., Hornberger, John C., Hosgood, H. Dean, Hossain, Mazeda, Hotez, Peter J., Hoy, Damian G., Hsairi, Mohamed, Hu, Howard, Hu, Guoqing, Huang, John J., Huang, Cheng, Huiart, Laetitia, Husseini, Abdullatif, Iannarone, Marissa, Iburg, Kim M., Innos, Kaire, Inoue, Manami, Jacobsen, Kathryn H., Jassal, Simerjot K., Jeemon, Panniyammakal, Jensen, Paul N., Jha, Vivekanand, Jiang, Guohong, Jiang, Ying, Jonas, Jost B., Joseph, Jonathan, Juel, Knud, Kan, Haidong, Karch, Andre, Karimkhani, Chante, Karthikeyan, Ganesan, Katz, Ronit, Kaul, Anil, Kawakami, Norito, Kazi, Dhruv S., Kemp, Andrew H., Kengne, Andre P., Khader, Yousef S., Khalifa, Shams Eldin A.H., Khan, Ejaz A., Khan, Gulfaraz, Khang, Young-Ho, Khonelidze, Irma, Kieling, Christian, Kim, Daniel, Kim, Sungroul, Kimokoti, Ruth W., Kinfu, Yohanne, Kinge, Jonas M., Kissela, Brett M., Kivipelto, Miia, Knibbs, Luke, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kosen, Soewarta, Kramer, Alexander, Kravchenko, Michael, Krishnamurthi, Rita V., Krishnaswami, Sanjay, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kuipers, Ernst J., Kulkarni, Veena S., Kumar, Kaushalendra, Kumar, G Anil, Kwan, Gene F., Lai, Taavi, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lansingh, Van C., Larson, Heidi, Larsson, Ander, Lawrynowicz, Alicia E.B., Leasher, Janet L., Lee, Jong-Tae, Leigh, Jame, Leung, Ricky, Levi, Miriam, Li, Bin, Li, Yichong, Li, Yongmei, Liang, Juan, Lim, Stephen, Lin, Hsien-Ho, Lind, Margaret, Lindsay, M Patrice, Lipshultz, Steven E., Liu, Shiwei, Lloyd, Belinda K., Ohno, Summer Lockett, Logroscino, Giancarlo, Looker, Katharine J., Lopez, Alan D., Lopez-Olmedo, Nancy, Lortet-Tieulent, Joannie, Lotufo, Paulo A., Low, Nicola, Lucas, Robyn M., Lunevicius, Raimunda, Lyons, Ronan A., Ma, Jixiang, Ma, Stefan, Mackay, Mark T., Majdan, Marek, Malekzadeh, Reza, Mapoma, Christopher C., Marcenes, Wagner, March, Lyn M., Margono, Chri, Marks, Guy B., Marzan, Melvin B., Masci, Joseph R., Mason-Jones, Amanda J., Matzopoulos, Richard G., Mayosi, Bongani M., Mazorodze, Tasara T., Mcgill, Neil W., Mcgrath, John J., Mckee, Martin, Mclain, Abby, Mcmahon, Brian J., Meaney, Peter A., Mehndiratta, Man Mohan, Mejia-Rodriguez, Fabiola, Mekonnen, Wubegzier, Melaku, Yohannes A., Meltzer, Michele, Memish, Ziad A., Mensah, George, Meretoja, Atte, Mhimbira, Francis A., Micha, Renata, Miller, Ted R., Mills, Edward J., Mitchell, Philip B., Mock, Charles N., Moffitt, Terrie E., Ibrahim, Norlinah Mohamed, Mohammad, Karzan A., Mokdad, Ali H., Mola, Glen L., Monasta, Lorenzo, Montico, Marcella, Montine, Thomas J., Moore, Ami R., Moran, Andrew E., Morawska, Lidia, Mori, Rintaro, Moschandreas, Joanna, Moturi, Wilkister N., Moyer, Madeline, Mozaffarian, Dariush, Mueller, Ulrich O., Mukaigawara, Mitsuru, Murdoch, Michele E., Murray, Joseph, Murthy, Kinnari S., Naghavi, Paria, Nahas, Ziad, Naheed, Aliya, Naidoo, Kovin S., Naldi, Luigi, Nand, Devina, Nangia, Vinay, Narayan, K.M. Venkat, Nash, Deni, Nejjari, Chakib, Neupane, Sudan P., Newman, Lori M., Newton, Charles R., Ng, Marie, Ngalesoni, Frida N., Nhung, Nguyen T., Nisar, Muhammad I., Nolte, Sandra, Norheim, Ole F., Norman, Rosana E., Norrving, Bo, Nyakarahuka, Luke, Oh, In Hwan, Ohkubo, Takayoshi, Omer, Saad B., Opio, John Nelson, Ortiz, Alberto, Pandian, Jeyaraj D., Panelo, Carlo Irwin A., Papachristou, Christina, Park, Eun-Kee, Parry, Charles D., Caicedo, Angel J. 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Ryan, Westerman, Ronny, Wilkinson, James D., Williams, Hywel C., Williams, Thomas N., Woldeyohannes, Solomon M., Wolfe, Charles D.A., Wong, John Q., Wong, Haidong, Woolf, Anthony D., Wright, Jonathan L., Wurtz, Brittany, Xu, Gelin, Yang, Gonghuan, Yano, Yuichiro, Yenesew, Muluken A., Yentur, Gokalp K., Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Younis, Mustafa, Yu, Chuanhua, Kim, Kim Yun, Zaki, Maysaa El Sayed, Zhang, Yong, Zhao, Zheng, Zhao, Yong, Zhu, Jun, Zonies, David, Zunt, Joseph R., Salomon, Joshua A., Murray, Christopher J.L., Cell biology, Gastroenterology & Hepatology, Epidemiology, Health Technology Assessment (HTA), and Public Health
- Subjects
Male ,Gerontology ,Nutrition and Disease ,Epidemiology ,years lived with disability, Global burden of disease, acute and chronic diseases, countries ,Prevalence ,Disease ,Global Health ,Medical and Health Sciences ,Conduct disorder ,Otitis-media ,Cost of Illness ,Residence Characteristics ,Voeding en Ziekte ,80 and over ,Global health ,2.2 Factors relating to the physical environment ,2.1 Biological and endogenous factors ,countries ,Aetiology ,Child ,Aged, 80 and over ,Medicine(all) ,education.field_of_study ,ATTENTION-DEFICIT/HYPERACTIVITY DISORDER ,Incidence ,Mortality rate ,Incidence (epidemiology) ,Pain Research ,Neglected Diseases ,Alcohol dependence ,General Medicine ,Middle Aged ,Global burden of disease ,Global Burden of Disease Study 2013 Collaborators ,Mental Health ,Infectious Diseases ,Attention deficit/Hyperactivity disorder ,Burden of Illness ,Child, Preschool ,Acute Disease ,Female ,Life Sciences & Biomedicine ,Adult ,medicine.medical_specialty ,Adolescent ,GBD 2013 ,Population ,acute and chronic diseases ,Young Adult ,Mental-disorders ,Age Distribution ,Medicine, General & Internal ,Weights ,General & Internal Medicine ,medicine ,Humans ,Life Science ,Disabled Persons ,Sex Distribution ,Preschool ,education ,Developing Countries ,VLAG ,Aged ,Science & Technology ,business.industry ,Developed Countries ,Cutaneous Leishmaniasis ,Infant, Newborn ,Infant ,Health outcomes ,Newborn ,medicine.disease ,Comorbidity ,Brain Disorders ,years lived with disability ,Good Health and Well Being ,Disease, injury, incidence, prevalence, YLDs, GBD 2010 ,Chronic Disease ,Wounds and Injuries ,business ,2.4 Surveillance and distribution ,Iron-deficiency ,Demography - Abstract
Summary Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries. Funding Bill & Melinda Gates Foundation. Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries. Funding Bill & Melinda Gates Foundation.
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- 2015
11. 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
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S., Islam, Nazrul, Jacobsen, Kathryn H., Jaenisch, Thomas, Jahanmehr, Nader, Jakovljevic, Mihajlo B., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jensen, Paul N., Jha, Vivekanand, Jin, Ye, John, Denny, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalkonde, Yogeshwar, Kamal, Ritul, Kan, Haidong, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Karthikeyan, Ganesan, Kasaeian, Amir, Kassaw, Nigussie Assefa, Kassebaum, Nicholas J., Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Keiyoro, Peter Njenga, Kelbore, Sefonias Getachew, Kemp, Andrew Haddon, Kengne, Andre Pascal, Keren, Andre, Kereselidze, Maia, Kesavachandran, Chandrasekharan Nair, Ketema, Ezra Belay, Khader, Yousef Saleh, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khang, Young-Ho, Khera, Sahil, Khoja, Abdullah Tawfih Abdullah, Khosravi, Mohammad Hossein, Kibret, 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Alex, Halasa, Yara A., Hamadeh, Randah Ribhi, Hambisa, Mitiku Teshome, Hamidi, Samer, Hammami, Mouhanad, Hancock, Jamie, Handal, Alexis J., Hankey, Graeme J., Hao, Yuantao, Harb, Hilda L., Hareri, Habtamu Abera, Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassanvand, Mohammad Sadegh, Havmoeller, Rasmus, Hay, Roderick J., Hay, Simon I., He, Fei, Heredia-Pi, Ileana Beatriz, Herteliu, Claudiu, Hilawe, Esayas Haregot, Hoek, Hans W., Horita, Nobuyuki, Hosgood, H. Dean, Hostiuc, Sorin, Hotez, Peter J., Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, Hsiang, Huang, John J., Iburg, Kim Moesgaard, Igumbor, Ehimario Uche, Ileanu, Bogdan Vasile, Inoue, Manami, Irenso, Asnake Ararsa, Irvine, Caleb M. S., Islam, Nazrul, Jacobsen, Kathryn H., Jaenisch, Thomas, Jahanmehr, Nader, Jakovljevic, Mihajlo B., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jensen, Paul N., Jha, Vivekanand, Jin, Ye, John, Denny, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalkonde, Yogeshwar, Kamal, Ritul, Kan, Haidong, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Karthikeyan, Ganesan, Kasaeian, Amir, Kassaw, Nigussie Assefa, Kassebaum, Nicholas J., Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Keiyoro, Peter Njenga, Kelbore, Sefonias Getachew, Kemp, Andrew Haddon, Kengne, Andre Pascal, Keren, Andre, Kereselidze, Maia, Kesavachandran, Chandrasekharan Nair, Ketema, Ezra Belay, Khader, Yousef Saleh, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khang, Young-Ho, Khera, Sahil, Khoja, Abdullah Tawfih Abdullah, Khosravi, Mohammad Hossein, Kibret, Getiye Dejenu, Kieling, Christian, Kim, Cho-Il, Kim, Daniel, Kim, Pauline, Kim, Sungroul, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kishawi, Sami, Kissimova-Skarbek, Katarzyna A., Kissoon, Niranjan, Kivimaki, Mika, Knudsen, Ann Kristin, Kopec, JA, Koul, PA, Krohn, KJ, Kuipers, EJ, Kulikoff, XR, Kulkarni, VS, Kumar, GA, Kumsa, FA, Lagat, AK, Lager, ACJ, Lal, DK, Larson, HJ, Laryea, DO, Lavados, PM, Lee, PH, Liben, ML, Lim, SS, Lipshultz, SE, Lorch, SA, Lotufo, PA, Lyons, RA, Macarayan, ERK, Machado, IE, Mackay, MT, Malta, DC, Mantovani, LG, Mapoma, CC, Marczak, LB, Marks, GB, Martins-Melo, FR, Maulik, PK, Mayosi, BM, McAlinden, C, McGarvey, ST, McGrath, JJ, McKee, M, Mehndiratta, MM, Mehta, KM, Mekonnen, TC, Meles, KG, Memish, ZA, Mengesha, MM, Mengistie, MA, Mengistu, DT, Menon, GR, Menota, BG, Mensah, GA, Meretoja, TJ, Mezgebe, HB, Miller, TR, Mills, EJ, Mirrakhimov, EM, Mishra, SR, Mohammad, KA, Mohammed, KE, Mohan, MBV, Mohanty, SK, Mokdad, AH, Mollenkopf, SK, Montañez Hernandez, JC, Mooney, MD, Moore, AR, Morrison, SD, Mruts, KB, Mueller, UO, Murthy, GVS, Musa, KI, Nachega, JB, Naidoo, KS, Nascimento, BR, Nguyen, CT, Nguyen, QL, Nguyen, TH, Ningrum, DNA, Nisar, MI, Nong, VM, Norheim, OF, Noubiap, JJN, Obermeyer, CM, O'Donnell, MJ, Ogbo, FA, Oh, IH, Olagunju, AT, Olusanya, BO, Olusanya, JO, Owolabi, MO, Oyekale, AS, Mahesh, PA, Pacella, RE, Panda, BK, Park, EK, Patten, SB, Patton, GC, Pereira, DM, Peterson, CB, Petri, WA, Phillips, MR, Piel, FB, Pigott, DM, Postma, MJ, Poulton, RG, Rabiee, RHS, Rahman, MHU, Rahman, SU, Rai, RK, Rana, SM, Ranabhat, CL, Rao, PV, Rego, MAS, Reiner, RC, Renzaho, AMNN, Rezai, MS, Ribeiro, AL, Rokni, MB, Roth, GA, Ruhago, GM, Sabde, YD, Sachdev, PS, Sahraian, MA, Salomon, JA, Salvi, SS, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Santos, IS, Santric Milicevic, MM, Saylan, MI, Schmidt, MI, Schneider, IJC, Schutte, AE, Schwebel, DC, Seid, AM, Sepanlou, SG, Servan-Mori, EE, Shackelford, KA, Shaikh, MA, Islam, SMS, Shetty, BP, Shrime, MG, Sigfusdottir, ID, Silberberg, DH, Silva, DAS, Silva, JP, Silveira, DGA, Singh, JA, Singh, PK, Sinha, DN, Smith, DL, Sobaih, BHA, Soriano, JB, Sreeramareddy, CT, Stein, DJ, Stokes, MA, Sufiyan, Muawiyyah B, Suliankatchi, Rizwan A, Sunguya, BF, Sur, PJ, Sykes, BL, Szoeke, CEI, Tadakamadla, SK, Tekle, Dejen Y, Temsah, MH, Terkawi, AS, Tesema, CL, Thompson, AH, Thomson, AJ, Thrift, AG, Tiruye, TY, Tran, BX, Tuem, KB, Tuzcu, EM, Ukwaja, KN, Undurraga, EA, Uthman, OA, Uzochukwu, BSC, Van Boven, JFM, Varakin, YY, Vasconcelos, AMN, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Waid, JL, Wang, YP, Weintraub, RG, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Workie, SB, Yalew, AZ, Yan, LL, Yimam, HH, Yirsaw, BD, Yoon, SJ, Younis, MZ, Zenebe, ZM, Zerfu, TA, Zhang, AL, Zuhlke, LJ, Lopez, AD, and Murray, CJL
- Abstract
Background: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. Methods: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to
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- 2017
12. Oncogenic Met receptor induces ectopic structures in Xenopus embryos
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Bong Ys, Hyun-Shik Lee, Kathleen Mood, Akihiko Ishimura, Caroline Saucier, I Daar, and Park Ek
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Embryonic Induction ,MAPK/ERK pathway ,Cancer Research ,Cell signaling ,Embryo, Nonmammalian ,biology ,Xenopus ,Signal transducing adaptor protein ,Proto-Oncogene Proteins c-met ,biology.organism_classification ,Mutation ,Genetics ,Cancer research ,biology.protein ,Animals ,Phosphorylation ,Female ,GRB2 ,Molecular Biology ,Tyrosine kinase - Abstract
Top of pageAbstract When aberrantly expressed or activated, the Met receptor tyrosine kinase is involved in tumor invasiveness and metastasis. In this study, we have used the Xenopus embryonic system to define the role of various Met proximal-binding partners and downstream signaling pathways in regulating an induced morphogenetic event. We show that expression of an oncogenic derivative of the Met receptor (Tpr-Met) induces ectopic morphogenetic structures during Xenopus embryogenesis. Using variant forms of Tpr-Met that are engineered to recruit a specific signaling molecule of choice, we demonstrate that the sole recruitment of either the Grb2 or the Shc adaptor protein is sufficient to induce ectopic structures and anterior reduction, while the recruitment of PI-3Kinase (PI-3K) is necessary but not sufficient for this effect. In contrast, the recruitment of PLC can initiate the induction, but fails to maintain or elongate supernumerary structures. Finally, evidence indicates that the Ras/Raf/MAPK pathway is necessary, but not sufficient to induce these structures. This study also emphasizes the importance of examining signaling molecules in the regulatory context that is provided by receptor/effector interactions when assessing a role in cell growth and differentiation. Keywords: Met receptor, Xenopus, tyrosine kinase signaling
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- 2006
13. Postoperative Pain After Total Laparoscopic Hysterectomy: A Comparison of Transumbilical Single-Port Access and Conventional Three-Port Laparoscopic Surgery
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Lee, YS, primary, Lee, KH, additional, Park, EK, additional, Lee, YK, additional, and Kim, SM, additional
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- 2016
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14. Study of Chung-Pae as a potential therapeutic agent against chronic obstructive pulmonary disease
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Kim, KH, primary, Hwang, JH, additional, Kim, KI, additional, Park, EK, additional, Lee, BJ, additional, Choi, JY, additional, Jung, HJ, additional, Jung, SK, additional, and Joo, M, additional
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- 2015
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15. Single-Port (Grove Port) Laparoscopic Hysterectomy With Extracoporeal Vaginal Cuff Closure Versus Conventional Laparoscopic Hysterectomy With Intracoporeal Vaginal Cuff Closure
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Han, YS, primary, Lee, YS, additional, and Park, EK, additional
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- 2015
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16. The anti-angiogenic herbal composition Ob-X inhibits adipose tissue growth in obese mice
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Park Ek, Hahm Jc, Park By, Kim My, Hyunghee Lee, Michung Yoon, Hong Y, Lee J, Choi S, Park D, and Lee Hs
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medicine.medical_specialty ,Matrix metalloproteinase inhibitor ,Angiogenesis ,Endocrinology, Diabetes and Metabolism ,Adipose tissue macrophages ,Immunoblotting ,Medicine (miscellaneous) ,Adipose tissue ,Mice, Obese ,Angiogenesis Inhibitors ,White adipose tissue ,Matrix metalloproteinase ,Matrix Metalloproteinase Inhibitors ,Melissa ,Neovascularization ,Mice ,Internal medicine ,medicine ,Adipocytes ,Animals ,Nutrition and Dietetics ,Chemistry ,Plant Extracts ,Rats ,Endocrinology ,Adipose Tissue ,Morus ,medicine.symptom ,Ex vivo ,Phytotherapy - Abstract
The growth and development of adipose tissue are thought to be associated with angiogenesis and extracellular matrix remodeling. As the composition of the herbal extract called Ob-X has been shown to have both anti-angiogenic and matrix metalloproteinase (MMP)-inhibiting activities, we hypothesized that growth of adipose tissue can be regulated by Ob-X. The effects of Ob-X on angiogenesis and extracellular matrix remodeling were measured using in vitro and ex vivo assays. The effects of Ob-X on adipose tissue growth were investigated in nutritionally obese mice. Ob-X inhibited angiogenesis in a dose-dependent manner in the human umbilical vein endothelial cell tube formation assay in vitro and the rat aortic ring assay ex vivo. Ob-X also suppressed MMP activity in vitro. Administration of Ob-X to high fat diet-induced obese mice produced significant reductions in body weight gain and adipose tissue mass compared with control. The mass of both visceral (VSC) and subcutaneous (SC) fat was reduced in Ob-X-treated mice. The size of adipocytes in VSC and SC adipose tissues was also significantly reduced in Ob-X-treated mice. Ob-X treatment decreased the blood vessel density and MMP activity in VSC adipose tissues of nutritionally obese mice. Ob-X reduced mRNA levels of angiogenic factors (VEGF-A and FGF-2) and MMPs (MMP-2 and MMP-9), whereas it increased mRNA levels of angiogenic inhibitors (TSP-1, TIMP-1 and TIMP-2) in SC and VSC adipose tissues of nutritionally obese mice. Ob-X, which has anti-angiogenic and MMP-inhibitory activities, reduces adipose tissue mass in nutritionally induced obese mice, providing evidence that adipose tissue growth and development may be prevented by inhibiting angiogenesis. In addition, these data suggest that regulation of adipose tissue growth by inhibiting angiogenesis may alter the expression of genes involved in angiogenesis and the MMP system.
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- 2010
17. ACM/springer mobile networks and applications (monet) special issue on 'collaborative computing: Networking, applications and worksharing
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Shi, W, Joshi, J, Zhang, T, Park, EK, Quemada, J, Shi, W, Joshi, J, Zhang, T, Park, EK, and Quemada, J
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The 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom) selected the three papers that relate to the theme of CollaborateCom and mobile computing. In the first paper titled 'Still Alive: Extending Keep-Alive Intervals in P2P Overlay Networks', Price et al. consider the node failure detection problem within peer-to-peer networks, an inherent trade-off between timely detection and bandwidth consumption for network maintenance. In the second paper titled 'The Design and Evaluation of Task Assignment Algorithms for GWAP-based Geospatial Tagging Systems', Chen et al. introduce three metrics and develop five task assignment algorithms to evaluate the GWAP-based geospatial tagging systems. In the third paper titled 'Secure Neighborhood Creation in Wireless Ad Hoc Networks using Hop Count Discrepancies', Hayajneh et al. study the secure neighborhood discovery problem in ad hoc and sensors networks, in which the nodes typically try to discover their neighbors simply by broadcasting a neighbor discovery request.
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- 2012
18. Flexible frameworks for actionable knowledge discovery
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Cao, L, Zhao, Y, Zhang, H, Luo, D, Zhang, C, Park, EK, Cao, L, Zhao, Y, Zhang, H, Luo, D, Zhang, C, and Park, EK
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Most data mining algorithms and tools stop at the mining and delivery of patterns satisfying expected technical interestingness. There are often many patterns mined but business people either are not interested in them or do not know what follow-up actions to take to support their business decisions. This issue has seriously affected the widespread employment of advanced data mining techniques in greatly promoting enterprise operational quality and productivity. In this paper, we present a formal view of actionable knowledge discovery (AKD) from the system and decision-making perspectives. AKD is a closed optimization problem-solving process from problem definition, framework/model design to actionable pattern discovery, and is designed to deliver operable business rules that can be seamlessly associated or integrated with business processes and systems. To support such processes, we correspondingly propose, formalize, and illustrate four types of generic AKD frameworks: Postanalysis-based AKD, Unified-Interestingness-based AKD, Combined-Mining-based AKD, and Multisource Combined-Mining-based AKD (MSCM-AKD). A real-life case study of MSCM-based AKD is demonstrated to extract debt prevention patterns from social security data. Substantial experiments show that the proposed frameworks are sufficiently general, flexible, and practical to tackle many complex problems and applications by extracting actionable deliverables for instant decision making. © 2006 IEEE.
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- 2010
19. ID1201, chinaberry extract, decreases β-amyloid and attenuates memory deficit
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Kim, JH, primary, Kim, JY, additional, Lee, MJ, additional, Yoo, JS, additional, Park, EK, additional, Jeon, YJ, additional, Yeon, SW, additional, Hwang, BY, additional, and Kang, JH, additional
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- 2012
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20. Dynamic biclustering of microarray data by multi-objective immune optimization
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Liu, Junwan, primary, Li, Zhoujun, additional, Hu, Xiaohua, additional, Chen, Yiming, additional, and Park, EK, additional
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- 2011
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21. Special issue on information dissemination and new services in P2P systems
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Song, Min, primary, Shetty, Sachin, additional, Jiang, Wenbin, additional, and Park, EK, additional
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- 2010
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22. Exploratory analysis of protein translation regulatory networks using hierarchical random graphs
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Wu, Daniel D, primary, Hu, Xiaohua, additional, Park, EK, additional, Wang, Xiaofeng, additional, Feng, Jiali, additional, and Wu, Xindong, additional
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- 2010
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23. Session details: Data mining (KM)
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Park, EK, primary
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- 2007
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24. 9-cis retinoic acid promotes lymphangiogenesis and enhances lymphatic vessel regeneration: therapeutic implications of 9-cis retinoic acid for secondary lymphedema.
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Choi I, Lee S, Kyoung Chung H, Suk Lee Y, Eui Kim K, Choi D, Park EK, Yang D, Ecoiffier T, Monahan J, Chen W, Aguilar B, Lee HN, Yoo J, Koh CJ, Chen L, Wong AK, Hong YK, Choi, Inho, and Lee, Sunju
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- 2012
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25. Proliferation and osteoblastic differentiation of bone marrow stem cells: comparison of vertebral body and iliac crest.
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Min WK, Bae JS, Park BC, Jeon IH, Jin HK, Son MJ, Park EK, Kim SY, Min, Woo-Kie, Bae, Jae-Sung, Park, Byung-Chul, Jeon, In-Ho, Jin, Hee Kyung, Son, Min-Jung, Park, Eui Kyun, and Kim, Shin-Yoon
- Abstract
Bone marrow stem cells (BMSCs) can be obtained from the vertebral body (VB) and iliac crest (IC) for augmenting spinal arthrodesis. However, it is still not evaluated, which of the two sites would have a better BMSCs potential on Proliferation and osteoblastic differentiation is still not evaluated. Fourteen patients (10 men and 4 women) undergoing posterolateral lumbar arthrodesis and pedicle screw instrumentation were involved. The mean age was 54.7 years (range 31-75 years). Bone marrow aspirates were obtained from the vertebral body through the bilateral pedicle and were quantified relative to matched, bilateral aspirates from the iliac crest that were obtained from the same patient and at the same time. The mononuclear cell count and concentration of BMSCs were calculated and compared. Proliferation and osteoblastic differentiation of each of the BMSCs were characterized using biochemical and molecular biology techniques. Concentration (cells/mL) of BMSCs from VB and IC were 3.73 × 10(3) and 3.19 × 10(3), respectively (P > 0.05). VB and IC exhibited similar proliferation pattern at 3, 5 and 7 days, but BMSCs from the VB exhibited an increased mineralization staining with Alizarin Red S at 14 days. BMSCs from both anatomic sites expressed comparable levels of CD29, CD34, CD44, CD90 and CD105. VB and IC displayed similar levels of expression of ALP, type I collagen and osterix, but VB expressed higher level of osteocalcin and Runx-2, especially at 14 and 21 days. Our studies show that BMSCs from VB have osteogenic differentiation potential similar to IC. Based on these findings, we suggest that BMSCs from VB would be comparable candidates for osseous graft supplementation especially in spinal fusion procedures. [ABSTRACT FROM AUTHOR]
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- 2010
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26. Soluble mesothelin-related protein in an asbestos-exposed population: the dust diseases board cohort study.
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Park EK, Sandrini A, Yates DH, Creaney J, Robinson BW, Thomas PS, and Johnson AR
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RATIONALE: Soluble mesothelin-related protein (SMRP) is raised in epithelial-type malignant mesothelioma (MM), but the utility of SMRP in screening for MM is unknown. OBJECTIVES: We aimed to evaluate SMRP in an asbestos-exposed cohort. METHODS: A total of 538 subjects were studied. Those with elevated SMRP (> or =2.5 nM) underwent further investigation including positron emission tomography/computed tomography. MEASUREMENTS AND MAIN RESULTS: Mean (+/-SD) SMRP in healthy subjects exposed to asbestos (n = 223) was 0.79 (+/-0.45) nM. Fifteen subjects had elevated SMRP, of whom one had lung cancer, which was successfully resected. Another with lung cancer was undetected by SMRP. No subjects were diagnosed with MM. Mean SMRP in healthy subjects was significantly lower than in subjects with pleural plaques alone (P < 0.01). CONCLUSIONS: This is the first large-scale prospective study of SMRP for screening for malignancy in asbestos-exposed individuals. A high false-positive rate was observed. SMRP seems unlikely to prove useful in screening for MM. [ABSTRACT FROM AUTHOR]
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- 2008
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27. Intense accumulation of 18F-FDG, not enhancement on MRI, helps to guide the surgical biopsy accurately in soft tissue tumors.
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Park JH, Park EK, Kang CH, Kim CH, Choe JG, Noh W, Park, Jong Hoon, Park, Eun Kyung, Kang, Chang Ho, Kim, Chul Hwan, Choe, Jae Gol, and Noh, Won
- Abstract
Soft tissue sarcomas are a highly heterogeneous group of malignancies that arise from mesenchymal tissues. Grading of soft tissue sarcomas is an important prerequisite for the choice of therapy and estimation of prognosis. However, incisional biopsy of huge soft tissue sarcoma lesions frequently fails to provide an accurate diagnosis when there is a benign component, cystic changes and/or necrosis. MRI is helpful in evaluating the extent of the sarcoma lesion, vascularization, invasiveness and integrity of surrounding tissue, but definitive differentiation of benignity and malignancy is not possible with it. In this study, positron emission tomography using [(18)F]-2-fluoro-2-deoxy-D-glucose successfully guided surgeons to identify the most hypermetabolic and, therefore, the most suitable biopsy sites of huge soft tissue sarcoma. [ABSTRACT FROM AUTHOR]
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- 2009
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28. Blood-based early detection of malignant mesothelioma.
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Park EK, Thomas PS, Creaney J, Johnson AR, Robinson BW, and Yates DH
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- 2009
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29. Voices of Korean-American students.
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Park EK
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KOREAN Americans , *QUESTIONNAIRES , *ATTITUDE (Psychology) , *STUDENTS - Abstract
The purpose of this study was to identify the special needs or concerns of Korean-American students by utilizing a survey questionnaire. Further, this data can be used to assess if any significant subset of these students are educationally at risk and in need of specialized services beyond regular education. A total sample of 207 Korean-American students in selected cities in California participated in the study. The findings suggest that the overwhelming majority of these students are well-adjusted to the way of life at home and school in California, and their self-concept appears to be highly positive. On the other hand, the majority (78%) of these students were concerned about their parents' limited English proficiency. Also, a considerable number (56%) were not happy with their school work, and approximately one third expressed concern regarding learning difficulties and the English language barrier. [ABSTRACT FROM AUTHOR]
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- 1995
30. Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020
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Dana Bryazka, Marissa B Reitsma, Max G Griswold, Kalkidan Hassen Abate, Cristiana Abbafati, Mohsen Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Amir Abdoli, Mohammad Abdollahi, Abu Yousuf Md Abdullah, E S Abhilash, Eman Abu-Gharbieh, Juan Manuel Acuna, Giovanni Addolorato, Oladimeji M Adebayo, Victor Adekanmbi, Kishor Adhikari, Sangeet Adhikari, Qorinah Estiningtyas Sakilah Adnani, Saira Afzal, Wubetu Yimam Agegnehu, Manik Aggarwal, Bright Opoku Ahinkorah, Araz Ramazan Ahmad, Sajjad Ahmad, Tauseef Ahmad, Ali Ahmadi, Sepideh Ahmadi, Haroon Ahmed, Tarik Ahmed Rashid, Chisom Joyqueenet Akunna, Hanadi Al Hamad, Md Zakiul Alam, Dejene Tsegaye Alem, Kefyalew Addis Alene, Yousef Alimohamadi, Atiyeh Alizadeh, Kasim Allel, Jordi Alonso, Saba Alvand, Nelson Alvis-Guzman, Firehiwot Amare, Edward Kwabena Ameyaw, Sohrab Amiri, Robert Ancuceanu, Jason A Anderson, Catalina Liliana Andrei, Tudorel Andrei, Jalal Arabloo, Muhammad Arshad, Anton A Artamonov, Zahra Aryan, Malke Asaad, Mulusew A Asemahagn, Thomas Astell-Burt, Seyyed Shamsadin Athari, Desta Debalkie Atnafu, Prince Atorkey, Alok Atreya, Floriane Ausloos, Marcel Ausloos, Getinet Ayano, Martin Amogre ayanore Ayanore, Olatunde O Ayinde, Jose L Ayuso-Mateos, Sina Azadnajafabad, Melkalem Mamuye Azanaw, Mohammadreza Azangou-Khyavy, Amirhossein Azari Jafari, Ahmed Y Azzam, Ashish D Badiye, Nasser Bagheri, Sara Bagherieh, Mohan Bairwa, Shankar M Bakkannavar, Ravleen Kaur Bakshi, Awraris Hailu Balchut/Bilchut, Till Winfried Bärnighausen, Fabio Barra, Amadou Barrow, Pritish Baskaran, Luis Belo, Derrick A Bennett, Isabela M Benseñor, Akshaya Srikanth Bhagavathula, Neeraj Bhala, Ashish Bhalla, Nikha Bhardwaj, Pankaj Bhardwaj, Sonu Bhaskar, Krittika Bhattacharyya, Vijayalakshmi S Bhojaraja, Bagas Suryo Bintoro, Elena A Elena Blokhina, Belay Boda Abule Bodicha, Archith Boloor, Cristina Bosetti, Dejana Braithwaite, Hermann Brenner, Nikolay Ivanovich Briko, Andre R Brunoni, Zahid A Butt, Chao Cao, Yin Cao, Rosario Cárdenas, Andre F Carvalho, Márcia Carvalho, Joao Mauricio Castaldelli-Maia, Giulio Castelpietra, Luis F S Castro-de-Araujo, Maria Sofia Cattaruzza, Promit Ananyo Chakraborty, Jaykaran Charan, Vijay Kumar Chattu, Akhilanand Chaurasia, Nicolas Cherbuin, Dinh-Toi Chu, Nandita Chudal, Sheng-Chia Chung, Chuchu Churko, Liliana G Ciobanu, Massimo Cirillo, Rafael M Claro, Simona Costanzo, Richard G Cowden, Michael H Criqui, Natália Cruz-Martins, Garland T Culbreth, Berihun Assefa Dachew, Omid Dadras, Xiaochen Dai, Giovanni Damiani, Lalit Dandona, Rakhi Dandona, Beniam Darge Daniel, Anna Danielewicz, Jiregna Darega Gela, Kairat Davletov, Jacyra Azevedo Paiva de Araujo, Antonio Reis de Sá-Junior, Sisay Abebe Debela, Azizallah Dehghan, Andreas K Demetriades, Meseret Derbew Molla, Rupak Desai, Abebaw Alemayehu Desta, Diana Dias da Silva, Daniel Diaz, Lankamo Ena Digesa, Mengistie Diress, Milad Dodangeh, Deepa Dongarwar, Fariba Dorostkar, Haneil Larson Dsouza, Bereket Duko, Bruce B Duncan, Kristina Edvardsson, Michael Ekholuenetale, Frank J Elgar, Muhammed Elhadi, Mohamed A Elmonem, Aman Yesuf Endries, Sharareh Eskandarieh, Azin Etemadimanesh, Adeniyi Francis Fagbamigbe, Ildar Ravisovich Fakhradiyev, Fatemeh Farahmand, Carla Sofia e Sá Farinha, Andre Faro, Farshad Farzadfar, Ali Fatehizadeh, Nelsensius Klau Fauk, Valery L Feigin, Rachel Feldman, Xiaoqi Feng, Zinabu Fentaw, Simone Ferrero, Lorenzo Ferro Desideri, Irina Filip, Florian Fischer, Joel Msafiri Francis, Richard Charles Franklin, Peter Andras Gaal, Mohamed M Gad, Silvano Gallus, Fabio Galvano, Balasankar Ganesan, Tushar Garg, Mesfin Gebrehiwot Damtew Gebrehiwot, Teferi Gebru Gebremeskel, Mathewos Alemu Gebremichael, Tadele Regasa Gemechu, Lemma Getacher, Motuma Erena Getachew, Abera Getachew Obsa, Asmare Getie, Amir Ghaderi, Mansour Ghafourifard, Alireza Ghajar, Seyyed-Hadi Ghamari, Lilian A Ghandour, Mohammad Ghasemi Nour, Ahmad Ghashghaee, Sherief Ghozy, Franklin N Glozah, Ekaterina Vladimirovna Glushkova, Justyna Godos, Amit Goel, Salime Goharinezhad, Mahaveer Golechha, Pouya Goleij, Mohamad Golitaleb, Felix Greaves, Michal Grivna, Giuseppe Grosso, Temesgen Worku Gudayu, Bhawna Gupta, Rajeev Gupta, Sapna Gupta, Veer Bala Gupta, Vivek Kumar Gupta, Nima Hafezi-Nejad, Arvin Haj-Mirzaian, Brian J Hall, Rabih Halwani, Tiilahun Beyene Handiso, Graeme J Hankey, Sanam Hariri, Josep Maria Haro, Ahmed I Hasaballah, Hossein Hassanian-Moghaddam, Simon I Hay, Khezar Hayat, Golnaz Heidari, Mohammad Heidari, Delia Hendrie, Claudiu Herteliu, Demisu Zenbaba Heyi, Kamal Hezam, Mbuzeleni Mbuzeleni Hlongwa, Ramesh Holla, Md Mahbub Hossain, Sahadat Hossain, Seyed Kianoosh Hosseini, Mehdi hosseinzadeh, Mihaela Hostiuc, Sorin Hostiuc, Guoqing Hu, Junjie Huang, Salman Hussain, Segun Emmanuel Ibitoye, Irena M Ilic, Milena D Ilic, Mustapha Immurana, Lalu Muhammad Irham, M Mofizul Islam, Rakibul M Islam, Sheikh Mohammed Shariful Islam, Hiroyasu Iso, Ramaiah Itumalla, Masao Iwagami, Roxana Jabbarinejad, Louis Jacob, Mihajlo Jakovljevic, Zahra Jamalpoor, Elham Jamshidi, Sathish Kumar Jayapal, Umesh Umesh Jayarajah, Ranil Jayawardena, Rime Jebai, Seyed Ali Jeddi, Alelign Tasew Jema, Ravi Prakash Jha, Har Ashish Jindal, Jost B Jonas, Tamas Joo, Nitin Joseph, Farahnaz Joukar, Jacek Jerzy Jozwiak, Mikk Jürisson, Ali Kabir, Robel Hussen Kabthymer, Bhushan Dattatray Kamble, Himal Kandel, Girum Gebremeskel Kanno, Neeti Kapoor, Ibraheem M Karaye, Salah Eddin Karimi, Bekalu Getnet Kassa, Rimple Jeet Kaur, Gbenga A Kayode, Mohammad Keykhaei, Himanshu Khajuria, Rovshan Khalilov, Imteyaz A Khan, Moien AB Khan, Hanna Kim, Jihee Kim, Min Seo Kim, Ruth W Kimokoti, Mika Kivimäki, Vitalii Klymchuk, Ann Kristin Skrindo Knudsen, Ali-Asghar Kolahi, Vladimir Andreevich Korshunov, Ai Koyanagi, Kewal Krishan, Yuvaraj Krishnamoorthy, G Anil Kumar, Narinder Kumar, Nithin Kumar, Ben Lacey, Tea Lallukka, Savita Lasrado, Jerrald Lau, Sang-woong Lee, Wei-Chen Lee, Yo Han Lee, Lee-Ling Lim, Stephen S Lim, Stany W Lobo, Platon D Lopukhov, Stefan Lorkowski, Rafael Lozano, Giancarlo Lucchetti, Farzan Madadizadeh, Áurea M Madureira-Carvalho, Soleiman Mahjoub, Ata Mahmoodpoor, Rashidul Alam Mahumud, Alaa Makki, Mohammad-Reza Malekpour, Narayana Manjunatha, Borhan Mansouri, Mohammad Ali Mansournia, Jose Martinez-Raga, Francisco A Martinez-Villa, Richard Matzopoulos, Pallab K Maulik, Mahsa Mayeli, John J McGrath, Jitendra Kumar Meena, Entezar Mehrabi Nasab, Ritesh G Menezes, Gert B M Mensink, Alexios-Fotios A Mentis, Atte Meretoja, Bedasa Taye Merga, Tomislav Mestrovic, Junmei Miao Jonasson, Bartosz Miazgowski, Ana Carolina Micheletti Gomide Nogueira de Sá, Ted R Miller, GK Mini, Andreea Mirica, Antonio Mirijello, Seyyedmohammadsadeq Mirmoeeni, Erkin M Mirrakhimov, Sanjeev Misra, Babak Moazen, Maryam Mobarakabadi, Marcello Moccia, Yousef Mohammad, Esmaeil Mohammadi, Abdollah Mohammadian-Hafshejani, Teroj Abdulrahman Mohammed, Nagabhishek Moka, Ali H Mokdad, Sara Momtazmanesh, Yousef Moradi, Ebrahim Mostafavi, Sumaira Mubarik, Erin C Mullany, Beemnet Tekabe Mulugeta, Efrén Murillo-Zamora, Christopher J L Murray, Julius C Mwita, Mohsen Naghavi, Mukhammad David Naimzada, Vinay Nangia, Biswa Prakash Nayak, Ionut Negoi, Ruxandra Irina Negoi, Seyed Aria Nejadghaderi, Samata Nepal, Sudan Prasad Prasad Neupane, Sandhya Neupane Kandel, Yeshambel T Nigatu, Ali Nowroozi, Khan M Nuruzzaman, Chimezie Igwegbe Nzoputam, Kehinde O Obamiro, Felix Akpojene Ogbo, Ayodipupo Sikiru Oguntade, Hassan Okati-Aliabad, Babayemi Oluwaseun Olakunde, Gláucia Maria Moraes Oliveira, Ahmed Omar Bali, Emad Omer, Doris V Ortega-Altamirano, Adrian Otoiu, Stanislav S Otstavnov, Bilcha Oumer, Mahesh P A, Alicia Padron-Monedero, Raffaele Palladino, Adrian Pana, Songhomitra Panda-Jonas, Anamika Pandey, Ashok Pandey, Shahina Pardhan, Tarang Parekh, Eun-Kee Park, Charles D H Parry, Fatemeh Pashazadeh Kan, Jay Patel, Siddhartha Pati, George C Patton, Uttam Paudel, Shrikant Pawar, Amy E Peden, Ionela-Roxana Petcu, Michael R Phillips, Marina Pinheiro, Evgenii Plotnikov, Pranil Man Singh Pradhan, Akila Prashant, Jianchao Quan, Amir Radfar, Alireza Rafiei, Pankaja Raghav Raghav, Vafa Rahimi-Movaghar, Azizur Rahman, Md Mosfequr Rahman, Mosiur Rahman, Amir Masoud Rahmani, Shayan Rahmani, Chhabi Lal Ranabhat, Priyanga Ranasinghe, Chythra R Rao, Drona Prakash Rasali, Mohammad-Mahdi Rashidi, Zubair Ahmed Ratan, David Laith Rawaf, Salman Rawaf, Lal Rawal, Andre M N Renzaho, Negar Rezaei, Saeid Rezaei, Mohsen Rezaeian, Seyed Mohammad Riahi, Esperanza Romero-Rodríguez, Gregory A Roth, Godfrey M Rwegerera, Basema Saddik, Erfan Sadeghi, Reihaneh Sadeghian, Umar Saeed, Farhad Saeedi, Rajesh Sagar, Amirhossein Sahebkar, Harihar Sahoo, Mohammad Ali Sahraian, KM Saif-Ur-Rahman, Sarvenaz Salahi, Hamideh Salimzadeh, Abdallah M Samy, Francesco Sanmarchi, Milena M Santric-Milicevic, Yaser Sarikhani, Brijesh Sathian, Ganesh Kumar Saya, Mehdi Sayyah, Maria Inês Schmidt, Aletta Elisabeth Schutte, Michaël Schwarzinger, David C Schwebel, Abdul-Aziz Seidu, Nachimuthu Senthil Kumar, SeyedAhmad SeyedAlinaghi, Allen Seylani, Feng Sha, Sarvenaz Shahin, Fariba Shahraki-Sanavi, Shayan Shahrokhi, Masood Ali Shaikh, Elaheh Shaker, Murad Ziyaudinovich Shakhmardanov, Mehran Shams-Beyranvand, Sara Sheikhbahaei, Rahim Ali Sheikhi, Adithi Shetty, Jeevan K Shetty, Damtew Solomon Shiferaw, Mika Shigematsu, Rahman Shiri, Reza Shirkoohi, K M Shivakumar, Velizar Shivarov, Parnian Shobeiri, Roman Shrestha, Negussie Boti Sidemo, Inga Dora Sigfusdottir, Diego Augusto Santos Silva, Natacha Torres da Silva, Jasvinder A Singh, Surjit Singh, Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina, David A Sleet, Marco Solmi, YONATAN SOLOMON, Suhang Song, Yimeng Song, Reed J D Sorensen, Sergey Soshnikov, Ireneous N Soyiri, Dan J Stein, Sonu Hangma Subba, Miklós Szócska, Rafael Tabarés-Seisdedos, Takahiro Tabuchi, Majid Taheri, Ker-Kan Tan, Minale Tareke, Elvis Enowbeyang Tarkang, Gebremaryam Temesgen, Worku Animaw Temesgen, Mohamad-Hani Temsah, Kavumpurathu Raman Thankappan, Rekha Thapar, Nikhil Kenny Thomas, Chalachew Tiruneh, Jovana Todorovic, Marco Torrado, Mathilde Touvier, Marcos Roberto Tovani-Palone, Mai Thi Ngoc Tran, Sergi Trias-Llimós, Jaya Prasad Tripathy, Alireza Vakilian, Rohollah Valizadeh, Mehdi Varmaghani, Shoban Babu Varthya, Tommi Juhani Vasankari, Theo Vos, Birhanu Wagaye, Yasir Waheed, Mandaras Tariku Walde, Cong Wang, Yanzhong Wang, Yuan-Pang Wang, Ronny Westerman, Nuwan Darshana Wickramasinghe, Abate Dargie Wubetu, Suowen Xu, Kazumasa Yamagishi, Lin Yang, Gesila Endashaw E Yesera, Arzu Yigit, Vahit Yiğit, Ayenew Engida Ayenew Engida Yimaw, Dong Keon Yon, Naohiro Yonemoto, Chuanhua Yu, Siddhesh Zadey, Mazyar Zahir, Iman Zare, Mikhail Sergeevich Zastrozhin, Anasthasia Zastrozhina, Zhi-Jiang Zhang, Chenwen Zhong, Mohammad Zmaili, Yves Miel H Zuniga, Emmanuela Gakidou, University of St Andrews. School of Medicine, University of St Andrews. Population and Behavioural Science Division, Department of Public Health, University of Helsinki, Hjelt Institute (-2014), Helsinki Inequality Initiative (INEQ), Clinicum, Helsinki University Hospital Area, Bill & Melinda Gates Foundation, King Edward Medical University (Pakistán), Alexander von Humboldt Foundation, University of Oxford (Reino Unido), Medical Research Council (Reino Unido), NIH - National Institute of Mental Health (NIMH) (Estados Unidos), Canada Research Chairs, National Health and Medical Research Council (Australia), National Heart Foundation of Australia, Ministry of Education, Science and Technological Development (Serbia), Wellcome Trust, NIH - National Institute on Aging (NIA) (Estados Unidos), Finlands Akademi (Finlandia), Panjab University (India), Federal Ministry of Education & Research (Alemania), National Council for Scientific and Technological Development (Brasil), Danish National Research Foundation, Queensland Centre for Mental Health Research (Australia), South African Medical Research Council, National Natural Science Foundation of China, Charles Sturt University (Australia), Ain Shams University (Egipto), Mizoram University (India), Kasturba Medical College (India), Manipal Academy of Higher Education (India), Coordenação de Aperfeicoamento de Pessoal de Nível Superior (Brasil), Ministerio de Ciencia e Innovación (España), Collaborators, GBD 2020 Alcohol, Bryazka, Dana, Reitsma, Marissa B, Griswold, Max G, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdoli, Amir, Abdollahi, Mohammad, Abdullah, Abu Yousuf Md, Abhilash, E S, Abu-Gharbieh, Eman, Acuna, Juan Manuel, Addolorato, Giovanni, Adebayo, Oladimeji M, Adekanmbi, Victor, Adhikari, Kishor, Adhikari, Sangeet, Adnani, Qorinah Estiningtyas Sakilah, Afzal, Saira, Agegnehu, Wubetu Yimam, Aggarwal, Manik, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Sajjad, Ahmad, Tauseef, Ahmadi, Ali, Ahmadi, Sepideh, Ahmed, Haroon, Ahmed Rashid, Tarik, Akunna, Chisom Joyqueenet, Al Hamad, Hanadi, Alam, Md Zakiul, Alem, Dejene Tsegaye, Alene, Kefyalew Addi, Alimohamadi, Yousef, Alizadeh, Atiyeh, Allel, Kasim, Alonso, Jordi, Alvand, Saba, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Amiri, Sohrab, Ancuceanu, Robert, Anderson, Jason A, Andrei, Catalina Liliana, Andrei, Tudorel, Arabloo, Jalal, Arshad, Muhammad, Artamonov, Anton A, Aryan, Zahra, Asaad, Malke, Asemahagn, Mulusew A, Astell-Burt, Thoma, Athari, Seyyed Shamsadin, Atnafu, Desta Debalkie, Atorkey, Prince, Atreya, Alok, Ausloos, Floriane, Ausloos, Marcel, Ayano, Getinet, Ayanore, Martin Amogre ayanore, Ayinde, Olatunde O, Ayuso-Mateos, Jose L, Azadnajafabad, Sina, Azanaw, Melkalem Mamuye, Azangou-Khyavy, Mohammadreza, Azari Jafari, Amirhossein, Azzam, Ahmed Y, Badiye, Ashish D, Bagheri, Nasser, Bagherieh, Sara, Bairwa, Mohan, Bakkannavar, Shankar M, Bakshi, Ravleen Kaur, Balchut/bilchut, Awraris Hailu, Bärnighausen, Till Winfried, Barra, Fabio, Barrow, Amadou, Baskaran, Pritish, Belo, Lui, Bennett, Derrick A, Benseñor, Isabela M, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhalla, Ashish, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhaskar, Sonu, Bhattacharyya, Krittika, Bhojaraja, Vijayalakshmi S, Bintoro, Bagas Suryo, Blokhina, Elena A Elena, Bodicha, Belay Boda Abule, Boloor, Archith, Bosetti, Cristina, Braithwaite, Dejana, Brenner, Hermann, Briko, Nikolay Ivanovich, Brunoni, Andre R, Butt, Zahid A, Cao, Chao, Cao, Yin, Cárdenas, Rosario, Carvalho, Andre F, Carvalho, Márcia, Castaldelli-Maia, Joao Mauricio, Castelpietra, Giulio, Castro-de-Araujo, Luis F S, Cattaruzza, Maria Sofia, Chakraborty, Promit Ananyo, Charan, Jaykaran, Chattu, Vijay Kumar, Chaurasia, Akhilanand, Cherbuin, Nicola, Chu, Dinh-Toi, Chudal, Nandita, Chung, Sheng-Chia, Churko, Chuchu, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Costanzo, Simona, Cowden, Richard G, Criqui, Michael H, Cruz-Martins, Natália, Culbreth, Garland T, Dachew, Berihun Assefa, Dadras, Omid, Dai, Xiaochen, Damiani, Giovanni, Dandona, Lalit, Dandona, Rakhi, Daniel, Beniam Darge, Danielewicz, Anna, Darega Gela, Jiregna, Davletov, Kairat, de Araujo, Jacyra Azevedo Paiva, de Sá-Junior, Antonio Rei, Debela, Sisay Abebe, Dehghan, Azizallah, Demetriades, Andreas K, Derbew Molla, Meseret, Desai, Rupak, Desta, Abebaw Alemayehu, Dias da Silva, Diana, Diaz, Daniel, Digesa, Lankamo Ena, Diress, Mengistie, Dodangeh, Milad, Dongarwar, Deepa, Dorostkar, Fariba, Dsouza, Haneil Larson, Duko, Bereket, Duncan, Bruce B, Edvardsson, Kristina, Ekholuenetale, Michael, Elgar, Frank J, Elhadi, Muhammed, Elmonem, Mohamed A, Endries, Aman Yesuf, Eskandarieh, Sharareh, Etemadimanesh, Azin, Fagbamigbe, Adeniyi Franci, Fakhradiyev, Ildar Ravisovich, Farahmand, Fatemeh, Farinha, Carla Sofia e Sá, Faro, Andre, Farzadfar, Farshad, Fatehizadeh, Ali, Fauk, Nelsensius Klau, Feigin, Valery L, Feldman, Rachel, Feng, Xiaoqi, Fentaw, Zinabu, Ferrero, Simone, Ferro Desideri, Lorenzo, Filip, Irina, Fischer, Florian, Francis, Joel Msafiri, Franklin, Richard Charle, Gaal, Peter Andra, Gad, Mohamed M, Gallus, Silvano, Galvano, Fabio, Ganesan, Balasankar, Garg, Tushar, Gebrehiwot, Mesfin Gebrehiwot Damtew, Gebremeskel, Teferi Gebru, Gebremichael, Mathewos Alemu, Gemechu, Tadele Regasa, Getacher, Lemma, Getachew, Motuma Erena, Getachew Obsa, Abera, Getie, Asmare, Ghaderi, Amir, Ghafourifard, Mansour, Ghajar, Alireza, Ghamari, Seyyed-Hadi, Ghandour, Lilian A, Ghasemi Nour, Mohammad, Ghashghaee, Ahmad, Ghozy, Sherief, Glozah, Franklin N, Glushkova, Ekaterina Vladimirovna, Godos, Justyna, Goel, Amit, Goharinezhad, Salime, Golechha, Mahaveer, Goleij, Pouya, Golitaleb, Mohamad, Greaves, Felix, Grivna, Michal, Grosso, Giuseppe, Gudayu, Temesgen Worku, Gupta, Bhawna, Gupta, Rajeev, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vivek Kumar, Hafezi-Nejad, Nima, Haj-Mirzaian, Arvin, Hall, Brian J, Halwani, Rabih, Handiso, Tiilahun Beyene, Hankey, Graeme J, Hariri, Sanam, Haro, Josep Maria, Hasaballah, Ahmed I, Hassanian-Moghaddam, Hossein, Hay, Simon I, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Hendrie, Delia, Herteliu, Claudiu, Heyi, Demisu Zenbaba, Hezam, Kamal, Hlongwa, Mbuzeleni Mbuzeleni, Holla, Ramesh, Hossain, Md Mahbub, Hossain, Sahadat, Hosseini, Seyed Kianoosh, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hu, Guoqing, Huang, Junjie, Hussain, Salman, Ibitoye, Segun Emmanuel, Ilic, Irena M, Ilic, Milena D, Immurana, Mustapha, Irham, Lalu Muhammad, Islam, M Mofizul, Islam, Rakibul M, Islam, Sheikh Mohammed Shariful, Iso, Hiroyasu, Itumalla, Ramaiah, Iwagami, Masao, Jabbarinejad, Roxana, Jacob, Loui, Jakovljevic, Mihajlo, Jamalpoor, Zahra, Jamshidi, Elham, Jayapal, Sathish Kumar, Jayarajah, Umesh Umesh, Jayawardena, Ranil, Jebai, Rime, Jeddi, Seyed Ali, Jema, Alelign Tasew, Jha, Ravi Prakash, Jindal, Har Ashish, Jonas, Jost B, Joo, Tama, Joseph, Nitin, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Ali, Kabthymer, Robel Hussen, Kamble, Bhushan Dattatray, Kandel, Himal, Kanno, Girum Gebremeskel, Kapoor, Neeti, Karaye, Ibraheem M, Karimi, Salah Eddin, Kassa, Bekalu Getnet, Kaur, Rimple Jeet, Kayode, Gbenga A, Keykhaei, Mohammad, Khajuria, Himanshu, Khalilov, Rovshan, Khan, Imteyaz A, Khan, Moien AB, Kim, Hanna, Kim, Jihee, Kim, Min Seo, Kimokoti, Ruth W, Kivimäki, Mika, Klymchuk, Vitalii, Knudsen, Ann Kristin Skrindo, Kolahi, Ali-Asghar, Korshunov, Vladimir Andreevich, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Yuvaraj, Kumar, G Anil, Kumar, Narinder, Kumar, Nithin, Lacey, Ben, Lallukka, Tea, Lasrado, Savita, Lau, Jerrald, Lee, Sang-woong, Lee, Wei-Chen, Lee, Yo Han, Lim, Lee-Ling, Lim, Stephen S, Lobo, Stany W, Lopukhov, Platon D, Lorkowski, Stefan, Lozano, Rafael, Lucchetti, Giancarlo, Madadizadeh, Farzan, Madureira-Carvalho, Áurea M, Mahjoub, Soleiman, Mahmoodpoor, Ata, Mahumud, Rashidul Alam, Makki, Alaa, Malekpour, Mohammad-Reza, Manjunatha, Narayana, Mansouri, Borhan, Mansournia, Mohammad Ali, Martinez-Raga, Jose, Martinez-Villa, Francisco A, Matzopoulos, Richard, Maulik, Pallab K, Mayeli, Mahsa, Mcgrath, John J, Meena, Jitendra Kumar, Mehrabi Nasab, Entezar, Menezes, Ritesh G, Mensink, Gert B M, Mentis, Alexios-Fotios A, Meretoja, Atte, Merga, Bedasa Taye, Mestrovic, Tomislav, Miao Jonasson, Junmei, Miazgowski, Bartosz, Micheletti Gomide Nogueira de Sá, Ana Carolina, Miller, Ted R, Mini, Gk, Mirica, Andreea, Mirijello, Antonio, Mirmoeeni, Seyyedmohammadsadeq, Mirrakhimov, Erkin M, Misra, Sanjeev, Moazen, Babak, Mobarakabadi, Maryam, Moccia, Marcello, Mohammad, Yousef, Mohammadi, Esmaeil, Mohammadian-Hafshejani, Abdollah, Mohammed, Teroj Abdulrahman, Moka, Nagabhishek, Mokdad, Ali H, Momtazmanesh, Sara, Moradi, Yousef, Mostafavi, Ebrahim, Mubarik, Sumaira, Mullany, Erin C, Mulugeta, Beemnet Tekabe, Murillo-Zamora, Efrén, Murray, Christopher J L, Mwita, Julius C, Naghavi, Mohsen, Naimzada, Mukhammad David, Nangia, Vinay, Nayak, Biswa Prakash, Negoi, Ionut, Negoi, Ruxandra Irina, Nejadghaderi, Seyed Aria, Nepal, Samata, Neupane, Sudan Prasad Prasad, Neupane Kandel, Sandhya, Nigatu, Yeshambel T, Nowroozi, Ali, Nuruzzaman, Khan M, Nzoputam, Chimezie Igwegbe, Obamiro, Kehinde O, Ogbo, Felix Akpojene, Oguntade, Ayodipupo Sikiru, Okati-Aliabad, Hassan, Olakunde, Babayemi Oluwaseun, Oliveira, Gláucia Maria Morae, Omar Bali, Ahmed, Omer, Emad, Ortega-Altamirano, Doris V, Otoiu, Adrian, Otstavnov, Stanislav S, Oumer, Bilcha, P A, Mahesh, Padron-Monedero, Alicia, Palladino, Raffaele, Pana, Adrian, Panda-Jonas, Songhomitra, Pandey, Anamika, Pandey, Ashok, Pardhan, Shahina, Parekh, Tarang, Park, Eun-Kee, Parry, Charles D H, Pashazadeh Kan, Fatemeh, Patel, Jay, Pati, Siddhartha, Patton, George C, Paudel, Uttam, Pawar, Shrikant, Peden, Amy E, Petcu, Ionela-Roxana, Phillips, Michael R, Pinheiro, Marina, Plotnikov, Evgenii, Pradhan, Pranil Man Singh, Prashant, Akila, Quan, Jianchao, Radfar, Amir, Rafiei, Alireza, Raghav, Pankaja Raghav, Rahimi-Movaghar, Vafa, Rahman, 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Ir, Phillips, Mr, Pinheiro, M, Plotnikov, E, Pradhan, Pm, Prashant, A, Quan, Jc, Radfar, A, Rafiei, A, Raghav, Pr, Movaghar, Vr, Rahman, A, Rahman, Mm, Rahman, M, Rahmani, Am, Rahmani, S, Ranabhat, Cl, Ranasinghe, P, Rao, Cr, Rasali, Dp, Rashidi, Mm, Ratan, Za, Rawaf, Dl, Rawaf, S, Rawal, L, Renzaho, Amn, Rezaei, N, Rezaei, S, Rezaeian, M, Riahi, Sm, Rodriguez, Er, Roth, Ga, Rwegerera, Gm, Saddik, B, Sadeghi, E, Sadeghian, R, Saeed, U, Saeedi, F, Sagar, R, Sahebkar, A, Sahoo, H, Sahraian, Ma, Rahman, Ksu, Salahi, S, Salimzadeh, H, Samy, Am, Sanmarchi, F, Milicevic, Mm, Sarikhani, Y, Sathian, B, Saya, Gk, Sayyah, M, Schmidt, Mi, Schutte, Ae, Schwarzinger, M, Schwebel, Dc, Seidu, Aa, Seyedalinaghi, S, Seylani, A, Sha, F, Shahin, S, Sanavi, F, Shahrokhi, S, Shaikh, Ma, Shaker, E, Shakhmardanov, Mz, Beyranvand, M, Sheikhbahaei, S, Sheikhi, Ra, Shetty, A, Shetty, Jk, Shiferaw, D, Shigematsu, M, Shiri, R, Shirkoohi, R, Shivakumar, Km, Shivarov, V, Shobeiri, P, Shrestha, R, Sidemo, Nb, Sigfusdottir, Id, Silva, Da, da Silva, Nt, Singh, Ja, Singh, S, Skryabin, Vy, Skryabina, Aa, Sleet, Da, Solmi, M, Solomon, Y, Song, S, Song, Ym, Sorensen, Rjd, Soshnikov, S, Soyiri, In, Stein, Dj, Subba, Sh, Szocska, M, Seisdedos, Rt, Tabuchi, T, Taheri, M, Tan, Kk, Tareke, M, Tarkang, Ee, Temesgen, G, Temesgen, Wa, Temsah, Mh, Thankappan, Kr, Thapar, R, Thomas, Nk, Tiruneh, C, Todorovic, J, Torrado, M, Touvier, M, Palone, Mrt, Tran, Mtn, Llimos, St, Tripathy, Jp, Vakilian, A, Valizadeh, R, Varmaghani, M, Varthya, Sb, Vasankari, Tj, Vos, T, Wagaye, B, Waheed, Y, Walde, Mt, Wang, C, Wang, Yz, Wang, Yp, Westerman, R, Wickramasinghe, Nd, Wubetu, Ad, Xu, S, Yamagishi, K, Yang, L, Yesera, Gee, Yigit, A, Yimaw, Ae, Yon, Dk, Yonemoto, N, Yu, Ch, Zadey, S, Zahir, M, Zare, I, Zastrozhin, M, Zastrozhina, A, Zhang, Zj, Zhong, Cw, Zmaili, M, Zuniga, Ymh, Gakidou, E, Madureira-Carvalho, Am, Ciobanu, LG, Gakidou, Emma, and GBD 2020 Alcohol Collaborators
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Adult ,Male ,Alcohol Drinking ,CONTROL POLICIES ,adult ,Child, Preschool ,Female ,Geography ,Global Burden of Disease ,Global Health ,Humans ,Middle Aged ,Quality-Adjusted Life Years ,Risk Factors ,NDAS ,ALL-CAUSE ,GUIDELINES ,GBD 2020 Alcohol Collaborators ,COST-EFFECTIVENESS ,Medicine, General & Internal ,DRINKING ,SDG 3 - Good Health and Well-being ,RA0421 ,General & Internal Medicine ,Quality-Adjusted Life Year ,RA0421 Public health. Hygiene. Preventive Medicine ,DRINKERS ,Child ,Preschool ,11 Medical and Health Sciences ,METAANALYSIS ,MCC ,Science & Technology ,global burden of disease ,Risk Factor ,General Medicine ,CANCER ,alcohol drinking ,AC ,3121 General medicine, internal medicine and other clinical medicine ,REDUCED MORTALITY ,Life Sciences & Biomedicine ,Human - Abstract
Background: The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year. Methods: For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol. Findings: The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male. Interpretation: There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol. Research reported in this publication was supported by the Bill & Melinda Gates Foundation. S Afzal acknowledges the support for intellectual contributions to this manuscript by the Department of Community Medicine and Epidemiology at King Edward Medical University, Lahore, Pakistan. T Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. L Belo acknowledges support from FCT in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of UCIBIO and the project LA/P/0140/2020 of i4HB. D Bennett is supported by the UK Medical Research Council Population Health Research Unit at the University of Oxford (Oxford, UK). M Carvalho acknowledges support from FCT in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of UCIBIO and the project LA/P/0140/2020 of i4HB. L Castro-de-Araujo was funded by the Medical Research Council (UK), Grant no. MR/T03355X/1 and by the National Institute of Mental Health Grant no. R01MH128911. FJ Elgar is supported by the Canada Research Chairs program. F Greaves acknowledges support from the NIHR Applied Research Collaboration for NW London. V K Gupta acknowledges funding support from the National Health and Medical Research Council (NHMRC), Australia. VB Gupta acknowledges funding support from the National Health and Medical Research Council (NHMRC), Australia. C Herteliu is partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. C Herteliu is partially supported by a grant from the Romanian Ministry of Research Innovation and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021. S Hussain was supported by the Operational Programme Research, Development and Education –Project, Postdoc2MUNI “(No. CZ.02.2.69/0.0/0.0/18_053/0016952). S M S Islam is funded by the National Health and Medical Research Council and received funding from the National Heart Foundation of Australia. The Serbian part of this GBD-related contribution has been co-financed through Grant OI 175 014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. M Kivimaki was supported by the Wellcome Trust (221854/Z/20/Z), the UK Medical Research Council (MR/S011676/1), the US National Institute on Aging (R01AG056477), and the Academy of Finland (350426). K Krishan is supported by the UGC Centre of Advanced Study (Phase II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. B Lacey acknowledges support from the UK Biobank, funded largely by the UK Medical Research Council and Wellcome. S Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research; grant agreement number 01EA1808A). G Lucchetti received a productivity scholarship from the Brazilian National Council for Scientific and Technological Development — CNPq (Level 1D). J McGrath was supported by the Danish National Research Foundation (Niels Bohr Professor). J McGrath is employed by the Queensland Centre for Mental Health Research (Australia), which receives support from the Queensland Health Department. C Parry acknowleges the South African Medical Research Council. A Peden is supported by a National Health and Medical Research Council Emerging Leadership Fellowship (Grant ID: APP2009306). M R Phillips was supported in part by the Global Alliance for Chronic Diseases - National Natural Science Foundation of China (NSFC. No. 81761128031). M Pinheiro acknowledges FCT for funding through program DL 57/2016 – Norma transitória. A Rahman acknowledges the support from the Data Science Research Unit in Charles Sturt University (Bathurst, NSW, Australia). U Saeed would like to acknowledge the International Center of Medical Sciences Research (ICMSR), Islamabad, Pakistan. A M Samy acknowledges support from Ain Shams University (Cairo, Egypt) and the Egyptian Fulbright Mission Program. N Senthil Kumar acknowledges the DBT, New Delhi sponsored Advanced State Level Biotech Hub (BT/NER/143/SP44475/2021), Mizoram University (Aizawl, Mizoram, India) for facilitating this work. F Sha is supported by the Shenzhen Science and Technology Program (Grant No. KQTD20190929172835662). A Shetty acknowledges Kasturba Medical College (Mangalore, India) and Manipal Academy of Higher Education (Manipal, India) for all the academic support. R Shrestha acknowledges a career development award from the National Institutes of Health (K01DA051346). D Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brazil (CAPES)-Finance Code 001 and is supported in part by CNPq - Brazil (309589/2021-5). D Sleet acknowledges partial support from Veritas Management Group, Inc and The Bizzell Group, LLC. S Trias-Llimós acknowledges research funding from the Juan de la Cierva-Formación program of the Spanish Ministry of Science and Innovation (FJC-2019-039314-I). Sí
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- 2022
31. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
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Zamani, M, Zare, Z, Zavala-Arciniega, L, Zegeye, Dt, Zegeye, Ea, Zeleke, Aj, Zendehdel, K, Zerfu, Ta, Zhang, Al, Zhang, X, Zhou, M, Zhu, J, Zimsen, Srm, Zodpey, S, Zoeckler, L, Zucker, I, Zuhlke, Ljj, Lim, S, and Murray, Cjl.
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GENDER-DIFFERENCES ,SUICIDE ,Medicine (all) ,Burden of Disease Study 2017 ,SDG ,CONSUMPTION ,11 Medical And Health Sciences ,GBD, Sustainable Development Goals ,PREVENTION ,ALCOHOL-USE ,CARDIOVASCULAR-DISEASE ,SMOKING PREVALENCE ,General & Internal Medicine ,factors risk ,Medicine and Health Sciences ,Human medicine ,CESSATION ,PERSPECTIVE ,TRANSITION - Abstract
Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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32. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Roth, Gregory A., Collaborotors, G. B. 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Miller, Tr, Miller-Petrie, Mk, Mini, Gk, Mirrakhimov, Em, Misganaw, At, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Moreno Velásquez, I, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Muchie, Kf, Mueller, Uo, Mumford, Je, Musa, Ki, Nachega, Jb, Nansseu, Jr, Nascimento, Br, Negoi, Ri, Newton, Crj, Ngalesoni, Fn, Ngunjiri, Jw, Nguyen, Aq, Nguyen, Ht, Nguyen, Lh, Nguyen, Th, Ningrum, Dna, Nirayo, Yl, Nixon, Mr, Norheim, Of, Noubiap, Jj, Nouri, Hr, Nourollahpour Shiadeh, M, Nowroozi, Mr, Odell, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Orpana, Hm, Ortiz, Jr, Øverland, S, Owolabi, Mo, Özdemir, R, P A, M, Pakhare, Ap, Pakpour, Ah, Pandian, Jd, Park, Ek, Parry, Cdh, Patton, Gc, Paturi, Vr, Paulson, Kr, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Postma, Mj, Purcell, Ca, Quistberg, Da, Rade, Kw, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahman, Mhu, Rahman, Ma, Rai, Rk, Ranabhat, Cl, Rao, Pc, Rawaf, Dl, Razo-García, C, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Robinson, Sr, Sahraian, Ma, Saldanha, Rf, Sambala, Ez, Samy, Am, Sanchez-Niño, Md, Santomauro, Df, Santos, Jv, Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sarmiento-Suárez, R, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serván-Mori, E, Shackelford, Ka, Shaheen, Aa, Shaikh, Ma, Shrime, Mg, Siddiqi, Tj, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Pk, Sinha, Dn, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Starodubov, Vi, Stein, Dj, Stewart, Lg, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sur, Pj, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekle, Mg, Temsah, Mh, Teshale, My, Tessema, Ga, Thankappan, Kr, Thrift, Ag, Thurston, Gd, To, Qg, Torre, Ae, Tortajada-Girbés, M, Tovani-Palone, Mr, Tran, Bx, Tran, Kb, Troeger, Ce, Truelsen, Tc, Truong, Nt, Tsadik, Ag, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Updike, Rl, Uthman, Oa, Uzun, Sb, Valdez, Pr, Vasankari, Tj, Vladimirov, Sk, Vollset, Se, Wagner, Gr, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weintraub, Rg, Weldegwergs, Kg, Werkneh, Aa, West, Te, Whiteford, Ha, Wilner, Lb, Wolfe, Cda, Wu, Yc, Wyper, Gma, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yentür, Gk, Yimer, Em, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaman, Sb, Zeleke, Aj, Zenebe, Zm, Zhang, Al, Zuhlke, Lj, and Murray, Cjl.
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Adult ,Male ,Adolescent ,national age-sex-specific mortality ,UNITED-STATES ,Global Health ,Socioeconomic Factor ,Global Burden of Disease ,GBD, causes of death ,Young Adult ,Age Distribution ,Life Expectancy ,General & Internal Medicine ,Cause of Death ,PUBLIC-HEALTH PROBLEM ,mortality ,282 causes global burden of disease ,Sex Distribution ,Child ,Aged ,Aged, 80 and over ,BARRIERS ,DEMENTIA ,Medicine (all) ,Infant, Newborn ,Infant ,11 Medical And Health Sciences ,Middle Aged ,TRENDS ,PREVENTION ,PREVALENCE ,ALZHEIMERS-DISEASE ,INDIVIDUALS ,3121 General medicine, internal medicine and other clinical medicine ,Child, Preschool ,REGISTRATION ,Female ,Human medicine ,Human - Abstract
Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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33. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Sk, Vollset, Se, Vu, Gt, Waller, Sg, Walson, Jl, Wang, Yp, Weintraub, Rg, Werkneh, Aa, West, Jj, Whiteford, Ha, Wiyeh, Ab, Wolfe, Cda, Wong, Ty, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yimer, Em, Yoon, Sj, Younis, Mz, Zaman, Sb, Zhang, Al, Zimsen, Srm, Murray, Cjl., Stanaway, Jeffrey D, Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S, Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adane, Akilew Awoke, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Admasie, Amha, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, 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Kumar, Takahashi, Ken, Tandon, Nikhil, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekelemedhin, Shishay Wahdey, Tekle, Merhawi Gebremedhin, Temesgen, Habtamu, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Tessema, Belay, Teweldemedhin, Mebrahtu, Thankappan, Kavumpurathu Raman, Theis, Andrew, Thirunavukkarasu, Sathish, Thomas, Hannah J, Thomas, Matthew Lloyd, Thomas, Nihal, Thurston, George D, Tilahun, Binyam, Tillmann, Taavi, To, Quyen G, Tobollik, Myriam, Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna E, Tortajada-Girbés, Miguel, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tudor Car, Lorainne, Tuzcu, E Murat, Tymeson, Hayley D, Tyrovolas, Stefano, Ukwaja, Kingsley N, Ullah, Irfan, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Van Donkelaar, Aaron, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venkateswaran, Vidhya, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vu, Giang Thu, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G, Walson, Judd L, Wang, Yafeng, Wang, Yanping, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weldegebreal, Fitsum, Werdecker, Andrea, Werkneh, Adhena Ayaliew, West, J Jason, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Wong, Tien Yin, Wu, Shouling, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zavala-Arciniega, Lui, Zhang, Anthony Lin, Zhang, Hao, Zhang, Kai, Zhou, Maigeng, Zimsen, Stephanie R M, Zodpey, Sanjay, and Murray, Christopher J L
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Science & Technology ,GBD, risks ,risk factors ,comparative risk assesment ,Dalys ,Medicine (all) ,CHOLESTEROL ,BLOOD-PRESSURE ,11 Medical And Health Sciences ,ILLNESS ,TRENDS ,humanities ,Medicine, General & Internal ,TOBACCO CONTROL ,General & Internal Medicine ,parasitic diseases ,Medicine and Health Sciences ,CARDIOVASCULAR-DISEASES ,TRIAL ,Human medicine ,Life Sciences & Biomedicine ,METAANALYSIS - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk– outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Lancet 2018; 392: 1923–94 *Collaborators listed at the end of the paper Correspondence to: Prof Christopher J L Murray, Institute for Health Metrics and Evalution, Seattle, WA 98121, USA cjlm@uw.edu Global Health Metrics 1924 www.thelancet.com Vol 392 November 10, 2018 Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.
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34. Population and fertility by age and sex for 195 countries and territories, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Murray, Christopher J L, Callender, Charlton S K H, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M E, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, Atique, Suleman, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Banach, Maciej, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gilles, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Biswas, Tuhin, Bizuneh, Hailemichael, Bleyer, Archie, Basara, Berrak Bora, Bosetti, Cristina, Boufous, Soufiane, Brady, Oliver J, Bragazzi, Nicola Luigi, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Brewer, Jerry D, Briant, Paul Svitil, Britton, Gabrielle, Burstein, Roy, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christopher, Devasahayam J, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Collado-Mateo, Daniel, Constantin, Maria-Magdalena, Conti, Sara, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cromwell, Elizabeth, Crowe, Christopher Stephen, Cukelj, Petra, Cunningham, Matthew, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De Leo, Diego, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Dessie, Getenet Ayalew, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Ding, Eric L, Dinsa, Girmaye Deye, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dolan, Kate A, Doyle, Kerrie E, Driscoll, Tim R, Dubey, Manisha, 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Sanjay Madhav, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehrzadi, Saeed, Mehta, Kala M, Mehta, Varshil, Mekonnen, Tefera C, Meles, Hagazi Gebre, Meles, Kidanu Gebremariam, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengesha, Melkamu Merid, 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, Miller-Petrie, Molly Katherine, Mini, G K, Mirabi, Parvaneh, Mirica, Andreea, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadi-Khanaposhtani, Maryam, Mohammed, Mohammed A, Mohammed, Shafiu, Mokdad, Ali H, Mola, Glen Dl, Molokhia, Mariam, Monasta, Lorenzo, Montañez, Julio Cesar, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morgado-Da-Costa, Joana, Mori, Rintaro, Morrison, Shane Douglas, Mosapour, Abbas, Moschos, Marilita M, Mousavi, Seyyed Meysam, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Mukhopadhyay, Satinath, Muller, Kate, Murphy, Tasha B, Murthy, G V S, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nachega, Jean B, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Naik, Paulami, Najafi, Farid, Naldi, Luigi, 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, Grant, Nguyen, Long Hoang, Nguyen, Trang Huyen, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nisar, Muhammad Imran, Nixon, Molly R, Nomura, Shuhei, Noroozi, Mehdi, Noubiap, Jean Jacques, Nouri, Hamid Reza, Shiadeh, Malihe Nourollahpour, Nowroozi, Mohammad Reza, Nyandwi, Alypio, Nyasulu, Peter S, Odell, Christopher M, 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, Ortiz, Alberto, Osgood-Zimmerman, Aaron, Ota, Erika, Otieno, Brenda Achieng, Otstavnov, Stanislav S, Owolabi, Mayowa Ojo, Oyekale, Abayomi Samuel, P A, Mahesh, Pakhale, Smita, Pakhare, Abhijit P, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandey, Achyut Raj, Park, Eun-Kee, Parsian, Hadi, Patel, Shanti, Patil, Snehal T, Patle, Ajay, Patton, George C, Paturi, Vishnupriya Rao, Paudel, Deepak, Pedroso, Marcel Moraes, Peprah, Emmanuel K, Pereira, David M, Perico, Norberto, Pesudovs, Konrad, Petri, William A, Petzold, Max, Pierce, Maxwell, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Polanczyk, Guilherme V, Postma, Maarten J, Pourmalek, Farshad, Pourshams, Akram, Poustchi, Hossein, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A, Purwar, Manorama B, Qorbani, Mostafa, Quansah, Reginald, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Md Shafiur, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E, Razo-García, Christian, Reiner, Robert C, Reis, Cesar, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Rios-Blancas, Maria Jesus, Roba, Kedir Teji, Roberts, Nicholas L S, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Rubagotti, Enrico, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S, Saddik, Basema, Saeedi Moghaddam, Sahar, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salahshoor, Mohamadreza, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saldanha, Raphael De Freitas, Saleem, Zikria, Salimi, Yahya, Salimzadeh, Hamideh, Salomon, Joshua A, Salvi, Sundeep Santosh, Salz, Inbal, Sambala, Evanson Zondani, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolores, Santos, Itamar S, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarmiento-Suárez, Rodrigo, Saroshe, Satish, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Schaeffner, Elke, Schelonka, Kathryn, Schneider, Ione J C, Schwebel, David C, Schwendicke, Falk, Seedat, Soraya, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabaninejad, Hosein, Shackelford, Katya Anne, Shafieesabet, Azadeh, Shaheen, Amira A, Shaikh, Masood Ali, Shakir, Raad A, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Shamsizadeh, Morteza, Sharafi, Heidar, Sharafi, Kiomars, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shibuya, Kenji, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shukla, Sharvari Rahul, Si, Si, Siabani, Soraya, Sibai, Abla Mehio, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silpakit, Naris, Silva, Diego Augusto Santos, Silva, João Pedro, Silveira, Dayane Gabriele Alves, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Sliwa, Karen, Soares Filho, Adauto Martins, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Soriano, Joan B, Soyiri, Ireneous N, Sreeramareddy, Chandrashekhar T, Starodubov, Vladimir I, Steiner, Caitlyn, Stewart, Leo G, Stokes, Mark A, Strong, Mark, Subart, Michelle L, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sutradhar, Ipsita, Sykes, Bryan L, Sylaja, P N, Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabb, Karen M, Tadakamadla, Santosh Kumar, Tandon, Nikhil, Tassew, Aberash Abay, Tassew, Segen Gebremeskel, Taveira, Nuno, Tawye, Nega Yimer, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekle, Merhawi Gebremedhin, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Teshale, Manaye Yihune, Tessema, Belay, Teweldemedhin, Mebrahtu, Thakur, Jarnail Singh, Thankappan, Kavumpurathu Raman, Thirunavukkarasu, Sathish, Thomas, Nihal, Thomson, Alan J, Tilahun, Binyam, To, Quyen G, Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna E, Tortajada-Girbés, Miguel, Tovani-Palone, Marcos Roberto, Toyoshima, Hideaki, Tran, Bach Xuan, Tran, Khanh Bao, Tripathy, Srikanth Prasad, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tsegay, Amanuel, Tsilimparis, Nikolaos, Tudor Car, Lorainne, Ukwaja, Kingsley N, Ullah, Irfan, Usman, Muhammad Shariq, Uthman, Olalekan A, Uzun, Selen Begüm, Vaduganathan, Muthiah, Vaezi, Afsane, Vaidya, Gaurang, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogales, Venketasubramanian, Narayanaswamy, Villafaina, Santos, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Walson, Judd L, Wang, Yanping, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yamada, Tomohide, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeleke, Mulugeta Molla, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Xueying, Zhao, Xiu-Ju, Zhou, Maigeng, Zhu, Jun, Zimsen, Stephanie R M, Zodpey, Sanjay, Zoeckler, Leo, Lopez, Alan D, Lim, Stephen S, Halk Sağlığı, GBD 2017 Population Fertility Coll, Murray, Cjl, Callender, Cskh, Kulikoff, Xr, Srinivasan, V, Abate, D, Abate, Kh, Abay, Sm, Abbasi, N, Abbastabar, H, Abdela, J, Abdelalim, A, Abdel-Rahman, O, Abdi, A, Abdoli, N, Abdollahpour, I, Abdulkader, R, Abebe, Ht, Abebe, M, Abebe, Z, Abebo, Ta, Abejie, An, Aboyans, V, Abraha, Hn, Abreu, Dmx, Abrham, Ar, Abu-Raddad, Lj, Abu-Rmeileh, Nme, Accrombessi, Mmk, Acharya, P, Adamu, Aa, Adebayo, Om, Adedeji, Ia, Adekanmbi, V, Adetokunboh, Oo, Adhena, Bm, Adhikari, Tb, Adib, Mg, Adou, Ak, Adsuar, Jc, Afarideh, M, Afshin, A, 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Vasconcelos, A, Vladimirov, S, Vollset, S, Walson, J, Weintraub, R, Weldegwergs, K, Wolfe, C, Wyper, G, Yasin, Y, Yentür, G, Yimer, E, Yoon, S, Younis, M, Zaman, S, Zeleke, M, Zenebe, Z, Zerfu, T, Zhao, X, Zimsen, S, Lopez, A, and Lim, S
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Adult ,Male ,Population Density ,GBD, population, fertility ,Adolescent ,Medicine (all) ,Infant, Newborn ,Infant ,11 Medical And Health Sciences ,Middle Aged ,Global Health ,Global Burden of Disease ,Young Adult ,Child, Preschool ,General & Internal Medicine ,Female ,Human medicine ,Mortality ,Child ,Population Growth ,Birth Rate ,Aged ,Human ,Maternal Age - Abstract
Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-cotnponent method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49.4% (95% uncertainty interval [UI] 46.4-52.0). The TFR decreased from 4.7 livebirths (4.5-4.9) to 2.4 livebirths (2.2-2.5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83.8 million people per year since 1985. The global population increased by 197-2% (193.3-200.8) since 1950, from 2.6 billion (2.5-2.6) to 7.6 billion (7.4-7.9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2.0%; this rate then remained nearly constant until 1970 and then decreased to 1.1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2.5% in 1963 to O7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2.7%. The global average age increased from 26.6 years in 1950 to 32.1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59.9% to 65.3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1.0 livebirths (95% UI 0. 9-1.2) in Cyprus to a high of 7.1 livebirths (6.8-7.4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0.08 livebirths (0.07-0.09) in South Korea to 2.4 livebirths (2.2-2.6) in Niger, and the TFR over age 30 years (I F030; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0.3 livebirths (0.3-0-4) in Puerto Rico to a high of 3.1 livebirths (3.0-3.2) in Niger. TF030 was higher than TFU25 in 145 countries and territories in 2017.33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2.0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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35. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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James, Spencer L., Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M. 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Marzan, Mb, Mashamba-Thompson, Tp, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehndiratta, Mm, Mehta, Km, Memiah, Ptn, Memish, Za, Mengistu, Dt, Mensah, Ga, Mereta, St, Meretoja, Tj, Mezerji, Nmg, Millear, Ai, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Misganaw, At, Mitchell, Pb, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Mruts, Kb, Muche, Aa, Muchie, Kf, Mueller, Uo, Mumford, Je, Musa, Ki, Nabhan, Af, Nansseu, Jr, Nascimento, Br, Negoi, Ri, Newton, Crj, Ngunjiri, Jw, Nguyen, Aq, Nguyen, Ht, Nguyen, Hlt, Nguyen, Lh, Nguyen, Nb, Nguyen, Sh, Ningrum, Dna, Nixon, Mr, Norheim, Of, Noubiap, Jj, Nouri, Hr, Nowroozi, Mr, Nsoesie, Eo, Odell, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Olsen, He, Olusanya, Bo, Ong, Kl, Ong, Sk, Owolabi, Mo, Pakpour, Ah, Park, Ek, Parry, Cdh, Patil, St, Patton, Gc, Paturi, Vr, Paulson, Kr, Pereira, Dm, Pham, Hq, Phillips, Mr, Pigott, Dm, Pillay, Jd, Piradov, Ma, Postma, Mj, Purcell, Ca, Purwar, Mb, 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Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shibuya, Kenji, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shishani, Kawkab, Shiue, Ivy, Shokraneh, Farhad, Shoman, Haitham, Shrime, Mark G, Si, Si, Siabani, Soraya, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Slepak, Erica Leigh N, Sliwa, Karen, Smith, David L, Smith, Mari, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Sobngwi, Eugène, Soneji, Samir S, Soofi, Moslem, Soosaraei, Masoud, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Stanaway, Jeffrey D, Stein, Dan J, Steiner, Caitlyn, Steiner, Timothy J, Stokes, Mark A, Stovner, Lars Jacob, 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Eduardo A, Unutzer, Jurgen, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Varughese, Santosh, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G, Wang, Yafeng, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T Eoin, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Wilner, Lauren B, Wilson, Shadrach, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Woolf, Anthony D, Wu, Shouling, Wu, Yun-Chun, Wyper, Grant M A, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeleke, Ayalew Jejaw, Zenebe, Zerihun Menlkalew, Zhang, Kai, Zhao, Zheng, Zhou, Maigeng, Zodpey, Sanjay, Zucker, Inbar, Vos, Theo, and Murray, Christopher J L
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YLDs ,global burden of disease ,General & Internal Medicine ,Medicine (all) ,prevalence ,incidence ,Human medicine ,global burden of disease, YLDs, incidence, prevalence ,GBD, years lived with disability - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 39% (95% uncertainty interval [UI] 3.1-4. 6) from 1990 to 2017; however, the all-age YLD rate increased by 7.2% (6.0-8.4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7.9% (6 6-9. 2) for males and 6.5% (5.4-7.7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-hatin and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
36. 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
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Chudi, Valdez, Pascual Rubén, Van Boven, Job F.M., Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wagnew, Fasil, Waheed, Yasir, Wallin, Mitchell T., Walson, Judd L., Wang, Yafeng, Wang, Yuan-Pang, Wassie, Molla Mesele, Weaver, Marcia R., Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Jordan, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T. Eoin, Westerman, Ronny, White, Richard G., Whiteford, Harvey A., Widecka, Justyna, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D.A., Wondimkun, Yohanes Ayele, Workicho, Abdulhalik, Wyper, Grant M.A., Xavier, Deni, Xu, Gelin, Yan, Lijing L., Yano, Yuichiro, Yaseri, Mehdi, Yimer, Nigus Bililign, Yin, Peng, Yip, Paul, Yirsaw, Biruck Desalegn, Yonemoto, Naohiro, Yonga, Gerald, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zaman, Sojib Bin, Zamani, Mohammad, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zhu, Jun, Zimsen, Stephanie R.M., Zipkin, Ben, Zodpey, Sanjay, Zuhlke, Liesl Joanna, Murray, Christopher J.L., Lozano, Rafael, Viðskiptadeild (HR), School of Business (RU), Háskólinn í Reykjavík, Reykjavik University, Abay, Sm, Abebo, Ta, Abraha, Hn, Abreu, Dmx, Abu-Raddad, Lj, Adane, Aa, Adedoyin, Ra, Adhikari, Tb, Aichour, Mte, Akinyemi, Ro, Akinyemiju, Tf, Al Lami, Fh, Albittar, Mi, Alene, Ka, Ali, 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, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.
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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.
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- 2018
37. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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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, 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Narayanaswamy, Vidavalur, Ramesh, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagner, Gregory R, Wagnew, Fasil Wagnew Shiferaw, Waheed, Yasir, Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weiss, Jordan, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wondemagegn, Sintayehu Ambachew, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yadav, Rajaram, Yakob, Bereket, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yearwood, Jamal A, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, York, Hunter W, Yotebieng, Marcel, 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Child mortality ,Alnæmi ,Dánartíðni ,Heilsufar ,GBD ,Börn ,Dauði ,Almennar lyflækningar ,Fullorðnir ,General & Internal Medicine ,parasitic diseases ,Psychology ,age-specific mortality ,Estimating adult mortality ,Medicine (all) ,HIV ,11 Medical And Health Sciences ,General Medicine ,All-cause mortality ,humanities ,Countries ,Death ,mortality, national ,Sálfræði ,Health ,GBD, mortality ,Human medicine ,Trends - Abstract
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data., Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing., Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163).
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- 2018
38. The transcription factor BBX regulates phosphate homeostasis through the modulation of FGF23.
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Lee SJ, Kim JA, Ihn HJ, Choi JY, Kwon TY, Shin HI, Cho ES, Bae YC, Jiang R, Kim JE, and Park EK
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Fibroblast growth factor 23 (FGF23) plays an important role in phosphate homeostasis, and increased FGF23 levels result in hypophosphatemia; however, the molecular mechanism underlying increased FGF23 expression has not been fully elucidated. In this study, we found that mice lacking the bobby sox homolog (Bbx
-/- ) presented increased FGF23 expression and low phosphate levels in the serum and skeletal abnormalities such as a low bone mineral density (BMD) and bone volume (BV), as well as short and weak bones associated with low bone formation. Osteocyte-specific deletion of Bbx using Dmp-1-Cre resulted in similar skeletal abnormalities, elevated serum FGF23 levels, and reduced serum phosphate levels. In Bbx-/- mice, the expression of sodium phosphate cotransporter 2a (Npt2a) and Npt2c in the kidney and Npt2b in the small intestine, which are negatively regulated by FGF23, was downregulated, leading to phosphate excretion/wasting and malabsorption. An in vitro Fgf23 promoter analysis revealed that 1,25-dihydroxyvitamin D3 (1,25(OH)2 D3 )-induced transactivation of the Fgf23 promoter was significantly inhibited by BBX overexpression, whereas it was increased following Bbx knockdown. Interestingly, 1,25(OH)2 D3 induced an interaction of the 1,25(OH)2 D3 receptor (VDR) with BBX and downregulated BBX protein levels. Cycloheximide (CHX) only partially downregulated BBX protein levels, indicating that 1,25(OH)2 D3 regulates BBX protein stability. Furthermore, the ubiquitination of BBX followed by proteasomal degradation was required for the increase in Fgf23 expression induced by 1,25(OH)2 D3 . Collectively, our data demonstrate that BBX negatively regulates Fgf23 expression, and consequently, the ubiquitin-dependent proteasomal degradation of BBX is required for FGF23 expression, thereby regulating phosphate homeostasis and bone development in mice., (© 2024. The Author(s).)- Published
- 2024
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39. Concordant and discordant breast density patterns by different approaches for assessing breast density and breast cancer risk.
- Author
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Cho Y, Park EK, Chang Y, Kwon MR, Kim EY, Kim M, Park B, Lee S, Jeong HE, Kim KH, Kim TS, Lee H, Kwon R, Lim GY, Choi J, Kook SH, and Ryu S
- Abstract
Purpose: To examine the discrepancy in breast density assessments by radiologists, LIBRA software, and AI algorithm and their association with breast cancer risk., Methods: Among 74,610 Korean women aged ≥ 34 years, who underwent screening mammography, density estimates obtained from both LIBRA and the AI algorithm were compared to radiologists using BI-RADS density categories (A-D, designating C and D as dense breasts). The breast cancer risks were compared according to concordant or discordant dense breasts identified by radiologists, LIBRA, and AI. Cox-proportional hazards models were used to determine adjusted hazard ratios (aHRs) [95% confidence intervals (CIs)]., Results: During a median follow-up of 9.9 years, 479 breast cancer cases developed. Compared to the reference non-dense breast group, the aHRs (95% CIs) for breast cancer were 2.37 (1.68-3.36) for radiologist-classified dense breasts, 1.30 (1.05-1.62) for LIBRA, and 2.55 (1.84-3.56) for AI. For different combinations of breast density assessment, aHRs (95% CI) for breast cancer were 2.40 (1.69-3.41) for radiologist-dense/LIBRA-non-dense, 11.99 (1.64-87.62) for radiologist-non-dense/LIBRA-dense, and 2.99 (1.99-4.50) for both dense breasts, compared to concordant non-dense breasts. Similar trends were observed with radiologists/AI classification: the aHRs (95% CI) were 1.79 (1.02-3.12) for radiologist-dense/AI-non-dense, 2.43 (1.24-4.78) for radiologist-non-dense/AI-dense, and 3.23 (2.15-4.86) for both dense breasts., Conclusion: The risk of breast cancer was highest in concordant dense breasts. Discordant dense breast cases also had a significantly higher risk of breast cancer, especially when identified as dense by either AI or LIBRA, but not radiologists, compared to concordant non-dense breast cases., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
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- 2024
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40. Ank-mediated pyrophosphate regulates shear stress-induced small extracellular vesicle production in 3D-cultured osteocytes.
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Lee SJ, Jung DK, Im S, You C, Kim JE, Bae JS, Kim MS, Yea K, and Park EK
- Abstract
Osteocytes are located in the lacunae of fluid-filled bone and communicate with neighboring or distant cells by secreting small extracellular vesicles (sEVs) and growth factors as well as via dendrite-dendrite direct connections. However, the mechanism regulating sEV production in osteocytes is yet to be elucidated. In this study, we investigated sEV production and its underlying mechanism in osteocytes cultured on a three dimensional (3D) scaffold. We employed a perfusion system to apply shear stress stimulation to MLO-Y4 cells cultured on a 3D biphasic calcium phosphate (BCP) scaffold and analyzed sEV production and gene expression using RNA sequencing. We found that the expression of genes associated with sEV biogenesis and the secretory pathway were enhanced by fluid shear stress in MLO-Y4 cells cultured on a 3D BCP scaffold. In particular, fluid shear stress induced the expression of Ank, a pyrophosphate transporter, in 3D-cultured MLO-Y4 cells. The role of Ank in sEV production was further examined. Probenecid, an Ank inhibitor, significantly suppressed shear stress-induced sEV production, whereas Ank cDNA overexpression stimulated it. The inhibition of shear stress-induced sEV production by probenecid was recovered by the exogenous addition of pyrophosphate to MLO-Y4 cells. These findings suggest that shear stress-mediated sEV production in 3D-cultured osteocytes is regulated by extracellular pyrophosphate transported by Ank., Competing Interests: No potential conflict of interest was reported by the author(s)., (© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)
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- 2024
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41. Tissue-Engineered Bone Regeneration for Medium-to-Large Osteonecrosis of the Femoral Head in the Weight-Bearing Portion: An Observational Study.
- Author
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Park EK, Shim BJ, Kim SY, Baek SH, and Kim SY
- Subjects
- Humans, Adult, Male, Female, Retrospective Studies, Young Adult, Mesenchymal Stem Cell Transplantation methods, Tissue Scaffolds, Osteoblasts, Femur Head Necrosis surgery, Bone Regeneration, Tissue Engineering methods, Weight-Bearing physiology
- Abstract
Background: Stem cell therapy for the treatment of osteonecrosis of the femoral head (ONFH) showed promising outcomes. However, ONFH with a large lesion in the weight-bearing portion is a poor prognostic factor and still challenging issue to be solved. We aimed to evaluate the effect of tissue-engineered bone regeneration for this challenging condition to preserve the femoral head., Methods: A total of 7 patients (9 hips) with ONFH who received osteoblasts expanded ex vivo from bone marrow-derived mesenchymal stem cells (BMdMSCs) and calcium metaphosphate (CMP) as scaffolds from March 2002 to March 2004 were retrospectively reviewed. The median age was 27.0 years (interquartile range [IQR], 23.0-34.0 years), and the median follow-up period was 20.0 years (IQR, 11.0-20.0 years). After culture and expansion of stem cells, we performed core decompression with BMdMSC implantation at a median number of 10.1 ×10
7 (IQR, 9.9-10.9 ×107 ). To evaluate radiographic outcomes, the Association Research Circulation Osseous (ARCO) classifications, the Japanese Investigation Committee (JIC) classification, and modified Kerboul combined necrotic angle (mKCNA) were evaluated preoperatively and during follow-up. Clinical outcomes were evaluated by a visual analog scale (VAS) and Harris Hip Score (HHS)., Results: The preoperative stage of ONFH was ARCO 2 in 5 hips and ARCO 3a in 4 hips. The ARCO staging was maintained in 3 hips of ARCO 2 and 4 hips of ARCO 3a. Two hips of ARCO 2 with radiographic progression underwent total hip arthroplasty. According to mKCNA, 2 hips showed medium lesions, and 7 hips showed large lesions. The size of necrotic lesion was decreased in 4 hips (2 were ARCO 2 and 2 were ARCO 3a). There were no significant changes in JIC classification in all hips (type C1: 3 hips and type C2: 6 hips) ( p = 0.655). Clinically, there were no significant changes in the VAS and HHS between preoperative and last follow-up ( p = 0.072 and p = 0.635, respectively)., Conclusions: Tissue engineering technique using osteoblasts expanded ex vivo from BMdMSC and CMP showed promising outcomes for the treatment of pre-collapsed and early-collapsed stage ONFH with medium-to-large size, mainly located in weight-bearing areas., Competing Interests: CONFLICT OF INTEREST: No potential conflict of interest relevant to this article was reported., (Copyright © 2024 by The Korean Orthopaedic Association.)- Published
- 2024
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42. Glycinamide Facilitates Nanocomplex Formation and Functions Synergistically with Bone Morphogenetic Protein 2 to Promote Osteoblast Differentiation In Vitro and Bone Regeneration in a Mouse Calvarial Defect Model.
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Nam SH, Kim JA, Lim S, Lee SJ, Kim CH, Bae JS, Boo YC, Kim YJ, and Park EK
- Subjects
- Animals, Humans, Mice, Cell Line, Disease Models, Animal, Glycine pharmacology, Glycine analogs & derivatives, Glycine chemistry, Mesenchymal Stem Cells metabolism, Mesenchymal Stem Cells drug effects, Bone Morphogenetic Protein 2 pharmacology, Bone Regeneration drug effects, Cell Differentiation drug effects, Osteoblasts drug effects, Osteoblasts metabolism, Osteogenesis drug effects, Skull drug effects
- Abstract
Background: This study aimed to identify glycine analogs conducive to the formation of cell-absorbable nanocomplexes, enhancing collagen synthesis and subsequent osteogenesis in combination with BMP2 for improved bone regeneration., Methods: Glycine and its derivatives were assessed for their effects on osteogenic differentiation in MC3T3-E1 cells and human bone marrow mesenchymal stem cells (BMSCs) under osteogenic conditions or with BMP2. Osteogenic differentiation was assessed through alkaline phosphatase staining and real-time quantitative polymerase chain reaction (RT-qPCR). Nanocomplex formation was examined via scanning electron microscopy, circular dichroism, and ultraviolet-visible spectroscopy. In vivo osteogenic effects were validated using a mouse calvarial defect model, and bone regeneration was evaluated through micro-computed tomography and histomorphometric analysis., Results: Glycine, glycine methyl ester, and glycinamide significantly enhanced collagen synthesis and ALP activity in conjunction with an osteogenic medium (OSM). GA emerged as the most effective inducer of osteoblast differentiation marker genes. Combining GA with BMP2 synergistically stimulated ALP activity and the expression of osteoblast markers in both cell lines. GA readily formed nanocomplexes, facilitating cellular uptake through strong electrostatic interactions. In an in vivo calvarial defect mouse model, the GA and BMP2 combination demonstrated enhanced bone volume, bone volume/tissue volume ratio, trabecular numbers, and mature bone formation compared to other combinations., Conclusion: GA and BMP2 synergistically promoted in vitro osteoblast differentiation and in vivo bone regeneration through nanocomplex formation. This combination holds therapeutic promise for individuals with bone defects, showcasing its potential for clinical intervention., (© 2024. Korean Tissue Engineering and Regenerative Medicine Society.)
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- 2024
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43. Fabrication, Microstructure and Plasma Resistance Behavior of Y-Al-Si-O (YAS) Glass-Ceramics Coated on Alumina Ceramics.
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Park EK, Jang HY, Jeon SY, Raju K, and Lee HK
- Abstract
This study investigates the fabrication, microstructural characteristics and plasma resistance of Y-Al-Si-O (YAS) glass-ceramics coated on alumina ceramics. YAS frits were initially prepared using a melt-quenching method, then homogenously milled and coated onto alumina ceramics. The melt-coating process was conducted at 1650 °C for 1 h. The composition and microstructure of the glass frits and coatings were thoroughly characterized using X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. These analyses revealed a dense microstructure with a polycrystalline structure predominantly composed of Y
3 Al5 O12 (YAG) phase and a minor phase of Y2 Si2 O7 . The YAS coatings on alumina revealed a dense layer with strong adhesion to the substrate. Subsequently, the coatings underwent C4 F6 /Ar/O2 plasma treatment for 1 h. Plasma exposure tests demonstrated that the YAS-coated alumina exhibited significantly better etching resistance compared to uncoated alumina, with minimal surface damage observed on the YAS coating, confirming its protective properties against plasma. The superior plasma resistance of YAS coatings is attributed to the predominance of its YAG phase. This research offers a more stable and cost-efficient solution for protecting ceramics in demanding plasma environments.- Published
- 2024
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44. The beneficial effects of lupeol on particulate matter-mediated pulmonary inflammation.
- Author
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Cho S, Park DH, Park EK, and Bae JS
- Subjects
- Animals, Mice, Male, Myeloid Differentiation Factor 88 metabolism, Myeloid Differentiation Factor 88 genetics, TOR Serine-Threonine Kinases metabolism, Bronchoalveolar Lavage Fluid chemistry, Bronchoalveolar Lavage Fluid cytology, Autophagy drug effects, Mice, Inbred C57BL, Cytokines metabolism, Lung drug effects, Lung metabolism, Lung pathology, Beclin-1 metabolism, Microtubule-Associated Proteins metabolism, Lupanes, Pentacyclic Triterpenes pharmacology, Particulate Matter toxicity, Toll-Like Receptor 4 metabolism, Pneumonia drug therapy, Pneumonia metabolism, Pneumonia chemically induced
- Abstract
Particulate matter (PM) poses significant health risks, especially fine particles (PM
2.5 ) that can cause severe lung injuries. Lupeol, a phytosterol from medicinal plants, has potential anti-cancer properties. This study investigated lupeol's protective effects against PM2.5 -induced lung damage. Mice received lupeol following intratracheal PM2.5 exposure. Results showed lupeol reduced lung damage, lowered wet/dry (W/D) weight ratio, and suppressed increased permeability caused by PM2.5 . Additionally, lupeol decreased plasma inflammatory cytokines, total protein concentration in bronchoalveolar lavage fluid (BALF), and PM2.5 -induced lymphocyte proliferation. Lupeol also reduced expression of toll-like receptor 4 (TLR4), myeloid differentiation primary response 88 (MyD88), and autophagy-related proteins microtubule-associated protein 1 A/1 B-light chain 3 (LC3) II and Beclin 1, while increasing phosphorylated mammalian target of rapamycin (mTOR) phosphorylation. These findings suggest lupeol's potential as a therapeutic agent for PM2.5 -induced lung damage via modulation of the TLR4-MyD88 and mTOR-autophagy pathways., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)- Published
- 2024
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45. S100P binds to RAGE and activates ERK/NF-κB signaling to promote osteoclast differentiation and activity.
- Author
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Lee SH, Park NR, Park EK, and Kim JE
- Subjects
- Animals, Mice, Humans, MAP Kinase Signaling System, Mice, Inbred C57BL, Cells, Cultured, Neoplasm Proteins metabolism, Extracellular Signal-Regulated MAP Kinases metabolism, Osteoclasts metabolism, Osteoclasts cytology, Cell Differentiation, Receptor for Advanced Glycation End Products metabolism, NF-kappa B metabolism, Bone Resorption metabolism, Bone Resorption pathology, Signal Transduction, Protein Binding
- Abstract
S100 calcium-binding protein P (S100P) is a secretory protein that is expressed in various healthy tissues and tumors. Megakaryocyte-secreted S100P promotes osteoclast differentiation and function; however, its receptor and cellular signaling in osteoclasts remain unclear. Receptor for advanced glycation end products (RAGE), which is the receptor for S100P on cancer cells, was expressed in osteoclast precursors, and S100P-RAGE binding was confirmed through co-immunoprecipitation. Additionally, the phosphorylation of ERK and NF-κB was increased in S100P-stimulated osteoclast precursors but was inhibited by addition of the RAGE antagonistic peptide (RAP). S100P-induced osteoclast differentiation and excessive bone resorption activity were also reduced by the addition of RAP. This study demonstrates that S100P, upon binding with RAGE, activates the ERK and NF-κB signaling pathways in osteoclasts, leading to increased cell differentiation and bone resorption activity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)
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- 2024
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46. Unique cartilage matrix-associated protein inhibits osteoclast differentiation by alleviating RANKL-induced reactive oxygen species.
- Author
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Nam B, Park NR, Park EK, and Kim JE
- Subjects
- Animals, Mice, RAW 264.7 Cells, Extracellular Matrix Proteins metabolism, Extracellular Matrix Proteins genetics, Oxidative Stress drug effects, Osteoclasts metabolism, Osteoclasts cytology, Osteoclasts drug effects, Reactive Oxygen Species metabolism, Cell Differentiation drug effects, RANK Ligand metabolism
- Abstract
Unique cartilage matrix-associated protein (UCMA) is a γ-carboxyglutamic acid-rich secretory protein primarily expressed in adult cartilage. UCMA promotes osteoblast differentiation and reduces high glucose-induced reactive oxygen species (ROS) production in osteoblasts; however, its role in osteoclasts remains unclear. Since Ucma is not expressed in osteoclasts, treatment with recombinant UCMA protein (rUCMA) was employed to investigate the effect of UCMA on osteoclasts. The rUCMA-treated osteoclasts exhibited significantly reduced osteoclast differentiation, resorption activity, and osteoclast-specific gene expression. Moreover, rUCMA treatment reduced RANKL-induced ROS production and increased the expression of antioxidant genes in osteoclasts. This study demonstrates that UCMA effectively inhibits RANKL-stimulated osteoclast differentiation and oxidative stress., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)
- Published
- 2024
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47. The Current Incidence and Future Projection of Acetabular Fractures in Korea.
- Author
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Park KT, Park EK, Lee DH, An JH, Won J, Kim SH, Lee YK, and Park JW
- Subjects
- Humans, Republic of Korea epidemiology, Female, Male, Retrospective Studies, Aged, Incidence, Middle Aged, Aged, 80 and over, Adult, Databases, Factual, Kaplan-Meier Estimate, Young Adult, Acetabulum injuries, Fractures, Bone epidemiology, Fractures, Bone surgery, Arthroplasty, Replacement, Hip
- Abstract
Background: As one of the most challenging fractures to orthopedic surgeons, acetabular fractures show a wide range of incidence among countries and regions with even more variance in the treatment modalities. In this study, we aimed to investigate the epidemiology of acetabular fractures, and to compare the rate of subsequent total hip arthroplasty (THA) between nonoperative and operative treatments in South Korea using a medical claims database., Methods: This was a retrospective study using the Korean Health Insurance Review and Assessment database. Patients admitted for acetabular fractures from January 2007 to December 2018 were identified using International Classification of Diseases-10 codes. Kaplan-Meier survival analysis was used to compare the cumulative incidence of THA between two groups. We also evaluated the survivorship of operative group according to the type of institutions., Results: The incidence rate of acetabular fractures increased by 28% between 2007 and 2018. Acetabular fractures were more common in men (62%) than women (38%), and most common in the patients older than 80 years. The number of acetabular fractures was estimated to increase 1.7-fold in 2030 compared to 2018. Operative treatment accounted for 16% of cases, and nonoperative treatment for 84%. The incidence of subsequent THA was higher in the operative treatment group than in the nonoperative group ( P < 0.001). The higher rate in the operative treatment group is probably related with the severity of the fracture type. The rate of subsequent THA was higher in patients who initially treated in general hospitals compared with those who were initially treated in tertiary hospitals., Conclusion: The incidence of acetabular fractures is increasing in South Korea, in line with global trends. Most acetabular fractures are treated conservatively, and those who receive surgery are more likely to require a subsequent THA. Patients who were operated in general hospitals had highest possibility of subsequent THA after acetabular fractures., Competing Interests: The authors have no potential conflicts of interest to disclose., (© 2024 The Korean Academy of Medical Sciences.)
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- 2024
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48. Artificial Intelligence-Powered Imaging Biomarker Based on Mammography for Breast Cancer Risk Prediction.
- Author
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Park EK, Lee H, Kim M, Kim T, Kim J, Kim KH, Kooi T, Chang Y, and Ryu S
- Abstract
The purposes of this study were to develop an artificial intelligence (AI) model for future breast cancer risk prediction based on mammographic images, investigate the feasibility of the AI model, and compare the AI model, clinical statistical risk models, and Mirai, a state of-the art deep learning algorithm based on screening mammograms for 1-5-year breast cancer risk prediction. We trained and developed a deep learning model using a total of 36,995 serial mammographic examinations from 21,438 women (cancer-enriched mammograms, 17.5%). To determine the feasibility of the AI prediction model, mammograms and detailed clinical information were collected. C-indices and area under the receiver operating characteristic curves (AUCs) for 1-5-year outcomes were obtained. We compared the AUCs of our AI prediction model, Mirai, and clinical statistical risk models, including the Tyrer-Cuzick (TC) model and Gail model, using DeLong's test. A total of 16,894 mammograms were independently collected for external validation, of which 4002 were followed by a cancer diagnosis within 5 years. Our AI prediction model obtained a C-index of 0.76, with AUCs of 0.90, 0.84, 0.81, 0.78, and 0.81, to predict the 1-5-year risks. Our AI prediction model showed significantly higher AUCs than those of the TC model (AUC: 0.57; p < 0.001) and Gail model (AUC: 0.52; p < 0.001), and achieved similar performance to Mirai. The deep learning AI model using mammograms and AI-powered imaging biomarkers has substantial potential to advance accurate breast cancer risk prediction.
- Published
- 2024
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49. Comparison of hypotension incidence between remimazolam and propofol in patients with hypertension undergoing neurosurgery: prospective, randomized, single-blind trial.
- Author
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Choi SH, Min KT, Park EK, and Park S
- Subjects
- Humans, Middle Aged, Female, Male, Single-Blind Method, Prospective Studies, Incidence, Adult, Aged, Young Adult, Propofol adverse effects, Propofol administration & dosage, Hypotension chemically induced, Hypotension epidemiology, Hypertension drug therapy, Hypertension epidemiology, Benzodiazepines adverse effects, Benzodiazepines administration & dosage, Anesthetics, Intravenous adverse effects, Neurosurgical Procedures adverse effects, Neurosurgical Procedures methods
- Abstract
Background: Remimazolam, a newer benzodiazepine that targets the GABA
A receptor, is thought to allow more stable blood pressure management during anesthesia induction. In contrast, propofol is associated with vasodilatory effects and an increased risk of hypotension, particularly in patients with comorbidities. This study aimed to identify medications that can maintain stable vital signs throughout the induction phase., Methods: We conducted a single-center, two-group, randomized controlled trial to investigate and compare the incidence of hypotension between remimazolam- and propofol-based total intravenous anesthesia (TIVA). We selected patients aged between 19 and 75 years scheduled for neurosurgery under general anesthesia, who were classified as American Society of Anesthesiologists Physical Status I-III and had a history of hypertension., Results: We included 94 patients in the final analysis. The incidence of hypotension was higher in the propofol group (91.3%) than in the remimazolam group (85.4%; P = 0.057). There was no significant difference in the incidence of hypotension among the various antihypertensive medications despite the majority of patients being on multiple medications. In comparison with the propofol group, the remimazolam group demonstrated a higher heart rate immediately after intubation., Conclusions: Our study indicated that the hypotension incidence of remimazolam-based TIVA was comparable to that of propofol-based TIVA throughout the induction phase of EEG-guided anesthesia. Both remimazolam and propofol may be equally suitable for general anesthesia in patients undergoing neurosurgery., Trial Registration: Clinicaltrials.gov (NCT05164146)., (© 2024. The Author(s).)- Published
- 2024
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50. Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time.
- Author
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Park EK, Kwak S, Lee W, Choi JS, Kooi T, and Kim EK
- Subjects
- Humans, Female, Middle Aged, Retrospective Studies, Radiographic Image Interpretation, Computer-Assisted methods, Republic of Korea epidemiology, Deep Learning, Adult, Time Factors, Algorithms, United States, Reproducibility of Results, Breast Neoplasms diagnostic imaging, Mammography methods, Artificial Intelligence, Sensitivity and Specificity
- Abstract
Purpose To develop an artificial intelligence (AI) model for the diagnosis of breast cancer on digital breast tomosynthesis (DBT) images and to investigate whether it could improve diagnostic accuracy and reduce radiologist reading time. Materials and Methods A deep learning AI algorithm was developed and validated for DBT with retrospectively collected examinations (January 2010 to December 2021) from 14 institutions in the United States and South Korea. A multicenter reader study was performed to compare the performance of 15 radiologists (seven breast specialists, eight general radiologists) in interpreting DBT examinations in 258 women (mean age, 56 years ± 13.41 [SD]), including 65 cancer cases, with and without the use of AI. Area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and reading time were evaluated. Results The AUC for stand-alone AI performance was 0.93 (95% CI: 0.92, 0.94). With AI, radiologists' AUC improved from 0.90 (95% CI: 0.86, 0.93) to 0.92 (95% CI: 0.88, 0.96) ( P = .003) in the reader study. AI showed higher specificity (89.64% [95% CI: 85.34%, 93.94%]) than radiologists (77.34% [95% CI: 75.82%, 78.87%]) ( P < .001). When reading with AI, radiologists' sensitivity increased from 85.44% (95% CI: 83.22%, 87.65%) to 87.69% (95% CI: 85.63%, 89.75%) ( P = .04), with no evidence of a difference in specificity. Reading time decreased from 54.41 seconds (95% CI: 52.56, 56.27) without AI to 48.52 seconds (95% CI: 46.79, 50.25) with AI ( P < .001). Interreader agreement measured by Fleiss κ increased from 0.59 to 0.62. Conclusion The AI model showed better diagnostic accuracy than radiologists in breast cancer detection, as well as reduced reading times. The concurrent use of AI in DBT interpretation could improve both accuracy and efficiency. Keywords: Breast, Computer-Aided Diagnosis (CAD), Tomosynthesis, Artificial Intelligence, Digital Breast Tomosynthesis, Breast Cancer, Computer-Aided Detection, Screening Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Bae in this issue.
- Published
- 2024
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