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1. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Brauer, M, Roth, GA, Aravkin, AY, Zheng, P, Abate, KH, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasi, MA, Abbasian, M, Abbasifard, M, Abbasi-Kangevari, M, Abd ElHafeez, S, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abedi, A, Abegaz, TM, Abeldaño Zuñiga, RA, Abiodun, O, Abiso, TL, Aboagye, RG, Abolhassani, H, Abouzid, M, Aboye, GB, Abreu, LG, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abukhadijah, HJJ, Aburuz, S, Abu-Zaid, A, Adane, MM, Addo, IY, Addolorato, G, Adedoyin, RA, Adekanmbi, V, Aden, B, Adetunji, JB, Adeyeoluwa, TE, Adha, R, Adibi, A, Adnani, QES, Adzigbli, LA, Afolabi, AA, Afolabi, RF, Afshin, A, Afyouni, S, Afzal, MS, Afzal, S, Agampodi, SB, Agbozo, F, Aghamiri, S, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, N, Ahmad, S, Ahmad, T, Ahmed, A, Ahmed, LA, Ahmed, MB, Ahmed, S, Ahmed, SA, Ajami, M, Akalu, GT, Akara, EM, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akkala, S, Akombi-Inyang, B, Al Awaidy, S, Al Hasan, SM, Alahdab, F, AL-Ahdal, TMA, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Alam, K, Alam, N, Alanezi, FM, Alanzi, TM, Albakri, A, AlBataineh, MT, Aldhaleei, WA, Aldridge, RW, Alemayohu, MA, Alemu, YM, Al-Fatly, B, Al-Gheethi, AAS, Al-Habbal, K, Alhabib, KF, Alhassan, RK, Ali, A, Ali, BA, Ali, I, Ali, L, Ali, MU, Ali, R, Ali, SSS, Ali, W, Alicandro, G, Alif, SM, Aljunid, SM, Alla, F, Al-Marwani, S, Al-Mekhlafi, HM, Almustanyir, S, Alomari, MA, Alonso, J, Alqahtani, JS, Alqutaibi, AY, Al-Raddadi, RM, Alrawashdeh, A, Al-Rifai, RH, Alrousan, SM, Al-Sabah, SK, Alshahrani, NZ, Altaany, Z, Altaf, A, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Alwafi, H, Al-Wardat, MS, Al-Worafi, YM, Aly, H, Aly, S, Alzoubi, KH, Al-Zyoud, W, Amaechi, UA, Aman Mohammadi, M, Amani, R, Amiri, S, Amirzade-Iranaq, MH, Ammirati, E, Amu, H, Amugsi, DA, Amusa, GA, Ancuceanu, R, Anderlini, D, Anderson, JA, Andrade, PP, Andrei, CL, Andrei, T, Anenberg, SC, Angappan, D, Angus, C, Anil, A, Anil, S, Anjum, A, Anoushiravani, A, Antonazzo, IC, Antony, CM, Antriyandarti, E, Anuoluwa, BS, Anvari, D, Anvari, S, Anwar, S, Anwar, SL, Anwer, R, Anyabolo, EE, Anyasodor, AE, Apostol, GLC, Arabloo, J, Arabzadeh Bahri, R, Arafat, M, Areda, D, Aregawi, BB, Aremu, A, Armocida, B, Arndt, MB, Ärnlöv, J, Arooj, M, Artamonov, AA, Artanti, KD, Aruleba, IT, Arumugam, A, Asbeutah, AM, Asgary, S, Asgedom, AA, Ashbaugh, C, Ashemo, MY, Ashraf, T, Askarinejad, A, Assmus, M, Astell-Burt, T, Athar, M, Athari, SS, Atorkey, P, Atreya, A, Aujayeb, A, Ausloos, M, Avila-Burgos, L, Awoke, AA, Ayala Quintanilla, BP, Ayatollahi, H, Ayestas Portugal, C, Ayuso-Mateos, JL, Azadnajafabad, S, Azevedo, RMS, Azhar, GS, Azizi, H, Azzam, AY, Backhaus, IL, Badar, M, Badiye, AD, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Baig, AA, Baker, JL, Bakkannavar, SM, Balasubramanian, M, Baltatu, OC, Bam, K, Bandyopadhyay, S, Banik, B, Banik, PC, Banke-Thomas, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Barteit, S, Basharat, Z, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Batchu, S, Batra, K, Batra, R, Baune, BT, Bayati, M, Bayileyegn, NS, Beaney, T, Behnoush, AH, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, UI, Bell, AW, Bell, ML, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bendak, S, Bennett, DA, Bennitt, FB, Bensenor, IM, Benzian, H, Beran, A, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, AN, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhatti, R, Bhuiyan, MA, Bhutta, ZA, Bikbov, B, Bishai, JD, Bisignano, C, Biswas, A, Biswas, B, Biswas, RK, Bjørge, T, Boachie, MK, Boakye, H, Bockarie, MJ, Bodolica, V, Bodunrin, AO, Bogale, EK, Bolla, SR, Boloor, A, Bonakdar Hashemi, M, Boppana, SH, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Bourne, R, Boxe, C, Braithwaite, D, Brant, LC, Brar, A, Breitborde, NJK, Breitner, S, Brenner, H, Briko, AN, Britton, G, Brown, CS, Browne, AJ, Brunoni, AR, Bryazka, D, Bulamu, NB, Bulto, LN, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, NS, Butt, ZA, Caetano dos Santos, FL, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, LA, Campos, LA, Campos-Nonato, IR, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, JJ, Carugno, A, Carvalho, F, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Catapano, AL, Cattaruzza, MS, Caye, A, Cederroth, CR, Cegolon, L, Cenderadewi, M, Cercy, KM, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, PA, Chakraborty, S, Chan, JSK, Chan, RNC, Chandan, JS, Chandika, RM, Chaturvedi, P, Chen, A-T, Chen, CS, Chen, H, Chen, MX, Chen, M, Chen, S, Cheng, C-Y, Cheng, ETW, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, WCS, Chong, B, Chopra, H, Chowdhury, R, Christopher, DJ, Chu, D-T, Chukwu, IS, Chung, E, Chung, S-C, Chutiyami, M, Cioffi, I, Cogen, RM, Cohen, AJ, Columbus, A, Conde, J, Corlateanu, A, Cortese, S, Cortesi, PA, Costa, VM, Costanzo, S, Criqui, MH, Cruz, JA, Cruz-Martins, N, Culbreth, GT, da Silva, AG, Dadras, O, Dai, X, Dai, Z, Daikwo, PU, Dalli, LL, Damiani, G, D'Amico, E, D'Anna, L, Darwesh, AM, Das, JK, Das, S, Dash, NR, Dashti, M, Dávila-Cervantes, CA, Davis Weaver, N, Davitoiu, DV, De la Hoz, FP, de la Torre-Luque, A, De Leo, D, Debopadhaya, S, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Delgado-Saborit, JM, Demoze, CK, Denova-Gutiérrez, E, Dervenis, N, Dervišević, E, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhane, AS, Dhimal, ML, Dhimal, M, Dhingra, S, Dhulipala, VR, Dhungana, RR, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Dinu, M, Djalalinia, S, Do, TC, Do, THP, do Prado, CB, Dodangeh, M, Dohare, S, Dokova, KG, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, ER, Doshi, R, Doshmangir, L, Dowou, RK, Driscoll, TR, Dsouza, AC, Dsouza, HL, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Dushpanova, A, Dzianach, PA, Dziedzic, AM, Ebrahimi, A, Echieh, CP, Ed-Dra, A, Edinur, HA, Edvardsson, D, Edvardsson, K, Efendi, F, Eftekharimehrabad, A, Eini, E, Ekholuenetale, M, Ekundayo, TC, El Arab, RA, El Sayed Zaki, M, El-Dahiyat, F, Elemam, NM, Elgar, FJ, ElGohary, GMT, Elhabashy, HR, Elhadi, M, Elmehrath, AO, Elmeligy, OAA, Elshaer, M, Elsohaby, I, Emeto, TI, Esfandiari, N, Eshrati, B, Eslami, M, Esmaeili, SV, Estep, K, Etaee, F, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Fahimi, S, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faris, PS, Faro, A, Fasina, FO, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Feng, X, Fereshtehnejad, S-M, Feroze, AH, Ferrara, P, Ferrari, AJ, Ferreira, N, Fetensa, G, Feyisa, BR, Filip, I, Fischer, F, Fitriana, I, Flavel, J, Flohr, C, Flood, D, Flor, LS, Foigt, NA, Folayan, MO, Force, LM, Fortuna, D, Foschi, M, Franklin, RC, Freitas, A, Friedman, SD, Fux, B, G, S, Gaal, PA, Gaihre, S, Gajdács, M, Galali, Y, Gallus, S, Gandhi, AP, Ganesan, B, Ganiyani, MA, Garcia, V, Gardner, WM, Garg, RK, Gautam, RK, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Gebremariam, TBB, Gebremeskel, TG, Gerema, U, Getacher, L, Getahun, GKA, Getie, M, Ghadirian, F, Ghafarian, S, Ghaffari Jolfayi, A, Ghailan, KY, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghassemi, F, Ghazy, RM, Gholami, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Gil, AU, Gil, GF, Gilbertson, NM, Gill, PS, Gill, TK, Gindaba, EZ, Girmay, A, Glasbey, JC, Gnedovskaya, EV, Göbölös, L, Godinho, MA, Goel, A, Golechha, M, Goleij, P, Golinelli, D, Gomes, NGM, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Gouravani, M, Goyal, A, Graham, SM, Grivna, M, Grosso, G, Guan, S-Y, Guarducci, G, Gubari, MIM, Guha, A, Guicciardi, S, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, B, Gupta, M, Gupta, R, Gupta, RD, Gupta, S, Gupta, VB, Gupta, VK, Habibzadeh, F, Habibzadeh, P, Hadaro, TS, Hadian, Z, Haep, N, Haghi-Aminjan, H, Haghmorad, D, Hagins, H, Haile, D, Hailu, A, Hajj Ali, A, Halboub, ES, Halimi, A, Hall, BJ, Haller, S, Halwani, R, Hamadeh, RR, Hamdy, NM, Hameed, S, Hamidi, S, Hammoud, A, Hanif, A, Hanifi, N, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, I, Hasan, MJ, Hasan, SMM, Hasani, H, Hasanian, M, Hashmeh, N, Hasnain, MS, Hassan, A, Hassan, I, Hassan Zadeh Tabatabaei, MS, Hassani, S, Hassanipour, S, Hassankhani, H, Haubold, J, Havmoeller, RJ, Hay, SI, Hebert, JJ, Hegazi, OE, Hegena, TY, Heidari, G, Heidari, M, Helfer, B, Hemmati, M, Henson, CA, Herbert, ME, Herteliu, C, Heuer, A, Hezam, K, Hinneh, TK, Hiraike, Y, Hoan, NQ, Holla, R, Hon, J, Hoque, ME, Horita, N, Hossain, S, Hosseini, SE, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hoven, H, Hsairi, M, Hsu, JM, Hu, C, Huang, J, Huda, MN, Hulland, EN, Hultström, M, Hushmandi, K, Hussain, J, Hussein, NR, Huynh, CK, Huynh, H-H, Ibitoye, SE, Idowu, OO, Ihler, AL, Ikeda, N, Ikuta, KS, Ilesanmi, OS, Ilic, IM, Ilic, MD, Imam, MT, Immurana, M, Inbaraj, LR, Irham, LM, Isa, MA, Islam, MR, Ismail, F, Ismail, NE, Iso, H, Isola, G, Iwagami, M, Iwu, CCD, Iwu-Jaja, CJ, J, V, Jaafari, J, Jacob, L, Jacobsen, KH, Jadidi-Niaragh, F, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jain, A, Jain, N, Jairoun, AA, Jaiswal, A, Jakovljevic, M, Jalilzadeh Yengejeh, R, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jeganathan, J, Jeswani, BM, Jiang, H, Johnson, CO, Jokar, M, Jomehzadeh, N, Jonas, JB, Joo, T, Joseph, A, Joseph, N, Joshi, V, Joshua, CE, Jozwiak, JJ, Jürisson, M, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kahn, EM, Kalani, R, Kaliyadan, F, Kalra, S, Kamath, R, Kanagasabai, T, Kanchan, T, Kandel, H, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Kapner, DJ, Kapoor, N, Karagiannidis, E, Karajizadeh, M, Karakasis, P, Karanth, SD, Karaye, IM, Karch, A, Karim, A, Karimi, H, Karmakar, S, Kashoo, FZ, Kasraei, H, Kassahun, WD, Kassebaum, NJ, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kawakami, N, Kaydi, N, Kayode, GA, Kazemi, F, Keiyoro, PN, Kemmer, L, Kempen, JH, Kerr, JA, Kesse-Guyot, E, Khader, YS, Khafaie, MA, Khajuria, H, Khalaji, A, Khalil, M, Khalilian, A, Khamesipour, F, Khan, A, Khan, MN, Khan, M, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Khavandegar, A, Khayat Kashani, HR, Khidri, FF, Khodadoust, E, Khormali, M, Khorrami, Z, Khosla, AA, Khosrowjerdi, M, Khreis, H, Khusun, H, Kifle, ZD, Kim, K, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Koh, DSQ, Kolahi, A-A, Kompani, F, Kong, J, Koren, G, Korja, M, Korshunov, VA, Korzh, O, Kosen, S, Kothari, N, Koul, PA, Koulmane Laxminarayana, SL, Krishan, K, Krishnamoorthy, V, Krishnamoorthy, Y, Krishnan, B, Krohn, KJ, Kuate Defo, B, Kucuk Bicer, B, Kuddus, MA, Kuddus, M, Kugbey, N, Kuitunen, I, Kulimbet, M, Kulkarni, V, Kumar, A, Kumar, N, Kumar, V, Kundu, S, Kurmi, OP, Kusnali, A, Kusuma, D, Kutluk, T, La Vecchia, C, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lal, DK, Lallukka, T, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Lévesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Leasher, JL, Ledda, C, Lee, M, Lee, PH, Lee, SW, Lee, SWH, Lee, YH, LeGrand, KE, Leigh, J, Leong, E, Lerango, TL, Lescinsky, H, Leung, J, Li, M-C, Li, W-Z, Li, W, Li, Y, Li, Z, Ligade, VS, Lim, L-L, Lim, SS, Lin, R-T, Lin, S, Liu, C, Liu, G, Liu, J, Liu, RT, Liu, S, Liu, W, Liu, X, Livingstone, KM, Llanaj, E, Lohiya, A, López-Bueno, R, Lopukhov, PD, Lorkowski, S, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, lv, H, M Amin, HI, Ma, ZF, Maass, KL, Mabrok, M, Machairas, N, Machoy, M, Mafhoumi, A, Magdy Abd El Razek, M, Maghazachi, AA, Mahadeshwara Prasad, DR, Maharaj, SB, Mahmoud, MA, Mahmoudi, E, Majeed, A, Makram, OM, Makris, KC, Malasala, S, Maled, V, Malhotra, K, Malik, AA, Malik, I, Malinga, LA, Malta, DC, Mamun, AA, Manda, AL, Manla, Y, Mansour, A, Mansouri, B, Mansouri, P, Mansourian, M, Mansournia, MA, Mantovani, LG, Manu, E, Marateb, HR, Maravilla, JC, Marsh, E, Martinez, G, Martinez-Piedra, R, Martini, S, Martins-Melo, FR, Martorell, M, Marx, W, Maryam, S, Mathangasinghe, Y, Mathioudakis, AG, Matozinhos, FP, Mattumpuram, J, Maugeri, A, Maulik, PK, Mayeli, M, Mazidi, M, Mazzotti, A, McGrath, JJ, McKee, M, McKowen, ALW, McLaughlin, SA, McPhail, MA, McPhail, SM, Mechili, EA, Mehmood, A, Mehmood, K, Mehrabani-Zeinabad, K, Mehrabi Nasab, E, Meier, T, Mejia-Rodriguez, F, Mekene Meto, T, Mekonnen, BD, Menezes, RG, Mengist, B, Mensah, GA, Mensah, LG, Mentis, A-FA, Meo, SA, Meretoja, A, Meretoja, TJ, Mersha, AM, Mesfin, BA, Mestrovic, T, Mettananda, KCD, Mettananda, S, Miazgowski, T, Micha, G, Michalek, IM, Micheletti Gomide Nogueira de Sá, AC, Miller, TR, Mirarefin, M, Mirghafourvand, M, Mirica, A, Mirijello, A, Mirrakhimov, EM, Mirshahi, A, Mirzaei, M, Mishra, AK, Mishra, V, Mitchell, PB, Mithra, P, Mittal, C, Moazen, B, Moberg, ME, Mocciaro, G, Mohamadkhani, A, Mohamed, AZ, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammadi, E, Mohammadi, S, Mohammadian-Hafshejani, A, Mohammadifard, N, Mohammed, H, Mohammed, M, Mohammed, S, Mokdad, AH, Monasta, L, Mondello, S, Moni, MA, Moodi Ghalibaf, A, Moore, CE, Moradi, M, Moradi, Y, Moraga, P, Morawska, L, Moreira, RS, Morovatdar, N, Morrison, SD, Morze, J, Mosaddeghi Heris, R, Mossialos, E, Motappa, R, Mougin, V, Mousavi, P, Msherghi, A, Mubarik, S, Muccioli, L, Mueller, UO, Mulita, F, Mullany, EC, Munjal, K, Murillo-Zamora, E, Murlimanju, BV, Musina, A-M, Mustafa, G, Muthu, S, Muthupandian, S, Muthusamy, R, Muzaffar, M, Myung, W, Nafei, A, Nagarajan, AJ, Nagaraju, SP, Nagel, G, Naghavi, M, Naghavi, P, Naik, GR, Naik, G, Nainu, F, Nair, TS, Najdaghi, S, Nakhostin Ansari, N, Nanavaty, DP, Nangia, V, Narasimha Swamy, S, Narimani Davani, D, Nascimento, BR, Nascimento, GG, Nashwan, AJ, Natto, ZS, Nauman, J, Navaratna, SNK, Naveed, M, Nayak, BP, Nayak, VC, Ndejjo, R, Nduaguba, SO, Negash, H, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nejjari, C, Nematollahi, MH, Nepal, S, Neupane, S, Ng, M, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, DH, Nguyen, NNY, Nguyen, PT, Nguyen, VT, Nguyen Tran Minh, D, Niazi, RK, Nicholson, SI, Nie, J, Nikoobar, A, Nikpoor, AR, Ningrum, DNA, Nnaji, CA, Noman, EA, Nomura, S, Noroozi, N, Norrving, B, Noubiap, JJ, Nri-Ezedi, CA, Ntaios, G, Ntsekhe, M, Nunemo, MH, Nurrika, D, Nutor, JJ, Oancea, B, O'Connell, EM, Odetokun, IA, O'Donnell, MJ, Oduro, MS, Ogunfowokan, AA, Ogunkoya, A, Oh, I-H, Okati-Aliabad, H, Okeke, SR, Okekunle, AP, Okonji, OC, Olagunju, AT, Olasupo, OO, Olatubi, MI, Oliveira, AB, Oliveira, GMM, Olorukooba, AA, Olufadewa, II, Olusanya, BO, Olusanya, JO, Oluwafemi, YD, Omar, HA, Omar Bali, A, Omer, GL, Ong, KL, Ong, S, Onwujekwe, OE, Onyedibe, KI, Oppong, AF, Ordak, M, Orish, VN, Ornello, R, Orpana, HM, Ortiz, A, Ortiz-Prado, E, Osman, WMS, Ostroff, SM, Osuagwu, UL, Otoiu, A, Otstavnov, N, Otstavnov, SS, Ouyahia, A, Owolabi, MO, Oyeyemi, IT, Oyeyemi, OT, P A, MP, Pacheco-Barrios, K, Padron-Monedero, A, Padubidri, JR, Pal, PK, Palicz, T, Pan, F, Pan, H-F, Pana, A, Panda, SK, Panda-Jonas, S, Pandey, A, Pandi-Perumal, SR, Pangaribuan, HU, Pantazopoulos, I, Pantea Stoian, AM, Papadopoulou, P, Parent, MC, Parija, PP, Parikh, RR, Park, S, Parsons, N, Pashaei, A, Pasovic, M, Passera, R, Patil, S, Patoulias, D, Patthipati, VS, Paudel, U, Pawar, S, Pazoki Toroudi, H, Peden, AE, Pedersini, P, Peng, M, Pensato, U, Pepito, VCF, Peprah, EK, Peprah, P, Peres, MFP, Perianayagam, A, Perico, N, Perna, S, Pesudovs, K, Petcu, I-R, Petermann-Rocha, FE, Pham, HT, Philip, AK, Phillips, MR, Pickering, BV, Pierannunzio, D, Pigeolet, M, Pigott, DM, Piracha, ZZ, Piradov, MA, 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YF, Wiangkham, T, Wickramasinghe, ND, Wilkerson, C, Willeit, P, Wilson, S, Wong, YJ, Wongsin, U, Wozniak, S, Wu, C, Wu, D, Wu, F, Wu, Z, Xia, J, Xiao, H, Xu, S, Xu, X, Xu, YY, Yadav, MK, Yaghoubi, S, Yamagishi, K, Yang, L, Yano, Y, Yaribeygi, H, Yasufuku, Y, Ye, P, Yesodharan, R, Yesuf, SA, Yezli, S, Yi, S, Yiğit, A, Yigzaw, ZA, Yin, D, Yip, P, Yismaw, MB, Yon, DK, Yonemoto, N, You, Y, Younis, MZ, Yousefi, Z, Yu, C, Yu, Y, Zadey, S, Zadnik, V, Zakham, F, Zaki, N, Zakzuk, J, Zamagni, G, Zaman, SB, Zandieh, GGZ, Zanghì, A, Zar, HJ, Zare, I, Zarimeidani, F, Zastrozhin, MS, Zeng, Y, Zhai, C, Zhang, AL, Zhang, H, Zhang, L, Zhang, M, Zhang, Y, Zhang, Z, Zhang, Z-J, Zhao, H, Zhao, JT, Zhao, X-JG, Zhao, Y, Zhong, C, Zhou, J, Zhou, S, Zhu, B, Zhu, L, Zhu, Z, Ziaeian, B, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoghi, G, Zoller, T, Zumla, A, Zyoud, SH, Murray, CJL, and Gakidou, E
Published: 2024

2. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Naghavi, M, Ong, KL, Aali, A, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbasi-Kangevari, M, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdelwahab, A, Abdollahi, M, Abdollahifar, M-A, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abebe, SS, Abedi, A, Abegaz, KH, Abhilash, ES, Abidi, H, Abiodun, O, Aboagye, RG, Abolhassani, H, Abolmaali, M, Abouzid, M, Aboye, GB, Abreu, LG, Abrha, WA, Abtahi, D, Abu Rumeileh, S, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abu-Rmeileh, NME, Aburuz, S, Abu-Zaid, A, Accrombessi, MMK, Adal, TG, Adamu, AA, Addo, IY, Addolorato, G, Adebiyi, AO, Adekanmbi, V, Adepoju, AV, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adeyinka, DA, Adeyomoye, OI, Admass, BAA, Adnani, QES, Adra, S, Afolabi, AA, Afzal, MS, Afzal, S, Agampodi, SB, Agasthi, P, Aggarwal, M, Aghamiri, S, Agide, FD, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmad, T, Ahmadi, K, Ahmadzade, AM, Ahmed, A, Ahmed, H, Ahmed, LA, Ahmed, MS, Ahmed, MB, Ahmed, SA, Ajami, M, Aji, B, Akara, EM, Akbarialiabad, H, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akyirem, S, Al Hamad, H, Al Hasan, SM, Alahdab, F, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Alam, K, Alam, M, Alam, N, Al-amer, RM, Alanezi, FM, Alanzi, TM, Al-Azzam, S, Albakri, A, Albashtawy, M, AlBataineh, MT, Alcalde-Rabanal, JE, Aldawsari, KA, Aldhaleei, WA, Aldridge, RW, Alema, HB, Alemayohu, MA, Alemi, S, Alemu, YM, Al-Gheethi, AAS, Alhabib, KF, Alhalaiqa, FAN, Al-Hanawi, MK, Ali, A, Ali, L, Ali, MU, Ali, R, Ali, S, Ali, SSS, Alicandro, G, Alif, SM, Alikhani, R, Alimohamadi, Y, Aliyi, AA, Aljasir, MAM, Aljunid, SM, Alla, F, Allebeck, P, Al-Marwani, S, Al-Maweri, SAA, Almazan, JU, Al-Mekhlafi, HM, Almidani, L, Almidani, O, Alomari, MA, Al-Omari, B, Alonso, J, Alqahtani, JS, Alqalyoobi, S, Alqutaibi, AY, Al-Sabah, SK, Altaany, Z, Altaf, A, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Alwafi, H, Al-Worafi, YM, Aly, H, Aly, S, Alzoubi, KH, Amani, R, Amare, AT, Amegbor, PM, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Amusa, GA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Angus, C, Anil, A, Anil, S, Anoushiravani, A, Ansari, H, Ansariadi, A, Ansari-Moghaddam, A, Antony, CM, Antriyandarti, E, Anvari, D, Anvari, S, Anwar, S, Anwar, SL, Anwer, R, Anyasodor, AE, Aqeel, M, Arab, JP, Arabloo, J, Arafat, M, Aravkin, AY, Areda, D, Aremu, A, Aremu, O, Ariffin, H, Arkew, M, Armocida, B, Arndt, MB, Ärnlöv, J, Arooj, M, Artamonov, AA, Arulappan, J, Aruleba, RT, Arumugam, A, Asaad, M, Asadi-Lari, M, Asgedom, AA, Asghariahmadabad, M, Asghari-Jafarabadi, M, Ashraf, M, Aslani, A, Astell-Burt, T, Athar, M, Athari, SS, Atinafu, BTT, Atlaw, HW, Atorkey, P, Atout, MMW, Atreya, A, Aujayeb, A, Ausloos, M, Avan, A, Awedew, AF, Aweke, AM, Ayala Quintanilla, BP, Ayatollahi, H, Ayuso-Mateos, JL, Ayyoubzadeh, SM, Azadnajafabad, S, Azevedo, RMS, Azzam, AY, B, DB, Babu, AS, Badar, M, Badiye, AD, Baghdadi, S, Bagheri, N, Bagherieh, S, Bah, S, Bahadorikhalili, S, Bahmanziari, N, Bai, R, Baig, AA, Baker, JL, Bako, AT, Bakshi, RK, Balakrishnan, S, Balasubramanian, M, Baltatu, OC, Bam, K, Banach, M, Bandyopadhyay, S, Banik, PC, Bansal, H, Bansal, K, Barbic, F, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Barteit, S, Barua, L, Basharat, Z, Bashiri, A, Basiru, A, Baskaran, P, Basnyat, B, Bassat, Q, Basso, JD, Basting, AVL, Basu, S, Batra, K, Baune, BT, Bayati, M, Bayileyegn, NS, Beaney, T, Bedi, N, Beghi, M, Behboudi, E, Behera, P, Behnoush, AH, Behzadifar, M, Beiranvand, M, Bejarano Ramirez, DF, Béjot, Y, Belay, SA, Belete, CM, Bell, ML, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bender, RG, Bensenor, IM, Beran, A, Berezvai, Z, Berhie, AY, Berice, BN, Bernstein, RS, Bertolacci, GJ, Bettencourt, PJG, Beyene, KA, Bhagat, DS, 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RG, Cramer, KM, Criqui, MH, Cruz-Martins, N, Cuadra-Hernández, SM, Culbreth, GT, Cullen, P, Cunningham, M, Curado, MP, Dadana, S, Dadras, O, Dai, S, Dai, X, Dai, Z, Dalli, LL, Damiani, G, Darega Gela, J, Das, JK, Das, S, Dascalu, AM, Dash, NR, Dashti, M, Dastiridou, A, Davey, G, Dávila-Cervantes, CA, Davis Weaver, N, Davletov, K, De Leo, D, de Luca, K, Debele, AT, Debopadhaya, S, Degenhardt, L, Dehghan, A, Deitesfeld, L, Del Bo', C, Delgado-Enciso, I, Demessa, BH, Demetriades, AK, Deng, K, Deng, X, Denova-Gutiérrez, E, Deravi, N, Dereje, N, Dervenis, N, Dervišević, E, Des Jarlais, DC, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhimal, M, Dhingra, S, Dhulipala, VR, Dias da Silva, D, Diaz, D, Diaz, MJ, Dima, A, Ding, DD, Ding, H, Dinis-Oliveira, RJ, Dirac, MA, Djalalinia, S, Do, THP, do Prado, CB, Doaei, S, Dodangeh, M, Dohare, S, Dokova, KG, Dolecek, C, Dominguez, R-MV, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, ER, dos Santos, WM, Doshi, R, 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Zhu, L, Ziafati, M, Zielińska, M, Zitoun, OA, Zoladl, M, Zou, Z, Zuhlke, LJ, Zumla, A, Zweck, E, Zyoud, SH, Wool, EE, and Murray, CJL
Published: 2024

3. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Author: Vollset, SE, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbastabar, H, Abd Al Magied, AHA, Abd ElHafeez, S, Abdelkader, A, Abdelmasseh, M, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdullahi, A, Abebe, M, Abiodun, O, Aboagye, RG, Abolhassani, H, Abouzid, M, Aboye, GB, Abreu, LG, Absalan, A, Abualruz, H, Abubakar, B, Abukhadijah, HJJ, Addolorato, G, Adekanmbi, V, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adha, R, Adhikary, RK, Adnani, QES, Adzigbli, LA, Afrashteh, F, Afzal, MS, Afzal, S, Agbozo, F, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahlstrom, AJ, Ahmad, A, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmed, A, Ahmed, H, Ahmed, S, Ahmed, SA, Akinosoglou, K, Akkaif, MA, Akrami, AE, Akter, E, Al Awaidy, S, Al Hasan, SM, Al Mosa, AS, Al Ta'ani, O, Al Zaabi, OAM, Alahdab, F, Alajlani, MM, Al-Ajlouni, Y, Alalalmeh, SO, Al-Aly, Z, Alam, K, Alam, N, Alam, T, Alam, Z, Al-amer, RM, Alanezi, FM, Alanzi, TM, Albakri, A, Aldhaleei, WA, Aldridge, RW, Alemohammad, SY, Alemu, YM, Al-Gheethi, AAS, Al-Hanawi, MK, Ali, A, Ali, I, Ali, MU, Ali, R, Ali, SSS, Ali, VE, Ali, W, Al-Ibraheem, A, Alicandro, G, Alif, SM, Aljunid, SM, Alla, F, Almazan, JU, Al-Mekhlafi, HM, Alqutaibi, AY, Alrawashdeh, A, Alrousan, SM, Al-Sabah, SK, Alsabri, MA, Altaany, Z, Al-Tammemi, AB, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Al-Wardat, MS, Al-Worafi, YM, Aly, H, Alyahya, MS, Alzoubi, KH, Al-Zyoud, W, Amani, R, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Andrews, EA, Anil, A, Anil, S, Anoushiravani, A, Antony, CM, Antriyandarti, E, Anuoluwa, BS, Anvari, S, Anyasodor, AE, Appiah, F, Aquilano, M, Arab, JP, Arabloo, J, Arafa, EA, Arafat, M, Aravkin, AY, Ardekani, A, Areda, D, Aregawi, BB, Aremu, A, Ariffin, H, Arkew, M, Armani, K, Artamonov, AA, Arumugam, A, Asghari-Jafarabadi, M, Ashbaugh, C, Astell-Burt, T, Athari, SS, 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Silva, AG, Dadras, O, Dai, X, Dai, Z, Dalton, BE, Damiani, G, Dandona, L, Dandona, R, Das, JK, Das, S, Dash, NR, Davletov, K, De la Hoz, FP, De Leo, D, Debopadhaya, S, Delgado-Enciso, I, Denova-Gutiérrez, E, Dervenis, N, Desai, HD, Devanbu, VGC, Dewan, SMR, Dhama, K, Dhane, AS, Dhingra, S, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Do, THP, do Prado, CB, Dodangeh, M, Doegah, PT, Dohare, S, Dong, W, D'Oria, M, Doshi, R, Dowou, RK, Dsouza, HL, Dsouza, V, Dube, J, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Durojaiye, OC, Dushpanova, A, Dutta, S, Dzianach, PA, Dziedzic, AM, Eboreime, E, Ebrahimi, A, Ebrahimi Kalan, M, Edinur, HA, Efendi, F, Eikemo, TA, Eini, E, Ekundayo, TC, El Arab, RA, El Sayed, I, Elamin, O, Elemam, NM, ElGohary, GMT, Elhadi, M, Elmeligy, OAA, Elmoselhi, AB, Elshaer, M, Elsohaby, I, Eltahir, ME, Emeto, TI, Eshrati, B, Eslami, M, Esmaeili, Z, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faro, A, Fasihi, K, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Fekadu, G, Feng, X, Fereshtehnejad, S-M, Ferrara, P, Ferreira, N, Firew, BS, Fischer, F, Fitriana, I, Flavel, J, Flor, LS, Folayan, MO, Foley, KM, Fonzo, M, Force, LM, Foschi, M, Freitas, A, Fridayani, NKY, Fukutaki, KG, Furtado, JM, Fux, B, Gaal, PA, Gadanya, MA, Gallus, S, Ganesan, B, Ganiyani, MA, Gautam, RK, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Getacher, L, Getahun, GKA, Gething, PW, Ghadimi, DJ, Ghadirian, F, Ghafarian, S, Ghailan, KY, Ghasemi, M, Ghasempour Dabaghi, G, Ghazy, RM, Ghoba, S, Gholami, E, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Ghorbani Vajargah, P, Ghotbi, E, Gil, AU, Gill, TK, Girmay, A, Glasbey, JC, Glushkova, EV, Gnedovskaya, EV, Göbölös, L, Goldust, M, Goleij, P, Golinelli, D, Gopalani, SV, Goulart, AC, Gouravani, M, Goyal, A, Grivna, M, Grosso, G, Guarducci, G, Gubari, MIM, Guicciardi, S, Guimarães, RA, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, R, Gupta, S, Gupta, VK, Haakenstad, A, Hadi, NR, Haep, N, Hafiz, A, Haghmorad, D, Haile, D, Hajj Ali, A, Haj-Mirzaian, A, Halboub, ES, Haller, S, Halwani, R, Hamagharib Abdullah, K, Hamdy, NM, Hamoudi, R, Hanifi, N, Hankey, GJ, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, SMM, Hasanian, M, Hasnain, MS, Hassan, A, Haubold, J, Hay, SI, Hebert, JJ, Hegazi, OE, Heidari, M, Hemmati, M, Henson, CA, Herrera-Serna, BY, Herteliu, C, Heydari, M, Hezam, K, Hidayana, I, Hiraike, Y, Hoan, NQ, Holla, R, Hoogar, P, Horita, N, Hossain, MM, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, C, Huang, J, Hultström, M, Hundie, TG, Hunt, AJ, Hushmandi, K, Hussain, J, Hussain, MA, Hussein, NR, Huynh, H-H, Hwang, B-F, Ibitoye, SE, Iftikhar, PM, Ikiroma, AI, Ikwegbue, PC, Ilic, IM, Ilic, MD, Immurana, M, Isa, MA, Islam, MR, Islam, SMS, Ismail, F, Ismail, NE, Isola, G, Iwagami, M, Iyamu, IO, Jacob, L, Jacobsen, KH, Jafarinia, M, Jahankhani, K, Jahanmehr, N, Jain, N, Jairoun, AA, Jakhmola Mani, DR, Jamil, S, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jee, SH, Jeganathan, J, Jiang, H, Jokar, M, Jonas, JB, Joseph, N, Joshua, CE, Jürisson, M, K, V, Kabir, A, Kabir, Z, Kadashetti, V, Kalankesh, LR, Kalra, S, Kamath, A, Kamath, R, Kamireddy, A, Kanaan, M, Kanchan, T, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Karim, A, Karkhah, S, Kashoo, FZ, Kasraei, H, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kaur, H, Kayode, GA, Kazemi, F, Kazemian, S, Kebede, F, Kendal, ES, Kesse-Guyot, E, Khademvatan, S, Khajuria, H, Khalaji, A, Khalid, A, Khalid, N, Khalilian, A, Khamesipour, F, Khan, F, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Khayat Kashani, HR, Kheirallah, KA, Khokhar, M, Khormali, M, Khorrami, Z, Khosla, AA, Khosravi, M, Khosrowjerdi, M, Khubchandani, J, Kifle, ZD, Kim, G, Kim, JS, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Kochhar, S, Kolahi, A-A, Kompani, F, Koren, G, Korzh, O, Krishan, K, Krishna, V, Krishnamoorthy, V, Kucuk Bicer, B, Kuddus, MA, Kuddus, M, Kuitunen, I, Kujan, O, Kulimbet, M, Kulkarni, V, Kumar, GA, Kumar, H, Kumar, N, Kumar, R, Kumar, V, Kundu, A, Kusuma, D, Kyei-Arthur, F, Kytö, V, Kyu, HH, La Vecchia, C, Lacey, B, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lalloo, R, Lallukka, T, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Lévesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Lawlor, HR, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Le, TDT, Leasher, JL, Lee, DW, Lee, M, Lee, PH, Lee, S-W, Lee, SW, Lee, SWH, Lee, YH, Leigh, J, Leong, E, Li, M-C, Libra, M, Ligade, VS, Lim, L-L, Lim, SS, Limenh, LW, Lindholm, D, Lindstedt, PA, Listl, S, Liu, G, Liu, S, Liu, X, Llanaj, E, López-Bueno, R, López-Gil, JF, Loreche, AM, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, Lusk, JB, Lv, L, M Amin, HI, Ma, ZF, Maass, KL, Machairas, N, Machoy, M, Madureira-Carvalho, ÁM, Magdy Abd El 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Published: 2024

4. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Ferrari, AJ, Santomauro, DF, Aali, A, Abate, YH, Abbafati, C, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdollahi, A, Abdullahi, A, Abegaz, KH, Abeldaño Zuñiga, RA, Aboagye, RG, Abolhassani, H, Abreu, LG, Abualruz, H, Abu-Gharbieh, E, Abu-Rmeileh, NME, Ackerman, IN, Addo, IY, Addolorato, G, Adebiyi, AO, Adepoju, AV, Adewuyi, HO, Afyouni, S, Afzal, S, Agodi, A, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, S, Ahmed, A, Ahmed, LA, Ahmed, MB, Ajami, M, Akinosoglou, K, Akkaif, MA, Al Hasan, SM, Alalalmeh, SO, Al-Aly, Z, Albashtawy, M, Aldridge, RW, Alemu, MD, Alemu, YM, Alene, KA, Al-Gheethi, AAS, Alharrasi, M, Alhassan, RK, Ali, MU, Ali, R, Ali, SSS, Alif, SM, Aljunid, SM, Al-Marwani, S, Almazan, JU, Alomari, MA, Al-Omari, B, Altaany, Z, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Alwafi, H, Al-Wardat, MS, Al-Worafi, YM, Aly, S, Alzoubi, KH, Amare, AT, Amegbor, PM, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Ansari, H, Antony, CM, Anwar, S, Anwar, SL, Anwer, R, Anyanwu, PE, Arab, JP, Arabloo, J, Arafat, M, Araki, DT, Aravkin, AY, Arkew, M, Armocida, B, Arndt, MB, Arooj, M, Artamonov, AA, Aruleba, RT, Arumugam, A, Ashbaugh, C, Ashemo, MY, Ashraf, M, Asika, MO, Askari, E, Astell-Burt, T, Athari, SS, Atorkey, P, Atout, MMW, Atreya, A, Aujayeb, A, Ausloos, M, Avan, A, Awotidebe, AW, Awuviry-Newton, K, Ayala Quintanilla, BP, Ayuso-Mateos, JL, Azadnajafabad, S, Azevedo, RMS, Babu, AS, Badar, M, Badiye, AD, Baghdadi, S, Bagheri, N, Bah, S, Bai, R, Baker, JL, Bakkannavar, SM, Bako, AT, Balakrishnan, S, Bam, K, Banik, PC, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Barqawi, HJ, Barrow, A, Barteit, S, Barua, L, Bashiri Aliabadi, S, Basiru, A, Basu, S, Bathini, PP, Batra, K, Baune, BT, Bayileyegn, NS, Behnam, B, Behnoush, AH, Beiranvand, M, Bejarano Ramirez, DF, Bell, ML, Bello, OO, Beloukas, A, Bensenor, IM, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Bhandari, D, Bhargava, A, Bhaskar, S, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhatti, R, Bhutta, ZA, Bikbov, B, Bishai, JD, Bisignano, C, Bitra, VR, Bjørge, T, Bodolica, V, Bodunrin, AO, Bogale, EK, Bonakdar Hashemi, M, Bonny, A, Bora Basara, B, Borhany, H, Boxe, C, Brady, OJ, Bragazzi, NL, Braithwaite, D, Brant, LC, Brauer, M, Breitner, S, Brenner, H, Brown, J, Brugha, T, Bulamu, NB, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, ZA, Byun, J, Caetano dos Santos, FL, Calina, D, Cámera, LA, Campos-Nonato, IR, Cao, C, Capodici, A, Carr, S, Carreras, G, Carugno, A, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catapano, AL, Cattaruzza, MS, Caye, A, Cegolon, L, Cembranel, F, Cenderadewi, M, Cerin, E, Chakraborty, PA, Chan, JSK, Chan, RNC, Chandika, RM, Chandrasekar, EK, Charalampous, P, Chattu, VK, Chatzimavridou-Grigoriadou, V, Chen, AW, Chen, A-T, Chen, CS, Chen, H, Chen, NM, Cheng, ETW, Chimed-Ochir, 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Nguyen, DH, Nguyen, HQ, Niazi, RK, Nikolouzakis, TK, Nikoobar, A, Nikoomanesh, F, Nikpoor, AR, Nnaji, CA, Nnyanzi, LA, Noman, EA, Nomura, S, Norrving, B, Nri-Ezedi, CA, Ntaios, G, Ntsekhe, M, Nurrika, D, Nzoputam, CI, Nzoputam, OJ, Oancea, B, Odetokun, IA, O'Donnell, MJ, Oguntade, AS, Oguta, JO, Okati-Aliabad, H, Okeke, SR, Okekunle, AP, Okonji, OC, Olagunju, AT, Olasupo, OO, Olatubi, MI, Oliveira, GMM, Olufadewa, II, Olusanya, BO, Olusanya, JO, Omar, HA, Omer, GL, Omonisi, AEE, Onie, S, Onwujekwe, OE, Ordak, M, Orish, VN, Ortega-Altamirano, DV, Ortiz, A, Ortiz-Brizuela, E, Osman, WMS, Ostroff, SM, Osuagwu, UL, Otoiu, A, Otstavnov, N, Otstavnov, SS, Ouyahia, A, Ouyang, G, Owolabi, MO, P A, MP, Padron-Monedero, A, Padubidri, JR, Palicz, T, Palladino, C, Pan, F, Pandi-Perumal, SR, Pangaribuan, HU, Panos, GD, Panos, LD, Pantea Stoian, AM, Pardhan, S, Parikh, RR, Pashaei, A, Pasovic, M, Passera, R, Patel, J, Patel, SK, Patil, S, Patoulias, D, Patthipati, VS, Pawar, S, Pazoki Toroudi, H, 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Y, Yusuf, H, Zahid, MH, Zakham, F, Zaki, L, Zaki, N, Zaman, BA, Zamora, N, Zand, R, Zandieh, GGZ, Zar, HJ, Zarrintan, A, Zastrozhin, MS, Zhang, H, Zhang, N, Zhang, Y, Zhao, H, Zhong, C, Zhong, P, Zhou, J, Zhu, Z, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoladl, M, Zumla, A, Zyoud, SH, Vos, T, and Murray, CJL
Published: 2024

5. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease 2019

Author: Nichols, E, Steinmetz, JD, Vollset, SE, Fukutaki, K, Chalek, J, Abd-Allah, F, Abdoli, A, Abualhasan, A, Abu-Gharbieh, E, Akram, TT, Al Hamad, H, Alahdab, F, Alanezi, FM, Alipour, V, Almustanyir, S, Amu, H, Ansari, I, Arabloo, J, Ashraf, T, Astell-Burt, T, Ayano, G, Ayuso-Mateos, JL, Baig, AA, Barnett, A, Barrow, A, Baune, BT, Bejot, Y, Bezabhe, WMM, Bezabih, YM, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bijani, A, Biswas, A, Bolla, SR, Boloor, A, Brayne, C, Brenner, H, Burkart, K, Burns, RA, Camera, LA, Cao, C, Carvalho, F, Castro-de-Araujo, LFS, Catala-Lopez, F, Cerin, E, Chavan, PP, Cherbuin, N, Chu, D-T, Costa, VM, Couto, RAS, Dadras, O, Dai, X, Dandona, L, Dandona, R, De La Cruz-Gongora, V, Dhamnetiya, D, da Silva, DD, Diaz, D, Douiri, A, Edvardsson, D, Ekholuenetale, M, El Sayed, I, El-Jaafary, S, Eskandari, K, Eskandarieh, S, Esmaeilnejad, S, Fares, J, Faro, A, Farooque, U, Feigin, VL, Feng, X, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Filip, I, Fillit, H, Fischer, F, Gaidhane, S, Galluzzo, L, Ghashghaee, A, Ghith, N, Gialluisi, A, Gilani, SA, Glavan, I-R, Gnedovskaya, E, Golechha, M, Gupta, R, Gupta, VB, Gupta, VK, Haider, MR, Hall, BJ, Hamidi, S, Hanif, A, Hankey, GJ, Haque, S, Hartono, RK, Hasaballah, A, Hasan, MT, Hassan, A, Hay, S, Hayat, K, Hegazy, M, Heidari, G, Heidari-Soureshjani, R, Herteliu, C, Househ, M, Hussain, R, Hwang, B-F, Iacoviello, L, Iavicoli, I, Ilesanmi, OS, Ilic, IM, Ilic, MD, Irvani, SSN, Iso, H, Iwagami, M, Jabbarinejad, R, Jacob, L, Jain, V, Jayapal, SK, Jayawardena, R, Jha, RP, Jonas, JB, Joseph, N, Kalani, R, Kandel, A, Kandel, H, Karch, A, Kasa, AS, Kassie, GM, Keshavarz, P, Khan, MAB, Khatib, MN, Khoja, TAM, Khubchandani, J, Kim, MS, Kim, YJ, Kisa, A, Kisa, S, Kivimaki, M, Koroshetz, WJ, Koyanagi, A, Kumar, GA, Kumar, M, Lak, HM, Leonardi, M, Li, B, Lim, SS, Liu, X, Liu, Y, Logroscino, G, Lorkowski, S, Lucchetti, G, Saute, RL, Magnani, FG, Malik, AA, Massano, J, Mehndiratta, MM, Menezes, RG, Meretoja, A, Mohajer, B, Ibrahim, NM, Mohammad, Y, Mohammed, A, Mokdad, AH, Mondello, S, Moni, MA, Moniruzzaman, M, Mossie, TB, Nagel, G, Naveed, M, Nayak, VC, Kandel, SN, Nguyen, TH, Oancea, B, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Panda-Jonas, S, Kan, FP, Pasovic, M, Patel, UK, Pathak, M, Peres, MFP, Perianayagam, A, Peterson, CB, Phillips, MR, Pinheiro, M, Piradov, MA, Pond, CD, Potashman, MH, Pottoo, FH, Prada, S, Radfar, A, Raggi, A, Rahim, F, Rahman, M, Ram, P, Ranasinghe, P, Rawaf, DL, Rawaf, S, Rezaei, N, Rezapour, A, Robinson, SR, Romoli, M, Roshandel, G, Sahathevan, R, Sahebkar, A, Sahraian, MA, Sathian, B, Sattin, D, Sawhney, M, Saylan, M, Schiavolin, S, Seylani, A, Sha, F, Shaikh, MA, Shaji, KS, Shannawaz, M, Shetty, JK, Shigematsu, M, Shin, JI, Shiri, R, Santos Silva, DA, Silva, JP, Silva, R, Singh, JA, Skryabin, VY, Skryabina, AA, Smith, AE, Soshnikov, S, Spurlock, EE, Stein, DJ, Sun, J, Tabares-Seisdedos, R, Thakur, B, Timalsina, B, Tovani-Palone, MR, Bach, XT, Tsegaye, GW, Tahbaz, SV, Valdez, PR, Venketasubramanian, N, Vlassov, V, Giang, TV, Linh, GV, Wang, Y-P, Wimo, A, Winkler, AS, Yadav, L, Jabbari, SHY, Yamagishi, K, Yang, L, Yano, Y, Yonemoto, N, Yu, C, Yunusa, I, Zadey, S, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Murray, CJL, Vos, T, Nichols, E, Steinmetz, JD, Vollset, SE, Fukutaki, K, Chalek, J, Abd-Allah, F, Abdoli, A, Abualhasan, A, Abu-Gharbieh, E, Akram, TT, Al Hamad, H, Alahdab, F, Alanezi, FM, Alipour, V, Almustanyir, S, Amu, H, Ansari, I, Arabloo, J, Ashraf, T, Astell-Burt, T, Ayano, G, Ayuso-Mateos, JL, Baig, AA, Barnett, A, Barrow, A, Baune, BT, Bejot, Y, Bezabhe, WMM, Bezabih, YM, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bijani, A, Biswas, A, Bolla, SR, Boloor, A, Brayne, C, Brenner, H, Burkart, K, Burns, RA, Camera, LA, Cao, C, Carvalho, F, Castro-de-Araujo, LFS, Catala-Lopez, F, Cerin, E, Chavan, PP, Cherbuin, N, Chu, D-T, Costa, VM, Couto, RAS, Dadras, O, Dai, X, Dandona, L, Dandona, R, De La Cruz-Gongora, V, Dhamnetiya, D, da Silva, DD, Diaz, D, Douiri, A, Edvardsson, D, Ekholuenetale, M, El Sayed, I, El-Jaafary, S, Eskandari, K, Eskandarieh, S, Esmaeilnejad, S, Fares, J, Faro, A, Farooque, U, Feigin, VL, Feng, X, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Filip, I, Fillit, H, Fischer, F, Gaidhane, S, Galluzzo, L, Ghashghaee, A, Ghith, N, Gialluisi, A, Gilani, SA, Glavan, I-R, Gnedovskaya, E, Golechha, M, Gupta, R, Gupta, VB, Gupta, VK, Haider, MR, Hall, BJ, Hamidi, S, Hanif, A, Hankey, GJ, Haque, S, Hartono, RK, Hasaballah, A, Hasan, MT, Hassan, A, Hay, S, Hayat, K, Hegazy, M, Heidari, G, Heidari-Soureshjani, R, Herteliu, C, Househ, M, Hussain, R, Hwang, B-F, Iacoviello, L, Iavicoli, I, Ilesanmi, OS, Ilic, IM, Ilic, MD, Irvani, SSN, Iso, H, Iwagami, M, Jabbarinejad, R, Jacob, L, Jain, V, Jayapal, SK, Jayawardena, R, Jha, RP, Jonas, JB, Joseph, N, Kalani, R, Kandel, A, Kandel, H, Karch, A, Kasa, AS, Kassie, GM, Keshavarz, P, Khan, MAB, Khatib, MN, Khoja, TAM, Khubchandani, J, Kim, MS, Kim, YJ, Kisa, A, Kisa, S, Kivimaki, M, Koroshetz, WJ, Koyanagi, A, Kumar, GA, Kumar, M, Lak, HM, Leonardi, M, Li, B, Lim, SS, Liu, X, Liu, Y, Logroscino, G, Lorkowski, S, Lucchetti, G, Saute, RL, Magnani, FG, Malik, AA, Massano, J, Mehndiratta, MM, Menezes, RG, Meretoja, A, Mohajer, B, Ibrahim, NM, Mohammad, Y, Mohammed, A, Mokdad, AH, Mondello, S, Moni, MA, Moniruzzaman, M, Mossie, TB, Nagel, G, Naveed, M, Nayak, VC, Kandel, SN, Nguyen, TH, Oancea, B, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Panda-Jonas, S, Kan, FP, Pasovic, M, Patel, UK, Pathak, M, Peres, MFP, Perianayagam, A, Peterson, CB, Phillips, MR, Pinheiro, M, Piradov, MA, Pond, CD, Potashman, MH, Pottoo, FH, Prada, S, Radfar, A, Raggi, A, Rahim, F, Rahman, M, Ram, P, Ranasinghe, P, Rawaf, DL, Rawaf, S, Rezaei, N, Rezapour, A, Robinson, SR, Romoli, M, Roshandel, G, Sahathevan, R, Sahebkar, A, Sahraian, MA, Sathian, B, Sattin, D, Sawhney, M, Saylan, M, Schiavolin, S, Seylani, A, Sha, F, Shaikh, MA, Shaji, KS, Shannawaz, M, Shetty, JK, Shigematsu, M, Shin, JI, Shiri, R, Santos Silva, DA, Silva, JP, Silva, R, Singh, JA, Skryabin, VY, Skryabina, AA, Smith, AE, Soshnikov, S, Spurlock, EE, Stein, DJ, Sun, J, Tabares-Seisdedos, R, Thakur, B, Timalsina, B, Tovani-Palone, MR, Bach, XT, Tsegaye, GW, Tahbaz, SV, Valdez, PR, Venketasubramanian, N, Vlassov, V, Giang, TV, Linh, GV, Wang, Y-P, Wimo, A, Winkler, AS, Yadav, L, Jabbari, SHY, Yamagishi, K, Yang, L, Yano, Y, Yonemoto, N, Yu, C, Yunusa, I, Zadey, S, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Murray, CJL, and Vos, T
Abstract: BACKGROUND: Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors. METHODS: We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis. FINDINGS: We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4-65·1) million cases globally in 2019 to 152·8 (130·8-175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [-7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64-1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52-1·85]). There was geographical heterogeneity in the projected inc
Published: 2022

6. Sustained Negative Mental Health Outcomes Among Healthcare Workers Over the First Year of the COVID-19 Pandemic: A Prospective Cohort Study.

Author: Mediavilla, R, Fernández-Jiménez, E, Martinez-Morata, I, Jaramillo, F, Andreo-Jover, J, Morán-Sánchez, I, Mascayano, F, Moreno-Küstner, B, Minué, S, Ayuso-Mateos, JL, Bryant, RA, Bravo-Ortiz, M-F, Martínez-Alés, G, Mediavilla, R, Fernández-Jiménez, E, Martinez-Morata, I, Jaramillo, F, Andreo-Jover, J, Morán-Sánchez, I, Mascayano, F, Moreno-Küstner, B, Minué, S, Ayuso-Mateos, JL, Bryant, RA, Bravo-Ortiz, M-F, and Martínez-Alés, G
Abstract: Objective: To characterize the evolution of healthcare workers' mental health status over the 1-year period following the initial COVID-19 pandemic outbreak and to examine baseline characteristics associated with resolution or persistence of mental health problems over time. Methods: We conducted an 8-month follow-up cohort study. Eligible participants were healthcare workers working in Spain. Baseline data were collected during the initial pandemic outbreak. Survey-based self-reported measures included COVID-19-related exposures, sociodemographic characteristics, and three mental health outcomes (psychological distress, depression symptoms, and posttraumatic stress disorder symptoms). We examined three longitudinal trajectories in mental health outcomes between baseline and follow-up assessments (namely asymptomatic/stable, recovering, and persistently symptomatic/worsening). Results: We recruited 1,807 participants. Between baseline and follow-up assessments, the proportion of respondents screening positive for psychological distress and probable depression decreased, respectively, from 74% to 56% and from 28% to 21%. Two-thirds remained asymptomatic/stable in terms of depression symptoms and 56% remained symptomatic or worsened over time in terms of psychological distress. Conclusion: Poor mental health outcomes among healthcare workers persisted over time. Occupational programs and mental health strategies should be put in place.
Published: 2022

7. Suicide numbers during the first 9-15 months of the COVID-19 pandemic compared with pre-existing trends: An interrupted time series analysis in 33 countries

Author: Pirkis, J, Gunnell, D, Shin, S, Del Pozo-Banos, M, Arya, V, Aguilar, PA, Appleby, L, Arafat, SMY, Arensman, E, Ayuso-Mateos, JL, Balhara, YPS, Bantjes, J, Baran, A, Behera, C, Bertolote, J, Borges, G, Bray, M, Brecic, P, Caine, E, Calati, R, Carli, V, Castelpietra, G, Chan, LF, Chang, S-S, Colchester, D, Coss-Guzman, M, Crompton, D, Curkovic, M, Dandona, R, De Jaegere, E, De Leo, D, Deisenhammer, EA, Dwyer, J, Erlangsen, A, Faust, JS, Fornaro, M, Fortune, S, Garrett, A, Gentile, G, Gerstner, R, Gilissen, R, Gould, M, Gupta, SK, Hawton, K, Holz, F, Kamenshchikov, I, Kapur, N, Kasal, A, Khan, M, Kirtley, OJ, Knipe, D, Kolves, K, Kolzer, SC, Krivda, H, Leske, S, Madeddu, F, Marshall, A, Memon, A, Mittendorfer-Rutz, E, Nestadt, P, Neznanov, N, Niederkrotenthaler, T, Nielsen, E, Nordentoft, M, Oberlerchner, H, O'Connor, RC, Papsdorf, R, Partonen, T, Phillips, MR, Platt, S, Portzky, G, Psota, G, Qin, P, Radeloff, D, Reif, A, Reif-Leonhard, C, Rezaeian, M, Roman-Vazquez, N, Roskar, S, Rozanov, V, Sara, G, Scavacini, K, Schneider, B, Semenova, N, Sinyor, M, Tambuzzi, S, Townsend, E, Ueda, M, Wasserman, D, Webb, RT, Winkler, P, Yip, PSF, Zalsman, G, Zoja, R, John, A, Spittal, MJ, Pirkis, J, Gunnell, D, Shin, S, Del Pozo-Banos, M, Arya, V, Aguilar, PA, Appleby, L, Arafat, SMY, Arensman, E, Ayuso-Mateos, JL, Balhara, YPS, Bantjes, J, Baran, A, Behera, C, Bertolote, J, Borges, G, Bray, M, Brecic, P, Caine, E, Calati, R, Carli, V, Castelpietra, G, Chan, LF, Chang, S-S, Colchester, D, Coss-Guzman, M, Crompton, D, Curkovic, M, Dandona, R, De Jaegere, E, De Leo, D, Deisenhammer, EA, Dwyer, J, Erlangsen, A, Faust, JS, Fornaro, M, Fortune, S, Garrett, A, Gentile, G, Gerstner, R, Gilissen, R, Gould, M, Gupta, SK, Hawton, K, Holz, F, Kamenshchikov, I, Kapur, N, Kasal, A, Khan, M, Kirtley, OJ, Knipe, D, Kolves, K, Kolzer, SC, Krivda, H, Leske, S, Madeddu, F, Marshall, A, Memon, A, Mittendorfer-Rutz, E, Nestadt, P, Neznanov, N, Niederkrotenthaler, T, Nielsen, E, Nordentoft, M, Oberlerchner, H, O'Connor, RC, Papsdorf, R, Partonen, T, Phillips, MR, Platt, S, Portzky, G, Psota, G, Qin, P, Radeloff, D, Reif, A, Reif-Leonhard, C, Rezaeian, M, Roman-Vazquez, N, Roskar, S, Rozanov, V, Sara, G, Scavacini, K, Schneider, B, Semenova, N, Sinyor, M, Tambuzzi, S, Townsend, E, Ueda, M, Wasserman, D, Webb, RT, Winkler, P, Yip, PSF, Zalsman, G, Zoja, R, John, A, and Spittal, MJ
Abstract: BACKGROUND: Predicted increases in suicide were not generally observed in the early months of the COVID-19 pandemic. However, the picture may be changing and patterns might vary across demographic groups. We aimed to provide a timely, granular picture of the pandemic's impact on suicides globally. METHODS: We identified suicide data from official public-sector sources for countries/areas-within-countries, searching websites and academic literature and contacting data custodians and authors as necessary. We sent our first data request on 22nd June 2021 and stopped collecting data on 31st October 2021. We used interrupted time series (ITS) analyses to model the association between the pandemic's emergence and total suicides and suicides by sex-, age- and sex-by-age in each country/area-within-country. We compared the observed and expected numbers of suicides in the pandemic's first nine and first 10-15 months and used meta-regression to explore sources of variation. FINDINGS: We sourced data from 33 countries (24 high-income, six upper-middle-income, three lower-middle-income; 25 with whole-country data, 12 with data for area(s)-within-the-country, four with both). There was no evidence of greater-than-expected numbers of suicides in the majority of countries/areas-within-countries in any analysis; more commonly, there was evidence of lower-than-expected numbers. Certain sex, age and sex-by-age groups stood out as potentially concerning, but these were not consistent across countries/areas-within-countries. In the meta-regression, different patterns were not explained by countries' COVID-19 mortality rate, stringency of public health response, economic support level, or presence of a national suicide prevention strategy. Nor were they explained by countries' income level, although the meta-regression only included data from high-income and upper-middle-income countries, and there were suggestions from the ITS analyses that lower-middle-income countries fared less well
Published: 2022

8. Mental health problems and needs of frontline healthcare workers during the COVID-19 pandemic in Spain: A qualitative analysis.

Author: Mediavilla, R, Monistrol-Mula, A, McGreevy, KR, Felez-Nobrega, M, Delaire, A, Nicaise, P, Palomo-Conti, S, Bayón, C, Bravo-Ortiz, M-F, Rodríguez-Vega, B, Witteveen, A, Sijbrandij, M, Turrini, G, Purgato, M, Vuillermoz, C, Melchior, M, Petri-Romão, P, Stoffers-Winterling, J, Bryant, RA, McDaid, D, Park, A-L, Ayuso-Mateos, JL, RESPOND Consortium, Mediavilla, R, Monistrol-Mula, A, McGreevy, KR, Felez-Nobrega, M, Delaire, A, Nicaise, P, Palomo-Conti, S, Bayón, C, Bravo-Ortiz, M-F, Rodríguez-Vega, B, Witteveen, A, Sijbrandij, M, Turrini, G, Purgato, M, Vuillermoz, C, Melchior, M, Petri-Romão, P, Stoffers-Winterling, J, Bryant, RA, McDaid, D, Park, A-L, Ayuso-Mateos, JL, and RESPOND Consortium
Abstract: BACKGROUND: Healthcare workers (HCWs) from COVID-19 hotspots worldwide have reported poor mental health outcomes since the pandemic's beginning. The virulence of the initial COVID-19 surge in Spain and the urgency for rapid evidence constrained early studies in their capacity to inform mental health programs accurately. Here, we used a qualitative research design to describe relevant mental health problems among frontline HCWs and explore their association with determinants and consequences and their implications for the design and implementation of mental health programs. MATERIALS AND METHODS: Following the Programme Design, Implementation, Monitoring, and Evaluation (DIME) protocol, we used a two-step qualitative research design to interview frontline HCWs, mental health experts, administrators, and service planners in Spain. We used Free List (FL) interviews to identify problems experienced by frontline HCWs and Key informant (KI) interviews to describe them and explore their determinants and consequences, as well as the strategies considered useful to overcome these problems. We used a thematic analysis approach to analyze the interview outputs and framed our results into a five-level social-ecological model (intrapersonal, interpersonal, organizational, community, and public health). RESULTS: We recruited 75 FL and 22 KI interviewees, roughly balanced in age and gender. We detected 56 themes during the FL interviews and explored the following themes in the KI interviews: fear of infection, psychological distress, stress, moral distress, and interpersonal conflicts among coworkers. We found that interviewees reported perceived causes and consequences across problems at all levels (intrapersonal to public health). Although several mental health strategies were implemented (especially at an intrapersonal and interpersonal level), most mental health needs remained unmet, especially at the organizational, community, and public policy levels. CONCLUSIONS: In keeping
Published: 2022

9. Effectiveness of a stepped-care programme of internet-based psychological interventions for healthcare workers with psychological distress: Study protocol for the RESPOND healthcare workers randomised controlled trial.

Author: Mediavilla, R, McGreevy, KR, Felez-Nobrega, M, Monistrol-Mula, A, Bravo-Ortiz, M-F, Bayón, C, Rodríguez-Vega, B, Nicaise, P, Delaire, A, Sijbrandij, M, Witteveen, AB, Purgato, M, Barbui, C, Tedeschi, F, Melchior, M, van der Waerden, J, McDaid, D, Park, A-L, Kalisch, R, Petri-Romão, P, Underhill, J, Bryant, RA, Haro, JM, Ayuso-Mateos, JL, RESPOND Consortium, Mediavilla, R, McGreevy, KR, Felez-Nobrega, M, Monistrol-Mula, A, Bravo-Ortiz, M-F, Bayón, C, Rodríguez-Vega, B, Nicaise, P, Delaire, A, Sijbrandij, M, Witteveen, AB, Purgato, M, Barbui, C, Tedeschi, F, Melchior, M, van der Waerden, J, McDaid, D, Park, A-L, Kalisch, R, Petri-Romão, P, Underhill, J, Bryant, RA, Haro, JM, Ayuso-Mateos, JL, and RESPOND Consortium
Abstract: BACKGROUND AND AIMS: The coronavirus disease 2019 pandemic has challenged health services worldwide, with a worsening of healthcare workers' mental health within initial pandemic hotspots. In early 2022, the Omicron variant is spreading rapidly around the world. This study explores the effectiveness and cost-effectiveness of a stepped-care programme of scalable, internet-based psychological interventions for distressed health workers on self-reported anxiety and depression symptoms. METHODS: We present the study protocol for a multicentre (two sites), parallel-group (1:1 allocation ratio), analyst-blinded, superiority, randomised controlled trial. Healthcare workers with psychological distress will be allocated either to care as usual only or to care as usual plus a stepped-care programme that includes two scalable psychological interventions developed by the World Health Organization: A guided self-help stress management guide (Doing What Matters in Times of Stress) and a five-session cognitive behavioural intervention (Problem Management Plus). All participants will receive a single-session emotional support intervention, namely psychological first aid. We will include 212 participants. An intention-to-treat analysis using linear mixed models will be conducted to explore the programme's effect on anxiety and depression symptoms, as measured by the Patient Health Questionnaire - Anxiety and Depression Scale summary score at 21 weeks from baseline. Secondary outcomes include post-traumatic stress disorder symptoms, resilience, quality of life, cost impact and cost-effectiveness. CONCLUSIONS: This study is the first randomised trial that combines two World Health Organization psychological interventions tailored for health workers into one stepped-care programme. Results will inform occupational and mental health prevention, treatment, and recovery strategies. REGISTRATION DETAILS: ClinicalTrials.gov Identifier: NCT04980326.
Published: 2022

10. Impact of work arrangements during the COVID-19 pandemic on mental health in France.

Author: Hecker, I, El Aarbaoui, T, Wallez, S, Andersen, AJ, Ayuso-Mateos, JL, Bryant, R, Corrao, G, McDaid, D, Mediavilla, R, Mittendorfer-Rutz, E, Compagnoni, MM, Park, A-L, Riepenhausen, A, Rigotti, T, Seeber, K, Sijbrandij, M, Smith, P, Tüscher, O, Walter, H, Witteveen, A, Mary-Krause, M, Melchior, M, Hecker, I, El Aarbaoui, T, Wallez, S, Andersen, AJ, Ayuso-Mateos, JL, Bryant, R, Corrao, G, McDaid, D, Mediavilla, R, Mittendorfer-Rutz, E, Compagnoni, MM, Park, A-L, Riepenhausen, A, Rigotti, T, Seeber, K, Sijbrandij, M, Smith, P, Tüscher, O, Walter, H, Witteveen, A, Mary-Krause, M, and Melchior, M
Abstract: •Symptoms of anxiety/depression were found in 28.8% of the participants at least once.•Unemployment and financial difficulties were associated with anxiety/depression.•Targeted mental health support could lessen mental health impact.
Published: 2022

11. The burden of injury in Central, Eastern, and Western European sub-region: a systematic analysis from the Global Burden of Disease 2019 Study

Author: Haagsma, JA, Charalampous, P, Ariani, F, Gallay, A, Moesgaard Iburg, K, Nena, E, Ngwa, CH, Rommel, A, Zelviene, A, Abegaz, KH, Al Hamad, H, Albano, L, Liliana Andrei, C, Andrei, T, Antonazzo, IC, Aremu, O, Arumugam, A, Atreya, A, Aujayeb, A, Ayuso-Mateos, JL, Engelbert Bain, L, Banach, M, Winfried Baernighausen, T, Barone-Adesi, F, Beghi, M, Bennett, DA, Bhagavathula, AS, Carvalho, F, Castelpietra, G, Caterina, L, Chandan, JS, Couto, RAS, Cruz-Martins, N, Damiani, G, Dastiridou, A, Demetriades, AK, Dias-da-Silva, D, Francis Fagbamigbe, A, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Fischer, F, Fra Paleo, U, Ghirini, S, Glasbey, JC, Glavan, I-R, Gomes, NGM, Grivna, M, Harlianto, NI, Haro, JM, Hasan, MT, Hostiuc, S, Iavicoli, I, Ilic, MD, Ilic, IM, Jakovljevic, M, Jonas, JB, Jerzy Jozwiak, J, Jurisson, M, Kauppila, JH, Kayode, GA, han, MAB, Kisa, A, Kisa, S, Koyanagi, A, Kumar, M, Kurmi, OP, La-Vecchia, C, Lamnisos, D, Lasrado, S, Lauriola, P, Linn, S, Loureiro, JA, Lunevicius, R, Madureira-Carvalho, A, Mechili, EA, Majeed, A, Menezes, RG, Mentis, A-FA, Meretoja, A, Mestrovic, T, Miazgowski, T, Miazgowski, B, Mirica, A, Molokhia, M, Mohammed, S, Monasta, L, Mulita, F, David Naimzada, M, Negoi, I, Neupane, S, Oancea, B, Orru, H, Otoiu, A, Otstavnov, N, Otstavnov, SS, Padron-Monedero, A, Panda-Jonas, S, Pardhan, S, Patel, J, Pedersini, P, Pinheiro, M, Rakovac, I, Rao, CR, Rawaf, S, Rawaf, DL, Rodrigues, V, Ronfani, L, Sagoe, D, Sanmarchi, F, Santric-Milicevic, MM, Sathian, B, Sheikh, A, Shiri, R, Shivalli, S, Dora Sigfusdottir, I, Sigurvinsdottir, R, Yurievich Skryabin, V, Aleksandrovna Skryabina, A, Smarandache, C-G, Socea, B, Sousa, RARC, Steiropoulos, P, Tabares-Seisdedos, R, Roberto Tovani-Palone, M, Tozija, F, Van de Velde, S, Juhani Vasankari, T, Veroux, M, Violante, FS, Vlassov, V, Wang, Y, Yadollahpour, A, Yaya, S, Sergeevich Zastrozhin, M, Zastrozhina, A, Polinder, S, Majdan, M, Haagsma, JA, Charalampous, P, Ariani, F, Gallay, A, Moesgaard Iburg, K, Nena, E, Ngwa, CH, Rommel, A, Zelviene, A, Abegaz, KH, Al Hamad, H, Albano, L, Liliana Andrei, C, Andrei, T, Antonazzo, IC, Aremu, O, Arumugam, A, Atreya, A, Aujayeb, A, Ayuso-Mateos, JL, Engelbert Bain, L, Banach, M, Winfried Baernighausen, T, Barone-Adesi, F, Beghi, M, Bennett, DA, Bhagavathula, AS, Carvalho, F, Castelpietra, G, Caterina, L, Chandan, JS, Couto, RAS, Cruz-Martins, N, Damiani, G, Dastiridou, A, Demetriades, AK, Dias-da-Silva, D, Francis Fagbamigbe, A, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Fischer, F, Fra Paleo, U, Ghirini, S, Glasbey, JC, Glavan, I-R, Gomes, NGM, Grivna, M, Harlianto, NI, Haro, JM, Hasan, MT, Hostiuc, S, Iavicoli, I, Ilic, MD, Ilic, IM, Jakovljevic, M, Jonas, JB, Jerzy Jozwiak, J, Jurisson, M, Kauppila, JH, Kayode, GA, han, MAB, Kisa, A, Kisa, S, Koyanagi, A, Kumar, M, Kurmi, OP, La-Vecchia, C, Lamnisos, D, Lasrado, S, Lauriola, P, Linn, S, Loureiro, JA, Lunevicius, R, Madureira-Carvalho, A, Mechili, EA, Majeed, A, Menezes, RG, Mentis, A-FA, Meretoja, A, Mestrovic, T, Miazgowski, T, Miazgowski, B, Mirica, A, Molokhia, M, Mohammed, S, Monasta, L, Mulita, F, David Naimzada, M, Negoi, I, Neupane, S, Oancea, B, Orru, H, Otoiu, A, Otstavnov, N, Otstavnov, SS, Padron-Monedero, A, Panda-Jonas, S, Pardhan, S, Patel, J, Pedersini, P, Pinheiro, M, Rakovac, I, Rao, CR, Rawaf, S, Rawaf, DL, Rodrigues, V, Ronfani, L, Sagoe, D, Sanmarchi, F, Santric-Milicevic, MM, Sathian, B, Sheikh, A, Shiri, R, Shivalli, S, Dora Sigfusdottir, I, Sigurvinsdottir, R, Yurievich Skryabin, V, Aleksandrovna Skryabina, A, Smarandache, C-G, Socea, B, Sousa, RARC, Steiropoulos, P, Tabares-Seisdedos, R, Roberto Tovani-Palone, M, Tozija, F, Van de Velde, S, Juhani Vasankari, T, Veroux, M, Violante, FS, Vlassov, V, Wang, Y, Yadollahpour, A, Yaya, S, Sergeevich Zastrozhin, M, Zastrozhina, A, Polinder, S, and Majdan, M
Abstract: BACKGROUND: Injury remains a major concern to public health in the European region. Previous iterations of the Global Burden of Disease (GBD) study showed wide variation in injury death and disability adjusted life year (DALY) rates across Europe, indicating injury inequality gaps between sub-regions and countries. The objectives of this study were to: 1) compare GBD 2019 estimates on injury mortality and DALYs across European sub-regions and countries by cause-of-injury category and sex; 2) examine changes in injury DALY rates over a 20 year-period by cause-of-injury category, sub-region and country; and 3) assess inequalities in injury mortality and DALY rates across the countries. METHODS: We performed a secondary database descriptive study using the GBD 2019 results on injuries in 44 European countries from 2000 to 2019. Inequality in DALY rates between these countries was assessed by calculating the DALY rate ratio between the highest-ranking country and lowest-ranking country in each year. RESULTS: In 2019, in Eastern Europe 80 [95% uncertainty interval (UI): 71 to 89] people per 100,000 died from injuries; twice as high compared to Central Europe (38 injury deaths per 100,000; 95% UI 34 to 42) and three times as high compared to Western Europe (27 injury deaths per 100,000; 95%UI 25 to 28). The injury DALY rates showed less pronounced differences between Eastern (5129 DALYs per 100,000; 95% UI: 4547 to 5864), Central (2940 DALYs per 100,000; 95% UI: 2452 to 3546) and Western Europe (1782 DALYs per 100,000; 95% UI: 1523 to 2115). Injury DALY rate was lowest in Italy (1489 DALYs per 100,000) and highest in Ukraine (5553 DALYs per 100,000). The difference in injury DALY rates by country was larger for males compared to females. The DALY rate ratio was highest in 2005, with DALY rate in the lowest-ranking country (Russian Federation) 6.0 times higher compared to the highest-ranking country (Malta). After 2005, the DALY rate ratio between the lowest- and the highe
Published: 2022

12. The effect of loneliness and social support on the course of major depressive disorder among adults aged 50 years and older: A longitudinal study

Author: Gabarrell-Pascuet A, Moneta MV, Ayuso-Mateos JL, Maria Miret, Lara E, Haro JM, Olaya B, and Joan Domènech Abella
Subjects: recurrence, major depressive disorder, loneliness, longitudinal study, social support, older adults
Abstract: BACKGROUND: Previous research indicates that social support, loneliness, and major depressive disorder (MDD) are interrelated. Little is known about the potential pathways among these factors, in particular in the case of adults aged 50 years and older and suffering from MDD. The objective was to investigate whether loneliness mediates the association between low social support and recurrent episodes of MDD. METHODS: We used data from a cohort of the Spanish general population interviewed at three time-points over a 7-year period. We included 404 individuals aged 50+ suffering from MDD in the baseline assessment. A 12-month major depressive episode was assessed with the Composite International Diagnostic Interview (CIDI) at each interview. The University of California, Los Angeles Loneliness Scale was used to measure loneliness, whereas social support was assessed through the Oslo Social Support Scale. We tested cross-lagged and autoregressive longitudinal associations using structural equation modeling. RESULTS: We identified two significant longitudinal mediation patterns: lower social support predicted higher subsequent levels of loneliness (Coef. = -0.16; p < .05), which in turn predicted an increase in MDD recurrence (Coef. = 0.05; p < .05). CONCLUSIONS: Interventions focused on promoting social support among older adults suffering from MDD may decrease feelings of loneliness and prevent recurrent episodes of MDD.
Published: 2022

13. Cohort Profile: The Spanish Longitudinal Study on Ageing and Health (Edad Con Salud)

Author: Lara E, Maria Miret, Olaya B, Caballero FF, Morillo D, Moneta MV, Haro JM, and Ayuso-Mateos JL
Published: 2022

14. The Structural and Intercultural Competence for Epidemiological Studies (SICES) guidelines: a 22-item checklist

Author: Martinez-Hernaez A, Bekele D, Sabariego C, Rodríguez-Laso Á, Vorstenbosch Ellen, Rico-Uribe LA, Ayuso-Mateos JL, Sánchez-Niubó A, Rodríguez-Mañas L, and Haro JM
Subjects: public health, other study design, epidemiology, other diagnostic or tool, review
Abstract: Structural and intercultural competence approaches have been widely applied to fields such as medical training, healthcare practice, healthcare policies and health promotion. Nevertheless, their systematic implementation in epidemiological research is absent. Based on a scoping review and a qualitative analysis, in this article we propose a checklist to assess cultural and structural competence in epidemiological research: the Structural and Intercultural Competence for Epidemiological Studies guidelines. These guidelines are organised as a checklist of 22 items and consider four dimensions of competence (awareness and reflexivity, cultural and structural validation, cultural and structural sensitivity, and cultural and structural representativeness), which are applied to the different stages of epidemiological research: (1) research team building and research questions; (2) study design, participant recruitment, data collection and data analysis; and (3) dissemination. These are the first guidelines addressing structural and cultural competence in epidemiological inquiry.
Published: 2021

15. Mediators of the socioeconomic status and life satisfaction relationship in older adults: a multi-country structural equation modeling approach

Author: Moreno-Agostino D, de la Fuente J, Leonardi M, Koskinen S, Tobiasz-Adamczyk B, Sánchez-Niubó A, Chatterji S, Haro JM, Ayuso-Mateos JL, and Maria Miret
Subjects: subjective social position, evaluative wellbeing, Subjective wellbeing, psychological wellbeing
Abstract: OBJECTIVES: Socioeconomic status (SES) relates to life satisfaction in old age, although the underlying mechanisms remain unclear. Health and subjective social status have shown to be related to both SES and life satisfaction. This study aims to test the mediating role of health and subjective social status in old age, and to analyze if these potential mediations vary among three European countries with different socioeconomic characteristics and welfare regimes. METHOD: The sample comprised 7,272 participants aged 50+ from COURAGE in Europe study, a household survey carried out in 2011-2012 on nationally representative samples from Finland, Poland, and Spain. A Multiple Indicators, Multiple Causes approach based on multi-group Structural Equation Modeling was implemented to test mediating effects. RESULTS: The structural invariance model showed an adequate fit (CFI = 0.971, RMSEA = 0.061). Health and subjective social status invariantly mediated the relationship between SES and life satisfaction across countries with different socioeconomic characteristics and welfare regimes. SES direct effects explained 0.83-0.85% of life satisfaction variance, whilst indirect effects explained 2.29-2.36% of life satisfaction variance via health, 3.30-3.42% via subjective social status, and 0.06% via both mediating variables. CONCLUSION: Policies aimed at increasing the SES of the older adults may entail multiple benefits, resulting in better subjective social status, health, and life satisfaction outcomes, thus fostering healthy aging of the population.
Published: 2021

16. Is there a combined effect of depression and cognitive reserve on cognitive function? Findings from a population-based study

Author: Lara E, Martín-María N, Maria Miret, Olaya B, Haro JM, and Ayuso-Mateos JL
Subjects: cognition, population-based study, depression, Cognitive reserve
Abstract: OBJECTIVE: To analyse the combined effect of depression and cognitive reserve (CR) on cognition over a three-year follow-up period; and to explore this relationship specifically in individuals aged 65+ years. DESIGN: Data from the 'Edad con Salud' project were analysed (n = 1,144; 50+ years). MAIN OUTCOME MEASURES: The Composite International Diagnostic Interview was used to evaluate depression. CR was assessed with the Cognitive Reserve Questionnaire. Episodic memory was assessed with the word list memory and recall. Verbal fluency was measured through the animal naming task. Random coefficient regression analyses were performed. RESULTS: Depression was associated with lower scores in episodic memory, whereas increased levels of CR were related with higher scores across all the cognitive tests. Among older-aged individuals, cognition decreased at lower levels of CR regardless of depression, while participants with depression exhibited decreased values in both measures of memory at higher levels of CR. CONCLUSION: Depression and CR were related with cognitive performance. Among older individuals, those with low levels of CR may constitute a vulnerable group with poor cognitive prognosis, whilst a harmful effect of depression on memory performance was observed among individuals with greater CR. Further evidence needs to be gathered to understand these associations.
Published: 2021

17. Effects of transient and chronic loneliness on major depression in older adults: A longitudinal study

Author: Martín-María N, Caballero FF, Lara E, Joan Domènech Abella, Haro JM, Olaya B, Ayuso-Mateos JL, and Maria Miret
Subjects: types of loneliness, mood disorder, observational study, subjective social isolation
Abstract: OBJECTIVES: The number of older adults is rapidly rising globally. Loneliness is a common problem that can deteriorate health. The aims of this work were to identify different types of loneliness (transient and chronic) and to assess their association with depression over time. METHODS: A nationally representative sample from the Spanish population comprising 1190 individuals aged 50+ years was interviewed on three evaluations over a 7-year period. The UCLA Loneliness Scale was used to measure loneliness. While chronic loneliness was defined as the presence of loneliness across all three waves, transient loneliness expressed the presence of loneliness in one wave only. A 12-month major depressive episode was assessed at each interview. After confirming the cross-sectional relationship, a multilevel mixed-effects model was used to examine the association between loneliness and depression. RESULTS: Almost a quarter of individuals felt lonely and one out of 10 presented depression at baseline. Of the sample, 22.78% showed transient loneliness, while 6.72% presented the chronic type. People experiencing chronic loneliness were at a higher risk of presenting major depression (OR = 6.11; 95% CI = 2.62, 14.22) than those presenting transient loneliness (OR = 2.22; 95% CI = 1.19, 4.14). This association varied over time and was stronger at the first follow-up than at the second one. CONCLUSIONS: Focusing on loneliness prevention could reduce the risk of depression. Chronic loneliness is a public health problem that should be addressed through the full participation of the political, social, and medical sectors.
Published: 2021

18. Metabolic dysregulation in older adults with depression and loneliness: The ATHLOS study

Author: de la Torre-Luque A, Lara E, de la Fuente J, Rico-Uribe LA, Caballero FF, Lopez-Garcia P, Sánchez-Niubó A, Bobak M, Koskinen S, Haro JM, and Ayuso-Mateos JL
Subjects: Late-life depression, Metabolic dysregulation, ATHLOS project, Loneliness, Multimorbidity
Abstract: This study aimed to examine how loneliness contributes to metabolic dysregulation among older adults with depression and determine the relative contribution of loneliness to the development of chronic diseases in late adulthood. Harmonised data from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project were used. Concretely, the sample comprised 6195 participants (53.95% women; M = 61.30 years, SD = 7.11) from three European cohorts. Three groups were considered: control group (CG); depressive symptom episode group (DEP); and a group with depression and loneliness (DEP + LONE). A metabolic score was estimated using anthropometric and blood indicators, by means of multi-indicator multi-causes (MIMIC) modelling and after controlling for sociodemographic and health-related covariates. Group-comparison was based on measurement-invariance procedures. Multimorbidity development was predicted at follow-up considering the study group and relevant covariates. All the analyses were sex-specific. As a result, measurement invariance revealed the influence of group ( CFI = -0.017 for male participants and CFI = -0.009 for female ones) on metabolic scores in both sexes. Metabolic scores were significantly lower (i.e., they had more metabolic risk) in DEP + LONE women in comparison to women from the other groups. DEP men showed the lowest metabolic scores but those from the DEP + LONE group showed meaningfully lower scores than CG men (d = 1.35). In terms of multimorbidity prediction, DEP + LONE group membership significantly predicted the outcome in both sexes; DEP group membership significantly predicted multimorbidity at follow-up in women. In summary, these results highlight the relevant contribution of loneliness in depression-related metabolic dysregulation in the short- (concurrent metabolic risk) and long-term (chronic condition development). Moreover, sex-specific mechanisms seem to be involved in metabolic alterations of depressed people showing loneliness feelings. This study calls for action to reduce the impact of loneliness in old age and to promote healthy ageing.
Published: 2021

19. Episodic Memory and Verbal Fluency Tasks: Normative Data from Nine Nationally Representative Samples

Author: Lara E, Maria Miret, Sánchez-Niubó A, Haro JM, Koskinen S, Leonardi M, Tobiasz-Adamczyk B, Chatterji S, and Ayuso-Mateos JL
Subjects: Cognition, Population-based study, Assessment, Neuropsychology, Elderly/Aging, Norms/Normative studies
Abstract: OBJECTIVE: This study aims to generate country-specific norms for two episodic memory tasks and a verbal fluency test among middle-aged and older adults using nationally representative data from nine low-, middle-, and high-income countries. METHOD: Data from nine countries in Africa, Asia, Europe, and Latin America were analyzed (n = 42,116; aged 50 years or older). Episodic memory was assessed with the word list memory (three trials of immediate recall) and word list recall (delayed recall). Verbal fluency was measured through the animal naming task. Multiple linear regression models with country-specific adjustments for gender, age, education, and residential area were carried out. RESULTS: Both age and education showed high influence on test performance (i.e. lower cognitive performance with increasing age and decreasing years of education, respectively), while the effect of sex and residential area on cognitive function was neither homogeneous across countries nor across cognitive tasks. CONCLUSIONS: Our study provided sex-, age-, education-, and residential area-specific regression-based norms that were obtained from one of the largest normative study worldwide on verbal recall and fluency tests to date. Findings derived from this study will be especially useful for clinicians and researchers based at countries where cognitive norms are limited.
Published: 2021

20. Determinants of verbal fluency trajectories among older adults from the English Longitudinal Study of Aging

Author: Gkotzamanis V, Koliopanos G, Sánchez-Niubó A, Olaya B, Caballero FF, Ayuso-Mateos JL, Chatterji S, Haro JM, and Panagiotakos DB
Abstract: BACKGROUND: Prevalence of dementia and cognitive impairment increase creating the need for identifying modifiable risk factors to reduce their burden. The aim of this study was to identify latent groups following similar trajectories in cognitive performance assessed with the verbal fluency test, as well as their determinants. METHODS: Data from English Longitudinal Study of Aging (ELSA) were studied. Latent groups of similar course through a 6-year period in the outcome variable (verbal fluency) were investigated, along with their determinants, using Group Based Trajectory Modeling (GBTM). RESULTS: Four latent groups of verbal fluency trajectories were revealed. Education was the strongest predictor for a favorable trajectory, while cardiovascular disease and depression symptoms were associated with lower within each trajectory. CONCLUSION: Cardiovascular diseases and depressive symptoms are associated with a worse course of verbal fluency through aging, implying that they might serve as targets for interventions to prevent cognitive decline in the aging population. Contrarily, higher level of education is associated with a more favorable course through aging.
Published: 2021

21. Late-life disability trajectories in Yoruba Nigerians and the Spanish population: a state space model in continuous time

Author: Ojagbemi A, Estrada E, de la Torre-Luque A, Moreno-Agostino D, Lara E, Caballero FF, Bello T, Olaya B, Haro JM, Gureje O, and Ayuso-Mateos JL
Subjects: Functional disability, longitudinal cohort, compression of disability, ADL limitations, low- and middle-income countries
Abstract: OBJECTIVES: We compared the trajectory of activities of daily living (ADL) in a nationally representative sample of older Nigerians with their Spanish peers and identified factors to explain country-specific growth models. METHODS: Data from two household multistage probability samples were used, comprising older adults from Spain (n = 2,011) and Nigeria (n = 1,704). All participants underwent assessment for ADL. Risk factors including sex, household income, urbanicity, years of education, depression, alcohol consumption and smoking were assessed using validated methods. State-space model in continuous time (SSM-CT) methods were used for trajectory comparison. RESULTS: Compared with Nigerians (µ(ADL80)=0.44, SE = 0.015, p < 0.001), Spanish older adults had higher disability scores (µ(ADL80)=1.23, SE = 0.021, p < 0.001). In SSM-CT models, the rate of increase in disability was faster in Nigerians (Nigeria: ß = 0.061, p
Published: 2021

22. To be happy and behave in a healthier way. A longitudinal study about gender differences in the older population

Author: Martín-María N, Lara E, Cabello M, Olaya B, Haro JM, Maria Miret, and Ayuso-Mateos JL
Abstract: INTRODUCTION: Subjective well-being plays a key role in health. The objectives of this study are to analyse the longitudinal associations between subjective well-being dimensions and healthy behaviours, and to examine gender differences. METHOD: A representative sample of 1,190 Spanish non-institutionalised adults aged 50+ were interviewed over a 6-year follow-up period. The Cantril scale was used to measure evaluative well-being. The Day Reconstruction Method measured experienced well-being. The Global Physical Activity Questionnaire was used, whereas fruit and vegetables, tobacco and alcohol consumption, and sleep quality were self-reported. The Generalised Estimating Equation was calculated. RESULTS: Women show significantly worse subjective well-being than men longitudinally. Higher scores in life satisfaction and positive affect were significantly related to a higher level of physical activity and better-quality sleep for both women and men. Associations between a higher life satisfaction and an adequate intake of fruits and vegetables and being a non-smoker was only found in women (OR = 1.05; 95% IC = 1.00, 1.10 and OR = 1.16; 95% IC = 1.09, 1.23, respectively). CONCLUSION: Subjective well-being levels and frequencies in healthy behaviours are different in women and men. Subjective well-being interventions should take into account these differences in the frequency of healthy-unhealthy behaviours.
Published: 2021

23. From childhood financial hardship to late-life depression: socioeconomic pathways

Author: Joan Domènech Abella, Mundó J, Maria Miret, Ayuso-Mateos JL, Sánchez-Niubó A, Abduljabbar AS, Haro JM, and Olaya B
Subjects: Childhood SES, Spain, depression, intergenerational social mobility
Abstract: OBJECTIVE: Childhood financial hardship is associated with depression throughout the life course, including older adulthood. However, it is still unclear the extent to which occupation, education level and household income are mediators of this association. We aimed to examine the association between childhood financial hardship and late-life depression, and potential socioeconomic mediators using community-based data. METHODS: A nationally representative sample of 3623 non-institutionalized older Spanish adults aged 50+ was used. The associations between childhood financial hardship and depression, socioeconomic mediator variables and confounding variables such as chronic physical conditions, number of close people, and loneliness, were assessed through logistic regression models. Mediation analyses of socioeconomic variables were carried out. RESULTS: Older Spanish adults who experienced a poor childhood financial situation were nine times more likely to obtain a lower level of education than those with a good childhood financial situation, and about three times more likely to suffer from depression. Participants' education level mediated about 35-40% of the association between childhood financial hardship and late-life depression whereas we found no significant mediation effect of household income and occupation skill. CONCLUSION: Improving access to the educational system during the life course might result in a reduction in the prevalence of depression in the general population of older adults and particularly among individuals with low socioeconomic status.
Published: 2021

24. The role of ageing in the wish to be dead: disentangling age, period and cohort effects in suicide ideation in European population

Author: Cabello M, Rico-Uribe LA, Martinez-Ávila JC, Sánchez-Niubó A, Caballero FF, Borges G, Mellor-Marsá B, Haro JM, Prina M, Koskinen S, and Ayuso-Mateos JL
Subjects: Europe, period, suicide ideation, Cohort
Abstract: AIMS: To investigate potential age, period and birth cohort effects in the prevalence of suicide ideation in European ageing population. METHODS: A total of 50 782 community-dwelling adults (aged + 50) from 20 different European countries were collected in the Survey Health Ageing and Retirement study. A multilevel logistic regression model of repeated measures was modelled to assess the effects of age and other variables, including the variability of observations over three levels: birth cohort groups, time period assessment and individual differences. RESULTS: The larger effect of variability was attributed to individual-level factors (57.8%). Youngest-old people (65-79 years) showed lower suicide ideation than middle-aged people (50-64 years). No significative differences were found for suicide ideation between middle-aged people and oldest-old (80 + years). Only 0.85% and 0.13% of the total variability of suicide ideation accounted for birth cohort and period effects, respectively. Cohorts born between 1941 and 1944 possessed the lowest estimates of suicide ideation. Conversely, suicide ideation started to rise with post-War generations and reached a significant level for people born from 1953-1957 to 1961-1964. Regarding the time period, participants assessed in 2006-2007 showed a lower likelihood of suicide ideation. The rest of the cohorts and period groups did not show any significant effect on the prevalence of suicide ideation. CONCLUSIONS: Our results suggest that age and suicide ideation relationship is not linear in middle and older age. The European Baby boomers born from 50s to mid-60s might report higher suicide ideation than their ancestors. This scenario would imply a greater need for mental healthcare services for older people in the future.
Published: 2021

25. Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Author: Nichols, E, Abd-Allah, F, Abdoli, A, Abualhasan, A, Abu-Gharbieh, E, Afshin, A, Akinyemi, RO, Alanezi, FM, Alipour, V, Almasi-Hashiani, A, Arabloo, J, Ashraf-Ganjouei, A, Ayano, G, Ayuso-Mateos, JL, Baig, AA, Banach, M, Barboza, MA, Barker-Collo, SL, Baune, BT, Bhagavathula, AS, Bhattacharyya, K, Bijani, A, Biswas, A, Boloor, A, Brayne, C, Brenner, H, Burkart, K, Nagaraja, S Burugina, Carvalho, F, Castro-de-Araujo, LFS, Catalá-López, F, Cerin, E, Cherbuin, N, Chu, DT, Dai, X, de Sá-Junior, AR, Djalalinia, S, Douiri, A, Edvardsson, David, El-Jaafary, SI, Eskandarieh, S, Faro, A, Farzadfar, F, Feigin, VL, Fereshtehnejad, SM, Fernandes, E, Ferrara, P, Filip, I, Fischer, F, Gaidhane, S, Galluzzo, L, Gebremeskel, GG, Ghashghaee, A, Gialluisi, A, Gnedovskaya, EV, Golechha, M, Gupta, R, Hachinski, V, Haider, MR, Haile, TG, Hamiduzzaman, M, Hankey, GJ, Hay, SI, Heidari, G, Heidari-Soureshjani, R, Ho, HC, Househ, M, Hwang, BF, Iacoviello, L, Ilesanmi, OS, Ilic, IM, Ilic, MD, Irvani, SSN, Iwagami, M, Iyamu, IO, Jha, RP, Kalani, R, Karch, A, Kasa, AS, Khader, YS, Khan, EA, Khatib, MN, Kim, YJ, Kisa, S, Kisa, A, Kivimäki, M, Koyanagi, A, Landires, I, Lasrado, S, Li, B, Lim, SS, Liu, X, Kunjathur, S Madhava, Majeed, A, Malik, P, Mehndiratta, MM, Menezes, RG, Mohammad, Y, and Mohammed, S
Subjects: Uncategorized
Abstract: Note: Not all authors listed; please see article (last page) for full list of Contributors).Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys.
Published: 2021
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26. The Structural and Intercultural Competence for Epidemiological Studies (SICES) guidelines: A 22-item checklist

Author: Universitat Rovira i Virgili, Martinez-Hernaez A; Bekele D; Sabariego C; Rodríguez-Laso Á; Vorstenbosch E; Rico-Uribe LA; Ayuso-Mateos JL; Sánchez-Niubò A; Rodríguez-Mañas L; Haro JM, Universitat Rovira i Virgili, and Martinez-Hernaez A; Bekele D; Sabariego C; Rodríguez-Laso Á; Vorstenbosch E; Rico-Uribe LA; Ayuso-Mateos JL; Sánchez-Niubò A; Rodríguez-Mañas L; Haro JM
Abstract: Structural and intercultural competence approaches have been widely applied to fields such as medical training, healthcare practice, healthcare policies and health promotion. Nevertheless, their systematic implementation in epidemiological research is absent. Based on a scoping review and a qualitative analysis, in this article we propose a checklist to assess cultural and structural competence in epidemiological research: the Structural and Intercultural Competence for Epidemiological Studies guidelines. These guidelines are organised as a checklist of 22 items and consider four dimensions of competence (awareness and reflexivity, cultural and structural validation, cultural and structural sensitivity, and cultural and structural representativeness), which are applied to the different stages of epidemiological research: (1) research team building and research questions; (2) study design, participant recruitment, data collection and data analysis; and (3) dissemination. These are the first guidelines addressing structural and cultural competence in epidemiological inquiry.
Published: 2021

27. Differential impact of transient and chronic loneliness on health status. A longitudinal study

Author: Martín-María N, Caballero FF, Maria Miret, Tyrovolas S, Haro JM, Ayuso-Mateos JL, and Chatterji S
Subjects: chronic loneliness, longitudinal study, Transient loneliness, health status
Abstract: Objective: Loneliness is associated with worse health status outcomes. Yet, the present study is one of the first to identify how patterns of loneliness (transient and chronic) are associated with health over time. Design: A total of 2,390 individuals were interviewed in 2011-2012 and 2014-2015 in a follow-up study conducted over a nationally representative sample of Spain. After confirming a longitudinal relationship between loneliness and health status, a growth curve mixture modeling was used to examine health trajectories. Main outcome measures: The three-item UCLA Loneliness Scale was used to assess loneliness. Health status was measured with self-reported questions regarding ten domains (vision, mobility, and self-care, among others), and seven measured tests (including grip strength, walking speed and immediate and delayed verbal recall). Results: A quarter of participants were lonely at baseline. Both the group of transient and chronic loneliness showed a negative significant relationship with health status at follow-up, (ß = -0.063 and ß = -0.075 respectively, p < 0.001). Nevertheless, the health status did not change across time in any group. Conclusion: People experiencing chronic loneliness had the worst health status. Different patterns of loneliness could benefit from the appropriate interventions.
Published: 2020

28. Cross-national prevalence and factors associated with suicide ideation and attempts in older and young-and-middle age people

Author: Cabello M, Maria Miret, Ayuso-Mateos JL, Caballero FF, Chatterji S, Tobiasz-Adamczyk B, Haro JM, Koskinen S, Leonardi M, and Borges G
Subjects: suicide, Epidemiology, cross-national study, prevalence
Abstract: Objectives: To report prevalence estimates of 12-month suicide ideation and attempts in young-and-middle age adults and older people, as well as their respective associated factors.Methods: A total of 52,150 community-dwelling adults who completed the adapted version of the Composite International Diagnostic Interview-Depression Module were included from SAGE and COURAGE in Europe studies. The presence of 12-month suicide ideation and attempts was measured among the participants who screened positively in the Depression Module. Global and national prevalence estimates of 12-month suicide ideation and attempts were calculated according to the total sample. Logistic regression analyses were conducted to separately determine factors associated with suicidal ideation and with suicide attempts in young-and-middle age adults and older adults.Results: Higher estimates of 12-month suicidal ideation were found for high-income countries and people aged 65 years and older. Higher negative affect, higher disability, and presence of food insecurity were associated with 12-month suicidal ideation and suicide attempts for young-and-middle-adults and older adults. Higher isolation, being female, and greater number of chronic health conditions were also related to 12-month suicidal ideation in both age groups. Younger age was associated with 12-month suicidal ideation for older people, and with suicide attempts in the young-and-middle age group. Finally, higher income was related to lower rates of 12-month suicidal ideation for the young-and-middle age group.Conclusions: Older people are at increased risk of suicidal ideation globally and of suicide attempts in some countries. There were common and different factors related to suicide in adults and older adults.
Published: 2020

29. Cognitive function associated with different diagnoses of anxiety disorders over the lifespan: Results from a Spanish representative sample

Author: Gayete S, Giné A, Maria Miret, Ayuso-Mateos JL, Haro JM, and Olaya B
Subjects: middle-aged adults, early adulthood, panic disorder, cognitive performance, generalized anxiety disorder, older adults
Abstract: BACKGROUND: Previous research suggests an association between anxiety disorders and worse cognitive function. However, this association may vary depending on the type of disorder and age. We analysed the association of panic attack, 12-month and lifetime panic disorder (PD), and generalized anxiety disorder (GAD), with cognitive function in a representative sample of Spanish adults, and compared three age groups (18-49, 50-64, and 65+). METHODS: Some 4,582 participants were interviewed with an adapted CIDI interview. Unadjusted and adjusted linear regression models were calculated by age group, using T scores of verbal fluency and episodic memory as the outcomes. RESULTS: In young adults, 12-month GAD was associated with significantly lower scores of memory performance and verbal fluency, and 12-month PD with worse verbal fluency. In middle-aged participants, lifetime panic attack was related to better performance in verbal fluency, whereas having a diagnosis of lifetime PD was associated with lower scores. However, only participants aged 18-49 with 12-month GAD showed lower memory and verbal fluency, at almost one standard deviation below participants without 12-month GAD. LIMITATIONS: Low prevalence rates of anxiety disorder could have led to biased results. CONCLUSIONS: In young adults, a concurrent GAD might be particularly associated with memory and verbal fluency deficits, whereas only verbal fluency is affected in middle-aged adults with a history of PD, although this association is small. In older adults, anxiety disorders are not clearly associated with worse cognition, probably because in this age group other confounder variables might be attenuating this link. Overall, our findings suggest that cognitive interventions for anxiety disorders may be relevant, especially for young and middle-aged adults.
Published: 2020

30. Cross-cultural comparison of symptom networks in late-life major depressive disorder: Yoruba Africans and the Spanish Population

Author: de la Torre-Luque A, Ojagbemi A, Caballero FF, Lara E, Moreno-Agostino D, Bello T, Olaya B, Haro JM, Gureje O, and Ayuso-Mateos JL
Subjects: ate-life major depression, centrality measures, clinical intervention targets, cross-cultural study, symptom network analysis
Abstract: The concept of European psychologization of depression versus somatisation in non-European populations has been the basis of several studies of cultural psychopathology in the general population. Little is currently known about cross-cultural differences and similarities in late-life depression symptom reporting. We cross-culturally compared symptom reporting in the context of Major Depressive Disorder (MDD) among community-dwelling older adults from Spain and Nigeria.
Published: 2020

31. Are retired people higher in experiential wellbeing than working older adults? A time use approach

Author: Moreno-Agostino D, Stone AA, Schneider S, Koskinen S, Leonardi M, Naidoo N, Tobiasz-Adamczyk B, Haro JM, Maria Miret, Kowal P, Ayuso-Mateos JL, and Chatterji S
Abstract: Little is known about how retirement and the time use redistribution that comes with it relate to experiential wellbeing, especially in low- and middle-income countries (LAMICs). This study aims to determine whether there are differences in experiential wellbeing between retired and working older adults; whether time use accounts for a portion of these differences; and whether these potential relationships differ across LAMICs and high-income countries. We used data from 2 multicountry studies conducted in countries at different levels of economic development: SAGE (China, Ghana, India, Mexico, and South Africa) and COURAGE in Europe (Finland, Poland, and Spain), focusing on participants aged 50+ (N = 21,000). Retirement was significantly associated with higher experiential wellbeing in both surveys, and time use accounted for more than 40% of the total effect. Retirees were higher in experiential wellbeing than working older adults, and differences in how individuals spend their day accounted for part of this relationship. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Published: 2020

32. Relationship between subjective well-being and healthy lifestyle behaviours in older adults: a longitudinal study

Author: Martín-María N, Caballero FF, Moreno-Agostino D, Olaya B, Haro JM, Ayuso-Mateos JL, and Maria Miret
Subjects: healthy lifestyle behaviours, life satisfaction, Positive affect, negative affect
Abstract: Objectives: People who report better subjective well-being tend to be healthier in their daily behaviours. The objective of this study is to assess whether different components of subjective well-being are prospectively associated with different healthy lifestyle behaviours and to assess whether these associations differ by age.Method: A total of 1,892 participants aged 50+ living in Spain were interviewed in 2011-12 and 2014-15. Life satisfaction was measured with the Cantril Self-Anchoring Striving Scale. Positive and negative affect were assessed using the Day Reconstruction Method. Physical activity was assessed with the Global Physical Activity Questionnaire version 2. The remaining healthy lifestyle behaviours were self-reported. Generalised Estimating Equations (GEE) models were run.Results: Not having a heavy episodic alcohol drinking was the healthy lifestyle behaviour most fulfilled (97.97%), whereas the intake of five or more fruits and vegetables was the least followed (33.12%). GEE models conducted over the 50-64 and the 65+ age groups showed that a higher life satisfaction was significantly related to a higher physical activity in both groups. Relationships between a higher negative affect and presenting a lower level of physical activity, and a higher positive affect and following the right consumption of fruits and vegetables and being a non-daily smoker, were only found in the older group.Conclusion: The relationship between subjective well-being and healthy lifestyle behaviours was found fundamentally in those aged 65+ years. Interventions focused on incrementing subjective well-being would have an impact on keeping a healthy lifestyle and, therefore, on reducing morbidity and mortality.
Published: 2020

33. The relationship between all-cause mortality and depression in different gender and age groups of the Spanish population

Author: Cabello M, Borges G, Lara E, Olaya B, Martín-Maria N, Moreno-Agostino D, Maria Miret, Caballero FF, Haro JM, and Ayuso-Mateos JL
Subjects: Age, All-cause, Depression, Gender, Mortality
Abstract: Literature has shown that the effect of depression on all-cause mortality is stronger in men. However, it is less clear whether depression affects older and younger people equally. The present study is aimed to analyze whether depression is associated to all-cause mortality in different age and gender groups.
Published: 2020

34. Development of a Combined Sensory-Cognitive Measure Based on the Common Cause Hypothesis: Heterogeneous Trajectories and Associated Risk Factors

Author: Fuente J, Moreno-Agostino D, Torre-Luque A, Prina AM, Haro JM, Caballero FF, and Ayuso-Mateos JL
Subjects: Sensory functioning, Cognitive functioning, Latent classes, Structural equation modeling
Abstract: There is a link between sensory and cognitive functioning across old age. However, there are no integrative measures for assessing common determinants of sensory-cognitive functioning. This study aims to develop a combined measure of sensory-cognitive functioning, and to identify heterogeneous trajectories and associated risk factors.
Published: 2020

35. Ageing trajectories of health-longitudinal opportunities and synergies (ATHLOS) Healthy Ageing Scale in adults from 16 international cohorts representing 38 countries worldwide

Author: Critselis E, Panaretos D, Sánchez-Niubó A, Giné-Vázquez I, Ayuso-Mateos JL, Caballero FF, de la Fuente J, Haro JM, and Panagiotakos D
Subjects: Ageing, research methods, screening, public health, epidemiology of ageing
Abstract: BACKGROUND: Uniform international measurement tools for assessing healthy ageing are currently lacking. OBJECTIVES: The study assessed the novel comprehensive global Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) Healthy Ageing Scale, using an Item Response Theory approach, for evaluating healthy ageing across populations. DESIGN: Pooled analysis of 16 international longitudinal studies. SETTING: 38 countries in five continents. SUBJECTS: International cohort (n=355 314), including 44.4% (n=153 597) males, aged (mean±SD) 61.7±11.5 years old. METHODS: The ATHLOS Healthy Ageing Scale (including 41 items related to intrinsic capacity and functional ability) was evaluated in a pooled international cohort (n=355 314 from 16 studies) according to gender, country of residence and age group. It was also assessed in a subset of eight cohorts with =3 waves of follow-up assessment. The independent samples t-test and Mann-Whitney test were applied for comparing normally and skewed continuous variables between groups, respectively. RESULTS: The ATHLOS Scale (range: 12.49-68.84) had a mean (±SD) value of 50.2±10.0, with males and individuals >65 years old exhibiting higher and lower mean scores, respectively. Highest mean scores were detected in Switzerland, Japan and Denmark, while lowest in Ghana, India and Russia. When the ATHLOS Scale was evaluated in a subset of cohorts with =3 study waves, mean scores were significantly higher than those of the baseline cohort (mean scores in =3 study waves vs baseline: 51.6±9.4 vs 50.2±10.0; p
Published: 2020

36. Predictors of pain in general ageing populations: results from a multi-country analysis based on ATHLOS harmonized database

Author: Raggi A, Leonardi M, Mellor-Marsá B, Moneta MV, Sánchez-Niubó A, Tyrovolas S, Giné-Vázquez I, Haro JM, Chatterji S, Bobak M, Ayuso-Mateos JL, Arndt H, Hossin MZ, Bickenbach J, Koskinen S, Tobiasz-Adamczyk B, Panagiotakos D, and Corso B
Published: 2020

37. Functioning profiles in a nationally representative cohort of Spanish older adults: A latent class study

Author: de la Torre-Luque A, Cabello M, Lara E, de la Fuente J, Maria Miret, Sánchez-Niubó A, Haro JM, and Ayuso-Mateos JL
Subjects: Functioning profile, health service utilisation, latent class analysis, mortality risk, quality of life, well-being
Abstract: Ageing well involves individuals continuing participating in personal, social and civic affairs even in older age. From this standpoint, limitations in individual's functioning (beyond the mere absence of disease) may drastically impact on how well people becoming older. This study aimed to identify functional status profiles in a nationally representative sample of older adults, using latent class analysis methods. Moreover, it intended to study the how identified classes would be related to health-related outcomes later in life, as a way to provide some evidence on predictive validity. Data from a nationally representative sample of Spanish older adults (N = 2,118; 56.18% women; M = 71.50 years, SD = 7.76), were used. Profiles were identified according to a large set of functioning indicators from multiple domains using latent class analysis. Outcomes were studied over a 3-year follow-up, considering both the individual (quality of life, well-being and mortality) and institutional level (health service utilisation). As a result, seven profiles were identified: normative profile (showed by most participants), limited cognitive functioning class, limited global functioning class, limited mental and mobility functioning class, poor self-reported health class, limited sensory functioning class and limited objective functioning class. All the profiles with limitations across domains showed poor outcomes. Multidimensional limitations were related to the worst outcomes, especially when psychosomatic complaints and high feelings of loneliness were reported. To sum up, latent class analysis constitutes a suitable alternative to study population heterogeneity, providing relevant evidence to help making decision in public and community health.
Published: 2020

38. Loneliness and depression among older European adults: The role of perceived neighborhood built environment

Author: Joan Domènech Abella, Mundó J, Leonardi M, Chatterji S, Tobiasz-Adamczyk B, Koskinen S, Ayuso-Mateos JL, Haro JM, and Olaya B
Subjects: mental disorders, Built environment, Depression, Loneliness, Older adults
Abstract: Depression and loneliness act in a synergistic way among older adults. We tested two indicators of the perceived neighborhood built environment (BE) as moderators of the association between these conditions in older European adults. Positive perceptions of neighborhood BE were related to lower levels of loneliness but not to major depressive disorder (MDD). Reporting low BE usability was significantly related to a higher likelihood of feeling lonely except for those suffering from MDD, whereas reporting low BE walkability was significantly related with a high likelihood of loneliness particularly among those with MDD. Therefore, improving neighborhood BE and, specifically, its walkability, might result in a reduction in the prevalence of loneliness.
Published: 2020

39. Pain rates in general population for the period 1991-2015 and 10-years prediction: results from a multi-continent age-period-cohort analysis

Author: Guido D, Leonardi M, Mellor-Marsá B, Moneta MV, Sánchez-Niubó A, Tyrovolas S, Giné-Vázquez I, Haro JM, Chatterji S, Bobak M, Ayuso-Mateos JL, Arndt H, Koupil I, Bickenbach J, Koskinen S, Tobiasz-Adamczyk B, Panagiotakos D, and Raggi A
Published: 2020

40. Exploring the effect of loneliness on all-cause mortality: Are there differences between older adults and younger and middle-aged adults?

Author: Lara E, Moreno-Agostino D, Martín-María N, Maria Miret, Rico-Uribe LA, Olaya B, Cabello M, Haro JM, and Ayuso-Mateos JL
Subjects: Age differences, All-cause mortality, Loneliness, Population-based study, Spain
Abstract: This study aims to investigate the association between loneliness and all-cause mortality over a six-year follow-up period using the overall sample and by age groups (18-59 years and 60+ years).
Published: 2020

41. Delirium in hospitalized COVID-19 patients: A case series

Author: Delgado-Parada E, Alonso-Sánchez M, and Ayuso-Mateos Jl
Subjects: 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), SARS-CoV-2, business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19, Delirium, Length of Stay, Virology, Article, Psychiatry and Mental health, Humans, Medicine, medicine.symptom, business, Biological Psychiatry
Published: 2021

42. Are loneliness and social isolation associated with cognitive decline?

Author: Lara E, Caballero FF, Rico-Uribe L, Olaya B, Haro JM, Ayuso-Mateos JL, and Maria Miret
Subjects: social isolation, population-based study, cognitive function, older adults, loneliness
Abstract: OBJECTIVE: This study aimed to examine the association of loneliness and social isolation on cognition over a 3-year follow-up period in middle- and older-aged adults. METHODS: Data from a Spanish nationally representative sample were analyzed (n = 1691; aged 50 years or older). Loneliness, social isolation, and cognition (immediate recall, delayed recall, verbal fluency, forward digit span, backward digit span, and a composite cognitive score) were assessed both at baseline and at follow-up. Adjusted generalized estimating equations models were performed. RESULTS: Loneliness was significantly associated with lower scores in the composite cognitive score, immediate and delayed recall, verbal fluency, and backward digit span (B = -0.14 to B = -3.16; P < .05) and with a more rapid decline from baseline to follow-up in two out of six cognitive tests. Higher social isolation was associated with lower scores in the composite cognitive score, verbal fluency, and forward digit span (B = -0.06 to B = -0.85; P < .05). The effect of loneliness and social isolation on cognition remained significant after the exclusion of individuals with depression. CONCLUSIONS: Both loneliness and social isolation are associated with decreased cognitive function over a 3-year follow-up period. The development of interventions that include the enhancement of social participation and the maintenance of emotionally supportive relationships might contribute to cognitive decline prevention and risk reduction.
Published: 2019

43. CIBERSAM: Ten years of collaborative translational research in mental disorders

Author: Salagre E, Cesar Arango Posada, Artigas F, Ayuso-Mateos JL, Bernardo M, Castro-Fornieles J, Bobes J, Desco M, Fañanás L, González-Pinto A, Haro JM, Leza JC, Mckenna PJ, Meana JJ, Menchón JM, Micó JA, Palomo T, Pazos Á, Pérez V, Saiz-Ruiz J, Sanjuán J, Tabarés-Seisdedos R, Crespo-Facorro B, Casas M, Vilella E, Palao D, Olivares JM, Rodriguez-Jimenez R, and Vieta E
Subjects: Translational Research, Biomedical, International Cooperation, Mental Disorders, Humans, General Medicine, Periodicals as Topic
Published: 2019

44. Course of Depression and Cognitive Decline at 3-Year Follow-Up: The Role of Age of Onset

Author: Olaya B, Moneta MV, Maria Miret, Ayuso-Mateos JL, and Haro JM
Published: 2019

45. The Effect of Exclusive Olive Oil Consumption on Successful Aging: A Combined Analysis of the ATTICA and MEDIS Epidemiological Studies

Author: Foscolou A, Critselis E, Tyrovolas S, Chrysohoou C, Sidossis LS, Naumovski N, Matalas AL, Rallidis L, Polychronopoulos E, Ayuso-Mateos JL, Haro JM, and Panagiotakos D
Subjects: successful aging, dietary fats, olive oil
Abstract: The consumption of dietary fats, which occur naturally in various foods, poses important impacts on health. The aim of this study was to elucidate the association of exclusive use of olive oil for culinary purposes with successful aging in adults aged >50 years old and residing in Greece. Use of olive oil in food preparation and bio-clinical characteristics of the Greek participants enrolled in the ATTICA (n = 1128 adults from Athens metropolitan area) and the MEDiterranean Islands Study (MEDIS) (n = 2221 adults from various Greek islands and Mani) studies, were investigated in relation to successful aging (SA). Participants were divided into the following three categories: (a) no olive oil consumption; (b) combined consumption of olive oil and other dietary fats; and (c) exclusive olive oil consumption. The SA was measured using the previously validated successful aging index (SAI). After adjusting for age, sex, and smoking habits, combined consumption of olive oil and other fats (vs. no olive oil use) was not significantly associated with SAI levels (p = 0.114). However, exclusive olive oil intake (vs. no use of olive oil) was significantly associated with SAI (p = 0.001), particularly among those aged older than 70 years. Therefore, the exclusive consumption of olive oil, as opposed to either combined or no olive oil consumption, beneficially impacts successful aging, particularly among individuals over 70 years of age. Primary public health prevention strategies should seek to encourage the enhanced adoption of such dietary practices in order to promote healthy aging and longevity.
Published: 2019

46. Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA)

Author: Engchuan W, Dimopoulos AC, Tyrovolas S, Caballero FF, Sánchez-Niubó A, Arndt H, Ayuso-Mateos JL, Haro JM, Chatterji S, and Panagiotakos DB
Abstract: BACKGROUND Studies on the effects of sociodemographic factors on health in aging now include the use of statistical models and machine learning. The aim of this study was to evaluate the determinants of health in aging using machine learning methods and to compare the accuracy with traditional methods. MATERIAL AND METHODS The health status of 6,209 adults, age 80 years (n=1,357) were measured using an established health metric (0-100) that incorporated physical function and activities of daily living (ADL). Data from the English Longitudinal Study of Ageing (ELSA) included socio-economic and sociodemographic characteristics and history of falls. Health-trend and personal-fitted variables were generated as predictors of health metrics using three machine learning methods, random forest (RF), deep learning (DL) and the linear model (LM), with calculation of the percentage increase in mean square error (%IncMSE) as a measure of the importance of a given predictive variable, when the variable was removed from the model. RESULTS Health-trend, physical activity, and personal-fitted variables were the main predictors of health, with the%incMSE of 85.76%, 63.40%, and 46.71%, respectively. Age, employment status, alcohol consumption, and household income had the%incMSE of 20.40%, 20.10%, 16.94%, and 13.61%, respectively. Performance of the RF method was similar to the traditional LM (p=0.7), but RF significantly outperformed DL (p=0.006). CONCLUSIONS Machine learning methods can be used to evaluate multidimensional longitudinal health data and may provide accurate results with fewer requirements when compared with traditional statistical modeling.
Published: 2019

47. Fruit and Vegetable Consumption and Potential Moderators Associated with All-Cause Mortality in a Representative Sample of Spanish Older Adults

Author: Olaya B, Moneta MV, Lara E, Maria Miret, Martín-María N, Moreno-Agostino D, Ayuso-Mateos JL, Abduljabbar AS, and Haro JM
Subjects: multimorbidity, fruit and vegetable consumption, interaction, survival, older adults
Abstract: This study sought to determine the association between levels of fruit and vegetable consumption and time to death, and to explore potential moderators. We analyzed a nationally-representative sample of 1699 older adults aged 65+ who were followed up for a period of 6 years. Participants were classified into low (=3 servings day), medium (4), or high (=5) consumption using tertiles. Unadjusted and adjusted cox proportional hazard regression models (by age, gender, cohabiting, education, multimorbidity, smoking, physical activity, alcohol consumption, and obesity) were calculated. The majority of participants (65.7%) did not meet the recommendation of five servings per day. High fruit and vegetable intake increased by 27% the probability of surviving among older adults with two chronic conditions, compared to those who consumed =3 servings per day (HR = 0.38, 95%CI = 0.21-0.69). However, this beneficial effect was not found for people with none, one chronic condition or three or more, indicating that this protective effect might not be sufficient for more severe cases of multimorbidity. Given a common co-occurrence of two non-communicable diseases in the elderly and the low frequency of fruit and vegetable consumption in this population, interventions to promote consuming five or more servings per day could have a significant positive impact on reducing mortality.
Published: 2019

48. Mediterranean diet and wellbeing: evidence from a nationwide survey

Author: Moreno-Agostino D, Caballero FF, Martín-María N, Tyrovolas S, López-García P, Rodríguez-Artalejo F, Haro JM, Ayuso-Mateos JL, and Maria Miret
Subjects: Mediterranean diet, experienced wellbeing, evaluative wellbeing, subjective wellbeing, Day Reconstruction Method
Abstract: OBJECTIVE: Although there is some evidence of the association between specific food groups, such as plant foods, and subjective wellbeing, this is the first study to assess the relationship between adherence to the Mediterranean dietary pattern and subjective wellbeing. DESIGN: Data were collected in 2014-2015, within the Edad con Salud project, a follow-up study of a multistage clustered survey on a representative sample of the population of Spain. The final sample comprised 2397 individuals with ages ranging from 21 to 101 years. MAIN OUTCOME MEASURES: Experienced wellbeing (positive and negative affect) was measured using the Day Reconstruction Method, and evaluative wellbeing was assessed with the Cantril Self-Anchoring Striving Scale. RESULTS: A higher adherence to the Mediterranean diet showed a small but statistically significant inverse relationship with negative affect (ß = -0.076, p=.001), and direct with evaluative wellbeing (ß = 0.053, p=.015), whereas it was not related to positive affect. Several components of the Mediterranean diet were independently associated with wellbeing. CONCLUSION: The results suggest that adherence to a dietary pattern such as the Mediterranean diet, and not only the isolated consumption of its components, is associated with a better subjective wellbeing.
Published: 2019

49. Are younger cohorts in the USA and England ageing better?

Author: de la Fuente J, Caballero FF, Verdes E, Rodríguez-Artalejo F, Cabello M, de la Torre-Luque A, Sánchez-Niubó A, Haro JM, Ayuso-Mateos JL, and Chatterji S
Subjects: cross-cultural comparison, functioning, Health, cohort effect
Abstract: BACKGROUND: Whether worldwide increases in life expectancy are accompanied by a better health status is still a debate. People age differently, and there is a need to disentangle whether healthy-ageing pathways can be shaped by cohort effects. This study aims to analyse trends in health status in two large nationally representative samples of older adults from England and the USA. METHODS: The sample comprised 55 684 participants from the first seven waves of the English Longitudinal Study of Ageing (ELSA), and the first 11 waves of the Health and Retirement Study (HRS). A common latent health score based on Bayesian multilevel item response theory was used. Two Bayesian mixed-effects multilevel models were used to assess cohort effects on health in ELSA and HRS separately, controlling for the effect of household wealth and educational attainment. RESULTS: Similar ageing trends were found in ELSA (ß = -0.311; p < 0.001) and HRS (ß = -0.393; p < 0.001). The level of education moderated the life-course effect on health in both ELSA (ß = -0.082; p < 0.05) and HRS (ß = -0.084; p < 0.05). A birth-year effect was found for those belonging to the highest quintiles of household wealth in both ELSA (ß = 0.125; p < 0.001) and HRS (ß = 0.170; p < 0.001). CONCLUSIONS: Health inequalities have increased in recent cohorts, with the wealthiest participants presenting a better health status in both the USA and English populations. Actions to promote health in the ageing population should consider the increasing inequality scenario, not only by applying highly effective interventions, but also by making them accessible to all members of society.
Published: 2019

50. Long-term trajectories of depressive symptoms in old age: Relationships with sociodemographic and health-related factors

Author: de la Torre-Luque A, de la Fuente J, Prina M, Sánchez-Niubó A, Haro JM, and Ayuso-Mateos JL
Subjects: Healthy ageing, Measurement invariance, Longitudinal trajectories, Mixture modelling, Depression
Abstract: BACKGROUND: This study aimed at depicting the course of depression symptoms over the old age, with a special interest in a) uncovering its relationships with sociodemographic and health-related factors; b) analysing its predictive role on healthy-ageing outcomes later in life. METHODS: The sample comprised 8317 older adults (46.02% men) from the English Longitudinal Study of Ageing. Robust structural equation modelling was used to identify symptom trajectories and their relationships with time-varying factors. Trajectory class and covariates were used to predict outcomes (quality of life, satisfaction with life, and daily living functioning) in a 2-year follow-up. RESULTS: Three trajectory classes (so-called, normative, subclinical, chronic symptom trajectories) were identified for both sexes. Rising hearing difficulties and history of psychiatric problems were consistently associated with the chronic symptom trajectory. Lower education level, history of psychiatric problems, and increasing visual difficulties were connected with the subclinical trajectories. Finally, participants with either a subclinical or a chronic symptom trajectory showed worse outcomes than the remaining participants in the follow-up. CONCLUSION: This study highlighted the presence of varying courses of depression symptoms (each showing some distinctive features from other another) over the old age, pointing to some relevant implications for clinical assessment and treatment prescription.
Published: 2019

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