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1. 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, MA, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abebe, SS, Abedi, A, Abegaz, KH, Abhilash, ES, Abidi, H, Abiodun, O, Aboagye, RG ; https://orcid.org/0000-0002-3498-2909, 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, NM, 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, BA, 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 ; https://orcid.org/0000-0003-2018-6378, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akyirem, S, Al Hamad, H, Al Hasan, SM, Alahdab, F, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Sharma, Saurab ; https://orcid.org/0000-0002-9817-5372, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Cullen, Patricia ; https://orcid.org/0000-0003-4652-0936, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Peprah, Prince ; https://orcid.org/0000-0002-3816-2713, Degenhardt, Louisa ; https://orcid.org/0000-0002-8513-2218, Sitas, Freddy ; https://orcid.org/0000-0001-9679-1481, Schutte, Alta ; https://orcid.org/0000-0001-9217-4937, Pesudovs, Konrad ; https://orcid.org/0000-0002-6322-9369, Maulik, Pallab Kumar ; https://orcid.org/0000-0001-6835-6175, Godinho, Myron ; https://orcid.org/0000-0002-0081-2506, Okeke, Sylvester ; https://orcid.org/0000-0001-9211-1813, Hunter, Julie ; https://orcid.org/0000-0002-7284-0127, Sachdev, Perminder ; https://orcid.org/0000-0002-9595-3220, Dai-Keller, Zhaoli ; https://orcid.org/0000-0003-0809-5692, 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, MA, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abebe, SS, Abedi, A, Abegaz, KH, Abhilash, ES, Abidi, H, Abiodun, O, Aboagye, RG ; https://orcid.org/0000-0002-3498-2909, 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, NM, 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, BA, 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 ; https://orcid.org/0000-0003-2018-6378, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akyirem, S, Al Hamad, H, Al Hasan, SM, Alahdab, F, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Sharma, Saurab ; https://orcid.org/0000-0002-9817-5372, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Cullen, Patricia ; https://orcid.org/0000-0003-4652-0936, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Peprah, Prince ; https://orcid.org/0000-0002-3816-2713, Degenhardt, Louisa ; https://orcid.org/0000-0002-8513-2218, Sitas, Freddy ; https://orcid.org/0000-0001-9679-1481, Schutte, Alta ; https://orcid.org/0000-0001-9217-4937, Pesudovs, Konrad ; https://orcid.org/0000-0002-6322-9369, Maulik, Pallab Kumar ; https://orcid.org/0000-0001-6835-6175, Godinho, Myron ; https://orcid.org/0000-0002-0081-2506, Okeke, Sylvester ; https://orcid.org/0000-0001-9211-1813, Hunter, Julie ; https://orcid.org/0000-0002-7284-0127, Sachdev, Perminder ; https://orcid.org/0000-0002-9595-3220, and Dai-Keller, Zhaoli ; https://orcid.org/0000-0003-0809-5692
Abstract: Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, locati
Published: 2024

2. 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, Zuñiga, RAA, Aboagye, RG ; https://orcid.org/0000-0002-3498-2909, 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, Ali Saeed, A, Al-Gheethi, 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, Onie, Sandersan ; https://orcid.org/0000-0003-2147-8102, Godinho, Myron ; https://orcid.org/0000-0002-0081-2506, Okeke, Sylvester ; https://orcid.org/0000-0001-9211-1813, Dai-Keller, Zhaoli ; https://orcid.org/0000-0003-0809-5692, Sharma, Saurab ; https://orcid.org/0000-0002-9817-5372, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Peprah, Prince ; https://orcid.org/0000-0002-3816-2713, Degenhardt, Louisa ; https://orcid.org/0000-0002-8513-2218, Pesudovs, Konrad ; https://orcid.org/0000-0002-6322-9369, Hunter, Julie ; https://orcid.org/0000-0002-7284-0127, Sachdev, Perminder ; https://orcid.org/0000-0002-9595-3220, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, 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, Zuñiga, RAA, Aboagye, RG ; https://orcid.org/0000-0002-3498-2909, 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, Ali Saeed, A, Al-Gheethi, 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, Onie, Sandersan ; https://orcid.org/0000-0003-2147-8102, Godinho, Myron ; https://orcid.org/0000-0002-0081-2506, Okeke, Sylvester ; https://orcid.org/0000-0001-9211-1813, Dai-Keller, Zhaoli ; https://orcid.org/0000-0003-0809-5692, Sharma, Saurab ; https://orcid.org/0000-0002-9817-5372, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Peprah, Prince ; https://orcid.org/0000-0002-3816-2713, Degenhardt, Louisa ; https://orcid.org/0000-0002-8513-2218, Pesudovs, Konrad ; https://orcid.org/0000-0002-6322-9369, Hunter, Julie ; https://orcid.org/0000-0002-7284-0127, Sachdev, Perminder ; https://orcid.org/0000-0002-9595-3220, and Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235
Abstract: Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause.
Published: 2024

3. Forecasting the effects of smoking prevalence scenarios on years of life lost and life expectancy from 2022 to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Author: Bryazka, D, Reitsma, MB, Abate, YH, Abd Al Magied, AHA, Abdelkader, A, Abdollahi, A, Abdoun, M, Abdulkader, RS, Abeldaño Zuñiga, RA, Abhilash, ES, Abiodun, OO, Andrei, CL, Zhang, L, Zhong, CC, Zhou, SC, Zhu, B, Zielińska, M, Zoghi, G, Zyoud, SH, Vollset, SE, Gakidou, E, Andrei, T, Ansari, MT, Anuoluwa, IA, Anvari, S, Anwar, SL, Anyasodor, AE, Arabloo, J, Arafa, EA, Aravkin, AY, Abiodun, O, Areda, D, Aregawi, BB, Aremu, O, Artamonov, AA, Asgedom, AA, Asghari-Jafarabadi, M, Ashemo, MY, Ashraf, T, Astell-Burt, T, Athari, SS, Aboagye, RG, Atorkey, P, Atreya, A, Aujayeb, A, Awotidebe, AW, Ayano, G, Aychiluhm, SB, Azadnajafabad, S, Azzam, AY, Babu, GR, Bahrami Taghanaki, P, Abreu, LG, Bahramian, S, Bai, R, Bakkannavar, SM, Balakrishnan, S, Bam, K, Banach, M, Bandyopadhyay, S, Baran, MF, Barchitta, M, Bardhan, M, Abtahi, D, Barker-Collo, SL, Barrow, A, Bashiru, HA, Basiru, A, Bastan, M-M, Basu, S, Batra, K, Bayati, M, Behnoush, AH, Abualruz, H, Bell, SL, Belo, L, Beneke, AA, Bennett, DA, Bensenor, IM, Beran, A, Bermudez, ANC, Beyene, HB, Bhagat, DS, Bhagavathula, AS, Abubakar, B, Bhala, N, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, AN, Bhattacharjee, NV, Bhattacharjee, P, Bhatti, JS, Bilgin, C, Biswas, A, Abu-Rmeileh, NME, Biswas, B, Boachie, MK, Bogale, EK, Bora Basara, B, Borhany, H, Bosoka, SA, Bouaoud, S, Boyko, EJ, Brenner, H, Brunoni, AR, Aburuz, S, Bugiardini, R, Bulamu, NB, Bustanji, Y, Butt, ZA, Caetano dos Santos, FL, Calina, D, Cao, C, Cao, F, Capodici, A, Cárdenas, R, Abu-Zaid, A, Carreras, G, Castaldelli-Maia, JM, Cattaruzza, MS, Caye, A, Cegolon, L, Cenko, E, Cerrai, S, Chakraborty, S, Chandika, RM, Chandrasekar, EK, Adane, MM, Chattu, VK, Chaudhary, AA, Chaurasia, A, Chen, A-T, Chen, G, Chen, H, Chen, MX, Chen, S, Cheng, KJG, Chi, G, Adebiyi, AO, Chichagi, F, Chimoriya, R, Chirinos-Caceres, JL, Chitheer, A, Chong, B, Chong, CL, Chong, YY, Chopra, H, Choudhari, SG, Chu, D-T, Adegboye, OA, Chukwu, IS, Chung, S-C, Chutiyami, M, Conde, J, Corlateanu, A, Criqui, MH, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, S, Adekanmbi, V, Dai, X, Damiani, G, Dandona, L, Dandona, R, Darcho, SD, Darvishi Cheshmeh Soltani, R, Das, S, Dash, NR, Davletov, K, Debele, AT, Adewuyi, HO, Debopadhaya, S, Demant, D, Desai, HD, Devegowda, D, Dewan, SMR, Dhali, A, Dhane, AS, Dhulipala, VR, Do, TC, Dodangeh, M, Adnani, QES, Doegah, PT, Dohare, S, Dongarwar, D, D'Oria, M, Doshi, OP, Doshi, RP, Dowou, RK, Dsouza, AC, Dsouza, HL, Dsouza, VS, Adzigbli, LA, Duncan, BB, Duraes, AR, Dziedzic, AM, E'mar, AR, Ebrahimi, A, Ebrahimi, N, Ebrahimi Kalan, M, Edvardsson, D, Edvardsson, K, Efendi, F, Afaghi, S, Effendi, DE, Eghbali, F, Ekholuenetale, M, El Arab, RA, El Bayoumy, IF, El Sayed, I, Elbarazi, I, Elhadi, M, El-Huneidi, W, Elmonem, MA, Afolabi, AA, ELNahas, G, Elsohaby, I, Eltaha, C, Eltahir, ME, Emamverdi, M, Emeto, TI, Erku, DA, Etaee, F, Ezenwankwo, EF, Fabin, N, Afzal, MS, Fagbamigbe, AF, Fagbule, OF, Faghani, S, Fahim, A, Fakhradiyev, IR, Falzone, L, Farooque, U, Fatehizadeh, A, Fatima, Z, Fauk, NK, Afzal, S, Fazylov, T, Feizkhah, A, Fekadu, G, Feng, X, Ferrara, P, Ferreira, N, Feyisa, BR, Filippidis, FT, Fischer, F, Flor, LS, Agodi, A, Foigt, NA, Fortuna Rodrigues, C, Foschi, M, G, S, Gaal, PA, Gadanya, MA, Gaidhane, AM, Gajdács, M, Gallus, S, Gandhi, AP, Agyemang-Duah, W, Ganesan, B, Gautam, P, Gautam, RK, Gebregergis, MW, Gebrehiwot, M, Gebremeskel, TG, Getacher, L, Ghadirian, F, Ghazy, RM, Gholamrezanezhad, A, Ahinkorah, BO, Ghorbani, M, Ghozy, S, Gil, AU, Gil, GF, Gnedovskaya, EV, Goel, S, Goharinezhad, S, Goldust, M, Golechha, M, Goleij, P, Ahlstrom, AJ, Golinelli, D, Gorini, G, Gouravani, M, Grada, A, Grivna, M, Grover, S, Guan, S-Y, Gubari, MIM, Guha, A, Guicciardi, S, Ahmad, A, Gulati, S, Gunawardane, DA, Gunturu, S, Guo, Z, Gupta, AK, Gupta, B, Gupta, I, Gupta, M, Gupta, R, Gupta, S, Ahmad, D, Gupta, VB, Gupta, V, Gupta, VK, Hadei, M, Hadi, NR, Hajj Ali, A, Halboub, ES, Hamdy, NM, Hamidi, S, Hammoud, A, Ahmad, MM, Hankey, GJ, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, F, Hasan, MK, Hasnain, MS, Hassan, A, Hassan, II, Hassan, S, Ahmad, S, Hay, SI, Heibati, B, Heidari, M, Hemmati, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hiraike, Y, Hoan, NQ, Holla, R, Horita, N, Hossain, MM, Hossain, S, Hosseinzadeh, H, Hostiuc, M, Hostiuc, S, Huang, J, Humayun, A, Hussain, J, Ahmadi, A, Hwang, B-F, Ibitoye, SE, Ikeda, N, Ikiroma, A, Ilesanmi, OS, Ilic, IM, Ilic, MD, Immurana, M, Inbaraj, LR, Iqhrammullah, M, Ahmed, A, Irham, LM, Islam, MR, Islam, SMS, Islami, F, Isola, G, Itumalla, R, Iwagami, M, Iyer, M, J, V, Jaafari, J, Jacob, L, Jafarzadeh, A, Jaggi, K, Jahanmehr, N, Jain, A, Jain, N, Jairoun, AA, Jaka, S, Jakovljevic, M, Jalilzadeh Yengejeh, R, Ahmed, H, Jamshidi, E, Janodia, MD, Jawaid, T, Jayapal, SK, Jayaram, S, Jayasinghe, RD, Jebai, R, Jee, SH, Jeswani, BM, Jiang, H, Ahmed, MB, Jokar, M, Jonas, JB, Joo, T, Joseph, N, Joshua, CE, Jozwiak, JJ, Jürisson, M, K, V, Kabir, A, Kabir, Z, Ahmed, S, Kadashetti, V, Kamarajah, SK, Kanaan, M, Kanmodi, KK, Kant, S, Kantar, RS, Karakasis, P, Karaye, IM, Karimi, SE, Karimi, Y, Ajami, M, Karimi Behnagh, A, Karkhah, S, Karki, P, Kashoo, FZ, Katikireddi, SV, Kaur, H, Kaur, N, Kazemian, S, Kazmi, TH, Keiyoro, PN, Akkaif, MA, Kesse-Guyot, E, Khader, YS, Khajuria, H, Khalaji, A, Khalilian, A, Khan, A, Khan, M, Khan, MJ, Khan, MAB, Khanmohammadi, S, Akter, E, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khater, AM, Kheirallah, KA, Khokhar, M, Khormali, M, Khosla, AA, Khosravi, S, Kim, K, Al Awaidy, S, Kim, MS, Kim, YJ, Kisa, A, Kolahi, A-A, Komaki, S, Kondlahalli, SKMM, Korja, M, Korzh, O, Kosen, S, Kostev, K, Al Hasan, SM, Krishan, K, Kuate Defo, B, Kuddus, M, Kujan, O, Kulimbet, M, Kumar, A, Kumar, GA, Kumar, N, Kumar, R, Kumar, V, Al-Ajlouni, Y, Kundu, A, Kundu, S, Kunutsor, SK, Kurmi, OP, Kusuma, D, Kyei-Arthur, F, Kytö, V, La Vecchia, C, Lahariya, C, Lai, DTC, Al-Aly, Z, Lai, H, Lalloo, R, Lallukka, T, Larijani, B, Lasrado, S, Lau, J, Lauriola, P, Le, TTT, Leasher, JL, Lee, M, Alam, K, Lee, SW, Lee, W-C, Lee, YH, Leong, E, Lerango, TL, Li, A, Li, W, Ligade, VS, Lim, SS, Lin, J, Alam, Z, Lindstedt, PA, Liu, G, Llanaj, E, López-Gil, JF, Lotufo, PA, Lucchetti, G, Lugo, A, Lusk, JB, M Amin, HI, Ma, ZF, Aldhaleei, WA, Machoy, M, Madadizadeh, F, Mahmoudi, E, Makram, AM, Makram, OM, Malhotra, K, Malik, AA, Malta, DC, Mamun, AA, Mansouri, P, Algammal, AM, Mansournia, MA, Manu, E, Marateb, HR, Martinez-Raga, J, Martorell, M, Marzo, RR, Mathangasinghe, Y, Mathews, E, Mathur, M, Mathur, N, Al-Gheethi, AAS, Mattiello, R, Maugeri, A, McKee, M, Mechili, EA, Mehrotra, R, Mekene Meto, T, Mekonnen, BD, Meles, HN, Mendoza, W, Menezes, RG, Alhabib, KF, Meo, SA, Meretoja, A, Meretoja, TJ, Mestrovic, T, Meyers, CCA, Michalek, IM, Miller, TR, Minervini, G, Mirghafourvand, M, Mirrakhimov, EM, Alhalaiqa, FN, Mishra, V, Misra, S, Mithra, P, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammad, AM, Mohammad-Alizadeh-Charandabi, 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Rawaf, S, Reddy, MMRK, Redwan, EMM, Rezaei, N, Rezaeian, M, Riad, A, Rodrigues, M, Rodrigues da Silva, TPR, Alsakarneh, S, Rodriguez, JAB, Roever, L, Root, KT, Roshandel, G, Ross, AG, Rout, HS, Roy, B, Roy, N, Roy, S, Ruela, GDA, Alshahrani, NZ, S N, C, Sabet, CJ, Sabour, S, Sadarangani, KP, Saddik, BA, Sadeghi, M, Saeb, MR, Saeed, U, Saeedi, P, Safi, SZ, Altaany, Z, Sagoe, D, Saheb Sharif-Askari, F, Sahebkar, A, Sahoo, SS, Sajib, MRUZ, Sajid, MR, Salaroli, LB, Saleh, MA, Salem, MZY, Salihu, D, Altaf, A, Samodra, YL, Samy, AM, Sanabria, J, Santric-Milicevic, MM, Sao Jose, BP, Saqib, MAN, Sarasmita, MA, Saravanan, A, Saravi, B, Sarikhani, Y, Alvis-Guzman, N, Sarkar, T, Sarode, GS, Sarode, SC, Sartorius, B, Sathian, B, Sathyanarayan, A, Satpathy, M, Sawhney, M, Saylan, M, Schaarschmidt, BM, Al-Wardat, M, Schaub, MP, Schlaich, MP, Schmidt, MI, Schuermans, A, Schumacher, AE, Selvaraj, S, Semreen, MH, Senthilkumaran, S, Sepanlou, SG, Sethi, Y, Al-Worafi, YM, Seyedi, SA, Seylani, A, Shafie, M, Shafiee, A, Shahbandi, A, Shahid, S, Shahsavari, HR, Shahwan, MJ, Shaikh, A, Shaikh, MA, Aly, H, Shalash, AS, Shamim, MA, Shamsi, A, Shamsutdinova, A, Shanawaz, M, Shankar, A, Shannawaz, M, Sharath, M, Sharifan, A, Sharma, M, Aly, S, Sharma, U, Sharma, V, Sheikh, A, Sheikhy, A, Shetty, M, Shetty, PH, Shetty, PK, Shiferaw, D, Shimels, T, Shiri, R, Alyahya, MSI, Shittu, A, Shiue, I, Shivarov, V, Shorofi, SA, Shrestha, S, Siddig, EE, Silva, JP, Singh, A, Singh, B, Singh, H, Alzoubi, KH, Singh, JA, Singh, P, Singh, S, Singh, V, Sitas, F, Smith, AE, Soboka, M, Solanki, R, Solmi, M, Al-Zyoud, WA, Soraneh, S, Soriano, JB, Soyiri, IN, Spartalis, M, Sreeramareddy, CT, Stachteas, P, Stein, DJ, Steiropoulos, P, Stevanović, A, Straif, K, Amani, R, Suleman, M, Sulo, G, Sun, Z, Suresh, V, Swain, CK, Szarpak, L, T Y, SS, Tabaee Damavandi, P, Tabatabaei Malazy, O, Tabatabaeizadeh, S-A, Amin, TT, Tabche, C, Tadakamadla, J, Tadakamadla, SK, Taiba, J, Talaat, IM, Talukder, A, Tampa, M, Tamuzi, JLJL, Tan, K-K, Tareke, M, Amiri, S, Tarigan, IU, Teimoori, M, Temsah, M-H, Temsah, RMH, Teramoto, M, Terefa, DR, Thangaraju, P, Thankappan, KR, Thapar, R, Thayakaran, R, Amu, H, Thomas, NK, Ticoalu, JHV, Tiwari, K, Topor-Madry, R, Tovani-Palone, MR, Trabelsi, K, Tran, AT, Tran, NH, Tran, TH, Tran Minh Duc, N, Amul, GGH, Trihandini, I, Tripathy, JP, Truyen, TTTT, Tsermpini, EE, Tualeka, AR, Udoakang, AJ, Udoh, A, Ullah, A, Ullah, S, Umair, M, Amusa, GA, Unim, B, Unnikrishnan, B, Usman, JS, Vahdati, S, Vaithinathan, AG, Van den Eynde, J, Vardavas, C, Vasankari, TJ, Vaziri, S, Vellingiri, B, Anand, T, Venketasubramanian, N, Verma, M, Villeneuve, PJ, Vinayak, M, Violante, FS, Vladimirov, SK, Volovat, SR, Wadood, A, Waheed, Y, Walde, MT, Anderlini, D, Wang, S, Wang, Y, Waqas, M, Wickramasinghe, ND, Willeit, P, Wojewodzic, MW, Wolde, AA, Wonde, TE, Xiao, H, Xu, S, Anderson, DB, Yadav, MK, Yamagishi, K, Yang, D, Yang, L, Yano, Y, Yarahmadi, A, Yesodharan, R, Yezli, S, Yi, X, Yiğit, A, Anderson, JA, Yin, D, Yon, DK, Yonemoto, N, Yoon, S-J, Yu, C, Yuan, C-W, Zakham, F, Zeariya, MGM, Zhang, H, and Zhang, J
Published: 2024

4. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.

Author: Wang, A, Shen, J, Rodriguez, AA, Saunders, EJ, Chen, F, Janivara, R, Darst, BF, Sheng, X, Xu, Y, Chou, AJ, Benlloch, S, Dadaev, T, Brook, MN, Plym, A, Sahimi, A, Hoffman, TJ, Takahashi, A, Matsuda, K, Momozawa, Y, Fujita, M, Laisk, T, Figuerêdo, J, Muir, K, Ito, S, Liu, X, Biobank Japan Project, Uchio, Y, Kubo, M, Kamatani, Y, Lophatananon, A, Wan, P, Andrews, C, Lori, A, Choudhury, PP, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokolorczyk, D, Lubinski, J, Rentsch, CT, Cho, K, Mcmahon, BH, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, A, Stroomberg, HV, Batra, J, Chambers, S, Horvath, L, Clements, JA, Tilly, W, Risbridger, GP, Gronberg, H, Aly, M, Szulkin, R, Eklund, M, Nordstrom, T, Pashayan, N, Dunning, AM, Ghoussaini, M, Travis, RC, Key, TJ, Riboli, E, Park, JY, Sellers, TA, Lin, H-Y, Albanes, D, Weinstein, S, Cook, MB, Mucci, LA, Giovannucci, E, Lindstrom, S, Kraft, P, Hunter, DJ, Penney, KL, Turman, C, Tangen, CM, Goodman, PJ, Thompson, IM, Hamilton, RJ, Fleshner, NE, Finelli, A, Parent, M-É, Stanford, JL, Ostrander, EA, Koutros, S, Beane Freeman, LE, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, KD, Borre, M, Blot, WJ, Zheng, W, Yeboah, ED, Mensah, JE, Lu, Y-J, Zhang, H-W, Feng, N, Mao, X, Wu, Y, Zhao, S-C, Sun, Z, Thibodeau, SN, McDonnell, SK, Schaid, DJ, West, CML, Barnett, G, Maier, C, Schnoeller, T, Luedeke, M, Kibel, AS, Drake, BF, Cussenot, O, Cancel-Tassin, G, Menegaux, F, Truong, T, Koudou, YA, John, EM, Grindedal, EM, Maehle, L, Khaw, K-T, Ingles, SA, Stern, MC, Vega, A, Gómez-Caamaño, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Butler, EN, Mohler, JL, Taylor, JA, Kogevinas, M, Dierssen-Sotos, T, Castaño-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Pilie, P, Yu, Y, Bohlender, RJ, Gu, J, Strom, SS, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Brenner, H, Chen, X, Holleczek, B, Schöttker, B, Klein, EA, Hsing, AW, Kittles, RA, Murphy, AB, Logothetis, CJ, Kim, J, Neuhausen, SL, Steele, L, Ding, YC, Isaacs, WB, Nemesure, B, Hennis, AJM, Carpten, J, Pandha, H, Michael, A, De Ruyck, K, De Meerleer, G, Ost, P, Xu, J, Razack, A, Lim, J, Teo, S-H, Newcomb, LF, Lin, DW, Fowke, JH, Neslund-Dudas, CM, Rybicki, BA, Gamulin, M, Lessel, D, Kulis, T, Usmani, N, Abraham, A, Singhal, S, Parliament, M, Claessens, F, Joniau, S, Van den Broeck, T, Gago-Dominguez, M, Castelao, JE, Martinez, ME, Larkin, S, Townsend, PA, Aukim-Hastie, C, Bush, WS, Aldrich, MC, Crawford, DC, Srivastava, S, Cullen, J, Petrovics, G, Casey, G, Wang, Y, Tettey, Y, Lachance, J, Tang, W, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Yamoah, K, Govindasami, K, Chokkalingam, AP, Keaton, JM, Hellwege, JN, Clark, PE, Jalloh, M, Gueye, SM, Niang, L, Ogunbiyi, O, Shittu, O, Amodu, O, Adebiyi, AO, Aisuodionoe-Shadrach, OI, Ajibola, HO, Jamda, MA, Oluwole, OP, Nwegbu, M, Adusei, B, Mante, S, Darkwa-Abrahams, A, Diop, H, Gundell, SM, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Kachuri, L, Varma, R, McKean-Cowdin, R, Torres, M, Preuss, MH, Loos, RJF, Zawistowski, M, Zöllner, S, Lu, Z, Van Den Eeden, SK, Easton, DF, Ambs, S, Edwards, TL, Mägi, R, Rebbeck, TR, Fritsche, L, Chanock, SJ, Berndt, SI, Wiklund, F, Nakagawa, H, Witte, JS, Gaziano, JM, Justice, AC, Mancuso, N, Terao, C, Eeles, RA, Kote-Jarai, Z, Madduri, RK, Conti, DV, Haiman, CA, Wang, A, Shen, J, Rodriguez, AA, Saunders, EJ, Chen, F, Janivara, R, Darst, BF, Sheng, X, Xu, Y, Chou, AJ, Benlloch, S, Dadaev, T, Brook, MN, Plym, A, Sahimi, A, Hoffman, TJ, Takahashi, A, Matsuda, K, Momozawa, Y, Fujita, M, Laisk, T, Figuerêdo, J, Muir, K, Ito, S, Liu, X, Biobank Japan Project, Uchio, Y, Kubo, M, Kamatani, Y, Lophatananon, A, Wan, P, Andrews, C, Lori, A, Choudhury, PP, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokolorczyk, D, Lubinski, J, Rentsch, CT, Cho, K, Mcmahon, BH, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, A, Stroomberg, HV, Batra, J, Chambers, S, Horvath, L, Clements, JA, Tilly, W, Risbridger, GP, Gronberg, H, Aly, M, Szulkin, R, Eklund, M, Nordstrom, T, Pashayan, N, Dunning, AM, Ghoussaini, M, Travis, RC, Key, TJ, Riboli, E, Park, JY, Sellers, TA, Lin, H-Y, Albanes, D, Weinstein, S, Cook, MB, Mucci, LA, Giovannucci, E, Lindstrom, S, Kraft, P, Hunter, DJ, Penney, KL, Turman, C, Tangen, CM, Goodman, PJ, Thompson, IM, Hamilton, RJ, Fleshner, NE, Finelli, A, Parent, M-É, Stanford, JL, Ostrander, EA, Koutros, S, Beane Freeman, LE, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, KD, Borre, M, Blot, WJ, Zheng, W, Yeboah, ED, Mensah, JE, Lu, Y-J, Zhang, H-W, Feng, N, Mao, X, Wu, Y, Zhao, S-C, Sun, Z, Thibodeau, SN, McDonnell, SK, Schaid, DJ, West, CML, Barnett, G, Maier, C, Schnoeller, T, Luedeke, M, Kibel, AS, Drake, BF, Cussenot, O, Cancel-Tassin, G, Menegaux, F, Truong, T, Koudou, YA, John, EM, Grindedal, EM, Maehle, L, Khaw, K-T, Ingles, SA, Stern, MC, Vega, A, Gómez-Caamaño, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Butler, EN, Mohler, JL, Taylor, JA, Kogevinas, M, Dierssen-Sotos, T, Castaño-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Pilie, P, Yu, Y, Bohlender, RJ, Gu, J, Strom, SS, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Brenner, H, Chen, X, Holleczek, B, Schöttker, B, Klein, EA, Hsing, AW, Kittles, RA, Murphy, AB, Logothetis, CJ, Kim, J, Neuhausen, SL, Steele, L, Ding, YC, Isaacs, WB, Nemesure, B, Hennis, AJM, Carpten, J, Pandha, H, Michael, A, De Ruyck, K, De Meerleer, G, Ost, P, Xu, J, Razack, A, Lim, J, Teo, S-H, Newcomb, LF, Lin, DW, Fowke, JH, Neslund-Dudas, CM, Rybicki, BA, Gamulin, M, Lessel, D, Kulis, T, Usmani, N, Abraham, A, Singhal, S, Parliament, M, Claessens, F, Joniau, S, Van den Broeck, T, Gago-Dominguez, M, Castelao, JE, Martinez, ME, Larkin, S, Townsend, PA, Aukim-Hastie, C, Bush, WS, Aldrich, MC, Crawford, DC, Srivastava, S, Cullen, J, Petrovics, G, Casey, G, Wang, Y, Tettey, Y, Lachance, J, Tang, W, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Yamoah, K, Govindasami, K, Chokkalingam, AP, Keaton, JM, Hellwege, JN, Clark, PE, Jalloh, M, Gueye, SM, Niang, L, Ogunbiyi, O, Shittu, O, Amodu, O, Adebiyi, AO, Aisuodionoe-Shadrach, OI, Ajibola, HO, Jamda, MA, Oluwole, OP, Nwegbu, M, Adusei, B, Mante, S, Darkwa-Abrahams, A, Diop, H, Gundell, SM, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Kachuri, L, Varma, R, McKean-Cowdin, R, Torres, M, Preuss, MH, Loos, RJF, Zawistowski, M, Zöllner, S, Lu, Z, Van Den Eeden, SK, Easton, DF, Ambs, S, Edwards, TL, Mägi, R, Rebbeck, TR, Fritsche, L, Chanock, SJ, Berndt, SI, Wiklund, F, Nakagawa, H, Witte, JS, Gaziano, JM, Justice, AC, Mancuso, N, Terao, C, Eeles, RA, Kote-Jarai, Z, Madduri, RK, Conti, DV, and Haiman, CA
Abstract: The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
Published: 2023

5. Knowledge and practice of universal precautions among professionals in public and private health facilities in Uyo, southern Nigeria- A comparative study

Author: Johnson OE, Asuzu MC, and Adebiyi AO
Subjects: Knowledge, Universal Precautions, Health Workers, Health Facilities, Bloodborne Pathogens, Practice Score, Medicine
Abstract: Background: Occupationally acquired blood borne pathogens are becoming major killers globally. Consequently, the practice of Universal Precautions (UP) is key in protecting health workers from these pathogens. Objective: This was to assess the knowledge and practice of UP among health workers in private and public hospitals in Uyo, Nigeria. Method: This was a cross sectional study in which all eligible health workers in the private facilities were enlisted, while health workers from the public facilities were selected through multistage sampling method. Data obtained was analysed using SPSS version 11. Result: A total of 360 respondents participated in the study, 240 (66.7%) from the public and 120 (33.3%) from the private facilities. Overall, 154 (64.2%) of the health workers in the public, compared to 65 (54.2%) in the private facilities had good knowledge of UP (x2= 8.09, p< 0.05) with a mean score of 14.5 out of 20 in the public and 12.3 in the private facilities. Those in the public facilities had a UP practice score of 11.86 out of a total score of 18 which was significantly higher than 9.54 in the private hospitals (t=6.01; p
Published: 2012
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6. Author Correction: Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017 (Nature Medicine, (2020), 26, 5, (750-759), 10.1038/s41591-020-0807-6)

Author: Kinyoki, DK, Ross, JM, Lazzar-Atwood, A, Munro, SB, Schaeffer, LE, Abbasalizad-Farhangi, M, Abbasi, M, Abbastabar, H, Abdelalim, A, Abdoli, A, Abdollahi, M, Abdollahpour, I, Abdulkader, RS, Abebe, ND, Abebo, TA, Abegaz, KH, Abolhassani, H, Abreu, LG, Abrigo, MRM, Abushouk, AI, Accrombessi, MMK, Acharya, D, Adabi, M, Adebiyi, AO, Adedeji, IA, Adekanmbi, V, Adeoye, AM, Adetokunboh, OO, Adham, D, Aduroja, PE, Advani, SM, Afarideh, M, Aghaali, M, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmadi, S, Ahmed, MB, Ahmed, R, Ajumobi, O, Akal, CG, Akalu, TY, Akinyemiju, T, Akombi, B ; https://orcid.org/0000-0002-6410-4154, Al-Aly, Z, Alam, S, Alamene, GM, Alanzi, TM, Rabanal, JEA, Alema, NM, Ali, BA, Ali, M, Alijanzadeh, M, Alinia, C, Alipour, V, Alizade, H, Aljunid, SM, Almasi, A, Almasi-Hashiani, A, Al-Mekhlafi, HM, Al-Raddadi, RM, Altirkawi, K, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amare, AT, Amegah, AK, Amini, S, Rarani, MA, Amiri, F, Amit, AML, Anber, NH, Andrei, CL, Ansari, F, Ansari-Moghaddam, A, Anteneh, ZA, Antonio, CAT, Antriyandarti, E, Anvari, D, Anwer, R, Appiah, SCY, Arabloo, J, Arab-Zozani, M, Araya, EM, Arefi, Z, Aremu, O, Ärnlöv, J, Arzani, A, Asadi-Aliabadi, M, Asadi-Pooya, AA, Asgari, S, Asghari, B, Ashagre, AF, Asrat, AA, Ataeinia, B, Atalay, HT, Atnafu, DD, Atout, MMW, Ausloos, M, Avokpaho, EFGA, Awasthi, A, Jha, Vivekanand ; https://orcid.org/0000-0002-8015-9470, Karki, Surendra ; https://orcid.org/0000-0003-1561-4171, Maulik, Pallab Kumar ; https://orcid.org/0000-0001-6835-6175, John, Oommen ; https://orcid.org/0000-0002-9008-1726, Biswas, Raaj Kishore ; https://orcid.org/0000-0003-4294-6323, Schutte, Alta ; https://orcid.org/0000-0001-9217-4937, Resnikoff, Serge ; https://orcid.org/0000-0002-5866-4446, Kinyoki, DK, Ross, JM, Lazzar-Atwood, A, Munro, SB, Schaeffer, LE, Abbasalizad-Farhangi, M, Abbasi, M, Abbastabar, H, Abdelalim, A, Abdoli, A, Abdollahi, M, Abdollahpour, I, Abdulkader, RS, Abebe, ND, Abebo, TA, Abegaz, KH, Abolhassani, H, Abreu, LG, Abrigo, MRM, Abushouk, AI, Accrombessi, MMK, Acharya, D, Adabi, M, Adebiyi, AO, Adedeji, IA, Adekanmbi, V, Adeoye, AM, Adetokunboh, OO, Adham, D, Aduroja, PE, Advani, SM, Afarideh, M, Aghaali, M, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmadi, S, Ahmed, MB, Ahmed, R, Ajumobi, O, Akal, CG, Akalu, TY, Akinyemiju, T, Akombi, B ; https://orcid.org/0000-0002-6410-4154, Al-Aly, Z, Alam, S, Alamene, GM, Alanzi, TM, Rabanal, JEA, Alema, NM, Ali, BA, Ali, M, Alijanzadeh, M, Alinia, C, Alipour, V, Alizade, H, Aljunid, SM, Almasi, A, Almasi-Hashiani, A, Al-Mekhlafi, HM, Al-Raddadi, RM, Altirkawi, K, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amare, AT, Amegah, AK, Amini, S, Rarani, MA, Amiri, F, Amit, AML, Anber, NH, Andrei, CL, Ansari, F, Ansari-Moghaddam, A, Anteneh, ZA, Antonio, CAT, Antriyandarti, E, Anvari, D, Anwer, R, Appiah, SCY, Arabloo, J, Arab-Zozani, M, Araya, EM, Arefi, Z, Aremu, O, Ärnlöv, J, Arzani, A, Asadi-Aliabadi, M, Asadi-Pooya, AA, Asgari, S, Asghari, B, Ashagre, AF, Asrat, AA, Ataeinia, B, Atalay, HT, Atnafu, DD, Atout, MMW, Ausloos, M, Avokpaho, EFGA, Awasthi, A, Jha, Vivekanand ; https://orcid.org/0000-0002-8015-9470, Karki, Surendra ; https://orcid.org/0000-0003-1561-4171, Maulik, Pallab Kumar ; https://orcid.org/0000-0001-6835-6175, John, Oommen ; https://orcid.org/0000-0002-9008-1726, Biswas, Raaj Kishore ; https://orcid.org/0000-0003-4294-6323, Schutte, Alta ; https://orcid.org/0000-0001-9217-4937, and Resnikoff, Serge ; https://orcid.org/0000-0002-5866-4446
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2020

7. Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

Author: Kinyoki, DK, Ross, JM, Lazzar-Atwood, A, Munro, SB, Schaeffer, LE, Abbasalizad-Farhangi, M, Abbasi, M, Abbastabar, H, Abdelalim, A, Abdoli, A, Abdollahi, M, Abdollahpour, I, Abdulkader, RS, Abebe, ND, Abebo, TA, Abegaz, KH, Abolhassani, H, Abreu, LG, Abrigo, MRM, Abushouk, AI, Accrombessi, MMK, Acharya, D, Adabi, M, Adebiyi, AO, Adedeji, IA, Adekanmbi, V, Adeoye, AM, Adetokunboh, OO, Adham, D, Aduroja, PE, Advani, SM, Afarideh, M, Aghaali, M, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmadi, S, Ahmed, MB, Ahmed, R, Ajumobi, O, Akal, CG, Akalu, TY, Akinyemiju, T, Akombi, B ; https://orcid.org/0000-0002-6410-4154, Al-Aly, Z, Alam, S, Alamene, GM, Alanzi, TM, Rabanal, JEA, Alema, NM, Ali, BA, Ali, M, Alijanzadeh, M, Alinia, C, Alipour, V, Alizade, H, Aljunid, SM, Almasi, A, Almasi-Hashiani, A, Al-Mekhlafi, HM, Al-Raddadi, RM, Altirkawi, K, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amare, AT, Amegah, AK, Amini, S, Rarani, MA, Amiri, F, Amit, AML, Anber, NH, Andrei, CL, Ansari, F, Ansari-Moghaddam, A, Anteneh, ZA, Antonio, CAT, Antriyandarti, E, Anvari, D, Anwer, R, Appiah, SCY, Arabloo, J, Arab-Zozani, M, Araya, EM, Arefi, Z, Aremu, O, Ärnlöv, J, Arzani, A, Asadi-Aliabadi, M, Asadi-Pooya, AA, Asgari, S, Asghari, B, Ashagre, AF, Asrat, AA, Ataeinia, B, Atalay, HT, Atnafu, DD, Atout, MMW, Ausloos, M, Avokpaho, EFGA, Awasthi, A, Karki, Surendra ; https://orcid.org/0000-0003-1561-4171, Jha, Vivekanand ; https://orcid.org/0000-0002-8015-9470, Biswas, Raaj Kishore ; https://orcid.org/0000-0003-4294-6323, Schutte, Alta ; https://orcid.org/0000-0001-9217-4937, Maulik, Pallab Kumar ; https://orcid.org/0000-0001-6835-6175, John, Oommen ; https://orcid.org/0000-0002-9008-1726, Resnikoff, Serge ; https://orcid.org/0000-0002-5866-4446, Iqbal, Usman ; https://orcid.org/0000-0002-0614-123X, Kinyoki, DK, Ross, JM, Lazzar-Atwood, A, Munro, SB, Schaeffer, LE, Abbasalizad-Farhangi, M, Abbasi, M, Abbastabar, H, Abdelalim, A, Abdoli, A, Abdollahi, M, Abdollahpour, I, Abdulkader, RS, Abebe, ND, Abebo, TA, Abegaz, KH, Abolhassani, H, Abreu, LG, Abrigo, MRM, Abushouk, AI, Accrombessi, MMK, Acharya, D, Adabi, M, Adebiyi, AO, Adedeji, IA, Adekanmbi, V, Adeoye, AM, Adetokunboh, OO, Adham, D, Aduroja, PE, Advani, SM, Afarideh, M, Aghaali, M, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmadi, S, Ahmed, MB, Ahmed, R, Ajumobi, O, Akal, CG, Akalu, TY, Akinyemiju, T, Akombi, B ; https://orcid.org/0000-0002-6410-4154, Al-Aly, Z, Alam, S, Alamene, GM, Alanzi, TM, Rabanal, JEA, Alema, NM, Ali, BA, Ali, M, Alijanzadeh, M, Alinia, C, Alipour, V, Alizade, H, Aljunid, SM, Almasi, A, Almasi-Hashiani, A, Al-Mekhlafi, HM, Al-Raddadi, RM, Altirkawi, K, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amare, AT, Amegah, AK, Amini, S, Rarani, MA, Amiri, F, Amit, AML, Anber, NH, Andrei, CL, Ansari, F, Ansari-Moghaddam, A, Anteneh, ZA, Antonio, CAT, Antriyandarti, E, Anvari, D, Anwer, R, Appiah, SCY, Arabloo, J, Arab-Zozani, M, Araya, EM, Arefi, Z, Aremu, O, Ärnlöv, J, Arzani, A, Asadi-Aliabadi, M, Asadi-Pooya, AA, Asgari, S, Asghari, B, Ashagre, AF, Asrat, AA, Ataeinia, B, Atalay, HT, Atnafu, DD, Atout, MMW, Ausloos, M, Avokpaho, EFGA, Awasthi, A, Karki, Surendra ; https://orcid.org/0000-0003-1561-4171, Jha, Vivekanand ; https://orcid.org/0000-0002-8015-9470, Biswas, Raaj Kishore ; https://orcid.org/0000-0003-4294-6323, Schutte, Alta ; https://orcid.org/0000-0001-9217-4937, Maulik, Pallab Kumar ; https://orcid.org/0000-0001-6835-6175, John, Oommen ; https://orcid.org/0000-0002-9008-1726, Resnikoff, Serge ; https://orcid.org/0000-0002-5866-4446, and Iqbal, Usman ; https://orcid.org/0000-0002-0614-123X
Abstract: A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic.
Published: 2020

8. Correction to Lancet HIV 2016; 3: e361-87

Author: Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Mills, EJ, Trickey, A, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Salomon, J, Larson, HJ, Friedman, J, Abajobir, AA, Abate, KH, Abbas, KM, Razek, MMAE, Abd-Allah, F, Abdulle, AM, Abera, SF, Abubakar, I, Abu-Raddad, LJ, Abu-Rmeileh, NME, Abyu, GY, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adofo, K, Adou, AK, Ajala, ON, Akinyemiju, TF, Akseer, N, Lami, FHA, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SFS, Aldridge, RW, Alegretti, MA, Aleman, AV, Alemu, ZA, Alfonso-Cristancho, R, Ali, R, Alkerwi, A, Alla, F, Mohammad, R, Al-Raddadi, S, Alsharif, U, Alvarez, E, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Antonio, CAT, Anwari, P, Ã„rnlÃ¶v, J, Artaman, A, Asayesh, H, Asghar, RJ, Assadi, R, Atique, S, Atkins, LS, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Bacha, U, Badawi, A, Barac, A, BÃ¤rnighausen, T, Basu, A, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, N, Bennett, DA, Bensenor, IM, Betsu, BD, Beyene, AS, Bhatia, E, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Bisanzio, D, Brainin, M, Brazinova, A, Breitborde, NJK, Brown, A, Burch, M, Butt, ZA, Campuzano, JC, and CÃ¡rdenas, R
Abstract: GBD 2015 HIV Collaborators. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2015: the Global Burden of Disease Study 2015. Lancet HIV 2016; 3: e361–87—In this Article, Kerrie E Doyle and David M Pereira have been added to the list of collaborators and Claudia C Pereira has been removed. These corrections have been made as of Aug 22, 2016.
Published: 2016

9. S001: PATTERN OF ACCIDENTAL FEMUR FRACTURES IN CHILDREN AND THE PREDICTORS OF CHILD ABUSE IN AN URBAN COMMUNITY IN NIGERIA

Author: Adeyemi, O.J., Oyetunde, O., Ayorinde, O., Ibukun, F.A, Onwu, VA, Adebayo, AM, and Adebiyi, AO
Subjects: Ophthalmology, trauma, wound sepsis, Oral Presentations, Preventive ophthalmology, Law prohibiting smoking, Eye diseases, spiral fractures, Tobacco smoking, Public places, Research Article, Child abuse
Abstract: Introduction: Investigating physical abuse in children in Nigeria is not a routine practice. Unlike other climes where there is an established team that intervenes in cases of child abuse and neglect, no such practice is done in Nigeria. But child abuse does exist. Such children are difficult to identify from other children with accidental fractures. The code of silence is also obeyed as the child, if able to vocalize, will refrain from talking, having been sternly warned by caregivers. This study seeks, within the ambit of the history, examination and radiologic characteristics of the femur fractures, predict the possibility of child abuse. Objectives: The aim of the study is to describe and analyze the pattern of accidental femur fractures in children and to predict the occurrences of child abuse in an urban community in Nigeria. Methods: A retrospective study was conducted using the Accident and Emergency records of the University College Hospital, Ibadan, Nigeria over a period of ten years (January 2006 - December 2015. 87 cases were retrieved. Selected cases were children between the ages of 0 and 15 that sustained at least a femur fracture. Demographic data, aetiologies of fractures, and X-Ray features of the different cases were collated and analyzed. Results: Of the 87 cases aged between 0 - 15 years, 52 were males while 32 were females and 41.4% of the cases were between the ages of 2 -5 years. Of the assessed etiologies for femur fractures, 32.3% of the cases occurred following fall from heights and this was followed by pedestrian road traffic accident (17.2%). The morbidities recorded were fever, wound sepsis and anaemia. Femur shaft was the commonest region of fracture and the patterns of fracture noted were majorly transverse fracture (37.9%), oblique fracture (27.6%), and spiral fracture (18.4%). 5.7% of the cases had fractures in other parts of the body. Of all the fracture patterns, spiral fracture pattern is the only one that has a significant relationship with a morbidity - wound sepsis. Also, spiral fractures tend to be seen more commonly as isolated fractures (87.5%) although this observed relationship is not statistically significant. Furthermore, spiral fractures are 1.2times likely to result from domestic accident; however this observed relationship is not significant. Conclusion: Fall from height and pedestrian road traffic accident remain the highest causes of femur fractures in children. The presence of spiral fracture either occurring in isolation or coexisting with wound sepsis or history of domestic violence should raise a high index of suspicion of a possible child abuse., Objective: To determine the pattern presentation of ocular diseases at eye outreach programmes of the community ophthalmology unit of the University College Hospital, Ibadan within a single year period to enhance planning of future programmes and develop strategies for improvement in efficiency of service delivery. Methods: A retrospective review of the records of the eye outreach unit between July 2015 and June 2016 was done. Information on location and frequency of programmes, client's demographic characteristics, clinical diagnosis, and interventions given were collected and descriptively summarised. Results: 59 programmes were carried out, mostly in Ibadan and its environs to reach 4,879 people of all age groups (mean=44.95, SD =/-20.05), with 60% being females. Presbyopia (24%) and refractive error (19.6%) were the commonest diagnosis followed by ocular allergy (13.6%). A large proportion had normal findings (12.2%) and the disease burden of cataract was high (10.2%). Other common ocular conditions were pterygium, dry eye disease and corneal opacity. Ocular medications were given for dry eyes, allergy and infections, spectacles prescribed for presbyopia. Cataract patients and other needing specialist care were referred to the base hospital. Conclusion: Majority of ocular conditions seen at our eye outreach programmes are noncommunicable, and correctable with simple ophthalmic care which can be delivered close to the people at little cost to them., Background: Tobacco smoking in public places is prevalent in Nigeria despite global recognition of its harm. Ekiti State is one of the few states in Nigeria with an enacted law prohibiting smoking in public places without decline in the practice. Aims/Objectives: This study assessed awareness, perception of State tobacco control law prohibiting smoking in public places and factors influencing adherence to the law in Ekiti State among selected stakeholders. Methods: Study was descriptive cross-sectional using a mixed methods approach. Respondents were selected stakeholders directly involved with tobacco control law within the State. Respondents, perception and attitude towards the law was assessed using standardized scales. The qualitative survey employed key informant interview (KII). Quantitative data were analyzed using descriptive statistics and Chisquare (p=0.05) while qualitative data were analyzed using thematic approach. Results: Majority (73.0%) were aware of the law, (86.0%) had good perception and (93.4%) positive attitude towards the law. Awareness was higher among the older age groups compared to the younger (p=0.018). Qualitative findings revealed little or no compliance with the law prohibiting tobacco smoking in public places in the State. Identified reasons for non-compliance among respondents were poor level of information dissemination, awareness and lack of political will. Conclusion: Despite high level of awareness, good perception and positive attitude to the law prohibiting tobacco smoking in public places, perceived adherence among stakeholders in Ekiti State is poor. Concerted governmental efforts are required to address identified barriers to compliance for effective implementation and enforcement of the law in the State.
Published: 2018

10. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015 : the Global Burden of Disease Study 2015

Author: GBD 2015 HIV Collaborators, Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Mills, EJ, Trickey, A, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Salomon, J, Larson, HJ, Friedman, J, Abajobir, AA, Abate, KH, Abbas, KM, Razek, MM, Abd-Allah, F, Abdulle, AM, Abera, SF, Abubakar, I, Abu-Raddad, LJ, Abu-Rmeileh, NM, Abyu, GY, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adofo, K, Adou, AK, Ajala, ON, Akinyemiju, TF, Akseer, N, Lami, FH, Al-Aly, Z, Alam, K, Alam, NK, Alasfoor, D, Aldhahri, SF, Aldridge, RW, Alegretti, MA, Aleman, AV, Alemu, ZA, Alfonso-Cristancho, R, Ali, R, Alkerwi, A, Alla, F, Mohammad, R, Al-Raddadi, S, Alsharif, U, Alvarez, E, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Antonio, CA, Anwari, P, Ärnlöv, J, Artaman, A, Asayesh, H, Asghar, RJ, Assadi, R, Atique, S, Atkins, LS, Avokpaho, EF, Awasthi, A, Quintanilla, BP, Bacha, U, Badawi, A, Barac, A, Bärnighausen, T, Basu, A, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, N, Bennett, DA, Bensenor, IM, Betsu, BD, Beyene, AS, Bhatia, E, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Bisanzio, D, Brainin, M, Brazinova, A, Breitborde, NJ, Brown, A, Burch, M, Butt, ZA, Campuzano, JC, Cárdenas, R, Carrero, JJ, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Chang, HY, Chang, JC, Chavan, L, Chen, W, Chiang, PP, Chibalabala, M, Chisumpa, VH, Choi, JY, Christopher, DJ, Ciobanu, LG, Cooper, C, Dahiru, T, Damtew, SA, Dandona, L, Dandona, R, Das Neves, J, De Jager, P, De Leo, D, Degenhardt, L, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dharmaratne, SD, Ding, EL, Doshi, PP, Driscoll, TR, Dubey, M, Elshrek, YM, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faghmous, ID, Farinha, CS, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, SM, Fernandes, JC, Fischer, F, Fitchett, JR, Foigt, N, Fullman, N, Fürst, T, Gankpé, FG, Gebre, T, Gebremedhin, AT, Gebru, AA, Geleijnse, JM, Gessner, BD, Gething, PW, Ghiwot, TT, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Goodridge, A, Gopalani, SV, Goto, A, Gugnani, HC, Guimaraes, MD, Gupta, R, Gupta, V, Haagsma, J, Hafezi-Nejad, N, Hagan, H, Hailu, GB, Hamadeh, RR, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Harikrishnan, S, Haro, JM, Harun, KM, Havmoeller, R, Hedayati, MT, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Hsairi, M, Hu, G, Huang, H, Huang, JJ, Iburg, KM, Idrisov, BT, Innos, K, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karema, CK, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Keiyoro, PN, Kemp, AH, Kengne, AP, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khang, YH, Khubchandani, J, Kim, YJ, Kinfu, Y, Kivipelto, M, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Defo, BK, Bicer, BK, Kulkarni, VS, Kumar, GA, Lal, DK, Lam, H, Lam, JO, Langan, SM, Lansingh, VC, Larsson, A, Leigh, J, Leung, R, Li, Y, Lim, SS, Lipshultz, SE, Liu, S, Lloyd, BK, Logroscino, G, Lotufo, PA, Lunevicius, R, Razek, HM, Mahdavi, M, Majdan, M, Majeed, A, Makhlouf, C, Malekzadeh, R, Mapoma, CC, Marcenes, W, Martinez-Raga, J, Marzan, MB, Masiye, F, Mason-Jones, AJ, Mayosi, BM, McKee, M, Meaney, PA, Mehndiratta, MM, Mekonnen, AB, Melaku, YA, Memiah, P, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mikesell, J, Mirarefin, M, Mohammad, KA, Mohammed, S, Mokdad, AH, Monasta, L, Moradi-Lakeh, M, Mori, R, Mueller, UO, Murimira, B, Murthy, GV, Naheed, A, Naldi, L, Nangia, V, Nash, D, Nawaz, H, Nejjari, C, Ngalesoni, FN, De Dieu Ngirabega, J, Nguyen, QL, Nisar, MI, Norheim, OF, Norman, RE, Nyakarahuka, L, Ogbo, FA, Oh, IH, Ojelabi, FA, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Padukudru, MA, Park, HY, Park, JH, Patil, ST, Patten, SB, Paul, VK, Pearson, K, Peprah, EK, Pereira, CC, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Plass, D, Polinder, S, Pourmalek, F, Prokop, DM, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MH, Rahman, SU, Rai, RK, Rajsic, S, Ram, U, Rana, SM, Rao, PV, Remuzzi, G, Rojas-Rueda, D, Ronfani, L, Roshandel, G, Roy, A, Ruhago, GM, Saeedi, MY, Sagar, R, Saleh, MM, Sanabria, JR, Santos, IS, Sarmiento-Suarez, R, Sartorius, B, Sawhney, M, Schutte, AE, Schwebel, DC, Seedat, S, Sepanlou, SG, Servan-Mori, EE, Shaikh, MA, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shibuya, K, Shin, HH, Sigfusdottir, ID, Silpakit, N, Silva, DA, Silveira, DG, Simard, EP, Sindi, S, Singh, JA, Singh, OP, Singh, PK, Skirbekk, V, Sliwa, K, Soneji, S, Sorensen, RJ, Soriano, JB, Soti, DO, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Sunguya, BF, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Talongwa, RT, Tavakkoli, M, Taye, B, Tedla, BA, Tekle, T, Shifa, GT, Temesgen, AM, Terkawi, AS, Tesfay, FH, Tessema, GA, Thapa, K, Thomson, AJ, Thorne-Lyman, AL, Tobe-Gai, R, Topor-Madry, R, Towbin, JA, Tran, BX, Dimbuene, ZT, Tsilimparis, N, Tura, AK, Ukwaja, KN, Uneke, CJ, Uthman, OA, Venketasubramanian, N, Vladimirov, SK, Vlassov, VV, Vollset, SE, Wang, L, Weiderpass, E, Weintraub, RG, Werdecker, A, Westerman, R, Wijeratne, T, Wilkinson, JD, Wiysonge, CS, Wolfe, CD, Won, S, Wong, JQ, Xu, G, Yadav, AK, Yakob, B, Yalew, AZ, Yano, Y, Yaseri, M, Yebyo, HG, Yip, P, Yonemoto, N, Yoon, SJ, Younis, MZ, Yu, C, Yu, S, Zaidi, Z, Zaki, MELS, Zeeb, H, Zhang, H, Zhao, Y, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Lopez, AD, and Murray, CJ
Subjects: GBD 2015 HIV Collaborators
Abstract: BACKGROUND: Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015. METHODS: For countries without high-quality vital registration data, we estimated prevalence and incidence with data from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4 cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS (UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for garbage coding and HIV misclassification. FINDINGS: Global HIV incidence reached its peak in 1997, at 3·3 million new infections (95% uncertainty interval [UI] 3·1-3·4 million). Annual incidence has stayed relatively constant at about 2·6 million per year (range 2·5-2·8 million) since 2005, after a period of fast decline between 1997 and 2005. The number of people living with HIV/AIDS has been steadily increasing and reached 38·8 million (95% UI 37·6-40·4 million) in 2015. At the same time, HIV/AIDS mortality has been declining at a steady pace, from a peak of 1·8 million deaths (95% UI 1·7-1·9 million) in 2005, to 1·2 million deaths (1·1-1·3 million) in 2015. We recorded substantial heterogeneity in the levels and trends of HIV/AIDS across countries. Although many countries have experienced decreases in HIV/AIDS mortality and in annual new infections, other countries have had slowdowns or increases in rates of change in annual new infections. INTERPRETATION: Scale-up of ART and prevention of mother-to-child transmission has been one of the great successes of global health in the past two decades. However, in the past decade, progress in reducing new infections has been slow, development assistance for health devoted to HIV has stagnated, and resources for health in low-income countries have grown slowly. Achievement of the new ambitious goals for HIV enshrined in Sustainable Development Goal 3 and the 90-90-90 UNAIDS targets will be challenging, and will need continued efforts from governments and international agencies in the next 15 years to end AIDS by 2030. Funding: We thank the countless individuals who have contributed to the Global Burden of Disease (GBD) Study 2015 in various capacities. We specifically thank Jeffrey Eaton and John Stover. HW and CJLM received funding for this study from the Bill & Melinda Gates Foundation; the National Institute of Mental Health, National Institutes of Health (NIH; R01MH110163); and the National Institute on Aging, NIH (P30AG047845). LJAR acknowledges the support of Qatar National Research Fund (NPRP 04-924-3-251) who provided the main funding for generating the data provided to the GBD-Institute for Health Metrics and Evaluation effort. BPAQ acknowledges institutional support from PRONABEC (National Program of Scholarship and Educational Loan), provided by the Peruvian government. DB is supported by the Bill & Melinda Gates Foundation (grant number OPP1068048). JDN was supported in his contribution to this work by a Fellowship from Fundacao para a Ciencia e a Tecnologia, Portugal (SFRH/BPD/92934/2013). KD is supported by a Wellcome Trust Fellowship in Public Health and Tropical Medicine (grant number 099876). TF received financial support from the Swiss National Science Foundation (SNSF; project number P300P3-154634). AG acknowledges funding from Sistema Nacional de Investigadores de Panama-SNI. PJ is supported by Wellcome Trust-DBT India Alliance Clinical and Public Health Intermediate Fellowship. MK receives research support from the Academy of Finland, the Swedish Research Council, Alzheimerfonden, Alzheimer's Research & Prevention Foundation, Center for Innovative Medicine (CIMED) at Karolinska Institutet South Campus, AXA Research Fund, Wallenberg Clinical Scholars Award from the Knut och Alice Wallenbergs Foundation, and the Sheika Salama Bint Hamdan Al Nahyan Foundation. AK's work was supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R&D&I and funded by the ISCIII (General Branch Evaluation and Promotion of Health Research), and the European Regional Development Fund (ERDF-FEDER). SML is funded by a National Institute for Health Research (NIHR) Clinician Scientist Fellowship (grant number NIHR/CS/010/014). HJL reports grants from the NIHR, EU Innovative Medicines Initiative, Centre for Strategic & International Studies, and WHO. WM is Program analyst, Population and Development, in the Peru Country Office of the United Nations Population Fund, which does not necessarily endorse this study. For UOM, funding from the German National Cohort Consortium (O1ER1511D) is gratefully acknowledged. KR reports grants from NIHR Oxford Biomedical Research Centre, NIHR Career Development Fellowship, and Oxford Martin School during the conduct of the study. GR acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). ISS reports grants from FAPESP (Brazilian public agency). RSS receives institutional support from Universidad de Ciencias Aplicadas y Ambientales, UDCA, Bogota Colombia. SS receives postdoctoral funding from the Fonds de la recherche en sante du Quebec (FRSQ), including its renewal. RTS was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI14/00894 from ISCIII-FEDER. PY acknowledges support from Strategic Public Policy Research (HKU7003-SPPR-12).
Published: 2016

11. Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015: A systematic analysis from the global burden of disease study 2015

Author: Reitsma, MB, Fullman, N, Ng, M, Salama, JS, Abajobir, A, Abate, KH, Abbafati, C, Abera, SF, Abraham, B, Abyu, GY, Adebiyi, AO, Al-Aly, Z, Aleman, AV, Ali, R, Alkerwi, AA, Allebeck, P, Al-Raddadi, RM, Amare, AT, Amberbir, A, Ammar, W, Amrock, SM, Antonio, CAT, Asayesh, H, Atnafu, NT, Azzopardi, P, Banerjee, A, Barac, A, Barrientos-Gutierrez, T, Basto-Abreu, AC, Bazargan-Hejazi, S, Bedi, N, Bell, B, Bello, AK, Bensenor, IM, Beyene, AS, Bhala, N, Biryukov, S, Bolt, K, Brenner, H, Butt, Z, Cavalleri, F, Cercy, K, Chen, H, Christopher, DJ, Ciobanu, LG, Colistro, V, Colomar, M, Cornaby, L, Dai, X, Damtew, SA, Dandona, L, Dandona, R, Dansereau, E, Davletov, K, Dayama, A, Degfie, TT, Deribew, A, Dharmaratne, SD, DImtsu, BD, Doyle, KE, Endries, AY, Ermakov, SP, Estep, K, Faraon, EJA, Farzadfar, F, Feigin, VL, Feigl, AB, Fischer, F, Friedman, J, Ghiwot, TT, Gall, SL, Gao, W, Gillum, RF, Gold, AL, Gopalani, SV, Gotay, CC, Gupta, R, Gupta, V, Hamadeh, RR, Hankey, G, Harb, HL, Hay, SI, Horino, M, Horita, N, Hosgood, HD, Husseini, A, Ileanu, BV, Islami, F, Jiang, G, Jiang, Y, Jonas, JB, Kabir, Z, Kamal, R, Kasaeian, A, Kesavachandran, CN, Khader, YS, Khalil, I, Khang, YH, Khera, S, Mekonnen, A, Reitsma, MB, Fullman, N, Ng, M, Salama, JS, Abajobir, A, Abate, KH, Abbafati, C, Abera, SF, Abraham, B, Abyu, GY, Adebiyi, AO, Al-Aly, Z, Aleman, AV, Ali, R, Alkerwi, AA, Allebeck, P, Al-Raddadi, RM, Amare, AT, Amberbir, A, Ammar, W, Amrock, SM, Antonio, CAT, Asayesh, H, Atnafu, NT, Azzopardi, P, Banerjee, A, Barac, A, Barrientos-Gutierrez, T, Basto-Abreu, AC, Bazargan-Hejazi, S, Bedi, N, Bell, B, Bello, AK, Bensenor, IM, Beyene, AS, Bhala, N, Biryukov, S, Bolt, K, Brenner, H, Butt, Z, Cavalleri, F, Cercy, K, Chen, H, Christopher, DJ, Ciobanu, LG, Colistro, V, Colomar, M, Cornaby, L, Dai, X, Damtew, SA, Dandona, L, Dandona, R, Dansereau, E, Davletov, K, Dayama, A, Degfie, TT, Deribew, A, Dharmaratne, SD, DImtsu, BD, Doyle, KE, Endries, AY, Ermakov, SP, Estep, K, Faraon, EJA, Farzadfar, F, Feigin, VL, Feigl, AB, Fischer, F, Friedman, J, Ghiwot, TT, Gall, SL, Gao, W, Gillum, RF, Gold, AL, Gopalani, SV, Gotay, CC, Gupta, R, Gupta, V, Hamadeh, RR, Hankey, G, Harb, HL, Hay, SI, Horino, M, Horita, N, Hosgood, HD, Husseini, A, Ileanu, BV, Islami, F, Jiang, G, Jiang, Y, Jonas, JB, Kabir, Z, Kamal, R, Kasaeian, A, Kesavachandran, CN, Khader, YS, Khalil, I, Khang, YH, Khera, S, and Mekonnen, A
Abstract: Background The scale-up of tobacco control, especially after the adoption of the Framework Convention for Tobacco Control, is a major public health success story. Nonetheless, smoking remains a leading risk for early death and disability worldwide, and therefore continues to require sustained political commitment. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) offers a robust platform through which global, regional, and national progress toward achieving smoking-related targets can be assessed. Methods We synthesised 2818 data sources with spatiotemporal Gaussian process regression and produced estimates of daily smoking prevalence by sex, age group, and year for 195 countries and territories from 1990 to 2015. We analysed 38 risk-outcome pairs to generate estimates of smoking-attributable mortality and disease burden, as measured by disability-adjusted life-years (DALYs). We then performed a cohort analysis of smoking prevalence by birth-year cohort to better understand temporal age patterns in smoking. We also did a decomposition analysis, in which we parsed out changes in all-cause smoking-attributable DALYs due to changes in population growth, population ageing, smoking prevalence, and risk-deleted DALY rates. Finally, we explored results by level of development using the Socio-demographic Index (SDI). Findings Worldwide, the age-standardised prevalence of daily smoking was 25·0% (95% uncertainty interval [UI] 24·2-25·7) for men and 5·4% (5·1-5·7) for women, representing 28·4% (25·8-31·1) and 34·4% (29·4-38·6) reductions, respectively, since 1990. A greater percentage of countries and territories achieved significant annualised rates of decline in smoking prevalence from 1990 to 2005 than in between 2005 and 2015; however, only four countries had significant annualised increases in smoking prevalence between 2005 and 2015 (Congo [Brazzaville] and Azerbaijan
Published: 2017

12. Oropharyngeal fetus-in fetu in Ilero Nigeria: A case report

Author: Adebiyi, AO, primary, Shorunmu, TO, additional, Owoeye, T, additional, Amoran, OE, additional, and Ojeleke, AA, additional
Published: 2017
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13. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2015: the Global Burden of Disease Study 2015

Author: Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Larson, HJ, Friedman, J, Brown, A, Dandona, L, Fullman, N, Haagsma, J, Khalil, I, Lim, SS, Mikesell, J, Mokdad, AH, Moradi-Lakeh, M, Pearson, K, Silpakit, B, Sorensen, MJD, Temesgen, AM, Vollset, SE, Zoeckler, L, Murray, CJL, Alfonso-Cristancho, R, Harun, KM, Prokop, DM, Mills, EJ, Trickey, A, Ajala, ON, Bärnighausen, T, Ding, EL, Farvid, MS, Thorne-Lyman, AL, Won, S, Fitchett, JRA, Salomon, J, Abajobir, AA, Hoy, DG, Alam, NKM, Abate, KH, Ghiwot, TT, Gebremedhin, AT, Abbas, KM, Abd El Razek, MM, Abd-Allah, F, Abdulle, AM, Abera, SF, Melaku, YA, Tesfay, Fisaha, Abyu, GY, Bayou, TA, Betsu, BD, Gebru, AA, Hailu, GB, Tekle, T, Yalew, AZ, Yebyo, HG, Abubakar, I, Aldridge, RW, Abu-Raddad, LJ, Abu-Rmeileh, NME, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Ojelabi, FA, Adofo, K, Adou, AK, Akinyemiju, TF, Schwebel, DC, Singh, JA, Akseer, N, Al Lami, FH, Al-Aly, Z, Alam, K, Weintraub, RG, Chiang, PP, Meretoja, A, Lopez, AD, Wijeratne, T, Driscoll, TR, Kemp, AH, Leigh, J, Mekonnen, Alemayehu, Karema, CK, Alasfoor, D, Aldhahri, SFS, Terkawi, AS, Alegretti, MA, Aleman, AV, Alemu, ZA, Cooper, C, Deribew, A, Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Larson, HJ, Friedman, J, Brown, A, Dandona, L, Fullman, N, Haagsma, J, Khalil, I, Lim, SS, Mikesell, J, Mokdad, AH, Moradi-Lakeh, M, Pearson, K, Silpakit, B, Sorensen, MJD, Temesgen, AM, Vollset, SE, Zoeckler, L, Murray, CJL, Alfonso-Cristancho, R, Harun, KM, Prokop, DM, Mills, EJ, Trickey, A, Ajala, ON, Bärnighausen, T, Ding, EL, Farvid, MS, Thorne-Lyman, AL, Won, S, Fitchett, JRA, Salomon, J, Abajobir, AA, Hoy, DG, Alam, NKM, Abate, KH, Ghiwot, TT, Gebremedhin, AT, Abbas, KM, Abd El Razek, MM, Abd-Allah, F, Abdulle, AM, Abera, SF, Melaku, YA, Tesfay, Fisaha, Abyu, GY, Bayou, TA, Betsu, BD, Gebru, AA, Hailu, GB, Tekle, T, Yalew, AZ, Yebyo, HG, Abubakar, I, Aldridge, RW, Abu-Raddad, LJ, Abu-Rmeileh, NME, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Ojelabi, FA, Adofo, K, Adou, AK, Akinyemiju, TF, Schwebel, DC, Singh, JA, Akseer, N, Al Lami, FH, Al-Aly, Z, Alam, K, Weintraub, RG, Chiang, PP, Meretoja, A, Lopez, AD, Wijeratne, T, Driscoll, TR, Kemp, AH, Leigh, J, Mekonnen, Alemayehu, Karema, CK, Alasfoor, D, Aldhahri, SFS, Terkawi, AS, Alegretti, MA, Aleman, AV, Alemu, ZA, Cooper, C, and Deribew, A
Abstract: Background Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015. Methods For countries without high-quality vital registration data, we estimated prevalence and incidence with data from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4 cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS (UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for garbage coding and HIV misclassification. Findings Global HIV incidence reached its peak in 1997, at 3·3 million new infections (95% uncertainty interval [UI] 3·1–3·4 million). Annual incidence has stayed relatively constant at about 2·6 mil
Published: 2016

14. Global, regional, and national levels of maternal mortality, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Author: Kassebaum, NJ, Barber, RM, Bhutta, ZA, Dandona, L, Gething, PW, Hay, SI, Kinfu, Y, Larson, HJ, Liang, X, Lim, SS, Lopez, AD, Lozano, R, Mensah, GA, Mokdad, AH, Naghavi, M, Pinho, C, Salomon, JA, Steiner, C, Vos, T, Wang, H, Abajobir, AA, Abate, KH, Abbas, KM, Abd-Allah, F, Abdallat, MA, Abdulle, AM, Abera, SF, Aboyans, V, Abubakar, I, Abu-Rmeileh, NME, Achoki, T, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adou, AK, Afanvi, KA, Agarwal, A, Kiadaliri, AA, Ajala, ON, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SF, Aldridge, RW, Alhabib, S, Ali, R, Alkerwi, A, Alla, F, Al-Raddadi, R, Alsharif, U, Martin, EA, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Andersen, HH, Anderson, GM, Antoine, RM, Antonio, CAT, Aregay, AF, Arnlov, J, Arora, M, Arsenijevic, VSA, Al, A, Asayesh, H, Atique, S, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Azzopardi, P, Bacha, U, Badawi, A, Bahit, MC, Balakrishnan, K, Banerjee, A, Barac, A, Barker-Collo, SL, Barnighausen, T, Basu, S, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, NW, Bekele, T, Bell, ML, Bennett, DA, Bensenor, IM, Berhane, A, Bernabe, E, Betsu, BD, Beyene, AS, Biadgilign, S, Bikbov, B, Bin Abdulhak, AA, Biroscak, BJ, Biryukov, S, Bisanzio, D, Bjertness, E, Blore, JD, Brainin, M, Brazinova, A, Breitborde, NJK, Brugha, TS, Butt, ZA, Campos-Nonato, IR, Campuzano, JC, Cardenas, R, Carrero, JJ, Carter, A, Casey, DC, Castaneda-Oquela, CA, Castro, RE, Catala-Lopez, F, Cavalleri, F, Chang, H-Y, Chang, J-C, Chavan, L, Chibueze, CE, Chisumpa, VH, Choi, J-YJ, Chowdhury, R, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coates, MM, Coggeshall, M, Colistro, V, Colquhoun, SM, Cooper, C, Cooper, LT, Cortinovis, M, Dahiru, T, Damasceno, A, Danawi, H, Dandona, R, Das Neves, J, De Leo, D, Dellavalle, RP, Deribe, K, Deribew, A, Jarlais, DCD, Dharmaratne, SD, Dicker, DJ, Ding, EL, Dossou, E, Dubey, M, Ebel, BE, Ellingsen, CL, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fernandes, JC, Fischer, F, Fitchett, JRA, Fleming, T, Gt, NF, Franca, EB, Franklin, RC, Fraser, MS, Friedman, J, Pullman, N, Furst, T, Futran, ND, Gambashidze, K, Gamkrelidze, A, Gebre, T, Gebrehiwot, TT, Gebremedhin, AT, Gebremedhin, M, Gebru, AA, Geleijnse, JM, Gibney, KB, Giref, AZ, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Gomez-Dantes, H, Gona, P, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Gugnani, HC, Guo, Y, Gupta, R, Gupta, V, Hafezi-Nejad, N, Hailu, AD, Hailu, GB, Hamadeh, RR, Hamidi, S, Hancock, J, Handal, AJ, Hankey, GJ, Harb, HL, Harikrishnan, S, Harun, KM, Havmoeller, R, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huybrechts, I, Huynh, C, Iannarone, M, Iburg, KM, Idrisov, BT, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jee, SH, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Kazanjan, K, Kazi, DS, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Keren, A, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khan, AR, Khan, EA, Khang, Y-H, Khonelidze, I, Khosravi, A, Khubchandani, J, Kim, YJ, Kivipelto, M, Knibbs, LD, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Krishnaswami, S, Defo, BK, Bicer, BK, Kudom, AA, Kulikoff, XR, Kulkarni, C, Kumar, GA, Kutz, MJ, Lal, DK, Lalloo, R, Lam, H, Lamadrid-Figueroa, H, Lan, Q, Larsson, A, Laryea, DO, Leigh, J, Leung, R, Li, Y, Lipshultz, SE, Liu, PY, Liu, S, Liu, Y, Lloyd, BK, Lotufo, PA, Lunevicius, R, Ma, S, El Razek, HMA, El Razek, MMA, Majdan, M, Majeed, A, Malekzadeh, R, Mapoma, CC, Marcenes, W, Margolis, DJ, Marquez, N, Masiye, F, Marzan, MB, Mason-Jones, AJ, Mazorodze, TT, Meaney, PA, Mehari, A, Mehndiratta, MM, Mena-Rodriguez, F, Mekonnen, AB, Melaku, YA, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mills, EJ, Mirarefin, M, Misganaw, A, Ibrahim, NM, Mohammad, KA, Mohammadi, A, Mohammed, S, Mola, GLD, Monasta, L, Monis, JDLC, Hernandez, JCM, Montero, P, Montico, M, Mooney, MD, Moore, AR, Moradi-Lakeh, M, Morawska, L, Mori, R, Mueller, U, Murthy, GVS, Murthy, S, Nachega, JB, Naheed, A, Naldi, L, Nand, D, Nangia, V, Nash, D, Neupane, S, Newton, JN, Ng, M, Ngalesoni, FN, Nguhiu, P, Nguyen, G, Le Nguyen, Q, Nisar, MI, Nomura, M, Norheim, OF, Norman, RE, Nyakarahuka, L, Obermeyer, CM, Ogbo, FA, Oh, I-H, Ojelabi, FA, Olivares, PR, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Oyekale, AS, Pa, M, Pain, A, Papantoniou, N, Park, E-K, Park, H-Y, Caicedo, AJP, Patten, SB, Paul, VK, Pereira, DM, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Pishgar, F, Polinder, S, Pope, D, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rahman, SU, Rai, RK, Ram, U, Ranabhat, CL, Rangaswamy, T, Rao, PV, Refaat, AH, Remuzzi, G, Violante, FS, Kassebaum, NJ, Barber, RM, Bhutta, ZA, Dandona, L, Gething, PW, Hay, SI, Kinfu, Y, Larson, HJ, Liang, X, Lim, SS, Lopez, AD, Lozano, R, Mensah, GA, Mokdad, AH, Naghavi, M, Pinho, C, Salomon, JA, Steiner, C, Vos, T, Wang, H, Abajobir, AA, Abate, KH, Abbas, KM, Abd-Allah, F, Abdallat, MA, Abdulle, AM, Abera, SF, Aboyans, V, Abubakar, I, Abu-Rmeileh, NME, Achoki, T, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adou, AK, Afanvi, KA, Agarwal, A, Kiadaliri, AA, Ajala, ON, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SF, Aldridge, RW, Alhabib, S, Ali, R, Alkerwi, A, Alla, F, Al-Raddadi, R, Alsharif, U, Martin, EA, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Andersen, HH, Anderson, GM, Antoine, RM, Antonio, CAT, Aregay, AF, Arnlov, J, Arora, M, Arsenijevic, VSA, Al, A, Asayesh, H, Atique, S, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Azzopardi, P, Bacha, U, Badawi, A, Bahit, MC, Balakrishnan, K, Banerjee, A, Barac, A, Barker-Collo, SL, Barnighausen, T, Basu, S, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, NW, Bekele, T, Bell, ML, Bennett, DA, Bensenor, IM, Berhane, A, Bernabe, E, Betsu, BD, Beyene, AS, Biadgilign, S, Bikbov, B, Bin Abdulhak, AA, Biroscak, BJ, Biryukov, S, Bisanzio, D, Bjertness, E, Blore, JD, Brainin, M, Brazinova, A, Breitborde, NJK, Brugha, TS, Butt, ZA, Campos-Nonato, IR, Campuzano, JC, Cardenas, R, Carrero, JJ, Carter, A, Casey, DC, Castaneda-Oquela, CA, Castro, RE, Catala-Lopez, F, Cavalleri, F, Chang, H-Y, Chang, J-C, Chavan, L, Chibueze, CE, Chisumpa, VH, Choi, J-YJ, Chowdhury, R, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coates, MM, Coggeshall, M, Colistro, V, Colquhoun, SM, Cooper, C, Cooper, LT, Cortinovis, M, Dahiru, T, Damasceno, A, Danawi, H, Dandona, R, Das Neves, J, De Leo, D, Dellavalle, RP, Deribe, K, Deribew, A, Jarlais, DCD, Dharmaratne, SD, Dicker, DJ, Ding, EL, Dossou, E, Dubey, M, Ebel, BE, Ellingsen, CL, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fernandes, JC, Fischer, F, Fitchett, JRA, Fleming, T, Gt, NF, Franca, EB, Franklin, RC, Fraser, MS, Friedman, J, Pullman, N, Furst, T, Futran, ND, Gambashidze, K, Gamkrelidze, A, Gebre, T, Gebrehiwot, TT, Gebremedhin, AT, Gebremedhin, M, Gebru, AA, Geleijnse, JM, Gibney, KB, Giref, AZ, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Gomez-Dantes, H, Gona, P, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Gugnani, HC, Guo, Y, Gupta, R, Gupta, V, Hafezi-Nejad, N, Hailu, AD, Hailu, GB, Hamadeh, RR, Hamidi, S, Hancock, J, Handal, AJ, Hankey, GJ, Harb, HL, Harikrishnan, S, Harun, KM, Havmoeller, R, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huybrechts, I, Huynh, C, Iannarone, M, Iburg, KM, Idrisov, BT, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jee, SH, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Kazanjan, K, Kazi, DS, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Keren, A, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khan, AR, Khan, EA, Khang, Y-H, Khonelidze, I, Khosravi, A, Khubchandani, J, Kim, YJ, Kivipelto, M, Knibbs, LD, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Krishnaswami, S, Defo, BK, Bicer, BK, Kudom, AA, Kulikoff, XR, Kulkarni, C, Kumar, GA, Kutz, MJ, Lal, DK, Lalloo, R, Lam, H, Lamadrid-Figueroa, H, Lan, Q, Larsson, A, Laryea, DO, Leigh, J, Leung, R, Li, Y, Lipshultz, SE, Liu, PY, Liu, S, Liu, Y, Lloyd, BK, Lotufo, PA, Lunevicius, R, Ma, S, El Razek, HMA, El Razek, MMA, Majdan, M, Majeed, A, Malekzadeh, R, Mapoma, CC, Marcenes, W, Margolis, DJ, Marquez, N, Masiye, F, Marzan, MB, Mason-Jones, AJ, Mazorodze, TT, Meaney, PA, Mehari, A, Mehndiratta, MM, Mena-Rodriguez, F, Mekonnen, AB, Melaku, YA, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mills, EJ, Mirarefin, M, Misganaw, A, Ibrahim, NM, Mohammad, KA, Mohammadi, A, Mohammed, S, Mola, GLD, Monasta, L, Monis, JDLC, Hernandez, JCM, Montero, P, Montico, M, Mooney, MD, Moore, AR, Moradi-Lakeh, M, Morawska, L, Mori, R, Mueller, U, Murthy, GVS, Murthy, S, Nachega, JB, Naheed, A, Naldi, L, Nand, D, Nangia, V, Nash, D, Neupane, S, Newton, JN, Ng, M, Ngalesoni, FN, Nguhiu, P, Nguyen, G, Le Nguyen, Q, Nisar, MI, Nomura, M, Norheim, OF, Norman, RE, Nyakarahuka, L, Obermeyer, CM, Ogbo, FA, Oh, I-H, Ojelabi, FA, Olivares, PR, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Oyekale, AS, Pa, M, Pain, A, Papantoniou, N, Park, E-K, Park, H-Y, Caicedo, AJP, Patten, SB, Paul, VK, Pereira, DM, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Pishgar, F, Polinder, S, Pope, D, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rahman, SU, Rai, RK, Ram, U, Ranabhat, CL, Rangaswamy, T, Rao, PV, Refaat, AH, Remuzzi, G, and Violante, FS
Abstract: BACKGROUND: In transitioning from the Millennium Development Goal to the Sustainable Development Goal era, it is imperative to comprehensively assess progress toward reducing maternal mortality to identify areas of success, remaining challenges, and frame policy discussions. We aimed to quantify maternal mortality throughout the world by underlying cause and age from 1990 to 2015. METHODS: We estimated maternal mortality at the global, regional, and national levels from 1990 to 2015 for ages 10-54 years by systematically compiling and processing all available data sources from 186 of 195 countries and territories, 11 of which were analysed at the subnational level. We quantified eight underlying causes of maternal death and four timing categories, improving estimation methods since GBD 2013 for adult all-cause mortality, HIV-related maternal mortality, and late maternal death. Secondary analyses then allowed systematic examination of drivers of trends, including the relation between maternal mortality and coverage of specific reproductive health-care services as well as assessment of observed versus expected maternal mortality as a function of Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. FINDINGS: Only ten countries achieved MDG 5, but 122 of 195 countries have already met SDG 3.1. Geographical disparities widened between 1990 and 2015 and, in 2015, 24 countries still had a maternal mortality ratio greater than 400. The proportion of all maternal deaths occurring in the bottom two SDI quintiles, where haemorrhage is the dominant cause of maternal death, increased from roughly 68% in 1990 to more than 80% in 2015. The middle SDI quintile improved the most from 1990 to 2015, but also has the most complicated causal profile. Maternal mortality in the highest SDI quintile is mostly due to other direct maternal disorders, indirect maternal disorders, and abortion, ectopic pregnancy
Published: 2016

15. Health Literacy Amongst Tuberculosis Patient in a General Hospital in North Central Nigeria

Author: Oladunjoye, AO, Adebiyi, AO, Cadmus, EO, Ige, OK, and Oladunjoye, OO
Subjects: Health Literacy, Tuberculosis, General Hospital, Nigeria
Abstract: Background: Healthy literacy has been shown to improve health care access and adherence to Tuberculosis (TB) treatment. Still it remains largely unstudied in many high risks, underserved and low literacy African populations. This study aims to bridge the existing knowledge gap by assessing health literacy among patients with TB in a rural town in Northern Nigeria.Methodology: A cross sectional study was conducted among patients who attended the TB clinic of a secondary health care facility in Babura, Jigawa State, Nigeria between Oct 2008 and March 2009. All patients who visited the TB clinic during this period were interviewed.Result: Many (71.6%) reported having been educated about TB by a health worker, mostly on predisposing factors 43.2%, general facts (31.1%) and disease process (21.6%) but less on patient's role in disease management (1.4%). Functional health literacy was high; mean score was 7.9±0.3 out of 10. Knowledge about the disease process, diagnostic requirements and treatment regimen were the highest. However 97.3% felt drugs were no longer necessary once symptoms abated. Patient involvement in treatment decisions was also suboptimal as only 52.7% reported making a joint decision about drug “pick up” options with their physicians.Conclusion: Very high functional literacy score seemed to have been achieved among these rural low literacy TB patients even without a structured health literacy program. However patient participation in treatment seems to be underemphasized and was thus suboptimal. An important gap in patient education regarding continued TB treatment was identified and should be targeted for intervention.Keywords: Health Literacy, Tuberculosis, General Hospital, Nigeria
Published: 2013

16. Biological studies on albino rats fed with Sorghum bicolorstarch hydrolyzed with &#8733-amylase from Rhizopus sp

Author: Adebiyi, AO, Oladipo, IC, Ayandele, AA, Adebiyi, AP, and Adelowo, OO
Subjects: &#8733-Amylase, Rhizopus sp., Sorghum bicolor starch, hydrolysis, feed formulation, biological studies, albino rats
Abstract: Partially purified amylase was extracted from the culture medium of Rhizopus sp. grown in potato dextrose broth for 48 h at room temperature by precipitation with 96.9% ethanol. The enzyme was usedto hydrolyze sorghum starch. The hydrolyzed product was afterwards formulated into rat feed, which was fed to albino rats for a period of thirty days. The average daily body weight of the albino rats fed with hydrolyzed formulated feed on the 30th day of the experiment was 131 g while the values recorded for the groups fed with unhydrolyzed and commercial feed were 120 and 97.4 grams respectively. Thehematological analysis revealed that the packed cell volume (PCV), Hemoglobin (Hb), red blood cells (RBC), mean cell hemoglobin concentration (MCHC) of the group fed with hydrolyzed formulated feed of 51.8%, 16.9 g/dl, 8.7 x 105 ƒÊl-1 and 32.7%, respectively, were higher than the experimental animals fed with commercial feed with values of 44.2%, 14.4 g/dl, 7.7 x 105
Published: 2010

17. The phytochemical analysis and antimicrobial screening of extracts of Olax subscorpioidea

Author: Ayandele, AA and Adebiyi, AO
Subjects: Antimicrobial activity, bacteria, fungi, alkaloids, tannins, glycosides, steroids, flavonoids, saponins
Abstract: The antimicrobial activities of the aqueous and ethanoic extracts of the stem of Olax subscorpioidea were evaluated. The ethanoic extract showed considerable activity on both the fungi and bacteria with zones of inhibition ranging from 7.2 mm to 21.5 mm, with minimum inhibitory concentrations ranging from 5 to 45 mg/ml, while the aqueous extract was only active against three of the test organisms used. Phytochemical test reveals the presence of alkaloids, steroids, and flavonoids together with otheractive ingredients in the ethanoic extract with the exception of saponins which is present in the aqueous extract alone.
Published: 2010

18. Condom use amongst out of school youths in a local government area in Nigeria

Author: Adebiyi, AO and Asuzu, MC
Abstract: Background: Reported low condom use amongst out of school requires studying the context in which condom use occurs.Methods: A cross sectional study of 350 out-of-school youth aged 15-24 years in a local government area of Nigeria was enrolledusing cluster sampling.Results: Those who had ever had sexual intercourse were 74.9%. Of these, 56.5% used no protection while 29.0% used condoms. Up to 78.6% have had sex within the preceding 12 months with 38.9% condom use. The commonest reason for non-condom use was that it reduces sexual enjoyment. Those who believed a single unprotected sexual exposure may result in HIV infection reported more condom use than those who believed otherwise (42% vs 27.2%, P
Published: 2009

19. Risk factors Schistosoma hematobium in Ajelanwa area of Oyo state, Nigeria

Author: Adebiyi, AO, Asuzu, MC, Sangowawa, AO, and Olatunji, MB
Subjects: Schistosoma hematobium, risk factors, infection, Oyo State
Abstract: Infection with Schistosoma hematobium has been on the rise in developing countries with studies done in Nigeria alluding to the risk factors for infection. However, these risks factors have often not been properly described in the context in which they occurred. This study aims to describe the situation in which these risk factors occur in a rural pcpulation. A cross sectional study of children aged 5 to 24 years was conducted in a rural transborder community in Nigeria using a systematic random sampling method. Five hundred and thirty one participants were interviewed and examined for anaemia, cleanliness and skin infections, while a mid-day urine sample was taken for microscopic identification of S haematobium. A large proportion of respondents were either dirty 271 (51.0%) or unkempt - uncut nails, unkempt hair and tattered clothes 105 (19.8%) with 11 (2.1 %) having scabies. Clinically detectable anaemia was present in 153 (28.8%) of the subjects. The prevalence rate of S haematobium was 14% in the study population with those within the ages 15 and 19 having the highest prevalence figure of 16.5%. Males were also more infected 48 (15.1%) than females 26 (12.2%). The risk factors for infection were water activities like swimming (OR 2.97,95% CI 1.55 - 5.77) and bathing (OR 3.22, 95% CI 1.53 - 6.79). In addition water visitation in the afternoon was also a risk factor for infection (OR 4.21,95% CI 1.85 - 9.93). It is advocated that water contact activities be reduced in areas at increased risk of infection with S haematobium. Nigerian Medical Practitioner Vol. 54 (1) 2008: pp. 3-7
Published: 2008

20. Comparative Studies on Mosses for Heavy Metals Pollution Monitoring in Sub-Urban and Rural Towns in Ekiti State

Author: Adebiyi, AO, primary and Oyedeji, AA, additional
Published: 2012
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21. Falls and outcomes amongst old people in rural dwellings

Author: Adebiyi, AO, primary, Uchendu, OC, additional, Ikotun, OT, additional, and Oluleye, OW, additional
Published: 2011
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22. Socio-demographic characteristics of street children in rural communities undergoing urbanization

Author: Owoaje, ET, primary, Adebiyi, AO, additional, and Asuzu, MC, additional
Published: 2011
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23. Relationships as determinants of substance use amongst street children in a local government area in south-western Nigeria

Author: Adebiyi, AO, primary, Owoaje, O, additional, and Asuzu, MC, additional
Published: 2008
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24. Health problems of the elderly in a rural community in Southwestern Nigeria.

Author: Uchendu OC, Adebiyi AO, Sangowawa AO, Adebayo AM, Ige OK, Fajola A, Ige-Orhionpaibima SF, Ezeakili OE, Otesile OA, Osuji NN, and Ajayi AO
Published: 2008

25. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Author: Vos, Theo, Allen, Christine, Arora, Megha, Barber, Ryan M, Bhutta, Zulfiqar A, Brown, Alexandria, Carter, Austin, Casey, Daniel C, Charlson, Fiona J, Chen, Alan Z, Coggeshall, Megan, Cornaby, Leslie, Dandona, Lalit, Dicker, Daniel J, Dilegge, Tina, Erskine, Holly E, Ferrari, Alize J, Fitzmaurice, Christina, Fleming, Tom, Forouzanfar, Mohammad H, Fullman, Nancy, Gething, Peter W, Goldberg, Ellen M, Graetz, Nicholas, Haagsma, Juanita A, Hay, Simon I, Johnson, Catherine O, Kassebaum, Nicholas J, Kawashima, Toana, Kemmer, Laura, Khalil, Ibrahim A, Kinfu, Yohannes, Kyu, Hmwe H, Leung, Janni, Liang, Xiaofeng, Lim, Stephen S, Lopez, Alan D, Lozano, Rafael, Marczak, Laurie, Mensah, George A, Mokdad, Ali H, Naghavi, Mohsen, Nguyen, Grant, Nsoesie, Elaine, Olsen, Helen, Pigott, David M, Pinho, Christine, Rankin, Zane, Reinig, Nikolas, Salomon, Joshua A, Sandar, Logan, Smith, Alison, Stanaway, Jeffrey, Steiner, Caitlyn, Teeple, Stephanie, Thomas, Bernadette A, Troeger, Christopher, Wagner, Joseph A, Wang, Haidong, Wanga, Valentine, Whiteford, Harvey A, Zoeckler, Leo, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abraham, Biju, Abubakar, Ibrahim, Abu-Raddad, Laith J, Abu-Rmeileh, Niveen M E, Ackerman, Ilana N, Adebiyi, Akindele Olupelumi, Ademi, Zanfina, Adou, Arsène Kouablan, Afanvi, Kossivi Agbelenko, Agardh, Emilie Elisabet, Agarwal, Arnav, Kiadaliri, Aliasghar Ahmad, Ahmadieh, Hamid, Ajala, Oluremi N, Akinyemi, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore K M, Aldhahri, Saleh Fahed, Alegretti, Miguel Angel, Alemu, Zewdie Aderaw, Alexander, Lily T, Alhabib, Samia, Ali, Raghib, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amberbir, Alemayehu, Amini, Heresh, Ammar, Walid, Amrock, Stephen Marc, Andersen, Hjalte H, Anderson, Gregory M, Anderson, Benjamin O, Antonio, Carl Abelardo T, Aregay, Atsede Fantahun, Ärnlöv, Johan, Artaman, Al, Asayesh, Hamid, Assadi, Reza, Atique, Suleman, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Azzopardi, Peter, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Banerjee, Amitava, Barac, Aleksandra, Barker-Collo, Suzanne L, Bärnighausen, Till, Barregard, Lars, Barrero, Lope H, Basu, Arindam, Bazargan-Hejazi, Shahrzad, Beghi, Ettore, Bell, Brent, Bell, Michelle L, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Bernabé, Eduardo, Betsu, Balem Demtsu, Beyene, Addisu Shunu, Bhala, Neeraj, Bhatt, Samir, Biadgilign, Sibhatu, Bienhoff, Kelly, Bikbov, Boris, Biryukov, Stan, Bisanzio, Donal, Bjertness, Espen, Blore, Jed, Borschmann, Rohan, Boufous, Soufiane, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brown, Jonathan, Buchbinder, Rachelle, Buckle, Geoffrey Colin, Butt, Zahid A, Calabria, Bianca, Campos-Nonato, Ismael Ricardo, Campuzano, Julio Cesar, Carabin, Hélène, Cárdenas, Rosario, Carpenter, David O, Carrero, Juan Jesus, Castañeda-Orjuela, Carlos A, Rivas, Jacqueline Castillo, Catalá-López, Ferrán, Chang, Jung-Chen, Chiang, Peggy Pei-Chia, Chibueze, Chioma Ezinne, Chisumpa, Vesper Hichilombwe, Choi, Jee-Young Jasmine, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam Jesudas, Ciobanu, Liliana G, Cirillo, Massimo, Coates, Matthew M, Colquhoun, Samantha M, Cooper, Cyrus, Cortinovis, Monica, Crump, John A, Damtew, Solomon Abrha, Dandona, Rakhi, Daoud, Farah, Dargan, Paul I, das Neves, José, Davey, Gail, Davis, Adrian C, Leo, Diego De, Degenhardt, Louisa, Gobbo, Liana C Del, Dellavalle, Robert P, Deribe, Kebede, Deribew, Amare, Derrett, Sarah, Jarlais, Don C Des, Dharmaratne, Samath D, Dhillon, Preet K, Diaz-Torné, Cesar, Ding, Eric L, Driscoll, Tim R, Duan, Leilei, Dubey, Manisha, Duncan, Bruce Bartholow, Ebrahimi, Hedyeh, Ellenbogen, Richard G, Elyazar, Iqbal, Endres, Matthias, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Eshrati, Babak, Estep, Kara, Farid, Talha A, Farinha, Carla Sofia e Sa, Faro, André, Farvid, Maryam S, Farzadfar, Farshad, Feigin, Valery L, Felson, David T, Fereshtehnejad, Seyed-Mohammad, Fernandes, Jefferson G, Fernandes, Joao C, Fischer, Florian, Fitchett, Joseph R A, Foreman, Kyle, Fowkes, F Gerry R, Fox, Jordan, Franklin, Richard C, Friedman, Joseph, Frostad, Joseph, Fürst, Thomas, Futran, Neal D, Gabbe, Belinda, Ganguly, Parthasarathi, Gankpé, Fortuné Gbètoho, Gebre, Teshome, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Geleijnse, Johanna M, Gessner, Bradford D, Gibney, Katherine B, Ginawi, Ibrahim Abdelmageem Mohamed, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Glaser, Elizabeth, Godwin, William W, Gomez-Dantes, Hector, Gona, Philimon, Goodridge, Amador, Gopalani, Sameer Vali, Gotay, Carolyn C, Goto, Atsushi, Gouda, Hebe N, Grainger, Rebecca, Greaves, Felix, Guillemin, Francis, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Vipin, Gutiérrez, Reyna A, Haile, Demewoz, Hailu, Alemayehu Desalegne, Hailu, Gessessew Bugssa, Halasa, Yara A, Hamadeh, Randah Ribhi, Hamidi, Samer, Hammami, Mouhanad, Hancock, Jamie, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Havmoeller, Rasmus, Hay, Roderick J, Heredia-Pi, Ileana Beatriz, Heydarpour, Pouria, Hoek, Hans W, Horino, Masako, Horita, Nobuyuki, Hosgood, H Dean, Hoy, Damian G, Htet, Aung Soe, Huang, Hsiang, Huang, John J, Huynh, Chantal, Iannarone, Marissa, Iburg, Kim Moesgaard, Innos, Kaire, Inoue, Manami, Iyer, Veena J, Jacobsen, Kathryn H, Jahanmehr, Nader, Jakovljevic, Mihajlo B, Javanbakht, Mehdi, Jayaraman, Sudha P, Jayatilleke, Achala Upendra, Jee, Sun Ha, Jeemon, Panniyammakal, Jensen, Paul N, Jiang, Ying, Jibat, Tariku, Jimenez-Corona, Aida, Jin, Ye, Jonas, Jost B, Kabir, Zubair, Kalkonde, Yogeshwar, Kamal, Ritul, Kan, Haidong, Karch, André, Karema, Corine Kakizi, Karimkhani, Chante, Kasaeian, Amir, Kaul, Anil, Kawakami, Norito, Keiyoro, Peter Njenga, Kemp, Andrew Haddon, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khan, Abdur Rahman, Khan, Ejaz Ahmad, Khang, Young-Ho, Khera, Sahil, Khoja, Tawfik Ahmed Muthafer, Khubchandani, Jagdish, Kieling, Christian, Kim, Pauline, Kim, Cho-il, Kim, Daniel, Kim, Yun Jin, Kissoon, Niranjan, Knibbs, Luke D, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kotsakis, Georgios A, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kudom, Andreas A, Kuipers, Ernst J, Kumar, G Anil, Kutz, Michael, Kwan, Gene F, Lal, Aparna, Lalloo, Ratilal, Lallukka, Tea, Lam, Hilton, Lam, Jennifer O, Langan, Sinead M, Larsson, Anders, Lavados, Pablo M, Leasher, Janet L, Leigh, James, Leung, Ricky, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Juan, Liu, Shiwei, Liu, Yang, Lloyd, Belinda K, Lo, Warren D, Logroscino, Giancarlo, Looker, Katharine J, Lotufo, Paulo A, Lunevicius, Raimundas, Lyons, Ronan A, Mackay, Mark T, Magdy, Mohammed, Razek, Abd El, Mahdavi, Mahdi, Majdan, Marek, Majeed, Azeem, Malekzadeh, Reza, Marcenes, Wagner, Margolis, David Joel, Martinez-Raga, Jose, Masiye, Felix, Massano, João, McGarvey, Stephen Theodore, McGrath, John J, McKee, Martin, McMahon, Brian J, Meaney, Peter A, Mehari, Alem, Mejia-Rodriguez, Fabiola, Mekonnen, Alemayehu B, Melaku, Yohannes Adama, Memiah, Peter, Memish, Ziad A, Mendoza, Walter, Meretoja, Atte, Meretoja, Tuomo J, Mhimbira, Francis Apolinary, Millear, Anoushka, Miller, Ted R, Mills, Edward J, Mirarefin, Mojde, Mitchell, Philip B, Mock, Charles N, Mohammadi, Alireza, Mohammed, Shafiu, Monasta, Lorenzo, Hernandez, Julio Cesar Montañez, Montico, Marcella, Mooney, Meghan D, Moradi-Lakeh, Maziar, Morawska, Lidia, Mueller, Ulrich O, Mullany, Erin, Mumford, John Everett, Murdoch, Michele E, Nachega, Jean B, Nagel, Gabriele, Naheed, Aliya, Naldi, Luigi, Nangia, Vinay, Newton, John N, Ng, Marie, Ngalesoni, Frida Namnyak, Nguyen, Quyen Le, Nisar, Muhammad Imran, Pete, Patrick Martial Nkamedjie, Nolla, Joan M, Norheim, Ole F, Norman, Rosana E, Norrving, Bo, Nunes, Bruno P, Ogbo, Felix Akpojene, Oh, In-Hwan, Ohkubo, Takayoshi, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ortiz, Alberto, Osman, Majdi, Ota, Erika, PA, Mahesh, Park, Eun-Kee, Parsaeian, Mahboubeh, de Azeredo Passos, Valéria Maria, Caicedo, Angel J Paternina, Patten, Scott B, Patton, George C, Pereira, David M, Perez-Padilla, Rogelio, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael Robert, Piel, Frédéric B, Pillay, Julian David, Pishgar, Farhad, Plass, Dietrich, Platts-Mills, James A, Polinder, Suzanne, Pond, Constance D, Popova, Svetlana, Poulton, Richie G, Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Noela M, Qorbani, Mostafa, Rabiee, Rynaz H S, Radfar, Amir, Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Rao, Puja, Refaat, Amany H, Reitsma, Marissa B, Remuzzi, Giuseppe, Resnikoff, Serge, Reynolds, Alex, Ribeiro, Antonio L, Blancas, Maria Jesus Rios, Roba, Hirbo Shore, Rojas-Rueda, David, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rothenbacher, Dietrich, Roy, Ambuj, Sagar, Rajesh, Sahathevan, Ramesh, Sanabria, Juan R, Sanchez-Niño, Maria Dolores, Santos, Itamar S, Santos, João Vasco, Sarmiento-Suarez, Rodrigo, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Schaub, Michael P, Schmidt, Maria Inês, Schneider, Ione J C, Schöttker, Ben, Schwebel, David C, Scott, James G, Seedat, Soraya, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shackelford, Katya A, Shaheen, Amira, Shaikh, Masood Ali, Sharma, Rajesh, Sharma, Upasana, Shen, Jiabin, Shepard, Donald S, Sheth, Kevin N, Shibuya, Kenji, Shin, Min-Jeong, Shiri, Rahman, Shiue, Ivy, Shrime, Mark G, Sigfusdottir, Inga Dora, Silva, Diego Augusto Santos, Silveira, Dayane Gabriele Alves, Singh, Abhishek, Singh, Jasvinder A, Singh, Om Prakash, Singh, Prashant Kumar, Sivonda, Anna, Skirbekk, Vegard, Skogen, Jens Christoffer, Sligar, Amber, Sliwa, Karen, Soljak, Michael, Søreide, Kjetil, Sorensen, Reed J D, Soriano, Joan B, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stathopoulou, Vasiliki, Steel, Nicholas, Stein, Dan J, Steiner, Timothy J, Steinke, Sabine, Stovner, Lars, Stroumpoulis, Konstantinos, Sunguya, Bruno F, Sur, Patrick, Swaminathan, Soumya, Sykes, Bryan L, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Takala, Jukka S, Tandon, Nikhil, Tanne, David, Tavakkoli, Mohammad, Taye, Bineyam, Taylor, Hugh R, Ao, Braden J Te, Tedla, Bemnet Amare, Terkawi, Abdullah Sulieman, Thomson, Alan J, Thorne-Lyman, Andrew L, Thrift, Amanda G, Thurston, George D, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Fotis, Tran, Bach Xuan, Truelsen, Thomas, Dimbuene, Zacharie Tsala, Tsilimbaris, Miltiadis, 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Ha, Jeemon, Panniyammakal, Jensen, Paul N, Jiang, Ying, Jibat, Tariku, Jimenez-Corona, Aida, Jin, Ye, Jonas, Jost B, Kabir, Zubair, Kalkonde, Yogeshwar, Kamal, Ritul, Kan, Haidong, Karch, André, Karema, Corine Kakizi, Karimkhani, Chante, Kasaeian, Amir, Kaul, Anil, Kawakami, Norito, Keiyoro, Peter Njenga, Kemp, Andrew Haddon, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khan, Abdur Rahman, Khan, Ejaz Ahmad, Khang, Young-Ho, Khera, Sahil, Khoja, Tawfik Ahmed Muthafer, Khubchandani, Jagdish, Kieling, Christian, Kim, Pauline, Kim, Cho-il, Kim, Daniel, Kim, Yun Jin, Kissoon, Niranjan, Knibbs, Luke D, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kotsakis, Georgios A, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kudom, Andreas A, Kuipers, Ernst J, Kumar, G Anil, Kutz, Michael, Kwan, Gene F, Lal, Aparna, Lalloo, Ratilal, Lallukka, Tea, Lam, Hilton, Lam, Jennifer O, Langan, Sinead M, Larsson, Ander, Lavados, Pablo M, Leasher, Janet L, Leigh, Jame, Leung, Ricky, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Juan, Liu, Shiwei, Liu, Yang, Lloyd, Belinda K, Lo, Warren D, Logroscino, Giancarlo, Looker, Katharine J, Lotufo, Paulo A, Lunevicius, Raimunda, Lyons, Ronan A, Mackay, Mark T, Magdy, Mohammed, Razek, Abd El, Mahdavi, Mahdi, Majdan, Marek, Majeed, Azeem, Malekzadeh, Reza, Marcenes, Wagner, Margolis, David Joel, Martinez-Raga, Jose, Masiye, Felix, Massano, João, Mcgarvey, Stephen Theodore, Mcgrath, John J, Mckee, Martin, Mcmahon, Brian J, Meaney, Peter A, Mehari, Alem, Mejia-Rodriguez, Fabiola, Mekonnen, Alemayehu B, Melaku, Yohannes Adama, Memiah, Peter, Memish, Ziad A, Mendoza, Walter, Meretoja, Atte, Meretoja, Tuomo J, Mhimbira, Francis Apolinary, Miller, Ted R, Mills, Edward J, Mirarefin, Mojde, Mitchell, Philip B, Mock, Charles N, Mohammadi, Alireza, Mohammed, Shafiu, Monasta, Lorenzo, Hernandez, Julio Cesar Montañez, Montico, Marcella, 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Svetlana, Poulton, Richie G, Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Noela M, Qorbani, Mostafa, Rabiee, Rynaz H S, Radfar, Amir, Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Rao, Puja, Refaat, Amany H, Reitsma, Marissa B, Remuzzi, Giuseppe, Resnikoff, Serge, Reynolds, Alex, Ribeiro, Antonio L, Blancas, Maria Jesus Rio, Roba, Hirbo Shore, Rojas-Rueda, David, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rothenbacher, Dietrich, Roy, Ambuj, Sagar, Rajesh, Sahathevan, Ramesh, Sanabria, Juan R, Sanchez-Niño, Maria Dolore, Santos, Itamar S, Santos, João Vasco, Sarmiento-Suarez, Rodrigo, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Schaub, Michael P, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schwebel, David C, Scott, James G, Seedat, Soraya, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shackelford, Katya A, Shaheen, Amira, Shaikh, Masood Ali, Sharma, Rajesh, Sharma, Upasana, Shen, Jiabin, Shepard, Donald S, Sheth, Kevin N, Shibuya, Kenji, Shin, Min-Jeong, Shiri, Rahman, Shiue, Ivy, Shrime, Mark G, Sigfusdottir, Inga Dora, Silva, Diego Augusto Santo, Silveira, Dayane Gabriele Alve, Singh, Abhishek, Singh, Jasvinder A, Singh, Om Prakash, Singh, Prashant Kumar, Sivonda, Anna, Skirbekk, Vegard, Skogen, Jens Christoffer, Sligar, Amber, Sliwa, Karen, Soljak, Michael, Søreide, Kjetil, Soriano, Joan B, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J, Steiner, Timothy J, Steinke, Sabine, Stovner, Lar, Stroumpoulis, Konstantino, Sunguya, Bruno F, Sur, Patrick, Swaminathan, Soumya, Sykes, Bryan L, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Takala, Jukka S, Tandon, Nikhil, Tanne, David, Tavakkoli, Mohammad, Taye, Bineyam, Taylor, Hugh R, Ao, Braden J Te, Tedla, Bemnet Amare, Terkawi, Abdullah Sulieman, Thomson, Alan J, Thorne-Lyman, Andrew L, Thrift, Amanda G, Thurston, George D, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Tran, Bach Xuan, Dimbuene, Zacharie Tsala, Tsilimbaris, Miltiadi, Tura, Abera Kenay, Tuzcu, Emin Murat, Tyrovolas, Stefano, Ukwaja, Kingsley N, Undurraga, Eduardo A, Uneke, Chigozie Jesse, Uthman, Olalekan A, van Gool, Coen H, Varakin, Yuri Y, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Verma, Raj Kumar, Violante, Francesco S, Vladimirov, Sergey K, Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Wagner, Gregory R, Waller, Stephen G, Wang, Linhong, Watkins, David A, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G, Werdecker, Andrea, Westerman, Ronny, White, Richard A, Williams, Hywel C, Wiysonge, Charles Shey, Wolfe, Charles D A, Won, Sungho, Woodbrook, Rachel, Wubshet, Mamo, Xavier, Deni, Xu, Gelin, Yadav, Ajit Kumar, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Ye, Pengpeng, Yebyo, Henock Gebremedhin, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Younis, Mustafa Z, Yu, Chuanhua, Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zeeb, Hajo, Zhou, Maigeng, Zodpey, Sanjay, Zuhlke, Liesl Joanna, and Murray, Christopher J L
Subjects: Medicine(all), VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801, Incidence, Medicine (all), Public Health, Global Health, Social Medicine and Epidemiology, Bayes Theorem, 11 Medical And Health Sciences, Articles, Department of Error, Global Health, Cost of Illne, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Cost of Illness, disability, General & Internal Medicine, Quality-Adjusted Life Year, Prevalence, Humans, Disabled Person, Disabled Persons, Quality-Adjusted Life Years, VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801, Human
Abstract: Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval [UI] 15·4–19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30–2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35–2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20–30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Funding Bill & Melinda Gates Foundation. Open Access funded by Bill & Melinda Gates FoundationUnder a Creative Commons license Attribution 4.0 International (CC BY 4.0)
Published: 2016
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26. Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups.

Author: Hoffmann TJ, Graff RE, Madduri RK, Rodriguez AA, Cario CL, Feng K, Jiang Y, Wang A, Klein RJ, Pierce BL, Eggener S, Tong L, Blot W, Long J, Goss LB, Darst BF, Rebbeck T, Lachance J, Andrews C, Adebiyi AO, Adusei B, Aisuodionoe-Shadrach OI, Fernandez PW, Jalloh M, Janivara R, Chen WC, Mensah JE, Agalliu I, Berndt SI, Shelley JP, Schaffer K, Machiela MJ, Freedman ND, Huang WY, Li SA, Goodman PJ, Till C, Thompson I, Lilja H, Ranatunga DK, Presti J, Van Den Eeden SK, Chanock SJ, Mosley JD, Conti DV, Haiman CA, Justice AC, Kachuri L, and Witte JS
Subjects: Humans, Male, Middle Aged, Aged, Hispanic or Latino genetics, White People genetics, Genetic Predisposition to Disease, Cohort Studies, Genome-Wide Association Study, Prostate-Specific Antigen blood, Prostate-Specific Antigen genetics, Prostatic Neoplasms genetics, Prostatic Neoplasms ethnology, Polymorphism, Single Nucleotide
Abstract: We conducted a multiancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry, 58,236 African ancestry, 23,546 Hispanic/Latino and 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (P ≤ 5 × 10 -8 ) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n = 95,768). Meta-analyzing discovery and replication (n = 392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6% to 16.6% for European ancestry, 5.5% to 9.5% for African ancestry, 13.5% to 18.2% for Hispanic/Latino and 8.6% to 15.3% for Asian ancestry and decreased with increasing age. Midlife genetically adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA levels. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening., Competing Interests: Competing interests: J.S.W. and C.L.C. are nonemployee co-founders of Avail Bio. H.L. is named on a patent for intact PSA assays and a patent for a statistical method to detect prostate cancer that is licensed to and commercialized by OPKO Health. H.L. receives royalties from sales of the test and has stock in OPKO Health. J.S.W. consults for DLA Piper on subject matter unrelated to this study. R.E.G. consults for Hunton Andrews Kurth on subject matter unrelated to this study. The other authors declare no competing interests., (© 2025. The Author(s).)
Published: 2025
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27. Heterogeneous genetic architectures of prostate cancer susceptibility in sub-Saharan Africa.

Author: Janivara R, Chen WC, Hazra U, Baichoo S, Agalliu I, Kachambwa P, Simonti CN, Brown LM, Tambe SP, Kim MS, Harlemon M, Jalloh M, Muzondiwa D, Naidoo D, Ajayi OO, Snyper NY, Niang L, Diop H, Ndoye M, Mensah JE, Abrahams AOD, Biritwum R, Adjei AA, Adebiyi AO, Shittu O, Ogunbiyi O, Adebayo S, Nwegbu MM, Ajibola HO, Oluwole OP, Jamda MA, Pentz A, Haiman CA, Spies PV, van der Merwe A, Cook MB, Chanock SJ, Berndt SI, Watya S, Lubwama A, Muchengeti M, Doherty S, Smyth N, Lounsbury D, Fortier B, Rohan TE, Jacobson JS, Neugut AI, Hsing AW, Gusev A, Aisuodionoe-Shadrach OI, Joffe M, Adusei B, Gueye SM, Fernandez PW, McBride J, Andrews C, Petersen LN, Lachance J, and Rebbeck TR
Subjects: Male, Humans, Africa South of the Sahara, Black People genetics, Gene Frequency, Haplotypes, Case-Control Studies, Alleles, Genetics, Population, Prostatic Neoplasms genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract: Men of African descent have the highest prostate cancer incidence and mortality rates, yet the genetic basis of prostate cancer in African men has been understudied. We used genomic data from 3,963 cases and 3,509 controls from Ghana, Nigeria, Senegal, South Africa and Uganda to infer ancestry-specific genetic architectures and fine-map disease associations. Fifteen independent associations at 8q24.21, 6q22.1 and 11q13.3 reached genome-wide significance, including four new associations. Intriguingly, multiple lead associations are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of prostate cancer differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African prostate cancer associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2024
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28. Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction.

Author: Hoffmann TJ, Graff RE, Madduri RK, Rodriguez AA, Cario CL, Feng K, Jiang Y, Wang A, Klein RJ, Pierce BL, Eggener S, Tong L, Blot W, Long J, Goss LB, Darst BF, Rebbeck T, Lachance J, Andrews C, Adebiyi AO, Adusei B, Aisuodionoe-Shadrach OI, Fernandez PW, Jalloh M, Janivara R, Chen WC, Mensah JE, Agalliu I, Berndt SI, Shelley JP, Schaffer K, Machiela MJ, Freedman ND, Huang WY, Li SA, Goodman PJ, Till C, Thompson I, Lilja H, Ranatunga DK, Presti J, Van Den Eeden SK, Chanock SJ, Mosley JD, Conti DV, Haiman CA, Justice AC, Kachuri L, and Witte JS
Abstract: We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6%-16.6% in European ancestry, 5.5%-9.5% in African ancestry, 13.5%-18.2% in Hispanic/Latino, and 8.6%-15.3% in Asian ancestry, and decreased with increasing age. Mid-life genetically-adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening.
Published: 2024
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29. Association of depression and anxiety with uncontrolled hypertension: A cross-sectional study in Southwest Nigeria.

Author: Amaike C, Salami OF, Bamidele OT, Ojo AM, Otaigbe I, Abiodun O, Adesola O, and Adebiyi AO
Abstract: Background: Hypertension is a medical condition of public health concern that increases the risk of chronic noncommunicable diseases and mortalities. In recent years, understanding its coexistence with other comorbidities has been the focus of better management. However, the relationship between hypertension and depression or anxiety has been contentious issue, with diverse findings reported by different studies. Understanding this relationship will be crucial for blood pressure control and reducing the mortality associated with hypertension. Therefore, this study was conducted to determine the association between depression or anxiety and hypertension control., Methods: A cross-sectional study was conducted among 321 hypertensive patients accessing care in two hospitals. Depression and anxiety symptoms were assessed using the Hospital Anxiety and Depression Scale (HADS). The relationship between blood pressure control and depression or anxiety was assessed using binary logistic regression., Results: The prevalence of depression and anxiety was 12.1% and 23.1%, respectively. Up to 261 (81.3%) participants had uncontrolled blood pressure. Of these 261 participants, 14.2% and 23.4% had depression and anxiety, respectively. Depression was associated with an increased risk of uncontrolled blood pressure after adjusting for sex, smoking cigarettes, age, marital status, and exercise (odds ratio (OR) = 7.751, 95% confidence interval (CI) = 1.79-43.4, P = 0.011)., Conclusion: Depression appears to be independently associated with an increased risk of uncontrolled blood pressure. It is therefore relevant for healthcare providers to assess for depression in patients with hypertension to ensure better hypertensive control., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Indian Journal of Psychiatry.)
Published: 2024
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30. Physician-brief advice for promoting smoking cessation among cancer patients on treatment in low and middle-income countries: a scoping review.

Author: Ilesanmi OS, Faseru B, Afolabi AA, Odukoya O, Ayo-Yusuf O, Akinsolu F, Adebiyi AO, and Evans WK
Subjects: Humans, Smoking, Developing Countries, Crisis Intervention, Smoking Prevention, Practice Patterns, Physicians', Smoking Cessation, Physicians, Neoplasms epidemiology, Neoplasms therapy
Abstract: Introduction: Physician-brief advice has been utilized in high-income countries to promote smoking cessation among cancer patients. Empirical evidence on its effectiveness among cancer patients in low and middle-income countries (LMICs) is lacking. The gap could be due to inadequate training, and competing healthcare priorities, leading to insufficient implementation of targeted smoking cessation interventions in oncology settings. We undertook this scoping review to determine if physician-brief advice is effective in promoting smoking cessation among cancer patients in LMICs., Methods: We conducted a literature search of all relevant articles across five databases: Cochrane Central Register of Controlled Trials, Cochrane Library (Tobacco Addiction Group trials), World Conference on Lung Cancer proceedings, PubMed, and Google Scholar up to November 2023, using pre-defined inclusion criteria and keywords. The study population was cancer survivors in LMICs, the intervention was smoking cessation advice by a physician in a clinic or oncology center during a consultation, and the outcome was the effect of smoking cessation programs in discontinuing smoking among cancer survivors in LMICs., Results: Overall, out of every 10 cancer patients in LMICs, about seven were smokers, and one-half had received physician-brief advice for smoking cessation. Physician-brief advice was more likely to be delivered to patients with smoking-related cancer (Cohen's d = 0.396). This means that there is a noticeable difference between patients with smoking-related cancer compared to those with cancer unrelated to smoking. Smoking cessation failure was due to the inability to cope with the symptoms of withdrawal, missed smoking cessation clinic visits, mental health disorders, limited time and resources, and minimal patient-physician contact., Conclusion: There is very little literature on the frequency of use or the efficacy of physician-brief advice on smoking cessation in LMICs. The literature suggests that cancer patients in LMICs have low self-efficacy to quit smoking, and smoking cessation is rarely part of cancer care in LMICs. Physicians in LMICs should be trained to use motivational messages and good counseling techniques to improve smoking cessation among cancer patients. Policymakers should allocate the resources to implement physician-brief advice and design training programs for physicians focusing on physician-brief advice tailored to cancer patients., (© 2024. The Author(s).)
Published: 2024
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31. Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men.

Author: Janivara R, Hazra U, Pfennig A, Harlemon M, Kim MS, Eaaswarkhanth M, Chen WC, Ogunbiyi A, Kachambwa P, Petersen LN, Jalloh M, Mensah JE, Adjei AA, Adusei B, Joffe M, Gueye SM, Aisuodionoe-Shadrach OI, Fernandez PW, Rohan TE, Andrews C, Rebbeck TR, Adebiyi AO, Agalliu I, and Lachance J
Abstract: Androgenetic alopecia is a highly heritable trait. However, much of our understanding about the genetics of male pattern baldness comes from individuals of European descent. Here, we examined a novel dataset comprising 2,136 men from Ghana, Nigeria, Senegal, and South Africa that were genotyped using a custom array. We first tested how genetic predictions of baldness generalize from Europe to Africa, finding that polygenic scores from European GWAS yielded AUC statistics that ranged from 0.513 to 0.546, indicating that genetic predictions of baldness in African populations performed notably worse than in European populations. Subsequently, we conducted the first African GWAS of androgenetic alopecia, focusing on self-reported baldness patterns at age 45. After correcting for present age, population structure, and study site, we identified 266 moderately significant associations, 51 of which were independent (p-value < 10 -5 , r 2 < 0.2). Most baldness associations were autosomal, and the X chromosomes does not appear to have a large impact on baldness in African men. Finally, we examined the evolutionary causes of continental differences in genetic architecture. Although Neanderthal alleles have previously been associated with skin and hair phenotypes, we did not find evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. Most loci that are associated with androgenetic alopecia are evolving neutrally. However, multiple baldness-associated SNPs near the EDA2R and AR genes have large allele frequency differences between continents. Collectively, our findings illustrate how evolutionary history contributes to the limited portability of genetic predictions across ancestries., Competing Interests: Declaration of interests The authors declare no competing interests.
Published: 2024
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32. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.

Author: Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, Darst BF, Sheng X, Xu Y, Chou AJ, Benlloch S, Dadaev T, Brook MN, Plym A, Sahimi A, Hoffman TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Laisk T, Figuerêdo J, Muir K, Ito S, Liu X, Uchio Y, Kubo M, Kamatani Y, Lophatananon A, Wan P, Andrews C, Lori A, Choudhury PP, Schleutker J, Tammela TLJ, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokolorczyk D, Lubinski J, Rentsch CT, Cho K, Mcmahon BH, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder A, Stroomberg HV, Batra J, Chambers S, Horvath L, Clements JA, Tilly W, Risbridger GP, Gronberg H, Aly M, Szulkin R, Eklund M, Nordstrom T, Pashayan N, Dunning AM, Ghoussaini M, Travis RC, Key TJ, Riboli E, Park JY, Sellers TA, Lin HY, Albanes D, Weinstein S, Cook MB, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM Jr, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Koutros S, Beane Freeman LE, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CML, Barnett G, Maier C, Schnoeller T, Luedeke M, Kibel AS, Drake BF, Cussenot O, Cancel-Tassin G, Menegaux F, Truong T, Koudou YA, John EM, Grindedal EM, Maehle L, Khaw KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Butler EN, Mohler JL, Taylor JA, Kogevinas M, Dierssen-Sotos T, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Pilie P, Yu Y, Bohlender RJ, Gu J, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Brenner H, Chen X, Holleczek B, Schöttker B, Klein EA, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Kim J, Neuhausen SL, Steele L, Ding YC, Isaacs WB, Nemesure B, Hennis AJM, Carpten J, Pandha H, Michael A, De Ruyck K, De Meerleer G, Ost P, Xu J, Razack A, Lim J, Teo SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas CM, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Abraham A, Singhal S, Parliament M, Claessens F, Joniau S, Van den Broeck T, Gago-Dominguez M, Castelao JE, Martinez ME, Larkin S, Townsend PA, Aukim-Hastie C, Bush WS, Aldrich MC, Crawford DC, Srivastava S, Cullen J, Petrovics G, Casey G, Wang Y, Tettey Y, Lachance J, Tang W, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Yamoah K, Govindasami K, Chokkalingam AP, Keaton JM, Hellwege JN, Clark PE, Jalloh M, Gueye SM, Niang L, Ogunbiyi O, Shittu O, Amodu O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Diop H, Gundell SM, Roobol MJ, Jenster G, van Schaik RHN, Hu JJ, Sanderson M, Kachuri L, Varma R, McKean-Cowdin R, Torres M, Preuss MH, Loos RJF, Zawistowski M, Zöllner S, Lu Z, Van Den Eeden SK, Easton DF, Ambs S, Edwards TL, Mägi R, Rebbeck TR, Fritsche L, Chanock SJ, Berndt SI, Wiklund F, Nakagawa H, Witte JS, Gaziano JM, Justice AC, Mancuso N, Terao C, Eeles RA, Kote-Jarai Z, Madduri RK, Conti DV, and Haiman CA
Subjects: Humans, Male, Black People genetics, Genome-Wide Association Study, Hispanic or Latino genetics, Polymorphism, Single Nucleotide, Risk Factors, White People genetics, Asian People genetics, Genetic Predisposition to Disease, Prostatic Neoplasms genetics
Abstract: The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2023
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33. Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry.

Author: Chen F, Madduri RK, Rodriguez AA, Darst BF, Chou A, Sheng X, Wang A, Shen J, Saunders EJ, Rhie SK, Bensen JT, Ingles SA, Kittles RA, Strom SS, Rybicki BA, Nemesure B, Isaacs WB, Stanford JL, Zheng W, Sanderson M, John EM, Park JY, Xu J, Wang Y, Berndt SI, Huff CD, Yeboah ED, Tettey Y, Lachance J, Tang W, Rentsch CT, Cho K, Mcmahon BH, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Sellers TA, Yamoah K, Murphy AB, Crawford DC, Patel AV, Bush WS, Aldrich MC, Cussenot O, Petrovics G, Cullen J, Neslund-Dudas CM, Stern MC, Kote-Jarai Z, Govindasami K, Cook MB, Chokkalingam AP, Hsing AW, Goodman PJ, Hoffmann TJ, Drake BF, Hu JJ, Keaton JM, Hellwege JN, Clark PE, Jalloh M, Gueye SM, Niang L, Ogunbiyi O, Idowu MO, Popoola O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Mensah JE, Diop H, Van Den Eeden SK, Blanchet P, Fowke JH, Casey G, Hennis AJ, Lubwama A, Thompson IM Jr, Leach R, Easton DF, Preuss MH, Loos RJ, Gundell SM, Wan P, Mohler JL, Fontham ET, Smith GJ, Taylor JA, Srivastava S, Eeles RA, Carpten JD, Kibel AS, Multigner L, Parent MÉ, Menegaux F, Cancel-Tassin G, Klein EA, Andrews C, Rebbeck TR, Brureau L, Ambs S, Edwards TL, Watya S, Chanock SJ, Witte JS, Blot WJ, Michael Gaziano J, Justice AC, Conti DV, and Haiman CA
Subjects: Male, Humans, Genome-Wide Association Study, Risk Factors, Black People genetics, Genetic Predisposition to Disease, Prostatic Neoplasms genetics, Prostatic Neoplasms epidemiology
Abstract: Background: Genetic factors play an important role in prostate cancer (PCa) susceptibility., Objective: To discover common genetic variants contributing to the risk of PCa in men of African ancestry., Design, Setting, and Participants: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry., Outcome Measurements and Statistical Analysis: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness., Results and Limitations: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10 -4 )., Conclusions: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry., Patient Summary: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease., (Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.)
Published: 2023
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34. Cigarette health warning label compliance in Nigeria: A multi-city observational study.

Author: Owopetu OF, Oladeinde O, Esan JO, Iacobelli M, Agaku I, and Adebiyi AO
Abstract: Introduction: Tobacco remains the world's leading preventable cause of death, with the majority of tobacco-caused deaths occurring in low- and middle-income countries. The first global health treaty, the Framework Convention on Tobacco Control (FCTC), outlines a set of policy initiatives that have been demonstrated as effective in reducing tobacco use. Article 11 of the FCTC focuses on using the tobacco package to communicate tobacco-caused harms; it also seeks to restrict the delivery of misleading information on the pack about the product.The objective of his study is to establish a surveillance system for tobacco packs in Nigeria to assess pack compliance with in-country health warning label requirements. The Tobacco Pack Surveillance System (TPackSS) monitors whether required health warnings on tobacco packages are being implemented as intended and identifies pack designs that might violate the communication of harm-related information and undermine the impact of the country's tobacco packaging laws., Methods: Tobacco cigarette packs were collected in three cities in 2019-2020. The intention was, to the extent possible, to construct a census of 'unique' pack presentations available for purchase in Nigeria. We implemented the TPackSS standardized Protocol for acquiring packs from 36 diverse neighborhoods across three cities. At the time of purchase, data on the price and place of acquisition of each pack were recorded. We photographed packs, coded, and archived them. Each pack was coded for compliance according to the current health warning label laws. Each pack was coded by two independent coders consistently. We routinely measured intercoder reliability and only retained variables for which a good level of reliability was achieved., Results: Across the three cities in Nigeria, the team collected 90 tobacco packs. Overall, 77% of packs evaluated for HWL compliance complied with all the relevant common indicators of HWL compliance. There was a 92% compliance with the location of the HWL (e.g. top or bottom of pack, front or back panel) with in-country requirements. Of the four compliance indicators, the size of the HWL (the minimum required coverage) showed the lowest compliance (31%) (i.e. the HWL was too small on most of the packs). Label elements (such as color contrast or content of warnings) showed 85% compliance overall., Conclusions: The analysis of the packs showed various levels of compliance with Health Warning Label provisions for Nigeria. Periodic evaluations are required to ensure that minimum requirements are met., Competing Interests: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none was reported., (© 2023 Owopetu O. F. et al.)
Published: 2023
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35. Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa.

Author: Kim MS, Naidoo D, Hazra U, Quiver MH, Chen WC, Simonti CN, Kachambwa P, Harlemon M, Agalliu I, Baichoo S, Fernandez P, Hsing AW, Jalloh M, Gueye SM, Niang L, Diop H, Ndoye M, Snyper NY, Adusei B, Mensah JE, Abrahams AOD, Biritwum R, Adjei AA, Adebiyi AO, Shittu O, Ogunbiyi O, Adebayo S, Aisuodionoe-Shadrach OI, Nwegbu MM, Ajibola HO, Oluwole OP, Jamda MA, Singh E, Pentz A, Joffe M, Darst BF, Conti DV, Haiman CA, Spies PV, van der Merwe A, Rohan TE, Jacobson J, Neugut AI, McBride J, Andrews C, Petersen LN, Rebbeck TR, and Lachance J
Subjects: Africa South of the Sahara epidemiology, Genetic Predisposition to Disease, Humans, Male, Risk Factors, Genome-Wide Association Study, Prostatic Neoplasms genetics
Abstract: Background: Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa., Results: Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608-0.707, OR 2.37-5.71) than for African individuals (AUC 0.502-0.585, OR 0.95-2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores., Conclusions: Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities., (© 2022. The Author(s).)
Published: 2022
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36. A randomized, open-label trial of combined nitazoxanide and atazanavir/ritonavir for mild to moderate COVID-19.

Author: Fowotade A, Bamidele F, Egbetola B, Fagbamigbe AF, Adeagbo BA, Adefuye BO, Olagunoye A, Ojo TO, Adebiyi AO, Olagunju OI, Ladipo OT, Akinloye A, Onayade A, Bolaji OO, Rannard S, Happi C, Owen A, and Olagunju A
Abstract: Background: The nitazoxanide plus atazanavir/ritonavir for COVID-19 (NACOVID) trial investigated the efficacy and safety of repurposed nitazoxanide combined with atazanavir/ritonavir for COVID-19., Methods: This is a pilot, randomized, open-label multicenter trial conducted in Nigeria. Mild to moderate COVID-19 patients were randomly assigned to receive standard of care (SoC) or SoC plus a 14-day course of nitazoxanide (1,000 mg b.i.d.) and atazanavir/ritonavir (300/100 mg od) and followed through day 28. Study endpoints included time to clinical improvement, SARS-CoV-2 viral load change, and time to complete symptom resolution. Safety and pharmacokinetics were also evaluated (ClinicalTrials.gov ID: NCT04459286)., Results: There was no difference in time to clinical improvement between the SoC ( n = 26) and SoC plus intervention arms ( n = 31; Cox proportional hazards regression analysis adjusted hazard ratio, aHR = 0.898, 95% CI: 0.492-1.638, p = 0.725). No difference was observed in the pattern of saliva SARS-CoV-2 viral load changes from days 2-28 in the 35% of patients with detectable virus at baseline (20/57) (aHR = 0.948, 95% CI: 0.341-2.636, p = 0.919). There was no significant difference in time to complete symptom resolution (aHR = 0.535, 95% CI: 0.251-1.140, p = 0.105). Atazanavir/ritonavir increased tizoxanide plasma exposure by 68% and median trough plasma concentration was 1,546 ng/ml (95% CI: 797-2,557), above its putative EC 90 in 54% of patients. Tizoxanide was undetectable in saliva., Conclusion: Nitazoxanide co-administered with atazanavir/ritonavir was safe but not better than standard of care in treating COVID-19. These findings should be interpreted in the context of incomplete enrollment (64%) and the limited number of patients with detectable SARS-CoV-2 in saliva at baseline in this trial., Clinical Trial Registration: [https://clinicaltrials.gov/ct2/show/NCT04459286], identifier [NCT04459286]., Competing Interests: AnO and SR are Directors of Tandem Nano Ltd. AnO received research funding from ViiV, Merck, Janssen, and consultancy from Gilead, ViiV, and Merck not related to the current manuscript. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Fowotade, Bamidele, Egbetola, Fagbamigbe, Adeagbo, Adefuye, Olagunoye, Ojo, Adebiyi, Olagunju, Ladipo, Akinloye, Onayade, Bolaji, Rannard, Happi, Owen and Olagunju.)
Published: 2022
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37. Epidemiology of physical inactivity in Nigeria: a systematic review and meta-analysis.

Author: Adeloye D, Ige-Elegbede JO, Auta A, Ale BM, Ezeigwe N, Omoyele C, Dewan MT, Mpazanje RG, Agogo E, Alemu W, Gadanya MA, Harhay MO, and Adebiyi AO
Subjects: Adult, Exercise, Female, Humans, Male, Nigeria epidemiology, Prevalence, Rural Population, Sedentary Behavior
Abstract: Background: Physical activity is crucial to preventing noncommunicable diseases. This study aimed to provide up-to-date evidence on the epidemiology of insufficient physical activity across Nigeria to increase awareness and prompt relevant policy and public health response., Methods: A systematic literature search of community-based studies on physical inactivity was conducted. We constructed a meta-regression epidemiologic model to determine the age-adjusted prevalence and number of physically inactive persons in Nigeria for 1995 and 2020., Results: Fifteen studies covering a population of 13 814 adults met our selection criteria. The pooled crude prevalence of physically inactive persons in Nigeria was 52.0% (95% CI: 33.7-70.4), with prevalence in women higher at 55.8% (95% CI: 29.4-82.3) compared to men at 49.3% (95% CI: 24.7-73.9). Across settings, prevalence of physically inactive persons was significantly higher among urban dwellers (56.8%, 35.3-78.4) compared to rural dwellers (18.9%, 11.9-49.8). Among persons aged 20-79 years, the total number of physically inactive persons increased from 14.4 million to 48.6 million between 1995 and 2020, equivalent to a 240% increase over the 25-year period., Conclusions: A comprehensive and robust strategy that addresses occupational policies, town planning, awareness and information, and sociocultural and contextual issues is crucial to improving physical activity levels in Nigeria., (© The Author(s) 2021. Published by Oxford University Press on behalf of Faculty of Public Health.)
Published: 2022
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38. Validation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: A meta-analysis within diverse populations.

Author: Chen F, Darst BF, Madduri RK, Rodriguez AA, Sheng X, Rentsch CT, Andrews C, Tang W, Kibel AS, Plym A, Cho K, Jalloh M, Gueye SM, Niang L, Ogunbiyi OJ, Popoola O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Mensah JE, Adjei AA, Diop H, Lachance J, Rebbeck TR, Ambs S, Gaziano JM, Justice AC, Conti DV, and Haiman CA
Subjects: Age Factors, Case-Control Studies, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Multifactorial Inheritance, Risk Factors, United States epidemiology, Genome-Wide Association Study, Prostatic Neoplasms epidemiology, Prostatic Neoplasms genetics
Abstract: Background: We recently developed a multi-ancestry polygenic risk score (PRS) that effectively stratifies prostate cancer risk across populations. In this study, we validated the performance of the PRS in the multi-ancestry Million Veteran Program and additional independent studies., Methods: Within each ancestry population, the association of PRS with prostate cancer risk was evaluated separately in each case-control study and then combined in a fixed-effects inverse-variance-weighted meta-analysis. We further assessed the effect modification by age and estimated the age-specific absolute risk of prostate cancer for each ancestry population., Results: The PRS was evaluated in 31,925 cases and 490,507 controls, including men from European (22,049 cases, 414,249 controls), African (8794 cases, 55,657 controls), and Hispanic (1082 cases, 20,601 controls) populations. Comparing men in the top decile (90-100% of the PRS) to the average 40-60% PRS category, the prostate cancer odds ratio (OR) was 3.8-fold in European ancestry men (95% CI = 3.62-3.96), 2.8-fold in African ancestry men (95% CI = 2.59-3.03), and 3.2-fold in Hispanic men (95% CI = 2.64-3.92). The PRS did not discriminate risk of aggressive versus nonaggressive prostate cancer. However, the OR diminished with advancing age (European ancestry men in the top decile: ≤55 years, OR = 7.11; 55-60 years, OR = 4.26; >70 years, OR = 2.79). Men in the top PRS decile reached 5% absolute prostate cancer risk ~10 years younger than men in the 40-60% PRS category., Conclusions: Our findings validate the multi-ancestry PRS as an effective prostate cancer risk stratification tool across populations. A clinical study of PRS is warranted to determine whether the PRS could be used for risk-stratified screening and early detection., Funding: This work was supported by the National Cancer Institute at the National Institutes of Health (grant numbers U19 CA214253 to C.A.H., U01 CA257328 to C.A.H., U19 CA148537 to C.A.H., R01 CA165862 to C.A.H., K99 CA246063 to B.F.D, and T32CA229110 to F.C), the Prostate Cancer Foundation (grants 21YOUN11 to B.F.D. and 20CHAS03 to C.A.H.), the Achievement Rewards for College Scientists Foundation Los Angeles Founder Chapter to B.F.D, and the Million Veteran Program-MVP017. This research has been conducted using the UK Biobank Resource under application number 42195. This research is based on data from the Million Veteran Program, Office of Research and Development, and the Veterans Health Administration. This publication does not represent the views of the Department of Veteran Affairs or the United States Government., Competing Interests: FC, AR, XS, CR, CA, WT, AK, AP, KC, MJ, SG, LN, OO, OP, AA, OA, HA, MJ, OO, MN, BA, SM, AD, JM, AA, HD, JL, TR, SA, JG, AJ, DC, CH No competing interests declared, BD received honorarium for presentations at Society of Urology Oncology Annual Meeting (2021) and the Social Genomics Group at the University of Wisconsin, Madison (2021). The author has no other competing interests to declare, RM has stock or stock options in Navipoint Genomics LLC. The author has no other competing interests to declare
Published: 2022
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39. A Rare Germline HOXB13 Variant Contributes to Risk of Prostate Cancer in Men of African Ancestry.

Author: Darst BF, Hughley R, Pfennig A, Hazra U, Fan C, Wan P, Sheng X, Xia L, Andrews C, Chen F, Berndt SI, Kote-Jarai Z, Govindasami K, Bensen JT, Ingles SA, Rybicki BA, Nemesure B, John EM, Fowke JH, Huff CD, Strom SS, Isaacs WB, Park JY, Zheng W, Ostrander EA, Walsh PC, Carpten J, Sellers TA, Yamoah K, Murphy AB, Sanderson M, Crawford DC, Gapstur SM, Bush WS, Aldrich MC, Cussenot O, Petrovics G, Cullen J, Neslund-Dudas C, Kittles RA, Xu J, Stern MC, Chokkalingam AP, Multigner L, Parent ME, Menegaux F, Cancel-Tassin G, Kibel AS, Klein EA, Goodman PJ, Stanford JL, Drake BF, Hu JJ, Clark PE, Blanchet P, Casey G, Hennis AJM, Lubwama A, Thompson IM Jr, Leach RJ, Gundell SM, Pooler L, Mohler JL, Fontham ETH, Smith GJ, Taylor JA, Brureau L, Blot WJ, Biritwum R, Tay E, Truelove A, Niwa S, Tettey Y, Varma R, McKean-Cowdin R, Torres M, Jalloh M, Magueye Gueye S, Niang L, Ogunbiyi O, Oladimeji Idowu M, Popoola O, Adebiyi AO, Aisuodionoe-Shadrach OI, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Yeboah ED, Mensah JE, Anthony Adjei A, Diop H, Cook MB, Chanock SJ, Watya S, Eeles RA, Chiang CWK, Lachance J, Rebbeck TR, Conti DV, and Haiman CA
Subjects: Case-Control Studies, Genetic Predisposition to Disease, Germ Cells pathology, Germ-Line Mutation, Homeodomain Proteins genetics, Humans, Male, Prostate-Specific Antigen genetics, Early Detection of Cancer, Prostatic Neoplasms genetics, Prostatic Neoplasms pathology
Abstract: A rare African ancestry-specific germline deletion variant in HOXB13 (X285K, rs77179853) was recently reported in Martinican men with early-onset prostate cancer. Given the role of HOXB13 germline variation in prostate cancer, we investigated the association between HOXB13 X285K and prostate cancer risk in a large sample of 22 361 African ancestry men, including 11 688 prostate cancer cases. The risk allele was present only in men of West African ancestry, with an allele frequency in men that ranged from 0.40% in Ghana and 0.31% in Nigeria to 0% in Uganda and South Africa, with a range of frequencies in men with admixed African ancestry from North America and Europe (0-0.26%). HOXB13 X285K was associated with 2.4-fold increased odds of prostate cancer (95% confidence interval [CI] = 1.5-3.9, p = 2 × 10 -4 ), with greater risk observed for more aggressive and advanced disease (Gleason ≥8: odds ratio [OR] = 4.7, 95% CI = 2.3-9.5, p = 2 × 10 -5 ; stage T3/T4: OR = 4.5, 95% CI = 2.0-10.0, p = 2 × 10 -4 ; metastatic disease: OR = 5.1, 95% CI = 1.9-13.7, p = 0.001). We estimated that the allele arose in West Africa 1500-4600 yr ago. Further analysis is needed to understand how the HOXB13 X285K variant impacts the HOXB13 protein and function in the prostate. Understanding who carries this mutation may inform prostate cancer screening in men of West African ancestry. PATIENT SUMMARY: A rare African ancestry-specific germline deletion in HOXB13, found only in men of West African ancestry, was reported to be associated with an increased risk of overall and advanced prostate cancer. Understanding who carries this mutation may help inform screening for prostate cancer in men of West African ancestry., (Copyright © 2022. Published by Elsevier B.V.)
Published: 2022
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40. Overall and central obesity and prostate cancer risk in African men.

Author: Agalliu I, Lin WJ, Zhang JS, Jacobson JS, Rohan TE, Adusei B, Snyper NYF, Andrews C, Sidahmed E, Mensah JE, Biritwum R, Adjei AA, Okyne V, Ainuson-Quampah J, Fernandez P, Irusen H, Odiaka E, Folasire OF, Ifeoluwa MG, Aisuodionoe-Shadrach OI, Nwegbu MM, Pentz A, Chen WC, Joffe M, Neugut AI, Diallo TA, Jalloh M, Rebbeck TR, Adebiyi AO, and Hsing AW
Subjects: Body Mass Index, Case-Control Studies, Humans, Male, Obesity complications, Obesity epidemiology, Risk Factors, Waist Circumference, Waist-Hip Ratio, Obesity, Abdominal complications, Obesity, Abdominal epidemiology, Prostatic Neoplasms epidemiology, Prostatic Neoplasms etiology
Abstract: Purpose: African men are disproportionately affected by prostate cancer (PCa). Given the increasing prevalence of obesity in Africa, and its association with aggressive PCa in other populations, we examined the relationship of overall and central obesity with risks of total and aggressive PCa among African men., Methods: Between 2016 and 2020, we recruited 2,200 PCa cases and 1,985 age-matched controls into a multi-center, hospital-based case-control study in Senegal, Ghana, Nigeria, and South Africa. Participants completed an epidemiologic questionnaire, and anthropometric factors were measured at clinic visit. Multivariable logistic regression was used to examine associations of overall and central obesity with PCa risk, measured by body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR), respectively., Results: Among controls 16.4% were obese (BMI ≥ 30 kg/m 2 ), 26% and 90% had WC > 97 cm and WHR > 0.9, respectively. Cases with aggressive PCa had lower BMI/obesity in comparison to both controls and cases with less aggressive PCa, suggesting weight loss related to cancer. Overall obesity (odds ratio: OR = 1.38, 95% CI 0.99-1.93), and central obesity (WC > 97 cm: OR = 1.60, 95% CI 1.10-2.33; and WHtR > 0.59: OR = 1.68, 95% CI 1.24-2.29) were positively associated with D'Amico intermediate-risk PCa, but not with risks of total or high-risk PCa. Associations were more pronounced in West versus South Africa, but these differences were not statistically significant., Discussion: The high prevalence of overall and central obesity in African men and their association with intermediate-risk PCa represent an emerging public health concern in Africa. Large cohort studies are needed to better clarify the role of obesity and PCa in various African populations., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
Published: 2022
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41. Estimating the prevalence of COPD in an African country: evidence from southern Nigeria.

Author: Ale BM, Ozoh OB, Gadanya MA, Li Y, Harhay MO, Adebiyi AO, and Adeloye D
Abstract: # Background: Though several environmental and demographic factors would suggest a high burden of chronic obstructive pulmonary disease (COPD) in most African countries, there is insufficient country-level synthesis to guide public health policy., # Methods: A systematic search of MEDLINE, EMBASE, Global Health and African Journals Online identified studies reporting the prevalence of COPD in Nigeria. We provided a detailed synthesis of study characteristics, and overall median and interquartile range (IQR) of COPD prevalence in Nigeria by case definitions (spirometry or non-spirometry)., # Results: Of 187 potential studies, eight studies (6 spirometry and 2 non-spirometry) including 4,234 Nigerians met the criteria. From spirometry assessment, which is relatively internally consistent, the median prevalence of COPD in Nigeria was 9.2% (interquartile range, IQR: 7.6-10.0), compared to a lower prevalence (5.1%, IQR: 2.2-15.4) from studies based on British Medical Research Council (BMRC) criteria or doctor's diagnosis. The median prevalence of COPD was almost the same among rural (9.5%, IQR: 7.6-10.3) and urban dwellers (9.0%, IQR: 5.3-9.3) from spirometry studies., # Conclusions: A limited number of studies on COPD introduces imprecision in prevalence estimates and presents concerns on the level of response available across different parts of Nigeria, and indeed across many countries in sub-Saharan Africa., Competing Interests: Competing interests: DA is a Co-Editor-in-Chief of the Journal of Global Health Reports. To ensure that any possible conflict of interest relevant to the journal has been addressed, this article was reviewed according to best practice guidelines of international editorial organisations. The authors completed the ICMJE Unified Competing Interests Form (available upon request) and declare no further conflicts of interest.
Published: 2022
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42. Estimating the prevalence of overweight and obesity in Nigeria in 2020: a systematic review and meta-analysis.

Author: Adeloye D, Ige-Elegbede JO, Ezejimofor M, Owolabi EO, Ezeigwe N, Omoyele C, Mpazanje RG, Dewan MT, Agogo E, Gadanya MA, Alemu W, Harhay MO, Auta A, and Adebiyi AO
Subjects: Adolescent, Adult, Aged, Body Mass Index, Female, Humans, Male, Middle Aged, Nigeria epidemiology, Prevalence, Rural Population statistics & numerical data, Urban Population statistics & numerical data, Waist Circumference, Young Adult, Obesity epidemiology, Overweight epidemiology
Abstract: Background: Targeted public health response to obesity in Nigeria is relatively low due to limited epidemiologic understanding. We aimed to estimate nationwide and sub-national prevalence of overweight and obesity in the adult Nigerian population., Methods: MEDLINE, EMBASE, Global Health, and Africa Journals Online were systematically searched for relevant epidemiologic studies in Nigeria published on or after 01 January 1990. We assessed quality of studies and conducted a random-effects meta-analysis on extracted crude prevalence rates. Using a meta-regression model, we estimated the number of overweight and obese persons in Nigeria in the year 2020., Results: From 35 studies ( n = 52,816), the pooled crude prevalence rates of overweight and obesity in Nigeria were 25.0% (95% confidence interval, CI: 20.4-29.6) and 14.3% (95% CI: 12.0-15.5), respectively. The prevalence in women was higher compared to men at 25.5% (95% CI: 17.1-34.0) versus 25.2% (95% CI: 18.0-32.4) for overweight, and 19.8% (95% CI: 3.9-25.6) versus 12.9% (95% CI: 9.1-16.7) for obesity, respectively. The pooled mean body mass index (BMI) and waist circumference were 25.6 kg/m 2 and 86.5 cm, respectively. We estimated that there were 21 million and 12 million overweight and obese persons in the Nigerian population aged 15 years or more in 2020, accounting for an age-adjusted prevalence of 20.3% and 11.6%, respectively. The prevalence rates of overweight and obesity were consistently higher among urban dwellers (27.2% and 14.4%) compared to rural dwellers (16.4% and 12.1%)., Conclusions: Our findings suggest a high prevalence of overweight and obesity in Nigeria. This is marked in urban Nigeria and among women, which may in part be due to widespread sedentary lifestyles and a surge in processed food outlets, largely reflective of a trend across many African settings.KEY MESSAGESAbout 12 million persons in Nigeria were estimated to be obese in 2020, with prevalence considerably higher among women. Nutritional and epidemiological transitions driven by demographic changes, rising income, urbanization, unhealthy lifestyles, and consumption of highly processed diets appear to be driving an obesity epidemic in the country.
Published: 2021
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43. Good Financial Grant Practice: A Tool for Developing and Demonstrating Institutional Financial and Grant Management Capacity in Global Health.

Author: Harste HJ, Kiff G, Okeke IN, Adebiyi AO, Ravikumar KL, Nagaraj G, Ajiboye JJ, Osma Castro ECD, Herrera E, and Aanensen DM
Subjects: Humans, Income, India, Nigeria, Financing, Organized, Global Health
Abstract: The administration and governance of grant funding across global health organizations presents enormous challenges. Meeting these challenges is crucial to ensuring that funds are used in the most effective way to improve health outcomes, in line with the United Nations' Sustainable Development Goal 3, "Ensure healthy lives and promote well-being for all at all ages." The Good Financial Grant Practice (GFGP) Standard (ARS 1651) is the world's first and, currently, only international standard for the financial governance and management of grant funding. Through consensus building and global harmonization between both low- and middle-income and high-income country players, the GFGP Standard has achieved a leveling impact: GFGP applies equally to, and can be implemented by, all types of organization, regardless of location, size, or whether they predominantly give or receive funding. GFGP can be used as a tool for addressing some of the challenges of the current funding model. Here, we describe our experiences and lessons learned from implementing GFGP across 4 diverse research institutions in India, Nigeria, Colombia, and the Philippines as part of our National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.)
Published: 2021
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44. Contextual interpretation of COVID-19 pandemic among public space users in Ibadan Metropolis, Oyo State, Nigeria: An ethnographic review.

Author: Omobowale MO, Bamgboye EA, Akinyode A, Falase OS, Ladipo TO, Salami O, and Adebiyi AO
Subjects: Adult, Aged, Aged, 80 and over, COVID-19 psychology, COVID-19 virology, Female, Government, Health Knowledge, Attitudes, Practice, Humans, Male, Middle Aged, Nigeria epidemiology, Surveys and Questionnaires, COVID-19 epidemiology, Pandemics, SARS-CoV-2 pathogenicity
Abstract: The COVID-19 pandemic has affected all dimensions of lives and has become a social problem as it continues to spread widely through the continuous interactions of people in public spaces where they earn a living. Curbing the spread of COVID-19 requires restrictions in these public spaces, however, the compliance to these measures depends largely on the understanding and interpretations of COVID 19 by users of these public spaces. This study examined the contextual interpretations of public space users about COVID-19 prevention in Ibadan Metropolis, Oyo State. The study was a rapid ethnographic survey in selected public spaces (markets and commercial motor parks) in Ibadan metropolis. Data were collected through participant observation, key informant interviews (3 females; 3 males) and in-depth interviews (30) with, traders, head porters, clients/buyers and commercial vehicle drivers in these public spaces. Interviews conducted were transcribed, sorted into themes using Atlas-ti 7.5.7 and subjected to interpretive-content analysis. Findings revealed that some respondents felt COVID-19 was brought into Nigeria by rich frequent global voyagers, others felt it was through "uncultured" sexual life or wrath of God. Some also doubted the existence of the disease and many of the respondents perceived COVID-19 as a disease reported by the government or a political propaganda to siphon funds. The users of the public spaces in Ibadan Metropolis have variegated perception about the existence and severity of this rapidly spreading virus and this has grave implications for COVID-19 control in the State. Thus, regular interaction with public space users are essential for control efforts., Competing Interests: The authors have declared that no competing interests exist.
Published: 2021
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45. FOCUS ON TOBACCO PREVENTION AMONG NON-SMOKING ADOLESCENTS IN AFRICA; A CALL TO TOBACCO CONTROL EXPERTS.

Author: Fagbule OF and Adebiyi AO
Published: 2021

46. Prevalence, awareness, treatment, and control of hypertension in Nigeria in 1995 and 2020: A systematic analysis of current evidence.

Author: Adeloye D, Owolabi EO, Ojji DB, Auta A, Dewan MT, Olanrewaju TO, Ogah OS, Omoyele C, Ezeigwe N, Mpazanje RG, Gadanya MA, Agogo E, Alemu W, Adebiyi AO, and Harhay MO
Subjects: Adult, Awareness, Blood Pressure, Cross-Sectional Studies, Female, Humans, Male, Nigeria epidemiology, Prevalence, Young Adult, Hypertension drug therapy, Hypertension epidemiology, Hypertension prevention & control, Prehypertension
Abstract: Improved understanding of the current burden of hypertension, including awareness, treatment, and control, is needed to guide relevant preventative measures in Nigeria. A systematic search of studies on the epidemiology of hypertension in Nigeria, published on or after January 1990, was conducted. The authors employed random-effects meta-analysis on extracted crude hypertension prevalence, and awareness, treatment, and control rates. Using a meta-regression model, overall hypertension cases in Nigeria in 1995 and 2020 were estimated. Fifty-three studies (n = 78 949) met our selection criteria. Estimated crude prevalence of pre-hypertension (120-139/80-89 mmHg) in Nigeria was 30.9% (95% confidence interval [CI]: 22.0%-39.7%), and the crude prevalence of hypertension (≥140/90 mmHg) was 30.6% (95% CI: 27.3%-34.0%). When adjusted for age, study period, and sample, absolute cases of hypertension increased by 540% among individuals aged ≥20 years from approximately 4.3 million individuals in 1995 (age-adjusted prevalence 8.6%, 95% CI: 6.5-10.7) to 27.5 million individuals with hypertension in 2020 (age-adjusted prevalence 32.5%, 95% CI: 29.8-35.3). The age-adjusted prevalence was only significantly higher among men in 1995, with the gap between both sexes considerably narrowed in 2020. Only 29.0% of cases (95% CI: 19.7-38.3) were aware of their hypertension, 12.0% (95% CI: 2.7-21.2) were on treatment, and 2.8% (95% CI: 0.1-5.7) had at-goal blood pressure in 2020. Our study suggests that hypertension prevalence has substantially increased in Nigeria over the last two decades. Although more persons are aware of their hypertension status, clinical treatment and control rates, however, remain low. These estimates are relevant for clinical care, population, and policy response in Nigeria and across Africa., (© 2021 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC.)
Published: 2021
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47. Efficacy and safety of nitazoxanide plus atazanavir/ritonavir for the treatment of moderate to severe COVID-19 (NACOVID): A structured summary of a study protocol for a randomised controlled trial.

Author: Olagunju A, Fowotade A, Olagunoye A, Ojo TO, Adefuye BO, Fagbamigbe AF, Adebiyi AO, Olagunju OI, Ladipo OT, Akinloye A, Adeagbo BA, Onayade A, Bolaji OO, Happi C, Rannard S, and Owen A
Subjects: Administration, Oral, Adolescent, Adult, Aged, Antiviral Agents adverse effects, Atazanavir Sulfate adverse effects, COVID-19 diagnosis, COVID-19 virology, COVID-19 Nucleic Acid Testing, Clinical Trials, Phase II as Topic, Drug Administration Schedule, Drug Combinations, Drug Repositioning, Drug Therapy, Combination adverse effects, Drug Therapy, Combination methods, Female, Humans, Male, Middle Aged, Multicenter Studies as Topic, Nigeria, Nitro Compounds, Pilot Projects, RNA, Viral isolation & purification, Randomized Controlled Trials as Topic, Ritonavir adverse effects, SARS-CoV-2 drug effects, SARS-CoV-2 isolation & purification, Severity of Illness Index, Standard of Care, Thiazoles adverse effects, Treatment Outcome, Viral Load drug effects, Young Adult, Antiviral Agents administration & dosage, Atazanavir Sulfate administration & dosage, Ritonavir administration & dosage, Thiazoles administration & dosage, COVID-19 Drug Treatment
Abstract: Objectives: To investigate the efficacy and safety of repurposed antiprotozoal and antiretroviral drugs, nitazoxanide and atazanavir/ritonavir, in shortening the time to clinical improvement and achievement of SARS-CoV-2 polymerase chain reaction (PCR) negativity in patients diagnosed with moderate to severe COVID-19., Trial Design: This is a pilot phase 2, multicentre 2-arm (1:1 ratio) open-label randomised controlled trial., Participants: Patients with confirmed COVID-19 diagnosis (defined as SARS-CoV-2 PCR positive nasopharyngeal swab) will be recruited from four participating isolation and treatment centres in Nigeria: two secondary care facilities (Infectious Diseases Hospital, Olodo, Ibadan, Oyo State and Specialist State Hospital, Asubiaro, Osogbo, Osun State) and two tertiary care facilities (Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Osun State and Olabisi Onabanjo University Teaching Hospital, Sagamu, Ogun State). These facilities have a combined capacity of 146-bed COVID-19 isolation and treatment ward., Inclusion Criteria: Confirmation of SARS-CoV-2 infection by PCR test within two days before randomisation and initiation of treatment, age bracket of 18 and 75 years, symptomatic, able to understand study information and willingness to participate. Exclusion criteria include the inability to take orally administered medication or food, known hypersensitivity to any of the study drugs, pregnant or lactating, current or recent (within 24 hours of enrolment) treatment with agents with actual or likely antiviral activity against SARS-CoV-2, concurrent use of agents with known or suspected interaction with study drugs, and requiring mechanical ventilation at screening., Intervention and Comparator: Participants in the intervention group will receive 1000 mg of nitazoxanide twice daily orally and 300/100 mg of atazanvir/ritonavir once daily orally in addition to standard of care while participants in the control group will receive only standard of care. Standard of care will be determined by the physician at the treatment centre in line with the current guidelines for clinical management of COVID-19 in Nigeria., Main Outcome Measures: Main outcome measures are: (1) Time to clinical improvement (defined as time from randomisation to either an improvement of two points on a 10-category ordinal scale (developed by the WHO Working Group on the Clinical Characterisation and Management of COVID-19 infection) or discharge from the hospital, whichever came first); (2) Proportion of participants with SARS-CoV-2 polymerase chain reaction (PCR) negative result at days 2, 4, 6, 7, 14 and 28; (3) Temporal patterns of SARS-CoV-2 viral load on days 2, 4, 6, 7, 14 and 28 quantified by RT-PCR from saliva of patients receiving standard of care alone versus standard of care plus study drugs., Randomisation: Allocation of participants to study arm is randomised within each site with a ratio 1:1 based on randomisation sequences generated centrally at Obafemi Awolowo University. The model was implemented in REDCap and includes stratification by age, gender, viral load at diagnosis and presence of relevant comorbidities., Blinding: None, this is an open-label trial., Number to Be Randomised (sample Size): 98 patients (49 per arm)., Trial Status: Regulatory approval was issued by the National Agency for Food and Drug Administration and Control on 06 October 2020 (protocol version number is 2.1 dated 06 August 2020). Recruitment started on 9 October 2020 and is anticipated to end before April 2021., Trial Registration: The trial has been registered on ClinicalTrials.gov (July 7, 2020), with identifier number NCT04459286 and on Pan African Clinical Trials Registry (August 13, 2020), with identifier number PACTR202008855701534 ., Full Protocol: The full protocol is attached as an additional file which will be made available on the trial website. In the interest of expediting dissemination of this material, the traditional formatting has been eliminated, and this letter serves as a summary of the key elements in the full protocol. The study protocol has been reported in accordance with the Standard Protocol Items: Recommendations for Clinical Interventional Trials (SPIRIT) guidelines (Additional file 2).
Published: 2021
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48. A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa.

Author: Harlemon M, Ajayi O, Kachambwa P, Kim MS, Simonti CN, Quiver MH, Petersen DC, Mittal A, Fernandez PW, Hsing AW, Baichoo S, Agalliu I, Jalloh M, Gueye SM, Snyper NYF, Adusei B, Mensah JE, Abrahams AOD, Adebiyi AO, Orunmuyi AT, Aisuodionoe-Shadrach OI, Nwegbu MM, Joffe M, Chen WC, Irusen H, Neugut AI, Quintana Y, Seutloali M, Fadipe MB, Warren C, Woehrmann MH, Zhang P, Ongaco CM, Mawhinney M, McBride J, Andrews CV, Adams M, Pugh E, Rebbeck TR, Petersen LN, and Lachance J
Subjects: Case-Control Studies, Cohort Studies, Genetic Loci, Genetics, Population, Genome-Wide Association Study, Humans, Male, Neoplasms classification, Prostatic Neoplasms classification, Risk Factors, South Africa epidemiology, Black People genetics, Genetic Predisposition to Disease, Neoplasms epidemiology, Neoplasms genetics, Polymorphism, Single Nucleotide, Prostatic Neoplasms epidemiology, Prostatic Neoplasms genetics
Abstract: Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. Samples from Ghana and Nigeria clustered together, whereas samples from Senegal and South Africa yielded distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores for prostate cancer were higher in Nigeria than in Senegal. In summary, individual and population-level differences in prostate cancer risk were revealed using a novel genotyping array. SIGNIFICANCE: This study presents an Africa-specific genotyping array, which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers., (©2020 American Association for Cancer Research.)
Published: 2020
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49. Delirium in Elderly Patients:Frequency and Precipitants in a Tertiary Hospital Setting.

Author: Yaria JO, Ogunjimi LO, Adebiyi AO, Olakehinde OO, Makanjuola AI, Paddick SM, and Ogunniyi A
Subjects: Aged, Aged, 80 and over, Cognitive Dysfunction epidemiology, Comorbidity, Confusion psychology, Delirium epidemiology, Delirium psychology, Dementia epidemiology, Diagnostic and Statistical Manual of Mental Disorders, Humans, Hypertension epidemiology, Mental Status Schedule statistics & numerical data, Middle Aged, Nervous System Diseases epidemiology, Neuropsychological Tests statistics & numerical data, Nigeria epidemiology, Sleep Wake Disorders epidemiology, Tertiary Care Centers, Cognitive Dysfunction diagnosis, Confusion diagnosis, Delirium diagnosis, Dementia diagnosis
Abstract: Objective: There is paucity of information on delirium in sub-Saharan Africa (SSA) particularly in the older persons (>60 years of age), leaving questions about the burden of the disease in an environment with lower health care standards. In this article, we set out to determine the frequency, precipitants and symptomatology of delirium in elderly patients admitted into medical wards in a teaching hospital in South-West Nigeria., Methods: This was a descriptive study involving a pre-planned sample of one hundred and fifty patients aged 60 years and over, assessed for cognitive impairment and delirium using the previously validated IDEA cognitive screen, and the Confusion Assessment Method (CAM) respectively. Diagnosis of delirium was made using the CAM and DSM-IV criteria., Results: Delirium was diagnosed in 32 patients giving a frequency of 21.3% (95%CI: 14.7-30.0%). Patients with delirium were significantly older (p<0.05). A quarter of the patients had dementia. Hypertension was a notable co-morbid condition. All the patients had altered sleep wake cycle, inattention, disorientation, and altered consciousness. Neurological diseases were the most common precipitant. There was a good agreement between the DSM-IV and CAM diagnoses., Conclusion: Delirium is common in hospitalised elderly patients particularly those with neurological diseases. Co-morbidities like hypertension, dementia, and depression should be looked for in delirious elderly patients.
Published: 2019

50. Medication adherence and 24-h blood pressure in apparently uncontrolled hypertensive Nigerian patients.

Author: Adeoye AM, Adebiyi AO, Adebayo OM, and Owolabi MO
Subjects: Adult, Aged, Antihypertensive Agents therapeutic use, Blood Pressure Monitoring, Ambulatory, Case-Control Studies, Cross-Sectional Studies, Female, Health Knowledge, Attitudes, Practice, Humans, Hypertension epidemiology, Middle Aged, Motivation, Nigeria epidemiology, Risk Factors, Antihypertensive Agents administration & dosage, Blood Pressure drug effects, Hypertension drug therapy, Hypertension psychology, Medication Adherence psychology
Abstract: Background: Uncontrolled hypertension is a major risk for major cardiovascular events. While medication adherence determines blood pressure (BP) control, studies on treatment adherence among apparently uncontrolled hypertensives are sorely lacking in sub-Saharan Africa. We report the pattern and correlate of medication adherence among the uncontrolled hypertensive population., Materials and Methods: We investigated 148 age- and sex-matched hypertensive adults on anti-hypertensive medication for a minimum of 1 year. Apparent uncontrolled BP was defined as clinic BP ≥140/90 mmHg, whereas 24-h ambulatory BP monitoring was used to determine the true uncontrolled hypertension and other BP phenotypes. Using the 8-item Morisky medication adherence scale participants were classified into high, moderate and low adherence while Modified Morisky Scale was used to assess knowledge and motivation., Results: The mean age and BP were 61 ± 13.3 years and 158/91 mmHg, respectively. High adherence was found in 4.1% of the participants while 68.9% and 27% had moderate and low adherence, respectively. A third had true uncontrolled hypertension. A high proportion of the study participants also had a high motivation (68.9%) and knowledge (89.2%). Medication adherence was associated with motivation (P = 0.0001), knowledge (P = 0.002) and obesity (P = 0.036). Knowledge was an independent determinant of medication adherence with no significant effect on BP control., Conclusion: High medication adherence was low and a third had true uncontrolled hypertension. Knowledge was an independent predictor of medication adherence with no significant effect on blood control. High medication adherence rather than moderate adherence, and knowledge are indeed needed for adequate BP control., Competing Interests: None
Published: 2019
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