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4. Adolescent transport and unintentional injuries: a systematic analysis using the Global Burden of Disease Study 2019

Author

Peden, Amy E, Cullen, Patricia, Francis, Kate Louise, Moeller, Holger, Peden, Margaret M, Ye, Pengpeng, Tian, Maoyi, Zou, Zhiyong, Sawyer, Susan M, Aali, Amirali, Abbasi-Kangevari, Zeinab, Abbasi-Kangevari, Mohsen, Abdelmasseh, Michael, Abdoun, Meriem, Abd-Rabu, Rami, Abdulah, Deldar Morad, Abebe, Getachew, Abebe, Ayele Mamo, Abedi, Aidin, Abidi, Hassan, Aboagye, Richard Gyan, Abubaker Ali, Hiwa, Abu-Gharbieh, Eman, Adane, Denberu Eshetie, Adane, Tigist Demssew, Addo, Isaac Yeboah, Adewole, Ololade Grace, Adhikari, Sangeet, Adnan, Mohammad, Adnani, Qorinah Estiningtyas Sakilah, Afolabi, Aanuoluwapo Adeyimika Bachelor, Afzal, Saira, Afzal, Muhammad Sohail, Aghdam, Zahra Babaei, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Tauseef, Ahmad, Sajjad, Ahmadi, Ali, Ahmed, Haroon, Ahmed, Muktar Beshir, Ahmed, Ali, Ahmed, Ayman, Ahmed, Jivan Qasim, Ahmed Rashid, Tarik, Aithala, Janardhana P, Aji, Budi, Akhlaghdoust, Meisam, Alahdab, Fares, Alanezi, Fahad Mashhour, Alemayehu, Astawus, Al Hamad, Hanadi, Ali, Syed Shujait, Ali, Liaqat, Alimohamadi, Yousef, Alipour, Vahid, Aljunid, Syed Mohamed, Almidani, Louay, Almustanyir, Sami, Altirkawi, Khalid A, Alvis-Zakzuk, Nelson J, Ameyaw, Edward Kwabena, Amin, Tarek Tawfik, Amir-Behghadami, Mehrdad, Amiri, Sohrab, Amiri, Hoda, Anagaw, Tadele Fentabil, Andrei, Tudorel, Andrei, Catalina Liliana, Anvari, Davood, Anwar, Sumadi Lukman, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Arab-Zozani, Morteza, Arja, Asrat, Arulappan, Judie, Arumugam, Ashokan, Aryannejad, Armin, Asgary, Saeed, Ashraf, Tahira, Athari, Seyyed Shamsadin, Atreya, Alok, Attia, Sameh, Aujayeb, Avinash, Awedew, Atalel Fentahun, Azadnajafabad, Sina, Azangou-Khyavy, Mohammadreza, Azari, Samad, Azari Jafari, Amirhossein, Azizi, Hosein, Azzam, Ahmed Y, Badiye, Ashish D, Baghcheghi, Nayereh, Bagherieh, Sara, Baig, Atif Amin, Bakkannavar, Shankar M, Balta, Asaminew Birhanu, Banach, Maciej, Banik, Palash Chandra, Bansal, Hansi, Bardhan, Mainak, Barone-Adesi, Francesco, Barrow, Amadou, Bashiri, Azadeh, Baskaran, Pritish, Basu, Saurav, Bayileyegn, Nebiyou Simegnew, Bekel, Abebe Ayalew, Bekele, Alehegn Bekele, Bendak, Salaheddine, Bensenor, Isabela M, Berhie, Alemshet Yirga, Bhagat, Devidas S, Bhagavathula, Akshaya Srikanth, Bhardwaj, Pankaj, Bhardwaj, Nikha, Bhaskar, Sonu, Bhat, Ajay Nagesh, Bhattacharyya, Krittika, Bhutta, Zulfiqar A, Bibi, Sadia, Bintoro, Bagas Suryo, Bitaraf, Saeid, Bodicha, Belay Boda Abule, Boloor, Archith, Bouaoud, Souad, Brown, Julie, Burkart, Katrin, Butt, Nadeem Shafique, Butt, Muhammad Hammad, Cámera, Luis Alberto, Campuzano Rincon, Julio Cesar, Cao, Chao, Carvalho, Andre F, Carvalho, Márcia, Chakraborty, Promit Ananyo, Chandrasekar, Eeshwar K, Chang, Jung-Chen, Charalampous, Periklis, Charan, Jaykaran, Chattu, Vijay Kumar, Chekole, Bitew Mekonnen, Chitheer, Abdulaal, Cho, Daniel Youngwhan, Chopra, Hitesh, Christopher, Devasahayam J, Chukwu, Isaac Sunday, Cruz-Martins, Natália, Dadras, Omid, Dahlawi, Saad M A, Dai, Xiaochen, Damiani, Giovanni, Darmstadt, Gary L, Darvishi Cheshmeh Soltani, Reza, Darwesh, Aso Mohammad, Das, Saswati, Dastiridou, Anna, Debela, Sisay Abebe, Dehghan, Amin, Demeke, Getnet Makasha, Demetriades, Andreas K, Demissie, Solomon, Dessalegn, Fikadu Nugusu, Desta, Abebaw Alemayehu, Dianatinasab, Mostafa, Diao, Nancy, Dias da Silva, Diana, Diaz, Daniel, Digesa, Lankamo Ena, Diress, Mengistie, Djalalinia, Shirin, Doan, Linh Phuong, Dodangeh, Milad, Doku, Paul Narh, Dongarwar, Deepa, Dsouza, Haneil Larson, Eini, Ebrahim, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Elagali, Ahmed Elabbas Mustafa, Elbahnasawy, Mostafa Ahmed, Elhabashy, Hala Rashad, Elhadi, Muhammed, El Sayed Zaki, Maysaa, Enyew, Daniel Berhanie, Erkhembayar, Ryenchindorj, Eskandarieh, Sharareh, Etaee, Farshid, Fagbamigbe, Adeniyi Francis, Faris, Pawan Sirwan, Farmany, Abbas, Faro, Andre, Farzadfar, Farshad, Fatehizadeh, Ali, Fereshtehnejad, Seyed-Mohammad, Feroze, Abdullah Hamid, Fetensa, Getahun, Feyisa, Bikila Regassa, Filip, Irina, Fischer, Florian, Foroutan, Behzad, Foroutan, Masoud, Fowobaje, Kayode Raphael, Franklin, Richard Charles, Fukumoto, Takeshi, Gaal, Peter Andras, Gadanya, Muktar A, Galali, Yaseen, Galehdar, Nasrin, Ganesan, Balasankar, Garg, Tushar, Gebrehiwot, Mesfin Gebrehiwot Damtew, Gebremariam, Yosef Haile, Gela, Yibeltal Yismaw, Gerema, Urge, Ghafourifard, Mansour, Ghamari, Seyyed-Hadi, Ghanbari, Reza, Ghasemi Nour, Mohammad, Gholamalizadeh, Maryam, Gholami, Ali, Gholamrezanezhad, Ali, Ghozy, Sherief, Gilani, Syed Amir, Gill, Tiffany K, Giné-Vázquez, Iago, Girma, Zeleke Abate, Glasbey, James C, Glozah, Franklin N, Golechha, Mahaveer, Goleij, Pouya, Grivna, Michal, Guadie, Habtamu Alganeh, Gunawardane, Damitha Asanga, Guo, Yuming, Gupta, Veer Bala, Gupta, Sapna, Gupta, Bhawna, Gupta, Vivek Kumar, Haj-Mirzaian, Arvin, Halwani, Rabih, Hamadeh, Randah R, Hameed, Sajid, Hanif, Asif, Hargono, Arief, Harlianto, Netanja I, Harorani, Mehdi, Hasaballah, Ahmed I, Hasan, S M Mahmudul, Hassan, Amr, Hassanipour, Soheil, Hassankhani, Hadi, Havmoeller, Rasmus J, Hay, Simon I, Heidari, Mohammad, Hendrie, Delia, Heyi, Demisu Zenbaba, Hiraike, Yuta, Holla, Ramesh, Horita, Nobuyuki, Hossain, Sheikh Jamal, Hossain, Mohammad Bellal Hossain, Hosseini Shabanan, Sedighe, Hosseinzadeh, Mehdi, Hostiuc, Sorin, Hoveidaei, Amir Human, Hsiao, Alexander Kevin, Hussain, Salman, Hussein, Amal, Ibitoye, Segun Emmanuel, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Immurana, Mustapha, Inbaraj, Leeberk Raja, Islam, Sheikh Mohammed Shariful, Islam, Rakibul M, Islam, Mohammad Mainul, Ismail, Nahlah Elkudssiah, J, Linda Merin, Jahrami, Haitham, Jakovljevic, Mihajlo, Janodia, Manthan Dilipkumar, Javaheri, Tahereh, Jayapal, Sathish Kumar, Jayarajah, Umesh Umesh, Jayaraman, Sudha, Jeganathan, Jayakumar, Jemal, Bedru, Jha, Ravi Prakash, Jonas, Jost B, Joo, Tamas, Joseph, Nitin, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Ali, Kadashetti, Vidya, Kadir, Dler Hussein, Kalankesh, Laleh R, Kalankesh, Leila R, Kalhor, Rohollah, Kamal, Vineet Kumar, Kamath, Rajesh, Kandel, Himal, Kantar, Rami S, Kapoor, Neeti, Karami, Hassan, Karaye, Ibraheem M, Karkhah, Samad, Katoto, Patrick DMC, Kauppila, Joonas H, Kayode, Gbenga A, Keikavoosi-Arani, Leila, Keskin, Cumali, Khader, Yousef Saleh, Khajuria, Himanshu, Khammarnia, Mohammad, Khan, Ejaz Ahmad, Khan, Md Nuruzzaman, Khan, Maseer, Khan, Yusra H, Khan, Imteyaz A, Khan, Abbas, Khan, Moien AB, Khanali, Javad, Khatatbeh, Moawiah Mohammad, Khayat Kashani, Hamid Reza, Khubchandani, Jagdish, Kifle, Zemene Demelash, Kim, Jihee, Kim, Yun Jin, Kisa, Sezer, Kisa, Adnan, Kneib, Cameron J, Kompani, Farzad, Koohestani, Hamid Reza, Koul, Parvaiz A, Koulmane Laxminarayana, Sindhura Lakshmi, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Vijay, Kucuk Bicer, Burcu, Kumar, Nithin, Kumar, Naveen, Kumar, Narinder, Kumar, Manasi, Kurmi, Om P, Laflamme, Lucie, Lám, Judit, Landires, Iván, Larijani, Bagher, Lasrado, Savita, Lauriola, Paolo, La Vecchia, Carlo, Lee, Shaun Wen Huey, Lee, Yo Han, Lee, Sang-woong, Lee, Wei-Chen, Legesse, Samson Mideksa, Li, Shanshan, Lim, Stephen S, Lorenzovici, László, Luke, Amana Ogeto, Madadizadeh, Farzan, Madureira-Carvalho, Áurea M, Magdy Abd El Razek, Muhammed, Mahjoub, Soleiman, Mahmoodpoor, Ata, Mahmoudi, Razzagh, Mahmoudimanesh, Marzieh, Majeed, Azeem, Makki, Alaa, Malakan Rad, Elaheh, Malekpour, Mohammad-Reza, Malik, Ahmad Azam, Mallhi, Tauqeer Hussain, Malta, Deborah Carvalho, Mansouri, Borhan, Mansournia, Mohammad Ali, Mathews, Elezebeth, Maulud, Sazan Qadir, Mazingi, Dennis, Mehrabi Nasab, Entezar, Mendoza-Cano, Oliver, Menezes, Ritesh G, Mengistu, Dechasa Adare, Mentis, Alexios-Fotios A, Meretoja, Atte, Mesregah, Mohamed Kamal, Mestrovic, Tomislav, Micheletti Gomide Nogueira de Sá, Ana Carolina, Miller, Ted R, Mirghaderi, Seyed Peyman, Mirica, Andreea, Mirmoeeni, Seyyedmohammadsadeq, Mirrakhimov, Erkin M, Mirza, Moonis, Misra, Sanjeev, Mithra, Prasanna, Mittal, Chaitanya, Moberg, Madeline E, Mohammadi, Mokhtar, Mohammadi, Soheil, Mohammadi, Esmaeil, Mohammadpourhodki, Reza, Mohammed, Shafiu, Mohammed, Teroj Abdulrahman, Mohseni, Mohammad, Mokdad, Ali H, Momtazmanesh, Sara, Monasta, Lorenzo, Moni, Mohammad Ali, Moreira, Rafael Silveira, Morrison, Shane Douglas, Mostafavi, Ebrahim, Mousavi Isfahani, Haleh, Mubarik, Sumaira, Muccioli, Lorenzo, Mukherjee, Soumyadeep, Mulita, Francesk, Mustafa, Ghulam, Nagarajan, Ahamarshan Jayaraman, Naimzada, Mukhammad David, Nangia, Vinay, Nassereldine, Hasan, Natto, Zuhair S, Nayak, Biswa Prakash, Negoi, Ionut, Nejadghaderi, Seyed Aria, Nepal, Samata, Neupane Kandel, Sandhya, Noroozi, Nafise, Nuñez-Samudio, Virginia, Nzoputam, Ogochukwu Janet, Nzoputam, Chimezie Igwegbe, Ochir, Chimedsuren, Odhiambo, Julius Nyerere, Odukoya, Oluwakemi Ololade, Okati-Aliabad, Hassan, Okonji, Osaretin Christabel, Olagunju, Andrew T, Omar Bali, Ahmed, Omer, Emad, Otoiu, Adrian, Otstavnov, Stanislav S, Otstavnov, Nikita, Oumer, Bilcha, Owolabi, Mayowa O, P A, Mahesh, Padron-Monedero, Alicia, Padubidri, Jagadish Rao, Pahlevan Fallahy, Mohammad Taha, Palicz, Tamás, Panda-Jonas, Songhomitra, Pandi-Perumal, Seithikurippu R, Pardhan, Shahina, Park, Eun-Kee, Patel, Sangram Kishor, Pathan, Aslam Ramjan, Pati, Siddhartha, Paudel, Uttam, Pawar, Shrikant, Pedersini, Paolo, Peres, Mario F P, Petcu, Ionela-Roxana, Phillips, Michael R, Pillay, Julian David, Piracha, Zahra Zahid, Poursadeqiyan, Mohsen, Pourtaheri, Naeimeh, Qattea, Ibrahim, Radfar, Amir, Rafiee, Ata, Raghav, Pankaja Raghav, Rahim, Fakher, Rahman, Muhammad Aziz, Rahman, Firman Suryadi, Rahman, Mosiur, Rahmani, Amir Masoud, Rahmani, Shayan, Raj Moolambally, Sheetal, Ramazanu, Sheena, Ramezanzadeh, Kiana, Rana, Juwel, Rao, Chythra R, Rao, Sowmya J, Rashedi, Vahid, Rashidi, Mohammad-Mahdi, Rastogi, Prateek, Rasul, Azad, Rawaf, Salman, Rawaf, David Laith, Rawal, Lal, Rawassizadeh, Reza, Rezaei, Negar, Rezaei, Nazila, Rezaeian, Mohsen, Rezapour, Aziz, Riad, Abanoub, Riaz, Muhammad, Rickard, Jennifer, Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Ronfani, Luca, Roy, Bedanta, S, Manjula, Saad, Aly M A, Sabour, Siamak, Sabzmakan, Leila, Saddik, Basema, Sadeghi, Malihe, Saeb, Mohammad Reza, Saeed, Umar, Saeedi Moghaddam, Sahar, Safi, Sher Zaman, Sahiledengle, Biniyam, Sahoo, Harihar, Sahraian, Mohammad Ali, Saki, Morteza, Salamati, Payman, Salehi, Sana, Salem, Marwa Rashad, Samy, Abdallah M, Sanabria, Juan, Santric-Milicevic, Milena M, Saqib, Muhammad Arif Nadeem, Sarikhani, Yaser, Sarveazad, Arash, Sathian, Brijesh, Satpathy, Maheswar, Saya, Ganesh Kumar, Schneider, Ione Jayce Ceola, Schwebel, David C, Seddighi, Hamed, Senthilkumaran, Subramanian, Seylani, Allen, Shabaninejad, Hosein, Shafeghat, Melika, Shah, Pritik A, Shahabi, Saeed, Shahbandi, Ataollah, Shahraki-Sanavi, Fariba, Shaikh, Masood Ali, Shaker, Elaheh, Shams-Beyranvand, Mehran, Shanawaz, Mohd, Shannawaz, Mohammed, Sharew, Mequannent Melaku Sharew, Sharma, Neeraj, Shashamo, Bereket Beyene, Shayan, Maryam, Sheikhi, Rahim Ali, Shen, Jiabin, Shetty, B Suresh Kumar, Shetty, Pavanchand H, Shin, Jae Il, Shitaye, Nebiyu Aniley, Shivakumar, K M, Shobeiri, Parnian, Shorofi, Seyed Afshin, Shrestha, Sunil, Siabani, Soraya, Sidemo, Negussie Boti, Simegn, Wudneh, Sinaei, Ehsan, Singh, Paramdeep, Sinto, Robert, Siraj, Md Shahjahan, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Sleet, David A, S N, Chandan, Socea, Bogdan, Solmi, Marco, Solomon, Yonatan, Song, Yi, Sousa, Raúl A R C, Soyiri, Ireneous N, Stokes, Mark A, Suleman, Muhammad, Suliankatchi Abdulkader, Rizwan, Sun, Jing, Szócska, Miklós, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabish, Mohammad, Taheri, Ensiyeh, Taheri Soodejani, Moslem, Tampa, Mircea, Tan, Ker-Kan, Tarigan, Ingan Ukur, Tariqujjaman, Md, Tat, Nathan Y, Tat, Vivian Y, Tavakoli, Arash, Tefera, Belay Negash, Tefera, Yibekal Manaye, Temesgen, Gebremaryam, Temsah, Mohamad-Hani, Thangaraju, Pugazhenthan, Thapar, Rekha, Thomas, Nikhil Kenny, Ticoalu, Jansje Henny Vera, Tincho, Marius Belmondo, Tiyuri, Amir, Togtmol, Munkhsaikhan, Tovani-Palone, Marcos Roberto, Tran, Mai Thi Ngoc, Ullah, Sana, Ullah, Saif, Ullah, Irfan, Umakanthan, Srikanth, Unnikrishnan, Bhaskaran, Upadhyay, Era, Valadan Tahbaz, Sahel, Valdez, Pascual R, Vasankari, Tommi Juhani, Vaziri, Siavash, Veroux, Massimiliano, Vervoort, Dominique, Violante, Francesco S, Vlassov, Vasily, Vu, Linh Gia, Waheed, Yasir, Wang, Yanzhong, Wang, Yuan-Pang, Wang, Cong, Wiangkham, Taweewat, Wickramasinghe, Nuwan Darshana, Woday, Abay Tadesse, Wu, Ai-Min, Yahya, Gahin Abdulraheem Tayib, Yahyazadeh Jabbari, Seyed Hossein, Yang, Lin, Yaya, Sanni, Yigit, Arzu, Yiğit, Vahit, Yisihak, Eshetu, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yu, Chuanhua, Yunusa, Ismaeel, Yusefi, Hossein, Zahir, Mazyar, Zaman, Sojib Bin, Zare, Iman, Zarea, Kourosh, Zastrozhin, Mikhail Sergeevich, Zhang, Zhi-Jiang, Zhang, Yunquan, Ziapour, Arash, Zodpey, Sanjay, Zoladl, Mohammad, Patton, George C, and Ivers, Rebecca Q

Published
2022
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7. Latrine utilization and associated factors among districts implementing and not-implementing community-led total sanitation and hygiene in East Wollega, Western Ethiopia: A comparative cross-sectional study.

Author

Shama, Adisu Tafari, Terefa, Dufera Rikitu, Geta, Edosa Tesfaye, Cheme, Melese Chego, Biru, Bayise, Feyisa, Jira Wakoya, Lema, Matiyos, Desisa, Adisu Ewunetu, Feyisa, Bikila Regassa, and Gebre, Dejene Seyoum

Subjects
SANITATION, TOILETS, HYGIENE, CROSS-sectional method, SURFACE contamination, PATHOGENIC microorganisms
Abstract

Introduction: Discharge of excreta to the environment lead to surface and groundwater contamination and human exposure to disease-causing micro-organisms. There is limitation of evidences regarding the latrine utilization among community-led total sanitation and hygiene implemented and non-implemented districts of the East Wollega Zone. Hence, this study aimed to determine the magnitude and associated factors of latrine utilization among households in community-led total sanitation and hygiene implemented and non-implemented Districts in East Wollega Zone, Western Ethiopia. Methods: A cross-sectional study was conducted. A Multi-stage sampling technique was applied to select the 461 households. Data were collected using interviews and observations guided by a pre-structured questionnaire. Data were entered using Epi Data and exported to SPSS software version 25 for data recording, cleaning, and statistical analysis. Bivariable logistic regression was run to identify the candidate variables at p-value <0.25. Variables that had associations with latrine utilization in the bi-variable analysis were entered together into multivariable logistic regression. An Adjusted odds ratio with a 95% confidence interval was calculated and P-value< 0.05 was used to declare a statistically significant association. Result: The overall prevalence of latrine utilization was found to be 52.7% (95%CI:48%, 57.3%). Religion (AOR = 0.149;95%CI:0.044,0.506), education (AOR = 3.861;95%CI:1.642,9.077), occupation, absence of children <5 years (AOR = 4.724;95%CI:2.313,9.648), toilet cleaning (AOR = 10.662;95%CI:5.571,20.403), frequency of latrine construction (AOR = 6.441;95%CI:2.203,18.826), maintenance need (AOR = 6.446; 95%CI:3.023,13.744), distance from health institution (AOR = 0.987; 95%CI:0.978, 0.996), distance from kebele office (AOR = 6.478; 95%CI:2.137,19.635), and latrine distance from dwelling (AOR = 11.656; 95%CI:2.108, 64.44) were the factors associated with latrine use. Conclusion: The latrine utilization in this study is low as compared to other studies. Religion, education, occupation, absence of children <5 years, toilet cleaning, frequency of latrine construction, maintenance need of the toilet, distance from health institution, distance from kebele, and latrine distance from dwelling are the associated factors of latrine utilization. Both households and health workers have to work together to improve latrine utilization and the safe disposal of children's feces. [ABSTRACT FROM AUTHOR]

Published
2023
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10. COVID-19 Vaccine Uptake and Associated Factors Among Health Professionals in Ethiopia

Author

Rikitu Terefa, Dufera, Shama, Adisu Tafari, Feyisa, Bikila Regassa, Ewunetu Desisa, Adisu, Geta, Edosa Tesfaye, Chego Cheme, Melese, and Tamiru Edosa, Afework

Subjects
Pharmacology, Infectious Diseases, Infection and Drug Resistance, vaccine, health professionals, uptake, COVID-19, Pharmacology (medical), Ethiopia, Original Research
Abstract

Dufera Rikitu Terefa, Adisu Tafari Shama, Bikila Regassa Feyisa, Adisu Ewunetu Desisa, Edosa Tesfaye Geta, Melese Chego Cheme, Afework Tamiru Edosa Department of Public Health, Institute of Health Science, Wollega University, Nekemte, EthiopiaCorrespondence: Dufera Rikitu TerefaDepartment of Public Health, Institute of Health Science, Wollega University, P.O.Box=395, Nekemte, EthiopiaTel +251-922260706Email duferarikitu24@gmail.com; duferar@wollegauniversity.edu.etBackground: Ethiopia has received 2.2 million doses of COVID-19 vaccine from the COVID-19 Vaccines Global Access (COVAX) facility and planned to vaccinate 20% of its population by the end of 2021. However, evidence on the current uptake of the vaccine in our country is scanty. Therefore, this study aimed to assess COVID-19 vaccine uptake and associated factors among health professionals in Ethiopia.Methods: A national online cross-sectional E-survey was conducted on COVID-19 vaccine Uptake and associated factors among health professionals in Ethiopia from June 1 to 30, 2021. A semi-structured questionnaire was created on Google forms and disseminated online. The snowball sampling technique through the authors’ network with Ethiopian residents on the popular social media like Facebook, telegram, and email was used. Descriptive statistics were performed. Multivariable logistic regression analysis was performed using Statistical Package for Social Sciences version 25, and all variables with P-value < 0.05 and adjusted odds ratio at 95% CI were used to declare the predictors of the outcome variable.Results: A total of 522 health professionals participated in the survey, of which about 324 (62.1%) of them were vaccinated with any of the COVID-19 vaccines at least once. The study indicated that COVID-19 vaccine uptake was associated with age range from 35 to 44 years [AOR = 12.97, 95% CI: 2.36– 71.21], age beyond 45 years [AOR = 18.95, 95% CI = 2.04– 36.29], being male [AOR = 2.91, 95% CI = 1.05,8.09], being only an academician [AOR = 0.23, 95% CI: 0.10– 0.49], academicians working in University hospitals [AOR = 0.19, 95% CI: 0.05– 0.83], perceiving their family as healthy [AOR = 4.40, 95% CI: 2.21– 8.75], no history of receiving other vaccine before as an adult [AOR = 4.07, 95% CI: 2.07– 8.01] and no history of contact with confirmed COVID-19 patients or clients [AOR = 0.42, 95% CI: 0.20– 0.86].Conclusion: The study found that COVID-19 vaccine uptake among health professionals was low. This was not sufficient to achieve herd immunity as at least nine out of ten health professionals are required for herd immunity. Ages, sex, place of work, perceived family health status, previous experience of receiving a vaccine as an adult and history of contact with COVID-19 clients or patients were the factors that influence the vaccine uptake among health professionals in Ethiopia. Hence, decision makers and health managers should consider instituting mandatory vaccination for health professionals and design strategies for the provision of the vaccine.Keywords: COVID-19, vaccine, health professionals, uptake, Ethiopia

Published
2021

13. Predictors of health related quality of life among diabetic patients on follow up at Nekemte Specialized Hospital, Western Ethiopia: A cross sectional study

Author

Feyisa, Bikila Regassa, Yilma, Mekdes Tigistu, and Tolessa, Belachew Etana

Subjects
Gerontology, Response rate (survey), business.industry, Cross-sectional study, media_common.quotation_subject, Vitality, medicine.disease, Mental health, Quality of life, Feeling, Diabetes mellitus, Medicine, business, Body mass index, media_common
Abstract

ObjectiveTo assess health related quality of life (HRQoL) and its predictors among diabetic patients on follow up at Nekemte Specialized Hospital (NSH) in Western Ethiopia.Design, setting and participantsThis facility based cross sectional study was conducted among 224 diabetic patients on follow up at one of the public hospitals in western Ethiopia.Main outcome measuredHRQoL was measured by using the Medical Outcome Study 36-item Short Form Health Survey from 15th April to 5th June. Structured questionnaire was used for data the collection from participants selected by systematic random sampling. Multiple linear regression was used for final model.ResultA total of 215 diabetic patients were involved in the study with the response rate of 96%. The mean score of the overall HRQoL of the study participants was found to be 50.30 ± 18.08 with highest mean score in physical functioning and lowest mean score in general health domain. Age, education status, history of smoking, feeling of stigmatized and Body mass index (BMI) were inversely associated while being male, being married, absence of co morbidity and absence of chronic complications related to diabetes mellitus were found to be positively associated with overall HRQoL.ConclusionThe overall HRQoL of diabetic patients on follow up at the study area was found to be moderate. General health, mental health, bodily pain and vitality were the most affected domains. Both the mental and physical components need to be considered when caring the diabetic patients on follow up beyond provision of treatment.Strength and limitations of this studyThe study was the first of its kind in assessing the predictors of health-related quality of life (HRQoL) among both diabetes mellitus type I and type II in Ethiopia.The tools used was validated across different culturesEight domains of HRQoL and two component summary scores were used to make the measurement more specific.The cross sectional nature of the study design made the result of the study difficult to identify either the cause or the effect comes first.

Published
2019

15. COVID-19 Vaccine Uptake and Associated Factors Among Health Professionals in Ethiopia.

Author

Terefa, Dufera Rikitu, Shama, Adisu Tafari, Feyisa, Bikila Regassa, Desisa, Adisu Ewunetu, Geta, Edosa Tesfaye, Cheme, Melese Chego, and Edosa, Afework Tamiru

Subjects
MEDICAL personnel, VACCINATION status, COVID-19 vaccines, VACCINATION, MULTIVARIABLE testing, COVID-19, SOCIAL media
Abstract

Background: Ethiopia has received 2.2 million doses of COVID-19 vaccine from the COVID-19 Vaccines Global Access (COVAX) facility and planned to vaccinate 20% of its population by the end of 2021. However, evidence on the current uptake of the vaccine in our country is scanty. Therefore, this study aimed to assess COVID-19 vaccine uptake and associated factors among health professionals in Ethiopia. Methods: A national online cross-sectional E-survey was conducted on COVID-19 vaccine Uptake and associated factors among health professionals in Ethiopia from June 1 to 30, 2021. A semi-structured questionnaire was created on Google forms and disseminated online. The snowball sampling technique through the authors' network with Ethiopian residents on the popular social media like Facebook, telegram, and email was used. Descriptive statistics were performed. Multivariable logistic regression analysis was performed using Statistical Package for Social Sciences version 25, and all variables with P-value < 0.05 and adjusted odds ratio at 95% CI were used to declare the predictors of the outcome variable. Results: A total of 522 health professionals participated in the survey, of which about 324 (62.1%) of them were vaccinated with any of the COVID-19 vaccines at least once. The study indicated that COVID-19 vaccine uptake was associated with age range from 35 to 44 years [AOR = 12.97, 95% CI: 2.36– 71.21], age beyond 45 years [AOR = 18.95, 95% CI = 2.04– 36.29], being male [AOR = 2.91, 95% CI = 1.05,8.09], being only an academician [AOR = 0.23, 95% CI: 0.10– 0.49], academicians working in University hospitals [AOR = 0.19, 95% CI: 0.05– 0.83], perceiving their family as healthy [AOR = 4.40, 95% CI: 2.21– 8.75], no history of receiving other vaccine before as an adult [AOR = 4.07, 95% CI: 2.07– 8.01] and no history of contact with confirmed COVID-19 patients or clients [AOR = 0.42, 95% CI: 0.20– 0.86]. Conclusion: The study found that COVID-19 vaccine uptake among health professionals was low. This was not sufficient to achieve herd immunity as at least nine out of ten health professionals are required for herd immunity. Ages, sex, place of work, perceived family health status, previous experience of receiving a vaccine as an adult and history of contact with COVID-19 clients or patients were the factors that influence the vaccine uptake among health professionals in Ethiopia. Hence, decision makers and health managers should consider instituting mandatory vaccination for health professionals and design strategies for the provision of the vaccine. [ABSTRACT FROM AUTHOR]

Published
2021
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16. Predictors of Health-Related Quality of Life among Patients with Diabetes Mellitus

Author

Feyisa, Bikila Regassa

Subjects
Medical
Abstract

The health of general population cannot be well characterized from the analyses of mortality and morbidity statistics alone, particularly for patients of chronic diseases including diabetes mellitus. It is equally important to contemplate health in terms of people’s assessment of their sense of well-being and ability to perform social roles. A number of reasons are there to measure the health-related quality of life among patients with diabetes mellitus. For one thing, diabetes patients are highly interested in functional capacity and well-being. On the other hand, patients in the same clinical manifestations might have different responses. Either general or specific instruments could be utilized to measure the health-related quality of life of diabetes patients. Choice of the instrument depends on time of the measurement, validity of the instrument and the interpretability. In Ethiopia, short form 36 (SF-36) instruments were utilized and the highest (63.2 ± 34.4) and the lowest (30.2 ± 22.9) mean score scored in physical functioning and general health domain respectively. The study indicated that age, sex, marital status, educational status, feeling of stigmatized, co-morbidity status, chronic complication and body mass index are some of the predictors of health-related quality of life for patients living with diabetes mellitus.

Published
2018

17. Time to first birth and its predictors among reproductive-age women in Ethiopia: multilevel analysis using shared frailty model.

Author

Feyisa BR, Shiferaw D, Yesse M, Shama AT, Duressa LT, and Biru B

Subjects
Humans, Female, Ethiopia epidemiology, Adult, Adolescent, Young Adult, Middle Aged, Rural Population statistics & numerical data, Pregnancy, Time Factors, Health Surveys, Socioeconomic Factors, Contraception Behavior statistics & numerical data, Multilevel Analysis
Abstract

Objective: To determine the time to first birth and its predictors among reproductive-age women in Ethiopia., Design, Setting and Participants: Nationwide secondary data analysis using mini Ethiopian Demographic and Health Survey, 2019. A stratified, two-stage cluster sampling technique was used to select the sample. Among 9012 women of age 15-49 years, 8885 completed the interview yielding a response rate of 99%., Main Outcomes Measured: Time to first birth was determined. Kaplan-Meier method was used to estimate the time to first birth. The lognormal inverse Gaussian shared frailty model was used to model the data at a 95% CI. CI and adjusted time ratio (ATR) were reported as effect size. Statistical significance was declared at p-value<0.05., Results: The overall median time to give first birth was 18 years (IQR: 15, 21). Age 20-29 (ATR=1.08; 95% CI, 1.05 to 1.12), Age>29 years (ATR=1.08; 95% CI, 1.05 to 1.11), northern regions (ATR=1.06; 95% CI, 1.03 to 1.08), rural residence (ATR=0.95; 95% CI, 0.93 to 0.98), never using contraceptive methods (ATR=0.98; 95% CI, 0.96 to 0.99), sex of household head (ATR=1.01; 95% CI, 1 to 1.03), poorest wealth index (ATR=1.04; 95% CI, 1.02 to 1.06) and richest wealth index (ATR=1.07; 95% CI, 1.04 to 1.1) were the significant predictors of time to first birth among reproductive-age women., Conclusion: In Ethiopia, women often gave birth to their first child at a younger age than what is recommended. Explicitly, women aged 20-29 and over 29, living in the northern region, leading a household as females, and belonging to the poorest or wealthiest wealth index tended to have a slightly delayed first childbirth. On the other hand, women in rural areas and those who had never used contraception were more likely to have an early first birth. The findings indicated the necessity of implementing targeted measures for rural Ethiopian women, especially those lacking knowledge about contraception., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Published
2024
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18. Magnitude of hypertension and its association with obesity among employees of Wallaga University, Ethiopia: a cross-sectional study.

Author

Feyisa BR, Tamiru A, Debelo S, Feyisa I, Tola EK, Tolesa EJ, Negeri A, Shibiru T, Galata A, and Biru B

Subjects
Humans, Adult, Middle Aged, Cross-Sectional Studies, Ethiopia epidemiology, Universities, Obesity epidemiology, Hypertension epidemiology
Abstract

Objective: To determine the magnitude of hypertension, its association with obesity and the associated factors among employees of Wallaga University, Ethiopia., Design, Setting and Participants: This institution-based cross-sectional study was employed among 588 employees of the university. Respondents were selected by stratified random sampling technique and interviewed with the aid of a structured questionnaire., The Main Outcome Measured: Hypertension and obesity were measured using WHO Stepwise approach and recommendations. We used a stratified random sampling technique to select 588 employees of the university from 3 August 2021 to 15 October 2021. A structured questionnaire and anthropometric measurements were used for data collection. Multivariable logistic regression analysis was used to determine factors independently associated with hypertension. A p value less than or equal to 0.05 and its 95% confidence level was used to declare the statistical significance., Results: A total of 578 participants consented and completed the study, giving a response rate of 98.3%. The mean age of the respondents was 31.78 years with SD of 5.4. The overall prevalence of hypertension, general obesity and central obesity was 14.4% (95% CI 11.6% to 17.5%), 31.3% (95% CI 27.6% to 35.3%) and 37% (95% CI 33.1% to 41.1%), respectively. Obesity was significantly associated with hypertension (adjusted OR (AOR): 6.3; 95% CI 2.60 to 8.19). Age range from 35 to 46 (AOR 7.01; 95% CI 1.56 to 31.74), age ≥46 years (AOR 8.45; 95% CI 1.14 to 62.04), being non-academic staff (AOR 2.74; 95% CI 1.56 to 4.81), having additional income (AOR 2.48; 95% CI 1.08 to 5.70), physical inactivity (AOR 2.36; 95% CI 1.44 to 3.88) and poor practice of dietary salt consumption (AOR 1.65; 95% CI 1.01 to 2.87) were factors associated with hypertension., Conclusion: One in seven, more than two in seven and nearly two in six of the employees of Wallaga University were hypertensive, centrally obese and generally obese, respectively. There was a positive association between obesity and hypertension. Comprehensive awareness creation and devising workplace intervention strategies are highly recommended to reduce the hypertension burden and associated obesity., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Published
2023
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