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1. TB and HIV Epidemiology and Collaborative Service: Evidence from Ethiopia, 2011–2015

Author: Gelaw YA, Assefa Y, Soares Magalhaes RJ, Demissie M, Tadele W, Dhewantara PW, and Williams G
Subjects: tuberculosis (tb), hiv, collaborative-services, implementations, ethiopia, Immunologic diseases. Allergy, RC581-607
Abstract: Yalemzewod Assefa Gelaw,1,2 Yibeltal Assefa,2 Ricardo J Soares Magalhaes,3,4 Minilik Demissie,5 Wegayehu Tadele,5 Pandji Wibawa Dhewantara,3,6 Gail Williams2 1Institute of Public Health, College of Medicine and Health Science, University of Gondar, Gondar 196, Ethiopia; 2School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4006, Australia; 3UQ Spatial Epidemiology Laboratory, School of Veterinary Science, Faculty of Science, the University of Queensland, Gatton 4343, Queensland, Australia; 4Children’s Health and Environment Program, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane 4101, Queensland, Australia; 5HIV/AIDS and Tuberculosis Research Directorate, Ethiopian Public Health Institute (EPHI), Addis Ababa, Ethiopia; 6Pangandaran Unit for Health Research and Development, National Institute of Health Research and Development, Ministry of Health of Indonesia, Pangandaran 46396, West Java, IndonesiaCorrespondence: Yalemzewod Assefa GelawSchool of Public Health, Faculty of Medicine, The University of Queensland, 288 Herston Road, Herston, Brisbane, Queensland 4006, AustraliaTel +61-469738918Email yalassefa@gmail.comBackground: Integrating and scaling up tuberculosis (TB) and HIV services are essential strategies to achieve the combined goals ending both TB and HIV, especially in TB and HIV high burden countries. This study aimed to examine the prevalence of TB and HIV co-infection and the implementation of collaborative services in Ethiopia.Methods: We used a national sentinel surveillance TB/HIV co-infection collected between 2010 and 2015. The Ethiopian Public Health Institute collected and collated the data quarterly from 79 health facilities in nine regional states and two city administrations.Results: A total of 55,336 people living with HIV/AIDS were screened for active TB between 2011 and 2015. Of these, 7.3% were found co-infected with TB, and 13% TB-negative PLWHA were on isoniazid preventive therapy. Nine out of ten (89.2%) active TB patients were screened for HIV counselling and 17.8% were found to be HIV positive; 78.2% and 53.0% of HIV/TB co-infected patients were receiving cotrimoxazole preventive therapy and antiretroviral treatment, respectively.Conclusion: This study showed that the prevalence of TB and HIV co-infection failed to decrease over the study period, and that, while there was an increasing trend for integration of collaborative services, this was not uniform over time. Aligning and integrating TB and HIV responses are still needed to achieve the target of ending TB and HIV by 2030.Keywords: tuberculosis, TB, HIV, collaborative services, implementations, Ethiopia
Published: 2020

2. Factors associated with overweight and obesity among adults in northeast Ethiopia: a cross-sectional study

Author: Dagne S, Gelaw YA, Abebe Z, and Wassie MM
Subjects: Overweight, Obesity, Adult, Dessie, Ethiopia, Specialties of internal medicine, RC581-951
Abstract: Samuel Dagne,1 Yalemzewod Assefa Gelaw,2 Zegeye Abebe,1 Molla Mesele Wassie1 1Department of Human Nutrition, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; 2Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia Objective: Currently, the growing prevalence of overweight and obesity is an emerging public health problem in middle- and low-income countries such as Ethiopia. However, the prevalence of overweight and obesity among Ethiopian adults who live in the major cities is not well documented. Therefore, the study aimed to assess the prevalence and factors associated with overweight and obesity among adults in Dessie town, northeast Ethiopia.Subjects and methods: A community-based cross-sectional study was conducted from March 15 to April 10, 2015. A total of 751 adults aged 18–64 years were included. Multistage followed by systematic random sampling method was used to select the study participants. Both bivariable and multivariable ordinal logistic regression were done. The proportional odds ratio (POR) with a 95% CI was reported to show the strength of association. A P-value
Published: 2019

3. Risk factors for COVID-19 infection, disease severity and related deaths in Africa: a systematic review

Author: Gesesew, HA, Koye, DN, Fetene, DM, Woldegiorgis, M, Kinfu, Y, Geleto, AB, Melaku, YA, Mohammed, H, Alene, KA, Awoke, MA, Birhanu, MM, Gebremedhin, AT, Gelaw, YA, Shifti, DM, Muluneh, MD, Tegegne, TK, Abrha, S, Aregay, AF, Ayalew, MB, Gebre, AK, Gebremariam, KT, Gebremedhin, T, Gebremichael, L, Leshargie, CT, Kibret, GD, Meazaw, MW, Mekonnen, AB, Tekle, DY, Tesema, AG, Tesfay, FH, Tesfaye, W, Wubishet, BL, Dachew, BA, Adane, AA, Gesesew, HA, Koye, DN, Fetene, DM, Woldegiorgis, M, Kinfu, Y, Geleto, AB, Melaku, YA, Mohammed, H, Alene, KA, Awoke, MA, Birhanu, MM, Gebremedhin, AT, Gelaw, YA, Shifti, DM, Muluneh, MD, Tegegne, TK, Abrha, S, Aregay, AF, Ayalew, MB, Gebre, AK, Gebremariam, KT, Gebremedhin, T, Gebremichael, L, Leshargie, CT, Kibret, GD, Meazaw, MW, Mekonnen, AB, Tekle, DY, Tesema, AG, Tesfay, FH, Tesfaye, W, Wubishet, BL, Dachew, BA, and Adane, AA
Abstract: Objective The aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa. Design A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa. Data sources Data were systematically searched from MEDLINE, Scopus, MedRxiv and BioRxiv. Eligibility criteria Studies for review were included if they were published in English and reported at least one risk factor and/or one health outcome. We included all relevant literature published up until 11 August 2020. Data extraction and synthesis We performed a systematic narrative synthesis to describe the available studies for each outcome. Data were extracted using a standardised Joanna Briggs Institute data extraction form. Results Fifteen articles met the inclusion criteria of which four were exclusively on Africa and the remaining 11 papers had a global focus with some data from Africa. Higher rates of infection in Africa are associated with high population density, urbanisation, transport connectivity, high volume of tourism and international trade, and high level of economic and political openness. Limited or poor access to healthcare are also associated with higher COVID-19 infection rates. Older people and individuals with chronic conditions such as HIV, tuberculosis and anaemia experience severe forms COVID-19 leading to hospitalisation and death. Similarly, high burden of chronic obstructive pulmonary disease, high prevalence of tobacco consumption and low levels of expenditure on health and low levels of global health security score contribute to COVID-19 related deaths. Conclusions Demographic, institutional, ecological, health system and politico-economic factors influenced the spectrum of COVID-19 infection, severity and death. We recommend multidisciplinary and integrated approaches to mitigate the identified factors and strengthen effective prevention strategi
Published: 2021

4. COVID-19 in Ethiopia: A geospatial analysis of vulnerability to infection, case severity and death

Author: Alene, KA, Gelaw, YA ; https://orcid.org/0000-0002-5338-586X, Fetene, DM, Koye, DN, Melaku, YA, Gesesew, H, Birhanu, MM, Adane, AA, Muluneh, MD, Dachew, BA, Abrha, S, Aregay, A, Ayele, AA, Bezabhe, WM, Gebremariam, KT, Gebremedhin, T, Gebremedhin, AT, Gebremichael, L, Geleto, AB, Kassahun, HT, Kibret, GD, Leshargie, CT, Mekonnen, A, Mirkuzie, AH, Mohammed, H, Tegegn, HG, Tesema, AG ; https://orcid.org/0000-0003-0618-4499, Tesfay, FH, Wubishet, BL, Kinfu, Y, Alene, KA, Gelaw, YA ; https://orcid.org/0000-0002-5338-586X, Fetene, DM, Koye, DN, Melaku, YA, Gesesew, H, Birhanu, MM, Adane, AA, Muluneh, MD, Dachew, BA, Abrha, S, Aregay, A, Ayele, AA, Bezabhe, WM, Gebremariam, KT, Gebremedhin, T, Gebremedhin, AT, Gebremichael, L, Geleto, AB, Kassahun, HT, Kibret, GD, Leshargie, CT, Mekonnen, A, Mirkuzie, AH, Mohammed, H, Tegegn, HG, Tesema, AG ; https://orcid.org/0000-0003-0618-4499, Tesfay, FH, Wubishet, BL, and Kinfu, Y
Abstract: Background COVID-19 has caused a global public health crisis affecting most countries, including Ethiopia, in various ways. This study maps the vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia. Methods Thirty-eight potential indicators of vulnerability to COVID-19 infection, case severity and likelihood of death, identified based on a literature review and the availability of nationally representative data at a low geographic scale, were assembled from multiple sources for geospatial analysis. Geospatial analysis techniques were applied to produce maps showing the vulnerability to infection, case severity and likelihood of death in Ethiopia at a spatial resolution of 1 km×1 km. Results This study showed that vulnerability to COVID-19 infection is likely to be high across most parts of Ethiopia, particularly in the Somali, Afar, Amhara, Oromia and Tigray regions. The number of severe cases of COVID-19 infection requiring hospitalisation and intensive care unit admission is likely to be high across Amhara, most parts of Oromia and some parts of the Southern Nations, Nationalities and Peoples' Region. The risk of COVID-19-related death is high in the country's border regions, where public health preparedness for responding to COVID-19 is limited. Conclusion This study revealed geographical differences in vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia. The study offers maps that can guide the targeted interventions necessary to contain the spread of COVID-19 in Ethiopia.
Published: 2021

5. The COVID-19 pandemic and healthcare systems in Africa: A scoping review of preparedness, impact and response

Author: Tessema, GA, Kinfu, Y, Dachew, BA, Tesema, AG, Assefa, Y, Alene, KA, Aregay, AF, Ayalew, MB, Bezabhe, WM, Bali, AG, Dadi, AF, Duko, B, Erku, D, Gebrekidan, K, Gebremariam, Kidane, Gebremichael, LG, Gebreyohannes, EA, Gelaw, YA, Gesesew, HA, Kibret, GD, Leshargie, CT, Meazew, MW, Mekonnen, Alemayehu, Mirkuzie, AH, Mohammed, H, Tekle, DY, Tesfay, Fisaha, Tessema, GA, Kinfu, Y, Dachew, BA, Tesema, AG, Assefa, Y, Alene, KA, Aregay, AF, Ayalew, MB, Bezabhe, WM, Bali, AG, Dadi, AF, Duko, B, Erku, D, Gebrekidan, K, Gebremariam, Kidane, Gebremichael, LG, Gebreyohannes, EA, Gelaw, YA, Gesesew, HA, Kibret, GD, Leshargie, CT, Meazew, MW, Mekonnen, Alemayehu, Mirkuzie, AH, Mohammed, H, Tekle, DY, and Tesfay, Fisaha
Abstract: BackgroundThe COVID-19 pandemic has overwhelmed health systems in both developed and developing nations alike. Africa has one of the weakest health systems globally, but there is limited evidence on how the region is prepared for, impacted by and responded to the pandemic.MethodsWe conducted a scoping review of PubMed, Scopus, CINAHL to search peer-reviewed articles and Google, Google Scholar and preprint sites for grey literature. The scoping review captured studies on either preparedness or impacts or responses associated with COVID-19 or covering one or more of the three topics and guided by Arksey and O’Malley’s methodological framework. The extracted information was documented following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension checklist for scoping reviews. Finally, the resulting data were thematically analysed.ResultsTwenty-two eligible studies, of which 6 reported on health system preparedness, 19 described the impacts of COVID-19 on access to general and essential health services and 7 focused on responses taken by the healthcare systems were included. The main setbacks in health system preparation included lack of available health services needed for the pandemic, inadequate resources and equipment, and limited testing ability and surge capacity for COVID-19. Reduced flow of patients and missing scheduled appointments were among the most common impacts of the COVID-19 pandemic. Health system responses identified in this review included the availability of telephone consultations, re-purposing of available services and establishment of isolation centres, and provisions of COVID-19 guidelines in some settings.ConclusionsThe health systems in Africa were inadequately prepared for the pandemic
Published: 2021

6. Predictors of mortality among multidrug-resistant tuberculosis patients in central Ethiopia; a retrospective follow-up study

Author: Kassa, GM, Woldetsadik, AT, Gelaw, YA ; https://orcid.org/0000-0002-5338-586X, Alemayehu, TT, Tsegaye, AT, Tamirat, KS, Akalu, TY, Kassa, GM, Woldetsadik, AT, Gelaw, YA ; https://orcid.org/0000-0002-5338-586X, Alemayehu, TT, Tsegaye, AT, Tamirat, KS, and Akalu, TY
Abstract: The burden of multidrug-resistant tuberculosis (MDR-TB) related to mortality in resource-poor countries remains high. This study aimed to estimate the incidence and predictors of death among MDR-TB patients in central Ethiopia. A retrospective followup study was conducted at three hospitals in the Amhara region on 451 patients receiving treatment for MDR-TB from September 2010 to January 2017. Data were collected from patient registration books, charts, and computer databases. Data were fitted to a parametric frailty model and survival was expressed as an Adjusted Hazard Ratio (AHR) with a 95% CI. The median follow-up time of participants was 20 months (IQR: 12, 22), and 46 (10.20%) of patients died during this period. The incidence rate of mortality was 7.42 (95% CI: 5.56, 9.91)/100 person year. Older age (AHR=1.04, 95% CI: 1.01, 1.08), inability to self-care (AHR=13.71, 95% CI: 5.46, 34.40), co-morbidity (AHR=5.74, 95% CI: 2.19, 15.08), low BMI (AHR=4.13, 95% CI: 1.02, 16.64), acute lung complications (AHR =4.22, 95% CI: 1.66, 10.70), and lung consolidation at baseline (AHR=5.27, 95% CI: 1.06, 26.18) were independent predictors of mortality. Most of the identified predictor factors of death in this study were considered to be avoidable if the TB program had provided nutritional support for malnourished patients and ensured a close follow-up of the elderly, and patients with co-morbidities.
Published: 2020

7. Determinants of default to fully completion of immunization among children aged 12 to 23 months in south Ethiopia: unmatched case-control study

Author: Asfaw, AG, Koye, DN, Demssie, AF, Zeleke, EG, Gelaw, YA, Asfaw, AG, Koye, DN, Demssie, AF, Zeleke, EG, and Gelaw, YA
Abstract: INTRODUCTION: Immunization is a cost effective interventions of vaccine preventable disease. There is still, 2.5 million children die by vaccine preventable disease every year in developing countries. In Ethiopia, default to fully completion of child immunization is high and determinants of default to completions are not explored well in the study setting. The aim of the study was to identify determinants of default to fully completion of immunization among children between ages 12 to 23 months in Sodo Zurea District, Southern Ethiopia. METHODS: Community based unmatched case-control study was conducted. Census was done to identify cases and controls before the actual data collection. A total of 344 samples (172 cases and 172 controls) were selected by simple random sampling technique. Cases were children in the age group of 12 to 23 months old who missed at least one dose from the recommended schedule. Bivariable and multivariable binary logistic regression was used to identify the determinant factors. Odds ratio, 95%CI and p - value less than 0.05 was used to measure the presence and strength of the association. RESULTS: Mothers of infants who are unable to read and write (AOR=8.9; 95%CI: 2.4, 33.9) and attended primary school (AOR=4.1; 95% CI:1.4-15.8), mothers who had no postnatal care follow up (AOR=0.4; 95%CI: 0.3, 0.7), good maternal knowledge towards immunization (AOR= 0.5; 95% CI: 0.3, 0.8) and maternal favorable perception towards uses of health institution for maternal and child care (AOR= 0.2; 95% CI: 0.1, 0.6) were significant determinant factors to default to fully completion of immunization. CONCLUSION: Working on maternal education, postnatal care follow up, promoting maternal knowledge and perception about child immunization are recommended measures to mitigate defaults to complete immunization.
Published: 2016

8. Effect of residence on mother's health care seeking behavior for common childhood illness in Northwest Ethiopia: A community based comparative cross sectional study

Author: Gelaw, YA ; https://orcid.org/0000-0002-5338-586X, Biks, GA, Alene, KA, Gelaw, YA ; https://orcid.org/0000-0002-5338-586X, Biks, GA, and Alene, KA
Abstract: Background: Children are at higher risk of acquiring infections and developing severe disease. This study assessed the health care seeking behavior and associated factors of urban and rural mothers for common childhood illness in Northwest Ethiopia. Methods: A comparative community based cross-sectional study was conducted among urban and rural mothers living in the district. A multistage sampling technique was used to select the study participants. A pre-tested and structured questioner via interview was used to collect the data. Binary logistic regression analysis was used to identify associated factors. Odds ratio with 95% CI was computed to assess the strength of the associations. Result: A total of 827 (274 urban and 553 rural) mothers were interviewed. Among these, 79.3% (95% CI: (76.5%, 82.06%)) of the mothers were sought health care in the district. Health care seeking behavior was higher among urban mothers (84.6%) than rural mothers (76.7%). Marital status, completion health extension package, and sex of child were significantly associated with health care seeking behavior of urban mothers. Whereas age of child, age and occupation of mothers, educational level of fathers, wealth quintile, and type of reported illness were significantly associated with rural mothers. Perceived severity of illness was significantly associated with both urban and rural mothers for health care seeking behavior. Conclusion: The overall health seeking behaviors of mothers for common childhood illness was high. However, urban mothers seek health care more than rural. Socio Economic position and types of reported illness has an effect for health seeking behavior of rural mothers. Whereas child sex preference and graduation status for health extension package has an effect for health care seeking behavior of urban mothers. Work on strengthen accessibility of health care services in the rural mothers and increase awareness of mothers about the disadvantage of sex preferences will im
Published: 2014

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

Author: Murray, Christopher J L, Callender, Charlton S K H, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M E, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, Atique, Suleman, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Banach, Maciej, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gilles, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Biswas, Tuhin, Bizuneh, Hailemichael, Bleyer, Archie, Basara, Berrak Bora, Bosetti, Cristina, Boufous, Soufiane, Brady, Oliver J, Bragazzi, Nicola Luigi, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Brewer, Jerry D, Briant, Paul Svitil, Britton, Gabrielle, Burstein, Roy, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christopher, Devasahayam J, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Collado-Mateo, Daniel, Constantin, Maria-Magdalena, Conti, Sara, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cromwell, Elizabeth, Crowe, Christopher Stephen, Cukelj, Petra, Cunningham, Matthew, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De Leo, Diego, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Dessie, Getenet Ayalew, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Ding, Eric L, Dinsa, Girmaye Deye, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dolan, Kate A, Doyle, Kerrie E, Driscoll, Tim R, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, El-Khatib, Ziad, Elyazar, Iqbal Rf, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhim, Hamed, Farag, Tamer, Faramarzi, Mahbobeh, Fareed, Mohammad, Farinha, Carla Sofia E Sá, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Fay, Kairsten A, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Feizy, Fariba, Fenny, Ama P, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Feyissa, Garumma Tolu, Filip, Irina, Finegold, Samuel, Fischer, Florian, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Fornari, Carla, Fürst, Thomas, Fukumoto, Takeshi, Fuller, John E, Fullman, Nancy, Gakidou, Emmanuela, Gallus, Silvano, Gamkrelidze, Amiran, Ganji, Morsaleh, Gankpe, Fortune Gbetoho, Garcia, Gregory M, Garcia-Gordillo, Miguel Á, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelano, Tilayie Feto, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M, Genova-Maleras, Ricard, Gething, Peter, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goli, Srinivas, Gomez, Ricardo Santiago, Gómez-Dantés, Hector, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Grosso, Giuseppe, Gugnani, Harish Chander C, Guo, Jingwen, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hagos, Tekleberhan B, Hailegiyorgis, Tewodros Tesfa, Hailu, 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Subjects: Adult, Male, Population Density, GBD, population, fertility, Adolescent, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, Global Health, Global Burden of Disease, Young Adult, Child, Preschool, General & Internal Medicine, Female, Human medicine, Mortality, Child, Population Growth, Birth Rate, Aged, Human, Maternal Age
Abstract: Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-cotnponent method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49.4% (95% uncertainty interval [UI] 46.4-52.0). The TFR decreased from 4.7 livebirths (4.5-4.9) to 2.4 livebirths (2.2-2.5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83.8 million people per year since 1985. The global population increased by 197-2% (193.3-200.8) since 1950, from 2.6 billion (2.5-2.6) to 7.6 billion (7.4-7.9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2.0%; this rate then remained nearly constant until 1970 and then decreased to 1.1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2.5% in 1963 to O7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2.7%. The global average age increased from 26.6 years in 1950 to 32.1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59.9% to 65.3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1.0 livebirths (95% UI 0. 9-1.2) in Cyprus to a high of 7.1 livebirths (6.8-7.4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0.08 livebirths (0.07-0.09) in South Korea to 2.4 livebirths (2.2-2.6) in Niger, and the TFR over age 30 years (I F030; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0.3 livebirths (0.3-0-4) in Puerto Rico to a high of 3.1 livebirths (3.0-3.2) in Niger. TF030 was higher than TFU25 in 145 countries and territories in 2017.33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2.0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

10. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Author: Nancy, Fullman, Jamal, Yearwood, Solomon, M, Abay, Cristiana, Abbafati, Foad, Abd-Allah, Jemal, Abdela, Ahmed, Abdelalim, Zegeye, Abebe, Teshome, Abuka, Abebo, Victor, Aboyans, Haftom, Niguse, Abraha, Daisy, M, X, Abreu, Laith, Abu-Raddad, J, Akilew, Awoke, Adane, Rufus, Adesoji, Adedoyin, Olatunji, Adetokunboh, Tara, Ballav, Adhikari, Mohsen, Afarideh, Ashkan, Afshin, Gina, Agarwal, Dominic, Agius, Anurag, Agrawal, Sutapa, Agrawal, Aliasghar, Ahmad, Kiadaliri, Miloud, Taki, Eddine, Aichour, Mohammed, Akibu, Rufus, Olusola, Akinyemi, Tomi, Akinyemiju, F, Nadia, Akseer, Faris, Hasan, Lami, Al, Fares, Alahdab, Ziyad, Al-Aly, Khurshid, Alam, Tahiya, Alam, Deena, Alasfoor, Mohammed, I, Albittar, Kefyalew, Addis, Alene, Ayman, Al-Eyadhy, Syed, Danish, Ali, Mehran, Alijanzadeh, Syed, M, Aljunid, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Mahmoud, A, Alomari, Rajaa, Al-Raddadi, Ubai, Alsharif, Khalid, A, Altirkawi, Nelson, Alvis-Guzman, Azmeraw, T, Amare, Kebede, Amenu, Walid, Ammar, Yaw, Ampem, Amoako, Nahla, Anber, Catalina, Liliana, Andrei, Sofia, Androudi, Carl, Abelardo, Antonio, T, Valdelaine, E, Araújo, M, Olatunde, Aremu, Johan, Ärnlöv, Artaman, Al, Krishna, Kumar, Aryal, Hamid, Asayesh, Ephrem, Tsegay, Asfaw, Solomon, Weldegebreal, Asgedom, Rana, Jawad, Asghar, Mengistu, Mitiku, Ashebir, Netsanet, Abera, Asseffa, Tesfay, Mehari, Atey, Sachin, R, Atre, Madhu, Atteraya, S, Leticia, Avila-Burgos, Euripide, Frinel, Arthur, G, Avokpaho, Ashish, Awasthi, Beatriz, Paulina, Ayala, Quintanilla, Animut, Alebel, Ayalew, Henok, Tadesse, Ayele, Rakesh, Ayer, Tambe, Betrand, Ayuk, Peter, Azzopardi, Natasha, Azzopardi-Muscat, Tesleem, Kayode, Babalola, Hamid, Badali, Alaa, Badawi, Maciej, Banach, Amitava, Banerjee, Amrit, Banstola, Ryan, M, Barber, Miguel, Barboza, A, Suzanne, L, Barker-Collo, Till, Bärnighausen, Simon, Barquera, Lope, H, Barrero, Quique, Bassat, Sanjay, Basu, Bernhard, T, Baune, Shahrzad, Bazargan-Hejazi, Neeraj, Bedi, Ettore, Beghi, Masoud, Behzadifar, Meysam, Behzadifar, Bayu, Begashaw, Bekele, Abate, Bekele, Belachew, Saba, Abraham, Belay, Yihalem, Abebe, Belay, Michelle, L, Bell, Aminu, Bello, K, Derrick, A, Bennett, James, Bennett, R, Isabela, M, Bensenor, Derbew, Fikadu, Berhe, Eduardo, Bernabé, Robert, Steven, Bernstein, Mircea, Beuran, Ashish, Bhalla, Paurvi, Bhatt, Soumyadeep, Bhaumik, Zulfiqar, A, Bhutta, Belete, Biadgo, Ali, Bijani, Boris, Bikbov, Charles, Birungi, Stan, Biryukov, Hailemichael, Bizuneh, Ian, W, Bolliger, Kaylin, Bolt, Ibrahim, R, Bou-Orm, Kayvan, Bozorgmehr, Oliver, Jerome, Brady, Alexandra, Brazinova, Nicholas, J, Breitborde, K, Hermann, Brenner, Gabrielle, Britton, Traolach, S, Brugha, Zahid, Butt, A, Lucero, Cahuana-Hurtado, Ismael, Ricardo, Campos-Nonato, Julio, Cesar, Campuzano, Josip, Car, Mate, Car, Rosario, Cárdenas, Juan, Jesus, Carrero, Felix, Carvalho, Carlos, A, Castañeda-Orjuela, Jacqueline, Castillo, Rivas, Ferrán, Catalá-López, Kelly, Cercy, Julian, Chalek, Hsing-Yi, Chang, Jung-Chen, Chang, Aparajita, Chattopadhyay, Pankaj, Chaturvedi, Peggy, Pei-Chia, Chiang, Vesper, Hichilombwe, Chisumpa, Jee-Young, J, Choi, Hanne, Christensen, Devasahayam, Jesudas, Christopher, Sheng-Chia, Chung, Liliana, G, Ciobanu, Cirillo, Massimo, Danny, Colombara, Sara, Conti, Cyrus, Cooper, Leslie, Cornaby, Paolo, Angelo, Cortesi, Monica, Cortinovis, Alexandre, Costa, Pereira, Ewerton, Cousin, Michael, H, Criqui, Elizabeth, Cromwell, A, Christopher, Stephen, Crowe, John, Crump, A, Alemneh, Kabeta, Daba, Berihun, Assefa, Dachew, Abel, Fekadu, Dadi, Lalit, Dandona, Rakhi, Dandona, Paul, I, Dargan, Ahmad, Daryani, Maryam, Daryani, Jai, Das, Siddharth, Kumar, Das, José, Das, Neves, Nicole, Davis, Weaver, Kairat, Davletov, Barbora, De, Courten, Diego, Leo, De, Jan-Walter, De, Neve, Robert, Dellavalle, P, Gebre, Demoz, Kebede, Deribe, Don, C, Des, Jarlais, Subhojit, Dey, Samath, D, Dharmaratne, Meghnath, Dhimal, Shirin, Djalalinia, David, Teye, Doku, Kate, Dolan, Ray, E, Dorsey, Kadine, Priscila, Bender, Dos, Santos, Kerrie, E, Doyle, Tim, Driscoll, R, Manisha, Dubey, Eleonora, Dubljanin, Bruce, Bartholow, Duncan, Michelle, Echko, Dumessa, Edessa, David, Edvardsson, Joshua, R, Ehrlich, Erika, Eldrenkamp, Ziad, El-Khatib, Matthias, Endres, Aman, Yesuf, Endries, Babak, Eshrati, Sharareh, Eskandarieh, Alireza, Esteghamati, Mahdi, Fakhar, Tamer, Farag, Mahbobeh, Faramarzi, Emerito, Jose, Aquino, Faraon, André, Faro, Farshad, Farzadfar, Adesegun, Fatusi, Mir, Sohail, Fazeli, Valery, Feigin, L, Andrea, B, Feigl, Netsanet, Fentahun, Seyed-Mohammad, Fereshtehnejad, Eduarda, Fernandes, João, C, Fernandes, Daniel, Obadare, Fijabi, Irina, Filip, Florian, Fischer, Christina, Fitzmaurice, Abraham, D, Flaxman, Luisa, Sorio, Flor, Nataliya, Foigt, Kyle, J, Foreman, Joseph, Frostad, J, Thomas, Fürst, Neal, D, Futran, Emmanuela, Gakidou, Silvano, Gallus, Ketevan, Gambashidze, Amiran, Gamkrelidze, Morsaleh, Ganji, Abadi, Kahsu, Gebre, Tsegaye, Tewelde, Gebrehiwot, Amanuel, Tesfay, Gebremedhin, Yalemzewod, Assefa, Gelaw, Johanna, M, Geleijnse, Demeke, Geremew, Peter, W, Gething, Reza, Ghadimi, Khalil, Ghasemi, Falavarjani, Maryam, Ghasemi-Kasman, Paramjit, Singh, Gill, Ababi, Zergaw, Giref, Maurice, Giroud, Melkamu, Dedefo, Gishu, Giorgia, Giussani, William, W, Godwin, Srinivas, Goli, Hector, Gomez-Dantes, Philimon, N, Gona, Amador, Goodridge, Sameer, Vali, Gopalani, Yevgeniy, Goryakin, Alessandra, Carvalho, Goulart, Ayman, Grada, Max, Griswold, Giuseppe, Grosso, Harish, Chander, Gugnani, Yuming, Guo, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Gupta, Juanita, A, Haagsma, Vladimir, Hachinski, Nima, Hafezi-Nejad, Gessessew, Bugssa, Hailu, Randah, Ribhi, Hamadeh, Samer, Hamidi, Graeme, J, Hankey, Hilda, Harb, L, Heather, C, Harewood, Sivadasanpillai, Harikrishnan, Josep, Maria, Haro, Hamid, Yimam, Hassen, Rasmus, Havmoeller, Caitlin, Hawley, Simon, I, Hay, Jiawei, He, Stephen, J, Hearps, C, Mohamed, I, Hegazy, Behzad, Heibati, Mohsen, Heidari, Delia, Hendrie, Nathaniel, J, Henry, Victor, Hugo, Herrera, Ballesteros, Claudiu, Herteliu, Desalegn, Tsegaw, Hibstu, Molla, Kahssay, Hiluf, Hans, W, Hoek, Enayatollah, Homaie, Rad, Nobuyuki, Horita, Dean, H, Hosgood, Mostafa, Hosseini, Seyed, Reza, Hosseini, Mihaela, Hostiuc, Sorin, Hostiuc, Damian, G, Hoy, Mohamed, Hsairi, Aung, Soe, Htet, Guoqing, Hu, John, J, Huang, Kim, Moesgaard, Iburg, Fachmi, Idris, Ehimario, Uche, Igumbor, Chad, Ikeda, Bogdan, Vasile, Ileanu, Olayinka, Ilesanmi, S, Kaire, Innos, Seyed, Sina, Naghibi, Irvani, Caleb, M, Irvine, S, Farhad, Islami, Troy, A, Jacobs, Kathryn, Jacobsen, H, Nader, Jahanmehr, Rajesh, Jain, Sudhir, Kumar, Jain, Mihajlo, Jakovljevic, M, Moti, Tolera, Jalu, Amr, Jamal, A, Mehdi, Javanbakht, Achala, Upendra, Jayatilleke, Panniyammakal, Jeemon, Ravi, Prakash, Jha, Vivekanand, Jha, Jacek, Józwiak, Oommen, John, Sarah, Charlotte, Johnson, Jost, Jonas, B, Vasna, Joshua, Mikk, Jürisson, Zubair, Kabir, Rajendra, Kadel, Amaha, Kahsay, Rizwan, Kalani, Chittaranjan, Kar, Marina, Karanikolos, André, Karch, Corine, Kakizi, Karema, Seyed, Karimi, M, Amir, Kasaeian, Dessalegn, Haile, Kassa, Getachew, Mullu, Kassa, Tesfaye, Dessale, Kassa, Nicholas, Kassebaum, J, Srinivasa, Vittal, Katikireddi, Anil, Kaul, Norito, Kawakami, Konstantin, Kazanjan, Seifu, Kebede, Peter, Njenga, Keiyoro, Grant, Rodgers, Kemp, Andre, Pascal, Kengne, Maia, Kereselidze, Ezra, Belay, Ketema, Yousef, Saleh, Khader, Morteza, Abdullatif, Khafaie, Alireza, Khajavi, Ibrahim, A, Khalil, Ejaz, Ahmad, Khan, Gulfaraz, Khan, Nuruzzaman, Md, Khan, Muhammad, Ali, Khan, Mukti, Nath, Khanal, Young-Ho, Khang, Mona, M, Khater, Abdullah, Tawfih, Abdullah, Khoja, Ardeshir, Khosravi, Jagdish, Khubchandani, Getiye, Dejenu, Kibret, Daniel, Ngari, Kiirithio, Daniel, Kim, Yun, Jin, Kim, Ruth, Kimokoti, W, Yohannes, Kinfu, Sanjay, Kinra, Adnan, Kisa, Niranjan, Kissoon, Sonali, Kochhar, Yoshihiro, Kokubo, Jacek, A, Kopec, Soewarta, Kosen, Parvaiz, A, Koul, 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Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G. 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Ray, Dos Santos, Kadine Priscila Bender, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duncan, Bruce Bartholow, Echko, Michelle, Edessa, Dumessa, Edvardsson, David, Ehrlich, Joshua R., Eldrenkamp, Erika, El-Khatib, Ziad, Endres, Matthia, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Fakhar, Mahdi, Farag, Tamer, Faramarzi, Mahbobeh, Faraon, Emerito Jose Aquino, Faro, André, Farzadfar, Farshad, Fatusi, Adesegun, Fazeli, Mir Sohail, Feigin, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, João C., Fijabi, Daniel Obadare, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Flor, Luisa Sorio, Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fürst, Thoma, Futran, Neal D., Gakidou, Emmanuela, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Ganji, Morsaleh, Gebre, Abadi Kahsu, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M., Geremew, Demeke, Gething, Peter W., Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Gill, Paramjit Singh, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Goli, Sriniva, Gomez-Dantes, Hector, Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Grada, Ayman, Griswold, Max, Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Haagsma, Juanita A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hankey, Graeme J., Harb, Hilda L., Harewood, Heather C., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassen, Hamid Yimam, Havmoeller, Rasmu, Hawley, Caitlin, Hay, Simon I., He, Jiawei, Hearps, Stephen J.C., Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henry, Nathaniel J., Herrera Ballesteros, Victor Hugo, Herteliu, Claudiu, Hibstu, Desalegn Tsegaw, Hiluf, Molla Kahssay, Hoek, Hans W., Homaie Rad, Enayatollah, Horita, Nobuyuki, Hosgood, H. Dean, Hosseini, Mostafa, Hosseini, Seyed Reza, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J., Iburg, Kim Moesgaard, Idris, Fachmi, Igumbor, Ehimario Uche, Ikeda, Chad, Ileanu, Bogdan Vasile, Ilesanmi, Olayinka S., Innos, Kaire, Irvani, Seyed Sina Naghibi, Irvine, Caleb M.S., Islami, Farhad, Jacobs, Troy A., Jacobsen, Kathryn H., Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo M., Jalu, Moti Tolera, Jamal, Amr A., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Józwiak, Jacek, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Joshua, Vasna, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kar, Chittaranjan, Karanikolos, Marina, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn Haile, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodger, Kengne, Andre Pascal, Kereselidze, Maia, Ketema, Ezra Belay, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Muhammad Ali, Khanal, Mukti Nath, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khubchandani, Jagdish, Kibret, Getiye Dejenu, Kiirithio, Daniel Ngari, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kinra, Sanjay, Kisa, Adnan, Kissoon, Niranjan, Kochhar, Sonali, Kokubo, Yoshihiro, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krishan, Kewal, Krohn, Kristopher J., Kuate Defo, Barthelemy, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kuzin, Igor, Kyu, Hmwe H., Lad, Deepesh Pravinkumar, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lang, Justin J., Lansingh, Van C., Lansky, Sonia, Larsson, Ander, Latifi, Arman, Lazarus, Jeffrey Victor, Leasher, Janet L., Lee, Paul H., Legesse, Yirga, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yongmei, Liang, Juan, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S., Lind, Margaret, Linn, Shai, Listl, Stefan, Liu, Patrick Y., Liu, Shiwei, Lodha, Rakesh, Lopez, Alan D., Lorch, Scott A., Lorkowski, Stefan, Lotufo, Paulo A., Lucas, Timothy C.D., Lunevicius, Raimunda, Lurton, Grégoire, Lyons, Ronan A., Maalouf, Fadi, Macarayan, Erlyn Rachelle King, Mackay, Mark T., Maddison, Emilie R., Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Mohammed, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A., Manguerra, Helena, Manhertz, Treh, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Manyazewal, Tsegahun, Mapoma, Chabila C., Margono, Christopher, Martinez-Raga, Jose, Martins, Sheila Cristina Ourique, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mejia-Rodriguez, Fabiola, Meles, Kidanu Gebremariam, Melku, Mulugeta, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengiste, Degu Abate, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Miazgowski, Tomasz, Micha, Renata, Milam, Robert, Millear, Anoushka, Miller, Ted R., Mini, G.K., Minnig, Shawn, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke, Mitchell, Philip B., Mlashu, Fitsum Weldegebreal, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadibakhsh, Roghayeh, Mohammed, Ebrahim, Mohammed, Mohammed A., Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Moosazadeh, Mahmood, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Moreno Velasquez, Ilai, Mori, Rintaro, Morrison, Shane D., Moses, Mark, Mousavi, Seyyed Meysam, Mueller, Ulrich O., Murhekar, Manoj, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta A., Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nangia, Vinay, Nansseu, Jobert Richie Njingang, Narayan, K.M. Venkat, Nascimento, Bruno Ramo, Negoi, Ionut, Negoi, Ruxandra Irina, Newton, Charles R., Ngunjiri, Josephine Wanjiku, Nguyen, Grant, Nguyen, Long, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nolte, Ellen, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Nyandwi, Alypio, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., De Oliveira, Patricia Pereira Vasconcelo, Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortega-Altamirano, Doris V., Ortiz, Alberto, Ozdemir, Raziye, Pa, Mahesh, Pain, Amanda W., Palone, Marcos Roberto Tovani, Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Park, Eun-Kee, Parsian, Hadi, Patel, Teja, Pati, Sanghamitra, Patil, Snehal T., Patle, Ajay, Patton, George C., Paturi, Vishnupriya Rao, Paudel, Deepak, De Moares Pedroso, Marcel, Pedroza, Sandra P., Pereira, David M., Perico, Norberto, Peterson, Hannah, Petzold, Max, Peykari, Niloofar, Phillips, Michael Robert, Piel, Frédéric B., Pigott, David M., Pillay, Julian David, Piradov, Michael A., Polinder, Suzanne, Pond, Constance D., Postma, Maarten J., Pourmalek, Farshad, Prakash, Swayam, Prakash, V., Prasad, Narayan, Prasad, Noela Marie, Purcell, Caroline, Qorbani, Mostafa, Quintana, Hedley Knewjen, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Raju, Sree Bhushan, Ram, Usha, Rana, Saleem M., Rankin, Zane, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E., Razo-García, Christian Aspacia, Reddy, Priscilla, Reiner, Robert C., Reis, Cesar, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio L., Rios Blancas, Maria Jesu, Rivera, Juan A., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A., Rothenbacher, Dietrich, Roy, Ambuj, Roy, Nobhojit, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S., Sadat, Nafi, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salama, Joseph, Salamati, Payman, De Freitas Saldanha, Raphael, Salimzadeh, Hamideh, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sancheti, Parag K., Sanchez-Niño, Maria Dolore, Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Saxena, Sonia, Saylan, Mete I., Schaeffner, Elke, Schmidhuber, Josef, Schmidt, Maria Inê, Schneider, Ione J.C., Schumacher, Austin E., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Sekerija, Mario, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shafieesabet, Azadeh, Shaikh, Masood Ali, Shakh-Nazarova, Marina, Shams-Beyranvand, Mehran, Sharafi, Heidar, Sharif-Alhoseini, Mahdi, Shariful Islam, Sheikh Mohammed, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shfare, Mebrahtu Teweldemedhin, Shi, Peilin, Shields, Chloe, Shigematsu, Mika, Shinohara, Yukito, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shrime, Mark G., Shukla, Sharvari Rahul, Siabani, Soraya, Sigfusdottir, Inga Dora, Silberberg, Donald H., Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Lavanya, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Sinke, Abiy Hiruye, Sisay, Mekonnen, Skirbekk, Vegard, Sliwa, Karen, Smith, Alison, Soares Filho, Adauto Martin, Sobaih, Badr H.A., Somai, Melek, Soneji, Samir, Soofi, Moslem, Sorensen, Reed J.D., Soriano, Joan B., Soyiri, Ireneous N., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J., Stokes, Mark Andrew, Sturua, Lela, Sufiyan, Muawiyyah Babale, Suliankatchi, Rizwan Abdulkader, Sunguya, Bruno F., Sur, Patrick J., Sykes, Bryan L., Sylaja, P.N., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Tadesse, Andualem Henok, Taffere, Getachew Redae, Tandon, Nikhil, Tariku, Amare Tariku, Taveira, Nuno, Tehrani-Banihashemi, Arash, Temam Shifa, Girma, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Tesema, Azeb Gebresilassie, Tesfaye, Dawit Jember, Tessema, Belay, Thakur, J.S., Thomas, Nihal, Thompson, Matthew J., Tillmann, Taavi, To, Quyen G., Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna, Tortajada, Miguel, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Avnish, Tripathy, Srikanth Prasad, Troeger, Christopher, Truelsen, Thoma, Tsoi, Derrick, Tudor Car, Lorainne, Tuem, Kald Beshir, Tyrovolas, Stefano, Uchendu, Uche S., Ukwaja, Kingsley Nnanna, Ullah, Irfan, Updike, Rachel, Uthman, Olalekan A., Uzochukwu, Benjamin S. Chudi, Valdez, Pascual Rubén, Van Boven, Job F.M., Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wagnew, Fasil, Waheed, Yasir, Wallin, Mitchell T., Walson, Judd L., Wang, Yafeng, Wang, Yuan-Pang, Wassie, Molla Mesele, Weaver, Marcia R., Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Jordan, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T. Eoin, Westerman, Ronny, White, Richard G., Whiteford, Harvey A., Widecka, Justyna, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D.A., Wondimkun, Yohanes Ayele, Workicho, Abdulhalik, Wyper, Grant M.A., Xavier, Deni, Xu, Gelin, Yan, Lijing L., Yano, Yuichiro, Yaseri, Mehdi, Yimer, Nigus Bililign, Yin, Peng, Yip, Paul, Yirsaw, Biruck Desalegn, Yonemoto, Naohiro, Yonga, Gerald, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zaman, Sojib Bin, Zamani, Mohammad, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zhu, Jun, Zimsen, Stephanie R.M., Zipkin, Ben, Zodpey, Sanjay, Zuhlke, Liesl Joanna, Murray, Christopher J.L., Lozano, Rafael, Viðskiptadeild (HR), School of Business (RU), Háskólinn í Reykjavík, Reykjavik University, Abay, Sm, Abebo, Ta, Abraha, Hn, Abreu, Dmx, Abu-Raddad, Lj, Adane, Aa, Adedoyin, Ra, Adhikari, Tb, Aichour, Mte, Akinyemi, Ro, Akinyemiju, Tf, Al Lami, Fh, Albittar, Mi, Alene, Ka, Ali, Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, Ay, Faraon, Eja, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Fijabi, Do, Flaxman, Ad, Foreman, Kj, Frostad, Jj, Futran, Nd, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gelaw, Ya, Geleijnse, Jm, Gething, Pw, Giref, Az, Gishu, Md, Godwin, Ww, Gona, Pn, Gopalani, Sv, Goulart, Ac, Gugnani, Hc, Haagsma, Ja, Hailu, Gb, Hamadeh, Rr, Hankey, Gj, Harb, Hl, Harewood, Hc, Haro, Jm, Hassen, Hy, Hay, Si, Hearps, Sjc, Hegazy, Mi, Henry, Nj, Herrera Ballesteros, Vh, Hibstu, Dt, Hiluf, Mk, Hoek, Hw, Hosgood, Hd, Hosseini, Sr, Hoy, Dg, Huang, Jj, Iburg, Km, Igumbor, Eu, Ileanu, Bv, Irvani, Ssn, Irvine, Cm, Jacobs, Ta, Jacobsen, Kh, Jain, Sk, Jakovljevic, Mb, Jalu, Mt, Jamal, Aa, Jayatilleke, Au, Jha, Rp, Johnson, Sc, Jonas, Jb, Karema, Ck, Karimi, Sm, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Ketema, Eb, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Mn, Khan, Ma, Khanal, Mn, Khang, Yh, Khater, Mm, Khoja, Ata, Kibret, Gd, Kiirithio, Dn, Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.
Subjects: Peformance, Coverage, Dánartíðni, Lífslíkur, Life expectancy, GBD, Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best), universal health coverage, Article, access quality health care, health care access and quality index, Nations, Healthcare Acce, Cause-specific mortality, Psychology, Healthcare Access and Quality Index, Mælitæki, States, Medicine (all), Health care, Þjóðir, Public Health, Global Health, Social Medicine and Epidemiology, Quality, Heilbrigðisþjónusta, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Sálfræði, Indicator, Amenable mortality, Transition, we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations, Trends, Inequalities
Abstract: Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.
Published: 2018

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

Author: Dicker, Daniel, Nguyen, Grant, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abdurahman, Ahmed Abdulahi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Agrawal, Anurag, Ahmadi, Mehdi, Ahmadi, Alireza, Ahmadieh, Hamid, Ahmed, Mohamed Lemine Cheikh brahim, Ahmed, Sayem, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Anlay, Degefaye Zelalem, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna K, Asadi-Lari, Mohsen, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Ataro, Zerihun, Atey, Tesfay Mehari Mehari, Athari, Seyyed Shamsadin, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Attia, Engi F, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Awuah, Baffour, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barquera, Simon, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, 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Kewal, Krishnaswami, Sanjay, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kudom, Andreas A, Kuipers, Ernst J, Kulikoff, Xie Rachel, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kumsa, Fekede Asefa, Kutz, Michael J, Lad, Sheetal D, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lami, Faris Hasan, Lan, Qing, Langan, Sinéad M, Lansingh, Van C, Lansky, Sonia, Larson, Heidi Jane, Laryea, Dennis Odai, Lassi, Zohra S, Latifi, Arman, Lavados, Pablo M, Laxmaiah, Avula, Lazarus, Jeffrey V, Lebedev, Georgy, Lee, Paul H, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Levi, Miriam, Li, Shanshan, Li, Yichong, Li, Xiaohong, Liang, Juan, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lonsdale, Chri, Lorch, Scott A, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Tim C D, Lunevicius, Raimunda, Lyons, Ronan A, Ma, Stefan, Mabika, Crispin, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Maddison, Ralph, Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Muhammed, Maghavani, Dhaval P, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malik, Manzoor Ahmad, Malta, Deborah Carvalho, Mamun, Abdullah A, Manamo, Wondimu Ayele, Manda, Ana-Laura, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C, Marcenes, Wagner, Marina, Shakhnazarova, Martinez-Raga, Jose, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, März, Winfried, Marzan, Melvin B, Mashamba-Thompson, Tivani Phosa, Masiye, Felix, Massenburg, Benjamin Ballard, Maulik, Pallab K, Mazidi, Mohsen, McGrath, John J, McKee, Martin, Mehata, Suresh, Mehendale, Sanjay Madhav, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Mekonen, Tesfa, Mekonnen, Tefera Chane, Meles, Hagazi Gebre, Meles, Kidanu Gebremariam, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Mensah, George A, Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Mezgebe, Haftay Berhane, Miangotar, Yode, Miazgowski, Bartosz, Miazgowski, Tomasz, Miller, Ted R, Mini, G.K., Mirica, Andreea, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Moazen, Babak, Moges, Nurilign Abebe, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadi-Khanaposhtani, Maryam, Mohammadnia-Afrouzi, Mousa, Mohammed, Shafiu, Mohammed, Mohammed A, Mohan, Viswanathan, Mokdad, Ali H, Molokhia, Mariam, Monasta, Lorenzo, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Moreno Velásquez, Ilai, Morgado-da-Costa, Joana, Morrison, Shane Dougla, Mosapour, Abba, Moschos, Marilita M, Mousavi, Seyyed Meysam, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Mukhopadhyay, Satinath, Mullany, Erin C, Muller, Kate, Murhekar, Manoj, Murphy, Tasha B, Murthy, G.V.S., Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nachega, Jean B, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Nair, Sanjeev, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramo, Nawaz, Haseeb, Ncama, Busisiwe P, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Suba, Newton, Charles Richard Jame, Ngalesoni, Frida N, Ngunjiri, Josephine W, Nguyen, Ha Thu, Nguyen, Huong Thanh, Nguyen, Long Hoang, Nguyen, Michele, Nguyen, Trang Huyen, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nisar, Muhammad Imran, Nixon, Molly R, Nolutshungu, Nomonde, Nomura, Shuhei, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacque, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Ofori-Asenso, Richard, Ogah, Okechukwu Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Sok King, Opio, John Nelson, Oren, Eyal, Ortiz, Justin R, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, Oyekale, Abayomi Samuel, P A, Mahesh, Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandey, Achyut Raj, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Patle, Ajay, Patten, Scott B, Patton, George C, Paudel, Deepak, Pearce, Neil, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perez, Krystle M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Plass, Dietrich, Polinder, Suzanne, Pond, Constance Dimity, Popova, Svetlana, Postma, Maarten J, Pourmalek, Farshad, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, V., Prakash, Swayam, Prasad, Narayan, Qorbani, Mostafa, Quistberg, D Alex, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Raju, Sree Bhushan, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Ranta, Anna, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E, Razo-García, Christian, Rego, Maria Albertina Santiago, Rehm, Jürgen, Reiner, Robert C, Reinig, Nickola, Reis, Cesar, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Ribeiro, Antonio Luiz P, Riojas, Horacio, Rios-Blancas, Maria Jesu, Roba, Kedir Teji, Robinson, Stephen R, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Roshchin, Denis O, Rostami, Ali, Rothenbacher, Dietrich, Rubagotti, Enrico, Ruhago, George Mugambage, Saadat, Soheil, Sabde, Yogesh Damodar, Sachdev, Perminder S, Saddik, Basema, Sadeghi, Ehsan, Moghaddam, Sahar Saeedi, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salahshoor, Mohamadreza, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saldanha, Raphael de Freita, Salimi, Yahya, Salimzadeh, Hamideh, Salz, Inbal, Sambala, Evanson Zondani, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolore, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Savic, Miloje, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Sayyah, Mehdi, Scaria, Vinod, Schaeffner, Elke, Schelonka, Kathryn, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schutte, Aletta Elisabeth, Schwebel, David C, Schwendicke, Falk, Scott, James G, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabaninejad, Hosein, Shackelford, Katya Anne, Shafieesabet, Azadeh, Shaheen, Amira A, Shaikh, Masood Ali, Shakir, Raad A, Shams-Beyranvand, Mehran, Shamsi, MohammadBagher, Shamsizadeh, Morteza, Sharafi, Heidar, Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Meenakshi, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Sheth, Kevin N, Shi, Peilin, Shibuya, Kenji, Shifa, Girma Temam, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shrime, Mark G, Shukla, Sharvari Rahul, Si, Si, Siabani, Soraya, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silpakit, Nari, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Virendra, Sinha, Anju Pradhan, Sinha, Dhirendra Narain, Sitas, Freddy, Skirbekk, Vegard, Sliwa, Karen, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Soriano, Joan B, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Srivastava, Rakesh Kumar, Starodubov, Vladimir I, Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J, Steiner, Caitlyn, Stewart, Leo G, Stokes, Mark A, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sutradhar, Ipsita, Sykes, Bryan L, Sylaja, P.N., Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Takahashi, Ken, Tandon, Nikhil, Tassew, Aberash Abay, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Tawye, Nega Yimer, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekle, Merhawi Gebremedhin, Temesgen, Habtamu, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Teshale, Manaye Yihune, Tessema, Belay, Teweldemedhin, Mebrahtu, Thakur, Jarnail Singh, Thankappan, Kavumpurathu Raman, Thirunavukkarasu, Sathish, Thomas, Laura Anne, Thomas, Nihal, Thrift, Amanda G, Tilahun, Binyam, To, Quyen G, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna E, Tortajada-Girbés, Miguel, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Suryakant, Tripathy, Srikanth Prasad, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tsilimparis, Nikolao, Tudor Car, Lorainne, Tuzcu, E Murat, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Usman, Muhammad Shariq, Uthman, Olalekan A, Uzun, Selen Begüm, Vaduganathan, Muthiah, Vaezi, Afsane, Vaidya, Gaurang, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagner, Gregory R, Wagnew, Fasil Wagnew Shiferaw, Waheed, Yasir, Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weiss, Jordan, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wondemagegn, Sintayehu Ambachew, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yadav, Rajaram, Yakob, Bereket, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yearwood, Jamal A, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, York, Hunter W, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zachariah, Geevar, Zadnik, Vesna, Zafar, Shamsa, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeeb, Hajo, Zeleke, Mulugeta Molla, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Kai, Zhang, Xueying, Zhou, Maigeng, Zhu, Jun, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna J, Lopez, Alan D, Gakidou, Emmanuela, and Murray, Christopher J L
Subjects: Child mortality, Alnæmi, Dánartíðni, Heilsufar, GBD, Börn, Dauði, Almennar lyflækningar, Fullorðnir, General & Internal Medicine, parasitic diseases, Psychology, age-specific mortality, Estimating adult mortality, Medicine (all), HIV, 11 Medical And Health Sciences, General Medicine, All-cause mortality, humanities, Countries, Death, mortality, national, Sálfræði, Health, GBD, mortality, Human medicine, Trends
Abstract: The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data., Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing., Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163).
Published: 2018
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12. Developmental trajectories of socio-emotional outcomes of children and young people in out-of-home care - Insights from data of Pathways of Care Longitudinal Study (POCLS).

Author: Hu N, Gelaw YA, Katz I, Fernandez E, Falster K, Hanly M, Newton BJ, Stephensen J, Hotton P, Zwi K, and Lingam R
Subjects: Child, Humans, Male, Adolescent, Female, Longitudinal Studies, Prospective Studies, Foster Home Care, Emotions, Home Care Services
Abstract: Background: There has been a limited understanding of the longitudinal trajectory and determinants of socio-emotional outcomes among children in out-of-home care (OOHC)., Objectives: This study aimed to examine child socio-demographics, pre-care maltreatment, placement, and caregiver factors associated with trajectories of socio-emotional difficulties of children in OOHC., Participants and Setting: The study sample (n = 345) included data from the Pathways of Care Longitudinal Study (POCLS), a prospective longitudinal cohort of children aged 3-17 years who entered the OOHC system in New South Wales (NSW) Australia, between 2010 and 2011., Methods: Group-based trajectory models were used to identify distinct socio-emotional trajectory groups based on the Child Behaviour Check List (CBCL) Total Problem T-scores completed at all four Waves 1-4. Modified Poisson regression analysis was conducted to assess the association (risk ratios) of socio-emotional trajectory group membership with pre-care maltreatment, placement, and caregiver-related factors., Results: Three trajectories of socio-emotional development were identified: 'persistently low difficulties' (average CBCL T-score changed from 40 to 38 over time), normal (average CBCL T-score changed from 52 to 55 over time), and clinical (average CBCL T-score remained at 68 over time) trajectories. Each trajectory presented a stable trend over time. Relative/kinship care, as compared with foster care, was associated with the "persistently low" socio-emotional trajectory. Being male, exposure to ≥8 pre-care substantiated risk of significant harm (ROSH) reports, placement changes, and caregiver's psychological distress (more than two-fold increased risk) were associated with the clinical socio-emotional trajectory., Conclusions: Early intervention to ensure children have a nurturing care environment and psychological support to caregivers are vital for positive socio-emotional development over time among children in long-term OOHC., (Copyright © 2023. Published by Elsevier Ltd.)
Published: 2024
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13. Socio-demographic correlates of unhealthy lifestyle in Ethiopia: a secondary analysis of a national survey.

Author: Gelaw YA, Koye DN, Alene KA, Ahmed KY, Assefa Y, Erku DA, Tegegn HG, Tesema AG, Zeleke BM, and Melaku YA
Subjects: Adult, Adolescent, Humans, Male, Young Adult, Middle Aged, Aged, Cross-Sectional Studies, Ethiopia epidemiology, Risk Factors, Vegetables, Demography, Prevalence, Life Style, Obesity epidemiology
Abstract: Background: Multiple lifestyle risk factors exhibit a stronger association with non-communicable diseases (NCDs) compared to a single factor, emphasizing the necessity of considering them collectively. By integrating these major lifestyle risk factors, we can identify individuals with an overall unhealthy lifestyle, which facilitates the provision of targeted interventions for those at significant risk of NCDs. The aim of this study was to evaluate the socio-demographic correlates of unhealthy lifestyles among adolescents and adults in Ethiopia., Methods: A national cross-sectional survey, based on the World Health Organization's NCD STEPS instruments, was conducted in Ethiopia. The survey, carried out in 2015, involved a total of 9,800 participants aged between 15 and 69 years. Lifestyle health scores, ranging from 0 (most healthy) to 5 (most unhealthy), were derived considering factors such as daily fruit and vegetable consumption, smoking status, prevalence of overweight/obesity, alcohol intake, and levels of physical activity. An unhealthy lifestyle was defined as the co-occurrence of three or more unhealthy behaviors. To determine the association of socio-demographic factors with unhealthy lifestyles, multivariable logistic regression models were utilized, adjusting for metabolic factors, specifically diabetes and high blood pressure., Results: Approximately one in eight participants (16.7%) exhibited three or more unhealthy lifestyle behaviors, which included low fruit/vegetable consumption (98.2%), tobacco use (5.4%), excessive alcohol intake (15%), inadequate physical activity (66%), and obesity (2.3%). Factors such as male sex, urban residency, older age, being married or in a common-law relationship, and a higher income were associated with these unhealthy lifestyles. On the other hand, a higher educational status was associated with lower odds of these behaviors., Conclusion: In our analysis, we observed a higher prevalence of concurrent unhealthy lifestyles. Socio-demographic characteristics, such as sex, age, marital status, residence, income, and education, were found to correlate with individuals' lifestyles. Consequently, tailored interventions are imperative to mitigate the burden of unhealthy lifestyles in Ethiopia., (© 2023. The Author(s).)
Published: 2023
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14. Evaluating COVID-19-Related Disruptions to Effective Malaria Case Management in 2020-2021 and Its Potential Effects on Malaria Burden in Sub-Saharan Africa.

Author: Dzianach PA, Rumisha SF, Lubinda J, Saddler A, van den Berg M, Gelaw YA, Harris JR, Browne AJ, Sanna F, Rozier JA, Galatas B, Anderson LF, Vargas-Ruiz CA, Cameron E, Gething PW, and Weiss DJ
Abstract: The COVID-19 pandemic has led to far-reaching disruptions to health systems, including preventative and curative services for malaria. The aim of this study was to estimate the magnitude of disruptions in malaria case management in sub-Saharan Africa and their impact on malaria burden during the COVID-19 pandemic. We used survey data collected by the World Health Organization, in which individual country stakeholders reported on the extent of disruptions to malaria diagnosis and treatment. The relative disruption values were then applied to estimates of antimalarial treatment rates and used as inputs to an established spatiotemporal Bayesian geostatistical framework to generate annual malaria burden estimates with case management disruptions. This enabled an estimation of the additional malaria burden attributable to pandemic-related impacts on treatment rates in 2020 and 2021. Our analysis found that disruptions in access to antimalarial treatment in sub-Saharan Africa likely resulted in approximately 5.9 (4.4-7.2 95% CI) million more malaria cases and 76 (20-132) thousand additional deaths in the 2020-2021 period within the study region, equivalent to approximately 1.2% (0.3-2.1 95% CI) greater clinical incidence of malaria and 8.1% (2.1-14.1 95% CI) greater malaria mortality than expected in the absence of the disruptions to malaria case management. The available evidence suggests that access to antimalarials was disrupted to a significant degree and should be considered an area of focus to avoid further escalations in malaria morbidity and mortality. The results from this analysis were used to estimate cases and deaths in the World Malaria Report 2022 during the pandemic years.
Published: 2023
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15. Mapping national, regional and local prevalence of hypertension and diabetes in Ethiopia using geospatial analysis.

Author: Koye DN, Melaku YA, Gelaw YA, Zeleke BM, Adane AA, Tegegn HG, Gebreyohannes EA, Erku DA, Tesfay FH, Gesesew HA, Mekonnen A, Dadi AF, and Alene KA
Subjects: Humans, Adolescent, Young Adult, Adult, Middle Aged, Aged, Ethiopia epidemiology, Prevalence, Bayes Theorem, Cross-Sectional Studies, Risk Factors, Hypertension epidemiology, Hypertension complications, Diabetes Mellitus epidemiology
Abstract: Objectives: This study aimed to map the national, regional and local prevalence of hypertension and diabetes in Ethiopia., Design and Setting: Nationwide cross-sectional survey in Ethiopia combined with georeferenced ecological level data from publicly available sources., Participants: 9801 participants aged between 15 and 69 years., Primary Outcome Measures: Prevalence of hypertension and diabetes were collected using the WHO's STEPS survey approach. Bayesian model-based geostatistical techniques were used to estimate hypertension and diabetes prevalence at national, regional and pixel levels (1×1 km 2 ) with corresponding 95% credible intervals (95% CrIs)., Results: The national prevalence was 19.2% (95% CI: 18.4 to 20.0) for hypertension and 2.8% (95% CI: 2.4 to 3.1) for diabetes. Substantial variation was observed in the prevalence of these diseases at subnational levels, with the highest prevalence of hypertension observed in Addis Ababa (30.6%) and diabetes in Somali region (8.7%). Spatial overlap of high hypertension and diabetes prevalence was observed in some regions such as the Southern Nations, Nationalities and People's region and Addis Ababa. Population density (number of people/km 2 ) was positively associated with the prevalence of hypertension (β: 0.015; 95% CrI: 0.003-0.027) and diabetes (β: 0.046; 95% CrI: 0.020-0.069); whereas altitude in kilometres was negatively associated with the prevalence of diabetes (β: -0.374; 95% CrI: -0.711 to -0.044)., Conclusions: Spatial clustering of hypertension and diabetes was observed at subnational and local levels in Ethiopia, which was significantly associated with population density and altitude. The variation at the subnational level illustrates the need to include environmental drivers in future NCDs burden estimation. Thus, targeted and integrated interventions in high-risk areas might reduce the burden of hypertension and diabetes in Ethiopia., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2022
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16. The COVID-19 pandemic and healthcare systems in Africa: a scoping review of preparedness, impact and response.

Author: Tessema GA, Kinfu Y, Dachew BA, Tesema AG, Assefa Y, Alene KA, Aregay AF, Ayalew MB, Bezabhe WM, Bali AG, Dadi AF, Duko B, Erku D, Gebrekidan K, Gebremariam KT, Gebremichael LG, Gebreyohannes EA, Gelaw YA, Gesesew HA, Kibret GD, Leshargie CT, Meazew MW, Mekonnen A, Mirkuzie AH, Mohammed H, Tekle DY, and Tesfay FH
Subjects: Africa epidemiology, Health Services Accessibility, Humans, SARS-CoV-2, COVID-19, Pandemics
Abstract: Background: The COVID-19 pandemic has overwhelmed health systems in both developed and developing nations alike. Africa has one of the weakest health systems globally, but there is limited evidence on how the region is prepared for, impacted by and responded to the pandemic., Methods: We conducted a scoping review of PubMed, Scopus, CINAHL to search peer-reviewed articles and Google, Google Scholar and preprint sites for grey literature. The scoping review captured studies on either preparedness or impacts or responses associated with COVID-19 or covering one or more of the three topics and guided by Arksey and O'Malley's methodological framework. The extracted information was documented following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension checklist for scoping reviews. Finally, the resulting data were thematically analysed., Results: Twenty-two eligible studies, of which 6 reported on health system preparedness, 19 described the impacts of COVID-19 on access to general and essential health services and 7 focused on responses taken by the healthcare systems were included. The main setbacks in health system preparation included lack of available health services needed for the pandemic, inadequate resources and equipment, and limited testing ability and surge capacity for COVID-19. Reduced flow of patients and missing scheduled appointments were among the most common impacts of the COVID-19 pandemic. Health system responses identified in this review included the availability of telephone consultations, re-purposing of available services and establishment of isolation centres, and provisions of COVID-19 guidelines in some settings., Conclusions: The health systems in Africa were inadequately prepared for the pandemic, and its impact was substantial. Responses were slow and did not match the magnitude of the problem. Interventions that will improve and strengthen health system resilience and financing through local, national and global engagement should be prioritised., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2021
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17. Geographical heterogeneity and socio-ecological risk profiles of dengue in Jakarta, Indonesia.

Author: Prasetyowati H, Dhewantara PW, Hendri J, Astuti EP, Gelaw YA, Harapan H, Ipa M, Widyastuti W, Handayani DOTL, Salama N, and Picasso M
Subjects: Climate, Geography, Humans, Incidence, Indonesia epidemiology, Dengue epidemiology
Abstract: The aim of this study was to assess the role of climate variability on the incidence of dengue fever (DF), an endemic arboviral infection existing in Jakarta, Indonesia. The work carried out included analysis of the spatial distribution of confirmed DF cases from January 2007 to December 2018 characterising the sociodemographical and ecological factors in DF high-risk areas. Spearman's rank correlation was used to examine the relationship between DF incidence and climatic factors. Spatial clustering and hotspots of DF were examined using global Moran's I statistic and the local indicator for spatial association analysis. Classification and regression tree (CART) analysis was performed to compare and identify demographical and socio-ecological characteristics of the identified hotspots and low-risk clusters. The seasonality of DF incidence was correlated with precipitation (r=0.254, P<0.01), humidity (r=0.340, P<0.01), dipole mode index (r= -0.459, P<0.01) and Tmin (r= -0.181, P<0.05). DF incidence was spatially clustered at the village level (I=0.294, P<0.001) and 22 hotspots were identified with a concentration in the central and eastern parts of Jakarta. CART analysis showed that age and occupation were the most important factors explaining DF clustering. Areaspecific and population-targeted interventions are needed to improve the situation among those living in the identified DF high-risk areas in Jakarta.
Published: 2021
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18. Risk factors for COVID-19 infection, disease severity and related deaths in Africa: a systematic review.

Author: Gesesew HA, Koye DN, Fetene DM, Woldegiorgis M, Kinfu Y, Geleto AB, Melaku YA, Mohammed H, Alene KA, Awoke MA, Birhanu MM, Gebremedhin AT, Gelaw YA, Shifti DM, Muluneh MD, Tegegne TK, Abrha S, Aregay AF, Ayalew MB, Gebre AK, Gebremariam KT, Gebremedhin T, Gebremichael L, Leshargie CT, Kibret GD, Meazaw MW, Mekonnen AB, Tekle DY, Tesema AG, Tesfay FH, Tesfaye W, Wubishet BL, Dachew BA, and Adane AA
Subjects: Africa epidemiology, COVID-19 mortality, Humans, Risk Factors, Severity of Illness Index, COVID-19 epidemiology
Abstract: Objective: The aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa., Design: A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa., Data Sources: Data were systematically searched from MEDLINE, Scopus, MedRxiv and BioRxiv., Eligibility Criteria: Studies for review were included if they were published in English and reported at least one risk factor and/or one health outcome. We included all relevant literature published up until 11 August 2020., Data Extraction and Synthesis: We performed a systematic narrative synthesis to describe the available studies for each outcome. Data were extracted using a standardised Joanna Briggs Institute data extraction form., Results: Fifteen articles met the inclusion criteria of which four were exclusively on Africa and the remaining 11 papers had a global focus with some data from Africa. Higher rates of infection in Africa are associated with high population density, urbanisation, transport connectivity, high volume of tourism and international trade, and high level of economic and political openness. Limited or poor access to healthcare are also associated with higher COVID-19 infection rates. Older people and individuals with chronic conditions such as HIV, tuberculosis and anaemia experience severe forms COVID-19 leading to hospitalisation and death. Similarly, high burden of chronic obstructive pulmonary disease, high prevalence of tobacco consumption and low levels of expenditure on health and low levels of global health security score contribute to COVID-19 related deaths., Conclusions: Demographic, institutional, ecological, health system and politico-economic factors influenced the spectrum of COVID-19 infection, severity and death. We recommend multidisciplinary and integrated approaches to mitigate the identified factors and strengthen effective prevention strategies., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2021
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19. COVID-19 in Ethiopia: a geospatial analysis of vulnerability to infection, case severity and death.

Author: Alene KA, Gelaw YA, Fetene DM, Koye DN, Melaku YA, Gesesew H, Birhanu MM, Adane AA, Muluneh MD, Dachew BA, Abrha S, Aregay A, Ayele AA, Bezabhe WM, Gebremariam KT, Gebremedhin T, Gebremedhin AT, Gebremichael L, Geleto AB, Kassahun HT, Kibret GD, Leshargie CT, Mekonnen A, Mirkuzie AH, Mohammed H, Tegegn HG, Tesema AG, Tesfay FH, Wubishet BL, and Kinfu Y
Subjects: COVID-19 mortality, Ethiopia epidemiology, Female, Humans, Male, Pandemics, Risk Factors, COVID-19 epidemiology, Geography, Medical
Abstract: Background: COVID-19 has caused a global public health crisis affecting most countries, including Ethiopia, in various ways. This study maps the vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia., Methods: Thirty-eight potential indicators of vulnerability to COVID-19 infection, case severity and likelihood of death, identified based on a literature review and the availability of nationally representative data at a low geographic scale, were assembled from multiple sources for geospatial analysis. Geospatial analysis techniques were applied to produce maps showing the vulnerability to infection, case severity and likelihood of death in Ethiopia at a spatial resolution of 1 km×1 km., Results: This study showed that vulnerability to COVID-19 infection is likely to be high across most parts of Ethiopia, particularly in the Somali, Afar, Amhara, Oromia and Tigray regions. The number of severe cases of COVID-19 infection requiring hospitalisation and intensive care unit admission is likely to be high across Amhara, most parts of Oromia and some parts of the Southern Nations, Nationalities and Peoples' Region. The risk of COVID-19-related death is high in the country's border regions, where public health preparedness for responding to COVID-19 is limited., Conclusion: This study revealed geographical differences in vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia. The study offers maps that can guide the targeted interventions necessary to contain the spread of COVID-19 in Ethiopia., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2021
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20. Predictors of mortality among multidrug-resistant tuberculosis patients in central Ethiopia: a retrospective follow-up study.

Author: Kassa GM, Tadesse A, Gelaw YA, Alemayehu TT, Tsegaye AT, Tamirat KS, and Akalu TY
Subjects: Adult, Ethiopia epidemiology, Female, Follow-Up Studies, Humans, Male, Middle Aged, Retrospective Studies, Risk Factors, Young Adult, Antitubercular Agents therapeutic use, Tuberculosis, Multidrug-Resistant epidemiology, Tuberculosis, Multidrug-Resistant mortality
Abstract: The burden of multidrug-resistant tuberculosis (MDR-TB) related to mortality in resource-poor countries remains high. This study aimed to estimate the incidence and predictors of death among MDR-TB patients in central Ethiopia. A retrospective follow-up study was conducted at three hospitals in the Amhara region on 451 patients receiving treatment for MDR-TB from September 2010 to January 2017. Data were collected from patient registration books, charts and computer databases. Data were fitted to a parametric frailty model and survival was expressed as an adjusted hazard ratio (AHR) with a 95% confidence interval (CI). The median follow-up time of participants was 20 months (interquartile range: 12, 22) and 46 (10.20%) of patients died during this period. The incidence rate of mortality was 7.42 (95% CI 5.56-9.91)/100 person-years. Older age (AHR = 1.04, 95% CI 1.01-1.08), inability to self-care (AHR = 13.71, 95% CI 5.46-34.40), co-morbidity (AHR = 5.74, 95% CI 2.19-15.08), low body mass index (AHR = 4.13, 95% CI 1.02-16.64), acute lung complications (AHR = 4.22, 95% CI 1.66-10.70) and lung consolidation at baseline (AHR = 5.27, 95% CI 1.06-26.18) were independent predictors of mortality. Most of the identified predictor factors of death in this study were considered to be avoidable if the TB programme had provided nutritional support for malnourished patients and ensured a close follow-up of the elderly, and patients with co-morbidities.
Published: 2020
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21. Sociodemographic profiling of tuberculosis hotspots in Ethiopia, 2014-2017.

Author: Gelaw YA, Williams G, Assefa Y, Asressie M, and Soares Magalhães RJ
Subjects: Adolescent, Child, Child, Preschool, Demography, Ethiopia epidemiology, Female, Geographic Information Systems, Humans, Male, Cluster Analysis, Tuberculosis epidemiology
Abstract: Background: Tuberculosis (TB) notification rates vary across regions in Ethiopia and districts within the Amhara Region. The Amhara Region is one of the main TB hotspot regions in the country. In this study we identified the spatial distribution of TB and characterized the sociodemographic factors of spatial clusters in the Amhara Region., Methods: An ecological spatial analysis of TB notifications from 2014 to 2017 was conducted to quantify the presence and location of spatial clusters of TB notifications at the district level within the Amhara Region. Global Moran's I statistics and local indicators of spatial association were used to explore the spatial clustering of TB notifications. Notifications from hotspots and low-risk districts were compared to identify significant sociodemographic factors using analysis of variance and Classification and Regression Tree analysis. The geographic information system and 'sp' packages of R software were used for spatial analysis., Results: From 2014 to 2017 the average notification rate of all forms of TB in the Amhara Region was 107/100 000 population (range 18-614 per 100 000 population). District-level TB notification rates were positively spatially autocorrelated, with Moran's I value ranging from 0.207 to 0.276 (p=0.01). Hotspot TB clusters were found in the northwest and central part of the region. The proportion of migrants (F(3,124)=23.21, p<0.001, d=1.4) was found to be the most important factor associated with hotspot TB clustering., Conclusions: TB notification rates in the Amhara Region of Ethiopia over the past 4 y were significantly clustered. Distinguishing high-risk areas from low-risk areas and characterizing the proportion of migrants and other risk factors is important for targeted TB prevention and control in the region., (© The Author(s) 2019. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Published: 2019
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22. Screening tools to exclude active pulmonary TB in high TB burden countries: systematic review and meta-analysis.

Author: Assefa Y, Woldeyohannes S, Gelaw YA, Hamada Y, and Getahun H
Subjects: Developing Countries, Family Characteristics, Humans, Prevalence, Sensitivity and Specificity, Tuberculosis, Pulmonary diagnosis, Tuberculosis, Pulmonary prevention & control, Mass Screening, Tuberculosis, Pulmonary epidemiology
Abstract: OBJECTIVE To examine the use of symptoms, chest X-ray (CXR) abnormalities, and combinations of symptoms and CXR in excluding active pulmonary tuberculosis (TB) before treating for latent tuberculous infection (LTBI) in high TB burden countries. METHODS We updated a systematic review and meta-analysis of studies on the sensitivities, specificities, predictive values, diagnostic odds ratios and areas under the curve for index tests. The analysis was conducted using the hierarchical summary receiver operating characteristic method in R software. RESULTS We included 24 publications in the systematic review and meta-analysis. 'Any CXR abnormality' had the highest sensitivity (94.1%, 95%CI 85.8-97.7) among all index tests. 'CXR abnormality suggestive of TB' had a higher specificity (92.2%, 95%CI 89.7-94.1) than 'any CXR abnormality' (86.8%, 95%CI 79.7-91.7). The sensitivity for 'any TB symptom' was 73.0% (95%CI 64.1-80.4), while 'prolonged cough' of ≥2 weeks had a specificity of 94.3% (95%CI 92.2-95.9). There was no significant difference in the sensitivity and specificity of all screening tools stratified by human immunodeficiency virus (HIV) settings, with the exception of 'CXR abnormality suggestive of TB', which had a significantly higher sensitivity in low than in high HIV prevalence settings (effect estimate 2.26, 95%CI 0.69-3.82; P = 0.002). CONCLUSION In countries with a high TB burden, the absence of any TB symptom and any CXR abnormality can be used to exclude active pulmonary TB before initiating treatment for LTBI in household contacts aged ≥5 years of patients with bacteriologically confirmed pulmonary TB. .
Published: 2019
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23. HIV Prevalence Among Tuberculosis Patients in Sub-Saharan Africa: A Systematic Review and Meta-analysis.

Author: Gelaw YA, Williams G, Soares Magalhães RJ, Gilks CF, and Assefa Y
Subjects: Africa South of the Sahara epidemiology, Humans, Prevalence, Regression Analysis, Coinfection epidemiology, HIV Infections epidemiology, Tuberculosis epidemiology
Abstract: HIV associated tuberculosis (TB) morbidity and mortality is a major concern in sub-Saharan Africa. Understanding the level of HIV infection among TB patients is vital for adequate response. We conducted a systematic review and meta-analysis to estimate the prevalence of HIV in TB patients in sub-Saharan Africa. We searched PubMed, EMBASE, Web of Science and CINAHL databases. A meta-analysis with a random-effects model was performed. Potential sources of heterogeneity in the prevalence estimates were explored using meta-regression analysis. We identified 68 studies that collectively included 62,969 TB patients between 1990 and 2017. The overall estimate of HIV prevalence in TB patients was 31.8% (95% CI 27.8-36.1). There was substantial heterogeneity in the prevalence estimates in Southern, Central, Eastern, and Western sub-Saharan Africa regions (43.7, 41.3, 31.1 and 25.5%, respectively). We noted an apparent reduction in the estimate from 33.7% (95% CI 27.6-40.4) in the period before 2000 to 25.7% (95% CI 17.6-336.6) in the period after 2010. The Eastern and Southern sub-Saharan Africa region had higher prevalence [34.4% (95% CI 29.3-34.4)] than the Western and Central region [27.3% (95% CI 21.6-33.8)]. The prevalence of HIV in TB patients has declined over time in sub-Saharan Africa. We argue that this is due to strengthened HIV prevention and control response and enhanced TB/HIV collaborative activities. Countries and regions with high burdens of HIV and TB should strengthen and sustain efforts in order to achieve the goal of ending both HIV and TB epidemics in line with the Sustainable Development Goals.
Published: 2019
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24. Spatial clustering and socio-demographic determinants of HIV infection in Ethiopia, 2015-2017.

Author: Gelaw YA, Magalhães RJS, Assefa Y, and Williams G
Subjects: Adolescent, Adult, Bayes Theorem, Child, Child, Preschool, Cluster Analysis, Condoms, Demography, Ethiopia epidemiology, Female, HIV Infections virology, Humans, Infant, Male, Middle Aged, Risk Factors, Spatial Analysis, Transients and Migrants, Young Adult, HIV Infections epidemiology
Abstract: Background: Amhara Region has the largest at-risk population in Ethiopia, with widespread traditional practices that are likely to increase transmission of HIV. However, the identification and characterization of HIV hotspots within this region have not been undertaken. This study aimed to explore and describe the geographical pattern of HIV infection using notification data in Amhara Region, Ethiopia., Methods: Data on HIV infection at the district level were obtained from the Amhara Regional Health Bureau. A Bayesian conditional autoregressive (CAR) model was used to explore the association between HIV infection and socio-demographic variables in OpenBUGS., Results: A total of 35 210 new HIV cases were reported during 2015-2017 in Amhara Region, Ethiopia. Metema and Mirab Armacho districts were found to be hotspots throughout the study period. There was a decrease in HIV infection in 2016 (odds ratio 0.77, 95% credible interval (CrI) 0.72-0.82) and 2017 (odds ratio 0.71, 95% CrI 0.60-0.76) as compared with HIV infection in 2015. HIV infection increased by 1.004 (95% CrI 1.001-1.008) and 1.47 (95% CrI 1.11-3.59) for a one-unit increase in the proportion of the population who had never attended school and migrants, respectively., Conclusions: This study identified spatial clustering of HIV infection in Amhara Region, with a slight reduction in the annual infection rates from 2015 to 2017. The proportion of the population who were migrants or who had a low educational status was associated with a high risk of infection. Access to HIV counselling and the promotion of condom utilization, integrated with other health care services, targeting those with a lower level of education and seasonal migrants, are important strategies for the prevention of new HIV infections., (Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Published: 2019
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25. Effect of Temperature and Altitude Difference on Tuberculosis Notification: A Systematic Review.

Author: Gelaw YA, Yu W, Magalhães RJS, Assefa Y, and Williams G
Abstract: Background: Ecological factors are important indicators for tuberculosis (TB) notification. However, consolidation of evidence on the effect of altitude and temperature on TB notification rate has not yet been done. The aim of this review is to illustrate the effect of altitude and temperature on TB notification rate., Methods: Electronic searches were undertaken from PubMed, EMBASE, and Scopus databases. Hand searches of bibliographies of retrieved papers provided additional references. A review was performed using the Meta-analysis Of Observational Studies in Epidemiology guideline., Results: Nine articles from various geographic regions were included in the study. Five out of nine studies showed the effect of altitude and four articles identified temperature effects. Results showed that TB notification rates were lower at higher altitude and higher at a higher temperature., Conclusion: This review provides qualitative evidence that TB notification rates increase with temperature and decrease with altitude. The findings of this review will encourage policymakers and program managers to consider seasonality and altitude differences in the design and implementation of TB prevention and control strategies., Competing Interests: There are no conflicts of interest.
Published: 2019
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26. Community health extension program of Ethiopia, 2003-2018: successes and challenges toward universal coverage for primary healthcare services.

Author: Assefa Y, Gelaw YA, Hill PS, Taye BW, and Van Damme W
Subjects: Ethiopia, Humans, Program Evaluation, Community Health Services organization & administration, Primary Health Care, Universal Health Insurance organization & administration
Abstract: Background: Ethiopia has been implementing a community health extension program (HEP) since 2003. We aimed to assess the successes and challenges of the HEP over time, and develop a framework that may assist the implementation of the program toward universal primary healthcare services., Methods: We conducted a systematic review and synthesis of the literature on the HEP in Ethiopia between 2003 and 2018. Literature search was accomplished in PubMed, Embase and Google scholar databases. Literature search strategies were developed using medical subject headings (MeSH) and text words related to the aim of the review. We used a three-stage screening process to select the publications. Data extraction was conducted by three reviewers using pre-prepared data extraction form. We conducted an interpretive (not aggregative) synthesis of studies., Findings: The HEP enabled Ethiopia to achieve significant improvements in maternal and child health, communicable diseases, hygiene and sanitation, knowledge and health care seeking. The HEP has been a learning organization that adapts itself to community demands. The program is also dynamic enough to shift tasks between health centers and community. The community has been a key player in the successful implementation of the HEP. In spite of these successes, the program is currently facing challenges that remain to be addressed. These challenges are related to productivity and efficiency of health extension workers (HEWs); working and living conditions of HEWs; capacity of health posts; and, social determinants of health. These require a systemic approach that involves the wider health system, community, and sectors responsible for social determinants of health. We developed a framework that may assist in the implementation of the HEP., Conclusion: The HEP has enabled Ethiopia to achieve significant improvements. However, several challenges remain to be addressed. The framework can be utilized to improve community health programs toward universal coverage for primary healthcare services.
Published: 2019
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27. Willingness to pay for community-based health insurance and associated factors among rural households of Bugna District, Northeast Ethiopia.

Author: Minyihun A, Gebregziabher MG, and Gelaw YA
Subjects: Adolescent, Adult, Aged, Community Networks, Ethiopia, Female, Humans, Male, Middle Aged, Young Adult, Consumer Behavior statistics & numerical data, Insurance, Health statistics & numerical data, Rural Population statistics & numerical data, Socioeconomic Factors
Abstract: Objective: Community based health insurance schemes are becoming recognized as powerful method to achieve universal health coverage and reducing the financial catastrophic shock of the community. Therefore, this study aimed to assess willingness to pay for community-based health insurance and associated factors among rural households of Bugna District, Ethiopia., Results: A total of 532 study participants were included in the study. The finding indicated that 77.8% of the households were willing to pay for the community-based health insurance. The average amount of money the households were willing to pay per household per annum was 233 ETB ($11.12 USD). The result of the study also revealed that attending formal education[ß = 3.20; 95% CI = 1.87, 4.53], history of illness [ß = 2.52; 95% CI = 1.29, 3.75], household size [ß = 0.408; 95% CI = 0.092, 0.724], awareness about the scheme [ß = 2.96; 95% CI = 1.61, 4.30], and wealth status [ß = 5.55; 95% CI = 4.19, 6.90] were factors significantly associated with willingness to pay. Therefore, enhancing awareness of the community about the scheme, considering the amount of premium as per household family size and wealth status might increase household's willingness to pay for community-based health insurance.
Published: 2019
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28. Incidence and risk factors of first-line antiretroviral treatment failure among human immunodeficiency virus-infected children in Amhara regional state, Ethiopia: a retrospective follow-up study.

Author: Sisay MM, Ayele TA, Gelaw YA, Tsegaye AT, Gelaye KA, and Melak MF
Subjects: Adolescent, Child, Ethiopia, Female, Follow-Up Studies, Humans, Incidence, Male, Retrospective Studies, Risk Factors, Treatment Failure, Anti-HIV Agents therapeutic use, Antiretroviral Therapy, Highly Active, HIV Infections drug therapy
Abstract: Objective: This study aimed to assess the incidence and risk factors of treatment failure among HIV/AIDS-infected children who were on antiretroviral therapy (ART) in Amhara National Regional State, Ethiopia., Methods: A retrospective follow-up study was conducted from January 2010 to March 2016. A total of 824 children under the age of 15 who had started ART were included in the study. Data were collected from children's medical charts and ART registration logbook using a standard checklist. A Weibull regression model was used to identify the risk factors of treatment failure. Adjusted HRs (AHRs) with 95% CIs were used to declare statistical significance., Results: The mean (±SD) age of the children was 6.4±3.6 years, with a median (IQR) follow-up of 30.5 (14.6-51.4) months. Sixty-three children (7.7%, 95% CI 5.8 to 9.5) developed treatment failure, 17 (27.0%) of whom were immunological and 46 (73.0%) were clinical failures. The incidence rate of treatment failure was 22.1/10 000 person-months. The cumulative probability of failure was 0.4, with 28 562.5 person-month observations. Lack of disclosure (AHR=4. 4, 95% CI 1.8 to 11.3), opportunistic infections during initiation of ART (AHR=2.3, 95% CI 1.3 to 4.1) and prolonged follow-up (AHR=0.06, 95% CI 0.02 to 0.18) were the main predictors of treatment failure., Conclusion: This study revealed that the incidence of treatment failure remains a significant public health concern in Ethiopia. Undisclosed HIV status to children, the presence of opportunistic infections during initiation of ART and prolonged follow-up were found to be the main predictors of treatment failure. Hence, early detection of treatment failure and further studies on viral monitoring need to be considered., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)
Published: 2018
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29. The role of smoking in the relationship between intimate partner violence and age at natural menopause: a mediation analysis.

Author: Mishra GD, Chung HF, Gelaw YA, and Loxton D
Abstract: Background: Age at natural menopause (ANM) is considered as a biologic marker of health and ageing. The relationship between intimate partner violence (IPV) and ANM is currently unknown, and whether smoking plays a role in this relationship is unclear. The aim of this study was to examine the association between IPV and ANM and to quantify the effect mediated through smoking., Methods: Data were drawn from the 1946-51 cohort of the Australian Longitudinal Study on Women's Health, a prospective cohort study first conducted in 1996. History of IPV (yes or no) was self-reported at baseline. ANM was confirmed by at least 12 months of cessation of menses where this was not a result of medical interventions such as bilateral oophorectomy or hysterectomy and categorised as <45 (early menopause), 45-49, 50-51, 52-53, and ≥54 years. Regression models and mediation analyses based on the counterfactual framework were performed to examine the relationship between IPV and ANM and to quantify the proportion mediated through smoking (never, past, current <10, 10-19 and ≥20 cigarettes/day)., Results: Of 6138 women in the study with natural menopause, 932 (15%) reported a history of IPV and 429 (7.0%) had an early ANM (before age 45 years). Women with IPV were more likely to smoke and be heavy smokers (Odds Ratio: 2.77, 95% CI 2.19-3.51). Women with IPV were also at increased risk of early menopause (ANM <45 years) (Relative Risk Ratio: 1.36, 95% CI 1.03-1.80) after accounting for education level, income difficulties, age at menarche, parity, body mass index, and perceived stress, compared to the reference group (women without IPV and ANM at 50-51 years). This relationship was attenuated after adjusting for smoking (Relative Risk Ratio: 1.20, 95% CI 0.90-1.59). Mediation analysis showed that cigarette smoking explained 36.7% of the association between IPV and early menopause (ANM <45 vs. ≥45 years)., Conclusion: Cigarette smoking substantially mediated the relationship between IPV and early menopause. Findings suggest that as part of addressing the impact of IPV, timely interventions that result in cessation of smoking will partly mitigate the increased risk of early menopause., Competing Interests: The study protocols were approved by the Human Research Ethics Committees of the University of Newcastle and University of Queensland, Australia. Informed consent was obtained from all participants at each survey.Not applicable.The authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Published: 2018
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30. Factors associated with utilization of long-acting and permanent contraceptive methods among women who have decided not to have more children in Gondar city.

Author: Zenebe CB, Adefris M, Yenit MK, and Gelaw YA
Subjects: Adolescent, Adult, Cross-Sectional Studies, Ethiopia, Female, Humans, Middle Aged, Odds Ratio, Prevalence, Surveys and Questionnaires, Young Adult, Contraception psychology, Contraception statistics & numerical data, Contraception Behavior psychology, Contraception Behavior statistics & numerical data, Family Planning Services statistics & numerical data
Abstract: Background: Despite the fact that long acting family planning methods reduce population growth and improve maternal health, their utilization remains poor. Therefore, this study assessed the prevalence of long acting and permanent family planning method utilization and associated factors among women in reproductive age groups who have decided not to have more children in Gondar city, northwest Ethiopia., Method: An institution based cross-sectional study was conducted from August to October, 2015. Three hundred seventeen women who have decided not to have more children were selected consecutively into the study. A structured and pretested questionnaire was used to collect data. Both bivariate and multi-variable logistic regressions analyses were used to identify factors associated with utilization of long acting and permanent family planning methods. The multi-variable logistic regression analysis was used to investigate factors associated with the utilization of long acting and permanent family planning methods. The Adjusted Odds Ratio (AOR) with the corresponding 95% Confidence Interval (CI) was used to show the strength of associations, and variables with a P-value of <0.05 were considered statistically significant., Results: In this study, the overall prevalence of long acting and permanent contraceptive (LAPCM) method utilization was 34.7% (95% CI: 29.5-39.9). According to the multi-variable logistic regression analysis, utilization of long acting and permanent contraceptive methods was significantly associated with women who had secondary school, (AOR: 2279, 95% CI: 1.17, 4.44), college, and above education (AOR: 2.91, 95% CI: 1.36, 6.24), history of previous utilization (AOR: 3.02, 95% CI: 1.69, 5.38), and information about LAPCM (AOR: 8.85, 95% CI: 2.04, 38.41)., Conclusion: In this study the prevalence of long acting and permanent family planning method utilization among women who have decided not to have more children was high compared with previous studies conducted elsewhere. Advanced educational status, previous utilization of LAPCM, and information on LAPCM were significantly associated with the utilization of LAPCM. As a result, strengthening behavioral change communication channels to make information accessible is highly recommended.
Published: 2017
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31. Pertussis outbreak investigation of Mekdela district, South Wollo zone, Amhara region, North-West Ethiopia.

Author: Alamaw SD, Kassa AW, and Gelaw YA
Subjects: Adolescent, Adult, Bordetella pertussis immunology, Child, Child, Preschool, Cross-Sectional Studies, Ethiopia epidemiology, Female, Humans, Infant, Infant, Newborn, Male, Mass Vaccination statistics & numerical data, Middle Aged, Risk Factors, Surveys and Questionnaires, Survival Analysis, Whooping Cough immunology, Whooping Cough mortality, Whooping Cough prevention & control, Bordetella pertussis isolation & purification, Disease Outbreaks, Pertussis Vaccine administration & dosage, Vaccination Coverage statistics & numerical data, Whooping Cough epidemiology
Abstract: Background: Pertussis is a highly contagious respiratory illness caused by Bordetella pertussis. It is one of the most common vaccine-preventable bacterial infections that affects all susceptible individuals, regardless of age. Investigation was done to verify the existence of an outbreak and to identify associated risk factors contributed for the occurrence of an outbreak in Tork and Warkaye villages of Mekdela district., Methods: Unmatched community based case control and descriptive cross sectional investigation were conducted with one to two ratios. We used structured questionnaire to collect data from cases and controls., Results: A total of 215 cases and eight deaths were identified with an overall attack rate of 1.3 per 1000 population. The mean age of the cases was 3.7 years which was ranged from 3 months to 45 years. The more affected groups were females. On multivariate logistic regression analysis, the risk factor that remained independently statically significant associated with developing pertussis was presence of infected person in the family AOR (adjusted odds ratio): 5.859, (95% CI 2.526-13.589). But previously sick with pertussis AOR: 0.053, (95% CI 0.006-0.460) and receiving full dose of vaccine AOR: 0.256, (95% CI 0.080-0.818) were remained as protective factors from pertussis infection., Conclusions: The suspected pertussis outbreak was occurred in remote pocket villages/kebeles of Mekdela district. Routine immunization was not given regularly and functional refrigerators were not available in the health posts. Routine immunization services and treatment of infected patients with appropriate antibiotics should be intensified.
Published: 2017
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32. The prevalence of impaired fasting glucose and undiagnosed diabetes mellitus and associated risk factors among adults living in a rural Koladiba town, northwest Ethiopia.

Author: Worede A, Alemu S, Gelaw YA, and Abebe M
Subjects: Adult, Aged, Aged, 80 and over, Cross-Sectional Studies, Ethiopia epidemiology, Female, Humans, Male, Middle Aged, Prevalence, Risk Factors, Young Adult, Blood Glucose, Delayed Diagnosis statistics & numerical data, Diabetes Mellitus blood, Diabetes Mellitus epidemiology, Hypertension epidemiology, Hypertriglyceridemia epidemiology, Obesity epidemiology, Rural Population statistics & numerical data
Abstract: Background: Diabetes mellitus is becoming a big public health challenge, particularly in developing countries like Ethiopia. It is a manageable disease if early screening and follow up is made. However, as studies in Ethiopia are limited and unorganized, determining the magnitude of prediabetes and diabetes and identifying associated risk factors is quite essential., Methods: A community-based, cross-sectional study was conducted from February to April 2015 among adults (aged ≥20 years) in a rural Koladiba town. A multistage sampling technique was used to select a total of 392 study participants. Data were collected after a fully informed written consent was obtained from each participant. Demographic, behavioral, and clinical data were collected using a well-structured questionnaire. Multivariable logistic regression models were fitted to control the effect of confounders. Adjusted odds ratios (AOR) with their 95% confidence intervals (95% CI) were computed to measure associations. A p value of <0.05 was considered as statistically significant., Results: The prevalence of impaired fasting glucose and undiagnosed diabetes mellitus were 12% (95% CI 9-16) and 2.3% (95% CI 1.1-4), respectively, in Koladiba. Overweight (AOR: 4.257, 95% CI 1.345-13.476), obesity (AOR: 5.26, 95% CI 1.138-24.316), hypertriglyceridemia (AOR: 2.83, 95% CI 1.451-5.521), and systolic hypertension (AOR: 3.858, 95% CI 1.62-9.189) were found to be independently associated with impaired fasting glucose. Positive family history of diabetes also showed a marginal association with impaired fasting glucose (p = 0.057). Male sex (p = 0.012) and hypertriglyceridemia (p = 0.030) were associated with undiagnosed diabetes mellitus., Conclusions: The prevalence of impaired fasting glucose and undiagnosed diabetes mellitus are found to be significant. Obesity, hypertriglyceridemia, and systolic hypertension are independently associated with impaired fasting glucose among adults. We recommend that the community be aware of healthy life style, early screening, and maintain continuous follow up.
Published: 2017
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33. Exclusive breastfeeding and mothers' employment status in Gondar town, Northwest Ethiopia: a comparative cross-sectional study.

Author: Chekol DA, Biks GA, Gelaw YA, and Melsew YA
Abstract: Background: Exclusive breastfeeding is defined as feeding an infant breast milk only, for the first six months. In Ethiopia, more than half of infants do not receive exclusive breastfeeding. Workplace barriers contribute to these low rates of exclusive breastfeeding practices. Understanding the sociodemographic, health related, behavioral and economic factors is crucial to promote the practice of exclusive breastfeeding in Ethiopia. Therefore, the aim of this study was to assess the extent of exclusive breastfeeding practice and associated factors among employed and unemployed mothers with children of age 7-12 months in Gondar town, northwest Ethiopia, 2015., Methods: A community based comparative cross-sectional study was conducted in October 2015. Simple random sampling technique was used to select 649 eligible mothers with children age 7-12 months during the study period. A structured and pretested interviewer administered questionnaire was used to collect the data. Three logistic regression models: whole sample, employed and not employed, were fitted., Results: A total of 649 (333 unemployed and 316 employed) mothers were interviewed. The mean duration of mothers to exclusively breastfeed was 4.77 months (± 1.36 Standard Deviation [SD]). Exclusive breastfeeding was higher among unemployed 48.0% with 95% Confidence Interval (CI) (42.0%, 54.0%) than employed (20.9%) with 95% CI (16.0%, 25.0%). Parity of three children and above (Adjusted Odds Ratio [AOR] = 3.48), and having social support (AOR = 3.45) were positively associated with exclusive breastfeeding while poor knowledge (AOR = 0.30), wealth index of the medium level (AOR = 0.38) were negatively associated among employed mothers. In the case of unemployed mothers, vaginal delivery (AOR = 2.60) and having social support (AOR = 3.03) were positively associated with exclusive breastfeeding while, poor knowledge (AOR = 0.28), and not having antenatal care (AOR = 0.56) were negatively associated., Conclusions: The overall exclusive breastfeeding practice of mothers was low. However, unemployed mothers breastfeed more than employed mothers. Providing a special support for employed mothers and revising either the legislation of the two month postpartum maternity leave or applying different alternatives is recommended.
Published: 2017
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34. Spatial patterns of childhood diarrhea in Ethiopia: data from Ethiopian demographic and health surveys (2000, 2005, and 2011).

Author: Bogale GG, Gelaye KA, Degefie DT, and Gelaw YA
Subjects: Child, Preschool, Cross-Sectional Studies, Ethiopia epidemiology, Health Surveys, Humans, Infant, Public Health, Spatio-Temporal Analysis, Diarrhea epidemiology
Abstract: Background: Childhood diarrhea is a major public health problem, especially in developing countries, including Ethiopia. Exploring the spatial pattern of childhood diarrhea is important to monitor and design effective intervention programs. Therefore, this study aimed to explore the spatial patterns of childhood diarrhea in Ethiopia over the past one decade., Methods: A total of 29,358 under-five children were retrieved from three consecutive Ethiopian demographic and health surveys (2000, 2005, and 2011) and included into the study. Spatial cluster and autocorrelation analysis was done to explore the patterns of childhood diarrhea., Results: Childhood diarrhea clustered spatially at a national level in all survey periods (Moran's I: 0.3830-1.3296, p < 0.05). Significant spatial clusters were found in different survey periods across the regions. The most likely spatial clusters were found in Southern Nations Nationalities and people, West Oromia, Gambella, Benshangul-Gumuz, and Somali regions. Childhood diarrhea also clustered at the border areas of Southern Nations Nationalities and People and Tigray, Central Somali and Western Oromia, Gambella and Amhara (West Gojam, Awi, Oromia, and Wag Himra) regions. In 2000, the most likely clusters were found in Southern Nations Nationalities and People, West Oromia, and Gambella regions (LLR = 55.37, p < 0.001); in 2005, at Southern Nations Nationalities and People (LLR: 45.69, p < 0.001); and in 2011, at Gambella, West Southern Nations Nationalities and People and Oromia, and Benshangul-Gumuz regions (LLR: 51.09, p < 0.001)., Conclusion: In this study, childhood diarrhea remains public health problem and had a spatial variation across the regions. Identifying the risk areas would help in designing effective interventions to reduce childhood diarrhea in these areas.
Published: 2017
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35. Determinants to antiretroviral treatment non-adherence among adult HIV/AIDS patients in northern Ethiopia.

Author: Gebrezgabher BB, Kebede Y, Kindie M, Tetemke D, Abay M, and Gelaw YA
Subjects: Adolescent, Adult, Aged, Aged, 80 and over, Case-Control Studies, Ethiopia, Female, Follow-Up Studies, Humans, Male, Middle Aged, Young Adult, Anti-HIV Agents therapeutic use, HIV Infections drug therapy, Medication Adherence
Abstract: Background: Adhering 95% and above of antiretroviral therapy reduces the rate of disease progression and death among people's living human immunodeficiency virus. Though manifold factors have reported as determinant factors of antiretroviral therapy adherence status, perhaps determinants of non-adherence differ up on the activities of patients in the study setting., Methods: An institution based unmatched case-control study was conducted in Aksum town. Individuals who had a 6-month follow-up with complete individual information were included in the study. Document review and interviewer based techniques were used to collect the data. Binary logistic regression analysis was used to identify the determinant factors of non-adherence., Results: A total of 411 (137 cases and 274 control) study participants were included in the study. The majority of them were male in sex. Having 2 years and above duration on ART [AOR = 7, 95% CI (2.2, 22.6)], history of adverse effect [AOR = 6.9, 95% CI (1.4, 32.9)], substance use [AOR = 5.3, 95% CI (1.4, 20.0)], living with parents [AOR = 3.4, 95% CI (1.2, 10.3)], having depression symptom [AOR = 3.3, 95% CI (1.4, 7.5)], <350 cells/mm 3 cluster of differentiation 4 count [AOR = 3.2, 95% CI (1.8, 5.8)] and low dietary diversity [AOR = 2, 95% CI (1.1, 3.7)] were found significant determinants of non-adherence to antiretroviral drug., Conclusion: Program, social and individual related factors showed a statistically significant associated with non-adherence to antiretroviral therapy. Managing lifestyle by developing self-efficacy of individuals and treating related threat to improve adherence status of antiretroviral therapy is recommended in this study.
Published: 2017
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36. Maternal health care service seeking behaviors and associated factors among women in rural Haramaya District, Eastern Ethiopia: a triangulated community-based cross-sectional study.

Author: Kifle D, Azale T, Gelaw YA, and Melsew YA
Subjects: Adolescent, Adult, Cross-Sectional Studies, Delivery, Obstetric, Female, Humans, Maternal Health, Pregnancy, Pregnancy Complications prevention & control, Rural Population, Socioeconomic Factors, Young Adult, Community Health Services statistics & numerical data, Health Knowledge, Attitudes, Practice, Health Services Accessibility statistics & numerical data, Maternal Health Services statistics & numerical data, Patient Acceptance of Health Care psychology
Abstract: Background: Regular utilization of maternal health care services reduces maternal morbidity and mortality. This study assessed the maternal health care seeking behavior and associated factors of reproductive age women in rural villages of Haramaya district, East Ethiopia., Methods: Community based cross sectional study supplemented with qualitative data was conducted in Haramaya district from November 15 to Decemeber 30, 2015. A total of 561 women in reproductive age group and who gave birth in the last 2 years were randomly included. Bivariate and multivariate logistic regressions model was used to identify the associated factors. Odds ratios with 95% CI were used to measure the strength of association., Result: Maternal health care service seeking of women was found as; antenatal care 74.3% (95% CI; 72.5, 76.14), attending institutional delivery 28.7% (95% CI; 26.8, 30.6) and postnatal care 22.6% (95% CI; 20.84, 24.36). Knowledge of pregnancy complications, Educational status, and religion of women were found to be significantly associated with antenatal health care, delivery and postnatal health care service seeking behaviours triangulated with individual, institutional and socio-cultural qualitative data., Conclusion: The maternal health care service seeking behavior of women in the study area was low. Educational status of the women, birth order and knowledge about pregnancy complications were the major factors associated with maternal health care service seeking behavior Focused health education with kind and supportive health care provider counseling will improve the maternal health care seeking behaviors of women.
Published: 2017
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37. Determinants of default to fully completion of immunization among children aged 12 to 23 months in south Ethiopia: unmatched case-control study.

Author: Asfaw AG, Koye DN, Demssie AF, Zeleke EG, and Gelaw YA
Subjects: Case-Control Studies, Data Collection, Ethiopia, Female, Humans, Infant, Logistic Models, Male, Patient Acceptance of Health Care, Health Knowledge, Attitudes, Practice, Immunization statistics & numerical data, Mothers statistics & numerical data, Vaccines administration & dosage
Abstract: Introduction: Immunization is a cost effective interventions of vaccine preventable disease. There is still, 2.5 million children die by vaccine preventable disease every year in developing countries. In Ethiopia, default to fully completion of child immunization is high and determinants of default to completions are not explored well in the study setting. The aim of the study was to identify determinants of default to fully completion of immunization among children between ages 12 to 23 months in Sodo Zurea District, Southern Ethiopia., Methods: Community based unmatched case-control study was conducted. Census was done to identify cases and controls before the actual data collection. A total of 344 samples (172 cases and 172 controls) were selected by simple random sampling technique. Cases were children in the age group of 12 to 23 months old who missed at least one dose from the recommended schedule. Bivariable and multivariable binary logistic regression was used to identify the determinant factors. Odds ratio, 95%CI and p - value less than 0.05 was used to measure the presence and strength of the association., Results: Mothers of infants who are unable to read and write (AOR=8.9; 95%CI: 2.4, 33.9) and attended primary school (AOR=4.1; 95% CI:1.4-15.8), mothers who had no postnatal care follow up (AOR=0.4; 95%CI: 0.3, 0.7), good maternal knowledge towards immunization (AOR= 0.5; 95% CI: 0.3, 0.8) and maternal favorable perception towards uses of health institution for maternal and child care (AOR= 0.2; 95% CI: 0.1, 0.6) were significant determinant factors to default to fully completion of immunization., Conclusion: Working on maternal education, postnatal care follow up, promoting maternal knowledge and perception about child immunization are recommended measures to mitigate defaults to complete immunization.
Published: 2016
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38. Married women's decision making power on family planning use and associated factors in Mizan-Aman, South Ethiopia: a cross sectional study.

Author: Belay AD, Mengesha ZB, Woldegebriel MK, and Gelaw YA
Subjects: Contraception psychology, Cross-Sectional Studies, Employment statistics & numerical data, Ethiopia, Female, Humans, Male, Spouses psychology, Spouses statistics & numerical data, Contraception statistics & numerical data, Contraception Behavior statistics & numerical data, Decision Making, Family Planning Services statistics & numerical data, Interpersonal Relations, Power, Psychological
Abstract: Background: Women's use of family planning service is influenced by many factors, especially by their decision making power. A woman's decision-making power, be it individual or decision made in collaboration with a partner, is the most important factor in the use of family planning in a household. The purpose of this study was to assess the impact of women's decision making power on family planning use and its associated factors., Methods: A community-based cross-sectional study was conducted on married women in the child bearing age. The women who were living in Mizan city were selected using the simple random sampling method. Trained nurses collected the data by interview, using a structured and pre-tested questioner. Bivariable and multivariable binary logistic regression analysis was used to identify the associated factors, and the odds ratio with a 95% CI was computed to assess the strength of the association. Collinearity was also assessed by looking at standard errors in the final fitted model., Result: Overall, more than two-thirds [67.2%: 95% CI (63-71%)] of the married women were found to be more autonomous to decide family planning use. Secondary education [AOR: 9.04, 95% CI: (4.50, 18.16)], government employment [AOR: 4.84, 95% CI: (2.03, 11.52)], being wives of government employed spouses [AOR 2.71, 95% CI: (1.24, 7.97)], having husbands with college or university education [AOR: 11.29, 95% CI: (4.66, 27.35)], and being in the younger age [AOR: 0.27, 95% CI :(0.09, 0.75)] were significantly associated with women's decision-making power on family planning., Conclusions: In this study, women had a high decision making power in family planning use. Age category (34-44-years), formal education, and occupational status had effects on women's decision making power. Promoting parental adult education and engaging women in out of house employment is essential to improve their decision making power in using family planning.
Published: 2016
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39. Determinants of late presentation to HIV/AIDS care in Southern Tigray Zone, Northern Ethiopia: an institution based case-control study.

Author: Gelaw YA, Senbete GH, Adane AA, and Alene KA
Abstract: Background: Late diagnosis and presentation to human immune deficiency virus (HIV)/acquired immune deficiency syndrome care reduce the benefits of antiretroviral therapy and increase the risk of HIV transmission., Objectives: This study was conducted to identify determinants of late presentation to HIV care among people living with HIV in Southern Tigray, Northern Ethiopia., Methods: An institution based un-matched case-control (1:2 ratios) supported with qualitative data was conducted in Southern Tigray Zone from March 1 to April 30, 2014. Individuals with HIV enrolled from six randomly selected health facilities were included in the study. Cases were people living with HIV who had cluster of differentiation four count <350 cells/μl or World Health Organization stages 3 or 4. A total of 442 study participants were included by systematic sampling techniques. Bivariable and multivariable binary logistic regression model was used to identify associated factors. Odds ratio with 95 % CI was computed to assess the strength of the associations., Result: Age categories, 25-29 years [AOR 3, 95 % CI (1.2-8.1)] and 35-39 years [AOR 4.1, 95 % CI (1.4-12.5)], having two [AOR 6, 95 % CI (1.3-28)] and more [AOR 5.2, 95 % CI (1.1-24.8)] lifetime sexual partners, poor social support [AOR 2.3, 95 % CI (1.26-4.30)], second (next to lowest) wealth quintile [AOR 3.3, 95 % CI 91.3-8.5)], fear of stigma [AOR 4.4, 95 % CI (2.2-8.3)], fear of losing job [AOR 6.8, 95 % CI (1.8-24.5)], and reported severe illness [AOR 4.3, 95 % CI (2.26-8)] were identified to be the risk factors for late presentation., Conclusion: Low socio-economic status and social support, fear of stigma were potential risk factors for late presentation. Efforts towards promoting early care seeking should target on these factors in the study area and other similar settings.
Published: 2015
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40. Prevalence and associated factors of hypertension among adults in Durame Town, Southern Ethiopia.

Author: Helelo TP, Gelaw YA, and Adane AA
Subjects: Adult, Ethiopia epidemiology, Female, Humans, Male, Middle Aged, Prevalence, Hypertension epidemiology
Abstract: Background: To date, non-communicable diseases, such as cardiovascular diseases, are becoming severe public health challenges particularly in developing countries. Hypertension is a modifiable risk factor that contributes the leading role for mortality. The problem is significant in low- and middle-income countries like sub-Saharan Africa. However, there are limited studies in developing countries, particularly in Ethiopia. Hence, determining the magnitude of hypertension and identifying risk groups are important., Methods: A community based cross sectional study was conducted in April 2013 among adults (age>31 years) old. A systematic sampling technique was used to select a total of 518 study participants. Data were collected after full verbal informed consent was obtained from each participant. Multivariable logistic regressions were fitted to control the effect of confounding. Adjusted Odds ratios (OR) with their 95% confidence intervals (95% CI) were calculated to measure associations. Variables having P-value <0.05 were considered as significant., Results: The overall prevalence of hypertension in Durame town was 22.4% (95% CI: 18.8-26.0). Nearly 40% of hypertensive patients were newly screened. Male sex [AOR = 2.03, 95% CI; 1.05-3.93], age [AOR = 29.49, 95% CI; 10.60-81.27], salt use [AOR = 6.55, 95% CI; 2.31-18.53], eating vegetable three or fewer days per week [AOR = 2.3,95% CI; 1.17-4.51], not continuously walking at least for 10 minutes per day [AOR = 7.82, 95% CI; 2.37-25.82], having family history of hypertension [AOR = 2.46, 95%CI; 1.31-4.61] and being overweight/obese [AOR = 15.7, 95% CI 7.89-31.21)] were found to be risk factors for hypertension., Conclusions: The prevalence of hypertension is found to be high. Older age, male sex, having family history of hypertension, physical inactivity, poor vegetable diet, additional salt consumption and obesity were important risk factors associated with hypertension among adults. Community level intervention measures with a particular emphasis on prevention by introducing lifestyle modifications are recommended.
Published: 2014
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41. Effect of residence on mothers' health care seeking behavior for common childhood illness in Northwest Ethiopia: a community based comparative cross--sectional study.

Author: Gelaw YA, Biks GA, and Alene KA
Subjects: Adult, Age Factors, Child, Child, Preschool, Cross-Sectional Studies, Ethiopia, Female, Humans, Infant, Infant, Newborn, Logistic Models, Male, Multivariate Analysis, Odds Ratio, Sex Factors, Socioeconomic Factors, Surveys and Questionnaires, Child Health Services, Health Knowledge, Attitudes, Practice, Maternal Behavior, Mothers psychology, Patient Acceptance of Health Care, Residence Characteristics, Rural Population, Urban Population
Abstract: Background: Children are at higher risk of acquiring infections and developing severe disease. This study assessed the health care seeking behavior and associated factors of urban and rural mothers for common childhood illness in Northwest Ethiopia., Methods: A comparative community based cross-sectional study was conducted among urban and rural mothers living in the district. A multistage sampling technique was used to select the study participants. A pre-tested and structured questioner via interview was used to collect the data. Binary logistic regression analysis was used to identify associated factors. Odds ratio with 95% CI was computed to assess the strength of the associations., Result: A total of 827 (274 urban and 553 rural) mothers were interviewed. Among these, 79.3% (95% CI: (76.5%, 82.06%)) of the mothers were sought health care in the district. Health care seeking behavior was higher among urban mothers (84.6%) than rural mothers (76.7%). Marital status, completion health extension package, and sex of child were significantly associated with health care seeking behavior of urban mothers. Whereas age of child, age and occupation of mothers, educational level of fathers, wealth quintile, and type of reported illness were significantly associated with rural mothers. Perceived severity of illness was significantly associated with both urban and rural mothers for health care seeking behavior., Conclusion: The overall health seeking behaviors of mothers for common childhood illness was high. However, urban mothers seek health care more than rural. Socio Economic position and types of reported illness has an effect for health seeking behavior of rural mothers. Whereas child sex preference and graduation status for health extension package has an effect for health care seeking behavior of urban mothers. Work on strengthen accessibility of health care services in the rural mothers and increase awareness of mothers about the disadvantage of sex preferences will improve the health care seek behavior of families regardless of the severity of illness and types of illnesses.
Published: 2014
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