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1. Population modifiable risk factors associated with under-5 acute respiratory tract infections and diarrhoea in 25 countries in sub-Saharan Africa (2014-2021): an analysis of data from demographic and health surveys.

Author

Ahmed, KY, Dadi, AF, Kibret, GD, Bizuayehu, HM, Hassen, TA, Amsalu, E, Ketema, DB, Kassa, ZY, Bore, MG, Alebel, A, Alemu, AA, Shifa, JE, Leshargie, CT, Thapa, S, Omar, SH, Ross, AG, Ahmed, KY, Dadi, AF, Kibret, GD, Bizuayehu, HM, Hassen, TA, Amsalu, E, Ketema, DB, Kassa, ZY, Bore, MG, Alebel, A, Alemu, AA, Shifa, JE, Leshargie, CT, Thapa, S, Omar, SH, and Ross, AG

Abstract

BACKGROUND: Identifying the critical modifiable risk factors for acute respiratory tract infections (ARIs) and diarrhoea is crucial to reduce the burden of disease and mortality among children under 5 years of age in sub-Saharan Africa (SSA) and ultimately achieving the Sustainable Development Goals (SDGs). We investigated the modifiable risk factors of ARI and diarrhoea among children under five using nationally representative surveys. METHODS: We used the most recent demographic and health survey (DHS) data (2014-2021) from 25 SSA countries, encompassing a total of 253,167 children. Countries were selected based on the availability of recent datasets (e.g., DHS-VII or DHS-VIII) that represent the current socioeconomic situations. Generalised linear latent mixed models were used to compute odds ratios (ORs). Population attributable fractions (PAFs) were calculated using adjusted ORs and prevalence estimates for key modifiable risk factors among ARI and diarrhoeal cases. FINDINGS: This study involved 253,167 children, with a mean age of 28.7 (±17.3) months, and 50.5% were male. The highest PAFs for ARI were attributed to unclean cooking fuel (PAF = 15.7%; 95% CI: 8.1, 23.1), poor maternal education (PAF = 13.4%; 95% CI: 8.7, 18.5), delayed initiation of breastfeeding (PAF = 12.4%; 95% CI: 9.0, 15.3), and poor toilets (PAF = 8.5%; 95% CI: 4.7, 11.9). These four modifiable risk factors contributed to 41.5% (95% CI: 27.2, 52.9) of ARI cases in SSA. The largest PAFs of diarrhoea were observed for unclean cooking fuel (PAF = 17.3%; 95% CI: 13.5, 22.3), delayed initiation of breastfeeding (PAF = 9.2%; 95% CI: 7.5, 10.5), household poverty (PAF = 7.0%; 95% CI: 5.0, 9.1) and poor maternal education (PAF = 5.6%; 95% CI: 2.9, 8.8). These four modifiable risk factors contributed to 34.0% (95% CI: 26.2, 42.3) of cases of diarrhoea in SSA. INTERPRETATION: This cross-sectional study identified four modifiable risk factors for ARI and diarrhoea that should be a priority for policy

Published
2024

2. Intention toward condom use and its associated factors among students of Debre Work Senior Secondary and Preparatory School, East Gojjam Zone, Amhara Region, Ethiopia

Author

Abera H, Tamiru F, and Kibret GD

Subjects
Condom, intension, high school students, health belief model, Immunologic diseases. Allergy, RC581-607
Abstract

Habtamu Abera,1 Fanta Tamiru,2 Getiye Dejenu Kibret2 1Department of Nursing and Midwifery, School of Allied Health Sciences, Addis Ababa University College of Health Sciences, Addis Ababa, 2Department of Public Health, College of Health Scienc, Debre Markos University, Debre Markos, Ethiopia Objective: The main aim of this research was to investigate the students’ intention toward condom use and associated factors among students in Debre Work Secondary and Preparatory School, 2015.Methods: A survey was carried out in the high school and the preparatory school. The self-administered semistructured questionnaire was distributed to 422 students. Systematic sampling techniques were employed to each class. Data were entered and analyzed by using SPSS version 20.0 software. Descriptive and analytical data analysis and presentation were used. Logistic regression model was used to check independent associations.Result: Most (80.8%) of the respondents were not married. More than half (53.0% and 52.3%) of the respondents had low perceived benefit and low perceived self-efficacy of using condom. About 46.79% of respondents had an interest in using condoms and the rest had no intention. Males were 1.96 times more likely to have intention to use condom compared to females (adjusted odds ratio [AOR], 95% confidence interval [CI] 1.96 [1.29, 2.99]). When the intention to use condoms was compared, married respondents were 2.41 times more likely than those who were not married (AOR, 95% CI 2.41 [1.41, 4.14]). Intention to use condoms among respondents who had high perceived benefit of using condom were 1.57 times more compared to those who had low perceived benefit of using condom (AOR, 95% CI 1.57 [1.03, 2.39]). Intention to use condoms among those who had high perceived self-efficacy on condom use was 4.37 times higher compared to those who had low perceived self-efficacy (AOR, 95% CI 4.37 [2.85, 6.71]).Conclusion: The level of intention to use condoms among students of Debre Work Senior Secondary and Preparatory School was low. Sex, current marital status, perceived benefit of using condom, and perceived self-efficacy on condom use were the most positive contributing factors for intention to condom use. Keywords: condom, intention, high school students, health belief model condom use, HIV risk

Published
2017

3. Unmet Supportive Care Needs Among Cancer Patients in Sub-Saharan African Countries: A Mixed Method Systematic Review and Meta-Analysis.

Author

Bore, MG, Dadi, AF, Ahmed, KY, Hassen, TA, Kibret, GD, Kassa, ZY, Amsalu, E, Ketema, DB, Perry, L, Alemu, AA, Shifa, JE, Alebel, A, Leshargie, CT, Bizuayehu, HM, Bore, MG, Dadi, AF, Ahmed, KY, Hassen, TA, Kibret, GD, Kassa, ZY, Amsalu, E, Ketema, DB, Perry, L, Alemu, AA, Shifa, JE, Alebel, A, Leshargie, CT, and Bizuayehu, HM

Abstract

INTRODUCTION: Supportive cancer care is vital to reducing the current disparities in cancer outcomes in Sub-Saharan Africa (SSA), including poor survival and low quality of life, and ultimately achieving equity in cancer care. This is the first review aimed to evaluate the extent of unmet supportive care needs and identify their contributing factors among patients with cancer in SSA. METHODS: Six electronic databases (CINAHL, Embase, Medline [Ovid], PsycINFO, PubMed, and Cochrane Library of Databases] were systematically searched. Studies that addressed one or more domains of unmet supportive cancer care needs were included. Findings were analyzed using narrative analysis and meta-analysis, as appropriate. RESULT: Eleven articles out of 2732 were retained in the review. The pooled prevalence of perceived unmet need for cancer care in SSA was 63% (95% CI: 45, 81) for physical, 59% (95% CI: 45, 72) for health information and system, 58% (95% CI: 42, 74) for psychological, 44% (95% CI: 29, 59) for patient care and support, and 43% (95% CI: 23, 63) for sexual. Older age, female sex, rural residence, advanced cancer stage, and low access to health information were related to high rates of multiple unmet needs within supportive care domains. CONCLUSION: In SSA, optimal cancer care provision was low, up to two-thirds of patients reported unmet needs for one or more domains. Strengthening efforts to develop comprehensive and integrated systems for supportive care services are keys to improving the clinical outcome, survival, and quality of life of cancer patients in SSA.

Published
2023

4. Birth asphyxia related mortality in Northwest Ethiopia: A multi-centre cohort study.

Author

Solevåg, AL, Ketema, DB, Aragaw, FM, Wagnew, F, Mekonnen, M, Mengist, A, Alamneh, AA, Belay, YA, Kibret, GD, Leshargie, CT, Birhanu, MY, Hibstie, YT, Temesgen, B, Alebel, A, Solevåg, AL, Ketema, DB, Aragaw, FM, Wagnew, F, Mekonnen, M, Mengist, A, Alamneh, AA, Belay, YA, Kibret, GD, Leshargie, CT, Birhanu, MY, Hibstie, YT, Temesgen, B, and Alebel, A

Abstract

BACKGROUND: Birth asphyxia is the second leading cause of neonatal death in Ethiopia, next to preterm-associated infections. Understanding the causes of death in asphyxiated newborns will help to design appropriate care. This study identifies predictors of neonatal mortality in asphyxiated newborns in selected hospitals in Northwest Ethiopia. METHODS: An institution-based prospective cohort study of 480 newborns with birth asphyxia was conducted at Debre Markos Comprehensive Specialized Hospital, Shegaw Motta District Hospital, and Injibara General Hospital. All newborns with asphyxia admitted to the neonatal critical care unit from the first of November 2018 to the first of November 2019 were included. Data were obtained prospectively from mothers using an interviewer's administered questionnaire. The Kaplan-Meier survival curve was used to estimate survival time, and Log rank test was used to compare the survival curves. Bivariable and multivariable Cox proportional hazards models were fitted to identify the independent predictors of mortality in asphyxiated newborns. Adjusted hazard Ratios (AHRs) with 95% Cis (Confidence Intervals) were used to measure the strength of association and test statistical significance. RESULTS: The overall cumulative incidence of mortality among asphyxiated newborns was 42.29% (95% CI: 38%, 46). Asphyxiated neonates with other comorbidities (sepsis, neonatal anemia) (AHR = 2.63, 95% CI:1.69, 4.10), oxygen saturation of 50-69 (AHR = 4.62, 95% CI:2.55, 8.37), oxygen saturation of 70-89 (AHR = 2.82, 95% CI: 1.80, 4.42), severe Apgar score at one minute (AHR = 1.59, 95% CI:1.12, 2.25), neonates with Hypoxic Ischemic Encephalopathy (HIE) (AHR = 6.12, 95% CI:2.23, 16.75) were at higher risk of mortality. CONCLUSIONS: The mortality rate among asphyxiated neonates remains high, and slightly higher than previous studies. Asphyxiated newborns with other comorbidities, severe Apgar score at one minute, who develop HIE, and low oxygen saturation

Published
2023

5. The effect of distance to health facility on neonatal mortality in Ethiopia.

Author

Kibret, GD, Demant, D, Hayen, A, Kibret, GD, Demant, D, and Hayen, A

Abstract

INTRODUCTION: In Ethiopia, more than half of newborn babies do not have access to Emergency Obstetric and Neonatal Care (EmONC) services. Understanding the effect of distance to health facilities on service use and neonatal survival is crucial to recommend policymakers and improving resource distribution. We aimed to investigate the effect of distance to health services on maternal service use and neonatal mortality. METHODS: We implemented a data integration method based on geographic coordinates. We calculated straight-line (Euclidean) distances from the Ethiopian 2016 demographic and health survey (EDHS) clusters to the closest health facility. We computed the distance in ESRI ArcGIS Version 10.3 using the geographic coordinates of DHS clusters and health facilities. Generalised Structural Equation Modelling (GSEM) was used to estimate the effect of distance on neonatal mortality. RESULTS: Poor geographic accessibility to health facilities affects maternal service usage and increases the risk of newborn mortality. For every ten kilometres (km) increase in distance to a health facility, the odds of neonatal mortality increased by 1.33% (95% CI: 1.06% to 1.67%). Distance also negatively affected antenatal care, facility delivery and postnatal counselling service use. CONCLUSIONS: A lack of geographical access to health facilities decreases the likelihood of newborns surviving their first month of life and affects health services use during pregnancy and immediately after birth. The study also showed that antenatal care use was positively associated with facility delivery service use and that both positively influenced postnatal care use, demonstrating the interconnectedness of the components of continuum of care for maternal and neonatal care services. Policymakers can leverage the findings from this study to improve accessibility barriers to health services.

Published
2023

6. Dental caries and associated factors among diabetic and nondiabetic adult patients attending Bichena Primary Hospital's Outpatient Department.

Author

Shiferaw, A, Alem, G, Tsehay, M, Kibret, GD, Shiferaw, A, Alem, G, Tsehay, M, and Kibret, GD

Abstract

PURPOSE: Dental caries is a significant public health issue affecting both the diabetic and nondiabetic populations. However, the problem and associated factors of dental caries among diabetics and nondiabetics patients are not well-known in Ethiopia. This study aims to compare the prevalence of dental caries and associated factors among diabetic and nondiabetic patients at the Outpatient Department of Bichena Primary Hospital in Northwest, Ethiopia. METHODS: Institutional based, comparative cross-sectional study was conducted from October 7 to December 6, 2019, among 200 diabetes and 400 nondiabetic adult patients. A consecutive sampling technique was implemented to recruit study participants. Data were collected by a pretested structured questionnaire and analysis was performed in Statistical Package for Social Science version 20. Bivariable and multivariable logistic regressions were employed and variables with a p-value < 0.05 were declared statistically significant. RESULTS: A total of 582 patients were involved in the study with a response rate of 97.0%. The prevalence of dental caries was 67.9% [95% confidence interval (CI): 63.2%-72.8%] and 79.6% (95% CI: 74.0%-85.70%) in nondiabetic and diabetic group, respectively. Females gender [adjusted odds ratio (AOR) = 1.79, 95% CI: 1.15-2.77], poor oral hygiene (AOR = 2.95, 95% CI: 1.71-5.11), lack of regular teeth cleaning habits (AOR = 3.26, 95% CI: 2.13-4.97), feeling dry mouth (AOR = 2.31, 95% CI: 1.11-4.81), sugared tea drinking (AOR = 2.00, 95% CI: 1.18-3.38), inadequate oral health knowledge (AOR = 3.51, 95% CI: 2.19-5.62), and khat chewing (AOR = 2.14, 95% CI: 1.24-3.71) were significantly associated factors with high prevalence of dental caries. CONCLUSION: The prevalence of caries was significantly higher among diabetics than nondiabetics. Oral health education with preventive measures such as improving teeth cleaning practice, reducing sugary foods and drinks intake, and improving oral hygiene practice of

Published
2022

7. Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia.

Author

Kibret, GD, Demant, D, Hayen, A, Kibret, GD, Demant, D, and Hayen, A

Abstract

BACKGROUND: Ethiopia is a Sub-Saharan country with very high neonatal mortality rates, varying across its regions. The rate of neonatal mortality reduction in Ethiopia is slow, and Ethiopia may not meet the third United Nations sustainable development target by 2030. This study aimed to investigate the spatial variations and contributing factors for neonatal mortality rates in Ethiopia. METHODS: We analysed data from the 2016 Ethiopian Demographic and Health Survey (EDHS), which used a two-stage cluster sampling technique with a census enumeration area as primary and households as secondary sampling units. A Bayesian spatial logistic regression model using the Stochastic Partial Differential Equation (SPDE) method was fitted accounting for socio-economic, health service-related and geographic factors. RESULTS: Higher neonatal mortality rates were observed in eastern, northeastern and southeastern Ethiopia, and the Somali region had higher risks of neonatal mortality. Neonates from frequently drought-affected areas had a higher mortality risk than less drought-affected areas. Application of traditional substances on the cord increased the risk of neonatal mortality (Adjusted Odds Ratio (AOR) = 2.07, 95% Credible Interval (CrI): 1.12 to 4.30) and getting health facility delivery services had a lower odds of neonatal mortality (AOR = 0.60, 95% CrI: 0.37, 0.98). CONCLUSIONS: Residing in drought-affected areas, applying traditional substances on the umbilical cord and not delivering at health facilities were associated with a higher risk of neonatal mortality. Policy-makers and resource administrators at different administrative levels could leverage the findings to prioritise and target areas identified with higher neonatal mortality rates.

Published
2022

8. Geographical accessibility of emergency neonatal care services in Ethiopia: analysis using the 2016 Ethiopian Emergency Obstetric and Neonatal Care Survey.

Author

Kibret, GD, Demant, D, Hayen, A, Kibret, GD, Demant, D, and Hayen, A

Abstract

INTRODUCTION: Access to emergency neonatal health services has not been explored widely in the Ethiopian context. Accessibility to health services is a function of the distribution and location of services, including distance, travel time, cost and convenience. Measuring the physical accessibility of health services contributes to understanding the performance of health systems, thereby enabling evidence-based health planning and policies. The physical accessibility of Ethiopian health services, particularly emergency neonatal care (EmNeC) services, is unknown. OBJECTIVE: To analyse the physical accessibility of EmNeC services at the national and subnational levels in Ethiopia. METHODS: We analysed the physical accessibility of EmNeC services within 30, 60 and 120 min of travel time in Ethiopia at a national and subnational level. We used the 2016 Ethiopian Emergency Obstetric and Neonatal Care survey in addition to several geospatial data sources. RESULTS: We estimated that 21.4%, 35.9% and 46.4% of live births in 2016 were within 30, 60 and 120 min of travel time of fully EmNeC services, but there was considerable variation across regions. Addis Ababa and the Hareri regional state had full access (100% coverage) to EmNeC services within 2 hours travel time, while the Afar (15.3%) and Somali (16.3%) regional states had the lowest access. CONCLUSIONS: The physical access to EmNeC services in Ethiopia is well below the universal health coverage expectations stated by the United Nations. Increasing the availability of EmNeC to health facilities where routine delivery services currently are taking place would significantly increase physical access. Our results reinforce the need to revise service allocations across administrative regions and consider improving disadvantaged areas in future health service planning.

Published
2022

9. Incidence and Predictors of Mortality among Preterm Neonates Admitted to the Neonatal Intensive Care Unit at Debre Markos Referral Hospital, Northwest Ethiopia

Author

Abebaw, E, Reta, A, Kibret, GD, and Wagnew, F

Subjects
Preterm, mortality, survival, incidence, Incidence, Infant, Newborn, Infant, Hospitals, Pregnancy, Intensive Care Units, Neonatal, Infant Mortality, Humans, Female, Ethiopia, Referral and Consultation, Follow-Up Studies, Retrospective Studies
Abstract

Background: Prematurity is the most frequent cause of neonatal death and the second leading cause of under-five mortality. Preterm related complications accounts for 35 % of neonatal deaths within the first week after birth. So far, most studies done in Ethiopia have focused on estimating the prevalence and determinant factors of premature neonatal death. The current study aimed to assess the incidence and predictors of mortality among preterm neonates admitted to neonatal intensive care unit at Debre Markos Referral Hospital. Methods: An institution-based retrospective follow up study was conducted among premature neonates admitted to Neonatal Intensive Care Unit at Debre Markos Referral Hospital from July 2019 to October 2019. Around 498 patients were selected randomly. A multivariable cox proportional hazards model was fitted to identify predictors of mortality. Results: A total of 498 preterm babies were followed, and the mean age for follow up at the time of admission to NICU was 15 hours ± 38 SD. Death rate in preterm was estimated to be 27.11% (95% CI: 23.3%, 31.1%). Preterm neonates with gestational age of less than 32 weeks (AHR=1.51; 95% CI: 1.02, 2.24), respiratory distress syndrome (AHR=1.49; 95% CI: 1.03, 2.17), perinatal asphyxia (AHR=1.74, 95% CI: 1.01, 2.76) and congenital malformation (AHR=3.38, 95% CI: 1.21, 8.77) were statistically significant predictors of mortality among preterms. Conclusion: The incidence of death in preterm neonates is relatively low. Gestational age less than 32 weeks, perinatal asphyxia, respiratory distress syndrome and congenital malformation were found as predictors.

Published
2021

10. 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

11. 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, Kinfu, Y, 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

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

12. 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

13. Factors affecting institutional delivery in Ethiopia: A multi-level analysis

Author

Gashaye, A, Kibret, GD, Bazezew, Y, Mengist, B, Gashaye, A, Kibret, GD, Bazezew, Y, and Mengist, B

Abstract

Background: Childbirth is a complex process that requires the safest care to prevent maternal and neonatal complications. The proportion of births occurring at health institutions in Ethiopia is still below expected (26%), which significantly contribute to a large number of maternal deaths. Hence, identifying factors affecting institutional delivery is crucial. Objectives: The main objective of this study was to assess factors affecting institutional delivery among women who had a live birth in Ethiopia within five years preceding Ethiopian Demographic and Health Survey 2016. Method: The 2016 Ethiopian demographic and health survey data were used to identify factors associated with institutional delivery. As the data has nested structure, a multilevel logistic regression model was used for analysis by taking a nationally representative sample of 7193 women nested within 645 clusters. Result: A significant heterogeneity was observed between clusters for institutional delivery which explains about 53.5% of the total variation. Individual-level variables: higher-level women education (AOR = 5.74; 95% CI 2.7–9.73), parity 5, and more (AOR = 0.39; 95% CI 0.32–0.49) and the number of ANC visit four and greater visit (AOR = 6.74; 95% CI 4.11–11.04) were significantly associated with institutional delivery. Community-level variables, Community media exposure (AOR = 1.80; 95% CI 1.31–2.4) and community antenatal coverage (AOR = 1.97; 95% CI 1.18–3.30) had a significant effect on institutional delivery. Conclusion: The effort to promote institutional delivery should pay special attention to multiparous and less educated women.

Published
2021

14. Incidence and predictors of surgical site infection following cesarean section in North-west Ethiopia: a prospective cohort study

Author

Ketema, DB, Wagnew, F, Assemie, MA, Ferede, A, Alamneh, AA, Leshargie, CT, Kibret, GD, Petrucka, P, Telayneh, AT, and Alebel, A

Subjects
Adult, Adolescent, Cesarean Section, Incidence, Middle Aged, Microbiology, Young Adult, Risk Factors, Pregnancy, Surveys and Questionnaires, Humans, Surgical Wound Infection, Female, Prospective Studies, Ethiopia, Referral and Consultation, 0605 Microbiology, 1103 Clinical Sciences, 1108 Medical Microbiology, Proportional Hazards Models
Abstract

BackgroundFollowing delivery by caesarean section, surgical site infection is the most common infectious complication. Despite a large number of caesarean sections performed at Debre Markos Referral Hospital, there was no study documenting the incidence of surgical site infection after caesarean section. Therefore, this study aimed to estimate the incidence of surgical site infection following caesarean section at Debre-Markos Referral Hospital in Amhara region, North-west Ethiopia.MethodsA prospective cohort study was conducted among 520 pregnant women who had a caesarean section between March 28, 2019 and August 31, 2019. Preoperative, intraoperative, and postoperative data were collected using a standardized questionnaire. Data was entered using EpiData™ Entry Version 4.1 software and analyzed using R Version 3.6.1 software. A descriptive analysis was conducted using tables, interquartile ranges and median. The time to development of surgical site infection was estimated using Kaplan-Meier method. The Cox regression model for bivariable and multivariable analyses was done. Adjusted Hazard Ratio (AHR) with 95% Confidence Interval (CI) was reported to show the strength of association.ResultThe mean age of the study cohort was 27.4 ± 4.8 years. The overall cumulative incidence of surgical site infection was 25.4% with an incidence of 11.7 (95% CI:9.8,13.9) per 1000 person/days. Not able to read and write (AHR = 1.30,95% CI:1.19,2.11), no antenatal care (AHR = 2.16, 95%CI:1.05,4.53), previous history of CS (AHR = 1.21, 95% CI:1.11,2.31), HIV positive (AHR = 1.39, 95% CI:1.21,2.57), emergency procedure (AHR = 1.13, 95% CI:1.11,2.43), vertical type of incision (AHR = 2.60, 95% CI:1.05,6.44), rupture of membrane (AHR = 1.50, 95% CI:1.31,1.64), multiple vaginal examination (AHR = 1.88, 95% CI: 1.71, 3.20) were significant predictors of surgical site infection in this study.ConclusionThis study concluded that the incidence of surgical site infection following caesarean section was relatively high compared to previous studies. Not able to read and write, have no ante natal care, previous history of caesarean section, HIV, emergency surgery, vertical type of incision, rupture of membranes before caesarean section, and multiple vaginal examinations were significant predictors of surgical site infection in this study. Therefore, intervention programs should focus on and address the identified factors to minimize and prevent the infection rate after caesarean section.

Published
2020

15. Neonatal mortality in the neonatal intensive care unit of Debre Markos referral hospital, Northwest Ethiopia: a prospective cohort study

Author

Alebel, A, Wagnew, F, Petrucka, P, Tesema, C, Moges, NA, Ketema, DB, Yismaw, L, Melkamu, MW, Hibstie, YT, Temesgen, B, Bitew, ZW, Tadesse, AA, and Kibret, GD

Subjects
Male, Cesarean Section, Infant, Newborn, Infant, Pediatrics, Hospitals, Cohort Studies, Pregnancy, Risk Factors, Intensive Care Units, Neonatal, Infant Mortality, 1114 Paediatrics and Reproductive Medicine, Humans, Female, Ethiopia, Prospective Studies, Referral and Consultation, Retrospective Studies
Abstract

BackgroundNeonatal mortality remains a serious global public health problem, but Sub-Saharan Africa (SSA), in particular, is largely affected. Current evidence on neonatal mortality is essential to inform programs and policies, yet there is a scarcity of information concerning neonatal mortality in our study area. Therefore, we conducted this prospective cohort study to determine the incidence and predictors of neonatal mortality at Debre Markos Referral Hospital, Northwest Ethiopia.MethodsThis institutionally-based prospective cohort study was undertaken among 513 neonates admitted to the neonatal intensive care unit of Debre Markos Referral Hospital between December 1st, 2017 and May 30th, 2018. All newborns consecutively admitted to the neonatal intensive care unit during the study period were included. An interviewer administered a questionnaire with the respective mothers. Data were entered using Epi-data™ Version 3.1 and analyzed using STATA™ Version 14. The neonatal survival time was estimated using the Kaplan-Meier survival curve, and the survival time between different categorical variables were compared using the log rank test. Both bi-variable and multivariable Cox-proportional hazard regression models were fitted to identify independent predictors of neonatal mortality.ResultsAmong a cohort of 513 neonates at Debre Markos Referral Hospital, 109 (21.3%) died during the follow-up time. The overall neonatal mortality rate was 25.8 deaths per 1, 000 neonate-days (95% CI: 21.4, 31.1). In this study, most (83.5%) of the neonatal deaths occurred in the early phase of neonatal period (ConclusionIn this study, we found a high rate of early neonatal mortality. Factors significantly linked with increased risk of neonatal mortality included: unemployed mothers, not attending ANC, not initiating exclusive breastfeeding, neonates admitted due to respiratory distress syndrome, and first minute Apgar score classified as severe.

Published
2020

16. Undernutrition among Ethiopian adults living with HIV: a meta-analysis

Author

Alebel, A, Kibret, GD, Petrucka, P, Tesema, C, Moges, NA, Wagnew, F, Asmare, G, Kumera, G, Bitew, ZW, Ketema, DB, Tiruneh, T, Melkamu, MW, Hibstie, YT, Temesgen, B, and Eshetie, S

Abstract

BackgroundMalnutrition and human immunodeficiency virus (HIV) are interlaced in a vicious cycle and worsened in low and middle-income countries. In Ethiopia, even though individuals are dually affected by both malnutrition and HIV, there is no a nationwide study showing the proportion of malnutrition among HIV-positive adults. Consequently, this review addressed the pooled burden of undernutrition among HIV-positive adults in Ethiopia.MethodsWe searched for potentially relevant studies through manual and electronic searches. An electronic search was carried out using the database of PubMed, Google Scholar, and Google for gray literature and reference lists of previous studies. A standardized data extraction checklist was used to extract the data from each original study. STATA Version 13 statistical software was used for our analysis. Descriptive summaries were presented in tables, and the quantitative result was presented in a forest plot. Heterogeneity within the included studies was examined using the Cochrane Q test statistics and I 2 test. Finally, a random-effects meta-analysis model was computed to estimate the pooled proportion of undernutrition among HIV-positive adults.ResultsAfter reviewing 418 studies, 15 studies met the inclusion criteria and were included in the meta-analysis. Findings from 15 studies revealed that the pooled percentage of undernutrition among HIV-positive adults in Ethiopia was 26% (95% CI: 22, 30%). The highest percentage of undernutrition (46.8%) was reported from Jimma University specialized hospital, whereas the lowest proportion of undernutrition (12.3%) was reported from Dilla Hospital. The subgroup analyses of this study also indicated that the percentage of undernourishment among HIV-positive adults is slightly higher in the Northern and Central parts of Ethiopia (27.5%) as compared to the Southern parts of Ethiopia (25%).ConclusionThis study noted that undernutrition among HIV-positive adults in Ethiopia was quite common. This study also revealed that undernutrition is more common among HIV-positive adults with advanced disease stage, anemia, diarrhea, CD4 count less than 200 cells/mm3, and living in rural areas. Based on our findings, we suggested that all HIV-positive adults should be assessed for nutritional status at the time of ART commencement.

Published
2020

17. Prevalence and predictors of uterine rupture among Ethiopian women: A systematic review and meta-analysis

Author

Desta, M, Amha, H, Anteneh Bishaw, K, Adane, F, Assemie, MA, Kibret, GD, and Yimer, NB

Subjects
Rural Population, Uterine Rupture, General Science & Technology, Cesarean Section, Risk Factors, Pregnancy, Prevalence, Humans, Prenatal Care, Female, Ethiopia
Abstract

BackgroundUterine rupture has a significant public health importance, contributing to 13% of maternal mortality and 74%-92% of perinatal mortality in Sub-Saharan Africa, and 36% of maternal mortality in Ethiopia. The prevalence and predictors of uterine rupture were highly variable and inconclusive across studies in the country. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence and predictor of uterine rupture in Ethiopia.MethodsThis systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009 checklist. PubMed, Cochrane Library, Google Scholar, and African Journals Online databases were searched. The Newcastle- Ottawa quality assessment tool was used for critical appraisal. I2 statistic and Egger's tests were used to assess the heterogeneity and publication bias, respectively. The random-effects model was used to estimate the pooled prevalence and odds ratios with a 95% confidence interval.ResultsSixteen studies were included, with a total of 91,784 women in the meta-analysis. The pooled prevalence of uterine rupture was 2% (95% CI: 1.99, 3.01). The highest prevalence was observed in the Amhara regional state (5%) and the lowest was in Tigray region (1%). Previous cesarean delivery (OR = 9.95, 95% CI: 3.09, 32.0), lack of antenatal care visit (OR = 8.40, 95% CI: 4.5, 15.7), rural residence (OR = 4.75, 95% CI: 1.17, 19.3), grand multiparity (OR = 4.49, 95% CI: 2.83, 7.11) and obstructed labor (OR = 6.75, 95%CI: 1.92, 23.8) were predictors of uterine rupture.ConclusionUterine rupture is still high in Ethiopia. Therefore, proper auditing on the appropriateness of cesarean section and proper labor monitoring, improving antenatal care visit, and birth preparedness and complication readiness plan are needed. Moreover, early referral and family planning utilization are the recommended interventions to reduce the burden of uterine rupture among Ethiopia women.

Published
2020

18. Incidence and predictors of loss to follow-up among HIV-positive adults in northwest Ethiopia: a retrospective cohort study.

Author

Birhanu, MY, Leshargie, CT, Alebel, A, Wagnew, F, Siferih, M, Gebre, T, Kibret, GD, Birhanu, MY, Leshargie, CT, Alebel, A, Wagnew, F, Siferih, M, Gebre, T, and Kibret, GD

Abstract

Background

Despite the rapid expansion of antiretroviral therapy services, 'loss to follow-up' is a significant public health concern globally. Loss to follow-up of individuals from ART has a countless negative impact on the treatment outcomes. There is, however, limited information about the incidence and predictors of loss to follow-up in our study area. Thus, this study aimed to determine the incidence rate and predictors of loss to follow-up among adult HIV patients on ART.

Methods

A retrospective cohort study was undertaken using 484 HIV patients between January 30, 2008, and January 26, 2018, at Debre Markos Referral Hospital. All eligible HIV patients who fulfilled the inclusion criteria were included in this study. Data were entered into Epi-data Version 4.2 and analyzed using STATATM Version 14.0 software. The Nelson-Aalen cumulative hazard estimator was used to estimate the hazard rate of loss to follow-up, and the log-rank test was used to compare the survival curve between different categorical variables. Both bivariable and multivariable Cox-proportional hazard regression models were fitted to identify predictors of LTFU.

Results

Among a cohort of 484 HIV patients at Debre Markos Referral Hospital, 84 (17.36%) were loss their ART follow-up. The overall incidence rate of loss to follow-up was 3.7 (95% CI 3.0, 5.0) per 100 adult-years. The total LTFU free time of the participants was 2294.8 person-years. In multivariable Cox-regression analysis, WHO stage IV (AHR 2.8; 95% CI 1.2, 6.2), having no cell phone (AHR 1.9; 95% CI 1.1, 3.4), and rural residence (AHR 0.6; 95% CI 0.37, 0.99) were significant predictors of loss to follow-up.

Conclusion

The incidence of loss to ART follow-up in this study was low. Having no cell phone and WHO clinical stage IV were causative predictors, and rural residence was the only protective factor of loss to follow-up. Therefore, available intervention modalities should be strengthened to

Published
2020

19. Mortality rate among HIV-positive children on ART in Northwest Ethiopia: a historical cohort study.

Author

Alebel, A, Engeda, EH, Kelkay, MM, Petrucka, P, Kibret, GD, Wagnew, F, Asmare, G, Bitew, ZW, Ketema, DB, Gedif, G, Temesgen, B, Hibstie, YT, Melkamu, MW, Eshetie, S, Alebel, A, Engeda, EH, Kelkay, MM, Petrucka, P, Kibret, GD, Wagnew, F, Asmare, G, Bitew, ZW, Ketema, DB, Gedif, G, Temesgen, B, Hibstie, YT, Melkamu, MW, and Eshetie, S

Abstract

Background

Though highly active antiretroviral therapy (HAART) has been available for more than a decade in Ethiopia, information regarding mortality rates of human immunodeficiency virus (HIV)-positive children after antiretroviral therapy antiretroviral therapy (ART) initiation is very scarce. Thus, this study intends to determine the predictors of mortality among HIV-positive children receiving ART in Amhara Region.

Methods

A multicenter facility-based historical cohort study was conducted in 538 HIV-positive children on ART from January 2012 to February 2017. We employed a standardized data extraction tool, adapted from ART entry and follow-up forms. Descriptive analyses were summarized using the Kaplan-Meier survival curve and log rank test. Then, the Cox-proportional hazard regression model was employed to estimate the hazard of death up to five-years after ART initiation. Variables with p-values ≤0.25 in bivariable analysis were candidates to the multivariable analysis. Finally, variables with p-values < 0.05 were considered as significant variables.

Results

The cohort contributed a total follow-up time of 14,600 child-months, with an overall mortality rate of 3.2 (95% CI: 2.3, 4.3) per 100 child-years. This study also indicated that HIV-infected children presenting with opportunistic infections (OIs) (AHR: 2.5, 95% CI: 1.04, 5.9), anemia (AHR: 3.1, 95% CI: 1.4, 6.7), severe immunodeficiency (AHR: 4.4, 95% CI: 1.7, 11.7), severe stunting (AHR: 3.3, 95% CI: 1.4, 8.0), severe wasting (AHR: 3.1, 95% CI: 1.3, 7.3), and advanced disease staging (III and IV) (AHR: 3.0, 95% CI: 1.2, 7.1) were at higher risk of mortality.

Conclusion

A higher rate of mortality was observed in our study as compared to previous Ethiopian studies. HIV-positive children presenting with anemia, OIs, severe immunodeficiency, advanced disease staging (III and IV), severe stunting, and severe wasting were at higher risk of mortality.

Published
2020

20. Level of self-care practice among diabetic patients in Ethiopia: a systematic review and meta-analysis.

Author

Ketema, DB, Leshargie, CT, Kibret, GD, Assemie, MA, Alamneh, AA, Kassa, GM, Alebel, A, Ketema, DB, Leshargie, CT, Kibret, GD, Assemie, MA, Alamneh, AA, Kassa, GM, and Alebel, A

Abstract

BACKGROUND:Diabetes Mellitus (DM) is increasingly become a serious global public health concern in developed and developing countries including Ethiopia. It imposes significant burden of care on the individual, health care professionals and health system. As the result, immense need of self-care behaviors in multiple domains like food choices, physical activity, foot care, and blood glucose monitoring is required. However, there is no national study on diabetic self-care practices in Ethiopia. This meta-analysis, therefore, aims to estimate the pooled level of self-care practice among individuals living with diabetes mellitus in Ethiopia. METHODS:The systematic review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline. We systematically searched the databases: PubMed /MEDLINE, EMBASE, Google Scholar, and Science Direct for studies conducted in Ethiopia about self-care practice of diabetes patients. We have included all cross-sectional studies, which were published until August 20th,2019. Data were analyzed using STATA™ version 14.1 software, and the pooled prevalence with 95% confidence intervals (CI) were presented using tables and forest plots. The presence of statistical heterogeneity within the included studies was evaluated using I-squared statistic. We used Higgins and Egger's test to identify evidence of publication bias. The random-effects meta-analysis model was employed to estimate the pooled proportion of good diabetic self-care practices. RESULTS:We included 35 studies (with 11,103 participants) in this meta-analysis. The overall pooled prevalence of good diabetes self-care behavior among diabetic patients was 49% (95% CI:43, 56%). When categorized by the major domains of diabetes self-care, the pooled estimate of dietary practice was 50% (95% CI:42, 58%), for self- monitoring of blood glucose was 28% (95% CI:19, 37%), for recommended physical activity was 49% (95% CI:38, 59%), and for diab

Published
2020

21. The effect of hourly nursing rounds on patient satisfaction at Debre Markos Referral Hospital, Northwest Ethiopia: A non-randomized controlled clinical trial

Author

Mulugeta, H, Afenigus, AD, Wagnew, F, Haile, D, Tadesse, A, Kibret, GD, Mulugeta, H, Afenigus, AD, Wagnew, F, Haile, D, Tadesse, A, and Kibret, GD

Abstract

Background: Today, implementation of hourly bedside nursing rounds is an important component of evaluating the excellence of hospitals and it is one of the strategies to increase the quality of care. Nevertheless, there has been little emphasis on the implementation of hourly nursing rounds and limited evidence is available on its effect on patient satisfaction with nursing care in Ethiopia. Hence, the objective of this study was to determine the effect of hourly nursing rounds on patient satisfaction with nursing care. Methods: A quasi-experimental nonequivalent groups study design was used to determine the effect of hourly nursing rounds on patient satisfaction with nursing care at Debre Markos Referral Hospital. A convenience sample of 104 hospitalized patients participated in this study (52 in control and 52 intervention group). The control group received the usual care in the selected units compared with the intervention group who received care with hourly nursing rounds. Patient satisfaction with nursing care scores was taken on the second and fifth days of hospitalization in both groups. Independent t-test was used to compare the statistical difference between the mean satisfaction scores of the two groups. A P-value of less than 0.05 was considered significant. Results: The result of the t-test demonstrated that patients in the intervention group had a higher satisfaction score than patients in the control group on the second day of hospitalization although it was not statistically significant (P = 0.215). However, there was a significant difference in the mean satisfaction scores on the fifth day of hospitalization (from 71.02 ± 14.37 in the control group to 79.69 ± 12.21 in the intervention group, P = 0.001). Conclusion: This study revealed that patients in the intervention group have higher satisfaction scores than the control group, providing evidence that hourly nursing rounds improve patient satisfaction with nursing care and quality of care. Therefore

Published
2020

22. Effects of maternal education on birth preparedness and complication readiness among Ethiopian pregnant women: a systematic review and meta-analysis.

Author

Ketema, DB, Leshargie, CT, Kibret, GD, Assemie, MA, Petrucka, P, Alebel, A, Ketema, DB, Leshargie, CT, Kibret, GD, Assemie, MA, Petrucka, P, and Alebel, A

Abstract

Background

Birth preparedness and complication readiness are broadly endorsed by governments and international agencies to reduce maternal and neonatal health threats in low income countries. Maternal education is broadly positioned to positively affect the mother's and her children's health and nutrition in low income countries. Thus, this systematic review and meta-analysis aims to estimate the effect of maternal education on birth preparedness and complication readiness.

Methods

This review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. We conducted an electronic based search using data bases of PubMed /MEDLINE, Science direct and google scholar. STATA™ Version 14.1 was used to analyze the data, and forest plots were used to present the findings. I2 test statistics and Egger's test were used to assess heterogeneity and publication bias. Pooled prevalence and pooled odd ratios with 95% confidence intervals were computed. Finally, Duval and Tweedie's nonparametric trim and fill analysis using random-effects meta-analysis was conducted to account for publication bias.

Results

In this meta-analysis, 20 studies involving 13,744 pregnant women meeting the inclusion criteria were included, of which 15 studies reported effects of maternal education on birth preparedness and complication readiness. Overall estimated level of birth preparedness and complication readiness was 25.2% (95% CI 20.0, 30.6%). This meta-analysis found that maternal education and level of birth preparedness and complication readiness were positively associated. Pregnant mothers whose level of education was primary and above were more likely to prepare for birth and obstetric emergencies (OR = 2.4, 95% CI: 1.9, 3.1) than non-educated mothers.

Conclusion

In Ethiopia, the proportion of women prepared for birth and related complications remained low. Maternal education has a positive effect on the level of birth

Published
2020

23. Nearly one in every six HIV-infected children lost from ART follow-up at Debre Markos Referral Hospital, Northwest Ethiopia: A 14-year retrospective follow-up study.

Author

Hibstie, YT, Kibret, GD, Talie, A, Temesgen, B, Melkamu, MW, Alebel, A, Hibstie, YT, Kibret, GD, Talie, A, Temesgen, B, Melkamu, MW, and Alebel, A

Abstract

Background

Although antiretroviral therapy (ART) significantly improves the survival status and quality of life among human immunodeficiency virus (HIV)-infected children, loss to follow-up (LTFU) from HIV-care profoundly affecting the treatment outcomes of this vulnerable population. For better interventions, up-to-date information concerning LTFU among HIV-infected children on ART is vital. However, only a few studies have been conducted in Ethiopia to address this concern. Thus, this study aims to identify the predictors of LTFU among HIV-infected children receiving ART at Debre Markos Referral Hospital.

Methods

An institution-based retrospective follow-up study was done among 408 HIV-infected children receiving ART at Debre Markos Referral Hospital between 2005 and March 15, 2019. Data were abstracted from the medical records of HIV-infected children using a standardized data abstracted checklist. We used Epi-Data Version 3.1 for data entry and Stata Version 14 for statistical analysis. The Kaplan-Meier survival curve was used to estimate the survival time. A generalized log-rank test was used to compare the survival curves of different categorical variables. Finally, both bi-variable and multivariable Cox proportional hazard regression models were used to identify the predictors of LTFU.

Results

Of 408 HIV-infected children included in the final analysis, 70 (17.1%) children were LTFU at the end of the study. The overall incidence rate of LTFU among HIV-infected children was found to be 4.5 (95%CI: 3.5-5.7) per 100-child years of observation. HIV-infected children living in rural areas (AHR: 3.2, 95%CI: 2.0-5.3), having fair or poor ART drug adherence (AHR: 2.3, 95%CI: 1.4-3.7), children started ART through test and treat approach (AHR: 2.7, 95%CI: 1.4-5.5), and children started protease inhibiter (PI)-based ART regimens (AHR: 2.2, 95%CI: 1.1-4.4) were at higher risk of LTFU.

Conclusion

This study found that one in every six HIV-inf

Published
2020

25. Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990–2015: a novel analysis from the Global Burden of Disease Study 2015

Author

Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alam, SS, Alemu, ZA, Alene, KA, Alexander, L, Ali, R, Ali, SD, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Amini, E, Ammar, W, Amo-Adjei, J, Amoako, YA, Anderson, BO, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Ärnlöv, J, Artaman, A, Asayesh, H, Assadi, R, Astatkie, A, Atey, TM, Atique, S, Atnafu, NT, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Quintanilla, BPA, Awasthi, A, Ayele, NN, Azzopardi, P, Saleem, HOB, Bärnighausen, T, Bacha, U, Badawi, A, Banerjee, A, Barac, A, Barboza, MA, Barker-Collo, SL, Barrero, LH, Basu, S, Baune, BT, Baye, K, Bayou, YT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bello, AK, Bennett, DA, Bensenor, IM, Berhane, A, Bernabé, E, Bernal, OA, Beyene, AS, Beyene, TJ, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bose, D, Brainin, M, Brauer, M, Brazinova, A, Breitborde, NJK, Brenner, H, Butt, ZA, Cárdenas, R, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Carrero, JJ, Casey, D, Caso, V, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Cecilio, P, Cercy, K, Charlson, FJ, Chen, AZ, Chew, A, Chibalabala, M, Chibueze, CE, Chisumpa, VH, Chitheer, AA, Chowdhury, R, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coggeshall, MS, Cooper, LT, Cortinovis, M, Crump, JA, Dalal, K, Danawi, H, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, De Leo, D, Del Gobbo, LC, del Pozo-Cruz, B, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dicker, D, Ding, EL, Dokova, K, Dorsey, ER, Doyle, KE, Dubey, M, Ehrenkranz, R, Ellingsen, CL, Elyazar, I, Enayati, A, Ermakov, SP, Eshrati, B, Esteghamati, A, Estep, K, Fürst, T, Faghmous, IDA, Fanuel, FBB, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Feigl, AB, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, Jahanmehr, N, Jakovljevic, MB, James, P, James, SL, Javanbakht, M, Jayaraman, SP, Jayatilleke, AU, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, SC, Jonas, JB, Juel, K, Kabir, Z, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Kasaeian, A, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kazanjan, K, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Kerbo, AA, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khan, G, Khang, Y-H, Khoja, ATA, Khonelidze, I, Khubchandani, J, Kibret, GD, Kim, D, Kim, P, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kissoon, N, Kivipelto, M, Kokubo, Y, Kolk, A, Kolte, D, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krishnaswami, S, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulkarni, VS, Kumar, GA, Kumsa, FA, Kutz, M, Kyu, HH, Lager, ACJ, Lal, A, Lal, DK, Lalloo, R, Lallukka, T, Lan, Q, Langan, SM, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Latif, AA, Lawrynowicz, AEB, Leasher, JL, Leigh, J, Leinsalu, M, Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Murray, CJL, Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alam, SS, Alemu, ZA, Alene, KA, Alexander, L, Ali, R, Ali, SD, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Amini, E, Ammar, W, Amo-Adjei, J, Amoako, YA, Anderson, BO, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Ärnlöv, J, Artaman, A, Asayesh, H, Assadi, R, Astatkie, A, Atey, TM, Atique, S, Atnafu, NT, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Quintanilla, BPA, Awasthi, A, Ayele, NN, Azzopardi, P, Saleem, HOB, Bärnighausen, T, Bacha, U, Badawi, A, Banerjee, A, Barac, A, Barboza, MA, Barker-Collo, SL, Barrero, LH, Basu, S, Baune, BT, Baye, K, Bayou, YT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bello, AK, Bennett, DA, Bensenor, IM, Berhane, A, Bernabé, E, Bernal, OA, Beyene, AS, Beyene, TJ, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bose, D, Brainin, M, Brauer, M, Brazinova, A, Breitborde, NJK, Brenner, H, Butt, ZA, Cárdenas, R, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Carrero, JJ, Casey, D, Caso, V, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Cecilio, P, Cercy, K, Charlson, FJ, Chen, AZ, Chew, A, Chibalabala, M, Chibueze, CE, Chisumpa, VH, Chitheer, AA, Chowdhury, R, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coggeshall, MS, Cooper, LT, Cortinovis, M, Crump, JA, Dalal, K, Danawi, H, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, De Leo, D, Del Gobbo, LC, del Pozo-Cruz, B, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dicker, D, Ding, EL, Dokova, K, Dorsey, ER, Doyle, KE, Dubey, M, Ehrenkranz, R, Ellingsen, CL, Elyazar, I, Enayati, A, Ermakov, SP, Eshrati, B, Esteghamati, A, Estep, K, Fürst, T, Faghmous, IDA, Fanuel, FBB, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Feigl, AB, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, Jahanmehr, N, Jakovljevic, MB, James, P, James, SL, Javanbakht, M, Jayaraman, SP, Jayatilleke, AU, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, SC, Jonas, JB, Juel, K, Kabir, Z, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Kasaeian, A, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kazanjan, K, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Kerbo, AA, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khan, G, Khang, Y-H, Khoja, ATA, Khonelidze, I, Khubchandani, J, Kibret, GD, Kim, D, Kim, P, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kissoon, N, Kivipelto, M, Kokubo, Y, Kolk, A, Kolte, D, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krishnaswami, S, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulkarni, VS, Kumar, GA, Kumsa, FA, Kutz, M, Kyu, HH, Lager, ACJ, Lal, A, Lal, DK, Lalloo, R, Lallukka, T, Lan, Q, Langan, SM, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Latif, AA, Lawrynowicz, AEB, Leasher, JL, Leigh, J, Leinsalu, M, Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, and Murray, CJL

Published
2017

26. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016

Author

Wang, H, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abera, SF, Abraha, HN, Abu-Raddad, LJ, Abu-Rmeileh, NME, Adedeji, IA, Adedoyin, RA, Adetifa, IMO, Adetokunboh, O, Afshin, A, Aggarwal, R, Agrawal, A, Agrawal, S, Kiadaliri, AA, Ahmed, MB, Aichour, AN, Aichour, I, Aichour, MTE, Aiyar, S, Akanda, S, Akinyemiju, TF, Akseer, N, Al-Eyadhy, A, Al Lami, FH, Alabed, S, Alahdab, F, Al-Aly, Z, Alam, K, Alam, N, Alasfoor, D, Aldridge, RW, Alene, KA, Alhabib, S, Ali, R, Alizadeh-Navaei, R, Aljunid, SM, Alkaabi, JM, Alkerwi, A, Alla, F, Allam, SD, Allebeck, P, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Ameh, EA, Amini, E, Ammar, W, Amoako, YA, Anber, N, Andrei, CL, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Anwari, P, Arnlov, J, Arora, M, Al, A, Aryal, KK, Asayesh, H, Asgedom, SW, Asghar, RJ, Assadi, R, Atey, TM, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Babalola, TK, Bacha, U, Badawi, A, Balakrishnan, K, Balalla, S, Barac, A, Barber, RM, Barboza, MA, Barker-Collo, SL, Barnighausen, T, Barquera, S, Barregard, L, Barrero, LH, Baune, BT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Bejot, Y, Bekele, BB, Bell, ML, Bello, AK, Bennett, DA, Bennett, JR, Bensenor, IM, Benson, J, Berhane, A, Berhe, DF, Bernabe, E, Beuran, M, Beyene, AS, Bhala, N, Bhansali, A, Bhaumik, S, Bhutta, ZA, Bikbov, B, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bjerregaard, P, Blosser, CD, Boneya, DJ, Boufous, S, Bourne, RRA, Brazinova, A, Breitborde, NJK, Brenner, H, Brugha, TS, Bukhman, G, Negesa, L, Bulto, B, Bumgarner, BR, Burch, M, Butt, ZA, Cahill, LE, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Car, M, Crdenas, R, Carpenter, DO, Carrero, JJ, Carter, A, Castaneda-Orjuela, CA, Rivas, JC, Castro, FF, Castro, RE, Catala-Lopez, F, Chen, H, Chiang, PP-C, Chibalabala, M, Chisumpa, VH, Chitheer, AA, Choi, J-YJ, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Cohen, AJ, Colquhoun, SM, Coresh, J, 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Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marczak, LB, Marks, GB, Martinez-Raga, J, Martins-Melo, FR, Massano, J, Maulik, PK, Mayosi, BM, Mazidi, M, McAlinden, C, McGarvey, ST, McGrath, JJ, Mckee, M, Mehata, S, Mehndiratta, MM, Mehta, KM, Meier, T, Mekonnen, TC, Meles, KG, Memiah, P, Memish, ZA, Mendoza, W, Mengesha, MM, Mengistie, MA, Tadese, D, Menon, MGR, Menota, BG, Mensah, GA, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Mikesell, J, Miller, TR, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Misganaw, A, Mishra, SR, Mohammad, KA, Mohammadi, A, Mohammed, KESM, Mohan, MBV, Mohanty, SK, Mokdad, AH, Assaye, AM, Mollenkopf, SK, Molokhia, M, Monasta, L, Hernandez, JCM, Montico, M, Mooney, MD, Moore, AR, Moradi-Lakeh, M, Moraga, P, Morawska, L, Velasquez, IM, Mori, R, Morrison, SD, Mruts, KB, Mueller, UO, Mullany, E, Muller, K, Venkata, G, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naidoo, KS, Nanda, L, Nangia, V, Nascimento, BR, Natarajan, 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S, Rezai, MS, Ribeiro, AL, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, A, Rubagotti, E, Ruhago, GM, Saadat, S, Sabde, YD, Sachdev, PS, Sadat, N, Safdarian, M, Safiri, SSS, Sagar, R, Sahathevan, R, Sahebkar, A, Sahraian, MA, Salama, J, Salamati, P, Salomon, JA, Salvi, SS, Samy, AM, Sanabria, JR, Sanchez-Nino, MD, Santos, IS, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Sawhney, M, Saxena, S, Saylan, MI, Schmidt, MI, Schneider, IJC, Schutte, AE, Schwebel, DC, Schwendicke, F, Seedat, S, Seid, AM, Sepanlou, SG, Servan-Mori, EE, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shamsipour, M, Shamsizadeh, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Shen, J, Shetty, BP, Shi, P, Shibuya, K, Shigematsu, M, Shiri, R, Shiue, I, Shrime, MG, Sigfusdottir, ID, Silberberg, DH, Silpakit, N, Silva, DAS, Silva, JP, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, PK, Singh, V, Sinha, DN, Skiadaresi, E, Sligar, A, Smith, DL, Sobaih, BHA, Sobngwi, E, Soneji, S, Soriano, JB, Sreeramareddy, CT, Srinivasan, V, Stathopoulou, V, Steel, N, Stein, DJ, Steiner, C, Stockl, H, Stokes, MA, Strong, M, Sufiyan, MB, Suliankatchi, RA, Sunguya, BF, Sur, PJ, Swaminathan, S, Sykes, BL, Szoeke, CEI, Tabares-Seisdedos, R, Tadakamadla, SK, Tadese, F, Tandon, N, Tanne, D, Tarajia, M, Tavakkoli, M, Taveira, N, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Temsah, M-H, Terkawi, AS, Tesema, CL, Tesssema, B, Theis, A, Thomas, N, Thompson, AH, Thomson, AJ, Thrift, AG, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Topouzis, F, Tortajada, M, Tran, BX, Trujillo, TTU, Tsilimparis, N, Tuem, KB, Tuzcu, EM, Tyrovolas, S, Ukwaja, KN, Undurraga, EA, Uthman, OA, Uzochukwu, BSC, van Boven, JFM, Varakin, YY, Varughese, S, Vasankari, T, Vasconcelos, AMN, Venketasubramanian, N, Vidavalur, R, Violante, FS, Vishnu, A, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Waid, JL, Wakayo, T, Wang, Y-P, Weichenthal, S, Weiderpass, E, Weintraub, RG, Werdecker, A, Wesana, J, Wijeratne, T, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Workicho, A, Workie, SB, Xavier, D, Xu, G, Yaghoubi, M, Yakob, B, Yalew, AZ, Yan, LL, Yano, Y, Yaseri, M, Ye, P, Yimam, HH, Yip, P, Yirsaw, BD, Yonemoto, N, Yoon, S-J, Yotebieng, M, Younis, MZ, Zaidi, Z, Zaki, MES, Zeeb, H, Zenebe, ZM, Zerfu, TA, Zhang, AL, Zhang, X, Zodpey, S, Zuhlke, LJ, Lopez, AD, and Murray, CJL

Published
2017

27. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author

Lozano, Rafael, Fullman, Nancy, Abate, Degu, 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, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, 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, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton SKH, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Josip, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carter, Austin, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Causey, Kate, Çavlin, Alanur, Cercy, Kelly M, Cerin, Ester, Chaiah, Yazan, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Claßen, Thomas Khaled Dwayne, Cohen, Aaron J, Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I, Daryani, Ahmad, Das, Siddharth K, Das Gupta, Rajat, das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, de Courten, Barbora, De Leo, Diego, De Neve, Jan-Walter, De Steur, Hans, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Douwes-Schultz, Dirk, Driscoll, Tim Robert, Duan, Leilei, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, Eldrenkamp, Erika, El-Khatib, Ziad, Elyazar, Iqbal RF, Enayati, Ahmadali, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhar, Mahdi, Fakhim, Hamed, Fanzo, Jessica, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Farid, Talha A, Farinha, Carla Sofia e Sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Farzam, Hossein, Fazaeli, Ali Akbar, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fekadu, Wubalem, Feldman, Rachel, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Finger, Jonas David, Fischer, Florian, Fitzmaurice, Christina, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fukutaki, Kai, Fuller, John E, Fürst, Thomas, Furtado, João M, Gakidou, Emmanuela, Gallus, Silvano, Gankpe, Fortune Gbetoho, Gansevoort, Ron T, Garcia, Ana Cristina, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gardner, William M, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M, Geramo, Yilma Chisha Dea, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goldberg, Ellen M, Goli, Srinivas, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gorman, Taren M, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Griswold, Max G, Grosso, Giuseppe, Gugnani, Harish Chander C, Guillemin, Francis, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Ha, Giang Hai, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Haghparast Bidgoli, Hassan, Hagos, Tekleberhan B, Haile, Michael Tamene, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Hankey, Graeme J, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Behzad, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T, Híjar, Martha, Hoek, Hans W, Hoffman, Daniel J, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Horita, Nobuyuki, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Huang, John J, Hughes, Caitlyn, Huynh, Chantal K, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ivers, Rebecca Q, Izadi, Neda, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, Jalu, Moti Tolera, Jamal, Amr A, James, Spencer L, Jassal, Simerjot K, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Johnson, Catherine O, Johnson, Sarah C, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, K, Madhanraj, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kahssay, Molla, Kalani, Rizwan, Kapil, Umesh, Karami, Manoochehr, Karami Matin, Behzad, Karanikolos, Marina, Karimi, Narges, Karimi, Seyed M, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, KC, Prakash, Kebede, Seifu, Keiyoro, Peter Njenga, Kemmer, Laura, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, Khatony, Alireza, Khazaeipour, Zahra, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A, Kiarie, Helen W, Kibret, Getiye D, Kiirithio, Daniel N, Kim, Daniel, Kim, Jun Y, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W, Kinfu, Yohannes, Kinra, Sanjay, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kissoon, Niranjan, Kivimäki, Mika, Kocarnik, Jonathan M, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A, Kosek, Margaret N, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kristopher J, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kudom, Andreas A, Kulikoff, Xie Rachel, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lagat, Abraham K, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lami, Faris Hasan, Lamichhane, Prabhat, Lan, Qing, Lang, Justin J, Lansingh, Van C, Lansky, Sonia, Larson, Heidi J, Larsson, Anders O, Laryea, Dennis Odai, Lassi, Zohra S, Latifi, Arman, Lau, Kathryn Mei-Ming, Laxmaiah, Avula, Lazarus, Jeffrey V, Leasher, Janet L, Lebedev, Georgy, Ledesma, Jorge R, Lee, James B, Lee, Paul H, Leever, Andrew T, Leigh, James, Leinsalu, Mall, Leshargie, Cheru Tesema, Leung, Janni, Lewycka, Sonia, Li, Shanshan, Li, Xiaohong, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Lee-Ling, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lucchesi, Lydia R, Lyons, Ronan A, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Madotto, Fabiana, Maghavani, Dhaval P, Magis-Rodriguez, Carlos, Mahotra, Narayan Bahadur, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Mangalam, Srikanth, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, Martin, Randall V, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, Mashamba-Thompson, Tivani Phosa, 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Subjects
GENDER-DIFFERENCES, SUICIDE, Medicine (all), Burden of Disease Study 2017, SDG, CONSUMPTION, 11 Medical And Health Sciences, GBD, Sustainable Development Goals, PREVENTION, ALCOHOL-USE, CARDIOVASCULAR-DISEASE, SMOKING PREVALENCE, General & Internal Medicine, factors risk, Medicine and Health Sciences, Human medicine, CESSATION, PERSPECTIVE, TRANSITION
Abstract

Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

Published
2018

28. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author

Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A., Adebayo, Oladimeji, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. G. A., Awasthi, Ashish, Quintattilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S., Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Ballesteros, Katherine E., Banach, Maciej, Banerjee, Kajori, Bannick, Marlena S., Banoub, Joseph Adel Mattar, Barboza, Miguel A., Barker-Collo, Suzanne Lyu, Barnighausen, Till Winfried, Barquera, Simon, Barrero, Lope, Bassat, Quique, Base, Sanjay, Baune, Bernhard T., Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Beth, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Mcysam, Bejot, Yannick, Bekele, Bayu Begashaw, Belacliew, Abate Bekele, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Berman, Adam F., Bernabe, Eduardo, Bernstein, Robert S., Bertolacci, Gregory J., Beuran, Mircea, Beyranvand, Tina, Bhalla, Ashish, Bhattarai, Suraj, Bhaumik, Sounayadeeep, Bhutta, Zulfiqar A., Biadgo, Belete, Biehl, Molly H., Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shandaat, Bisanzio, Donal, Biswas, Tuhin, Blacker, Brigitte F., Basara, Berrak Bora, Borschmann, Rohan, Bosetti, Cristina, Bozorgmehr, Kayvan, Brady, Oliver J., Brant, Luisa C., Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J. K., Brenner, Hermann, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Busse, Reinhard, Butt, Zahid A., Callender, Charlton S. K. H., Campos-Nonato, Ismael R., Rincon, Julio Cesar Canapuzano, Cano, Jorge, Car, Mate, Cardenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carter, Austin, Carvalho, Felix, Castaneda-Orjuela, Carlos A., Rivas, Jacqueline Castillo, Castle, Chris D., Castro, Clara, Castro, Franz, Catala-Lopez, Ferran, Cerin, Ester, Chaiah, Yazan, Chang, Jung -Chen, Chanson, Fiona J., Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheet, Abdulaal, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chiang, Sheng-Chia, Cicuttini, Flavia M., Ciobanu, Liliana G., Cirillo, Massimo, Cohen, Aaron J., Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Cowie, Benjamin C., Criqui, Michael H., Cromwell, Elizabeth A., Crowe, Christopher Stephen, Crump, John A., Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I., Daryani, Ahmad, Das, Siddharth K., Das Gupta, Rajat, Das Neves, Jose, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C., Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De La Hoz, Fernando Pio, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T., Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Baleen Betsu, Denova-Gutierrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Jarlais, Don C. Des, Dessie, Getenet Ayalew, Dey, Subhojit, Dhannaratne, Samath D., Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L., Dirac, M. Ashworth, Djalalinia, Shirin, Dokova, Klara, Ter Doku, David, Donnelly, Christl A., Dorsey, E. Ray, Doshi, Pratik P., Douwes-Schultz, Dirk, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B., Duraes, Andre R., Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edessa, Dumessa, Edvardsson, David, Eggen, Anne Elise, El Bcheraoui, Charbel, Zaki, Maysaa El Sayed, El-Khatib, Ziad, Elkout, Hajer, Eltinsel, Christian Lycke, Endres, Matthias, Endries, Aman Yesuf, Er, Benjamin, Erskine, Holly E., Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Fakhar, Mahdi, Fakhim, Hamed, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Faninha, Carla Sofia E. Sa, Faro, Andre, Farvid, Maryam S., Farzadfar, Farshad, Farzaei, Mohammad Hosein, Feign, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Eereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C., Ferrari, Alice J., Feyissa, Garumma Tolu, Filip, Irina, Finegold, Samuel, Fischer, Florian, Eitzmaurice, Christina, Foigt, Nataliya A., Foreman, Kyle J., Fornari, Carla, Frank, Tahvi D., Fukumoto, Takeshi, Fuller, John E., Fullman, Nancy, Furst, Thomas, Furtado, Joao M., Futran, Neal D., Gallus, Silvano, Garcia-Basteiro, Alberto L., Garcia-Gordillo, Miguel A., Gardner, William M., Gebre, Abadi Kahsu, Gebrehiwol, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijinse, Johanna M., Genova-Maleras, Ricard, Geramo, Yilma Chisha Dea, Gething, Peter W., Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Falavarjani, Khalil Ghasemi, Ghasemi-Kasman, Maryam, Ghimire, Mamata, Gibney, Katherine B., Gill, Paramjit Singh, Gill, Tiffany K., Gillum, Richard F., Ginawi, Ibrahim Abdelmageed, Giroud, Maurice, Giussani, Giorgia, Goenka, Shifalika, Goldberg, Ellen M., Goli, Srinivas, Gomez-Dantes, Hector, Gona, Philimon N., Gopalani, Sameer Vali, Gorman, Taren M., Goto, Atsushi, Goulart, Alessandra C., Gnedovskaya, Elena V., Grada, Aymara, Grosso, Giuseppe, Gugnani, Hanish Chander, Guimaraes, Andre Luiz Sena, Gun, Nailing, Gupta, Prakash C., Gupta, Rahid, Gupta, Rajenv, Gupta, Tanush, Gutierrez, Reyna Alma, Gyawali, Bishal, Haagsma, Juanita A., Hafezi-Nejad, Nima, Hagos, Tekleberhan B., Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randall R., Hamidi, Sinner, Handal, Meads J., Hankey, Graeme J., Harb, Hilda L., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid, Havmoeller, Rasmus, Hay, Roderick J., Hay, Simon I., He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Henry, Nathaniel J., Herteliu, Claudiu, Heydarpour, Fatemeh, Heydarpour, Pouria, Heydarpour, Sousan, Hibstu, Desalegn Tsegaw, Hoek, Hans W., Hole, Michael K., Red, Enayatollah Homaie, Hoogar, Praveen, Hosgood, H. Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J., Hoy, Damian C., Hsiao, Thomas, Hu, Guoqing, Huang, John J., Husseini, Abdullatif, Hussen, Mohammedaman Mama, Hutfless, Susan, Idrisov, Bulat, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Nazrul, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jacobsen, Kathryn H., Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovlievic, Mihajlo, Jalu, Moti Tolera, James, Spencer L., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jenkins, Kathy J., Jha, Ravi Prakash, Jha, Vivekanand, Johnson, Catherine O., Johnson, Sarah C., Jonas, Jost B., Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jurisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Karami, Manoochehr, Matin, Behzad Karami, Karch, Andre, Karema, Corine, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H., Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, Kefale, Adane Teshome, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah T., Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A., Kibret, Getiye D., Kidanemariam, Zelalem Teklemariam, Kiirithio, Daniel N., Kim, Daniel, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kivimaki, Mika, Knudsen, Ann Kristin Skrindo, Kocarnik, Jonathan M., Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A., Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael A., Krishan, Kewal, Defo, Barthelemy Kuate, Bicer, Burcu Kinuk, Kumar, G. Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J., Kuzin, Igor, Kyu, Hmwe Hmwe, Lad, Deepesh P., Lad, Sheetal D., Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lam, Jennifer O., Lami, Faris Hasan, Van Lansingh, C., Lansky, Sonia, Larson, Heidi J., Latifi, Amman, Lau, Kathryn Mei-Ming, Lazarus, Jeffrey V., Lebedev, Georgy, Lee, Paul H., Leigh, James, Leili, Mostafa, Leshargie, Cheru Tesema, Li, Shanshan, Li, Yichong, Liang, Juan, Lim, Lee-Ling, Lim, Stephen S., Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Lansdale, Chris, Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lunevicius, Raimundas, Ma, Stefan, Macarayan, Erlyn Rachelle King, Mackay, Mark T., MacLachlan, Jennifer H., Maddison, Emilie R., Nadotto, Fabiana, Abd El Razek, Hassan Magdy, Abd El Razek, Muhammed Magdy, Maghavani, Dhaval P., Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C., Marcenes, Wagner, Marczak, Laurie, Marks, Ashley, Marks, Guy B., Martinez, Gabriel, Martins-Melo, Francisco Rogerlandio, Martopullo, Ira, Marz, Winfried, Marron, Melvin B., Masci, Joseph R., Lylassenburg, Benjamin Ballard, Mathur, Manu Raj, Mathur, Prashant, Matzopoulos, Richard, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Cohn, McGrath, John J., McKee, Martin, McMahon, Brian J., Mehata, Suiiesh, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Mekonnen, Tefera C., 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., Meshovic, Tbmislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I., Miller, Ted R., Katherine, Molly, Petrie, Miller, Mini, G. K., Mirabi, Parvaneh, Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke Temesgen, Mitiku, Habtamu, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammad, Moslem, Mohammadifard, Noushin, Mohammed, A. Mohammed, Mohammed, Shafiu, Mohan, Viswanathan, Mokdad, Ali H., Molokhia, Mariam, Monasta, Lorenzo, Moradi, Ghobad, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Velasquez, Ilais Moreno, Morgado-Da-Costa, Joana, Morrison, Shane Douglas, Moschos, Marilita M., Mouodi, Simin, Mousavi, Seyyed Meysam, Muchie, Kindie Eentahun, Mueller, Ulrich Otto, Mukhopadhyay, Satinath, Muller, Kate, Mumford, John Everett, Musa, Jonah, Musa, Kamand Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nachega, Jean B., Nagel, Gabriele, Naheed, Aliya, Nahvijou, Azin, Naik, Gunidatta, Nair, Sanjeev, Najafi, Farid, Naldi, Luigi, Nam, Hae Sung, Nangia, Vinay, Nansseu, Jobert Richie, Nascirnento, Bruno Ramos, Natarajan, Gopalakrishnan, Nearnati, Nahid, Negoi, Ionut, Negoi, Ruxcandra Irina, Nettpane, Subas, Newton, Charles R. J., Ngalesoni, Frida N., Ngunjiri, Josephine W., Anh Quynh Nguyen, Nguyen, Grant, Ha Thu Nguyen, Luong Thanh Nguyen, Long Hoang Nguyen, Nguyen, Minh, Trang Huyen Nguyen, Nichols, Emma, Ningnun, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nixon, Molly R., Nolutshungu, Nomonde, Nomura, Shhhei, Norhelin, Ole F., Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Shiadeh, Malihe Nourollahpour, Nowroozi, Mohammad Reza, Nyasulu, Peter S., Odell, Christopher M., Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T., Olivares, Pedro R., Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L., Ong, Sok King Sk, Oren, Eyal, Orpana, Heather M., Ortiz, Alberto, Ortiz, Justin R., Otstavnov, Stanislav S., Overland, Simon, Owolabi, Mayowa Ojo, Ozdemir, Raziye, Mahesh, P. 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S., Robinson, Stephen R., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Rothenbacher, Dietrich, Roy, Ambuj, Rubagotti, Enrico, Sachdev, Perminder S., Saddik, Basema, Sadeghi, Ehsan, Safari, Hosein, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Salam, Nasir, Salama, Joseph S., Salamati, Payman, De Saldanha, Raphael Freitas, Saleem, Zikria, Salimi, Yahya, Salvi, Sundeep Santosh, Salz, Inbal, Sambala, Evanson Zondani, Samy, Abdatiah M., Sanabria, Juan, Sanchez-Nino, Maria Dolores, Santomauro, Damian Francesco, Santos, Itamar S., Santos, Joao Vasco, Milicevic, Milena M. Santric, Jose, Bruno Piassi Sao, Sarker, Abdur Razzaque, Sarmiento-Suarez, Rodrigo, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R., Sawhney, Monika, Saxena, Sonia, Sayyah, Mehdi, Schaeffher, Elke, Schmidt, Maria Ines, Schneider, Ione J. 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Subjects
Adult, Male, Adolescent, national age-sex-specific mortality, UNITED-STATES, Global Health, Socioeconomic Factor, Global Burden of Disease, GBD, causes of death, Young Adult, Age Distribution, Life Expectancy, General & Internal Medicine, Cause of Death, PUBLIC-HEALTH PROBLEM, mortality, 282 causes global burden of disease, Sex Distribution, Child, Aged, Aged, 80 and over, BARRIERS, DEMENTIA, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, TRENDS, PREVENTION, PREVALENCE, ALZHEIMERS-DISEASE, INDIVIDUALS, 3121 General medicine, internal medicine and other clinical medicine, Child, Preschool, REGISTRATION, Female, Human medicine, Human
Abstract

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.

Published
2018

29. 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, 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Purcell, C, Purwar, M, Rahman, S, Rai, R, Ranabhat, C, Rawaf, D, Ray, S, Reiner, R, Renzaho, A, Riahi, S, Rios-Blancas, M, Roba, K, Roberts, N, Ruhago, G, Sabde, Y, Sahraian, M, Saldanha, R, Salomon, J, Sambala, E, Samy, A, Sanchez-Niño, M, Santric Milicevic, M, Sao Jose, B, Sarker, A, Sawant, A, Schneider, I, Schwebel, D, Sepanlou, S, Shackelford, K, Shaheen, A, Shaikh, M, Shakir, R, Shukla, S, Sibai, A, Siddiqi, T, Sigfusdottir, I, Silva, D, Silva, J, Silveira, D, Singam, N, Singh, J, Singh, N, Sinha, D, Soares Filho, A, Sobaih, B, Soriano, J, Soyiri, I, Sreeramareddy, C, Starodubov, V, Stewart, L, Stokes, M, Subart, M, Sufiyan, M, Sunguya, B, Sur, P, Sykes, B, Sylaja, P, Sylte, D, Szoeke, C, Tabb, K, Tadakamadla, S, Tassew, A, Tassew, S, Tawye, N, Tekalign, T, Tekle, M, Temsah, M, Teshale, M, Thankappan, K, Thomson, A, To, Q, Torre, A, Tovani-Palone, M, Tran, B, Tran, K, Tripathy, S, Truelsen, T, Truong, N, Tsadik, A, Ukwaja, K, Uthman, O, Uzun, S, Valdez, P, Vasankari, T, 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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

30. 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, 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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, 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Agrawal, Anurag, Agrawal, Sutapa, Ahmad Kiadaliri, Aliasghar, Aichour, Miloud Taki Eddine, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi F., Akseer, Nadia, Al Lami, Faris Hasan, Alahdab, Fare, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Alasfoor, Deena, Albittar, Mohammed I., Alene, Kefyalew Addi, Al-Eyadhy, Ayman, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed M., Alkerwi, Ala'a, Alla, Françoi, Allebeck, Peter, Allen, Christine, Alomari, Mahmoud A., Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A., Alvis-Guzman, Nelson, Amare, Azmeraw T., Amenu, Kebede, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andrei, Catalina Liliana, Androudi, Sofia, Antonio, Carl Abelardo T., Araújo, Valdelaine E.M., Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Ashebir, Mengistu Mitiku, Asseffa, Netsanet Abera, Atey, Tesfay Mehari, Atre, Sachin R., Atteraya, Madhu S., 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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

31. Global Disparities of Cancer and Its Projected Burden in 2050.

Author

Bizuayehu HM, Ahmed KY, Kibret GD, Dadi AF, Belachew SA, Bagade T, Tegegne TK, Venchiarutti RL, Kibret KT, Hailegebireal AH, Assefa Y, Khan MN, Abajobir A, Alene KA, Mengesha Z, Erku D, Enquobahrie DA, Minas TZ, Misgan E, and Ross AG

Subjects
Humans, Male, Cross-Sectional Studies, Female, Middle Aged, Aged, Adult, Incidence, Prevalence, Health Status Disparities, Young Adult, Adolescent, Aged, 80 and over, SARS-CoV-2, Neoplasms epidemiology, Global Health statistics & numerical data, COVID-19 epidemiology
Abstract

Importance: Cancer prevention and care efforts have been challenged by the COVID-19 pandemic and armed conflicts, resulting in a decline in the global Human Development Index (HDI), particularly in low- and middle-income countries. These challenges and subsequent shifts in health care priorities underscore the need to continuously monitor cancer outcome disparities and statistics globally to ensure delivery of equitable and optimal cancer prevention and care in uncertain times., Objective: To measure the global burden of 36 cancers in 2022 by sex, age, and geographic location and to project future trends by 2050., Design, Setting, and Participants: This cross-sectional study used population-based data from 2022 in 185 countries and territories were obtained from the Global Cancer Observatory database. Data extraction and analysis were carried out in April 2024., Main Outcomes and Measures: Counts, rates, prevalence, mortality to incidence ratios (MIRs), and demography-based projections were used to characterize current and future cancer burden., Results: This population-based study included 36 cancer types from 185 countries and territories. By 2050, 35.3 million cancer cases worldwide are expected, a 76.6% increase from the 2022 estimate of 20 million. Similarly, 18.5 million cancer deaths are projected by 2050, an 89.7% increase from the 2022 estimate of 9.7 million. Cancer cases and deaths are projected to nearly triple in low-HDI countries by 2050, compared to a moderate increase in very high-HDI countries (142.1% vs 41.7% for cancer cases and 146.1% vs 56.8% for cancer deaths). Males had a higher incidence and greater number of deaths in 2022 than females, with this disparity projected to widen by up to 16.0% in 2050. In 2022, the MIR for all cancers was 46.6%, with higher MIRs observed for pancreatic cancer (89.4%), among males (51.7%), among those aged 75 years or older (64.3%), in low-HDI countries (69.9%), and in the African region (67.2%)., Conclusions and Relevance: In this cross-sectional study based on data from 2022, cancer disparities were evident across HDI, geographic regions, age, and sex, with further widening projected by 2050. These findings suggest that strengthening access to and quality of health care, including universal health insurance coverage, is key to providing evidence-based cancer prevention, diagnostics, and care.

Published
2024
Full Text
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32. Spatiotemporal patterns and factors contributing to neonatal mortality in Ethiopia: Data from EDHS 2000 to 2019.

Author

Kibret GD, Bizuayehu HM, Dadi AF, Amsalu E, Alemu AA, Hassen TA, Leshargie CT, Bore MG, Kassa ZY, Ketema DB, Shifa JE, Alebel A, and Ahmed KY

Subjects
Humans, Ethiopia epidemiology, Infant, Newborn, Female, Infant, Male, Adult, Health Surveys, Young Adult, Risk Factors, Spatio-Temporal Analysis, Adolescent, Pregnancy, Infant Mortality trends
Abstract

Background: Although Ethiopia has substantial improvements in various health indicators such as maternal and child mortality, the burden of neonatal mortality remains high. Between 2016 and 2019, neonatal mortality increased from 29 deaths per 1,000 live births to 33 deaths per 1,000 live births. This study aimed to explore the spatial patterns and factors contributing to neonatal mortality in Ethiopia., Methods: Data from the Ethiopian Demographic and Health Surveys (EDHS) for the years 2000, 2005, 2011, 2016, and 2019 were analyzed. The EDHS sampling design uses a two-stage cluster sampling technique, considering census enumeration areas as primary sampling units and households as secondary sampling units. We used the Spatial Scan analysis in SaTScan and Getis-Ord Gi* statistic in Geographic Information System (GIS), to analyse the spatiotemporal patterns of neonatal mortality. Maternal, newborn and health service-related factors contributing to neonatal mortality were also analyzed using a multilevel logistic regression model. Adjusted Odds Rios (AOR) with corresponding 95% CI were presented as a measure of association and a P-value of 0.05 was used to declare statistical significance., Results: During the initial three consecutive surveys, there was a consistent pattern of hot spot clusters in the Amhara and Benshangul Gumuz regions, along with certain parts of the Oromia region. However, in later surveys, these clusters shifted to the eastern parts of the country, notably including the Somali region. Early initiation of breast feeding was associated with reduced chances of neonatal death (Adjusted Odds Ratio [AOR]) = 0.27; 95% Confidence Interval [CI]: 0.23, 0.32). Neonates born at home (AOR = 1.46; 95% CI: 1.16, 1.82) and male babies had a higher likelihood of mortality during the neonatal period compared to their counterparts (AOR = 1.36; 95% CI: 1.24, 1.51). The odds of neonatal mortality increased with the number of children a mother had ever given birth to (AOR = 1.36; 95% CI: 1.24, 1.51). In contrast, longer birth intervals were associated with a reduced risk of neonatal mortality (AOR = 0.76; 95% CI: 0.68, 0.83)., Conclusion: The central southern, central-western, north-western, and northern parts of Ethiopia had most of the neonatal death clusters in the first three rounds of DHS while eastern Ethiopia had the highest neonatal mortality clusters in the latest two surveys. Our results underscore the importance for policymakers and health administrators to reassess intervention approaches and reallocate resources to regions identified as hot spots for neonatal mortality. Enhancing the initiation of breastfeeding within the first hour of birth would improve newborn survival rates. Special attention and care need to be given to babies born of smaller sizes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kibret et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2024
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33. Intimate partner violence and childhood health outcomes in 37 sub-Saharan African countries: an analysis of demographic health survey data from 2011 to 2022.

Author

Dadi AF, Ahmed KY, Berhane Y, Bizuayehu HM, Tesema GA, Hassen TA, Kibret GD, Ketema DB, Bore MG, Belachew SA, Amsalu E, Nhassengo S, Shifti DM, Seid A, Mesfin YM, Tegegne TK, Odo DB, Kassa ZY, Thapa S, Kidane EG, Desyibelew HD, Misganaw A, Zeleke BM, Bolarinwa OA, and Ross AG

Subjects
Humans, Africa South of the Sahara epidemiology, Female, Child, Preschool, Infant, Adult, Male, Adolescent, Young Adult, Mothers statistics & numerical data, Mothers psychology, Intimate Partner Violence statistics & numerical data, Health Surveys, Child Health statistics & numerical data, Child Mortality
Abstract

Background: Understanding the contribution of intimate partner violence (IPV) to childhood health outcomes (eg, morbidity and mortality) is crucial for improving child survival in sub-Saharan Africa. This comprehensive study aimed to explore the associations between maternal exposure to physical, sexual, or emotional violence and adverse childhood health outcomes in sub-Saharan Africa., Methods: We analysed Demographic Health Survey datasets from 37 sub-Saharan African countries from 2011 to 2022. A generalised linear mixed model was used to examine the associations between maternal physical violence, sexual violence, or emotional violence, and early childhood health outcomes (eg, acute respiratory infection, diarrhoea, undernutrition, and child mortality). A random effects meta-analysis was used to calculate pooled odds ratios (ORs) for adverse childhood health outcomes. The odds of undernutrition and mortality were 55% and 58% higher among children younger than 5 years born to mothers who were exposed to physical and sexual violence, respectively., Findings: 238 060 children younger than 5 years were included. Children whose mothers experienced physical violence (adjusted OR 1·33, 95% CI 1·29-1·42), sexual violence (1·47, 1·34-1·62), emotional violence (1·39, 1·32-1·47), or a combination of emotional and sexual violence (1·64, 1·20-2·22), or a combination of all the three forms of violence (1·88, 1·62-2·18) were associated with an increased odds of developing diarrhoeal disease. Similarly, children whose mothers experienced physical violence (1·43, 1·28-1·59), sexual violence (1·47, 1·34-1·62), emotional violence (1·39, 1·32-1·47), or a combination of emotional and sexual violence (1·48, 1·16-1·89), or a combination of all three forms of violence (1·66, 1·47-1·88) were positively associated with symptoms of acute respiratory infection., Interpretation: We found a strong link between maternal exposure to IPV and health outcomes for children younger than 5 years in sub-Saharan Africa, with minor variations across countries. To address childhood morbidity and mortality attributed to IPV, interventions need to be tailored for specific countries. Burkina Faso, Burundi, Chad, Comoros, Gabon, Liberia, Nigeria, Sierra Leone, South Africa, and Uganda should be priority nations., Funding: None., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

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2024
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34. Burden of 30 cancers among men: Global statistics in 2022 and projections for 2050 using population-based estimates.

Author

Bizuayehu HM, Dadi AF, Ahmed KY, Tegegne TK, Hassen TA, Kibret GD, Ketema DB, Bore MG, Thapa S, Odo DB, Kassa ZY, Shifti DM, Amsalu E, Sarich P, Venchiarutti RL, Melaku YA, Kibret KT, Habte A, Mefsin YM, Seid A, and Belachew SA

Subjects
Humans, Male, Aged, Middle Aged, Incidence, Adult, Young Adult, Aged, 80 and over, Risk Factors, Adolescent, Prevalence, Survival Rate, Neoplasms epidemiology, Neoplasms mortality, Global Health statistics & numerical data
Abstract

Background: Men exhibit higher prevalence of modifiable risk factors, such as smoking and alcohol consumption, leading to greater cancer incidence and lower survival rates. Comprehensive evidence on global cancer burden among men, including disparities by age group and country, is sparse. To address this, the authors analyzed 30 cancer types among men in 2022, with projections estimated for 2050., Methods: The 2022 GLOBOCAN estimates were used to describe cancer statistics for men in 185 countries/territories worldwide. Mortality-to-incidence ratios (MIRs) were calculated by dividing age-standardized mortality rates by incidence rates., Results: In 2022, a high MIR (indicating poor survival) was observed among older men (aged 65 years and older; 61%) for rare cancer types (pancreatic cancer, 91%) and in countries with low a Human Development Index (HDI; 74%). Between 2022 and 2050, cancer cases are projected to increase from 10.3 million to 19 million (≥84%). Deaths are projected to increase from 5.4 million to 10.5 million (≥93%), with a greater than two-fold increase among men aged 65 years and older (≥117%) and for low-HDI and medium-HDI countries/territories (≥160%). Cancer cases and deaths are projected to increase among working-age groups (≥39%) and very-high-HDI countries/territories (≥50%)., Conclusions: Substantial disparities in cancer cases and deaths were observed among men in 2022, and these are projected to widen by 2050. Strengthening health infrastructure, enhancing workforce quality and access, fostering national and international collaborations, and promoting universal health coverage are crucial to reducing cancer disparities and ensuring cancer equity among men globally., (© 2024 The Author(s). Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

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2024
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35. Trends and social determinants of the obesity epidemic among reproductive-age women in ten Asian countries.

Author

Thapa S, Ahmed KY, Bizuayehu HM, Huda MM, Chalise B, Bore MG, Belachew SA, Hassen TA, Amsalu E, Shifti DM, Seid A, Mesfin YM, Tegegne TK, Dadi AF, Odo DB, Kibret GD, Ketema DB, Kassa ZY, Anyasodor AE, Mahmood S, Astawesegn FH, and Ross AG

Subjects
Humans, Female, Adult, Middle Aged, Adolescent, Young Adult, Cross-Sectional Studies, Risk Factors, Asia epidemiology, Prevalence, Social Determinants of Health, Socioeconomic Factors, Health Surveys, Epidemics, Obesity epidemiology
Abstract

The rapid epidemiological transition in Asian countries, resulting from the rising trend of urbanisation and lifestyle changes, is associated with an increasing risk of obesity in women of reproductive age. This is the first study to investigate the trends and population-attributable fraction (PAF) of obesity, and the interaction effects of education and wealth on obesity among reproductive-age women aged 15-49 years in ten Asian countries. This cross-sectional study examined the most recent (2000 to 2022) Demographic and Health Surveys (DHS) data from ten Central and Southeast Asian countries. Multilevel multinomial logistic regression models were used to compute odds ratios (ORs). PAFs adjusted for communality were calculated using adjusted ORs and prevalence estimates for each risk factor. This study included a weighted sample of 743,494 reproductive-age women. All the countries showed an increasing trend for obesity and a decreasing trend for underweight, except for the Maldives. The highest PAFs of obesity were associated with women who were married (PAF = 22.2%; 95% CI 22.1, 22.4), aged 35-49 years (PAF = 16.4%; 95% CI 15.5, 17.1), resided in wealthy households (PAF = 14.5%; 95% CI 14.4, 14.5), watched television regularly (PAF = 12.5%; 95% CI 12.1, 12.8), and lived in urban areas (PAF = 7.8%; 95% CI 7.7, 8.0). The combined PAF showed that these five risk factors were associated with 73.3% (95% CI 71.8, 74.9) of obesity among reproductive-age women. Interaction analysis between women's education and household wealth revealed that having a secondary or higher level of education and residing in a wealthier household was associated with a lower risk of obesity (OR = 0.71, 95% CI 0.66, 0.76). The findings of this study suggest that, in order to address the rising rate of obesity among women in Asian countries, education and lifestyle modifications in urban areas should be a priority. Pakistan and the Maldives need to be a priority given the rapidly increasing trends in obesity and underweight subpopulations in their respective countries., (© 2024. The Author(s).)

Published
2024
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36. Individual- and community-level predictors of healthcare-seeking behaviour for acute respiratory tract infections among children under five in 29 low-and middle-income countries: a multilevel analysis.

Author

Ketema DB, Dadi AF, Hassen TA, Kibret GD, Kassa ZY, Amsalu E, Alemu AA, Shifa JE, Alebel A, Leshargie CT, Bore MG, Bizuayehu HM, and Ahmed KY

Abstract

Objectives: This study aimed to identify the individual- and community-level determinants of mothers' healthcare-seeking behaviour for children under the age of 5 years with acute respiratory infection (ARI) symptoms in low-and middle-income countries (LMICs)., Study Design: Nationally representative Demographic and Health Survey datasets from 29 LMICs were used., Methods: The study included 16,893 children aged under 5 years with ARI symptoms in the 2 weeks prior to the survey. A multilevel logistic regression model was used to examine associations between individual- and community-level factors with health-seeking behaviour for ARIs. The adjusted odds ratio (AOR) along with 95% confidence intervals (CIs) were reported as a measure of association., Results: The overall prevalence of healthcare-seeking behaviour for ARIs among children under 5 years in LMICs was 58.83% (95% CI: 58.08, 59.57). Findings showed that mothers with primary or higher education (AOR = 1.20; 95% CI: 1.08, 1.33), and those residing in rich households (AOR = 1.32; 95% CI: 1.18, 1.48), attending antenatal care (ANC) visits (AOR = 1.53; 95% CI: 1.31, 1.79) and delivering at a healthcare facility (AOR = 1.28; 95% CI: 1.16, 1.41) were more likely to seek healthcare for ARIs. A higher level of community maternal education (AOR = 1.44; 95% CI: 1.24, 1.68) was positively associated with seeking healthcare for ARIs, while a higher level of community poverty (AOR = 0.83; 95% CI: 0.72, 0.96) was negatively associated with healthcare seeking for ARIs., Conclusions: This study revealed that mothers' healthcare-seeking behaviour for ARIs was closely linked to modifiable risk factors, including maternal education, household wealth, use of maternal health services (e.g., ANC), as well as community poverty and literacy levels. Future interventions should consider these modifiable risk factors when developing strategies to improve child health outcomes in LMICs., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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2024
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37. Spatial patterns of maternal and neonatal continuum of care use and its correlations with women's empowerment.

Author

Kibret GD, Demant D, Dawson A, and Hayen A

Subjects
Humans, Female, Adult, Adolescent, Infant, Newborn, Young Adult, Ethiopia, Middle Aged, Pregnancy, Maternal Health Services statistics & numerical data, Spatial Analysis, Health Services Accessibility statistics & numerical data, Continuity of Patient Care statistics & numerical data, Empowerment
Abstract

Background: The continuum of care (CoC) in maternal health refers to the continuity of individual reproductive health care across the antenatal, intrapartum, and postnatal periods. The CoC is an indicator of the quality of maternal and newborn health outcomes and women's empowerment is crucial to improving maternal and neonatal health service access and utilisation., Objective: To examine the spatial patterns of continuum of care use for maternal and neonatal health services and its correlation with women's empowerment., Methods: We analysed data from the Ethiopian Demographic and Health Surveys (EDHS) of 2011 and 2016. All women aged 15-49 who had live births in the preceding five years of the DHS surveys were included in the analysis. We measured the continuum of care using the modified co-coverage index (CoCI), which consisted of six indicators. Women's empowerment was assessed using a validated survey-based Women's Empowerment (SWPER) index. We used the Getis-Ord-Gi* spatial analysis tool to portray locations with clusters of CoC service use and spatial correlations between CoC use and women empowerment., Results: None of the newborn-mother pairs in the 2011 survey received the entire continuum of care and only 2.5% of newborn-mother pairs received the full range of continuum of care services in the 2016 survey. In 2016, 6.9% of mother-newborn pairs received the basic CoC services (four or more antenatal care [ANC] visits, skilled birth attendance [SBA], and postnatal care [PNC]), and no mother-newborn pair received all three services at the same time in 2011. The Amhara, Afar, and Somali regional states had the least CoC service use in both surveys. There was a positive spatial correlation between CoC use and women's empowerment domains., Conclusion: Our analysis showed that the use of four or more ANC visits, SBS, newborn PNC, Bacillus Calmette-Guérin (BCG) vaccine uptake, and tetanus toxoid protection at birth were low in Ethiopia. Women empowerment domains were found to have a positive spatial correlation with CoC services use. To improve and preserve continuity of care, it is critical to leverage every maternal health facility encounter to encourage sustained service usage at each step of the continuum. Government policies should prioritise women's empowerment and raise public awareness of maternity services., (© 2024. The Author(s).)

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2024
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38. One-Year Anti-VEGF Therapy Outcomes in Diabetic Macular Edema Based on Treatment Intensity: Data from the Fight Retinal Blindness! Registry.

Author

Mehta H, Gabrielle PH, Hashimoto Y, Kibret GD, Arnold J, Guillaumie T, Kheir WJ, Kok G, Vujosevic S, O'Toole L, Mangelschots E, Jaross N, Ceklic L, Daien V, Viola F, Squirrell D, Lavid FJ, Creuzot-Garcher C, Barthelmes D, and Gillies M

Subjects
Humans, Male, Female, Middle Aged, Follow-Up Studies, Treatment Outcome, Aged, Bevacizumab administration & dosage, Receptors, Vascular Endothelial Growth Factor administration & dosage, Receptors, Vascular Endothelial Growth Factor antagonists & inhibitors, Time Factors, Retrospective Studies, Recombinant Fusion Proteins administration & dosage, Macular Edema drug therapy, Macular Edema diagnosis, Macular Edema etiology, Diabetic Retinopathy drug therapy, Diabetic Retinopathy diagnosis, Diabetic Retinopathy complications, Angiogenesis Inhibitors administration & dosage, Intravitreal Injections, Visual Acuity, Registries, Vascular Endothelial Growth Factor A antagonists & inhibitors, Tomography, Optical Coherence methods, Ranibizumab administration & dosage
Abstract

Purpose: To compare 1-year outcomes of eyes with diabetic macular edema (DME) treated in routine clinical practice based on the proportion of visits where intravitreal VEGF inhibitor injections were delivered., Design: Cohort study., Participants: There were 2288 treatment-naive eyes with DME starting intravitreal VEGF inhibitor therapy from October 31, 2015 to October 31, 2021 from the Fight Retinal Blindness! international outcomes registry., Methods: Eyes were grouped according to the proportion of visits at which an injection was received, Group A with less than the median of 67% (n = 1172) versus Group B with greater than the median (n = 1116)., Main Outcome Measures: Mean visual acuity (VA) change after 12 months of treatment., Results: The mean (95% confidence interval [CI]) VA change after 12 months of treatment was 3.6 (2.8-4.4) letters for eyes in Group A versus 5.2 (4.4-5.9) letters for eyes in Group B (P = 0.005). The mean (95% CI) central subfield thickness (CST) change was -69 (-76 to -61) μm and -85 (-92 to -78) μm for eyes in Group A versus Group B, respectively (P = 0.002). A moderate positive correlation was observed between the number of injections received over 12 months of treatment and the change in VA (P < 0.001). Additionally, eyes that received more injections had a moderately greater CST reduction., Conclusions: This registry analysis found that overall VA and anatomic outcomes tended to be better in DME eyes treated at a greater proportion of visits in the first year of intravitreal VEGF inhibitor therapy., Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (Copyright © 2024 American Academy of Ophthalmology. All rights reserved.)

Published
2024
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39. The intergenerational association of preterm birth: A systematic review and meta-analysis.

Author

Seid A, Cumpston MS, Ahmed KY, Bizuayehu HM, Thapa S, Tegegne TK, Dadi AF, Odo DB, Shifti DM, Belachew SA, Kibret GD, Ketema DB, Kassa ZY, Amsalu E, Bore MG, and Hassen TA

Abstract

Background: Around half of preterm births lack identifiable causes, indicating the need for further investigation to understand preterm birth risk factors. Existing studies on the intergenerational association of preterm birth showed inconsistency in effect size and direction., Objective: This systematic review and meta-analysis aimed to review existing studies and provide comprehensive evidence on the intergenerational association of preterm births., Search Strategy: We searched MEDLINE, Embase and Maternity and Infant Care databases, from the inception of each database to 04 April 2024., Selection Criteria: Eligibility criteria included studies that reported on women who had given birth and had recorded information about a family history of preterm birth in one or both of the child's biological parents., Data Collection and Analysis: Data were extracted by two independent reviewers. A random-effects model was used to compute pooled estimates using odds ratios., Main Results: Sixteen eligible studies with a total of 2 271 612 mothers were included. The findings indicated a 1.44 (OR = 1.44, 95% CI: 1.34, 1.54) fold increase in odds of giving preterm births among women who were born preterm. Additionally, having a sibling born preterm (OR = 1.53, 95% CI: 1.24, 1.87) and having a partner born preterm (OR = 1.12, 95% CI: 1.01, 1.25) were associated with increased likelihood of giving preterm births among women., Conclusion: The study revealed that women with a family history of preterm birth face an increased risk of giving preterm births. Screening pregnant women for a family history of preterm birth is essential, with those having a positive family history requiring closer follow-up., (© 2024 The Author(s). BJOG: An International Journal of Obstetrics and Gynaecology published by John Wiley & Sons Ltd.)

Published
2024
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40. Population modifiable risk factors associated with neonatal mortality in 35 sub-Saharan Africa countries: analysis of data from demographic and health surveys.

Author

Ahmed KY, Thapa S, Hassen TA, Tegegne TK, Dadi AF, Odo DB, Bizuayehu HM, Shifti DM, Belachew SA, Kibret GD, Ketema DB, Kassa ZY, Amsalu E, Bore MG, Seid A, Mesfin YM, Kibret KT, Huda MM, Mahmood S, Anyasodor AE, and Ross AG

Abstract

Background: Sub-Saharan Africa (SSA) has the highest burden of neonatal mortality in the world. Identifying the most critical modifiable risk factors is imperative for reducing neonatal mortality rates. This study is the first to calculate population-attributable fractions (PAFs) for modifiable risk factors of neonatal mortality in SSA., Methods: We analysed the most recent Demographic and Health Surveys data sets from 35 SSA countries conducted between 2010 and 2022. Generalized linear latent and mixed models were used to estimate odds ratios (ORs) along with 95% confidence intervals (CIs). PAFs adjusted for communality were calculated using ORs and prevalence estimates for key modifiable risk factors. Subregional analyses were conducted to examine variations in modifiable risk factors for neonatal mortality across Central, Eastern, Southern, and Western SSA regions., Findings: In this study, we included 255,891 live births in the five years before the survey. The highest PAFs of neonatal mortality among singleton children were attributed to delayed initiation of breastfeeding (>1 h after birth: PAF = 23.88%; 95% CI: 15.91, 24.86), uncleaned cooking fuel (PAF = 5.27%; 95% CI: 1.41, 8.73), mother's lacking formal education (PAF = 4.34%; 95% CI: 1.15, 6.31), mother's lacking tetanus vaccination (PAF = 3.54%; 95% CI: 1.55, 4.92), and infrequent antenatal care (ANC) visits (PAF = 2.45; 95% CI: 0.76, 3.63). Together, these five modifiable risk factors were associated with 39.49% (95% CI: 21.13, 48.44) of neonatal deaths among singleton children in SSA. Our subregional analyses revealed some variations in modifiable risk factors for neonatal mortality. Notably, delayed initiation of breastfeeding consistently contributed to the highest PAFs of neonatal mortality across all four regions of SSA: Central, Eastern, Southern, and Western SSA., Interpretation: The PAF estimates in the present study indicate that a considerable proportion of neonatal deaths in SSA are preventable. We identified five modifiable risk factors that accounted for approximately 40% of neonatal deaths in SSA. The findings have policy implications., Funding: None., Competing Interests: All authors declare no competing interests., (© 2024 The Author(s).)

Published
2024
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41. Global burden of 34 cancers among women in 2020 and projections to 2040: Population-based data from 185 countries/territories.

Author

Bizuayehu HM, Dadi AF, Hassen TA, Ketema DB, Ahmed KY, Kassa ZY, Amsalu E, Kibret GD, Alemu AA, Alebel A, Shifa JE, Assefa Y, Tessema GA, Sarich P, Gebremedhin AF, and Bore MG

Subjects
Male, Humans, Female, Life Expectancy, Incidence, Forecasting, Global Burden of Disease, Global Health, Neoplasms epidemiology
Abstract

Globally women face inequality in cancer outcomes; for example, smaller improvements in life expectancy due to decreased cancer-related deaths than men (0.5 vs 0.8 years, 1981-2010). However, comprehensive global evidence on the burden of cancer among women (including by reproductive age spectrum) as well as disparities by region, remains limited. This study aimed to address these evidence gaps by considering 34 cancer types in 2020 and their projections for 2040. The cancer burden among women in 2020 was estimated using population-based data from 185 countries/territories sourced from GLOBOCAN. Mortality to Incidence Ratios (MIR), a proxy for survival, were estimated by dividing the age-standardised mortality rates by the age-standardised incidence rates. Demographic projections were performed to 2040. In 2020, there were an estimated 9.3 million cancer cases and 4.4 million cancer deaths globally. Projections showed an increase to 13.3 million (↑44%) and 7.1 million (↑60%) in 2040, respectively, with larger proportional increases in low- and middle-income countries. MIR among women was higher (poorer survival) in rare cancers and with increasing age. Countries with low Human Development Indexes (HDIs) had higher MIRs (69%) than countries with very high HDIs (30%). There was inequality in cancer incidence and mortality worldwide among women in 2020, which will further widen by 2040. Implementing cancer prevention efforts and providing basic cancer treatments by expanding universal health coverage through a human rights approach, expanding early screening opportunities and strengthening medical infrastructure are key to improving and ensuring equity in cancer control and outcomes., (© 2023 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Published
2024
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42. Unmet Supportive Care Needs Among Cancer Patients in Sub-Saharan African Countries: A Mixed Method Systematic Review and Meta-Analysis.

Author

Bore MG, Dadi AF, Ahmed KY, Hassen TA, Kibret GD, Kassa ZY, Amsalu E, Ketema DB, Perry L Professor, Alemu AA, Shifa JE, Alebel A, Leshargie CT, and Bizuayehu HM

Subjects
Humans, Africa South of the Sahara epidemiology, Quality of Life, Needs Assessment, Palliative Care, Neoplasms therapy, Health Services Needs and Demand
Abstract

Introduction: Supportive cancer care is vital to reducing the current disparities in cancer outcomes in Sub-Saharan Africa (SSA), including poor survival and low quality of life, and ultimately achieving equity in cancer care. This is the first review aimed to evaluate the extent of unmet supportive care needs and identify their contributing factors among patients with cancer in SSA., Methods: Six electronic databases (CINAHL, Embase, Medline [Ovid], PsycINFO, PubMed, and Cochrane Library of Databases] were systematically searched. Studies that addressed one or more domains of unmet supportive cancer care needs were included. Findings were analyzed using narrative analysis and meta-analysis, as appropriate., Result: Eleven articles out of 2732 were retained in the review. The pooled prevalence of perceived unmet need for cancer care in SSA was 63% (95% CI: 45, 81) for physical, 59% (95% CI: 45, 72) for health information and system, 58% (95% CI: 42, 74) for psychological, 44% (95% CI: 29, 59) for patient care and support, and 43% (95% CI: 23, 63) for sexual. Older age, female sex, rural residence, advanced cancer stage, and low access to health information were related to high rates of multiple unmet needs within supportive care domains., Conclusion: In SSA, optimal cancer care provision was low, up to two-thirds of patients reported unmet needs for one or more domains. Strengthening efforts to develop comprehensive and integrated systems for supportive care services are keys to improving the clinical outcome, survival, and quality of life of cancer patients in SSA., (Crown Copyright © 2023. Published by Elsevier Inc. All rights reserved.)

Published
2024
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43. Population modifiable risk factors associated with under-5 acute respiratory tract infections and diarrhoea in 25 countries in sub-Saharan Africa (2014-2021): an analysis of data from demographic and health surveys.

Author

Ahmed KY, Dadi AF, Kibret GD, Bizuayehu HM, Hassen TA, Amsalu E, Ketema DB, Kassa ZY, Bore MG, Alebel A, Alemu AA, Shifa JE, Leshargie CT, Thapa S, Omar SH, and Ross AG

Abstract

Background: Identifying the critical modifiable risk factors for acute respiratory tract infections (ARIs) and diarrhoea is crucial to reduce the burden of disease and mortality among children under 5 years of age in sub-Saharan Africa (SSA) and ultimately achieving the Sustainable Development Goals (SDGs). We investigated the modifiable risk factors of ARI and diarrhoea among children under five using nationally representative surveys., Methods: We used the most recent demographic and health survey (DHS) data (2014-2021) from 25 SSA countries, encompassing a total of 253,167 children. Countries were selected based on the availability of recent datasets (e.g., DHS-VII or DHS-VIII) that represent the current socioeconomic situations. Generalised linear latent mixed models were used to compute odds ratios (ORs). Population attributable fractions (PAFs) were calculated using adjusted ORs and prevalence estimates for key modifiable risk factors among ARI and diarrhoeal cases., Findings: This study involved 253,167 children, with a mean age of 28.7 (±17.3) months, and 50.5% were male. The highest PAFs for ARI were attributed to unclean cooking fuel (PAF = 15.7%; 95% CI: 8.1, 23.1), poor maternal education (PAF = 13.4%; 95% CI: 8.7, 18.5), delayed initiation of breastfeeding (PAF = 12.4%; 95% CI: 9.0, 15.3), and poor toilets (PAF = 8.5%; 95% CI: 4.7, 11.9). These four modifiable risk factors contributed to 41.5% (95% CI: 27.2, 52.9) of ARI cases in SSA. The largest PAFs of diarrhoea were observed for unclean cooking fuel (PAF = 17.3%; 95% CI: 13.5, 22.3), delayed initiation of breastfeeding (PAF = 9.2%; 95% CI: 7.5, 10.5), household poverty (PAF = 7.0%; 95% CI: 5.0, 9.1) and poor maternal education (PAF = 5.6%; 95% CI: 2.9, 8.8). These four modifiable risk factors contributed to 34.0% (95% CI: 26.2, 42.3) of cases of diarrhoea in SSA., Interpretation: This cross-sectional study identified four modifiable risk factors for ARI and diarrhoea that should be a priority for policymakers in SSA. Enhancing home-based care and leveraging female community health workers is crucial for accelerating the reduction in under-5 mortality linked to ARI and diarrhoea in SSA., Funding: None., Competing Interests: All other authors declare no competing interests., (© 2024 The Author(s).)

Published
2024
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44. Birth asphyxia related mortality in Northwest Ethiopia: A multi-centre cohort study.

Author

Ketema DB, Aragaw FM, Wagnew F, Mekonnen M, Mengist A, Alamneh AA, Belay YA, Kibret GD, Leshargie CT, Birhanu MY, Hibstie YT, Temesgen B, and Alebel A

Subjects
Female, Humans, Infant, Newborn, Asphyxia complications, Ethiopia epidemiology, Prospective Studies, Infant Mortality, Perinatal Death, Asphyxia Neonatorum epidemiology
Abstract

Background: Birth asphyxia is the second leading cause of neonatal death in Ethiopia, next to preterm-associated infections. Understanding the causes of death in asphyxiated newborns will help to design appropriate care. This study identifies predictors of neonatal mortality in asphyxiated newborns in selected hospitals in Northwest Ethiopia., Methods: An institution-based prospective cohort study of 480 newborns with birth asphyxia was conducted at Debre Markos Comprehensive Specialized Hospital, Shegaw Motta District Hospital, and Injibara General Hospital. All newborns with asphyxia admitted to the neonatal critical care unit from the first of November 2018 to the first of November 2019 were included. Data were obtained prospectively from mothers using an interviewer's administered questionnaire. The Kaplan-Meier survival curve was used to estimate survival time, and Log rank test was used to compare the survival curves. Bivariable and multivariable Cox proportional hazards models were fitted to identify the independent predictors of mortality in asphyxiated newborns. Adjusted hazard Ratios (AHRs) with 95% Cis (Confidence Intervals) were used to measure the strength of association and test statistical significance., Results: The overall cumulative incidence of mortality among asphyxiated newborns was 42.29% (95% CI: 38%, 46). Asphyxiated neonates with other comorbidities (sepsis, neonatal anemia) (AHR = 2.63, 95% CI:1.69, 4.10), oxygen saturation of 50-69 (AHR = 4.62, 95% CI:2.55, 8.37), oxygen saturation of 70-89 (AHR = 2.82, 95% CI: 1.80, 4.42), severe Apgar score at one minute (AHR = 1.59, 95% CI:1.12, 2.25), neonates with Hypoxic Ischemic Encephalopathy (HIE) (AHR = 6.12, 95% CI:2.23, 16.75) were at higher risk of mortality., Conclusions: The mortality rate among asphyxiated neonates remains high, and slightly higher than previous studies. Asphyxiated newborns with other comorbidities, severe Apgar score at one minute, who develop HIE, and low oxygen saturation were at higher risk of death. Therefore, designing appropriate interventions and prevention methods should be considered for identified variables., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ketema et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2023
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45. The effect of distance to health facility on neonatal mortality in Ethiopia.

Author

Kibret GD, Demant D, and Hayen A

Subjects
Infant, Newborn, Female, Humans, Pregnancy, Ethiopia epidemiology, Infant Mortality, Health Facilities, Prenatal Care, Delivery, Obstetric, Health Services Accessibility, Maternal Health Services
Abstract

Introduction: In Ethiopia, more than half of newborn babies do not have access to Emergency Obstetric and Neonatal Care (EmONC) services. Understanding the effect of distance to health facilities on service use and neonatal survival is crucial to recommend policymakers and improving resource distribution. We aimed to investigate the effect of distance to health services on maternal service use and neonatal mortality., Methods: We implemented a data integration method based on geographic coordinates. We calculated straight-line (Euclidean) distances from the Ethiopian 2016 demographic and health survey (EDHS) clusters to the closest health facility. We computed the distance in ESRI ArcGIS Version 10.3 using the geographic coordinates of DHS clusters and health facilities. Generalised Structural Equation Modelling (GSEM) was used to estimate the effect of distance on neonatal mortality., Results: Poor geographic accessibility to health facilities affects maternal service usage and increases the risk of newborn mortality. For every ten kilometres (km) increase in distance to a health facility, the odds of neonatal mortality increased by 1.33% (95% CI: 1.06% to 1.67%). Distance also negatively affected antenatal care, facility delivery and postnatal counselling service use., Conclusions: A lack of geographical access to health facilities decreases the likelihood of newborns surviving their first month of life and affects health services use during pregnancy and immediately after birth. The study also showed that antenatal care use was positively associated with facility delivery service use and that both positively influenced postnatal care use, demonstrating the interconnectedness of the components of continuum of care for maternal and neonatal care services. Policymakers can leverage the findings from this study to improve accessibility barriers to health services., (© 2023. The Author(s).)

Published
2023
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46. Dental caries and associated factors among diabetic and nondiabetic adult patients attending Bichena Primary Hospital's Outpatient Department.

Author

Shiferaw A, Alem G, Tsehay M, and Kibret GD

Abstract

Purpose: Dental caries is a significant public health issue affecting both the diabetic and nondiabetic populations. However, the problem and associated factors of dental caries among diabetics and nondiabetics patients are not well-known in Ethiopia. This study aims to compare the prevalence of dental caries and associated factors among diabetic and nondiabetic patients at the Outpatient Department of Bichena Primary Hospital in Northwest, Ethiopia., Methods: Institutional based, comparative cross-sectional study was conducted from October 7 to December 6, 2019, among 200 diabetes and 400 nondiabetic adult patients. A consecutive sampling technique was implemented to recruit study participants. Data were collected by a pretested structured questionnaire and analysis was performed in Statistical Package for Social Science version 20. Bivariable and multivariable logistic regressions were employed and variables with a p -value < 0.05 were declared statistically significant., Results: A total of 582 patients were involved in the study with a response rate of 97.0%. The prevalence of dental caries was 67.9% [95% confidence interval (CI): 63.2%-72.8%] and 79.6% (95% CI: 74.0%-85.70%) in nondiabetic and diabetic group, respectively. Females gender [adjusted odds ratio (AOR) = 1.79, 95% CI: 1.15-2.77], poor oral hygiene (AOR = 2.95, 95% CI: 1.71-5.11), lack of regular teeth cleaning habits (AOR = 3.26, 95% CI: 2.13-4.97), feeling dry mouth (AOR = 2.31, 95% CI: 1.11-4.81), sugared tea drinking (AOR = 2.00, 95% CI: 1.18-3.38), inadequate oral health knowledge (AOR = 3.51, 95% CI: 2.19-5.62), and khat chewing (AOR = 2.14, 95% CI: 1.24-3.71) were significantly associated factors with high prevalence of dental caries., Conclusion: The prevalence of caries was significantly higher among diabetics than nondiabetics. Oral health education with preventive measures such as improving teeth cleaning practice, reducing sugary foods and drinks intake, and improving oral hygiene practice of patients should be mainstreamed along with diabetic follow-up care., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Shiferaw, Alem, Tsehay and Kibret.)

Published
2022
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47. Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia.

Author

Kibret GD, Demant D, and Hayen A

Subjects
Bayes Theorem, Ethiopia epidemiology, Humans, Infant, Newborn, Risk Factors, Spatial Analysis, Infant Mortality
Abstract

Background: Ethiopia is a Sub-Saharan country with very high neonatal mortality rates, varying across its regions. The rate of neonatal mortality reduction in Ethiopia is slow, and Ethiopia may not meet the third United Nations sustainable development target by 2030. This study aimed to investigate the spatial variations and contributing factors for neonatal mortality rates in Ethiopia., Methods: We analysed data from the 2016 Ethiopian Demographic and Health Survey (EDHS), which used a two-stage cluster sampling technique with a census enumeration area as primary and households as secondary sampling units. A Bayesian spatial logistic regression model using the Stochastic Partial Differential Equation (SPDE) method was fitted accounting for socio-economic, health service-related and geographic factors., Results: Higher neonatal mortality rates were observed in eastern, northeastern and southeastern Ethiopia, and the Somali region had higher risks of neonatal mortality. Neonates from frequently drought-affected areas had a higher mortality risk than less drought-affected areas. Application of traditional substances on the cord increased the risk of neonatal mortality (Adjusted Odds Ratio (AOR) = 2.07, 95% Credible Interval (CrI): 1.12 to 4.30) and getting health facility delivery services had a lower odds of neonatal mortality (AOR = 0.60, 95% CrI: 0.37, 0.98)., Conclusions: Residing in drought-affected areas, applying traditional substances on the umbilical cord and not delivering at health facilities were associated with a higher risk of neonatal mortality. Policy-makers and resource administrators at different administrative levels could leverage the findings to prioritise and target areas identified with higher neonatal mortality rates., Competing Interests: The authors have declared that no competing interests exist.

Published
2022
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48. Geographical accessibility of emergency neonatal care services in Ethiopia: analysis using the 2016 Ethiopian Emergency Obstetric and Neonatal Care Survey.

Author

Kibret GD, Demant D, and Hayen A

Subjects
Ethiopia, Female, Health Facilities, Humans, Infant, Newborn, Pregnancy, Surveys and Questionnaires, Emergency Medical Services, Health Services Accessibility
Abstract

Introduction: Access to emergency neonatal health services has not been explored widely in the Ethiopian context. Accessibility to health services is a function of the distribution and location of services, including distance, travel time, cost and convenience. Measuring the physical accessibility of health services contributes to understanding the performance of health systems, thereby enabling evidence-based health planning and policies. The physical accessibility of Ethiopian health services, particularly emergency neonatal care (EmNeC) services, is unknown., Objective: To analyse the physical accessibility of EmNeC services at the national and subnational levels in Ethiopia., Methods: We analysed the physical accessibility of EmNeC services within 30, 60 and 120 min of travel time in Ethiopia at a national and subnational level. We used the 2016 Ethiopian Emergency Obstetric and Neonatal Care survey in addition to several geospatial data sources., Results: We estimated that 21.4%, 35.9% and 46.4% of live births in 2016 were within 30, 60 and 120 min of travel time of fully EmNeC services, but there was considerable variation across regions. Addis Ababa and the Hareri regional state had full access (100% coverage) to EmNeC services within 2 hours travel time, while the Afar (15.3%) and Somali (16.3%) regional states had the lowest access., Conclusions: The physical access to EmNeC services in Ethiopia is well below the universal health coverage expectations stated by the United Nations. Increasing the availability of EmNeC to health facilities where routine delivery services currently are taking place would significantly increase physical access. Our results reinforce the need to revise service allocations across administrative regions and consider improving disadvantaged areas in future health service planning., 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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49. 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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50. Effect of a self-care educational intervention to improve self-care adherence among patients with chronic heart failure: a clustered randomized controlled trial in Northwest Ethiopia.

Author

Dessie G, Burrowes S, Mulugeta H, Haile D, Negess A, Jara D, Alem G, Tesfaye B, Zeleke H, Gualu T, Getaneh T, Kibret GD, Amare D, Worku Mengesha E, Wagnew F, and Khanam R

Subjects
Adult, Ethiopia, Female, Humans, Male, Marital Status, Middle Aged, Self Care statistics & numerical data, Self-Management education, Socioeconomic Factors, Heart Failure therapy, Patient Compliance, Patient Education as Topic methods, Self Care methods
Abstract

Background: As the burden of cardiovascular disease increases in sub-Saharan Africa, there is a growing need for low-cost interventions to mitigate its impact. Providing self-care health education to patients with chronic heart failure (CHF) is recommended as an intervention to prevent complications, improve quality of life, and reduce financial burdens on fragile health systems. However, little is known about health education's effectiveness at improving CHF self-management adherence in sub-Saharan Africa. Therefore the present study aimed to assess the effectiveness of an educational intervention to improve self-care adherence among patients with CHF at Debre Markos and Felege Hiwot Referral Hospitals in Northwest Ethiopia., Methods: To address this gap, we adapted a health education intervention based on social cognitive theory comprising of intensive four-day training and, one-day follow-up sessions offered every four months. Patients also received illustrated educational leaflets. We then conducted a clustered randomized control trial of the intervention with 186 randomly-selected patients at Debre Markos and Felege Hiwot referral hospitals. We collected self-reported data on self-care behavior before each educational session. We analyzed these data using a generalized estimating equations model to identify health education's effect on a validated 8-item self-care adherence scale., Results: Self-care adherence scores were balanced at baseline. After the intervention, patients in the intervention group (n = 88) had higher adherence scores than those in the control group (n = 98). This difference was statistically significant (β = 4.15, p < 0.05) and increased with each round of education. Other factors significantly associated with adherence scores were being single (β = - 0.25, p < 0.05), taking aspirin (β = 0.76, p < 0.05), and having a history of hospitalization (β = 0.91, p < 0.05)., Conclusions: We find that self-care education significantly improved self-care adherence scores among CHF patients. This suggests that policymakers should consider incorporating self-care education into CHF management., Trial Registration Number: PACTR201908812642231., (© 2021. The Author(s).)

Published
2021
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