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      National mortality burden due to communicable, non-communicable, and other diseases in Ethiopia, 1990–2015: findings from the Global Burden of Disease Study 2015

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          Abstract

          Background

          Ethiopia lacks a complete vital registration system that would assist in measuring disease burden and risk factors. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) estimates to describe the mortality burden from communicable, non-communicable, and other diseases in Ethiopia over the last 25 years.

          Methods

          GBD 2015 mainly used cause of death ensemble modeling to measure causes of death by age, sex, and year for 195 countries. We report numbers of deaths and rates of years of life lost (YLL) for communicable, maternal, neonatal, and nutritional (CMNN) disorders, non-communicable diseases (NCDs), and injuries with 95% uncertainty intervals (UI) for Ethiopia from 1990 to 2015.

          Results

          CMNN causes of death have declined by 65% in the last two-and-a-half decades. Injury-related causes of death have also decreased by 70%. Deaths due to NCDs declined by 37% during the same period. Ethiopia showed a faster decline in the burden of four out of the five leading causes of age-standardized premature mortality rates when compared to the overall sub-Saharan African region and the Eastern sub-Saharan African region: lower respiratory infections, tuberculosis, HIV/AIDS, and diarrheal diseases; however, the same could not be said for ischemic heart disease and other NCDs. Non-communicable diseases, together, were the leading causes of age-standardized mortality rates, whereas CMNN diseases were leading causes of premature mortality in 2015. Although lower respiratory infections, tuberculosis, and diarrheal disease were the leading causes of age-standardized death rates, they showed major declines from 1990 to 2015. Neonatal encephalopathy, iron-deficiency anemia, protein-energy malnutrition, and preterm birth complications also showed more than a 50% reduction in burden. HIV/AIDS-related deaths have also decreased by 70% since 2005. Ischemic heart disease, hemorrhagic stroke, and ischemic stroke were among the top causes of premature mortality and age-standardized death rates in Ethiopia in 2015.

          Conclusions

          Ethiopia has been successful in reducing deaths related to communicable, maternal, neonatal, and nutritional deficiency diseases and injuries by 65%, despite unacceptably high maternal and neonatal mortality rates. However, the country’s performance regarding non-communicable diseases, including cardiovascular disease, diabetes, cancer, and chronic respiratory disease, was minimal, causing these diseases to join the leading causes of premature mortality and death rates in 2015. While the country is progressing toward universal health coverage, prevention and control strategies in Ethiopia should consider the double burden of common infectious diseases and non-communicable diseases: lower respiratory infections, diarrhea, tuberculosis, HIV/AIDS, cardiovascular disease, cancer, and diabetes. Prevention and control strategies should also pay special attention to the leading causes of premature mortality and death rates caused by non-communicable diseases: cardiovascular disease, cancer, and diabetes. Measuring further progress requires a data revolution in generating, managing, analyzing, and using data for decision-making and the creation of a full vital registration system in the country.

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          Most cited references21

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          Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

          The fifth Millennium Development Goal (MDG 5) established the goal of a 75% reduction in the maternal mortality ratio (MMR; number of maternal deaths per 100,000 livebirths) between 1990 and 2015. We aimed to measure levels and track trends in maternal mortality, the key causes contributing to maternal death, and timing of maternal death with respect to delivery. We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990-2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values. 292,982 (95% UI 261,017-327,792) maternal deaths occurred in 2013, compared with 376,034 (343,483-407,574) in 1990. The global annual rate of change in the MMR was -0·3% (-1·1 to 0·6) from 1990 to 2003, and -2·7% (-3·9 to -1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290-2866) maternal deaths were related to HIV in 2013, 0·4% (0·2-0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1-1262·8) in South Sudan to 2·4 (1·6-3·6) in Iceland. Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            The epidemiologic transition: a theory of the epidemiology of population change. 1971.

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              Success factors for reducing maternal and child mortality

              Reducing maternal and child mortality is a priority in the Millennium Development Goals (MDGs), and will likely remain so after 2015. Evidence exists on the investments, interventions and enabling policies required. Less is understood about why some countries achieve faster progress than other comparable countries. The Success Factors for Women’s and Children’s Health studies sought to address this knowledge gap using statistical and econometric analyses of data from 144 low- and middle-income countries (LMICs) over 20 years; Boolean, qualitative comparative analysis; a literature review; and country-specific reviews in 10 fast-track countries for MDGs 4 and 5a. There is no standard formula – fast-track countries deploy tailored strategies and adapt quickly to change. However, fast-track countries share some effective approaches in addressing three main areas to reduce maternal and child mortality. First, these countries engage multiple sectors to address crucial health determinants. Around half the reduction in child mortality in LMICs since 1990 is the result of health sector investments, the other half is attributed to investments made in sectors outside health. Second, these countries use strategies to mobilize partners across society, using timely, robust evidence for decision-making and accountability and a triple planning approach to consider immediate needs, long-term vision and adaptation to change. Third, the countries establish guiding principles that orient progress, align stakeholder action and achieve results over time. This evidence synthesis contributes to global learning on accelerating improvements in women’s and children’s health towards 2015 and beyond.
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                Author and article information

                Contributors
                awoket@uw.edu
                tilahunigatu@gmail.com
                kebededeka@yahoo.com
                agizachew@gmail.com
                amare_deribew@yahoo.com
                adamayohannes@gmail.com
                azmerawtayelgn3@gmail.com
                semawfer@yahoo.com
                mollagedefaw@yahoo.com
                destamule@gmail.com
                yihunierh@yahoo.com
                tolesa2003@yahoo.com
                mesoud.mohammed@gmail.com
                biruck471@yahoo.ca
                abrsole2006@gmail.com
                kkrohn1@uw.edu
                tachoki@uw.edu
                jedblore@uw.edu
                yibeltalassefa343@gmail.com
                nagham@uw.edu
                Journal
                Popul Health Metr
                Popul Health Metr
                Population Health Metrics
                BioMed Central (London )
                1478-7954
                21 July 2017
                21 July 2017
                2017
                : 15
                : 29
                Affiliations
                [1 ]ISNI 0000000122986657, GRID grid.34477.33, Institute for Health Metrics and Evaluation, , University of Washington, ; Seattle, USA
                [2 ]Africa Population and Health Research Center, Nairobi, Kenya
                [3 ]ISNI 0000 0000 8853 076X, GRID grid.414601.6, , Brighton and Sussex Medical School, ; Brighton, UK
                [4 ]ISNI 0000 0001 1250 5688, GRID grid.7123.7, School of Public Health, , Addis Ababa University, ; Addis Ababa, Ethiopia
                [5 ]ISNI 0000 0004 1936 7304, GRID grid.1010.0, School of Public Health, , University of Adelaide, ; Adelaide, Australia
                [6 ]ISNI 0000 0000 8539 4635, GRID grid.59547.3a, Department of Reproductive Health, Institute of Public Health, , University of Gondar, ; Gondar, Ethiopia
                [7 ]ISNI 0000 0001 0155 5938, GRID grid.33058.3d, , KEMRI-Wellcome Trust Research Programme, ; Kilifi, Kenya
                [8 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Nuffield Department of Clinical Medicine, , University of Oxford, ; Oxford, UK
                [9 ]St. Paul Millennium Medical College, Addis Ababa, Ethiopia
                [10 ]ISNI 0000 0001 1539 8988, GRID grid.30820.39, School of Public Health, College of Health Sciences, , Mekelle University, ; Mekelle, Ethiopia
                [11 ]GRID grid.414835.f, , Federal Ministry of Health, ; Addis Ababa, Ethiopia
                [12 ]ISNI 0000 0004 0439 5951, GRID grid.442845.b, College of Medicine and Health Sciences, , Bahir Dar University, ; Bahir Dar, Ethiopia
                [13 ]ISNI 0000 0001 2290 1502, GRID grid.9464.f, Institute for Biological Chemistry and Nutrition, , University of Hohenheim, ; Stuttgart, Germany
                [14 ]Amref Health Africa in Ethiopia, Addis Ababa, Ethiopia
                [15 ]GRID grid.428935.1, , Ethiopian Public Health Association, ; Addis Ababa, Ethiopia
                [16 ]Department of Public Health, College of Medicine and Health Sciences, Madda Walabu University, Bale Robe, Ethiopia
                [17 ]ISNI 0000 0000 8994 5086, GRID grid.1026.5, , University of South Australia, ; Adelaide, Australia
                [18 ]College of Health Sciences and Medicine, Wolayta Sodo University, Sodo, Ethiopia
                [19 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, , University of Queensland, ; Brisbane, Australia
                Author information
                http://orcid.org/0000-0002-3949-9457
                Article
                145
                10.1186/s12963-017-0145-1
                5521057
                28736507
                f2228cfb-2833-4f71-9d73-e11f1721855c
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 May 2016
                : 14 July 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Health & Social care
                causes of death,mortality,communicable disease,non-communicable diseases,ethiopia,global burden of disease

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