Neglected burden of injuries in Ethiopia, from 1990 to 2019: a systematic analysis of the global burden of diseases study 2019

BackgroundThe 2030 agenda for sustainable development goals has given injury prevention new attention, including halving road traffic injuries. This study compiled the best available evidence on injury from the global burden of diseases study for Ethiopia from 1990 to 2019.MethodsInjury data on incidence, prevalence, mortality, disability-adjusted life years lost, years lived with disability, and years of life lost were extracted from the 2019 global burden of diseases study for regions and chartered cities in Ethiopia from 1990 to 2019. Rates were estimated per 100,000 population.ResultsIn 2019, the age-standardized rate of incidence was 7,118 (95% UI: 6,621–7,678), prevalence was 21,735 (95% UI: 19,251–26,302), death was 72 (95% UI: 61–83), disability-adjusted life years lost was 3,265 (95% UI: 2,826–3,783), years of live lost was 2,417 (95% UI: 2,043–2,860), and years lived with disability was 848 [95% UI: (620–1,153)]. Since 1990, there has been a reduction in the age-standardized rate of incidence by 76% (95% UI: 74–78), death by 70% (95% UI: 65–75), and prevalence by 13% (95% UI: 3–18), with noticeable inter-regional variations. Transport injuries, conflict and terrorism, interpersonal violence, self-harm, falls, poisoning, and exposure to mechanical forces were the leading causes of injury-related deaths and long-term disabilities. Since 1990, there has been a decline in the prevalence of transport injuries by 32% (95% UI: 31–33), exposure to mechanical forces by 12% (95% UI: 10–14), and interpersonal violence by 7.4% (95% UI: 5–10). However, there was an increment in falls by 8.4% (95% UI: 7–11) and conflict and terrorism by 1.5% (95% UI: 38–27).ConclusionEven though the burden of injuries has steadily decreased at national and sub-national levels in Ethiopia over the past 30 years, it still remains to be an area of public health priority. Therefore, injury prevention and control strategies should consider regional disparities in the burden of injuries, promoting transportation safety, developing democratic culture and negotiation skills to solve disputes, using early security-interventions when conflict arises, ensuring workplace safety and improving psychological wellbeing of citizens

Progress in health among regions of Ethiopia, 1990–2019: a subnational country analysis for the Global Burden of Disease Study 2019

Background Previous Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) studies have reported national health estimates for Ethiopia. Substantial regional variations in socioeconomic status, population, demography, and access to health care within Ethiopia require comparable estimates at the subnational level. The GBD 2019 Ethiopia subnational analysis aimed to measure the progress and disparities in health across nine regions and two chartered cities. Methods We gathered 1057 distinct data sources for Ethiopia and all regions and cities that included census, demographic surveillance, household surveys, disease registry, health service use, disease notifications, and other data for this analysis. Using all available data sources, we estimated the Socio-demographic Index (SDI), total fertility rate (TFR), life expectancy, years of life lost, years lived with disability, disability-adjusted life-years, and risk-factor-attributable health loss with 95% uncertainty intervals (UIs) for Ethiopia's nine regions and two chartered cities from 1990 to 2019. Spatiotemporal Gaussian process regression, cause of death ensemble model, Bayesian meta-regression tool, DisMod-MR 2.1, and other models were used to generate fertility, mortality, cause of death, and disability rates. The risk factor attribution estimations followed the general framework established for comparative risk assessment. Findings The SDI steadily improved in all regions and cities from 1990 to 2019, yet the disparity between the highest and lowest SDI increased by 54% during that period. The TFR declined from 6·91 (95% UI 6·59–7·20) in 1990 to 4·43 (4·01–4·92) in 2019, but the magnitude of decline also varied substantially among regions and cities. In 2019, TFR ranged from 6·41 (5·96–6·86) in Somali to 1·50 (1·26–1·80) in Addis Ababa. Life expectancy improved in Ethiopia by 21·93 years (21·79–22·07), from 46·91 years (45·71–48·11) in 1990 to 68·84 years (67·51–70·18) in 2019. Addis Ababa had the highest life expectancy at 70·86 years (68·91–72·65) in 2019; Afar and Benishangul-Gumuz had the lowest at 63·74 years (61·53–66·01) for Afar and 64.28 (61.99-66.63) for Benishangul-Gumuz. The overall increases in life expectancy were driven by declines in under-5 mortality and mortality from common infectious diseases, nutritional deficiency, and war and conflict. In 2019, the age-standardised all-cause death rate was the highest in Afar at 1353·38 per 100 000 population (1195·69–1526·19). The leading causes of premature mortality for all sexes in Ethiopia in 2019 were neonatal disorders, diarrhoeal diseases, lower respiratory infections, tuberculosis, stroke, HIV/AIDS, ischaemic heart disease, cirrhosis, congenital defects, and diabetes. With high SDIs and life expectancy for all sexes, Addis Ababa, Dire Dawa, and Harari had low rates of premature mortality from the five leading causes, whereas regions with low SDIs and life expectancy for all sexes (Afar and Somali) had high rates of premature mortality from the leading causes. In 2019, child and maternal malnutrition; unsafe water, sanitation, and handwashing; air pollution; high systolic blood pressure; alcohol use; and high fasting plasma glucose were the leading risk factors for health loss across regions and cities. Interpretation There were substantial improvements in health over the past three decades across regions and chartered cities in Ethiopia. However, the progress, measured in SDI, life expectancy, TFR, premature mortality, disability, and risk factors, was not uniform. Federal and regional health policy makers should match strategies, resources, and interventions to disease burden and risk factors across regions and cities to achieve national and regional plans, Sustainable Development Goals, and universal health coverage targets. Funding Bill & Melinda Gates Foundation

Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.Peer reviewe

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990-2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was 1·94 (1·76–2·12). No regions met suggested thresholds for progress. Interpretation: Sub-Saharan Africa had both the highest HIV burden and the greatest progress between 1990 and 2019. The number of incident cases and deaths in males and females approached parity in 2019, although there remained more females with HIV than males with HIV. Globally, the HIV epidemic is far from the UNAIDS benchmarks on progress metrics. Funding: The Bill & Melinda Gates Foundation, the National Institute of Mental Health of the US National Institutes of Health (NIH), and the National Institute on Aging of the NIH

Predictors of Neonatal mortality in Neonatal intensive care unit at referral Hospital in Southern Ethiopia: a retrospective cohort study

Abstract Background The first one month of life; the neonatal period is the most risky time for child survival. In Ethiopia, neonatal mortality is unacceptably high, and the trend in reduction is slower as compared to infant and child mortality. The magnitude and associated factors of neonatal mortality in a tertiary care facility were not well documented. Therefore, the aim of this study was to determine neonatal mortality and predictors among neonates admitted to neonatal intensive care unit of Wolaita Sodo University Teaching and Referral Hospital, South Ethiopia. Methods A retrospective cohort study design was done among neonates admitted to neonatal intensive care unit of a University Teaching and Referral Hospital from 2015 to 2017. Data were collected using data extraction checklist from the medical registry. The main outcome was the occurrence of death within the first four weeks. The survival time was calculated in days between the date of admission and the date of death. Kaplan-Meier survival was used to depict the pattern of death in 28 days and Cox-Proportional model was used to identify the predictors of the neonatal mortality. Results A total of 964 neonates which contributed to 5889 neonates-days were included in the study. There were 159 neonatal deaths during the follow-up time. Overall, the neonatal mortality incidence was 27 per 1000 neonates-days. Predictors of neonatal mortality were: multiple birth, mothers who did not attend antenatal care visits, neonates born by cesarean section, not initiated breast feeding within 1 h of birth, neonates resuscitated, hyaline membrane disease and perinatal asphyxia. Conclusion Neonatal mortality at neonatal intensive care unit was high. Managing neonatal complications, initiating breast feeding within 1 h of birth, promoting antenatal care visits, improving quality of services and ensuring continuum of care are recommended to increase survival of neonates

National and subnational burden of under-5, infant, and neonatal mortality in Ethiopia, 1990–2019: Findings from the Global Burden of Disease Study 2019

The under-5 mortality rate is a commonly used indicator of population health and socioeconomic status worldwide. However, as in most low- and middle-income countries settings, deaths among children under-5 and in any age group in Ethiopia remain underreported and fragmented. We aimed to systematically estimate neonatal, infant, and under-5 mortality trends, identify underlying causes, and make subnational (regional and chartered cities) comparisons between 1990 and 2019. We used the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD 2019) to estimate three key under-5 mortality indicators—the probability of death between the date of birth and 28 days (neonatal mortality rate, NMR), the date of birth and 1 year (infant mortality rate, IMR), and the date of birth and 5 years (under-5 mortality rate, U5MR). The causes of death by age groups, sex, and year were estimated using Cause of Death Ensemble modelling (CODEm). Specifically, this involved a multi-stage process that includes a non-linear mixed-effects model, source bias correction, spatiotemporal smoothing, and a Gaussian process regression to synthesise mortality estimates by age, sex, location, and year. In 2019, an estimated 190,173 (95% uncertainty interval 149,789–242,575) under-5 deaths occurred in Ethiopia. Nearly three-quarters (74%) of under-5 deaths in 2019 were within the first year of life, and over half (52%) in the first 28 days. The overall U5MR, IMR, and NMR in the country were estimated to be 52.4 (44.7–62.4), 41.5 (35.2–50.0), and 26.6 (22.6–31.5) deaths per 1000 livebirths, respectively, with substantial variations between administrative regions. Over three-quarters of under-5 deaths in 2019 were due to five leading causes, namely neonatal disorders (40.7%), diarrhoeal diseases (13.2%), lower respiratory infections (10.3%), congenital birth defects (7.0%), and malaria (6.0%). During the same period, neonatal disorders alone accounted for about 76.4% (70.2–79.6) of neonatal and 54.7% (51.9–57.2) of infant deaths in Ethiopia. While all regional states in Ethiopia have experienced a decline in under-5, infant, and neonatal mortality rates in the past three decades, the rate of change was not large enough to meet the targets of the Sustainable Development Goals (SDGs). Inter-regional disparities in under 5 mortality also remain significant, with the biggest differences being in the neonatal period. A concerted effort is required to improve neonatal survival and lessen regional disparity, which may require strengthening essential obstetric and neonatal care services, among others. Our study also highlights the urgent need for primary studies to improve the accuracy of regional estimates in Ethiopia, particularly in pastoralist regions

Lists of causes of level 3 causes of death for under 5 children in GBD Study 2019*.

Lists of causes of level 3 causes of death for under 5 children in GBD Study 2019*.</p

Percentage of under-5 deaths attributable to each risk factors in Ethiopia and its regional states, 2019.

*All risk factors column does not reflect the addition of groups of risk factors. (DOCX)</p

The number of under-5, infant, and neonatal deaths in 1990, 2015, 2019 and rate of change in Ethiopia and administrative regions.

The number of under-5, infant, and neonatal deaths in 1990, 2015, 2019 and rate of change in Ethiopia and administrative regions.</p