39 research outputs found

    Association of age and colostrum discarding with breast-feeding practice in Ethiopia:Systematic review and meta-analyses

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    OBJECTIVE: To investigate whether maternal/caregiver's age, infant age (0-6 months) and discarding colostrum affects timely initiation of breast-feeding (TIBF) and exclusive breast-feeding (EBF) in Ethiopia. DESIGN: A systematic search of PubMed, SCOPUS, EMBASE, CINHAL, Web of Science and WHO Global Health Library electronic databases was done for all articles published in English from 2000 to January 2018. Two reviewers independently screened, extracted and graded the quality of studies using Newcastle-Ottawa Scale. A weighted inverse-variance random-effects model meta-analysis, cumulative meta-analysis and mixed-effects meta-regression analysis were done. SETTING: All observational studies conducted in Ethiopia.ParticipantsMothers of children aged less than 2 years.ResultA total of forty articles (fourteen studies on TIBF and twenty-six on EBF) were included. TIBF was associated with colostrum discarding (OR=0·38; 95 % CI 0·21, 0·68) but not with maternal/caregiver's age (OR=0·98; 95 % CI 0·83, 1·15). In addition, colostrum discarding (OR=0·53; 95 % CI 0·36, 0·78) and infant age (OR=1·77; 95 % CI 1·38, 2·27) were significantly associated with EBF but not maternal/caregiver's age (OR=1·09; 95 % CI 0·84, 1·41). CONCLUSIONS: There was no association between maternal/caregiver's age and breast-feeding practice (EBF and TIBF). Colostrum discarding was associated with both EBF and TIBF. This evidence could be helpful to counsel all mothers of reproductive age and who discard colostrum

    Mother's knowledge on prevention of mother-to-child transmission of HIV, Ethiopia:A cross sectional study

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    Objective To identify proportion of and factors for comprehensive knowledge on prevention of mother-to-child transmission of HIV in pregnant women attending antenatal care in Northern Ethiopia. Methods A total of 416 pregnant women were interviewed between October 2012 and May 2013. Logistic regression analysis was used to identify factors for comprehensive knowledge on prevention of mother-to-child transmission of HIV. Results The proportion of pregnant women, who have comprehensive knowledge on prevention of mother-to-child transmission of HIV, was 52%. The odds of having comprehensive knowledge on prevention of mother-to-child transmission of HIV were higher among pregnant women who were younger (16 to 24 years old) (Adjusted Odds Ratio (AOR) = 2.95; 95%Cl: 1.20, 7.26), urban residents (AOR = 2.45; 95%CI: 1.39, 4.32), attending secondary education and above (AOR = 4.43; 95%CI: 2.40, 8.20), employed (AOR = 4.99;95%CI: 2.45, 10.16), have five children or more (AOR = 9.34; 95%CI:3.78, 23.07), have favored attitude towards HIV positive living (AOR = 2.53; 95%CI: 1.43, 4.44) and have perceived susceptibility to HIV (AOR = 10.72; 95%CI: 3.90, 29.39). Conclusion The proportion of women who have comprehensive knowledge on prevention of mother-to-child transmission of HIV in this study setting was low. Measures which will escalate mother's knowledge on prevention of mother-to-child transmission of HIV should be emphasized. Efforts to improve mother's knowledge on prevention of mother-to-child transmission of HIV should target women who were older age (> = 35years), rural residents, unemployed, not 16 attending formal education, primigravids, have no favored attitude towards HIV positive living and have not perceived susceptibility to HIV

    Magnitude of Cryptococcal Antigenemia among HIV Infected Patients at a Referral Hospital, Northwest Ethiopia

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    BACKGROUND: Cryptococcosis is one of the common opportunistic fungal infections among HIV infected patients living in Sub-Saharan Africa, including Ethiopia. The magnitude of thedisease at Felege Hiwot Referral Hospital (FHRH) in particular and in Ethiopia at large is not well explored.METHODS: A retrospective document review and analysis was done on records of 137 HIV infected patients who visited FHRH ART clinic from 1 Sep to 30 Dec 2016 and had registered data on their sex, age, CD4 count and cryptococcal antigen screening result. The cryptoccocal antigen (CrAg) detection was done by the IMMY CrAg® LFA (Cryptococcal Antigen Lateral Flow Assay) kit from patient serum as per the manufacturer’s instruction. All data were entered, cleared, and analyzed using SPSS v20. Descriptive data analysis and cross tabulation were done to assess factors associated with cryptococcal antigenemia. Statistical significance was set at p-value less than or equal to 0.05.RESULTS: More than half of the participants, 54.7% (75/137), included in the study were females. The median age of the participants was 32.0 years (ranged: 8-52 years). The mean CD4 count was 51.8 with SD of 26.3 (range 3-98). All the patients were HIV stage IV. The proportion of positive cryptococal antigen from serum test was at 11.7% (95% CI: 7.3-18.1%). The IMMYCrAg® LFA result was found statically associated with patient sex (p= 0.045). However, it was not associated with patient age group and the CD4 count (P>0.05)CONCLUSIONS: This study provided baseline data on the magnitude of cryptococcal antigenemia among HIV positive patients that is not touched before in the studied area. The results of the study showed that this opportunistic fungal infection is an important health concern among HIV patients. Further studies with sound design employing adequate sample size should be considered.

    Determinants for tuberculosis in HIV-infected adults in Northwest Ethiopia: a multicentre case-control study.

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    OBJECTIVE: The objective of this study was to identify determinants for tuberculosis (TB) among HIV-infected adults in Northwest Ethiopia. DESIGN: Case-control study. SETTING: Three hospitals and 10 health centres in Northwest Ethiopia. PARTICIPANTS: A total of 446 individuals consented to participate in the study (150 cases and 296 controls). Cases were HIV-infected adults diagnosed with active TB, and controls were HIV-infected adults without active TB. MAIN OUTCOME MEASURE: The link between TB and determinants was assessed using logistic regression. Determinants were categorised as sociodemographic, host-related, clinical and environmental. RESULTS: Smoking (adjusted OR (AOR) 5.47; 95% CI 2.26 to 13.22), presence of a TB patient in the family (AOR 2.66; 95% CI 1.25 to 5.66), alcohol consumption (AOR 2.49; 95% CI 1.29 to 4.80) and chewing khat (AOR 2.22; 95% CI 1.11 to 4.41) were independent determinants for increased occurrence of TB. Highly active antiretroviral therapy (HAART) (AOR 0.25; 95% CI 0.13 to 0.51), isoniazid preventive therapy (IPT) (AOR 0.22; 95% CI 0.11 to 0.41) and cotrimoxazole preventive therapy (AOR 0.32; 95% CI 0.19 to 0.55) had a protective effect against TB. CONCLUSIONS: HIV-infected adults with substance abuse (tobacco smoking, khat chewing and alcohol) should be prioritised for TB screening. This study reaffirmed that HAART and IPT are some of the best strategies for reducing TB occurrence in HIV-infected adults. These findings provide impetus to intensify tracing of TB household contacts

    Sociodemographic Factors Predicting Exclusive Breastfeeding in Ethiopia:Evidence from a Meta-analysis of Studies Conducted in the Past 10 Years

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    OBJECTIVES: To investigate the association between EBF and educational status, household income, marital status, media exposure, and parity in Ethiopia.METHODS: PubMed, EMBASE, Web of Science, SCOPUS, CINAHL and WHO Global health library databases were searched using key terms for all studies published in English between September 2009 and March 2019. The methodological quality of studies was examined using the Newcastle-Ottawa Scale (NOS) for cross-sectional studies. To obtain the pooled odds ratio (OR), extracted data were fitted in a random-effects meta-analysis model. Statistical heterogeneity was quantified using Cochran's Q test, τ2, and I2 statistics. In addition, Jackknife sensitivity analysis, cumulative meta-analysis, and meta-regression analysis were conducted.RESULTS: Out of 553 studies retrieved, 31 studies fulfilled our inclusion criteria. Almost all included studies were conducted among mothers with newborn less than 23 months old. Maternal primary school education (OR 1.39; 95% CI 1.03-1.89; I2 = 86.11%), medium household income (OR 1.27; 95% CI 1.05-1.55; I2 = 60.9%) and being married (OR 1.39; 95% CI 1.05-1.83; I2 = 76.96%) were found to be significantly associated with EBF. We also observed an inverse dose-response relationship of EBF with educational status and income. However, EBF was not significantly associated with parity, media exposure, and paternal educational status.CONCLUSIONS: In this meta-analysis, we showed the relevant effect of maternal education, income, and marital status on EBF. Therefore, multifaceted, effective, and evidence-based efforts are needed to increase the national level of exclusive breastfeeding in Ethiopia.</p

    Breast and complementary feeding in Ethiopia:New national evidence from systematic review and meta-analyses of studies in the past 10 years

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    PURPOSE: The aim of this systematic review and meta-analysis was to provide a national estimate of breast and complementary feeding practices and its predictors in Ethiopia.METHODS: PubMed, SCOPUS, EMBASE, CINHAL, Web of Science and WHO Global Health Library electronic databases were searched for all available literature published until April 2018. Observational studies including cross-sectional, case-control and cohort studies were included. Newcastle-Ottawa Scale was used to assess the quality of studies. Heterogeneity of studies was quantified using Cochran's Q χ2 statistic and Higgins's method (I2). A meta-analysis using a weighted inverse variance method was performed. Subgroup analysis was carried out based on region and study area.RESULTS: In total, 70 studies that involved &gt; 55,000 women from nine regions and two chartered cities in Ethiopia were included. The pooled national prevalence for timely initiation of breastfeeding (TIBF), exclusive breastfeeding (EBF) and timely initiation of complementary feeding was 66.5%, 60.1% and 62.5%, respectively. Guidance and counselling on breastfeeding, vaginal delivery and health institution delivery significantly increased the odds of TIBF and EBF. In addition, TIBF significantly associated with high EBF practice. Maternal occupational status significantly associated with low EBF practice, but not TIBF.CONCLUSIONS: Based on the WHO standard, the current breast and complementary feeding practice in Ethiopia is good and improving. Integrated intervention is still required for further improvement and minimizing the effect of occupational status.</p

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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    © 2020 Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods: Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings: Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Funding: Bill & Melinda Gates Foundation

    Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

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    Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions. Funding: Bill & Melinda Gates Foundation

    Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

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    Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC
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