Global Patterns of Healthy Life Expectancy for Older Women
In: Journal of women & aging: the multidisciplinary quarterly of psychosocial practice, theory, and research, Band 14, Heft 1-2, S. 99-117
ISSN: 1540-7322
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In: Journal of women & aging: the multidisciplinary quarterly of psychosocial practice, theory, and research, Band 14, Heft 1-2, S. 99-117
ISSN: 1540-7322
In: Revue belge de musicologie vol. 69 (2015)
Many health problems require international action, but getting governments to agree on strategies for prevention or treatment is difficult. By making use of scientific evidence on the effects of tobacco, the member states of WHO have negotiated their first global health treaty. If the treaty can be implemented effectively, it could act as a possible model for tackling other health issues
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In: Population and development review, Band 19, Heft 4, S. 864
ISSN: 1728-4457
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 $1398 pooled health spending per capita (US$ 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. 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.
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In: Ethnicity & disease: an international journal on population differences in health and disease patterns, Band 29, Heft Suppl 1, S. 159-172
ISSN: 1945-0826
Objectives: Everyone deserves a long and healthy life, but in reality, health outcomes differ across populations. We use results from the Global Burden of Disease Study 2017 (GBD 2017) to report patterns in the burden of diseases, injuries, and risks at the global, regional, national, and subnational level, and by sociodemographic index (SDI), from 1990 to 2017.Design: GBD 2017 undertook a systematic analysis of published studies and available data providing information on prevalence, incidence, remission, and excess mortality. We computed prevalence, incidence, mortality, life expectancy, healthy life expectancy, years of life lost due to premature mortality, years lived with disability, and disability-adjusted life years with 95% uncertainty intervals for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries from 1990 to 2017. We also computed SDI, a summary indicator combining measures of income, education, and fertility.Results: There were wide disparities in the burden of disease by SDI, with smaller burdens in affluent countries and in specific regions within countries. Select diseases and risks, such as drug use disorders, high blood pressure, high body mass index, diet, high fasting plasma glucose, smoking, and alcohol use disorders warrant increased global attention and indicate a need for greater investment in prevention and treatment across the life course.Conclusions: Policymakers need a comprehensive picture of what risks and causes result in disability and death. The GBD provides the means to quantify health loss: these findings can be used to examine root causes of disparities and develop programs to improve health and health equity.Ethn Dis. 2019;29(Suppl 1): 159-172; doi:10.18865/ed.29.S1.159.
Cost-effectiveness analysis (CEA) is potentially an important aid to public health decision-making but, with some notable exceptions, its use and impact at the level of individual countries is limited. A number of potential reasons may account for this, among them technical shortcomings associated with the generation of current economic evidence, political expediency, social preferences and systemic barriers to implementation. As a form of sectoral CEA, Generalized CEA sets out to overcome a number of these barriers to the appropriate use of cost-effectiveness information at the regional and country level. Its application via WHO-CHOICE provides a new economic evidence base, as well as underlying methodological developments, concerning the cost-effectiveness of a range of health interventions for leading causes of, and risk factors for, disease. The estimated sub-regional costs and effects of different interventions provided by WHO-CHOICE can readily be tailored to the specific context of individual countries, for example by adjustment to the quantity and unit prices of intervention inputs (costs) or the coverage, efficacy and adherence rates of interventions (effectiveness). The potential usefulness of this information for health policy and planning is in assessing if current intervention strategies represent an efficient use of scarce resources, and which of the potential additional interventions that are not yet implemented, or not implemented fully, should be given priority on the grounds of cost-effectiveness. Health policy-makers and programme managers can use results from WHO-CHOICE as a valuable input into the planning and prioritization of services at national level, as well as a starting point for additional analyses of the trade-off between the efficiency of interventions in producing health and their impact on other key outcomes such as reducing inequalities and improving the health of the poor.
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In: Bulletin of the World Health Organization: the international journal of public health = Bulletin de l'Organisation Mondiale de la Santé, Band 92, Heft 1, S. 10-19C
ISSN: 1564-0604
BACKGROUND: Between 2012 and 2016, development assistance for HIV/AIDS decreased by 20·0%; domestic financing is therefore critical to sustaining the response to HIV/AIDS. To understand whether domestic resources could fill the financing gaps created by declines in development assistance, we aimed to track spending on HIV/AIDS and estimated the potential for governments to devote additional domestic funds to HIV/AIDS. METHODS: We extracted 8589 datapoints reporting spending on HIV/AIDS. We used spatiotemporal Gaussian process regression to estimate a complete time series of spending by domestic sources (government, prepaid private, and out-of-pocket) and spending category (prevention, and care and treatment) from 2000 to 2016 for 137 low-income and middle-income countries (LMICs). Development assistance data for HIV/AIDS were from Financing Global Health 2018, and HIV/AIDS prevalence, incidence, and mortality were from the Global Burden of Disease study 2017. We used stochastic frontier analysis to estimate potential additional government spending on HIV/AIDS, which was conditional on the current government health budget and other finance, economic, and contextual factors associated with HIV/AIDS spending. All spending estimates were reported in 2018 US$. FINDINGS: Between 2000 and 2016, total spending on HIV/AIDS in LMICs increased from $4·0 billion (95% uncertainty interval 2·9–6·0) to $19·9 billion (15·8–26·3), spending on HIV/AIDS prevention increased from $596 million (258 million to 1·3 billion) to $3·0 billion (1·5–5·8), and spending on HIV/AIDS care and treatment increased from $1·1 billion (458·1 million to 2·2 billion) to $7·2 billion (4·3–11·8). Over this time period, the share of resources sourced from development assistance increased from 33·2% (21·3–45·0) to 46·0% (34·2–57·0). Care and treatment spending per year on antiretroviral therapy varied across countries, with an IQR of $284–2915. An additional $12·1 billion (8·4–17·5) globally could be mobilised by governments of LMICs to finance the ...
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Although substantial reductions in under-5 mortality have been observed during the past 35 years, progress in the Eastern Mediterranean Region (EMR) has been uneven. This paper provides an overview of child mortality and morbidity in the EMR based on the Global Burden of Disease (GBD) study. We used GBD 2015 study results to explore under-5 mortality and morbidity in EMR countries. In 2015, 755,844 (95% uncertainty interval (UI) 712,064-801,565) children under 5 died in the EMR. In the early neonatal category, deaths in the EMR decreased by 22.4%, compared to 42.4% globally. The rate of years of life lost per 100,000 population under 5 decreased 54.38% from 177,537 (173,812-181,463) in 1990 to 80,985 (76,308-85,876) in 2015; the rate of years lived with disability decreased by 0.57% in the EMR compared to 9.97% globally. Our findings call for accelerated action to decrease child morbidity and mortality in the EMR. Governments and organizations should coordinate efforts to address this burden. Political commitment is needed to ensure that child health receives the resources needed to end preventable deaths.
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In: Ethnicity & disease: an international journal on population differences in health and disease patterns, Band 32, Heft 3, S. 193-202
ISSN: 1945-0826
Background: Race and ethnicity are major considerations in the incidence, management, and long-term outcome of ST-elevation myocardial infarction (STEMI) in the United States, but there is limited existing comparative data.Methods: We assembled a registry in a health system serving Bronx, NY of STEMI patients from 2008-2014 and analyzed differences in presentation, treatment and mortality between Hispanic/Latino (H/L), non-Hispanic Black (NHB) and non-Hispanic White (NHW). Upon discharge post-treatment for STEMI, all patients were followed for a median of 4.4 years (interquartile range 2.5, 6.0). Out of 966 STEMI patients, mean age was 61 years, 46% were H/L and 65% were male. H/Ls and NHBs had a higher prevalence of hypertension and diabetes mellitus than their NHW counterparts, coinciding with a lower socioeconomic status (SES).Results: The number of critically diseased vessels found at cardiac catheterization and mean troponin levels did not vary by race-ethnicity; neither did the adjusted hazard ratios (HR) for death. However, age-sex adjusted rates of general hospital readmission were higher in NHBs vs NHWs (HR 1.30, P=.03). Age-sex adjusted cardiovascular readmissions rates were higher in H/Ls than NHWs (HR 1.42, P=.03). Age-sex adjusted heart failure readmissions were increased for both H/Ls (HR 2.14, P=.01) and NHBs (HR 2.12, P=.02) over NHWs.Conclusions: Among STEMI patients, a higher prevalence of modifiable cardiovascular risk factors and a lower SES was seen among NHBs and H/Ls compared to NHWs. Despite similar coronary disease severity and in-hospital death, NHBs and H/Ls had a greater risk of general, cardiovascular and heart failure readmissions post-STEMI compared to NHWs.Ethn Dis. 2022;32(3):193- 202; doi:10.18865/ed.32.3.193
Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9.3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17.2 billion, 95% uncertainty interval [UI] 15.4-19.2 billion) and diarrhoeal diseases (2.39 billion, 2.30-2.50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2.36 billion (2.35-2.37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20-30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available.
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Background Established in 2000, Millennium Development Goal 4 (MDG4) catalysed extraordinary political, financial, and social commitments to reduce under-5 mortality by two-thirds between 1990 and 2015. At the country level, the pace of progress in improving child survival has varied markedly, highlighting a crucial need to further examine potential drivers of accelerated or slowed decreases in child mortality. The Global Burden of Disease 2015 Study (GBD 2015) provides an analytical framework to comprehensively assess these trends for under-5 mortality, age-specific and cause-specific mortality among children under 5 years, and stillbirths by geography over time. Methods Drawing from analytical approaches developed and refined in previous iterations of the GBD study, we generated updated estimates of child mortality by age group (neonatal, post-neonatal, ages 1–4 years, and under 5) for 195 countries and territories and selected subnational geographies, from 1980–2015. We also estimated numbers and rates of stillbirths for these geographies and years. Gaussian process regression with data source adjustments for sampling and non-sampling bias was applied to synthesise input data for under-5 mortality for each geography. Age-specific mortality estimates were generated through a two-stage age–sex splitting process, and stillbirth estimates were produced with a mixed-effects model, which accounted for variable stillbirth definitions and data source-specific biases. For GBD 2015, we did a series of novel analyses to systematically quantify the drivers of trends in child mortality across geographies. First, we assessed observed and expected levels and annualised rates of decrease for under-5 mortality and stillbirths as they related to the Soci-demographic Index (SDI). Second, we examined the ratio of recorded and expected levels of child mortality, on the basis of SDI, across geographies, as well as differences in recorded and expected annualised rates of change for under-5 mortality. Third, we analysed levels and cause compositions of under-5 mortality, across time and geographies, as they related to rising SDI. Finally, we decomposed the changes in under-5 mortality to changes in SDI at the global level, as well as changes in leading causes of under-5 deaths for countries and territories. We documented each step of the GBD 2015 child mortality estimation process, as well as data sources, in accordance with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, 5·8 million (95% uncertainty interval [UI] 5·7–6·0) children younger than 5 years died in 2015, representing a 52·0% (95% UI 50·7–53·3) decrease in the number of under-5 deaths since 1990. Neonatal deaths and stillbirths fell at a slower pace since 1990, decreasing by 42·4% (41·3–43·6) to 2·6 million (2·6–2·7) neonatal deaths and 47·0% (35·1–57·0) to 2·1 million (1·8-2·5) stillbirths in 2015. Between 1990 and 2015, global under-5 mortality decreased at an annualised rate of decrease of 3·0% (2·6–3·3), falling short of the 4·4% annualised rate of decrease required to achieve MDG4. During this time, 58 countries met or exceeded the pace of progress required to meet MDG4. Between 2000, the year MDG4 was formally enacted, and 2015, 28 additional countries that did not achieve the 4·4% rate of decrease from 1990 met the MDG4 pace of decrease. However, absolute levels of under-5 mortality remained high in many countries, with 11 countries still recording rates exceeding 100 per 1000 livebirths in 2015. Marked decreases in under-5 deaths due to a number of communicable diseases, including lower respiratory infections, diarrhoeal diseases, measles, and malaria, accounted for much of the progress in lowering overall under-5 mortality in low-income countries. Compared with gains achieved for infectious diseases and nutritional deficiencies, the persisting toll of neonatal conditions and congenital anomalies on child survival became evident, especially in low-income and low-middle-income countries. We found sizeable heterogeneities in comparing observed and expected rates of under-5 mortality, as well as differences in observed and expected rates of change for under-5 mortality. At the global level, we recorded a divergence in observed and expected levels of under-5 mortality starting in 2000, with the observed trend falling much faster than what was expected based on SDI through 2015. Between 2000 and 2015, the world recorded 10·3 million fewer under-5 deaths than expected on the basis of improving SDI alone. Interpretation Gains in child survival have been large, widespread, and in many places in the world, faster than what was anticipated based on improving levels of development. Yet some countries, particularly in sub-Saharan Africa, still had high rates of under-5 mortality in 2015. Unless these countries are able to accelerate reductions in child deaths at an extraordinary pace, their achievement of proposed SDG targets is unlikely. Improving the evidence base on drivers that might hasten the pace of progress for child survival, ranging from cost-effective intervention packages to innovative financing mechanisms, is vital to charting the pathways for ultimately ending preventable child deaths by 2030. Funding Bill & Melinda Gates Foundation.
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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 $1398 pooled health spending per capita (US$ 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. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.
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In: Bulletin of the World Health Organization: the international journal of public health = Bulletin de l'Organisation Mondiale de la Santé, Band 89, Heft 3, S. 172-183
ISSN: 1564-0604