Quality-Adjusted Life Years

BackgroundEnding the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally.MethodsWe estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available.FindingsGlobally in 2019, 1·14 billion (95% uncertainty interval 1·13-1·16) individuals were current smokers, who consumed 7·41 trillion (7·11-7·74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27·5% [26·5-28·5] reduction) and females (37·7% [35·4-39·9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0·99 billion (0·98-1·00) in 1990. Globally in 2019, smoking tobacco use accounted for 7·69 million (7·16-8·20) deaths and 200 million (185-214) disability-adjusted life-years, and was the leading risk factor for death among males (20·2% [19·3-21·1] of male deaths). 6·68 million [86·9%] of 7·69 million deaths attributable to smoking tobacco use were among current smokers.InterpretationIn the absence of intervention, the annual toll of 7·69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a clear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens.FundingBloomberg Philanthropies and the Bill & Melinda Gates Foundation.

Background and purposePrediction of stroke impact provides essential information for healthcare planning and priority setting. We aim to estimate 30-year projections of stroke epidemiology in the European Union using multiple modeling approaches.MethodsData on stroke incidence, prevalence, deaths, and disability-adjusted life years in the European Union between 1990 and 2017 were obtained from the global burden of disease study. Their trends over time were modeled using 3 modeling strategies: linear, Poisson, and exponential regressions-adjusted for the gross domestic product per capita, which reflects the impact of economic development on health status. We used the Akaike information criterion for model selection. The 30-year projections up to 2047 were estimated using the best fitting models, with inputs on population projections from the United Nations and gross domestic product per capita prospects from the World Bank. The technique was applied separately by age-sex-country groups for each stroke measure.ResultsIn 2017, there were 1.12 million incident strokes in the European Union, 9.53 million stroke survivors, 0.46 million deaths, and 7.06 million disability-adjusted life years lost because of stroke. By 2047, we estimated an additional 40 000 incident strokes (+3%) and 2.58 million prevalent cases (+27%). Conversely, 80 000 fewer deaths (-17%) and 2.31 million fewer disability-adjusted life years lost (-33%) are projected. The largest increase in the age-adjusted incidence and prevalence rates are expected in Lithuania (average annual percentage change, 0.48% and 0.7% respectively), and the greatest reductions in Portugal (-1.57% and -1.3%). Average annual percentage change in mortality rates will range from -2.86% (Estonia) to -0.08% (Lithuania), and disability-adjusted life years' from -2.77% (Estonia) to -0.23% (Romania).ConclusionsThe number of people living with stroke is estimated to increase by 27% between 2017 and 2047 in the European Union, mainly because of population ageing and improved survival rates. Variations are expected to persist between countries showing opportunities for improvements in prevention and case management particularly in Eastern Europe.

BackgroundThe past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030.Methods16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort.FindingsWe estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52-88) deaths between 2000 and 2030, of which 37 million (30-48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36-58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52-66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93-150) deaths will be averted by vaccination, of which 58 million (39-76) are due to measles vaccination and 38 million (25-52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59-81) reduction in lifetime mortality in the 2019 birth cohort.InterpretationIncreases in vaccine coverage and the introduction of new vaccines into LMICs have had a major impact in reducing mortality. These public health gains are predicted to increase in coming decades if progress in increasing coverage is sustained.FundingGavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.

ObjectivesTo examine how using binary rather than continuous adjustments for health-related quality of life (HRQOL) influences the estimated magnitude of social inequality in lifetime health and to explore the implications for equity weighting in distributional cost-effectiveness analysis.MethodsWe used 2018 Health Survey for England and UK Office for National Statistics mortality and population data to compare health distributions in quality-adjusted life expectancy at birth (EuroQol 5-Dimension 5-Level instrument [EQ-5D-5L], 2018 value set), disability-free life expectancy (limiting long-term illness), and healthy life expectancy (self-assessed health), across neighborhood deprivation quintiles. Indirect equity weights were derived using Atkinson inequality aversion parameters, and implied mean HRQOL scores were cross-tabulated by age and deprivation to understand discrepancies.ResultsContinuous adjustment yielded substantially smaller inequality gaps between the most and least deprived quintile groups than binary adjustments: quality-adjusted life expectancy gap 11.25, disability-free life expectancy gap 16.00, healthy life expectancy gap 18.53. Equity weights based on binary adjustments were substantially higher, especially at higher levels of health inequality aversion (4 times higher at Atkinson parameter 10). Social group HRQOL differences reflected both increased prevalence of morbidity and increased HRQOL burden of morbidity. However, the morbidity prevalence differential between groups was larger than the HRQOL differential.ConclusionsDisability-free and healthy life expectancy yield larger estimated magnitudes of health inequality than quality-adjusted life expectancy. This is due to their binary scaling, which implicitly assigns a HRQOL value of 0 (as bad as death) to disability or non-good health. A simple adjustment to narrow both ends of the binary scale renders the approaches more comparable.