Expands on previous analyses of the contribution of illicit drug use to the global burden of disease (GBD). Conducts the first assessment of the global burden of cannabis (e.g. marijuana, hashish and ...hash oil) dependence. Outlines the methodology used to estimate burden for this disorder specifically. Assembles data on the incidence and prevalence of cannabis use and dependence into a comprehensive disease model which adjusts for known sources of variability between studies. Investigates trends in the burden of cannabis dependence. Investigates the model used in GBD 2010 to estimate the global burden of disease attributable to cannabis dependence as a risk factor for schizophrenia. Looks at the effect on mortality. Includes data from New Zealand. Source: National Library of New Zealand Te Puna Matauranga o Aotearoa, licensed by the Department of Internal Affairs for re-use under the Creative Commons Attribution 3.0 New Zealand Licence.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Summary Background We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) to estimate the burden of disease attributable to mental and substance use ...disorders in terms of disability-adjusted life years (DALYs), years of life lost to premature mortality (YLLs), and years lived with disability (YLDs). Methods For each of the 20 mental and substance use disorders included in GBD 2010, we systematically reviewed epidemiological data and used a Bayesian meta-regression tool, DisMod-MR, to model prevalence by age, sex, country, region, and year. We obtained disability weights from representative community surveys and an internet-based survey to calculate YLDs. We calculated premature mortality as YLLs from cause of death estimates for 1980–2010 for 20 age groups, both sexes, and 187 countries. We derived DALYs from the sum of YLDs and YLLs. We adjusted burden estimates for comorbidity and present them with 95% uncertainty intervals. Findings In 2010, mental and substance use disorders accounted for 183·9 million DALYs (95% UI 153·5 million–216·7 million), or 7·4% (6·2–8·6) of all DALYs worldwide. Such disorders accounted for 8·6 million YLLs (6·5 million–12·1 million; 0·5% 0·4–0·7 of all YLLs) and 175·3 million YLDs (144·5 million–207·8 million; 22·9% 18·6–27·2 of all YLDs). Mental and substance use disorders were the leading cause of YLDs worldwide. Depressive disorders accounted for 40·5% (31·7–49·2) of DALYs caused by mental and substance use disorders, with anxiety disorders accounting for 14·6% (11·2–18·4), illicit drug use disorders for 10·9% (8·9–13·2), alcohol use disorders for 9·6% (7·7–11·8), schizophrenia for 7·4% (5·0–9·8), bipolar disorder for 7·0% (4·4–10·3), pervasive developmental disorders for 4·2% (3·2–5·3), childhood behavioural disorders for 3·4% (2·2–4·7), and eating disorders for 1·2% (0·9–1·5). DALYs varied by age and sex, with the highest proportion of total DALYs occurring in people aged 10–29 years. The burden of mental and substance use disorders increased by 37·6% between 1990 and 2010, which for most disorders was driven by population growth and ageing. Interpretation Despite the apparently small contribution of YLLs—with deaths in people with mental disorders coded to the physical cause of death and suicide coded to the category of injuries under self-harm—our findings show the striking and growing challenge that these disorders pose for health systems in developed and developing regions. In view of the magnitude of their contribution, improvement in population health is only possible if countries make the prevention and treatment of mental and substance use disorders a public health priority. Funding Queensland Department of Health, National Health and Medical Research Council of Australia, National Drug and Alcohol Research Centre-University of New South Wales, Bill & Melinda Gates Foundation, University of Toronto, Technische Universität, Ontario Ministry of Health and Long Term Care, and the US National Institute of Alcohol Abuse and Alcoholism.
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In efforts to inform public health decision makers, the Global Burden of Diseases, Injuries, and Risk Factors 2010 (GBD2010) Study aims to estimate the burden of disease using available parameters. ...This study was conducted to collect and analyze available prevalence data to be used for estimating the hepatitis C virus (HCV) burden of disease. In this systematic review, antibody to HCV (anti‐HCV) seroprevalence data from 232 articles were pooled to estimate age‐specific seroprevalence curves in 1990 and 2005, and to produce age‐standardized prevalence estimates for each of 21 GBD regions using a model‐based meta‐analysis. This review finds that globally the prevalence and number of people with anti‐HCV has increased from 2.3% (95% uncertainty interval UI: 2.1%‐2.5%) to 2.8% (95% UI: 2.6%‐3.1%) and >122 million to >185 million between 1990 and 2005. Central and East Asia and North Africa/Middle East are estimated to have high prevalence (>3.5%); South and Southeast Asia, sub‐Saharan Africa, Andean, Central, and Southern Latin America, Caribbean, Oceania, Australasia, and Central, Eastern, and Western Europe have moderate prevalence (1.5%‐3.5%); whereas Asia Pacific, Tropical Latin America, and North America have low prevalence (<1.5%). Conclusion: The high prevalence of global HCV infection necessitates renewed efforts in primary prevention, including vaccine development, as well as new approaches to secondary and tertiary prevention to reduce the burden of chronic liver disease and to improve survival for those who already have evidence of liver disease. (HEPATOLOGY 2013)
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Verbal autopsy (VA) is a practical method for determining probable causes of death at the population level in places where systems for medical certification of cause of death are weak. VA methods ...suitable for use in routine settings, such as civil registration and vital statistics (CRVS) systems, have developed rapidly in the last decade. These developments have been part of a growing global momentum to strengthen CRVS systems in low-income countries. With this momentum have come pressure for continued research and development of VA methods and the need for a single standard VA instrument on which multiple automated diagnostic methods can be developed.
In 2016, partners harmonized a WHO VA standard instrument that fully incorporates the indicators necessary to run currently available automated diagnostic algorithms. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality. This VA instrument offers the opportunity to harmonize the automated diagnostic algorithms in the future.
Despite all improvements in design and technology, VA is only recommended where medical certification of cause of death is not possible. The method can nevertheless provide sufficient information to guide public health priorities in communities in which physician certification of deaths is largely unavailable. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Summary Background Healthy life expectancy (HALE) summarises mortality and non-fatal outcomes in a single measure of average population health. It has been used to compare health between countries, ...or to measure changes over time. These comparisons can inform policy questions that depend on how morbidity changes as mortality decreases. We characterise current HALE and changes over the past two decades in 187 countries. Methods Using inputs from the Global Burden of Disease Study (GBD) 2010, we assessed HALE for 1990 and 2010. We calculated HALE with life table methods, incorporating estimates of average health over each age interval. Inputs from GBD 2010 included age-specific information for mortality rates and prevalence of 1160 sequelae, and disability weights associated with 220 distinct health states relating to these sequelae. We computed estimates of average overall health for each age group, adjusting for comorbidity with a Monte Carlo simulation method to capture how multiple morbidities can combine in an individual. We incorporated these estimates in the life table by the Sullivan method to produce HALE estimates for each population defined by sex, country, and year. We estimated the contributions of changes in child mortality, adult mortality, and disability to overall change in population health between 1990 and 2010. Findings In 2010, global male HALE at birth was 59·0 years (uncertainty interval 57·3–60·6) and global female HALE at birth was 63·2 years (61·4–65·0). HALE increased more slowly than did life expectancy over the past 20 years, with each 1-year increase in life expectancy at birth associated with a 10-month increase in HALE. Across countries in 2010, male HALE at birth ranged from 27·8 years (17·2–36·5) in Haiti, to 70·6 years (68·6–72·2) in Japan. Female HALE at birth ranged from 37·1 years (26·8–43·8) in Haiti, to 75·5 years (73·3–77·3) in Japan. Between 1990 and 2010, male HALE increased by 5 years or more in 48 countries compared with 43 countries for female HALE, while male HALE decreased in 22 countries and 11 for female HALE. Between countries and over time, life expectancy was strongly and positively related to number of years lost to disability. This relation was consistent between sexes, in cross-sectional and longitudinal analysis, and when assessed at birth, or at age 50 years. Changes in disability had small effects on changes in HALE compared with changes in mortality. Interpretation HALE differs substantially between countries. As life expectancy has increased, the number of healthy years lost to disability has also increased in most countries, consistent with the expansion of morbidity hypothesis, which has implications for health planning and health-care expenditure. Compared with substantial progress in reduction of mortality over the past two decades, relatively little progress has been made in reduction of the overall effect of non-fatal disease and injury on population health. HALE is an attractive indicator for monitoring health post-2015. Funding The Bill & Melinda Gates Foundation
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Abraham D. Flaxman and Theo Vos of the Institute for Health Metrics and Evaluation, University of Washington, discuss near-term applications for ML in population health and name their priorities for ...ongoing ML development.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aims
To estimate the prevalence and burden of disease attributable to opioid dependence globally, regionally and at country level.
Methods
Multiple search strategies: (i) peer‐reviewed literature ...searches; (ii) systematic searches of online databases; (iii) internet searches; (iv) consultation and feedback from experts. Culling and data extraction followed protocols. DisMod‐MR, the latest version of the generic disease modelling system, a Bayesian meta‐regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. Disability weight for opioid dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs). Opioid dependence premature mortality was computed as years of life lost (YLLs) and summed with YLDs to calculate disability‐adjusted life years (DALYs).
Results
There were 15.5 million opioid‐dependent people globally in 2010 0.22%, 95% uncertainty interval (UI) = 0.20–0.25%. Age‐standardized prevalence was higher in males (0.30%, 95% UI = 0.27–0.35%) than females (0.14%, 95% UI = 0.12–0.16%), and peaked at 25–29 years. Prevalence was higher than the global pooled prevalence in Australasia (0.46%, 95% UI = 0.41–0.53%), western Europe (0.35%, 95% UI = 0.32–0.39) and North America (0.30%, 95% UI = 0.25–0.36). Opioid dependence was estimated to account for 9.2 million DALYs globally (0.37% of global DALYs) in 2010, a 73% increase on DALYs estimated in 1990. Regions with the highest opioid dependence DALY rates were North America (292.1 per 100 000), eastern Europe (288.4 per 100 000), Australasia (278.6 per 100 000) and southern sub‐Saharan Africa (263.5 per 100 000). The contribution of YLLs to opioid dependence burden was particularly high in North America, eastern Europe and southern sub‐Saharan Africa.
Conclusion
Opioid dependence is a substantial contributor to the global disease burden; its contribution to premature mortality (relative to prevalence) varies geographically, with North America, eastern Europe and southern sub‐Saharan Africa most strongly affected.
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BFBNIB, DOBA, FSPLJ, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
IMPORTANCE: US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how ...these amounts have changed over time. OBJECTIVE: To estimate US spending on health care according to 3 types of payers (public insurance including Medicare, Medicaid, and other government programs, private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. DESIGN AND SETTING: Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. EXPOSURES: Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. MAIN OUTCOMES AND MEASURES: National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. RESULTS: Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product GDP; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending (estimated at $129.8 billion 95% CI, $116.3-$149.7 billion) and most had private insurance (56.4% 95% CI, 52.6%-59.3%). Diabetes accounted for the third highest amount of the health care spending (estimated at $111.2 billion 95% CI, $105.7-$115.9 billion) and most had public insurance (49.8% 95% CI, 44.4%-56.0%). Other conditions estimated to have substantial health care spending in 2016 were ischemic heart disease ($89.3 billion 95% CI, $81.1-$95.5 billion), falls ($87.4 billion 95% CI, $75.0-$100.1 billion), urinary diseases ($86.0 billion 95% CI, $76.3-$95.9 billion), skin and subcutaneous diseases ($85.0 billion 95% CI, $80.5-$90.2 billion), osteoarthritis ($80.0 billion 95% CI, $72.2-$86.1 billion), dementias ($79.2 billion 95% CI, $67.6-$90.8 billion), and hypertension ($79.0 billion 95% CI, $72.6-$86.8 billion). The conditions with the highest spending varied by type of payer, age, sex, type of care, and year. After adjusting for changes in inflation, population size, and age groups, public insurance spending was estimated to have increased at an annualized rate of 2.9% (95% CI, 2.9%-2.9%); private insurance, 2.6% (95% CI, 2.6%-2.6%); and out-of-pocket payments, 1.1% (95% CI, 1.0%-1.1%). CONCLUSIONS AND RELEVANCE: Estimates of US spending on health care showed substantial increases from 1996 through 2016, with the highest increases in population-adjusted spending by public insurance. Although spending on low back and neck pain, other musculoskeletal disorders, and diabetes accounted for the highest amounts of spending, the payers and the rates of change in annual spending growth rates varied considerably.
A major challenge in monitoring universal health coverage (UHC) is identifying an indicator that can adequately capture the multiple components underlying the UHC initiative. Effective coverage, ...which unites individual and intervention characteristics into a single metric, offers a direct and flexible means to measure health system performance at different levels. We view effective coverage as a relevant and actionable metric for tracking progress towards achieving UHC. In this paper, we review the concept of effective coverage and delineate the three components of the metric - need, use, and quality - using several examples. Further, we explain how the metric can be used for monitoring interventions at both local and global levels. We also discuss the ways that current health information systems can support generating estimates of effective coverage. We conclude by recognizing some of the challenges associated with producing estimates of effective coverage. Despite these challenges, effective coverage is a powerful metric that can provide a more nuanced understanding of whether, and how well, a health system is delivering services to its populations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Summary Background Previous assessments have highlighted that less than a quarter of countries are on track to achieve Millennium Development Goal 4 (MDG 4), which calls for a two-thirds reduction in ...mortality in children younger than 5 years between 1990 and 2015. In view of policy initiatives and investments made since 2000, it is important to see if there is acceleration towards the MDG 4 target. We assessed levels and trends in child mortality for 187 countries from 1970 to 2010. Methods We compiled a database of 16 174 measurements of mortality in children younger than 5 years for 187 countries from 1970 to 2009, by use of data from all available sources, including vital registration systems, summary birth histories in censuses and surveys, and complete birth histories. We used Gaussian process regression to generate estimates of the probability of death between birth and age 5 years. This is the first study that uses Gaussian process regression to estimate child mortality, and this technique has better out-of-sample predictive validity than do previous methods and captures uncertainty caused by sampling and non-sampling error across data types. Neonatal, postneonatal, and childhood mortality was estimated from mortality in children younger than 5 years by use of the 1760 measurements from vital registration systems and complete birth histories that contained specific information about neonatal and postneonatal mortality. Findings Worldwide mortality in children younger than 5 years has dropped from 11·9 million deaths in 1990 to 7·7 million deaths in 2010, consisting of 3·1 million neonatal deaths, 2·3 million postneonatal deaths, and 2·3 million childhood deaths (deaths in children aged 1–4 years). 33·0% of deaths in children younger than 5 years occur in south Asia and 49·6% occur in sub-Saharan Africa, with less than 1% of deaths occurring in high-income countries. Across 21 regions of the world, rates of neonatal, postneonatal, and childhood mortality are declining. The global decline from 1990 to 2010 is 2·1% per year for neonatal mortality, 2·3% for postneonatal mortality, and 2·2% for childhood mortality. In 13 regions of the world, including all regions in sub-Saharan Africa, there is evidence of accelerating declines from 2000 to 2010 compared with 1990 to 2000. Within sub-Saharan Africa, rates of decline have increased by more than 1% in Angola, Botswana, Cameroon, Congo, Democratic Republic of the Congo, Kenya, Lesotho, Liberia, Rwanda, Senegal, Sierra Leone, Swaziland, and The Gambia. Interpretation Robust measurement of mortality in children younger than 5 years shows that accelerating declines are occurring in several low-income countries. These positive developments deserve attention and might need enhanced policy attention and resources. Funding Bill & Melinda Gates Foundation.
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