Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study 201

Global, regional, and national burden of respiratory tract cancers and associated risk factors from 1990 to 2019 a systematic analysis for the Global Burden of Disease Study 2019

BackgroundPrevention, control, and treatment of respiratory tract cancers are important steps towards achieving target 3.4 of the UN Sustainable Development Goals (SDGs)-a one-third reduction in premature mortality due to non-communicable diseases by 2030. We aimed to provide global, regional, and national estimates of the burden of tracheal, bronchus, and lung cancer and larynx cancer and their attributable risks from 1990 to 2019.MethodsBased on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 methodology, we evaluated the incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs) of respiratory tract cancers (ie, tracheal, bronchus, and lung cancer and larynx cancer). Deaths from tracheal, bronchus, and lung cancer and larynx cancer attributable to each risk factor were estimated on the basis of risk exposure, relative risks, and the theoretical minimum risk exposure level input from 204 countries and territories, stratified by sex and Socio-demographic Index (SDI). Trends were estimated from 1990 to 2019, with an emphasis on the 2010-19 period.FindingsGlobally, there were 2·26 million (95% uncertainty interval 2·07 to 2·45) new cases of tracheal, bronchus, and lung cancer, and 2·04 million (1·88 to 2·19) deaths and 45·9 million (42·3 to 49·3) DALYs due to tracheal, bronchus, and lung cancer in 2019. There were 209 000 (194 000 to 225 000) new cases of larynx cancer, and 123 000 (115 000 to 133 000) deaths and 3·26 million (3·03 to 3·51) DALYs due to larynx cancer globally in 2019. From 2010 to 2019, the number of new tracheal, bronchus, and lung cancer cases increased by 23·3% (12·9 to 33·6) globally and the number of larynx cancer cases increased by 24·7% (16·0 to 34·1) globally. Global age-standardised incidence rates of tracheal, bronchus, and lung cancer decreased by 7·4% (-16·8 to 1·6) and age-standardised incidence rates of larynx cancer decreased by 3·0% (-10·5 to 5·0) in males over the past decade; however, during the same period, age-standardised incidence rates in females increased by 0·9% (-8·2 to 10·2) for tracheal, bronchus, and lung cancer and decreased by 0·5% (-8·4 to 8·1) for larynx cancer. Furthermore, although age-standardised incidence and death rates declined in both sexes combined from 2010 to 2019 at the global level for tracheal, bronchus, lung and larynx cancers, some locations had rising rates, particularly those on the lower end of the SDI range. Smoking contributed to an estimated 64·2% (61·9-66·4) of all deaths from tracheal, bronchus, and lung cancer and 63·4% (56·3-69·3) of all deaths from larynx cancer in 2019. For males and for both sexes combined, smoking was the leading specific risk factor for age-standardised deaths from tracheal, bronchus, and lung cancer per 100 000 in all SDI quintiles and GBD regions in 2019. However, among females, household air pollution from solid fuels was the leading specific risk factor in the low SDI quintile and in three GBD regions (central, eastern, and western sub-Saharan Africa) in 2019.InterpretationThe numbers of incident cases and deaths from tracheal, bronchus, and lung cancer and larynx cancer increased globally during the past decade. Even more concerning, age-standardised incidence and death rates due to tracheal, bronchus, lung cancer and larynx cancer increased in some populations-namely, in the lower SDI quintiles and among females. Preventive measures such as smoking control interventions, air quality management programmes focused on major air pollution sources, and widespread access to clean energy should be prioritised in these settings

The global epidemiology and health burden of the autism spectrum: findings from the Global Burden of Disease Study 2021

Background: High-quality estimates of the epidemiology of the autism spectrum and the health needs of autistic people are necessary for service planners and resource allocators. Here we present the global prevalence and health burden of autism spectrum disorder from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 following improvements to the epidemiological data and burden estimation methods. Methods: For GBD 2021, a systematic literature review involving searches in PubMed, Embase, PsycINFO, the Global Health Data Exchange, and consultation with experts identified data on the epidemiology of autism spectrum disorder. Eligible data were used to estimate prevalence via a Bayesian meta-regression tool (DisMod-MR 2.1). Modelled prevalence and disability weights were used to estimate health burden in years lived with disability (YLDs) as the measure of non-fatal health burden and disability-adjusted life-years (DALYs) as the measure of overall health burden. Data by ethnicity were not available. People with lived experience of autism were involved in the design, preparation, interpretation, and writing of this Article. Findings: An estimated 61·8 million (95% uncertainty interval 52·1–72·7) individuals (one in every 127 people) were on the autism spectrum globally in 2021. The global age-standardised prevalence was 788·3 (663·8–927·2) per 100 000 people, equivalent to 1064·7 (898·5–1245·7) autistic males per 100 000 males and 508·1 (424·6–604·3) autistic females per 100 000 females. Autism spectrum disorder accounted for 11·5 million (7·8–16·3) DALYs, equivalent to 147·6 (100·2–208·2) DALYs per 100 000 people (age-standardised) globally. At the super-region level, age-standardised DALY rates ranged from 126·5 (86·0–178·0) per 100 000 people in southeast Asia, east Asia, and Oceania to 204·1 (140·7–284·7) per 100 000 people in the high-income super-region. DALYs were evident across the lifespan, emerging for children younger than age 5 years (169·2 [115·0–237·4] DALYs per 100 000 people) and decreasing with age (163·4 [110·6–229·8] DALYs per 100 000 people younger than 20 years and 137·7 [93·9–194·5] DALYs per 100 000 people aged 20 years and older). Autism spectrum disorder was ranked within the top-ten causes of non-fatal health burden for people younger than 20 years. Interpretation: The high prevalence and high rank for non-fatal health burden of autism spectrum disorder in people younger than 20 years underscore the importance of early detection and support to autistic young people and their caregivers globally. Work to improve the precision and global representation of our findings is required, starting with better global coverage of epidemiological data so that geographical variations can be better ascertained. The work presented here can guide future research efforts, and importantly, decisions concerning allocation of health services that better address the needs of all autistic individuals. Funding: Queensland Health and the Bill & Melinda Gates Foundation.</p

The Burden of Dementia due to Down Syndrome, Parkinson's Disease, Stroke, and Traumatic Brain Injury: A Systematic Analysis for the Global Burden of Disease Study 2019

Background: In light of the increasing trend in the global number of individuals affected by dementia and the lack of any available disease-modifying therapies, it is necessary to fully understand and quantify the global burden of dementia. This work aimed to estimate the proportion of dementia due to Down syndrome, Parkinson’s disease, clinical stroke, and traumatic brain injury (TBI), globally and by world region, in order to better understand the contribution of clinical diseases to dementia prevalence. Methods: Through literature review, we obtained data on the relative risk of dementia with each condition and estimated relative risks by age using a Bayesian meta-regression tool. We then calculated population attributable fractions (PAFs), or the proportion of dementia attributable to each condition, using the estimates of relative risk and prevalence estimates for each condition from the Global Burden of Disease Study 2019. Finally, we multiplied these estimates by dementia prevalence to calculate the number of dementia cases attributable to each condition. Findings: For each clinical condition, the relative risk of dementia decreased with age. Relative risks were highest for Down syndrome, followed by Parkinson’s disease, stroke, and TBI. However, due to the high prevalence of stroke, the PAF for dementia due to stroke was highest. Together, Down syndrome, Parkinson’s disease, stroke, and TBI explained 10.0% (95% UI: 6.0–16.5) of the global prevalence of dementia. Interpretation: Ten percent of dementia prevalence globally could be explained by Down syndrome, Parkinson’s disease, stroke, and TBI. The quantification of the proportion of dementia attributable to these 4 conditions constitutes a small contribution to our overall understanding of what causes dementia. However, epidemiological research into modifiable risk factors as well as basic science research focused on elucidating intervention approaches to prevent or delay the neuropathological changes that commonly characterize dementia will be critically important in future efforts to prevent and treat disease

Mapping disparities in education across low- and middle-income countries

Educational attainment is an important social determinant of maternal, newborn, and child health1–3. As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting4–6. The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness7,8; however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health9–11. Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but—to our knowledge—no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries12–14. By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations

Mapping child growth failure across low- and middle-income countries

Childhood malnutrition is associated with high morbidity and mortality globally1. Undernourished children are more likely to experience cognitive, physical, and metabolic developmental impairments that can lead to later cardiovascular disease, reduced intellectual ability and school attainment, and reduced economic productivity in adulthood2. Child growth failure (CGF), expressed as stunting, wasting, and underweight in children under five years of age (0–59 months), is a specific subset of undernutrition characterized by insufficient height or weight against age-specific growth reference standards3–5. The prevalence of stunting, wasting, or underweight in children under five is the proportion of children with a height-for-age, weight-for-height, or weight-for-age z-score, respectively, that is more than two standard deviations below the World Health Organization’s median growth reference standards for a healthy population6. Subnational estimates of CGF report substantial heterogeneity within countries, but are available primarily at the first administrative level (for example, states or provinces)7; the uneven geographical distribution of CGF has motivated further calls for assessments that can match the local scale of many public health programmes8. Building from our previous work mapping CGF in Africa9, here we provide the first, to our knowledge, mapped high-spatial-resolution estimates of CGF indicators from 2000 to 2017 across 105 low- and middle-income countries (LMICs), where 99% of affected children live1, aggregated to policy-relevant first and second (for example, districts or counties) administrative-level units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the ambitious World Health Organization Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and progress exist across and within countries; our maps identify high-prevalence areas even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where the highest-need populations reside, these geospatial estimates can support policy-makers in planning interventions that are adapted locally and in efficiently directing resources towards reducing CGF and its health implications

Additional file 3 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Additional file 3: Supplemental figures.Figure S1. Prevalence of male circumcision. Figure S2. Prevalence of signs and symptoms of sexually transmitted infections. Figure S3. Prevalence of marriage or living as married. Figure S4. Prevalence of partner living elsewhere among females. Figure S5. Prevalence of condom use during most recent sexual encounter. Figure S6. Prevalence of sexual activity among young females. Figure S7. Prevalence of multiple partners among males in the past year. Figure S8. Prevalence of multiple partners among females in the past year. Figure S9. HIV prevalence predictions from the boosted regression tree model. Figure S10. HIV prevalence predictions from the generalized additive model. Figure S11. HIV prevalence predictions from the lasso regression model. Figure S12. Modeling regions. Figure S13. Age- and sex-specific vs. adult prevalence modeling. Figure S14. Data sensitivity. Figure S15. Model specification validation. Figure S16. Modeled and re-aggregated adult prevalence comparison. Figure S17. HIV prevalence raking factors for males. Figure S18. HIV prevalence raking factors for females. Figure S19. Age-specific HIV prevalence in males, 2000. Figure S20. Age-specific HIV prevalence in females, 2000. Figure S21. Age-specific HIV prevalence in males, 2005. Figure S22. Age-specific HIV prevalence in females, 2005. Figure S23. Age-specific HIV prevalence in males, 2010. Figure S24. Age-specific HIV prevalence in females, 2010. Figure S25. Age-specific HIV prevalence in males, 2018. Figure S26. Age-specific HIV prevalence in females, 2018. Figure S27. Age-specific uncertainty interval range estimates in males, 2000. Figure S28. Age-specific uncertainty interval range estimates in females, 2000. Figure S29. Age-specific uncertainty interval range estimates in males, 2005. Figure S30. Age-specific uncertainty interval range estimates in females, 2005. Figure S31. Age-specific uncertainty interval range estimates in males, 2010. Figure S32. Age-specific uncertainty interval range estimates in females, 2010. Figure S33. Age-specific uncertainty interval range estimates in males, 2018. Figure S34. Age-specific uncertainty interval range estimates in females, 2018. Figure S35. Change in HIV prevalence in males, 2000-2005. Figure S36. Change in HIV prevalence in females, 2000-2005. Figure S37. Change in HIV prevalence in males, 2005-2010. Figure S38. Change in HIV prevalence in females, 2005-2010. Figure S39. Change in HIV prevalence in males, 2010-2018. Figure S40. Change in HIV prevalence in females, 2010-2018. Figure S41. Space mesh for geostatistical models

Additional file 1 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Additional file 1: Supplemental information.1. Compliance with the Guidlines for Accurate and Transparent Health Estimates Reporting (GATHER). 2. HIV data sources and data processing. 3. Covariate and auxiliary data. 4. Statistical model. 5. References

Additional file 4 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Additional file 4: Supplemental results.1. README. 2. Prevalence range across districts. 3. Prevalence range between sexes. 4. Prevalence range between ages. 5. Age-specific district ranges

Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

BackgroundRegularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels.MethodsWe applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level.FindingsIn 2019, there were 12·2 million (95% UI 11·0-13·6) incident cases of stroke, 101 million (93·2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6·55 million (6·00-7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8-12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1-6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0-73·0), prevalent strokes increased by 85·0% (83·0-88·0), deaths from stroke increased by 43·0% (31·0-55·0), and DALYs due to stroke increased by 32·0% (22·0-42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0-18·0), mortality decreased by 36·0% (31·0-42·0), prevalence decreased by 6·0% (5·0-7·0), and DALYs decreased by 36·0% (31·0-42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0-24·0) and incidence rates increased by 15·0% (12·0-18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5-3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5-3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57-8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97-3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01-1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7-90·8] DALYs or 55·5% [48·2-62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3-48·6] DALYs or 24·3% [15·7-33·2]), high fasting plasma glucose (28·9 million [19·8-41·5] DALYs or 20·2% [13·8-29·1]), ambient particulate matter pollution (28·7 million [23·4-33·4] DALYs or 20·1% [16·6-23·0]), and smoking (25·3 million [22·6-28·2] DALYs or 17·6% [16·4-19·0]).InterpretationThe annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.FundingBill & Melinda Gates Foundation