METHODS: To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10-54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values-a metric assessing gain in forecasting accuracy-by comparing predicted versus observed ASFRs from the past 15 years (2007-21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.

FINDINGS: During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63-5·06) to 2·23 (2·09-2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137-147), declining to 129 million (121-138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1-canonically considered replacement-level fertility-in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7-29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59-2·08) in 2050 and 1·59 (1·25-1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6-43·1) in 2050 and 54·3% (47·1-59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions-decreasing, for example, in south Asia from 24·8% (23·7-25·8) in 2021 to 16·7% (14·3-19·1) in 2050 and 7·1% (4·4-10·1) in 2100-but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40-1·92) in 2050 and 1·62 (1·35-1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.

INTERPRETATION: Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.

METHODS: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

METHODS: The age, sex and year-wise estimates of incidence, mortality, and disability-adjusted life years (DALYs) of 29 cancers for 49 Asian countries from 1990 through 2019 were generated as a part of the Global Burden of Disease, Injuries and Risk Factors 2019 study. Besides incidence, mortality and DALYs, we also examined the cancer burden measured in terms of DALYs and deaths attributable to risk factors, which had evidence of causation with different cancers. The development status of countries was measured using the socio-demographic index. Decomposition analysis was performed to gauge the change in cancer incidence between 1990 and 2019 due to population growth, aging and age-specific incidence rates.

FINDINGS: All cancers combined claimed an estimated 5.6 million [95% uncertainty interval, 5.1-6.0 million] lives in Asia with 9.4 million [8.6-10.2 million] incident cases and 144.7 million [132.7-156.5 million] DALYs in 2019. The age-standardized incidence rate (ASIR) of all cancers combined in Asia was 197.6/100,000 [181.0-214.4] in 2019, varying from 99.2/100,000 [76.1-126.0] in Bangladesh to 330.5/100,000 [298.5-365.8] in Cyprus. The age-standardized mortality rate (ASMR) was 120.6/100,000 [110.1-130.7] in 2019, varying 4-folds across countries from 71.0/100,000 [59.9-83.5] in Kuwait to 284.2/100,000 [229.2-352.3] in Mongolia. The age-standardized DALYs rate was 2970.5/100,000 [2722.6-3206.5] in 2019, varying from 1578.0/100,000 [1341.2-1847.0] in Kuwait to 6574.4/100,000 [5141.7-8333.0] in Mongolia. Between 1990 and 2019, deaths due to 17 of the 29 cancers either doubled or more, and 20 of the 29 cancers underwent an increase of 150% or more in terms of new cases. Tracheal, bronchus, and lung cancer (both sexes), breast cancer (among females), colon and rectum cancer (both sexes), stomach cancer (both sexes) and prostate cancer (among males) were among top-5 cancers in most Asian countries in terms of ASIR and ASMR in 2019 and cancers of liver, stomach, hodgkin lymphoma and esophageal cancer posted the most significant decreases in age-standardized rates between 1990 and 2019. Among the modifiable risk factors, smoking, alcohol use, ambient particulate matter (PM) pollution and unsafe sex remained the dominant risk factors between 1990 and 2019. Cancer DALYs due to ambient PM pollution, high body mass index and fasting plasma glucose has increased most notably between 1990 and 2019.

INTERPRETATION: With growing incidence, cancer has become more significant public health threat in Asia, demanding urgent policy attention and guidance. Its heightened risk calls for increased cancer awareness, preventive measures, affordable early-stage detection, and cost-effective therapeutics in Asia. The current study can serve as a useful resource for policymakers and researchers in Asia for devising interventions for cancer management and control.

METHODS: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic.

FINDINGS: Global DALYs increased from 2·63 billion (95% UI 2·44-2·85) in 2010 to 2·88 billion (2·64-3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7-17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8-6·3) in 2020 and 7·2% (4·7-10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0-234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7-198·3]), neonatal disorders (186·3 million [162·3-214·9]), and stroke (160·4 million [148·0-171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3-51·7) and for diarrhoeal diseases decreased by 47·0% (39·9-52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54-1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5-9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0-19·8]), depressive disorders (16·4% [11·9-21·3]), and diabetes (14·0% [10·0-17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7-27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6-63·6) in 2010 to 62·2 years (59·4-64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6-2·9) between 2019 and 2021.

INTERPRETATION: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades.

METHODS: Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults.

FINDINGS: There were 1·19 million (95% UI 1·11-1·28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5-65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8-57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9-15·6] per 100 000 person-years) and middle SDI (13·6 [12·6-14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9-25·2) DALYs to the global burden of disease, of which 2·7% (1·9-3·6) came from YLDs and 97·3% (96·4-98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally.

INTERPRETATION: Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts.

METHODS: The global prevalence, years lived with disabilities (YLDs), disability-adjusted life years (DALYs), projection, and inequality were estimated for early MSK diseases, including rheumatoid arthritis (RA), osteoarthritis (OA), low back pain (LBP), neck pain (NP), gout, and other MSK diseases (OMSKDs).

FINDINGS: More adolescents and young adults were expected to develop MSK disorders by 2050. Across five age groups, the rates of prevalence, YLDs, and DALYs for RA, NP, LBP, gout, and OMSKDs sharply increased from ages 15-19 to 35-39; however, these were negligible for OA before age 30 but increased notably at ages 30-34, rising at least 6-fold by 35-39. The disease burden of gout, LBP, and OA attributable to high BMI and gout attributable to kidney dysfunction increased, while the contribution of smoking to LBP and RA and occupational ergonomic factors to LBP decreased. Between 1990 and 2019, the slope index of inequality increased for six MSK disorders, and the relative concentration index increased for gout, NP, OA, and OMSKDs but decreased for LBP and RA.

CONCLUSIONS: Multilevel interventions should be initiated to prevent disease burden related to RA, NP, LBP, gout, and OMSKDs among individuals ages 15-19 and to OA among individuals ages 30-34 to tightly control high BMI and kidney dysfunction.

METHODS: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.

FINDINGS: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000-257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.

INTERPRETATION: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution.

METHOD: This international multi-center prospective study across 137 hospitals in 41 countries included patients who underwent an esophagectomy for esophageal cancer, with 90-day follow-up. The main explanatory variable was country income, defined according to the World Bank Data classification. The primary outcome was 90-day postoperative mortality, and secondary outcomes were composite leaks (anastomotic leak or conduit necrosis) and major complications (Clavien-Dindo Grade III - V). Multivariable generalized estimating equation models were used to produce adjusted odds ratios (ORs) and 95% confidence intervals (CI95%).

METHODS: Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018-December 2018. Definitions for AL and CN were those set out by the Oesophageal Complications Consensus Group. Univariate and multivariate analyses were performed to identify risk factors for both AL and CN. A risk score was then produced for both AL and CN using the derivation set, then internally validated using the validation set.

RESULTS: This study included 2247 oesophagectomies across 137 hospitals in 41 countries. The AL rate was 14.2% and CN rate was 2.7%. Preoperative factors that were independent predictors of AL were cardiovascular comorbidity and chronic obstructive pulmonary disease. The risk scoring model showed insufficient predictive ability in internal validation (area under the receiver-operating-characteristic curve [AUROC] = 0.618). Preoperative factors that were independent predictors of CN were: body mass index, Eastern Cooperative Oncology Group performance status, previous myocardial infarction and smoking history. These were converted into a risk-scoring model and internally validated using the validation set with an AUROC of 0.775.

METHODS: We surveyed four countries to determine the public's understanding of keloids. A quantitative, subjective and cross-sectional street survey was designed using the knowledge, attitudes and practice model principles. The target populations were cities in Ghana, Australia, Canada and England. Surveyors used a hybrid stratified/convenience sampling method. Primary outcomes were prevalence, exposure to keloids as an entity and overall keloid knowledge score compared across demographic groups. Study data have been made fully available for reproducibility and education (https://doi.org/10.17605/OSF.IO/3KZ5E).

RESULTS: There were 402 respondents, with a median age of 32 (interquartile range 25-45.25) years, of which 193 were females. The survey was carried out between June 2015 and October 2017. The prevalence of self-identified keloids was 11% in Ghana, 6% in Australia, 2% in Canada and 7% in England. Prevalence, exposure and knowledge were higher in the Ghanaian population.

METHODS: We used a matched case-control design using the Virtual International Stroke Trials Archive (VISTA). Cases were patients who had an acute coronary syndrome, recurrent stroke or transient ischaemic attack within 90 days post-stroke and were matched for age ± 10 years and sex with up to four controls. Antiplatelet use was categorized as persistent (used for >3 days and continued up to day 90), early cessation (used antiplatelet <3 days) or stopped/interrupted users (used for >3 days but stopped prior to day 90). These categories were compared in cases and controls using a conditional logistic regression model that adjusted for potential confounders.

RESULTS: A total of 970 patients were included, of whom 194 were cases and 776 were matched controls. At 90 days, 10 cases (5.2%) and 58 controls (7.5%) stopped/interrupted their antiplatelet. The risk of cardiovascular event was not different in stopped/interrupted users (adjusted odds ratio 0.70, 95% confidence interval 0.33, 1.48; P = 0.352) and early cessations (adjusted odds ratio 1.04, 95% confidence interval 0.62, 1.74; P = 0.876) when compared to persistent users.

DESIGN: A focus group and individual interview qualitative study using purposive sampling of participants to obtain diverse views. Data collection was guided by piloted semistructured topic guides. The focus groups and interviews were audiorecorded, transcribed verbatim and analysed using inductive thematic analysis. We completed data collection once data saturation was reached.

SETTING: Stakeholders in education and health sectors in Malaysia.

PARTICIPANTS: Fifty-two participants (40 school staff, 9 healthcare professionals and 3 policy-makers) contributed to nine focus groups and eleven individual interviews.

RESULTS: School staff had limited awareness of asthma and what to do in emergencies. There was no guidance on asthma management in government schools, and teachers were unclear about their role in school children's health. These uncertainties led to delays in the treatment of asthma symptoms/attacks, and suggestions that an asthma education programme and a school plan would improve asthma care. Perceived challenges in conducting school health programmes included a busy school schedule and poor parental participation. A tailored asthma programme in partnerships with schools could facilitate the programme's adoption and implementation.

METHODS: Using data from the Global Burden of Diseases (GBD), Injuries, and Risk Factors Study 2019, we assessed the age-standardized prevalence, incidence, mortality, and disability-adjusted life years (DALYs) of both asthma and AD from 1990 to 2019, stratified by geographic region, age, sex, and socio-demographic index (SDI). DALYs were calculated as the sum of years lived with disability and years of life lost to premature mortality. Additionally, the disease burden of asthma attributable to high body mass index, occupational asthmagens, and smoking was described.

RESULTS: In 2019, there were a total of 262 million [95% uncertainty interval (UI): 224-309 million] cases of asthma and 171 million [95% UI: 165-178 million] total cases of AD globally; age-standardized prevalence rates were 3416 [95% UI: 2899-4066] and 2277 [95% UI: 2192-2369] per 100,000 population for asthma and AD, respectively, a 24.1% [95% UI: -27.2 to -20.8] decrease for asthma and a 4.3% [95% UI: 3.8-4.8] decrease for AD compared to baseline in 1990. Both asthma and AD had similar trends according to age, with age-specific prevalence rates peaking at age 5-9 years and rising again in adulthood. The prevalence and incidence of asthma and AD were both higher for individuals with higher SDI; however, mortality and DALYs rates of individuals with asthma had a reverse trend, with higher mortality and DALYs rates in those in the lower SDI quintiles. Of the three risk factors, high body mass index contributed to the highest DALYs and deaths due to asthma, accounting for a total of 3.65 million [95% UI: 2.14-5.60 million] asthma DALYs and 75,377 [95% UI: 40,615-122,841] asthma deaths.

METHODS: The World Health Organization Service Availability and Readiness Assessment tool was used to collect data on the care of hip fractures in Malaysia, Thailand, the Philippines, Sri Lanka, and Nepal. Respondents were asked to provide details about the current pathway of care for patients with hip fracture, including pre-hospital transport, time to admission, time to surgery, and time to weightbearing, along with healthcare professionals involved at different stages of care, information on discharge, and patient follow-up.

RESULTS: Responses were received from 98 representative hospitals across the five countries. Most hospitals were publicly funded. There was consistency in clinical pathways of care within country, but considerable variation between countries. Patients mostly travel to hospital via ambulance (both publicly- and privately-funded) or private transport, with only half arriving at hospital within 12 hours of their injury. Access to surgery was variable and time to surgery ranged between one day and more than five days. The majority of hospitals mobilized patients on the first or second day after surgery, but there was notable variation in postoperative weightbearing protocols. Senior medical input was variable and specialist orthogeriatric expertise was unavailable in most hospitals.