Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

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.

FUNDING

Bill & Melinda Gates Foundation.

Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021

BACKGROUND

Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.

METHODS

Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.

FINDINGS

In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8-63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0-45·0] in 2050) and south Asia (31·7% [29·2-34·1] to 15·5% [13·7-17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4-40·3) to 41·1% (33·9-48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6-25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5-43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5-17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7-11·3) in the high-income super-region to 23·9% (20·7-27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5-6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2-26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [-0·6 to 3·6]).

INTERPRETATION

Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.

FUNDING

Bill & Melinda Gates Foundation.

Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Accurate assessments of current and future fertility-including overall trends and changing population age structures across countries and regions-are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.

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.

FUNDING

Bill & Melinda Gates Foundation.

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic.

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.

FUNDING

Bill & Melinda Gates Foundation.

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021.

METHODS

The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws.

FINDINGS

Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP).

INTERPRETATION

Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions.

FUNDING

Bill & Melinda Gates Foundation.

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period.

METHODS

22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.

FINDINGS

Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.

INTERPRETATION

Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic.

FUNDING

Bill & Melinda Gates Foundation.

Mortality in Patients Hospitalized for COVID-19 vs Influenza in Fall-Winter 2023-2024

This cohort study evaluates the risk of death in patients hospitalized for COVID-19 or seasonal influenza following the emergence of the JN.1 variant in winter 2023.

Long-term outcomes following hospital admission for COVID-19 versus seasonal influenza: a cohort study

BACKGROUND

Previous comparative analyses of people admitted to hospital for COVID-19 versus influenza evaluated the risk of death, hospital readmission, and a narrow set of health outcomes up to 6 months following infection. We aimed to do a comparative evaluation of both acute and long-term risks and burdens of a comprehensive set of health outcomes following hospital admission for COVID-19 or seasonal influenza.

METHODS

For this cohort study we used the health-care databases of the US Department of Veterans Affairs to analyse data from 81 280 participants admitted to hospital for COVID-19 between March 1, 2020, and June 30, 2022, and 10 985 participants admitted to hospital for seasonal influenza between Oct 1, 2015, and Feb 28, 2019. Participants were followed up for up to 18 months to comparatively evaluate risks and burdens of death, a prespecified set of 94 individual health outcomes, ten organ systems, overall burden across all organ systems, readmission, and admission to intensive care. Inverse probability weighting was used to balance the baseline characteristics. Cox and Poisson models were used to generate estimates of risk on both the relative scale and absolute scale as the event rate and disability-adjusted life-years (DALYs) per 100 persons.

FINDINGS

Over 18 months of follow-up, compared to seasonal influenza, the COVID-19 group had an increased risk of death (hazard ratio [HR] 1·51 [95% CI 1·45-1·58]), corresponding to an excess death rate of 8·62 (95% CI 7·55-9·44) per 100 persons in the COVID-19 group versus the influenza group. Comparative analyses of 94 prespecified health outcomes showed that COVID-19 had an increased risk of 68·1% (64 of 94) pre-specified health outcomes; seasonal influenza was associated with an increased risk of 6·4% (six of 94) pre-specified health outcomes, including three out of four pre-specified pulmonary outcomes. Analyses of organ systems showed that COVID-19 had a higher risk across all organ systems except for the pulmonary system, the risk of which was higher in seasonal influenza. The cumulative rates of adverse health outcomes across all organ systems were 615·18 (95% CI 605·17-624·88) per 100 persons in COVID-19 and 536·90 (527·38-544·90) per 100 persons in seasonal influenza, corresponding to an excess rate of 78·72 (95% CI 66·15-91·24) per 100 persons in COVID-19. The total number of DALYs across all organ systems were 287·43 (95% CI 281·10-293·59) per 100 persons in the COVID-19 group and 242·66 (236·75, 247·67) per 100 persons in the seasonal influenza group, corresponding to 45·03 (95% CI 37·15-52·90) higher DALYs per 100 persons in COVID-19. Decomposition analyses showed that in both COVID-19 and seasonal influenza, there was a higher burden of health loss in the post-acute than the acute phase; and comparatively, except for the pulmonary system, COVID-19 had a higher burden of health loss across all other organ systems than seasonal influenza in both the acute and post-acute phase. Compared to seasonal influenza, COVID-19 also had an increased risk of hospital readmission (excess rate 20·50 [95% CI 16·10-24·86] per 100 persons) and admission to intensive care (excess rate 9·23 [6·68-11·82] per 100 persons). The findings were consistent in analyses comparatively evaluating risks in seasonal influenza versus COVID-19 by individuals' respective vaccination status and in those admitted to hospital during the pre-delta, delta, and omicron eras.

INTERPRETATION

Although rates of death and adverse health outcomes following hospital admission for either seasonal influenza or COVID-19 are high, this comparative analysis shows that hospital admission for COVID-19 was associated with higher long-term risks of death and adverse health outcomes in nearly every organ system (except for the pulmonary system) and significant cumulative excess DALYs than hospital admission for seasonal influenza. The substantial cumulative burden of health loss in both groups calls for greater prevention of hospital admission for these two viruses and for greater attention to the care needs of people with long-term health effects due to either seasonal influenza or SARS-CoV-2 infection.

FUNDING

US Department of Veterans Affairs.

Solving the puzzle of Long Covid

Long Covid provides an opportunity to understand how acute infections cause chronic disease.

Fluctuating risk of acute kidney injury-related mortality for four weeks after exposure to air pollution: A multi-country time-series study in 6 countries

BACKGROUND

Recent studies have reported that air pollution is related to kidney diseases. However, the global evidence on the risk of death from acute kidney injury (AKI) owing to air pollution is limited. Therefore, we investigated the association between short-term exposure to air pollution-particulate matter ≤ 2.5 μm (PM2.5), ozone (O3), and nitrogen dioxide (NO2)-and AKI-related mortality using a multi-country dataset.

METHODS

This study included 41,379 AKI-related deaths in 136 locations in six countries during 1987-2018. A novel case time-series design was applied to each air pollutant during 0-28 lag days to estimate the association between air pollution and AKI-related deaths. Moreover, we calculated AKI deaths attributable to non-compliance with the World Health Organization (WHO) air quality guidelines.

RESULTS

The relative risks (95% confidence interval) of AKI-related deaths are 1.052 (1.003, 1.103), 1.022 (0.994, 1.050), and 1.022 (0.982, 1.063) for 5, 10, and 10 µg/m3 increase in lag 0-28 days of PM2.5, warm-season O3, and NO2, respectively. The lag-distributed association showed that the risk appeared immediately on the day of exposure to air pollution, gradually decreased, and then increased again reaching the peak approximately 20 days after exposure to PM2.5 and O3. We also found that 1.9%, 6.3%, and 5.2% of AKI deaths were attributed to PM2.5, warm-season O3, and NO2 concentrations above the WHO guidelines.

CONCLUSIONS

This study provides evidence that public health policies to reduce air pollution may alleviate the burden of death from AKI and suggests the need to investigate the several pathways between air pollution and AKI death.

Comparative effectiveness of SGLT2 inhibitors, GLP-1 receptor agonists, DPP-4 inhibitors, and sulfonylureas on risk of major adverse cardiovascular events: emulation of a randomised target trial using electronic health records

BACKGROUND

Randomised clinical trials showed that compared with placebo, SGLT2 inhibitors and GLP-1 receptor agonists reduced risk of adverse cardiovascular events. The evidence base for the older antihyperglycaemic drug classes (DPP-4 inhibitors and sulfonylureas) is generally less well developed. Because most randomised trials evaluated one antihyperglycaemic medication versus placebo, a head-to-head comparative effectiveness analysis of the newer drug classes (SGLT2 inhibitors vs GLP-1 receptor agonists) or newer (SGLT2 inhibitors or GLP-1 receptor agonists) versus older (DPP-4 inhibitors or sulfonylureas) drug classes on risk of major adverse cardiovascular events (MACE) is not available. In this study, we aimed to evaluate the comparative effectiveness of incident use of SGLT2 inhibitors, GLP-1 receptor agonists, DPP-4 inhibitors, or sulfonylureas on risk of MACE.

METHODS

We first specified the protocol of a four-arm randomised pragmatic clinical trial and then emulated it using the health-care databases of the US Department of Veterans Affairs. We built a cohort of metformin users with incident use of SGLT2 inhibitors, GLP-1 receptor agonists, DPP-4 inhibitors, or sulfonylureas between Oct 1, 2016 and Sept 30, 2021, and followed up until Dec 31, 2022. We used the overlap weighting approach to balance the treatment groups using a battery of predefined variables and a set of algorithmically selected variables from high-dimensional data domains. Both intention-to-treat and per-protocol analyses (the latter estimated the effect of maintained use of the antihyperglycaemic throughout follow-up) were conducted to estimate risk of MACE-defined as a composite endpoint of stroke, myocardial infarction, and all-cause mortality.

FINDINGS

The final cohort consisted of 283 998 new users of SGLT2 inhibitors (n=46 516), GLP-1 receptor agonists (n=26 038), DPP-4 inhibitors (n=55 310), or sulfonylureas (n=156 134). In intention-to-treat analyses, compared with sulfonylureas, SGLT2 inhibitors, GLP-1 receptor agonists, and DPP-4 inhibitors were associated with lower risk of MACE (hazard ratio [HR] 0·77 [95% CI 0·74-0.80], 0·78 [0·74-0·81), and 0·90 [0·86-0.93], respectively). Both SGLT2 inhibitors and GLP-1 receptor agonists were associated with a lower risk of MACE when compared with DPP-4 inhibitors (HR 0·86 [0·82-0·89] and 0·86 [0·82-0·90], respectively). The risk of MACE between SGLT2 inhibitors and GLP-1 receptor agonists yielded an HR of 0·99 (0·94-1·04). In per-protocol analyses, compared with sulfonylureas, SGLT2 inhibitors, GLP1 receptor agonists, and DPP-4 inhibitors were associated with reduced risk of MACE (HR 0·77 [95% CI 0·73-0·82], 0·77 [0·72-0·82], and 0·88 [0·83-0·93], respectively). Both SGLT2 inhibitors and GLP-1 receptor agonists were associated with a lower risk of MACE when compared with DPP-4 inhibitors (HR 0·88 [0·83-0·93] and 0·88 [0·82-0·93], respectively). The risk of MACE between SGLT2 inhibitors and GLP-1 receptor agonists yielded an HR of 1·01 (0·94-1·07).

INTERPRETATION

Both SGLT2 inhibitors and GLP-1 receptor agonists were associated with reduced risk of MACE compared with DPP-4 inhibitors or sulfonylureas. DPP-4 inhibitors were associated with reduced risk of MACE compared with sulfonylureas. There was no statistically significant difference in risk of MACE between SGLT2 inhibitors and GLP-1 receptor agonists. The results provide evidence of the real-world comparative effectiveness of the four most commonly used second-line antihyperglycaemics and could guide choice of antihyperglycaemic therapy.

FUNDING

US Department of Veterans Affairs and the American Society of Nephrology.

Postacute sequelae of COVID-19 at 2 years

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can lead to postacute sequelae in multiple organ systems, but evidence is mostly limited to the first year postinfection. We built a cohort of 138,818 individuals with SARS-CoV-2 infection and 5,985,227 noninfected control group from the US Department of Veterans Affairs and followed them for 2 years to estimate the risks of death and 80 prespecified postacute sequelae of COVID-19 (PASC) according to care setting during the acute phase of infection. The increased risk of death was not significant beyond 6 months after infection among nonhospitalized but remained significantly elevated through the 2 years in hospitalized individuals. Within the 80 prespecified sequelae, 69% and 35% of them became not significant at 2 years after infection among nonhospitalized and hospitalized individuals, respectively. Cumulatively at 2 years, PASC contributed 80.4 (95% confidence interval (CI): 71.6-89.6) and 642.8 (95% CI: 596.9-689.3) disability-adjusted life years (DALYs) per 1,000 persons among nonhospitalized and hospitalized individuals; 25.3% (18.9-31.0%) and 21.3% (18.2-24.5%) of the cumulative 2-year DALYs in nonhospitalized and hospitalized were from the second year. In sum, while risks of many sequelae declined 2 years after infection, the substantial cumulative burden of health loss due to PASC calls for attention to the care needs of people with long-term health effects due to SARS-CoV-2 infection.

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050.

METHODS

Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively.

FINDINGS

In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%.

INTERPRETATION

Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.

FUNDING

Bill & Melinda Gates Foundation.

Molnupiravir and risk of post-acute sequelae of covid-19: cohort study

OBJECTIVE

To examine whether treatment with the antiviral agent molnupiravir during the first five days of SARS-CoV-2 infection is associated with reduced risk of post-acute adverse health outcomes.

DESIGN

Cohort study.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

229 286 participants who tested positive for SARS-CoV-2 between 5 January 2022 and 15 January 2023, had at least one risk factor for progression to severe covid-19, and survived the first 30 days after testing positive were enrolled. 11 472 participants received a prescription for molnupiravir within five days of the positive test result and 217 814 received no covid-19 antiviral or antibody treatment (no treatment group).

MAIN OUTCOME MEASURES

Risks of post-acute sequelae of SARS-CoV-2 (PASC, defined based on a prespecified set of 13 post-acute sequelae), post-acute death, post-acute hospital admission, and each individual post-acute sequela between the molnupiravir group and no treatment group were examined after application of inverse probability weighting to balance the treatment and no treatment groups. Post-acute outcomes were ascertained from 30 days after the first SARS-CoV-2 positive test result until end of follow-up. Risks on the relative scale (relative risk or hazard ratio) and absolute scale (absolute risk reduction at 180 days) were estimated.

RESULTS

Compared with no treatment, molnupiravir use within five days of a positive SARS-CoV-2 test result was associated with reduced risk of PASC (relative risk 0.86 (95% confidence interval 0.83 to 0.89); absolute risk reduction at 180 days 2.97% (95% confidence interval 2.31% to 3.60%)), post-acute death (hazard ratio 0.62 (0.52 to 0.74); 0.87% (0.62% to 1.13%)), and post-acute hospital admission (0.86 (0.80 to 0.93); 1.32% (0.72% to 1.92%)). Molnupiravir was associated with reduced risk of eight of the 13 post-acute sequelae: dysrhythmia, pulmonary embolism, deep vein thrombosis, fatigue and malaise, liver disease, acute kidney injury, muscle pain, and neurocognitive impairment. Molnupiravir was also associated with reduced risk of PASC in people who had not received a covid-19 vaccine, had received at one or two vaccine doses, and had received a booster dose, and in people with primary SARS-CoV-2 infection and reinfection.

CONCLUSIONS

In people with SARS-CoV-2 infection and at least one risk factor for progression to severe covid-19, compared with no treatment, molnupiravir use within five days of infection was associated with reduced risk of PASC in people who had not received a covid-19 vaccine, had received one or two vaccine doses, and had received a booster dose, and in those with primary SARS-CoV-2 infection and reinfection. Among people at high risk of progression to severe covid-19, molnupiravir use within five days of SARS-CoV-2 infection may be a viable approach to reduce the risk of PASC.

Nirmatrelvir and risk of hospital admission or death in adults with covid-19: emulation of a randomized target trial using electronic health records

OBJECTIVE

To estimate the effectiveness of nirmatrelvir, compared with no treatment, in reducing admission to hospital or death at 30 days in people infected with the SARS-CoV-2 virus and at risk of developing severe disease, according to vaccination status and history of previous SARS-CoV-2 infection.

DESIGN

Emulation of a randomized target trial with electronic health records.

SETTING

Healthcare databases of the US Department of Veterans Affairs PARTICIPANTS: 256 288 participants with a SARS-CoV-2 positive test result and at least one risk factor for developing severe covid-19 disease, between 3 January and 30 November 2022. 31 524 were treated with nirmatrelvir within five days of testing positive for SARS-CoV-2 and 224 764 received no treatment.

MAIN OUTCOME MEASURES

The effectiveness of starting nirmatrelvir within five days of a positive SARS-CoV-2 test result versus no treatment in reducing the risk of admission to hospital or death at 30 days was estimated in those who were not vaccinated, in those who received one or two doses of vaccine, and those who received a vaccine booster and, separately, in participants with a primary SARS-CoV-2 infection or reinfection. The inverse probability weighting method was used to balance personal and health characteristics between the groups. Relative risk and absolute risk reduction were computed from cumulative incidence at 30 days, estimated by weighted Kaplan-Meier estimator.

RESULTS

Among people who were not vaccinated (n=76 763; 5338 nirmatrelvir and 71 425 no treatment), compared with no treatment, the relative risk of nirmatrelvir in reducing admission to hospital or death at 30 days was 0.60 (95% confidence interval 0.50 to 0.71); the absolute risk reduction was 1.83% (95% confidence interval 1.29% to 2.49%). The relative risk and absolute risk reduction, compared with no treatment, were 0.65 (0.57 to 0.74) and 1.27% (0.90% to 1.61%), respectively, in people who received one or two doses of vaccine (n=84 620; 7989 nirmatrelvir and 76 631 no treatment); 0.64 (0.58 to 0.71) and 1.05% (0.85% to 1.27%) in individuals who received a booster dose of vaccine (n=94 905; 18 197 nirmatrelvir and 76 708 no treatment); 0.61 (0.57 to 0.65) and 1.36% (1.19% to 1.53%) in participants with a primary SARS-CoV-2 infection (n=228 081; 26 350 nirmatrelvir and 201 731 no treatment); and 0.74 (0.63 to 0.87) and 0.79% (0.36% to 1.18%) in participants who were reinfected with the SARS-CoV-2 virus (n=28 207; 5174 nirmatrelvir and 23 033 no treatment). Nirmatrelvir was associated with a reduced risk of admission to hospital or death in those aged ≤65 years and > 65 years; in men and women; in black and white participants; in those with 1-2, 3-4, and ≥5 risk factors for progression to severe covid-19 illness; and in those infected during the omicron BA.1 or BA.2 predominant era, and the BA.5 predominant era.

CONCLUSIONS

In people with SARS-CoV-2 infection who were at risk of developing severe disease, compared with no treatment, nirmatrelvir was associated with a reduced risk of admission to hospital or death at 30 days in people who were not vaccinated, vaccinated, and had received a booster vaccine, and in those with a primary SARS-CoV-2 infection and reinfection.

Air Pollution and Acute Kidney Injury in the U.S. Medicare Population: A Longitudinal Cohort Study

BACKGROUND

Recent studies have reported the association between air pollution exposure and reduced kidney function. However, it is unclear whether air pollution is associated with an increased risk of acute kidney injury (AKI).

OBJECTIVES

To address this gap in knowledge, we investigated the effect estimates of long-term exposures to fine particulate matter [PM ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 )], nitrogen dioxide (NO 2 ), and ozone (O 3 ) on the risk of first hospital admission for AKI using nationwide Medicare data.

METHODS

This nationwide population-based longitudinal cohort study included 61,300,754 beneficiaries enrolled in Medicare Part A fee-for-service (FFS) who were ≥ 65 years of age and resided in the continental United States from the years 2000 through 2016. We applied Cox-equivalent Poisson models to estimate the association between air pollution and first hospital admission for AKI.

RESULTS

Exposure to PM 2.5 , NO 2 , and O 3 was associated with increased risk for first hospital admission for AKI, with hazard ratios (HRs) of 1.17 (95% CI: 1.16, 1.19) for a 5 - μ g / m 3 increase in PM 2.5 , 1.12 (95% CI: 1.11, 1.13) for a 10 -ppb increase in NO 2 , and 1.03 (95% CI: 1.02, 1.04) for a 10 -ppb increase in summer-period O 3 (June to September). The associations persisted at annual exposures lower than the current National Ambient Air Quality Standard.

DISCUSSION

This study found an association between exposures to air pollution and the risk of the first hospital admission with AKI, and this association persisted even at low concentrations of air pollution. Our findings provide beneficial implications for public health policies and air pollution guidelines to alleviate health care expenditures and the disease burden attributable to AKI. https://doi.org/10.1289/EHP10729.

Association of Treatment With Nirmatrelvir and the Risk of Post-COVID-19 Condition

Importance

Post-COVID-19 condition (PCC), also known as long COVID, affects many individuals. Prevention of PCC is an urgent public health priority.

Objective

To examine whether treatment with nirmatrelvir in the acute phase of COVID-19 is associated with reduced risk of PCC.

Design, Setting, and Participants

This cohort study used the health care databases of the US Department of Veterans Affairs (VA) to identify patients who had a SARS-CoV-2 positive test result between January 3, 2022, and December 31, 2022, who were not hospitalized on the day of the positive test result, who had at least 1 risk factor for progression to severe COVID-19 illness, and who had survived the first 30 days after SARS-CoV-2 diagnosis. Those who were treated with oral nirmatrelvir within 5 days after the positive test (n = 35 717) and those who received no COVID-19 antiviral or antibody treatment during the acute phase of SARS-CoV-2 infection (control group, n = 246 076) were identified.

Exposures

Treatment with nirmatrelvir or receipt of no COVID-19 antiviral or antibody treatment based on prescription records.

Main Outcomes and Measures

Inverse probability weighted survival models were used to estimate the association of nirmatrelvir (vs control) with post-acute death, post-acute hospitalization, and a prespecified panel of 13 post-acute COVID-19 sequelae (components of PCC) and reported in relative scale as relative risk (RR) or hazard ratio (HR) and in absolute scale as absolute risk reduction in percentage at 180 days (ARR).

Results

A total of 281 793 patients (mean [SD] age, 61.99 [14.96]; 242 383 [86.01%] male) who had a positive SARS-CoV-2 test result and had at least 1 risk factor for progression to severe COVID-19 illness were studied. Among them, 246 076 received no COVID-19 antiviral or antibody treatment during the acute phase of SARS-CoV-2 infection, and 35 717 received oral nirmatrelvir within 5 days after the positive SARS-CoV-2 test result. Compared with the control group, nirmatrelvir was associated with reduced risk of PCC (RR, 0.74; 95% CI, 0.72-0.77; ARR, 4.51%; 95% CI, 4.01-4.99), including reduced risk of 10 of 13 post-acute sequelae (components of PCC) in the cardiovascular system (dysrhythmia and ischemic heart disease), coagulation and hematologic disorders (pulmonary embolism and deep vein thrombosis), fatigue and malaise, acute kidney disease, muscle pain, neurologic system (neurocognitive impairment and dysautonomia), and shortness of breath. Nirmatrelvir was also associated with reduced risk of post-acute death (HR, 0.53; 95% CI, 0.46-0.61); ARR, 0.65%; 95% CI, 0.54-0.77), and post-acute hospitalization (HR, 0.76; 95% CI, 0.73-0.80; ARR, 1.72%; 95% CI, 1.42-2.01). Nirmatrelvir was associated with reduced risk of PCC in people who were unvaccinated, vaccinated, and boosted, and in people with primary SARS-CoV-2 infection and reinfection.

Conclusions and Relevance

This cohort study found that in people with SARS-CoV-2 infection who had at least 1 risk factor for progression to severe disease, treatment with nirmatrelvir within 5 days of a positive SARS-CoV-2 test result was associated with reduced risk of PCC across the risk spectrum in this cohort and regardless of vaccination status and history of prior infection; the totality of findings suggests that treatment with nirmatrelvir during the acute phase of COVID-19 may reduce the risk of post-acute adverse health outcomes.

Molnupiravir and risk of hospital admission or death in adults with covid-19: emulation of a randomized target trial using electronic health records

OBJECTIVE

To emulate a randomized target trial to estimate the association between the antiviral drug molnupiravir and hospital admission or death in adults with SARS-CoV-2 infection in the community during the omicron predominant era who were at high risk of progression to severe covid-19.

DESIGN

Emulation of a randomized target trial using electronic health records.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

85 998 adults with SARS-CoV-2 infection between 5 January and 30 September 2022 and at least one risk factor for progression to severe covid-19: 7818 participants were eligible for and treated with molnupiravir and 78 180 received no treatment.

MAIN OUTCOMES MEASURE

The primary outcome was a composite of hospital admission or death at 30 days. The clone method with inverse probability of censoring weighting was used to adjust for informative censoring and balance baseline characteristics between the groups. The cumulative incidence function was used to estimate the relative risk and the absolute risk reduction at 30 days.

RESULTS

Molnupiravir was associated with a reduction in hospital admissions or death at 30 days (relative risk 0.72 (95% confidence interval 0.64 to 0.79)) compared with no treatment; the event rates for hospital admission or death at 30 days were 2.7% (95% confidence interval 2.5% to 3.0%) for molnupiravir and 3.8% (3.7% to 3.9%) for no treatment; the absolute risk reduction was 1.1% (95% confidence interval 0.8% to 1.4%). Molnupiravir appeared to be effective in those who had not been vaccinated against covid-19 (relative risk 0.83 (0.70 to 0.97) and absolute risk reduction 0.9% (0.2% to 1.9%)), had received one or two vaccine doses (0.69 (0.56 to 0.83) and 1.3% (0.7% to 1.9%)), and had received a booster dose (0.71 (0.58 to 0.83) and 1.0% (0.5% to 1.4%)); in those infected during the era when the omicron subvariant BA.1 or BA.2 was predominant (0.72 (0.62 to 0.83) and 1.2% (0.7% to 1.6%)) and when BA.5 was predominant (0.75 (0.66 to 0.86) and 0.9% (0.5% to 1.3%)); and in those with no history of SARS-CoV-2 infection (0.72 (0.64 to 0.81) and 1.1% (0.8% to 1.4%)) and with a history of SARS-CoV-2 infection (0.75 (0.58 to 0.97) and 1.1% (0.1% to 1.8%)).

CONCLUSIONS

The findings of this emulation of a randomized target trial suggest that molnupiravir might have reduced hospital admission or death at 30 days in adults with SARS-CoV-2 infection in the community during the recent omicron predominant era who were at high risk of progression to severe covid-19 and eligible for treatment with molnupiravir.

Risks and burdens of incident dyslipidaemia in long COVID: a cohort study

BACKGROUND

Non-clinical evidence and a few human studies with short follow-ups suggest increased risk of dyslipidaemia in the post-acute phase of COVID-19 (ie, >30 days after SARS-CoV-2 infection). However, detailed large-scale controlled studies with longer follow-ups and in-depth assessment of the risks and burdens of incident dyslipidaemia in the post-acute phase of COVID-19 are not yet available. We, therefore, aimed to examine the risks and 1-year burdens of incident dyslipidaemia in the post-acute phase of COVID-19 among people who survive the first 30 days of SARS-CoV-2 infection.

METHODS

In this cohort study, we used the national health-care databases of the US Department of Veterans Affairs to build a cohort of 51 919 participants who had a positive COVID-19 test and survived the first 30 days of infection between March 1, 2020, and Jan 15, 2021; a non-infected contemporary control group (n=2 647 654) that enrolled patients between March 1, 2020, and Jan 15, 2021; and a historical control group (n=2 539 941) that enrolled patients between March 1, 2018, and Jan 15, 2019. Control groups had no evidence of SARS-CoV-2 infection, and participants in all three cohorts were free of dyslipidaemia before cohort enrolment. We then used inverse probability weighting using predefined and algorithmically-selected high dimensional variables to estimate the risks and 1-year burdens of incident dyslipidaemia, lipid-lowering medications use, and a composite of these outcomes. We reported two measures of risk: hazard ratios (HRs) and burden per 1000 people at 12 months. Additionally, we estimated the risks and burdens of incident dyslipidaemia outcomes in mutually exclusive groups based on the care setting of the acute infection (ie, participants who were non-hospitalised, hospitalised, or admitted to intensive care during the acute phase of SARS-CoV-2 infection).

FINDINGS

In the post-acute phase of the SARS-CoV-2 infection, compared with the non-infected contemporary control group, those in the COVID-19 group had higher risks and burdens of incident dyslipidaemia, including total cholesterol greater than 200 mg/dL (hazard ratio [HR] 1·26, 95% CI 1·22-1·29; burden 22·46, 95% CI 19·14-25·87 per 1000 people at 1 year), triglycerides greater than 150 mg/dL (1·27, 1·23-1·31; 22·03, 18·85-25·30), LDL cholesterol greater than 130 mg/dL (1·24, 1·20-1·29; 18·00, 14·98-21·11), and HDL cholesterol lower than 40 mg/dL (1·20, 1·16-1·25; 15·58, 12·52-18·73). The risk and burden of a composite of these abnormal lipid laboratory outcomes were 1·24 (95% CI 1·21-1·27) and 39·19 (95% CI 34·71-43·73), respectively. There was also increased risk and burden of incident lipid-lowering medications use (HR 1·54, 95% CI 1·48-1·61; burden 25·50, 95% CI 22·61-28·50). A composite of any dyslipidaemia outcome (laboratory abnormality or lipid-lowering medications use) yielded an HR of 1·31 (95% CI 1·28-1·34) and a burden of 54·03 (95% CI 49·21-58·92). The risks and burdens of these post-acute outcomes increased in a graded fashion corresponding to the severity of the acute phase of COVID-19 infection (ie, whether patients were non-hospitalised, hospitalised, or admitted to intensive care). The results were consistent in analyses comparing the COVID-19 group to the non-infected historical control group.

INTERPRETATION

Our findings suggest increased risks and 1-year burdens of incident dyslipidaemia and incident lipid-lowering medications use in the post-acute phase of COVID-19 infection. Post-acute care for those with COVID-19 should involve attention to dyslipidaemia as a potential post-acute sequela of SARS-CoV-2 infection.

FUNDING

US Department of Veterans Affairs.

Estimated Global Proportions of Individuals With Persistent Fatigue, Cognitive, and Respiratory Symptom Clusters Following Symptomatic COVID-19 in 2020 and 2021

Importance

Some individuals experience persistent symptoms after initial symptomatic SARS-CoV-2 infection (often referred to as Long COVID).

Objective

To estimate the proportion of males and females with COVID-19, younger or older than 20 years of age, who had Long COVID symptoms in 2020 and 2021 and their Long COVID symptom duration.

Design, Setting, and Participants

Bayesian meta-regression and pooling of 54 studies and 2 medical record databases with data for 1.2 million individuals (from 22 countries) who had symptomatic SARS-CoV-2 infection. Of the 54 studies, 44 were published and 10 were collaborating cohorts (conducted in Austria, the Faroe Islands, Germany, Iran, Italy, the Netherlands, Russia, Sweden, Switzerland, and the US). The participant data were derived from the 44 published studies (10 501 hospitalized individuals and 42 891 nonhospitalized individuals), the 10 collaborating cohort studies (10 526 and 1906), and the 2 US electronic medical record databases (250 928 and 846 046). Data collection spanned March 2020 to January 2022.

Exposures

Symptomatic SARS-CoV-2 infection.

Main Outcomes and Measures

Proportion of individuals with at least 1 of the 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after SARS-CoV-2 infection in 2020 and 2021, estimated separately for hospitalized and nonhospitalized individuals aged 20 years or older by sex and for both sexes of nonhospitalized individuals younger than 20 years of age.

Results

A total of 1.2 million individuals who had symptomatic SARS-CoV-2 infection were included (mean age, 4-66 years; males, 26%-88%). In the modeled estimates, 6.2% (95% uncertainty interval [UI], 2.4%-13.3%) of individuals who had symptomatic SARS-CoV-2 infection experienced at least 1 of the 3 Long COVID symptom clusters in 2020 and 2021, including 3.2% (95% UI, 0.6%-10.0%) for persistent fatigue with bodily pain or mood swings, 3.7% (95% UI, 0.9%-9.6%) for ongoing respiratory problems, and 2.2% (95% UI, 0.3%-7.6%) for cognitive problems after adjusting for health status before COVID-19, comprising an estimated 51.0% (95% UI, 16.9%-92.4%), 60.4% (95% UI, 18.9%-89.1%), and 35.4% (95% UI, 9.4%-75.1%), respectively, of Long COVID cases. The Long COVID symptom clusters were more common in women aged 20 years or older (10.6% [95% UI, 4.3%-22.2%]) 3 months after symptomatic SARS-CoV-2 infection than in men aged 20 years or older (5.4% [95% UI, 2.2%-11.7%]). Both sexes younger than 20 years of age were estimated to be affected in 2.8% (95% UI, 0.9%-7.0%) of symptomatic SARS-CoV-2 infections. The estimated mean Long COVID symptom cluster duration was 9.0 months (95% UI, 7.0-12.0 months) among hospitalized individuals and 4.0 months (95% UI, 3.6-4.6 months) among nonhospitalized individuals. Among individuals with Long COVID symptoms 3 months after symptomatic SARS-CoV-2 infection, an estimated 15.1% (95% UI, 10.3%-21.1%) continued to experience symptoms at 12 months.

Conclusions and Relevance

This study presents modeled estimates of the proportion of individuals with at least 1 of 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after symptomatic SARS-CoV-2 infection.

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000-18: a geospatial modelling study

BACKGROUND

More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.

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.

FUNDING

Bill & Melinda Gates Foundation.

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2·5 air pollution, 1990-2019: an analysis of data from the Global Burden of Disease Study 2019

BACKGROUND

Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution.

METHODS

We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure-response curve from the extracted relative risk estimates using the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals.

FINDINGS

In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68-4·83) deaths per 100 000 population and 167 (117-223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49-17·5) of deaths and 13·6% (9·73-17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22-9·53) of deaths and 5·92% (3·81-8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5.

INTERPRETATION

Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes.

FUNDING

Bill & Melinda Gates Foundation.

Long COVID after breakthrough SARS-CoV-2 infection

The post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-also referred to as Long COVID-have been described, but whether breakthrough SARS-CoV-2 infection (BTI) in vaccinated people results in post-acute sequelae is not clear. In this study, we used the US Department of Veterans Affairs national healthcare databases to build a cohort of 33,940 individuals with BTI and several controls of people without evidence of SARS-CoV-2 infection, including contemporary (n = 4,983,491), historical (n = 5,785,273) and vaccinated (n = 2,566,369) controls. At 6 months after infection, we show that, beyond the first 30 days of illness, compared to contemporary controls, people with BTI exhibited a higher risk of death (hazard ratio (HR) = 1.75, 95% confidence interval (CI): 1.59, 1.93) and incident post-acute sequelae (HR = 1.50, 95% CI: 1.46, 1.54), including cardiovascular, coagulation and hematologic, gastrointestinal, kidney, mental health, metabolic, musculoskeletal and neurologic disorders. The results were consistent in comparisons versus the historical and vaccinated controls. Compared to people with SARS-CoV-2 infection who were not previously vaccinated (n = 113,474), people with BTI exhibited lower risks of death (HR = 0.66, 95% CI: 0.58, 0.74) and incident post-acute sequelae (HR = 0.85, 95% CI: 0.82, 0.89). Altogether, the findings suggest that vaccination before infection confers only partial protection in the post-acute phase of the disease; hence, reliance on it as a sole mitigation strategy may not optimally reduce long-term health consequences of SARS-CoV-2 infection. The findings emphasize the need for continued optimization of strategies for primary prevention of BTI and will guide development of post-acute care pathways for people with BTI.

A global systematic analysis of the occurrence, severity, and recovery pattern of long COVID in 2020 and 2021

Importance:

While much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID.

Objective:

To estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery

Design:

We jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study.

Results:

Analyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8–312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38–7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9–92.4), 60.4% (18.9–89.1), and 35.4% (9.4–75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84–4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10–9.78]). At twelve months, 15.1% (10.3–21.1) continued to experience long COVID symptoms.

Conclusions and relevance:

The occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane.

Risks and burdens of incident diabetes in long COVID: a cohort study

BACKGROUND

There is growing evidence suggesting that beyond the acute phase of SARS-CoV-2 infection, people with COVID-19 could experience a wide range of post-acute sequelae, including diabetes. However, the risks and burdens of diabetes in the post-acute phase of the disease have not yet been comprehensively characterised. To address this knowledge gap, we aimed to examine the post-acute risk and burden of incident diabetes in people who survived the first 30 days of SARS-CoV-2 infection.

METHODS

In this cohort study, we used the national databases of the US Department of Veterans Affairs to build a cohort of 181 280 participants who had a positive COVID-19 test between March 1, 2020, and Sept 30, 2021, and survived the first 30 days of COVID-19; a contemporary control (n=4 118 441) that enrolled participants between March 1, 2020, and Sept 30, 2021; and a historical control (n=4 286 911) that enrolled participants between March 1, 2018, and Sept 30, 2019. Both control groups had no evidence of SARS-CoV-2 infection. Participants in all three comparison groups were free of diabetes before cohort entry and were followed up for a median of 352 days (IQR 245-406). We used inverse probability weighted survival analyses, including predefined and algorithmically selected high dimensional variables, to estimate post-acute COVID-19 risks of incident diabetes, antihyperglycaemic use, and a composite of the two outcomes. We reported two measures of risk: hazard ratio (HR) and burden per 1000 people at 12 months.

FINDINGS

In the post-acute phase of the disease, compared with the contemporary control group, people with COVID-19 exhibited an increased risk (HR 1·40, 95% CI 1·36-1·44) and excess burden (13·46, 95% CI 12·11-14·84, per 1000 people at 12 months) of incident diabetes; and an increased risk (1·85, 1·78-1·92) and excess burden (12·35, 11·36-13·38) of incident antihyperglycaemic use. Additionally, analyses to estimate the risk of a composite endpoint of incident diabetes or antihyperglycaemic use yielded a HR of 1·46 (95% CI 1·43-1·50) and an excess burden of 18·03 (95% CI 16·59-19·51) per 1000 people at 12 months. Risks and burdens of post-acute outcomes increased in a graded fashion according to the severity of the acute phase of COVID-19 (whether patients were non-hospitalised, hospitalised, or admitted to intensive care). All the results were consistent in analyses using the historical control as the reference category.

INTERPRETATION

In the post-acute phase, we report increased risks and 12-month burdens of incident diabetes and antihyperglycaemic use in people with COVID-19 compared with a contemporary control group of people who were enrolled during the same period and had not contracted SARS-CoV-2, and a historical control group from a pre-pandemic era. Post-acute COVID-19 care should involve identification and management of diabetes.

FUNDING

US Department of Veterans Affairs and the American Society of Nephrology.

Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019

BACKGROUND

Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019.

METHODS

We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990-2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals.

FINDINGS

In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (-28·4 to -2·9) for all diabetes, and by 21·0% (-33·0 to -5·9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (-13·6% [-28·4 to 3·4]) and for type 1 diabetes (-13·6% [-29·3 to 8·9]).

INTERPRETATION

Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations.

FUNDING

Bill & Melinda Gates Foundation.

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019

IMPORTANCE

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden.

OBJECTIVE

To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019.

EVIDENCE REVIEW

The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).

FINDINGS

In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles.

CONCLUSIONS AND RELEVANCE

The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Risks of mental health outcomes in people with covid-19: cohort study

OBJECTIVE

To estimate the risks of incident mental health disorders in survivors of the acute phase of covid-19.

DESIGN

Cohort study.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

Cohort comprising 153 848 people who survived the first 30 days of SARS-CoV-2 infection, and two control groups: a contemporary group (n=5 637 840) with no evidence of SARS-CoV-2, and a historical control group (n=5 859 251) that predated the covid-19 pandemic.

MAIN OUTCOMES MEASURES

Risks of prespecified incident mental health outcomes, calculated as hazard ratio and absolute risk difference per 1000 people at one year, with corresponding 95% confidence intervals. Predefined covariates and algorithmically selected high dimensional covariates were used to balance the covid-19 and control groups through inverse weighting.

RESULTS

The covid-19 group showed an increased risk of incident anxiety disorders (hazard ratio 1.35 (95% confidence interval 1.30 to 1.39); risk difference 11.06 (95% confidence interval 9.64 to 12.53) per 1000 people at one year), depressive disorders (1.39 (1.34 to 1.43); 15.12 (13.38 to 16.91) per 1000 people at one year), stress and adjustment disorders (1.38 (1.34 to 1.43); 13.29 (11.71 to 14.92) per 1000 people at one year), and use of antidepressants (1.55 (1.50 to 1.60); 21.59 (19.63 to 23.60) per 1000 people at one year) and benzodiazepines (1.65 (1.58 to 1.72); 10.46 (9.37 to 11.61) per 1000 people at one year). The risk of incident opioid prescriptions also increased (1.76 (1.71 to 1.81); 35.90 (33.61 to 38.25) per 1000 people at one year), opioid use disorders (1.34 (1.21 to 1.48); 0.96 (0.59 to 1.37) per 1000 people at one year), and other (non-opioid) substance use disorders (1.20 (1.15 to 1.26); 4.34 (3.22 to 5.51) per 1000 people at one year). The covid-19 group also showed an increased risk of incident neurocognitive decline (1.80 (1.72 to 1.89); 10.75 (9.65 to 11.91) per 1000 people at one year) and sleep disorders (1.41 (1.38 to 1.45); 23.80 (21.65 to 26.00) per 1000 people at one year). The risk of any incident mental health diagnosis or prescription was increased (1.60 (1.55 to 1.66); 64.38 (58.90 to 70.01) per 1000 people at one year). The risks of examined outcomes were increased even among people who were not admitted to hospital and were highest among those who were admitted to hospital during the acute phase of covid-19. Results were consistent with those in the historical control group. The risk of incident mental health disorders was consistently higher in the covid-19 group in comparisons of people with covid-19 not admitted to hospital versus those not admitted to hospital for seasonal influenza, admitted to hospital with covid-19 versus admitted to hospital with seasonal influenza, and admitted to hospital with covid-19 versus admitted to hospital for any other cause.

CONCLUSIONS

The findings suggest that people who survive the acute phase of covid-19 are at increased risk of an array of incident mental health disorders. Tackling mental health disorders among survivors of covid-19 should be a priority.

Long-term cardiovascular outcomes of COVID-19

The cardiovascular complications of acute coronavirus disease 2019 (COVID-19) are well described, but the post-acute cardiovascular manifestations of COVID-19 have not yet been comprehensively characterized. Here we used national healthcare databases from the US Department of Veterans Affairs to build a cohort of 153,760 individuals with COVID-19, as well as two sets of control cohorts with 5,637,647 (contemporary controls) and 5,859,411 (historical controls) individuals, to estimate risks and 1-year burdens of a set of pre-specified incident cardiovascular outcomes. We show that, beyond the first 30 d after infection, individuals with COVID-19 are at increased risk of incident cardiovascular disease spanning several categories, including cerebrovascular disorders, dysrhythmias, ischemic and non-ischemic heart disease, pericarditis, myocarditis, heart failure and thromboembolic disease. These risks and burdens were evident even among individuals who were not hospitalized during the acute phase of the infection and increased in a graded fashion according to the care setting during the acute phase (non-hospitalized, hospitalized and admitted to intensive care). Our results provide evidence that the risk and 1-year burden of cardiovascular disease in survivors of acute COVID-19 are substantial. Care pathways of those surviving the acute episode of COVID-19 should include attention to cardiovascular health and disease.

Individuals with COVID-19 are at increased long-term risk for a wide range of cardiovascular disorders, even for individuals who were not hospitalized during the acute phase of the infection.

A Deep Learning Approach for the Estimation of Glomerular Filtration Rate

An accurate estimation of glomerular filtration rate (GFR) is clinically crucial for kidney disease diagnosis and predicting the prognosis of chronic kidney disease (CKD). Machine learning methodologies such as deep neural networks provide a potential avenue for increasing accuracy in GFR estimation. We developed a novel deep learning architecture, a deep and shallow neural network, to estimate GFR (dlGFR for short) and examined its comparative performance with estimated GFR from Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. The dlGFR model jointly trains a shallow learning model and a deep neural network to enable both linear transformation from input features to a log GFR target, and non-linear feature embedding for stage of kidney function classification. We validate the proposed methods on the data from multiple studies obtained from the NIDDK Central Database Repository. The deep learning model predicted values of GFR within 30% of measured GFR with 88.3% accuracy, compared to the 87.1% and 84.7% of the accuracy achieved by CKD-EPI and MDRD equations (p=0.051 and p<0.001, respectively). Our results suggest that deep learning methods are superior to equations resulting from traditional statistical methods in estimating glomerular filtration rate. Based on these results, an end-to-end predication system has been deployed to facilitate use of the proposed dlGFR algorithm.

Fine particles matter components and interstitial lung disease in rheumatoid arthritis

Exposure to ambient fine particulate matter (PM_2.5) is a risk factor for pulmonary and systemic autoimmune diseases, however evidence on which PM_2.5 chemical components are more harmful is still scant. Our goal is to investigate potential associations between PM_2.5 components and interstitial lung disease (ILD) onset in rheumatoid arthritis (RA).New-onset RA subjects identified from a United States health care insurance database (MarketScan) were followed for new onset of RA associated ILD (RA-ILD) from 2011 to 2018. Annual ambient PM_2.5 concentrations of its chemical components (i.e. sulfate, nitrate, ammonium, organic matter, black carbon, mineral dust, and sea salt) were estimated by combining satellite retrievals with chemical transport modelling and refined by geographically weighted regression. Exposures from 2006 up to one year before ILD onset or end of study were assigned to subjects based on their metropolitan division or core-based statistical area codes. A novel time-to-event quantile-based g(generalised)-computation approach was used to estimate potential associations between RA-ILD onset and the exposure mixture of all seven PM_2.5 chemical components adjusting for age, sex, and prior chronic obstructive pulmonary disease (as a proxy for smoking).We followed 280 516 new-onset RA patients and detected 2194 RA-ILD cases across 1 394 385 person-years. The adjusted hazard ratio for RA-ILD onset was 1.54 (95% confidence interval 1.47-1.63) per every decile increase in all seven exposures. Ammonium, mineral dust, and black carbon contributed more to ILD risk than the other PM_2.5 components.In conclusion, exposure to elements of PM_2.5, particularly ammonium, increases ILD risk in RA.

Burdens of post-acute sequelae of COVID-19 by severity of acute infection, demographics and health status

The Post-Acute Sequelae of SARS-CoV-2 infection (PASC) have been characterized; however, the burden of PASC remains unknown. Here we used the healthcare databases of the US Department of Veterans Affairs to build a cohort of 181,384 people with COVID-19 and 4,397,509 non-infected controls and estimated that burden of PASC-defined as the presence of at least one sequela in excess of non-infected controls-was 73.43 (72.10, 74.72) per 1000 persons at 6 months. Burdens of individual sequelae varied by demographic groups (age, race, and sex) but were consistently higher in people with poorer baseline health and in those with more severe acute infection. In sum, the burden of PASC is substantial; PASC is non-monolithic with sequelae that are differentially expressed in various population groups. Collectively, our results may be useful in informing health systems capacity planning and care strategies of people with PASC.

Kidney Outcomes in Long COVID

BACKGROUND

COVID-19 is associated with increased risk of post-acute sequelae involving pulmonary and extrapulmonary organ systems-referred to as long COVID. However, a detailed assessment of kidney outcomes in long COVID is not yet available.

METHODS

We built a cohort of 1,726,683 US Veterans identified from March 1, 2020 to March 15, 2021, including 89,216 patients who were 30-day survivors of COVID-19 and 1,637,467 non-infected controls. We examined risks of AKI, eGFR decline, ESKD, and major adverse kidney events (MAKE). MAKE was defined as eGFR decline ≥50%, ESKD, or all-cause mortality. We used inverse probability-weighted survival regression, adjusting for predefined demographic and health characteristics, and algorithmically selected high-dimensional covariates, including diagnoses, medications, and laboratory tests. Linear mixed models characterized intra-individual eGFR trajectory.

RESULTS

Beyond the acute illness, 30-day survivors of COVID-19 exhibited a higher risk of AKI (aHR, 1.94; 95% CI, 1.86 to 2.04), eGFR decline ≥30% (aHR, 1.25; 95% CI, 1.14 to 1.37), eGFR decline ≥40% (aHR, 1.44; 95% CI, 1.37 to 1.51), eGFR decline ≥50% (aHR, 1.62; 95% CI, 1.51 to 1.74), ESKD (aHR, 2.96; 95% CI, 2.49 to 3.51), and MAKE (aHR, 1.66; 95% CI, 1.58 to 1.74). Increase in risks of post-acute kidney outcomes was graded according to the severity of the acute infection (whether patients were non-hospitalized, hospitalized, or admitted to intensive care). Compared with non-infected controls, 30-day survivors of COVID-19 exhibited excess eGFR decline (95% CI) of -3.26 (-3.58 to -2.94), -5.20 (-6.24 to -4.16), and -7.69 (-8.27 to -7.12) ml/min per 1.73 m² per year, respectively, in non-hospitalized, hospitalized, and those admitted to intensive care during the acute phase of COVID-19 infection.

CONCLUSIONS

Patients who survived COVID-19 exhibited increased risk of kidney outcomes in the post-acute phase of the disease. Post-acute COVID-19 care should include attention to kidney disease.

Global, regional, and national mortality among young people aged 10-24 years, 1950-2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10-24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019.

METHODS

We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10-24 years by age group (10-14 years, 15-19 years, and 20-24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10-24 years with that in children aged 0-9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10-24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017).

FINDINGS

In 2019 there were 1·49 million deaths (95% uncertainty interval 1·39-1·59) worldwide in people aged 10-24 years, of which 61% occurred in males. 32·7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32·1% were due to communicable, nutritional, or maternal causes; 27·0% were due to non-communicable diseases; and 8·2% were due to self-harm. Since 1950, deaths in this age group decreased by 30·0% in females and 15·3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10-14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15-19 years was 1·3% in males and 1·6% in females, almost half that of males aged 1-4 years (2·4%), and around a third less than in females aged 1-4 years (2·5%). The proportion of global deaths in people aged 0-24 years that occurred in people aged 10-24 years more than doubled between 1950 and 2019, from 9·5% to 21·6%.

INTERPRETATION

Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10-24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group.

FUNDING

Bill & Melinda Gates Foundation.

Association of Ambient Fine Particulate Matter Air Pollution With Kidney Transplant Outcomes

IMPORTANCE

Increased levels of ambient fine particulate matter (PM2.5) air pollution are associated with increased risks for detrimental health outcomes, but risks for patients with kidney transplants (KTs) remain unknown.

OBJECTIVE

To investigate the association of PM2.5 exposure with KT outcomes.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study was conducted using data on patients who received KTs from 2004 to 2016 who were identified in the national US transplant registry and followed up through March 2021. Multiple databases were linked to obtain data on PM2.5 concentration, KT outcomes, and patient clinical, transplant, and contextual factors. Data were analyzed from April 2020 through July 2021.

EXPOSURES

Exposures included post-KT time-dependent annual mean PM2.5 level (in 10 μg/m3) and mean PM2.5 level in the year before KT (ie, baseline levels) in quartiles, as well as baseline annual mean PM2.5 level (in 10 μg/m3).

MAIN OUTCOMES AND MEASURES

Acute kidney rejection (ie, rejection within 1 year after KT), time to death-censored graft failure, and time to all-cause death. Multivariable logistic regression for kidney rejection and Cox analyses with nonlinear assessment of exposure-response for death-censored graft failure and all-cause death were performed. The national burden of graft failure associated with PM2.5 levels greater than the Environmental Protection Agency recommended level of 12 μg/m3 was estimated.

RESULTS

Among 112 098 patients with KTs, 70 522 individuals (62.9%) were older than age 50 years at the time of KT, 68 117 (60.8%) were men, and the median (IQR) follow-up was 6.0 (3.9-8.9) years. There were 37 265 Black patients (33.2%), 17 047 Hispanic patients (15.2%), 48 581 White patients [43.3%]), and 9205 patients (8.2%) of other race or ethnicity. The median (IQR) baseline PM2.5 level was 9.8 (8.3-11.9) μg/m3. Increased baseline PM2.5 level, compared with quartile 1 baseline PM2.5 level, was not associated with higher odds of acute kidney rejection for quartile 2 (adjusted odds ratio [aOR], 0.99; 95% CI, 0.92-1.06) but was associated with increased odds for quartile 3 (aOR, 1.11; 95% CI, 1.04-1.20) and quartile 4 (aOR, 1.13; 95% CI, 1.05-1.23). Nonlinear assessment of exposure-response for graft failure and death showed no evidence for nonlinearity. Increased PM2.5 levels were associated with increased risk of death-censored graft failure (adjusted hazard ratio [aHR] per 10 μg/m3 increase, 1.17; 95% CI, 1.09-1.25) and all-cause death (aHR per 10 μg/m3 increase, 1.21; 95% CI, 1.14-1.28). The national burden of death-censored graft failure associated with PM2.5 above 12 μg/m3 was 57 failures (95% uncertainty interval, 48-67 failures) per year among patients with KTs.

CONCLUSIONS AND RELEVANCE

This cohort study found that PM2.5 level was an independent risk factor associated with acute rejection, graft failure, and death among patients with KTs. These findings suggest that efforts toward decreasing levels of PM2.5 concentration may be associated with improved outcomes after KT.

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

BACKGROUND

Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival.

METHODS

We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (U5MR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index.

FINDINGS

Global U5MR decreased from 71·2 deaths per 1000 livebirths (95% uncertainty interval [UI] 68·3-74·0) in 2000 to 37·1 (33·2-41·7) in 2019 while global NMR correspondingly declined more slowly from 28·0 deaths per 1000 live births (26·8-29·5) in 2000 to 17·9 (16·3-19·8) in 2019. In 2019, 136 (67%) of 204 countries had a U5MR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030, 154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9·65 million (95% UI 9·05-10·30) in 2000 and 5·05 million (4·27-6·02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3·76 million [95% UI 3·53-4·02]) in 2000 to 48% (2·42 million; 2·06-2·86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0·80 (95% UI 0·71-0·86) deaths per 1000 livebirths and U5MR to 1·44 (95% UI 1·27-1·58) deaths per 1000 livebirths, and in 2019, there were as many as 1·87 million (95% UI 1·35-2·58; 37% [95% UI 32-43]) of 5·05 million more deaths of children younger than 5 years than the survival potential frontier.

INTERPRETATION

Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve U5MR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress.

FUNDING

Bill & Melinda Gates Foundation.

Ambient fine particulate matter air pollution and the risk of hospitalization among COVID-19 positive individuals: Cohort study

BACKGROUND

Ecologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking.

METHODS

We leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization.

RESULTS

There were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001).

CONCLUSIONS

Exposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.

Temporal trends of COVID-19 mortality and hospitalisation rates: an observational cohort study from the US Department of Veterans Affairs

OBJECTIVES

To investigate the temporal trends of 30-day mortality and hospitalisation in US Veterans with COVID-19 and 30-day mortality in hospitalised veterans with COVID-19 and to decompose the contribution of changes in the underlying characteristics of affected populations to these temporal changes.

DESIGN

Observational cohort study.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

49 238 US veterans with a positive COVID-19 test between 20 March 2020 and 19 September 2020; and 9428 US veterans hospitalised with a positive COVID-19 test during the same period.

OUTCOME MEASURES

30-day mortality rate and hospitalisation rate.

RESULTS

Between 20 March 2020 and 19 September 2020 and in COVID-19 positive individuals, 30-day mortality rate dropped by 9.2% from 13.6% to 4.4%; hospitalisation rate dropped by 16.8% from 33.8% to 17.0%. In hospitalised COVID-19 individuals, 30-day mortality rate dropped by 12.7% from 23.5% to 10.8%. Among COVID-19 positive individuals, decomposition analyses suggested that changes in demographic, health and contextual characteristics, COVID-19 testing capacity, and hospital occupancy rates accounted for 40.2% and 33.3% of the decline in 30-day mortality and hospitalisation, respectively. Changes in the underlying characteristics of hospitalised COVID-19 individuals accounted for 29.9% of the decline in 30-day mortality.

CONCLUSION

Between March and September 2020, changes in demographic and health characteristics of people infected with COVID-19 contributed measurably to the substantial decline in 30-day mortality and hospitalisation.