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

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

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

Molecular Mechanisms of AMPK- and Akt-Dependent Survival of Glucose-Starved Cardiac Myocytes

Muscle may experience hypoglycemia during ischemia or insulin infusion. During severe hypoglycemia energy production is blocked and an increase in AMP:ATP activates the energy sensor and putative insulin-sensitizer AMP-dependent protein kinase (AMPK). AMPK promotes energy conservation and survival by shutting down anabolism and activating catabolic pathways. We investigated the molecular mechanism of a unique glucose stress defense pathway involving AMPK-dependent, insulin-independent activation of the insulin signaling pathway. Results from my work showed that the central insulin signaling pathway is rapidly activated when cardiac and skeletal myocytes are subjected to conditions of glucose starvation. The effect occurred independently of insulin receptor ligands (insulin and IGF-1). There was a \u3e10-fold increase in the activity of Akt as determined by phosphorylation on both Thr308 and Ser473. Phosphorylation of glycogen synthase 3 beta (GSK3b) increased in parallel, but phosphorylation of ribosomal 70S subunit-S6 protein kinase (S6K) and the mammalian target of rapamycin complex 1 (mTORC1) decreased. We identified AMPK as an intermediate in this signaling network; AMPK was activated by glucose starvation and many of the effects were mimicked by the AMPK-selective activator aminoimidazole carboxamide ribonucleotide (AICAR) and blocked by AMPK inhibitors. Glucose starvation increased the phosphorylation on IRS-1 on Ser789, but phosphomimetics revealed that this conferred negative regulation. Glucose starvation enhanced tyrosine phosphorylation of IRS-1 and the insulin receptor, effects that were blocked by AMPK inhibition and mimicked by AICAR. In vitro kinase assays using purified proteins confirmed that the insulin receptor is a direct target of AMPK. Insulin receptor kinase activity was essential for cardiac myocytes to survive gluose starvation as inhibition of the IR led to increased cell death in glucose-starved myocytes. Selective activation of mTORC2 by glucose starvation to increase Akt-Ser473 phosphorylation was dependent on the presence of rictor. SIN1 also seemed to be instrumental in the activation of mTORC2 as its levels and binding to rictor increased under glucose starvation. AMPK-mediated activation of the insulin signaling pathway conferred significant protection against the stresses of glucose starvation. Glucose starvation promoted energy conservation, augmented glucose uptake and enhanced insulin sensitivity in an AMPK- and Akt-dependent manner. My results describe a novel ligand-independent and AMPK-dependent activation of the insulin signaling pathway via direct phosphorylation and activation of the IR followed by activation of PI3K and Akt. These results may be relevant in conditions of myocardial ischemia superimposed with type 2 diabetes where AMPK could directly modify the IR to promote cell survival and confer protection

Heterogeneity in SDF-1 expression defines the vasculogenic potential of adult cardiac progenitor cells.

The adult myocardium has been reported to harbor several classes of multipotent progenitor cells (CPCs) with tri-lineage differentiation potential. It is not clear whether c-kit+CPCs represent a uniform precursor population or a more complex mixture of cell types.To characterize and understand vasculogenic heterogeneity within c-kit+presumptive cardiac progenitor cell populations.c-kit+, sca-1+ CPCs obtained from adult mouse left ventricle expressed stem cell-associated genes, including Oct-4 and Myc, and were self-renewing, pluripotent and clonogenic. Detailed single cell clonal analysis of 17 clones revealed that most (14/17) exhibited trilineage differentiation potential. However, striking morphological differences were observed among clones that were heritable and stable in long-term culture. 3 major groups were identified: round (7/17), flat or spindle-shaped (5/17) and stellate (5/17). Stellate morphology was predictive of vasculogenic differentiation in Matrigel. Genome-wide expression studies and bioinformatic analysis revealed clonally stable, heritable differences in stromal cell-derived factor-1 (SDF-1) expression that correlated strongly with stellate morphology and vasculogenic capacity. Endogenous SDF-1 production contributed directly to vasculogenic differentiation: both shRNA-mediated knockdown of SDF-1 and AMD3100, an antagonist of the SDF-1 receptor CXC chemokine Receptor-4 (CXCR4), reduced tube-forming capacity, while exogenous SDF-1 induced tube formation by 2 non-vasculogenic clones. CPCs producing SDF-1 were able to vascularize Matrigel dermal implants in vivo, while CPCs with low SDF-1 production were not.Clonogenic c-kit+, sca-1+ CPCs are heterogeneous in morphology, gene expression patterns and differentiation potential. Clone-specific levels of SDF-1 expression both predict and promote development of a vasculogenic phenotype via a previously unreported autocrine mechanism

c-Jun N-terminal Kinase (JNK-1) Confers Protection against Brief but Not Extended Ischemia during Acute Myocardial Infarction*

Brief periods of ischemia do not damage the heart and can actually protect against reperfusion injury caused by extended ischemia. It is not known what causes the transition from protection to irreversible damage as ischemia progresses. c-Jun N-terminal kinase-1 (JNK-1) is a stress-regulated kinase that is activated by reactive oxygen and thought to promote injury during severe acute myocardial infarction. Because some reports suggest that JNK-1 can also be protective, we hypothesized that the function of JNK-1 depends on the metabolic state of the heart at the time of reperfusion, a condition that changes progressively with duration of ischemia. Mice treated with JNK-1 inhibitors or transgenic mice wherein the JNK-1 gene was ablated were subjected to 5 or 20 min of ischemia followed by reperfusion. When JNK-1 was inactive, ischemia of only 5 min duration caused massive apoptosis, infarction, and negative remodeling that was equivalent to or greater than extended ischemia. Conversely, when ischemia was extended JNK-1 inactivation was protective. Mechanisms of the JNK-1 switch in function were investigated in vivo and in cultured cardiac myocytes. In vitro there was a comparable switch in the function of JNK-1 from protective when ATP levels were maintained during hypoxia to injurious when reoxygenation followed glucose and ATP depletion. Both apoptotic and necrotic death pathways were affected and responded reciprocally to JNK-1 inhibitors. JNK-1 differentially regulated Akt phosphorylation of the regulatory sites Ser-473 and Thr-450 and the catalytic Thr-308 site in vivo. The studies define a novel role for JNK-1 as a conditional survival kinase that protects the heart against brief but not protracted ischemia

Phase I Trial of the PARP Inhibitor Olaparib and AKT Inhibitor Capivasertib in Patients with BRCA1/2- and Non-BRCA1/2-Mutant Cancers.

Preclinical studies have demonstrated synergy between PARP and PI3K/AKT pathway inhibitors in BRCA1 and BRCA2 (BRCA1/2)-deficient and BRCA1/2-proficient tumors. We conducted an investigator-initiated phase I trial utilizing a prospective intrapatient dose- escalation design to assess two schedules of capivasertib (AKT inhibitor) with olaparib (PARP inhibitor) in 64 patients with advanced solid tumors. Dose expansions enrolled germline BRCA1/2-mutant tumors, or BRCA1/2 wild-type cancers harboring somatic DNA damage response (DDR) or PI3K-AKT pathway alterations. The combination was well tolerated. Recommended phase II doses for the two schedules were: olaparib 300 mg twice a day with either capivasertib 400 mg twice a day 4 days on, 3 days off, or capivasertib 640 mg twice a day 2 days on, 5 days off. Pharmacokinetics were dose proportional. Pharmacodynamic studies confirmed phosphorylated (p) GSK3β suppression, increased pERK, and decreased BRCA1 expression. Twenty-five (44.6%) of 56 evaluable patients achieved clinical benefit (RECIST complete response/partial response or stable disease ≥ 4 months), including patients with tumors harboring germline BRCA1/2 mutations and BRCA1/2 wild-type cancers with or without DDR and PI3K-AKT pathway alterations. SIGNIFICANCE: In the first trial to combine PARP and AKT inhibitors, a prospective intrapatient dose- escalation design demonstrated safety, tolerability, and pharmacokinetic-pharmacodynamic activity and assessed predictive biomarkers of response/resistance. Antitumor activity was observed in patients harboring tumors with germline BRCA1/2 mutations and BRCA1/2 wild-type cancers with or without somatic DDR and/or PI3K-AKT pathway alterations.This article is highlighted in the In This Issue feature, p. 1426.Sponsor: Institute of Cancer Research and Royal Marsden Hospital Funding: AstraZeneca CRUK ECMC Allianc