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

The blame game of the US baby formula crisis

Abstract The United States cannot meet the demand for infant formula. The nation is currently experiencing a problem due to the industry being controlled by a small number of enterprises, states relying on a single supplier, and a ban on importing infant formula from other nations. The four major corporations’ control 89% of the domestic infant formula market creating an industry monopoly within the United States. Second, the dependence of separate states on a single baby formula provider is the cause of the infant formula shortage. In exchange for granting monopolies to formula producers inside specific areas, the federal government is given price cuts on baby formula goods, enabling it to pay for the acquisition. Finally, the United States's inability to import infant formula has significantly exacerbated the current scarcity. However, in the meanwhile, President Joe Biden's administration has put stopgap measures in place to end this shortage, like loosening limits on imports from abroad, but these measures are unlikely to provide long‐term remedies. A multi‐level strategy with long‐lasting structural adjustments is required to avert future infant formula shortages in the United States, but for the time being, caregivers must find individual‐level solutions to meet their children's nutritional needs

Racial/ethnic differences in maternal feeding practices and beliefs at 6 months postpartum

Objective: To examine racial/ethnic differences in maternal feeding practices and beliefs in a sample of low-income smoke-exposed women. Design: Cross-sectional analysis using data collected during a randomised control trial. Maternal feeding practices and beliefs were assessed using the Infant Feeding Questionnaire (IFQ), which was administered at 6 months postpartum. ANOVA was used to examine differences in IFQ items by race/ethnicity, while multivariable linear regression models were used to examine differences in IFQ factor scores by race/ethnicity adjusting for potential confounders. Setting: Participants were recruited from prenatal clinics. Participants: 343 women (39 % non-Hispanic White, 28 % Hispanic/Latina, 13 % Black, and 20 % other). Results: Racial/ethnic minority mothers were more likely than non-Hispanic White mothers to put cereal in their infant's bottle so that the infant would stay full longer (P = 0 center dot 032), state their infant wanted more than just formula or breast milk prior to 4 months (P = 0 center dot 019), allow their infant to eat whenever he/she wanted (P = 0 center dot 023) and only allow their infant to eat at set times (P < 0 center dot 001). Adjusting for potential confounders, racial/ethnic minority mothers had higher scores for factors 1 (concern about infant undereating or becoming underweight), 2 (concern about infant's hunger), 4 (concern about infant overeating or becoming overweight) and 5 (feeding infant on a schedule), and lower scores for factor 7 (social interaction with the infant during feeding) than White mothers. Racial/ethnic differences were not found for the other two factors. Conclusions: Differences in maternal feeding practices and beliefs across race/ethnicity are present at 6 months postpartum

The Regulation and Function of the Forkhead Transcription Factor, Forkhead Box O1, Is Dependent on the Progesterone Receptor in Endometrial Carcinoma

In many type I endometrial cancers, the PTEN gene is inactivated, which ultimately leads to constitutively active Akt and the inhibition of Forkhead box O1 (FOXO1), a member of the FOXO subfamily of Forkhead/winged helix family of transcription factors. The expression, regulation, and function of FOXO1 in endometrial cancer were investigated in this study. Immunohistochemical analysis of 49 endometrial tumor tissues revealed a decrease of FOXO1 expression in 95.9% of the cases compared with the expression in normal endometrium. In four different endometrial cancer cell lines (ECC1, Hec1B, Ishikawa, and RL95), FOXO1 mRNA was expressed at similar levels; however, protein levels were low or undetectable in Ecc1, Ishikawa, and RL95 cells. Using small interfering RNA technology, we demonstrated that the low levels of FOXO1 protein were due to the involvement of Skp2, an oncogenic subunit of the Skp1/Cul1/F-box protein ubiquitin complex, given that silencing Skp2 increased FOXO1 protein expression in Ishikawa cells. Inhibition of Akt in Ishikawa cells also increased nuclear FOXO1 protein levels. Additionally, progestins increased FOXO1 protein levels, specifically through progesterone receptor B (PRB) as determined by using stably transfected PRA-specific and PRB-specific Ishikawa cell lines. Finally, overexpression of triple mutant (Tm) FOXO1 in the PR-specific Ishikawa cell lines caused cell cycle arrest and significantly decreased proliferation in the presence and absence of the progestin, R5020. Furthermore, TmFOXO1 overexpression induced apoptosis in PRB-specific cells in the presence and absence of ligand. Taken together, these data provide insight into the phosphoinositide-3-kinase/Akt/FOXO pathway for the determination of progestin responsiveness and the development of alternate therapies for endometrial cancer

Bacterial community structures of an alpine apatite deposit

Apatite represents an important source of inorganic P for natural ecosystems and may favour the establishment of microbial communities able to exploit it. We investigated if microbial community composition in a natural alpine apatite deposit (Piatto della Miniera, canton of Ticino, Switzerland) would differ from the surroundings. Soils were sampled from 3 transects across the apatite deposit and divided in apatite (AP) and non-apatite (NAP) samples. The presence of apatite in the AP samples was confirmed by X-ray diffraction (XRD) and X-ray fluorescence (XRF) analyses. Bacterial community structures were assessed by 16S rRNA gene-based terminal restriction fragment length polymorphism (t-RFLP) and clone libraries. Generally, the AP samples were characterised by higher water-extractable P (e.g. up to 3.1 mg P (g soil dry wt)− 1), and higher concentrations of organic acids than the NAP samples. t-RFLP analysis showed different bacterial community structures in the AP and NAP samples. The 16S rRNA gene clone libraries of the AP samples were dominated by Acidobacteria, Chloroflexi, Actinobacteria, Rhizobiales and Firmicutes (relative abundance > 10%), while the NAP samples had a higher relative abundance of Actinobacteria and Chloroflexi (relative abundance > 20%). The number of different phylotypes related to the dominant groups of the AP clone libraries (11–13) was lower than those in the NAP libraries (17–32). Libshuff analysis of the obtained sequences indicated that the communities developing on the AP are a subpopulation of the flanking NAP sites. Our results suggest that under natural conditions, the presence of rock phosphate may not be the main driving force for bacterial community structures

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

BackgroundRegular, 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.MethodsThe 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.FindingsThe 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.InterpretationLong-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

Global Burden of Cardiovascular Diseases and Risks, 1990-2022

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is a multinational collaborative research study with >10,000 collaborators around the world. GBD generates a time series of summary measures of health, including prevalence, cause-specific mortality (CSMR), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) to provide a comprehensive view of health burden for a wide range of stakeholders including clinicians, public and private health systems, ministries of health, and other policymakers. These estimates are produced for 371 causes of death and 88 risk factors according to mutually exclusive, collectively exhaustive hierarchies of health conditions and risks. The study is led by a principal investigator and governed by a study protocol, with oversight from a Scientific Council, and an Independent Advisory Committee.1 GBD is performed in compliance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).2 GBD uses de-identified data, and the waiver of informed consent was reviewed and approved by the University of Washington Institutional Review Board (study number 9060). This almanac presents results for 18 cardiovascular diseases (CVD) and the CVD burden attributed to 15 risk factors (including an aggregate grouping of dietary risks) by GBD region. A summary of methods follows. Additional information can be found online at https://ghdx.healthdata.org/record/ihme-data/cvd-1990-2022, including:Funding was provided by the Bill and Melinda Gates Foundation, and the American College of Cardiology Foundation. The authors have reported that they have no relationships relevant to the contents of this paper to disclose. The contents and views expressed in this report are those of the authors and do not necessarily reflect the official views of the National Institutes of Health, the Department of Health and Human Services, the U.S. Government, or the affiliated institutions