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BACKGROUND: In countries with high life expectancy, a growing share of the population is living with several diseases, a situation referred to as multi-morbidity. In addition to health data, cause-of-death data, based on the information reported on death certificates, can help monitor and characterize this situation. This requires going beyond the underlying cause of death and accounting for all causes on the death certificates which may have played various roles in the morbid process, depending on how they relate to each other. METHODS: Apart from the underlying cause, the cause-of death data available in vital registration systems do not differentiate all other causes. We developed an algorithm based on the WHO rules that assigns a role to each entry on the death certificate. We distinguish between the following roles: originating (o), when the condition has initiated a sequence of events leading directly to death; precipitating (p), when it was caused by an originating condition or one of its consequences; associated (a), when it contributed to death but was not part of the direct sequence leading to death; ill-defined (i), i.e., conditions such as symptoms or signs or poorly informative causes. We applied this algorithm to all death records in four countries (Italy, France, Spain and the US) in 2017. RESULTS: The average number of originating causes is similar in the four countries. The proportion of death certificates with more than one originating cause-a situation typical of multi-morbidity-ranges from 10% in the US to 18% in Spain. All ages combined, the proportion of deaths with at least one associated cause is higher in Italy (41%) and in the US (42%) than in France (29%) and in Spain (27%). It is especially high in the US at all adult ages. Variations in the average number of causes between the four countries are mainly due to precipitating and ill-defined causes. CONCLUSIONS: The output of our algorithm sheds light on cross-country differences in the average number of causes on death certificates. It also opens the door for improvements in the methods used for multiple cause-of-death analysis.

Bariatric dentistry is the branch of dental medicine focused on preventive and comprehensive oral health care of overweight or obese patients. Obesity is an increasing US and international health problem and is a condition characterized by abnormal or excessive fat accumulation in the adipose tissue and is categorized by body mass index (BMI) according to the World Health Organization (WHO). With the increase of morbid obesity worldwide and the unfavorable effect on the overall health and life expectancy, it is necessary that proper accommodations are made for accessible dental care of this vulnerable population of patients. The following case report details the emergency and the subsequent elective dental treatment of a patient with a morbid obesity and demonstrates the importance of necessary equipment, a multidisciplinary approach, and broad networking communication needed to treat bariatric patients. The aim of the present case report was to bring awareness and start professional discussions on the importance of dental practitioners in the community and dental academic programs working together to assure access for primary oral health for bariatric patients. [ABSTRACT FROM AUTHOR]

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.

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.

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.

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.

BACKGROUND: Research on the health and economic costs due to insufficient sleep remains scant in developing countries. In this study we aimed to estimate the years of life lost (YLLs) due to short sleep and quantify its economic burden in China. METHODS: We estimated both individual and aggregate YLLs due to short sleep (ie, ≤6 hours) among Chinese adults aged 20 years or older by sex and five-year age groups in 2010, 2014, and 2018. YLL estimates were derived from 1) the prevalence of short sleep using three survey waves of the China Family Panel Studies, 2) relative mortality risks from meta-analyses, and 3) life tables in China. YLL was the difference between the estimated life expectancy of an individual in the short sleep category vs in the recommended sleep category. We estimated the economic cost using the human capital approach. RESULTS: The sample sizes of the three survey waves were 31 393, 31 207, and 28 618. Younger age groups and men had more YLLs due to short sleep compared to their counterparts. For individuals aged 20-24, men had an average YLL of nearly 0.95, in contrast to the approximate 0.75 in women across the observed years of 2010, 2014, and 2018. The trend in individual YLLs remained consistent over these years. In aggregate, China experienced a rise from 66.75 million YLLs in 2010 to 95.29 million YLLs in 2014, and to 115.05 million YLLs in 2018. Compared to 2010 (USD 191.83 billion), the associated economic cost in 2014 increased to USD 422.24 billion, and the cost in 2018 more than tripled (USD 628.15 billion). The percentage of cost to Chinese gross domestic product in corresponding years was 3.23, 4.09, and 4.62%. CONCLUSIONS: Insufficient sleep is associated with substantial YLLs in China, potentially impacting the populations overall life expectancy. The escalating economic toll attributed to short sleep underscores the urgent need for public health interventions to improve sleep health at the population level.

BACKGROUND: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. METHODS: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. FINDINGS: Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378-521), affecting 3·40 billion (3·20-3·62) individuals (43·1%, 40·5-45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7-26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6-38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5-32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7-2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimers disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. INTERPRETATION: As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. FUNDING: Bill & Melinda Gates Foundation.

Despite long-term survival reports in early gastric cancer, comparative life expectancy data with the general population is scarce. This study aimed to estimate patients' life expectancy and analyze disparities between early gastric cancer patients and the general population. Patients with stage 1 gastric cancer who underwent curative gastrectomy at Asan Medical Center were enrolled. Survival status was tracked via national health insurance records. Life expectancy was compared with general population data from the Korean Statistical Information Service database. The cohort comprised 8,637 patients (64.7% men, 17.3% aged 70+). Approximately 20% of patients underwent total gastrectomy. Life expectancy was favorable among women. Across all age groups, women's life expectancy generally exceeded 80 years. Male patients showed a reduced life expectancy, typically 4–10 years shorter than their female counterparts. The average life expectancy of male patients aged over 80 years who underwent total gastrectomy was about 5 years, whereas that of their female counterparts was approximately 7 years. Female patients undergoing distal gastrectomy did not demonstrate a statistically significant variance in life expectancy compared to the general population. This study provided comprehensive life expectancy data, organized by age, sex, and type of gastrectomy in a large stage 1 gastric cancer cohort. Our findings are expected to alleviate uncertainties and anxieties for individuals diagnosed with early gastric cancer. [ABSTRACT FROM AUTHOR]

Internet use has become an important factor affecting health. The spatio-temporal heterogeneity of the influence of internet utilization on life expectancy has not been thoroughly investigated on a global scale. The spatial clustering patterns that influence of internet usage on residents' health levels have not yet been detected. The Geographically and Temporally Weighted Regression (GTWR) model is used to examine the spatio-temporal variation of the associations between internet use and life expectancy in 182 countries from 1990 to 2020. K-mean is employed to reveal the spatial clustering patterns exhibited by GTWR fitting coefficients. The results demonstrate that internet use significantly and positively impacts life expectancy globally based on GTWR fitting coefficients. Meanwhile, the influence of internet use on life expectancy demonstrates spatio-temporal heterogeneity and non-stationarity. Furthermore, six distinctive spatial clusters are revealed utilizing the GTWR fitting coefficients as a foundation. Spatial cluster 1 is the region where internet use has the least health-promoting effect, whereas spatial cluster 6 is the region where internet use has the greatest health-promoting effect. Our findings offer novel insights into the spatio-temporal heterogeneity relationship and non-stationarity between internet use and life expectancy while providing empirical evidence to support the implementation of region-specific internet policies aimed at enhancing health outcomes. [ABSTRACT FROM AUTHOR]

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Estimating population from archaeological data involves understanding the representativeness of the supporting material, its chronology and its duration. The Bury grave, located NW of Paris and dated from the late fourth and third millennia BCE, provides all the data for a precise characterisation of more than three hundred dead. The living population was estimated, both qualitatively and quantitatively, on the basis of chronological modeling and references from historical demography for pre-industrial populations.The results show a major societal shift between the short first phase of the grave use (late fourth millennium BCE), which corresponds to a real community, and the more extensive second phase during the third millennium BCE, which contains a more drastic selection of dead.We propose to consider the results from Bury as a reference for other graves, which did not provide all the information required for demographic analysis. Bury was thus used to examine the Late Neolithic population of the area located NW of Paris, which corresponds to the main concentration of large collective and megalithic graves, named allées sépulcrales. No less than ten thousand people lived in this area of 2500 km2 during the last centuries of the fourth millennium BCE. It can be assumed that the very high concentration of megalithic burials between northern Germany and southern Sweden refers to a situation identical to that of the Paris area. [ABSTRACT FROM AUTHOR]

In the context of the ongoing war in the Gaza Strip, the Gaza Health Ministry (GHM) has reported 45 936 fatalities and more than 10 000 individuals missing or under the rubble for the period Oct 7, 2023, to Jan 8, 2025. The scope of this death count is difficult to fully interpret because it does not account for the size and age distribution of the Gaza Strip population. Moreover, the quality of this death count has been questioned. In this study, we evaluated the quality of the GHM death count by comparing GHM data against register data, and we estimated life expectancy losses in the Gaza Strip for the period October, 2023, to September, 2024, ie, the first 12 months of the war. We matched individuals included in the GHM nominative list of killed individuals for the period Oct 7, 2023, to Aug 30, 2024, with individuals included in the refugee register maintained by the UN Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), which covers about 66% of the Gaza Strip population. We compared proportions of matched fatalities with proportions of registered refugees in the 2017 census. We then used census data, vital registration data, and GHM fatality information since Oct 7, 2023, to produce estimates of life expectancy losses in the Gaza Strip for the first 12 months of the war. We used three scenarios for these life expectancy estimates, based on the different types of counts provided by GHM. These scenarios did not account for the indirect effect of the war. 21 953 (63·9%) of 34 344 individuals in the GHM list of killed individuals (and 19 744 [64·4%] of 30 673 excluding those who were not yet born at the time of the 2017 census) were matched with individuals included in the UNRWA refugee register. This proportion is similar to the proportion of registered refugees in the 2017 census (65·7%), providing additional evidence regarding the reliability of the GHM data. In the central variant, life expectancy in the Gaza Strip decreased by 34·9 years during the first 12 months of the war, about half (–46·3%) the prewar level of 75·5 years. Life expectancy losses were larger for males (–38·0 years [–51·6%]) than for females, but nonetheless, females also suffered large losses (–29·9 years [–38·6%]). Losses between the low and high variants ranged between –31·1 years (–41·1%) and –39·4 years (–52·2%) for both sexes combined. Our approach to estimating life expectancy losses in this study is conservative as it ignores the indirect effect of the war on mortality. Even ignoring this indirect effect, results show that the ongoing war in the Gaza Strip generated a life expectancy loss of more than 30 years during the first 12 months of the war, nearly halving prewar levels. Actual losses are likely to be higher. None. [ABSTRACT FROM AUTHOR]

Background: Research on carceral institutions and mortality finds that people in prisons and jails have a high risk of death immediately following release from custody and that while incarcerated, racial disparities in prisoner mortality counter observed death patterns among similarly situated non-incarcerated, demographic groups. Yet, many of these studies rely on data prior to the millennium, during the COVID-19 pandemic, or are relegated to a small number or select group of states. In this paper, we explore changes in mortality and life-expectancy among different demographic groups, before and after the Great Recession, across forty-four states that reported deaths in custody to the federal government between 2000 and 2014. Methods: Drawing on a novel dataset created and curated, we calculate standard, age- specific quantities (death rates and life-expectancy) using period lifetable methods, disaggregated by race and sex, across three different periods (2000–2004, 2005–2009, and 2010–2014) for each state. Ordinary least squares regression models with state and year fixed-effects are included to examine state-level factors that may explain differences in prisoner mortality rates between 2000 and 2014. We also benchmark death counts reported to federal agencies with official state reports to cross-validate general mortality patterns. Results: Among imprisoned men, age-specific trends in mortality have shifted across the three periods. Following the Great Recession and the push for criminal justice reforms, prisoner mortality dropped significantly and is concentrated at older ages among men during 2010–2014; the shifting pattern of mortality means that men age 30 in 2010–2014 had similar death rates as men in their early 20s during 2000–2004, representing a 7.5 year shift in age-specific mortality rates. Gains in the mortality decline were disproportionately experienced by Non-Hispanic White and Non-Hispanic Black men, with the latter experiencing the greatest gains in life-expectancy of any demographic group. State-level violent crime rates are strongly and positively associated with prison mortality rates across states, net of socioeconomic and political factors. The large and significant disappearance of deaths in prisons from official data reported to federal agencies calls into question the narrowing gap in racial disparities among people in carceral facilities. Conclusions: Legal decisions and social policies aimed at reducing mortality may be most effective in the short-run; however, the effects of these policy changes may fadeout over time. Research should clearly discern whether changes in mortality rates across states are due to diminished gains in social policies or increases in the disappearance (or underreporting) of deaths in custody. Understanding how and why gains in survivorship may stall is important for aligning health initiatives with social policy to facilitate maximal and consistent mortality declines for all demographic groups. [ABSTRACT FROM AUTHOR]

This review aimed to formulate the most current, evidence-based recommendations for the prediction of outcome, life expectancy, and quality of life in patients with metastatic vertebral tumors. A systematic literature search on PubMed and Google Scholar from 2012–2022 was done, using the keywords "metastatic vertebral tumors + outcome prediction + prognoses," "quality of life + spine metastases," and "spine metastases + life expectancy." Our PubMed search yielded 402 articles for outcome prediction, whereas 40 articles were identified for life expectancy in spine metastases. These were carefully screened by the co-authors, resulting in 61 and 11 final articles analyzed for this study. Our PubMed search for quality of life yielded 137 articles, of which 63 were carefully analyzed for this study. This up-to-date information was reviewed at two separate Spine Committee meetings of the World Federation of Neurosurgical Societies (WFNS). Two rounds of the Delphi method were used to vote and arrive at a positive or negative consensus. The WFNS Spine Committee finalized seven recommendation guidelines on the prediction of outcome, life expectancy, and quality of life in metastatic vertebral tumors. Irrespective of the primary tumor, surgical decompression in appropriately selected patients potentially improves the quality of life. Pre-operative ambulatory status, overall performance, and age are independent predictors of outcome and overall survival. Prognostic scoring systems have evolved to principle-based algorithms, amongst which NOMS is the most widely used.The best tools to measure the quality of life are EUQOL5-D and SOSGOQ in patients with metastatic spine disease. [ABSTRACT FROM AUTHOR]

Dentists can be exposed to dust and nanoparticles from teeth, dental composites, and metal alloys generated during dental procedures, and exposure to dust can cause respiratory diseases, including pulmonary fibrosis. The authors describe mortality from nonmalignant respiratory diseases (NMRDs) among dentists in the United States. The authors submitted information on US dentists who died from 1979 through 2018 to a centralized US death records database to obtain underlying causes of death. Decedent data that met records-matching criteria were analyzed using the Life Table Analysis System software (National Institute for Occupational Safety and Health) to calculate proportionate mortality ratios (PMRs), indirectly standardized for age, sex, race, and 5-year calendar period with 95% CIs, for NMRD and a group of International Classification of Diseases, Ninth and Tenth Revision codes approximating idiopathic pulmonary fibrosis. Among 21,928 dentist decedents with complete race information, 1,583 deaths (7.2%) resulted from NMRD. Proportionate mortality for dentist decedents was significantly lower than the general population for NMRD overall (PMR, 0.66; 95% CI, 0.62 to 0.69), chronic obstructive pulmonary disease (PMR, 0.44; 95% CI, 0.41 to 0.48), and pneumonia (PMR, 0.73; 95% CI, 0.67 to 0.81) but significantly higher than the general population for the pulmonary fibrosis group (PMR, 1.57; 95% CI, 1.37 to 1.80). Dentists had decreased proportionate mortality for most NMRD and increased proportionate mortality for underlying causes of death associated with pulmonary fibrosis. Existing engineering controls that reduce inhalational exposures during dental procedures might be inadequate. Improved characterization of these exposures could help inform more effective engineering controls. [ABSTRACT FROM AUTHOR]

Gender mainstreaming is designed to address the social roles of both women and men. How are men included in gender equality policies? I conduct an analysis of all gender equality strategies and annual reports of the European Commission – a global leader in this field – since 1982. I find that, since the mid 1990s, the Commission has included men as contributors to gender equality ('problem solvers'). Yet, men's disadvantages in education and health were only addressed between 2006 and 2015. Later on, men's problems have been ignored, as they have been increasingly portrayed as a uniformly privileged group, undeserving of European policies. This withdrawal from addressing men's problems exposes the tension between legitimising policies for one group (women) and addressing the needs of a complementary group (men). A novel approach to gender equality policies should revive the global debate on their meaning and implications. My findings also raise new questions about the power of the European Commission to construct policy target populations. [ABSTRACT FROM AUTHOR]

Background: The rate of disease progression, measured by the decline of ALS Functional Rating Scale-Revised (ALSFRS-R) from symptom onset to diagnosis (ΔFS) is a well-established prognostic biomarker for predicting survival. Objectives: This study aims to categorize a large patient cohort based on the initial ΔFS and subsequently investigate survival deviations from the expected prognosis defined by ΔFS. Methods: 1056 ALS patients were stratified into three progression categories based on their ΔFS: slow progressors (below 25th percentile), intermediate progressors (between 25th and 75th percentiles), and fast progressors (above 75th percentile). Survival outcomes were classified as short survivors (<2 years), average survivors (2–5 years), and long survivors (>5 years). Clinical and demographic characteristics within each subgroup were then analyzed. Results: ΔFS stratification yielded cutoff values of <0.29, 0.29–1.03, and >1.03 points/month. Long survivors comprised 26% and 21% were short survivors. Six percent of the fast progressors had a life expectancy of more than 5 years, and none of the clinical and demographic characteristics analyzed could fully explain this discrepancy. Conversely, 13% of intermediate progressors lived less than 2 years, according to a short-diagnostic delay in these patients. Discussion: Our study reaffirms ΔFS as a prognostic biomarker for ALS. We disclosed outliers defying anticipated patterns. The observed shift in progression categories underscores the non-linear nature of disease progression. Genetic and unknown biological reasons may explain these deviations. Further research is needed to fully understand modulation of ALS survival. [ABSTRACT FROM AUTHOR]

[Display omitted] • This review has provided a comprehensive synthesis of evidences on aging-related/caused gut microbiota features. • The gut microbiota of centenarians has been emphasized in revealing healthy-aging related microbial and metabolic properties. • This review has depicted aging-related gut microbiota features in higher resolution (at species, and even strain levels). • This review has explored and proposed potential dietary approaches including specific dietary components that target aging-associated microbiota biomarkers. • This review has updated new findings on microbial-related aging (e.g., new microbial-derived biomarker including δ-valerobetaine). Population aging has become a primary global public health issue, and the prevention of age-associated diseases and prolonging healthy life expectancies are of particular importance. Gut microbiota has emerged as a novel target in various host physiological disorders including aging. Comprehensive understanding on changes of gut microbiota during aging, in particular gut microbiota characteristics of centenarians, can provide us possibility to achieving healthy aging or intervene pathological aging through gut microbiota-directed strategies. This review aims to summarize the characteristics of the gut microbiota associated with aging, explore potential biomarkers of aging and address microbiota-associated mechanisms of host aging focusing on intestinal barrier and immune status. By summarizing the existing effective dietary strategies in aging interventions, the probability of developing a diet targeting the gut microbiota in future is provided. This review is focused on three key notions: Firstly, gut microbiota has become a new target for regulating health status and lifespan, and its changes are closely related to age. Thus, we summarized aging-associated gut microbiota features at the levels of key genus/species and important metabolites through comparing the microbiota differences among centenarians, elderly people and younger people. Secondly, exploring microbiota biomarkers related to aging and discussing future possibility using dietary regime/components targeted to aging-related microbiota biomarkers promote human healthy lifespan. Thirdly, dietary intervention can effectively improve the imbalance of gut microbiota related to aging, such as probiotics, prebiotics, and postbiotics, but their effects vary among. [ABSTRACT FROM AUTHOR]

Objective: To investigate the longevity of a large sample of Olympic Games participants, considering the interaction between different types of sports and medal awards. Methodolgy: Data scraping from Wikipedia and Wikidata allowed us to collect a sample of 102,993 famous athletes. We selected 20 of the most populated disciplines to make the groups comparable. We conducted a comparison of life duration on a subset of 17,194 elite athletes, predominantly male, dead at the time of analysis. Results: Olympic medalists' lifespan was shorter than non-medalists. Athletes in such disciplines as boxing, weightlifting, ice hockey, cycling, football, swimming, and wrestling lived significantly shorter lives than the mean of the group of athletes. In contrast, the duration of life in athletes involved in athletics, rowing, fencing, artistic gymnastics, shooting, cross-country skiing, sailing, and equestrian sports was highest compared with the mean of the group. Conclusions: Disciplines classified as engaging mostly power were linked to shorter lifespans, whereas those involving predominantly skill were associated with longer life durations. The interaction of being a medalist and sport was found to be significant. Medalists in the disciplines of athletics, basketball, boxing, equestrian sports, wrestling, and water polo had significantly shorter lives (the final item was insignificant after correction for multiple comparisons). Olympic achievement was linked to length of life in mainly individual, not team, sports. [ABSTRACT FROM AUTHOR]

Objective: This study investigated changes in life expectancy due to the COVID-19 pandemic by analyzing the contributions of age, sex, and cause of death in 2019 and 2022. Methods: Korea's simplified life table and cause-of-death statistics from 2019 to 2022 were used to assess mortality changes by age, sex, and cause of death during the pandemic. Joinpoint regression analysis was applied to detect trends, and the Arriaga decomposition method was used to quantify the contributions of age, sex, and cause of death to life expectancy changes. Results: Joinpoint regression identified a slow increase in life expectancy in 2007 and a decline in 2020, coinciding with the COVID-19 pandemic. Life expectancy decreased markedly for men (−0.36 years per year, 95%CI: −0.68 to −0.03) and women (−0.45 years per year, 95%CI: −0.71 to −0.18). Age-specific contributions revealed declines across age groups, with the steepest reductions in the older population (80 years or older: −0.35 years for men; −0.52 years for women). Women (−0.68 years) contributed more to the decline in life expectancy than men (−0.41 years). COVID-19 ranked as the third leading cause of death in 2022, significantly contributing to the decline in life expectancy among the older population (aged 80 years or older: −0.306 years for men, −0.408 years for women). Women in Korea were more affected than men, reducing the sex-specific gap in life expectancy by 0.3 years. Conclusions: The COVID-19 pandemic significantly impacted the life expectancy in Korea, particularly among older adults, with women experiencing a greater decline than men. These findings emphasize the need for targeted public health strategies to address age and sex disparities in future pandemics. Before the pandemic, non-communicable diseases such as malignant neoplasms, heart disease, and cerebrovascular disease dominated Korea's top 10 causes of death. During the pandemic, however, COVID-19 rose to third place by 2022. Notably, intentional self-harm (suicide) contributed to an increase in life expectancy, suggesting shifts in the relative impact of various causes of death. [ABSTRACT FROM AUTHOR]