Age-specific and cause-specific mortality contributions to the socioeconomic gap in life expectancy in Germany, 2003-21: an ecological study.

BACKGROUND: Earlier death among people in socioeconomically deprived circumstances has been found internationally and for various causes of death, resulting in a considerable life-expectancy gap between socioeconomic groups. We examined how age-specific and cause-specific mortality contributions to the socioeconomic gap in life expectancy have changed at the area level in Germany over time. METHODS: In this ecological study, official German population and cause-of-death statistics provided by the Federal Statistical Office of Germany for the period Jan 1, 2003, to Dec 31, 2021, were linked to district-level data of the German Index of Socioeconomic Deprivation. Life-table and decomposition methods were applied to calculate life expectancy by area-level deprivation quintile and decompose the life-expectancy gap between the most and least deprived quintiles into age-specific and cause-specific mortality contributions. FINDINGS: Over the study period, population numbers varied between 80 million and 83 million people per year, with the number of deaths ranging from 818 000 to 1 024 000, covering the entire German population. Between Jan 1, 2003, and Dec 31, 2019, the gap in life expectancy between the most and least deprived quintiles of districts increased by 0·7 years among females (from 1·1 to 1·8 years) and by 0·1 years among males (from 3·0 to 3·1 years). Thereafter, during the COVID-19 pandemic, the gap increased more rapidly to 2·2 years in females and 3·5 years in males in 2021. Between 2003 and 2021, the causes of death that contributed the most to the life-expectancy gap were cardiovascular diseases and cancer, with declining contributions of cardiovascular disease deaths among those aged 70 years and older and increasing contributions of cancer deaths among those aged 40-74 years over this period. COVID-19 mortality among individuals aged 45 years and older was the strongest contributor to the increase in life-expectancy gap after 2019. INTERPRETATION: To reduce the socioeconomic gap in life expectancy, effective efforts are needed to prevent early deaths from cardiovascular disease and cancer in socioeconomically deprived populations, with cancer prevention and control becoming an increasingly important field of action in this respect. FUNDING: German Cancer Aid and European Research Council.

Association of State Social and Environmental Factors With Rates of Self-injury Mortality and Suicide in the United States.

Importance: Self-injury mortality (SIM) combines suicides and the preponderance of drug misuse-related overdose fatalities. Identifying social and environmental factors associated with SIM and suicide may inform etiologic understanding and intervention design. Objective: To identify factors associated with interstate SIM and suicide rate variation and to assess potential for differential suicide misclassification. Design, Setting, and Participants: This cross-sectional study used a partial panel time series with underlying cause-of-death data from 50 US states and the District of Columbia for 1999-2000, 2007-2008, 2013-2014 and 2018-2019. Applying data from the Centers for Disease Control and Prevention, SIM includes all suicides and the preponderance of unintentional and undetermined drug intoxication deaths, reflecting self-harm behaviors. Data were analyzed from February to June 2021. Exposures: Exposures included inequity, isolation, demographic characteristics, injury mechanism, health care access, and medicolegal death investigation system type. Main Outcomes and Measures: The main outcome, SIM, was assessed using unstandardized regression coefficients of interstate variation associations, identified by the least absolute shrinkage and selection operator; ratios of crude SIM to suicide rates per 100 000 population were assessed for potential differential suicide misclassification. Results: A total of 101 325 SIMs were identified, including 74 506 (73.5%) among males and 26 819 (26.5%) among females. SIM to suicide rate ratios trended upwards, with an accelerating increase in overdose fatalities classified as unintentional or undetermined (SIM to suicide rate ratio, 1999-2000: 1.39; 95% CI, 1.38-1.41; 2018-2019: 2.12; 95% CI, 2.11-2.14). Eight states recorded a SIM to suicide rate ratio less than 1.50 in 2018-2019 vs 39 states in 1999-2000. Northeastern states concentrated in the highest category (range, 2.10-6.00); only the West remained unrepresented. Least absolute shrinkage and selection operator identified 8 factors associated with the SIM rate in 2018-2019: centralized medical examiner system (ß = 4.362), labor underutilization rate (ß = 0.728), manufacturing employment (ß = -0.056), homelessness rate (ß = -0.125), percentage nonreligious (ß = 0.041), non-Hispanic White race and ethnicity (ß = 0.087), prescribed opioids for 30 days or more (ß = 0.117), and percentage without health insurance (ß = -0.013) and 5 factors associated with the suicide rate: percentage male (ß = 1.046), military veteran (ß = 0.747), rural (ß = 0.031), firearm ownership (ß = 0.030), and pain reliever misuse (ß = 1.131). Conclusions and Relevance: These findings suggest that SIM rates were associated with modifiable, upstream factors. Although embedded in SIM, suicide unexpectedly deviated in proposed social and environmental determinants. Heterogeneity in medicolegal death investigation processes and data assurance needs further characterization, with the goal of providing the highest-quality reports for developing and tracking public health policies and practices.

Global, regional, and national causes of under-5 mortality in 2000-19: an updated systematic analysis with implications for the Sustainable Development Goals.

BACKGROUND: Causes of mortality are a crucial input for health systems for identifying appropriate interventions for child survival. We present an updated series of cause-specific mortality for neonates and children younger than 5 years from 2000 to 2019. METHODS: We updated cause-specific mortality estimates for neonates and children aged 1-59 months, stratified by level (low, moderate, or high) of mortality. We made a substantial change in the statistical methods used for previous estimates, transitioning to a Bayesian framework that includes a structure to account for unreported causes in verbal autopsy studies. We also used systematic covariate selection in the multinomial framework, gave more weight to nationally representative verbal autopsy studies using a random effects model, and included mortality due to tuberculosis. FINDINGS: In 2019, there were 5·30 million deaths (95% uncertainty range 4·92-5·68) among children younger than 5 years, primarily due to preterm birth complications (17·7%, 16·1-19·5), lower respiratory infections (13·9%, 12·0-15·1), intrapartum-related events (11·6%, 10·6-12·5), and diarrhoea (9·1%, 7·9-9·9), with 49·2% (47·3-51·9) due to infectious causes. Vaccine-preventable deaths, such as for lower respiratory infections, meningitis, and measles, constituted 21·7% (20·4-25·6) of under-5 deaths, and many other causes, such as diarrhoea, were preventable with low-cost interventions. Under-5 mortality has declined substantially since 2000, primarily because of a decrease in mortality due to lower respiratory infections, diarrhoea, preterm birth complications, intrapartum-related events, malaria, and measles. There is considerable variation in the extent and trends in cause-specific mortality across regions and for different strata of all-cause under-5 mortality. INTERPRETATION: Progress is needed to improve child health and end preventable deaths among children younger than 5 years. Countries should strategize how to reduce mortality among this age group using interventions that are relevant to their specific causes of death. FUNDING: Bill & Melinda Gates Foundation; WHO.

Health benefits of decreases in on-road transportation emissions in the United States from 2008 to 2017.

Decades of air pollution regulation have yielded enormous benefits in the United States, but vehicle emissions remain a climate and public health issue. Studies have quantified the vehicle-related fine particulate matter (PM2.5)-attributable mortality but lack the combination of proper counterfactual scenarios, latest epidemiological evidence, and detailed spatial resolution; all needed to assess the benefits of recent emission reductions. We use this combination to assess PM2.5-attributable health benefits and also assess the climate benefits of on-road emission reductions between 2008 and 2017. We estimate total benefits of $270 (190 to 480) billion in 2017. Vehicle-related PM2.5-attributable deaths decreased from 27,700 in 2008 to 19,800 in 2017; however, had per-mile emission factors remained at 2008 levels, 48,200 deaths would have occurred in 2017. The 74% increase from 27,700 to 48,200 PM2.5-attributable deaths with the same emission factors is due to lower baseline PM2.5 concentrations (+26%), more vehicle miles and fleet composition changes (+22%), higher baseline mortality (+13%), and interactions among these (+12%). Climate benefits were small (3 to 19% of the total). The percent reductions in emissions and PM2.5-attributable deaths were similar despite an opportunity to achieve disproportionately large health benefits by reducing high-impact emissions of passenger light-duty vehicles in urban areas. Increasingly large vehicles and an aging population, increasing mortality, suggest large health benefits in urban areas require more stringent policies. Local policies can be effective because high-impact primary PM2.5 and NH3 emissions disperse little outside metropolitan areas. Complementary national-level policies for NOx are merited because of its substantial impacts-with little spatial variability-and dispersion across states and metropolitan areas.

Understanding longevity in Hong Kong: a comparative study with long-living, high-income countries.

BACKGROUND: Since 2013, Hong Kong has sustained the world's highest life expectancy at birth-a key indicator of population health. The reasons behind this achievement remain poorly understood but are of great relevance to both rapidly developing and high-income regions. Here, we aim to compare factors behind Hong Kong's survival advantage over long-living, high-income countries. METHODS: Life expectancy data from 1960-2020 were obtained for 18 high-income countries in the Organisation for Economic Co-operation and Development from the Human Mortality Database and for Hong Kong from Hong Kong's Census and Statistics Department. Causes of death data from 1950-2016 were obtained from WHO's Mortality Database. We used truncated cross-sectional average length of life (TCAL) to identify the contributions to survival differences based on 263 million deaths overall. As smoking is the leading cause of premature death, we also compared smoking-attributable mortality between Hong Kong and the high-income countries. FINDINGS: From 1979-2016, Hong Kong accumulated a substantial survival advantage over high-income countries, with a difference of 1·86 years (95% CI 1·83-1·89) for males and 2·50 years (2·47-2·53) for females. As mortality from infectious diseases declined, the main contributors to Hong Kong's survival advantage were lower mortality from cardiovascular diseases for both males (TCAL difference 1·22 years, 95% CI 1·21-1·23) and females (1·19 years, 1·18-1·21), cancer for females (0·47 years, 0·45-0·48), and transport accidents for males (0·27 years, 0·27-0·28). Among high-income populations, Hong Kong recorded the lowest cardiovascular mortality and one of the lowest cancer mortalities in women. These findings were underpinned by the lowest absolute smoking-attributable mortality in high-income regions (39·7 per 100 000 in 2016, 95% CI 34·4-45·0). Reduced smoking-attributable mortality contributed to 50·5% (0·94 years, 0·93-0·95) of Hong Kong's survival advantage over males in high-income countries and 34·8% (0·87 years, 0·87-0·88) of it in females. INTERPRETATION: Hong Kong's leading longevity is the result of fewer diseases of poverty while suppressing the diseases of affluence. A unique combination of economic prosperity and low levels of smoking with development contributed to this achievement. As such, it offers a framework that could be replicated through deliberate policies in developing and developed populations globally. FUNDING: Early Career Scheme (RGC ECS Grant #27602415), Research Grants Council, University Grants Committee of Hong Kong.

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

BACKGROUND: Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10-24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. METHODS: We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10-24 years by age group (10-14 years, 15-19 years, and 20-24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10-24 years with that in children aged 0-9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10-24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017). FINDINGS: In 2019 there were 1·49 million deaths (95% uncertainty interval 1·39-1·59) worldwide in people aged 10-24 years, of which 61% occurred in males. 32·7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32·1% were due to communicable, nutritional, or maternal causes; 27·0% were due to non-communicable diseases; and 8·2% were due to self-harm. Since 1950, deaths in this age group decreased by 30·0% in females and 15·3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10-14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15-19 years was 1·3% in males and 1·6% in females, almost half that of males aged 1-4 years (2·4%), and around a third less than in females aged 1-4 years (2·5%). The proportion of global deaths in people aged 0-24 years that occurred in people aged 10-24 years more than doubled between 1950 and 2019, from 9·5% to 21·6%. INTERPRETATION: Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10-24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group. FUNDING: Bill & Melinda Gates Foundation.

Assessment of Nonfatal Myocardial Infarction as a Surrogate for All-Cause and Cardiovascular Mortality in Treatment or Prevention of Coronary Artery Disease: A Meta-analysis of Randomized Clinical Trials.

Importance: Although nonfatal myocardial infarction (MI) is associated with an increased risk of mortality, evidence validating nonfatal MI as a surrogate end point for all-cause or cardiovascular (CV) mortality is lacking. Objective: To examine whether nonfatal MI may be a surrogate for all-cause or CV mortality in patients with or at risk for coronary artery disease. Data Sources: In this meta-analysis, PubMed was searched from inception until December 31, 2020, for randomized clinical trials of interventions to treat or prevent coronary artery disease reporting mortality and nonfatal MI published in 3 leading journals. Study Selection: Randomized clinical trials including at least 1000 patients with 24 months of follow-up. Data Extraction and Synthesis: Trial-level correlations between nonfatal MI and all-cause or CV mortality were assessed for surrogacy using the coefficient of determination (R2). The criterion for surrogacy was set at 0.8. Subgroup analyses based on study subject (primary prevention, secondary prevention, mixed primary and secondary prevention, and revascularization), era of trial (before 2000, 2000-2009, and 2010 and after), and follow-up duration (2.0-3.9, 4.0-5.9, and ≥6.0 years) were performed. Main Outcomes and Measures: All-cause or CV mortality and nonfatal MI. Results: A total of 144 articles randomizing 1 211 897 patients met the criteria for inclusion. Nonfatal MI did not meet the threshold for surrogacy for all-cause (R2 = 0.02; 95% CI, 0.00-0.08) or CV (R2 = 0.11; 95% CI, 0.02-0.27) mortality. Nonfatal MI was not a surrogate for all-cause mortality in primary (R2 = 0.01; 95% CI, 0.001-0.26), secondary (R2 = 0.03; 95% CI, 0.00-0.20), mixed primary and secondary prevention (R2 = 0.001; 95% CI, 0.00-0.08), or revascularization trials (R2 = 0.21; 95% CI, 0.002-0.50). For trials enrolling patients before 2000 (R2 = 0.22; 95% CI, 0.08-0.36), between 2000 and 2009 (R2 = 0.02; 95% CI, 0.00-0.17), and from 2010 and after (R2 = 0.01; 95% CI, 0.00-0.09), nonfatal MI was not a surrogate for all-cause mortality. Nonfatal MI was not a surrogate for all-cause mortality in randomized clinical trials with 2.0 to 3.9 (R2 = 0.004; 95% CI, 0.00-0.08), 4.0 to 5.9 (R2 = 0.06; 95% CI, 0.001-0.16), or 6.0 or more years of follow-up (R2 = 0.30; 95% CI, 0.01-0.55). Conclusions and Relevance: The findings of this meta-analysis do not appear to establish nonfatal MI as a surrogate for all-cause or CV mortality in randomized clinical trials of interventions to treat or prevent coronary artery disease.

Deaths: Leading Causes for 2019.

Objectives-This report presents final 2019 data on the 10 leading causes of death in the United States by age, race and Hispanic origin, and sex. Leading causes of infant, neonatal, and postneonatal death are also presented. This report supplements "Deaths: Final Data for 2019," the National Center for Health Statistics' annual report of final mortality statistics.

Postmortem investigations and identification of multiple causes of child deaths: An analysis of findings from the Child Health and Mortality Prevention Surveillance (CHAMPS) network.

BACKGROUND: The current burden of >5 million deaths yearly is the focus of the Sustainable Development Goal (SDG) to end preventable deaths of newborns and children under 5 years old by 2030. To accelerate progression toward this goal, data are needed that accurately quantify the leading causes of death, so that interventions can target the common causes. By adding postmortem pathology and microbiology studies to other available data, the Child Health and Mortality Prevention Surveillance (CHAMPS) network provides comprehensive evaluations of conditions leading to death, in contrast to standard methods that rely on data from medical records and verbal autopsy and report only a single underlying condition. We analyzed CHAMPS data to characterize the value of considering multiple causes of death. METHODS AND FINDINGS: We examined deaths identified from December 2016 through November 2020 from 7 CHAMPS sites (in Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa), including 741 neonatal, 278 infant, and 241 child <5 years deaths for which results from Determination of Cause of Death (DeCoDe) panels were complete. DeCoDe panelists included all conditions in the causal chain according to the ICD-10 guidelines and assessed if prevention or effective management of the condition would have prevented the death. We analyzed the distribution of all conditions listed as causal, including underlying, antecedent, and immediate causes of death. Among 1,232 deaths with an underlying condition determined, we found a range of 0 to 6 (mean 1.5, IQR 0 to 2) additional conditions in the causal chain leading to death. While pathology provides very helpful clues, we cannot always be certain that conditions identified led to death or occurred in an agonal stage of death. For neonates, preterm birth complications (most commonly respiratory distress syndrome) were the most common underlying condition (n = 282, 38%); among those with preterm birth complications, 256 (91%) had additional conditions in causal chains, including 184 (65%) with a different preterm birth complication, 128 (45%) with neonatal sepsis, 69 (24%) with lower respiratory infection (LRI), 60 (21%) with meningitis, and 25 (9%) with perinatal asphyxia/hypoxia. Of the 278 infant deaths, 212 (79%) had ≥1 additional cause of death (CoD) beyond the underlying cause. The 2 most common underlying conditions in infants were malnutrition and congenital birth defects; LRI and sepsis were the most common additional conditions in causal chains, each accounting for approximately half of deaths with either underlying condition. Of the 241 child deaths, 178 (75%) had ≥1 additional condition. Among 46 child deaths with malnutrition as the underlying condition, all had ≥1 other condition in the causal chain, most commonly sepsis, followed by LRI, malaria, and diarrheal disease. Including all positions in the causal chain for neonatal deaths resulted in 19-fold and 11-fold increases in attributable roles for meningitis and LRI, respectively. For infant deaths, the proportion caused by meningitis and sepsis increased by 16-fold and 11-fold, respectively; for child deaths, sepsis and LRI are increased 12-fold and 10-fold, respectively. While comprehensive CoD determinations were done for a substantial number of deaths, there is potential for bias regarding which deaths in surveillance areas underwent minimally invasive tissue sampling (MITS), potentially reducing representativeness of findings. CONCLUSIONS: Including conditions that appear anywhere in the causal chain, rather than considering underlying condition alone, markedly changed the proportion of deaths attributed to various diagnoses, especially LRI, sepsis, and meningitis. While CHAMPS methods cannot determine when 2 conditions cause death independently or may be synergistic, our findings suggest that considering the chain of events leading to death can better guide research and prevention priorities aimed at reducing child deaths.

Institutional mortality rate and cause of death at health facilities in Ghana between 2014 and 2018.

BACKGROUND: The epidemiological transition, touted as occurring in Ghana, requires research that tracks the changing patterns of diseases in order to capture the trend and improve healthcare delivery. This study examines national trends in mortality rate and cause of death at health facilities in Ghana between 2014 and 2018. METHODS: Institutional mortality data and cause of death from 2014-2018 were sourced from the Ghana Health Service's District Health Information Management System. The latter collates healthcare service data routinely from government and non-governmental health institutions in Ghana yearly. The institutional mortality rate was estimated using guidelines from the Ghana Health Service. Percent change in mortality was examined for 2014 and 2018. In addition, cause of death data were available for 2017 and 2018. The World Health Organisation's 11th International Classification for Diseases (ICD-11) was used to group the cause of death. RESULTS: Institutional mortality decreased by 7% nationally over the study period. However, four out of ten regions (Greater Accra, Volta, Upper East, and Upper West) recorded increases in institutional mortality. The Upper East (17%) and Volta regions (13%) recorded the highest increase. Chronic non-communicable diseases (NCDs) were the leading cause of death in 2017 (25%) and 2018 (20%). This was followed by certain infectious and parasitic diseases (15% for both years) and respiratory infections (10% in 2017 and 13% in 2018). Among the NCDs, hypertension was the leading cause of death with 2,243 and 2,472 cases in 2017 and 2018. Other (non-ischemic) heart diseases and diabetes were the second and third leading NCDs. Septicaemia, tuberculosis and pneumonia were the predominant infectious diseases. Regional variations existed in the cause of death. NCDs showed more urban-region bias while infectious diseases presented more rural-region bias. CONCLUSIONS: This study examined national trends in mortality rate and cause of death at health facilities in Ghana. Ghana recorded a decrease in institutional mortality throughout the study. NCDs and infections were the leading causes of death, giving a double-burden of diseases. There is a need to enhance efforts towards healthcare and health promotion programmes for NCDs and infectious diseases at facility and community levels as outlined in the 2020 National Health Policy of Ghana.

Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.

BACKGROUND: Associations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done. Therefore, we aimed to estimate the global and regional burden due to non-optimal temperature exposure. METHODS: In part 1 of this study, we linked deaths to daily temperature estimates from the ERA5 reanalysis dataset. We modelled the cause-specific relative risks for 176 individual causes of death along daily temperature and 23 mean temperature zones using a two-dimensional spline within a Bayesian meta-regression framework. We then calculated the cause-specific and total temperature-attributable burden for the countries for which daily mortality data were available. In part 2, we applied cause-specific relative risks from part 1 to all locations globally. We combined exposure-response curves with daily gridded temperature and calculated the cause-specific burden based on the underlying burden of disease from the Global Burden of Diseases, Injuries, and Risk Factors Study, for the years 1990-2019. Uncertainty from all components of the modelling chain, including risks, temperature exposure, and theoretical minimum risk exposure levels, defined as the temperature of minimum mortality across all included causes, was propagated using posterior simulation of 1000 draws. FINDINGS: We included 64·9 million individual International Classification of Diseases-coded deaths from nine different countries, occurring between Jan 1, 1980, and Dec 31, 2016. 17 causes of death met the inclusion criteria. Ischaemic heart disease, stroke, cardiomyopathy and myocarditis, hypertensive heart disease, diabetes, chronic kidney disease, lower respiratory infection, and chronic obstructive pulmonary disease showed J-shaped relationships with daily temperature, whereas the risk of external causes (eg, homicide, suicide, drowning, and related to disasters, mechanical, transport, and other unintentional injuries) increased monotonically with temperature. The theoretical minimum risk exposure levels varied by location and year as a function of the underlying cause of death composition. Estimates for non-optimal temperature ranged from 7·98 deaths (95% uncertainty interval 7·10-8·85) per 100 000 and a population attributable fraction (PAF) of 1·2% (1·1-1·4) in Brazil to 35·1 deaths (29·9-40·3) per 100 000 and a PAF of 4·7% (4·3-5·1) in China. In 2019, the average cold-attributable mortality exceeded heat-attributable mortality in all countries for which data were available. Cold effects were most pronounced in China with PAFs of 4·3% (3·9-4·7) and attributable rates of 32·0 deaths (27·2-36·8) per 100 000 and in New Zealand with 3·4% (2·9-3·9) and 26·4 deaths (22·1-30·2). Heat effects were most pronounced in China with PAFs of 0·4% (0·3-0·6) and attributable rates of 3·25 deaths (2·39-4·24) per 100 000 and in Brazil with 0·4% (0·3-0·5) and 2·71 deaths (2·15-3·37). When applying our framework to all countries globally, we estimated that 1·69 million (1·52-1·83) deaths were attributable to non-optimal temperature globally in 2019. The highest heat-attributable burdens were observed in south and southeast Asia, sub-Saharan Africa, and North Africa and the Middle East, and the highest cold-attributable burdens in eastern and central Europe, and central Asia. INTERPRETATION: Acute heat and cold exposure can increase or decrease the risk of mortality for a diverse set of causes of death. Although in most regions cold effects dominate, locations with high prevailing temperatures can exhibit substantial heat effects far exceeding cold-attributable burden. Particularly, a high burden of external causes of death contributed to strong heat impacts, but cardiorespiratory diseases and metabolic diseases could also be substantial contributors. Changes in both exposures and the composition of causes of death drove changes in risk over time. Steady increases in exposure to the risk of high temperature are of increasing concern for health. FUNDING: Bill & Melinda Gates Foundation.

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

BACKGROUND: Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. METHODS: We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (U5MR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. FINDINGS: Global U5MR decreased from 71·2 deaths per 1000 livebirths (95% uncertainty interval [UI] 68·3-74·0) in 2000 to 37·1 (33·2-41·7) in 2019 while global NMR correspondingly declined more slowly from 28·0 deaths per 1000 live births (26·8-29·5) in 2000 to 17·9 (16·3-19·8) in 2019. In 2019, 136 (67%) of 204 countries had a U5MR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030, 154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9·65 million (95% UI 9·05-10·30) in 2000 and 5·05 million (4·27-6·02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3·76 million [95% UI 3·53-4·02]) in 2000 to 48% (2·42 million; 2·06-2·86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0·80 (95% UI 0·71-0·86) deaths per 1000 livebirths and U5MR to 1·44 (95% UI 1·27-1·58) deaths per 1000 livebirths, and in 2019, there were as many as 1·87 million (95% UI 1·35-2·58; 37% [95% UI 32-43]) of 5·05 million more deaths of children younger than 5 years than the survival potential frontier. INTERPRETATION: Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve U5MR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. FUNDING: Bill & Melinda Gates Foundation.

Nationwide burden of sudden cardiac death: A study of 54,028 deaths in Denmark.

BACKGROUND: A large proportion of all deaths are sudden cardiac deaths (SCDs). Reliable estimates of nationwide incidence of SCD, however, are missing. OBJECTIVES: The goals of this study were to estimate SCD burden across all age groups in Denmark and to compare it with the estimates of other common causes of death. METHODS: All deaths in Denmark (population of 5.5 million) in 2010 were manually reviewed case by case. Autopsy reports, death certificates, and information from nationwide health registries were systematically examined to identify all SCD cases in 2010. According to the level of detail of the available information, all deaths were categorized as either non-SCD, definite SCD, probable SCD, or possible SCD. RESULTS: There were 54,028 deaths in Denmark in 2010, of which 6867 (13%) were categorized as SCD (591 (9%) definite SCD, 1568 (23%) probable SCD, and 4708 (68%) possible SCD). The incidence rate of definite SCD was 11 (95% confidence interval 10-12) per 100,000 person-years. Including definite, probable, and possible SCD cases, the highest possible overall SCD incidence rate was 124 (95% confidence interval 121-127) per 100,000 person-years. Estimated SCD burden was similar to or greater than the estimates of all other common causes of death. Of all SCD cases, 49% were not diagnosed with cardiovascular disease before death. CONCLUSION: SCD accounted for up to 13% of all deaths. Almost half of all SCD cases occurred in persons without a history of cardiovascular disease. Consequently, the optimization of risk stratification and prevention of SCD in the general population should be given high priority.

Temporal trends and sex differences in sudden cardiac death in the Copenhagen City Heart Study.

OBJECTIVE: More knowledge about the development of sudden cardiac death (SCD) in the general population is needed to develop meaningful predictors of SCD. Our aim with this study was to estimate the incidence of SCD in the general population and examine the temporal changes, demographics and clinical characteristics. METHODS: All participants in the Copenhagen City Heart Study were followed from 1993 to 2016. All death certificates, autopsy reports and national registry data were used to identify all cases of SCD. RESULTS: A total of 14 562 subjects were included in this study. There were 8394 deaths with all information available, whereof 1335 were categorised as SCD. The incidence of SCD decreased during the study period by 41% for persons aged 40-90 years, and the standardised incidence rates decreased from 504 per 100 000 person-years (95% CI 447 to 569) to 237 per 100 000 person-years (95% CI 195 to 289). The incidence rate ratio of SCD between men and women ≤75 years was 1.99 (95% CI 1.62 to 2.46). The proportion of SCD of all cardiac deaths decreased during the observation period and decreased with increasing age. Men had more cardiovascular comorbidities (OR 1.34, 95% CI 1.07 to 1.68, p<0. 01), and SCD was the first registered manifestation of cardiac disease in 50% of all cases. CONCLUSION: The incidence of SCD in the general population has declined significantly during the study period but should be further investigated for more recent variations as well as novel risk predictors for persons with low to medium risk of SCD.

Variation in Non-external and External Causes of Death in Peru in Relation to the COVID-19 Lockdown.

Introduction: Lockdowns are designed to slow COVID-19 transmission, but they may have unanticipated relationships with other aspects of public health. Assessing the overall pattern in population health as a country implements and relaxes a lockdown is relevant, as these patterns may not necessarily be symmetric. We aimed to estimate the changing trends in cause-specific mortality in relation to the 2020 COVID-19 related lockdowns in Peru. Methods: Based on data from the Peruvian National Death Information System (SINADEF), we calculated death rates per 10 million population to assess the trends in mortality rates for non-external and external causes of death (suicides, traffic accidents, and homicides). We compared these trends to 2018-2019, before, during, and after the lockdown, stratified by sex, and adjusted by Peruvian macro-region (Lima & Callao (capital region), Coast, Highland, and Jungle). Results: Non-external deaths presented a distinctive pattern among macro-regions, with an early surge in the Jungle and a later increase in the Highland. External deaths dropped during the lockdown, however, suicides and homicides returned to previous levels in the post-lockdown period. Deaths due to traffic accidents dropped during the lockdown and returned to pre-pandemic levels by December 2020. Conclusions: We found a sudden drop in external causes of death, with suicides and homicides returning to previous levels after the lifting of the lockdown. Non-external deaths showed a differential pattern by macro-region. A close monitoring of these trends could help identify early spikes among these causes of death and take action to prevent a further increase in mortality indirectly affected by the pandemic.

Provisional Mortality Data - United States, 2020.

CDC's National Vital Statistics System (NVSS) collects and reports annual mortality statistics using data from U.S. death certificates. Because of the time needed to investigate certain causes of death and to process and review data, final annual mortality data for a given year are typically released 11 months after the end of the calendar year. Daily totals reported by CDC COVID-19 case surveillance are timely but can underestimate numbers of deaths because of incomplete or delayed reporting. As a result of improvements in timeliness and the pressing need for updated, quality data during the global COVID-19 pandemic, NVSS expanded provisional data releases to produce near real-time U.S. mortality data.* This report presents an overview of provisional U.S. mortality data for 2020, including the first ranking of leading causes of death. In 2020, approximately 3,358,814 deaths† occurred in the United States. From 2019 to 2020, the estimated age-adjusted death rate increased by 15.9%, from 715.2 to 828.7 deaths per 100,000 population. COVID-19 was reported as the underlying cause of death or a contributing cause of death for an estimated 377,883 (11.3%) of those deaths (91.5 deaths per 100,000). The highest age-adjusted death rates by age, race/ethnicity, and sex occurred among adults aged ≥85 years, non-Hispanic Black or African American (Black) and non-Hispanic American Indian or Alaska Native (AI/AN) persons, and males. COVID-19 death rates were highest among adults aged ≥85 years, AI/AN and Hispanic persons, and males. COVID-19 was the third leading cause of death in 2020, after heart disease and cancer. Provisional death estimates provide an early indication of shifts in mortality trends and can guide public health policies and interventions aimed at reducing numbers of deaths that are directly or indirectly associated with the COVID-19 pandemic.

Life expectancy in adulthood is falling for those without a BA degree, but as educational gaps have widened, racial gaps have narrowed.

A 4-y college degree is increasingly the key to good jobs and, ultimately, to good lives in an ever-more meritocratic and unequal society. The bachelor's degree (BA) is increasingly dividing Americans; the one-third with a BA or more live longer and more prosperous lives, while the two-thirds without face rising mortality and declining prospects. We construct a time series, from 1990 to 2018, of a summary of each year's mortality rates and expected years lived from 25 to 75 at the fixed mortality rates of that year. Our measure excludes those over 75 who have done relatively well over the last three decades and focuses on the years when deaths rose rapidly through drug overdoses, suicides, and alcoholic liver disease and when the decline in mortality from cardiovascular disease slowed and reversed. The BA/no-BA gap in our measure widened steadily from 1990 to 2018. Beyond 2010, as those with a BA continued to see increases in our period measure of expected life, those without saw declines. This is true for the population as a whole, for men and for women, and for Black and White people. In contrast to growing education gaps, gaps between Black and White people diminished but did not vanish. By 2018, intraracial college divides were larger than interracial divides conditional on college; by our measure, those with a college diploma are more alike one another irrespective of race than they are like those of the same race who do not have a BA.

All-cause mortality over a three-year period among community-dwelling older adults in Southern Brazil.

OBJECTIVE: To evaluate all-cause mortality in approximately three years of follow-up and related sociodemographic, behavioral and health factors in community-dwelling older adults in Pelotas, RS. METHODS: This was a longitudinal observational study that included 1,451 older adults (≥ 60 years) who were interviewed in 2014. Information on mortality was collected from their households in 2016-2017 and confirmed with the Epidemiological Surveillance department of the city and by documents from family members. Associations between mortality and independent variables were assessed by crude and multiple Cox regression, with hazard ratio with respective 95% confidence intervals (95%CI). RESULTS: Almost 10% (n = 145) of the participants died during an average of 2.5 years of follow-up, with a higher frequency of deaths among males (12.9%), ?80 years (25.2%), widowhood (15.0%), no education (13.8%) and who did not work (10.5%). Factors associated with higher mortality were: being a male (HR = 2.8; 95%CI 1.9 - 4.2), age ?80 years (HR = 3.9; 95%CI 2.4 - 6.2), widowhood (HR = 2.2; 95%CI 1.4 - 3.7), physical inactivity (HR = 2.3; 95%CI 1.1 - 4..6), current smoking (HR = 2.1; 95%CI 1.2 - 3.6), hospitalizations in the previous year (HR = 2.0; 95%CI 1.2 - 3.2), depressive symptoms (HR = 2.0; 95%CI 1.2 - 3,4) and dependence for two or more daily life activities (HR = 3.1; 95%CI 1,7 - 5.7). CONCLUSION: The identification of factors that increased the risk of early death makes it possible to improve public policies aimed at controlling the modifiable risk factors that can lead to aging with a better quality of life.

Trends in "Deaths of Despair" Among Working-Aged White and Black Americans, 1990-2017.

Life expectancy for US White men and women declined between 2013 and 2017. Initial explanations for the decline focused on increases in "deaths of despair" (i.e., deaths from suicide, drug use, and alcohol use), which have been interpreted as a cohort-based phenomenon afflicting middle-aged White Americans. There has been less attention on Black mortality trends from these same causes, and whether the trends are similar or different by cohort and period. We complement existing research and contend that recent mortality trends in both the US Black and White populations most likely reflect period-based exposures to 1) the US opioid epidemic and 2) the Great Recession. We analyzed cause-specific mortality trends in the United States for deaths from suicide, drug use, and alcohol use among non-Hispanic Black and non-Hispanic White Americans, aged 20-64 years, over 1990-2017. We employed sex-, race-, and cause-of-death-stratified Poisson rate models and age-period-cohort models to compare mortality trends. Results indicate that rising "deaths of despair" for both Black and White Americans are overwhelmingly driven by period-based increases in drug-related deaths since the late 1990s. Further, deaths related to alcohol use and suicide among both White and Black Americans changed during the Great Recession, despite some racial differences across cohorts.

Understanding the Differences in COVID-19 Case Fatality Rates Observed Across Alabama Counties.

To understand county-level variation in case fatality rates of COVID-19, a statewide analysis of COVID-19 incidence and fatality data was performed, using publicly available incidence and case fatality rate data of COVID-19 for all 67 Alabama counties and mapped with health disparities at the county level. A specific adaptation of the Shewhart p-chart, called a funnel chart, was used to compare case fatality rates. Important differences in case fatality rates across the counties did not appear to be reflective of differences in testing or incidence rates. Instead, a higher prevalence of comorbidities and vulnerabilities was observed in high fatality rate counties, while showing no differences in access to acute care. Funnel charts reliably identify counties with unexpected high and low COVID-19 case fatality rates. Social determinants of health are strongly associated with such differences. These data may assist in public health decisions including vaccination strategies, especially in southern states with similar demographics.