Probabilidade de adolescentes cometerem suicídio superou a de jovens adultos na pandemia

Uma pesquisa sobre a mortalidade por suicídio no Brasil revelou que a probabilidade de casos entre adolescentes tem crescido de forma mais intensa do que em outras faixas etárias. O estudo de tendência temporal realizado por pesquisadores da Escola Nacional de Saúde Pública (Ensp/Fiocruz) mostra que, entre 2000 e 2022, há indicativo de alta da proporção de suicídios em relação ao total de mortes em todos os grupos estudados.

Expert judgement reveals current and emerging UK climate-mortality burden.

Weather and climate patterns play an intrinsic role in societal health, yet a comprehensive synthesis of specific hazard-mortality causes does not currently exist. Country-level health burdens are thus highly uncertain, but harnessing collective expert knowledge can reduce this uncertainty, and help assess diverse mortality causes beyond what is explicitly quantified. Here, surveying 30 experts, we provide the first structured expert judgement of how weather and climate directly impact mortality, using the UK as an example. Current weather-related mortality is dominated by short-term exposure to hot and cold temperatures leading to cardiovascular and respiratory failure. We find additional underappreciated health outcomes, especially related to long-exposure hazards, including heat-related renal disease, cold-related musculoskeletal health, and infectious diseases from compound hazards. We show potential future worsening of cause-specific mortality, including mental health from flooding or heat, and changes in infectious diseases. Ultimately, this work could serve to develop an expert-based understanding of the climate-related health burden in other countries.

Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity With Mortality.

Step cadence-based and machine-learning (ML) methods have been used to classify physical activity (PA) intensity in health-related research. This study examined the association of intensity-specific PA duration with all-cause (ACM) and CVD mortality using the cadence-based and ML methods in 68 561 UK Biobank participants wearing wrist-worn accelerometers. The two-stage-ML method categorized activity type and then intensity. The one-level-cadence-method (1LC) derived intensity-specific duration using all detected steps (including standing utilitarian steps) and cadence thresholds of ≥100 steps/min (moderate intensity) and ≥130 steps/min (vigorous intensity). The two-level-cadence-method (2LC) detected ambulatory steps (i.e., walking and running) and then applied the same cadence thresholds. The 2LC exhibited the most pronounced association at the lower end of duration spectrum. For example, the 2LC showed the smallest minimum moderate-to-vigorous-PA (MVPA) duration (amount associated with 50% of optimal risk reduction) with similar corresponding ACM hazard ratio (HR) to other methods (2LC: 2.8 min/day [95% CI: 2.6, 2.8], HR: 0.83 [95% CI: 0.78, 0.88]; 1LC, 11.1[10.8, 11.4], 0.80 [0.76, 0.85]; ML, 14.9 [14.6, 15.2], 0.82 [0.76, 0.87]). The ML elicited the greatest mortality risk reduction. For example, the medians and corresponding HR in VPA-ACM association: 2LC, 2.0 min/day [95% CI: 2.0, 2.0], HR, 0.69 [95% CI: 0.61, 0.79]; 1LC, 6.9 [6.9, 7.0], 0.68 [0.60, 0.77]; ML, 3.2 [3.2, 3.2], 0.53 [0.44, 0.64]. After standardizing durations, the ML exhibited the most pronounced associations. For example, the standardized minimum durations in MPA-CVD mortality association were: 2LC, -0.77; 1LC, -0.85; ML, -0.94; with corresponding HR of 0.82 [0.72, 0.92], 0.79 [0.69, 0.90], and 0.77 [0.69, 0.85], respectively. The 2LC exhibited the most pronounced association with all-cause and CVD mortality at the lower end of the duration spectrum. The ML method provided the most pronounced association with all-cause and CVD mortality, thus might be appropriate for estimating health benefits of moderate and vigorous intensity PA in observational studies.

Health Care Resource Use and Total Mortality After Hospital Admission for Severe COVID-19 Infections During the Initial Pandemic Wave in France: Descriptive Study.

BACKGROUND: Little is known about post-hospital health care resource use (HRU) of patients admitted for severe COVID-19, specifically for the care of patients with postacute COVID-19 syndrome (PACS). OBJECTIVE: A list of HRU domains and items potentially related to PACS was defined, and potential PACS-related HRU (PPRH) was compared between the pre- and post-COVID-19 periods, to identify new outpatient care likely related to PACS. METHODS: A retrospective cohort study was conducted with the French National Health System claims data (SNDS). All patients hospitalized for COVID-19 between February 1, 2020, and June 30, 2020 were described and investigated for 6 months, using discharge date as index date. Patients who died during index stay or within 30 days after discharge were excluded. PPRH was assessed over the 5 months from day 31 after index date to end of follow-up, that is, for the post-COVID-19 period. For each patient, a pre-COVID-19 period was defined that covered the same calendar time in 2019, and pre-COVID-19 PPRH was assessed. Post- or pre- ratios (PP ratios) of the percentage of users were computed with their 95% CIs, and PP ratios>1.2 were considered as "major HRU change." RESULTS: The final study population included 68,822 patients (median age 64.8 years, 47% women, median follow-up duration 179.3 days). Altogether, 23% of the patients admitted due to severe COVID-19 died during the hospital stay or within the 6 months following discharge. A total of 8 HRU domains were selected to study PPRH: medical visits, technical procedures, dispensed medications, biological analyses, oxygen therapy, rehabilitation, rehospitalizations, and nurse visits. PPRs showed novel outpatient care in all domains and in most items, without specificity, with the highest ratios observed for the care of thoracic conditions. CONCLUSIONS: Patients hospitalized for severe COVID-19 during the initial pandemic wave had high morbi-mortality. The analysis of HRU domains and items most likely to be related to PACS showed that new care was commonly initiated after discharge but with no specificity, potentially suggesting that any impact of PACS was part of the overall high HRU of this population after hospital discharge. These purely descriptive results need to be completed with methods for controlling for confusion bias through subgroup analyses. TRIAL REGISTRATION: ClinicalTrials.gov NCT05073328; https://clinicaltrials.gov/ct2/show/NCT05073328.

[Assessment of the impact on mortality of air pollution by particles in the city of Valencia during the period 2015-2017]. / Evaluación del impacto en mortalidad de la contaminación del aire por partículas en la ciudad de València en el periodo 2015-2017.

OBJECTIVE: Air pollution is a global public health issue, with particulate matter (PM) being the pollutant with the greatest impact on health. The main objective of this article was to estimate the impact of mortality attributable to particulate pollution in the city of Valencia during the period 2015-2017. METHODS: The Health Impact Assessment (HIA) methodology from the Aphekom project was used. Scenarios of a 5 µg/m3 reduction in the annual mean concentration of PM10 and PM2.5 were employed, along with the assumption of meeting the World Health Organization (WHO) recommendations in effect during the study period, to estimate both short- and long-term impacts. RESULTS: The estimated average concentrations for 2015-2017 were 18.4 µg/m3 for PM10 and 12.3 µg/m3 for PM2.5. The short-term HIA, assuming a reduction of 5 µg/m3 in the averages, resulted in a total of 65.4 premature deaths that could be postponed during that period (21.8 annually), corresponding to a rate of 2.8 deaths per 100,000 inhabitants. In the long term, if PM2.5 concentrations had been reduced by 5 µg/m3, 124 premature deaths could have been postponed annually. CONCLUSIONS: The annual average concentrations of these pollutants meet the limits set by European regulations. However, compared to WHO recommendations, PM2.5 levels are higher by 2.3 µg/m3. An air quality scenario in line with WHO recommendations would have resulted in a reduction of 122 premature deaths annually.

OBJETIVO: La contaminación del aire es un problema de Salud Pública de importancia global, siendo las partículas en suspensión (PM) el contaminante con mayor impacto en la salud. El objetivo principal de este artículo fue estimar el impacto en mortalidad atribuible a la contaminación por partículas en la ciudad de València en el periodo 2015-2017. METODOS: Se utilizó la metodología para la Evaluación del Impacto en Salud (EIS) del proyecto Aphekom. Se realizó un estudio descriptivo y para la correlación se emplearon los escenarios de reducción de la media anual de 5 µg/m3 en la concentración de PM10 y de PM2,5 y el supuesto de cumplir las recomendaciones de la Organización Mundial de la Salud (OMS) vigentes en el periodo a estudio para estimar el impacto a corto y largo plazo. RESULTADOS: Las concentraciones estimadas del promedio 2015-2017 para PM10 y PM2,5 fueron de 18,4 µg/m3 y 12,3 µg/m3, respectivamente. La EIS a corto plazo, en el supuesto de reducir en 5 µg/m3 las medias, tuvo como resultado un total de 65,4 muertes prematuras que se podrían posponer en ese periodo (21,8 anuales), correspondiendo con una tasa de 2,8 defunciones por cada 100.000 habitantes. A largo plazo, si se hubiesen reducido las concentraciones de PM2,5 en 5 µg/m3, se hubieran podido posponer 124 muertes prematuras anuales. CONCLUSIONES: Las concentraciones medias anuales de estos contaminantes se ajustan a los límites marcados por la normativa europea. Sin embargo, respecto a las recomendaciones de la OMS, los niveles de PM2,5 son superiores en 2,3 µg/m3. Un escenario de calidad del aire conforme a las recomendaciones de la OMS se hubiera traducido en una reducción de 122 defunciones prematuras anuales.

The effects of ambient temperature on non-accidental mortality in the elderly hypertensive subjects, a cohort-based study.

BACKGROUND: The association between ambient temperature and mortality has yielded inconclusive results with previous studies relying on in-patient data to assess the health effects of temperature. Therefore, we aimed to estimate the effect of ambient temperature on non-accidental mortality among elderly hypertensive patients through a prospective cohort study conducted in northeastern China. METHODS: A total of 9634 elderly hypertensive patients from the Kailuan research who participated in the baseline survey and follow-up from January 1, 2006 to December 31, 2017, were included in the study. We employed a Poisson generalized linear regression model to estimate the effects of monthly ambient temperature and temperature variations on non-accidental mortality. RESULTS: After adjusting for meteorological parameters, the monthly mean temperature (RR = 0.989, 95% CI: 0.984-0.993, p < 0.001), minimum temperature (RR = 0.987, 95% CI: 0.983-0.992, p < 0.001) and maximum temperature (RR = 0.989, 95% CI: 0.985-0.994, p < 0.001) exhibited a negative association with an increased risk of non-accidental mortality. The presence of higher monthly temperature variation was significantly associated with an elevated risk of mortality (RR = 1.097, 95% CI:1.051-1.146, p < 0.001). Further stratified analysis revealed that these associations were more pronounced during colder months as well as among male and older individuals. CONCLUSIONS: Decreased temperature and greater variations in ambient temperature were observed to be linked with non-accidental mortality among elderly hypertensive patients, particularly notable within aging populations and males. These understanding regarding the effects of ambient temperature on mortality holds clinical significance for appropriate treatment strategies targeting these individuals while also serving as an indicator for heightened risk of death.

Trends of primary liver cancer incidence and mortality in the United States: A population-based study over the last four decades.

BACKGROUND: Primary liver cancer is the third leading cause of cancer deaths worldwide and has one of the worst 5-year survival rates. This study examines US primary liver cancer incidence and incidence-based mortality trends over four decades. RESEARCH DESIGN AND METHODS: The SEER-9 registry was used to study primary liver cancer cases from 1978 to 2018. The incidence and mortality rates were calculated based on gender, age, race, and stage of diagnosis. Joinpoint regression software was used to calculate the annual percent change. RESULTS: The overall incidence rate of primary liver cancer from 1978 to 2018 increased by 2.71%/year (p<0.001). Rates in patients <50 years old began to fall in 2002 at a rate of -3.62%/year (p<0.001). Similarly, the incidence-based mortality rates for primary liver cancer increased by 2.15%/year (p<0.001). Whereas Whites incidence-based mortality rates began to plateau in 2012 (0.18%/year; p = 0.84), Blacks rates have declined since 2010 (-2.93%/year; p = 0.03), and Asian rates have declined since 1999 (-1.30%/year; p<0.001). CONCLUSION: While the overall primary liver cancer incidence and incidence-based mortality have been increasing over the last four decades, there was an observed decline in incidence and incidence-based mortality in recent years, especially among at-risk subgroups.

Trends on Prevalence, All-Cause Mortality, and Survival Status of Dementia Patients in Rural China Based on Pooling Analysis.

Objectives: No study has reported secular trends in dementia prevalence, all-cause mortality, and survival status in rural China. Methods: We established two cohorts (XRRCC1 and XRRCC2) in the same region of China, 17 years apart, to compare dementia prevalence, all-cause mortality, and survival status, and performed regression analysis to identify associated factors. Results: Dementia prevalence was 3.49% in XRRCC1 and 4.25% in XRRCC2, with XRRCC2 showing a significantly higher prevalence (OR = 1.79, 95%CI: 1.2-2.65). All-cause mortality rates for dementia patients were 62.0% in XRRCC1 and 35.7% in XRRCC2. Mortality in the normal population of XRRCC2 decreased by 66% compared to XRRCC1, mainly due to improved survival rates in women with dementia. Dementia prevalence was positively associated with age >65, spouse-absent status, and stroke, and negatively associated with ≥6 years of education. Conclusion: Dementia prevalence in rural China increased over 17 years, while mortality decreased. Major risk factors include aging, no spouse, and stroke, with higher education offering some protection.

Global forecasting of chronic kidney disease mortality rates and numbers with the generalized additive model.

BACKGROUND: Chronic kidney disease (CKD) is an important public health problem worldwide; therefore, forecasting CKD mortality rates and death numbers globally is vital for planning CKD prevention programs. This study aimed to characterize the temporal trends in CKD mortality at the international level from 1990 to 2019 and predict CKD mortality rates and numbers until 2030. METHODS: Data were obtained from the Global Burden of Disease 2019 Study. A joinpoint regression model was used to estimate the average annual percentage change in CKD mortality rates and numbers. Finally, we used a generalized additive model to predict CKD mortality through 2030. RESULTS: The number of CKD-related deaths worldwide increased from 591.80 thousand in 1990 to 1425.67 thousand in 2019. The CKD age-adjusted mortality rate increased from 15.95 per 100,000 people to 18.35 per 100,000 people during the same period. Between 2020 and 2030, the number of CKD deaths is forecasted to increase further to 1812.85 thousand by 2030. The CKD age-adjusted mortality rate is expected to decrease slightly to 17.76 per 100,000 people (95% credible interval (CrI): 13.84 to 21.68). Globally, it is predicted that in the next decade, the CKD mortality rate will decrease in men, women, all subgroups of disease etiology except glomerulonephritis, people younger than 40 years old, and all groupings of countries based on the sociodemographic index (SDI) except high-middle-SDI countries. CONCLUSIONS: The CKD mortality rate is predicted to decrease in the next decade. However, more attention should be given to people with glomerulonephritis, people over 40 years old, and people in high- to middle-income countries because the mortality rate due to CKD in these subgroups is expected to increase until 2030.

Mortality risk predicts global, local, and individual patterns of human reproduction.

BACKGROUND: Human reproductive dynamics in the post-industrial world are typically explained by economic, technological, and social factors including the prevalence of contraception and increasing numbers of women in higher education and the workforce. These factors have been targeted by multiple world governments as part of family policies, yet those policies have had limited success. The current work adopts a life history perspective from evolutionary biology: like most species, human populations may respond to safer environments marked by lower morbidity and mortality by slowing their reproduction and reducing their number of offspring. We test this association on three levels of analysis using global, local, and individual data from publicly available databases. RESULTS: Data from over 200 world nations, 3,000 U.S. counties and 2,800 individuals confirm an association between human reproductive outcomes and local mortality risk. Lower local mortality risk predicts "slower" reproduction in humans (lower adolescent fertility, lower total fertility rates, later age of childbearing) on all levels of analyses, even while controlling for socioeconomic variables (female employment, education, contraception). CONCLUSIONS: The association between extrinsic mortality risk and reproductive outcomes, suggested by life history theory and previously supported by both animal and human data, is now supported by novel evidence in humans. Social and health policies governing human reproduction, whether they seek to boost or constrain fertility, may benefit from incorporating a focus on mortality risk.

Estimating future climate change impacts on human mortality and crop yields via air pollution.

Future climate change may bring local benefits or penalties to surface air pollution, resulting from changing temperature, precipitation, and transport patterns, as well as changes in climate-sensitive natural precursor emissions. Here, we estimate the climate penalties and benefits at the end of this century with regard to surface ozone and fine particulate matter (PM[Formula: see text]; excluding dust and smoke) using a one-way offline coupling between a general circulation model and a global 3-D chemical-transport model. We archive meteorology for the present day (2005 to 2014) and end of this century (2090 to 2099) for seven future scenarios developed for Phase 6 of the Coupled Model Intercomparison Project. The model isolates the impact of forecasted anthropogenic precursor emission changes versus that of climate-only driven changes on surface ozone and PM[Formula: see text] for scenarios ranging from extreme mitigation to extreme warming. We then relate these changes to impacts on human mortality and crop production. We find ozone penalties over nearly all land areas with increasing warming. We find net benefits due to climate-driven changes in PM[Formula: see text] in the Northern Extratropics, but net penalties in the Tropics and Southern Hemisphere, where most population growth is forecast for the coming century.

The heat-mortality association in Jordan: Effect modification by greenness, population density and urbanization level.

BACKGROUND: The Middle East is one of the most vulnerable regions to the impacts of climate change, yet evidence of the heat-related mortality remains limited in this area. Our present study investigated the heat-mortality association in Jordan and the potential modifying effect of greenness, population density and urbanization level on the association. METHODS: For each of the 42 included districts, daily meteorological and mortality data from 2000 to 2020 were obtained for the warmest months (May to September). First, a distributed lag non-linear model was applied to estimate the district level heat-mortality association, then the district specific estimates were pooled using multivariate meta-regression models to obtain an overall estimate. Last, the modifying effect of district level greenness, population density and urbanization level was examined through subgroup analysis. RESULTS: When compared to the minimum mortality temperature (MMT, percentile 0th, 22.20 °C), the 99th temperature percentile exhibited a relative risk (RR) of 1.34 (95 % CI 1.23, 1.45). Districts with low greenness had a higher heat-mortality risk (RR 1.39, 95 % CI 1.22, 1.58) when compared to the high greenness (RR 1.28, 95 % CI 1.13, 1.45). While heat-mortality risk did not significantly differ between population density subgroups, highly urbanized districts had a greater heat-mortality risk (RR 1.41, 95 % CI 1.23, 1.62) as compared to ones with low levels of urbanization (RR 1.32, 95 % CI 1.13, 1.55). Districts with high urbanization level had the highest heat-mortality risk if they were further categorized as having low greenness (RR 1.63, 95 % CI 1.30, 2.04). CONCLUSION: Exposure to heat was associated with increased mortality risk in Jordan. This risk was higher in districts with low greenness and high urbanization level. As climate change-related heat mortality will be on the rise, early warning systems in highly vulnerable communities in Jordan are required and greening initiatives should be pursued.

Inequality in Mortality and Cardiovascular Risk Among Young, Low-Income, Self-Employed Workers: Nationwide Retrospective Cohort Study.

Background: Self-employment is a significant component of South Korea's labor force; yet, it remains relatively understudied in the context of occupational safety and health. Owing to different guidelines for health checkup participation among economically active individuals, disparities in health maintenance may occur across varying employment statuses. Objective: This study aims to address such disparities by comparing the risk of all-cause mortality and comorbidities between the self-employed and employee populations in South Korea, using nationwide data. We sought to provide insights relevant to other countries with similar cultural, social, and economic contexts. Methods: This nationwide retrospective study used data from the Korean National Health Insurance Service database. Participants (aged 20-59 y) who maintained the same insurance type (self-employed or employee insurance) for ≥3 years (at least 2008-2010) were recruited for this study and monitored until death or December 2021-whichever occurred first. The primary outcome was all-cause mortality. The secondary outcomes were ischemic heart disease, ischemic stroke, cancer, and hospitalization with a mental illness. Age-standardized cumulative incidence rates were estimated through an indirect method involving 5-unit age standardization. A multivariable Cox proportional hazards model was used to estimate the adjusted hazard ratio (HR) and 95% CI for each sex stratum. Subgroup analyses and an analysis of the effect modification of health checkup participation were also performed. Results: A total of 11,652,716 participants were analyzed (follow-up: median 10.92, IQR 10.92-10.92 y; age: median 42, IQR 35-50 y; male: n=7,975,116, 68.44%); all-cause mortality occurred in 1.27% (99,542/7,851,282) of employees and 3.29% (124,963/3,801,434) of self-employed individuals (P<.001). The 10-year cumulative incidence rates of all-cause mortality differed significantly by employment status (1.1% for employees and 2.8% for self-employed individuals; P<.001). The risk of all-cause mortality was significantly higher among the self-employed individuals when compared with that among employees, especially among female individuals, according to the final model (male: adjusted HR 1.44, 95% CI 1.42-1.45; female: adjusted HR 1.89, 95% CI 1.84-1.94; P<.001). The risk of the secondary outcomes, except all types of malignancies, was significantly higher among the self-employed individuals (all P values were <.001). According to subgroup analyses, this association was prominent in younger individuals with lower incomes who formed a part of the nonparticipation groups. Furthermore, health checkup participation acted as an effect modifier for the association between employment status and all-cause mortality in both sexes (male: relative excess risk due to interaction [RERI] 0.76, 95% CI 0.74-0.79; female: RERI 1.13, 95% CI 1.05-1.21). Conclusions: This study revealed that self-employed individuals face higher risks of all-cause mortality, cardio-cerebrovascular diseases, and mental illnesses when compared to employees. The mortality risk is particularly elevated in younger, lower-income individuals who do not engage in health checkups, with health checkup nonparticipation acting as an effect modifier for this association.

A protein risk score for all-cause and respiratory-specific mortality in non-Hispanic white and African American individuals who smoke.

Protein biomarkers are associated with mortality in cardiovascular disease, but their effect on predicting respiratory and all-cause mortality is not clear. We tested whether a protein risk score (protRS) can improve prediction of all-cause mortality over clinical risk factors in smokers. We utilized smoking-enriched (COPDGene, LSC, SPIROMICS) and general population-based (MESA) cohorts with SomaScan proteomic and mortality data. We split COPDGene into training and testing sets (50:50) and developed a protRS based on respiratory mortality effect size and parsimony. We tested multivariable associations of the protRS with all-cause, respiratory, and cardiovascular mortality, and performed meta-analysis, area-under-the-curve (AUC), and network analyses. We included 2232 participants. In COPDGene, a penalized regression-based protRS was most highly associated with respiratory mortality (OR 9.2) and parsimonious (15 proteins). This protRS was associated with all-cause mortality (random effects HR 1.79 [95% CI 1.31-2.43]). Adding the protRS to clinical covariates improved all-cause mortality prediction in COPDGene (AUC 0.87 vs 0.82) and SPIROMICS (0.74 vs 0.6), but not in LSC and MESA. Protein-protein interaction network analyses implicate cytokine signaling, innate immune responses, and extracellular matrix turnover. A blood-based protein risk score predicts all-cause and respiratory mortality, identifies potential drivers of mortality, and demonstrates heterogeneity in effects amongst cohorts.

Projections of Extreme Temperature-Related Deaths in the US.

Importance: Extreme heat in the US is increasing due to climate change, while extreme cold is projected to decline. Understanding how extreme temperature along with demographic changes will affect population health is important for devising policies to mitigate the health outcome of climate change. Objective: To assess the burden of extreme temperature-related deaths in the contiguous US currently (2008-2019) and estimate the burden in the mid-21st century (2036-2065). Design, Setting, and Participants: This cross-sectional study used historical (1979-2000) daily mean temperatures to calculate monthly extreme heat (>97.5th percentile value) and extreme cold days (<2.5th percentile value) for all contiguous US counties for 2008 to 2019 (current period). Temperature projections from 20 climate models and county population projections were used to estimate extreme temperature-related deaths for 2036 to 2065 (mid-21st century period). Data were analyzed from November 2023 to July 2024. Exposure: Current monthly frequency of extreme heat days and projected mid-21st century frequency using 2 greenhouse gas emissions scenarios: Shared Socioeconomic Pathway (SSP)2-4.5, representing socioeconomic development with a lower emissions increase, and SSP5-8.5, representing higher emissions increase. Main Outcomes and Measures: Mean annual estimated number of extreme temperature-related excess deaths. Poisson regression model with county, month, and year fixed effects was used to estimate the association between extreme temperature and monthly all-cause mortality for older adults (aged ≥65 years) and younger adults (aged 18-64 years). Results: Across the contiguous US, extreme temperature days were associated with 8248.6 (95% CI, 4242.6-12 254.6) deaths annually in the current period and with 19 348.7 (95% CI, 11 388.7-27 308.6) projected deaths in the SSP2-4.5 scenario and 26 574.0 (95% CI, 15 408.0-37 740.1) in the SSP5-8.5 scenario. The mortality data included 30 924 133 decedents, of whom 15 573 699 were males (50.4%), with 6.3% of Hispanic ethnicity, 11.5% of non-Hispanic Black race, and 79.3% of non-Hispanic White race. Non-Hispanic Black adults (278.2%; 95% CI, 158.9%-397.5%) and Hispanic adults (537.5%; 95% CI, 261.6%-813.4%) were projected to have greater increases in extreme temperature-related deaths from the current period to the mid-21st century period compared with non-Hispanic White adults (70.8%; 95% CI, -5.8% to 147.3%). Conclusions and Relevance: This cross-sectional study found that extreme temperature-related deaths in the contiguous US were projected to increase substantially by mid-21st century, with certain populations, such as non-Hispanic Black and Hispanic adults, projected to disproportionately experience this increase. The results point to the need to mitigate the adverse outcome of extreme temperatures for population health.

Assessing educational disparities in COVID-19 related excess mortality in Spain: a population register-linked mortality study.

Introduction: Data on the increase in mortality during the COVID-19 pandemic based on individuals' socioeconomic positions are limited. This study examines this increase in mortality in Spain during the epidemic waves of 2020 and 2021. Methods: We calculated the overall and cause-specific mortality rates during the 2017-2019 pre-pandemic period and four epidemic periods in 2020 and 2021 (first, second, third-fourth, and fifth-sixth waves). Mortality rates were analyzed based on educational levels (low, medium, and high) and across various age groups (25-64, 65-74, and 75+). The increase in mortality during each epidemic period compared to the pre-pandemic period was estimated using mortality rate ratios (MRR) derived from Poisson regression models. Results: An inverse educational gradient in overall mortality was observed across all periods; however, this pattern was not consistent for COVID-19 mortality in some age groups. Among those aged 75 years and older, highly educated individuals showed higher COVID-19 mortality during the first wave. In the 25-64 age group, individuals with low education experienced the highest overall mortality increase, while those with high education had the lowest increase. The MRRs were 1.21 and 1.06 during the first wave and 1.12 and 0.97 during the last epidemic period. In the 65-74 age group, highly educated individuals showed the highest overall mortality increase during the first wave, whereas medium-educated individuals had the highest increase during the subsequent epidemic periods. Among those aged 75 and older, highly educated individuals exhibited the highest overall mortality increase while the individuals with low education showed the lowest overall mortality increment, except during the last epidemic period. Conclusion: The varying educational patterns of COVID-19 mortality across different age groups contributed to the disparities of findings in increased overall mortality by education levels during the COVID-19 pandemic.

Unveiling the female experience through adult mortality and survivorship in Milan over the last 2000 years.

This study challenges historical paradigms using a large-scale integrated bioarchaeological approach, focusing on the female experience over the last 2,000 years in Milan, Italy. Specifically, 492 skeletons from the osteological collection of Milan were used to elucidate female survivorship and mortality by integrating bioarchaeological and paleopathological data, paleoepidemiological analyses, and historical contextualization. Findings revealed changes in female longevity, with a notable increase from Roman to contemporary eras, albeit plateauing in the Middle Ages/modern period. Significant sex-specific differences in mortality risk and survivorship were observed: females had higher mortality risk and lower survivorship in the Roman (first-fifth century AD) and Modern (16th-18th century AD) eras, but this trend reversed in the contemporary period (19th-20th century AD). Cultural and social factors negatively impacted female mortality in Roman and modern Milan, while others buffered it during the Middle Ages (sixth-15th century AD). This study underscored the importance of bioarchaeological inquiries in reconstructing the past, providing answers that may challenge historical assumptions and shedding light on how the interplay of cultural, social, and biological factors shaped the female experience across millennia.

The impact of different censoring methods for analyzing survival using real-world data with linked mortality information: a simulation study.

BACKGROUND: Evaluating outcome reliability is critical in real-world evidence studies. Overall survival is a common outcome in these studies; however, its capture in real-world data (RWD) sources is often incomplete and supplemented with linked mortality information from external sources. Conflicting recommendations exist for censoring overall survival in real-world evidence studies. This simulation study aimed to understand the impact of different censoring methods on estimating median survival and log hazard ratios when external mortality information is partially captured. METHODS: We used Monte Carlo simulation to emulate a non-randomized comparative effectiveness study of two treatments with RWD from electronic health records and linked external mortality data. We simulated the time to death, the time to last database activity, and the time to data cutoff. Death events after the last database activity were attributed to linked external mortality data and randomly set to missing to reflect the sensitivity of contemporary real-world data sources. Two censoring schemes were evaluated: (1) censoring at the last activity date and (2) censoring at the end of data availability (data cutoff) without an observed death. We assessed the performance of each method in estimating median survival and log hazard ratios using bias, coverage, variance, and rejection rate under varying amounts of incomplete mortality information and varying treatment effects, length of follow-up, and sample size. RESULTS: When mortality information was fully captured, median survival estimates were unbiased when censoring at data cutoff and underestimated when censoring at the last activity. When linked mortality information was missing, censoring at the last activity date underestimated the median survival, while censoring at the data cutoff overestimated it. As missing linked mortality information increased, bias decreased when censoring at the last activity date and increased when censoring at data cutoff. CONCLUSIONS: Researchers should consider the completeness of linked external mortality information when choosing how to censor the analysis of overall survival using RWD. Substantial bias in median survival estimates can occur if an inappropriate censoring scheme is selected. We advocate for RWD providers to perform validation studies of their mortality data and publish their findings to inform methodological decisions better.