Loss Of Life Expectancy Research Articles

Loss in Overall and Quality-Adjusted Life Expectancy for Patients With Chronic-Phase Chronic Myeloid Leukemia.

The introduction of tyrosine kinase inhibitors has considerably improved the life expectancy (LE) for patients with chronic myeloid leukemia (CML). Evaluating health-related quality of life within the treatment pathway remains crucial. Using the Swedish CML register, we included 991 adult patients with chronic-phase (CP) CML diagnosed 2007 to 2017, with follow-up until 2018. We developed a multistate model to estimate the loss in LE (LLE) and loss in quality-adjusted life expectancy (LQALE) for the patient population compared to the general population, along with the respective proportions of losses relative to the general population. All patients with CP-CML had a relatively low reduced LE but with larger LQALE. The maximum LLE within age/sex subgroups was 5.7 years (general population LE: 43.2 years vs. CP-CML LE: 37.5 years) for females diagnosed at age 45 years, with LQALE of 12.0 quality-adjusted life years (QALYs) (general population QALE: 38.2 QALYs vs. CP-CML QALE: 26.3 QALYs). Across all ages, the proportions of LLE ranged from 9% to 15%, and the proportions of LQALE were 29% to 33%. Despite a low LLE, our findings reveal a greater LQALE for patients with CP-CML. Further improvements in management of CP-CML are thus warranted to successfully address the prevailing medical needs.

Outcome and life expectancy associated with novel subgroups of atrial fibrillation: a data-driven cluster analysis

Abstract Background/Introduction Atrial fibrillation (AF) presents a significant global health burden, affecting millions and associated with elevated risks of mortality, heart failure, and stroke despite current treatment strategies. The current diagnosis of AF relies on episode characteristics, yet its heterogeneity calls for personalized assessment incorporating clinical features, biomarkers, and substrate determination for improved classification and management. Purpose This study aimed to develop a refined classification of AF according to comprehensive risk factors to identify patients at high-risk for poor prognosis and their life expectancy, aiming to facilitate personalized interventions. Methods A total of 7,391 participants aged 40-69 with AF at baseline, from UK Biobank, were recruited in the main analyses. Firstly, LASSO regression with Cox model and factor analysis were adopted for identification and integration of principal risk factors. Second, Consensus clustering analysis was employed to estimate the optimal cluster number and group all 7,391 participants. Difference in the risk of death and major complications, as well as reductions in life expectancy, among clusters were estimated. Replication was done in 2,399 participants with newly diagnosed AF within two years after baseline. Results Risk factors for AF were categorized into seven aspects (metabolic factors, respiratory factors, cardiovascular factors, renal and immunity diseases, mental health, acute illness, age), based on the correlation between them. Five distinct AF clusters were identified according to these seven characteristics: acute illness-related (Cluster 1), mental health-related (Cluster 2), cardiovascular disease-related (Cluster 3), immune-and-renal disease-related (Cluster 4), and respiratory-and-metabolism disease-related AF (Cluster 5). Patients with respiratory-and-metabolism disease-related AF had the highest risk of death, acute myocardial infarction, heart failure, and cerebral ischemic stroke, while those with acute illness-related AF had the lowest corresponding risk. In addition, compared with individuals with acute illness-related AF, those with respiratory-and-metabolism disease-related and mental health-related AF had the top 2 greatest loss of life expectancy. Furthermore, genetic variants for AF had different effect among the five clusters. Replication analysis confirmed the result stability. Conclusion A novel AF classification was developed, which provided insights into varying life expectancy and risks of death and complications among AF subgroups with distinct characteristics. It offers a practical approach for identifying high-risk patients, which may help to tailor precise interventions for AF management.Graphic abstractCluster features

Impacts of PM2.5 exposure near cement facilities on human health and years of life lost: A case study in Brazil

Cement factories significantly contribute to atmospheric pollution by generating fine particulate matter (PM2.5), which can potentially increase the mortality risk. The lack of information on the health impacts of PM2.5 pollution from cement operations in Brazil prompted this investigation. We used corrected PM2.5 measurements from low-cost sensors from March 2021 to October 2022 in Rio Branco do Sul, city in the southern region of the country and home to Latin America's largest cement plant, to assess exposure data. Disability-adjusted life years (DALY) method was applied to estimate the years of life lost (YLL) and cost estimate due to deaths from non-accidental causes, cardiovascular and respiratory diseases. The total YLL attributable to PM2.5 concentration was estimated by calculating the attributable fraction (AF) through relative risk. We also collected PM2.5 using a Harvard impactor to evaluate health risks from toxic metals components. During the study period, the analysis of chemical characterization of PM2.5 showed enrichment factors for most elements and the possible influence of the calcination process facilities on the PM2.5 levels. The mean concentration of PM2.5 exceeded the annual WHO air quality guideline (AQG) level, accounted for 3.5%, 4.7%, and 4.3% of total YLL from all causes, cardiovascular, and respiratory diseases, which corresponded to 0.23 (95% CI: 0.17–0.26), 0.06 (95% CI: 0.05–0.07) and 0.03 (95% CI: 0.01–0.06) years loss in life expectancy, respectively. An indirect health cost attributable to PM2.5 resulted in US$ 1.4 million, equivalent to about 3.5% of the total local annual health costs in Rio Branco do Sul, underscoring the significant financial burden of PM2.5 exposures. The greatest economic loss was found in the male age group of 40–69 years and among those with cardiovascular disease, rather than those with respiratory disease. Despite this, the carcinogenic and non-carcinogenic risks from inhalation of hazardous elements were within safe ranges. This work demonstrated PurpleAir's potential for air quality and public health applications. Our findings indicate health and economic benefits from reducing PM2.5 levels by adopting WHO air pollution standards. The results can guide policies toward delivering more effective health care.

Impact of age at HBsAg seroclearance on hepatic outcomes and life expectancy in men with chronic HBV infection based on multi-state modeling of the natural history.

The effects of age at HBsAg seroclearance on clinical outcomes and survival in chronic hepatitis B (CHB) have not been adequately assessed. We evaluated the impact of age at HBsAg seroclearance on long-term outcomes, along with how coexisting factors modified risks and life expectancy in CHB patients. We used multi-state modeling approach to examine transitions through the CHB continuum in a longitudinal cohort study of male civil servants recruited in 1989-1992. Hepatic outcomes and deaths were identified by clinical evaluation and linkage with national health databases. Four sets of risk factors (CHB-related, metabolic, lifestyle, and genetic factors) were assessed. Of 2551 HBsAg carriers, with follow-up until 2021 or death, 695 achieved HBsAg seroclearance, 490 developed cirrhosis (88 decompensated), 252 developed hepatocellular carcinoma (HCC), and 652 died. The cumulative rates for HCC were 1.1% and 1.5% at 10years after HBsAg seroclearance, respectively, for patients achieving seroclearance at age 50 and 60; correspondingly, the rates for cirrhosis were 2.3% and 3.0%. Developing HBsAg seroclearance was associated with a reduced risk of cirrhosis (HR = 0.37, 95% CI 0.15-0.92) but not HCC. Patients experiencing HBsAg seroclearance lived longer years free of major liver diseases than HBsAg-persistent patients, and achieving seroclearance at age 50 (vs 60) led to a greater increase in the disease-free life expectancy. However, obesity and smoking were associated with adverse hepatic outcomes and loss of the disease-free life expectancy following HBsAg seroclearance. Our findings highlight the benefit of earlier HBsAg seroclearance for gains in disease-free life expectancy and the impact of obesity and smoking on loss of the life years free of major liver diseases following HBsAg seroclearance.

All-cause and cause-specific mortality risk and loss in life expectancy associated with incident type 2 diabetes onset age and duration.

Evidence on type 2 diabetes onset age and duration on mortality risk has been limited by short follow-up, inadequate control for confounding, missing repeated measurements, and inability to cover the full range of onset age, duration, and major causes of death. Moreover, scarce data dissect how type 2 diabetes onset age and duration shape life expectancy. We evaluate prospectively these topics based on 270,075 eligible participants in the Nurses' Health Studies and Health Professionals Follow-up Study, leveraging repeated measurements throughout up to 40 years of follow-up. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). In fully adjusted analyses, incident early onset type 2 diabetes (diagnosed <40 years of age) was associated with significantly higher mortality from all-causes (HR, 95% CI was 3.16, 2.64-3.79; vs. individuals without type 2 diabetes), cardiovascular disease (6.56, 4.27-10.1), respiratory disease (3.43, 1.38-8.51), neurodegenerative disease (5.13, 2.09-12.6), and kidney disease (8.55, 1.98-36.9). The relative risk elevations declined dramatically with each higher decade of age at diagnosis for deaths from most of these causes, though the absolute risk difference increased continuously. A substantially higher cumulative incidence of mortality and a greater loss in life expectancy were associated with younger age at type 2 diabetes diagnosis. Longer disease duration was associated with generally higher relative and absolute risk of mortality. Early onset of type 2 diabetes and longer disease duration are associated with substantially increased risk of all-cause and cause-specific mortality and greater loss in life expectancy.

The effect of peri-urban parks on life expectancy and socioeconomic inequalities: A 16-year longitudinal study in Hong Kong

Exposure to greenspaces has well-established benefits for the health and well-being of urban dwellers. Among these greenspaces, peri-urban parks (PUPs), which are human-modified, large-scale, and public-accessible greenspaces located on the urban fringe, have received increasing attention from policymakers and researchers in recent years, as the limited provision of greenspaces in urban areas barely meet the residents’ needs for nature engagement. However, the associations between PUPs and life expectancy and their potential socioeconomic inequalities remain unclear. In this study, we employed a longitudinal, territory-wide death-registration dataset to address such research gaps. The results showed that both the area and greenery of PUP significantly decreased life expectancy loss with standardized coefficients of −0.156 (p = 0.001) and −0.173 (p < 0.001), respectively. The life-expectancy benefits of PUP greenery remain significant throughout 200–8000 m buffer radii. Nevertheless, socioeconomic inequalities were found between PUPs and life expectancy associations. We found that people with higher socioeconomic status (SES) received higher PUP exposure. In addition, contrary to the hypothesis of equigenesis theory, higher-SES populations received greater benefits in life expectancy than lower-SES populations, even after controlling for inequalities in PUP exposure. Our findings uncover a complex relationship between PUPs, life expectancy, and SES, highlighting the need for targeted interventions for people with different SES to ensure equitable health benefits for all.

Impact of historical disease conditions on mortality and life expectancy in patients with advanced schistosomiasis in Hunan Province, China.

Although the prognosis of advanced schistosomiasis patients has significantly improved, the impact of historical disease conditions on life expectancy remains unclear. Utilizing data from an advanced schistosomiasis cohort (n=10 362) from 2008 to 2019 in Hunan, China, we examined five historical disease conditions: times of praziquantel treatment, the history of ascites, splenectomy, upper gastrointestinal bleeding (UGIB) and hepatic coma. Using latent class analysis, participants were categorized into three groups: Group 1 (characterized by no risk conditions), Group 2 (had ≤3 times of praziquantel treatment without UGIB history) and Group 3 (had UGIB history). Life expectancies were calculated using the life table method. At the age of 45 y, patients with ≤3 times of praziquantel treatment, a history of ascites, UGIB, hepatic coma and those without splenectomy exhibited lower life expectancies. Groups 1, 2 and 3 had estimated life expectancies of 32.32, 26.76 and 25.38 y, respectively. Compared with Group 1, women in Group 3 experienced greater life expectancy loss than those in Group 2, with the difference narrowing with age. Based on the consideration of overall physical conditions, tailored treatment and healthcare, along with public health interventions targeting diverse populations, could mitigate the prevalence of poor disease conditions and premature deaths.

Mortality and disease burden of oral cancer in China: a time-trend analysis on the China Death Surveillance Database from 2006 to 2021

BackgroundOral cancer is one of the most common cancers in China and seriously threaten life and health of Chinese people. We analysed the trends and disparities of oral cancer mortality rates and the disease burden of oral cancer in China from 2006 to 2021 to provide a reference for its prevention and control.MethodsAnnual death data for oral cancer was gleaned from the China Death Surveillance Database. The age-standardized mortality rate (ASMR), annual percentage change (APC), and average APC (AAPC) were used to analyze the trend of mortality. Loss of life expectancy (LLE) and years of life lost (YLL) were adopted to assess disease burden.ResultsFrom 2006 to 2021, the overall ASMR of oral cancer lightly declined (AAPC: − 0.97%; 95% CI: − 1.89%, − 0.04%), and the similar trend was observed among females (AAPC: − 1.22%; 95% CI: − 1.89%, − 0.55%). The ASMR of males was 2.31–3.16 times higher than that of females per year. The median of LLE for overall, males and females caused by oral cancer from 2006 to 2021 were 0.05, 0.06 and 0.03 years, respectively. There was a decrease of standardized YLL rate from 2006 to 2021 for overall (AAPC: − 1.31%, 95% CI: − 2.24% ~ − 0.37%) and for female (AAPC: − 1.63%, 95% CI: − 2.30% ~ − 0.95%). ASMR in urban areas was 1.02–1.28 times higher than that in rural areas from 2006 to2011, but 0.85–0.97 times lower in urban areas than that in rural areas from 2018 to 2021. The disease burden was higher in urban areas than in rural areas in 2006, whereas the reverse was observed in 2021.ConclusionsThere are severe health gaps and disparities in trends between sexes and different areas in China. Males and rural populations need to be focused on targeted interventions for the main influencing factors.

Trends in life expectancy and life disparity in Turkiye before and during the Covid-19 period

Objective: This descriptive study examines Turkiye's life expectancy trends from 2013 to 2022, encompassing the COVID-19 period. Methods: This study used the Turkish Statistical Institute (TURKSTAT) cause of death data and explored trends in life expectancy and life disparity by using the line-integral decomposition model. Results: According to results, before the pandemic, increased male life expectancy and reduced disparity resulted from improved outcomes in unintentional injuries and malignant neoplasms during adulthood. Female life expectancy gains were driven by declining cardiovascular diseases in old age. However, during COVID-19, males experienced a greater loss of life expectancy than females in youth and adulthood, while females faced higher mortality rates in old age than males. The pandemic has exacerbated the female-male gap in life expectancy and disparity, with all causes of death increasing except for an improvement in malignant neoplasms among males. Conclusion: The study suggests prioritizing policies that address the health challenges faced by elderly females and young/adult males to mitigate the pandemic's impact on public health.

Semi-diurnal distribution of polycyclic aromatic hydrocarbons bound to PM2.5 and PM0.1 during pollution episode in the urban area of Hanoi.

Every year, Hanoi suffers from several episodes (periods with daily concentration of PM2.5 higher than 50µgm-3 during at least two consecutive days). These episodes are of health concern because of the high concentration of PM2.5 and/or PM0.1 and the presence of PM-bound toxic components, such as, PAHs. In this study, the concentrations of PAHs bound to PM2.5 and PM0.1 in night-time and day-time samples during episode and non-episode periods in December 2021 were determined. The concentrations of PAHs bound to PM2.5 were found to increase significantly from day-time samples of 3.24 ± 0.83ngm-3 to night-time samples of 10.8 ± 4.45ngm-3 in episode periods. However, PAHs bound to PM0.1 increased slightly from day-time samples of 0.58 ± 0.12ngm-3 to night-time samples of 0.89 ± 0.30ngm-3 in episode periods. Diagnostic ratios of PAHs indicate that biomass/coal combustion andvehicular emissionare the primary sources of PAHs. The incremental lifetime cancer risk was estimated to vary from 8.7E-09 to 2.5E-08 for children and 6.7E-08 to 2.2E-07 for adults, respectively. Accordingly, loss of life expectancy was estimated at 0.11min and 0.82min for children and adults, respectively. These findings imply that the carcinogenic impact induced by PAHs via inhalation is negligible during the episode period.

Associations of social determinants of health with life expectancy and future health risks among individuals with type 2 diabetes: two nationwide cohort studies in the UK and USA

Social determinants of health (SDHs) are the primary drivers of preventable health inequities, and the associations between SDHs and health outcomes among individuals with type 2diabetes remain unclear. This study aimed to estimate the associations of combined SDHs with life expectancy and future health risks among adults with type 2diabetes from the UK and USA. In an analysis of two nationwide cohort studies, adults with type 2diabetes were identified from the UKBiobank from March 13, 2006, to Oct 1, 2010 (adults aged 37-73years) and the US National Health and Nutrition Examination Survey (NHANES) from 1999to 2018 (adults aged ≥20years). Participants with type 2diabetes at baseline were included in our analysis. Participants without information on SDHs or follow-up were excluded. TheUKBiobank assessed 17SDHs and the US NHANES assessed ten SDHs, with each SDH dichotomised into advantaged and disadvantaged levels. The combined score of SDHs were calculated as the sum of the weighted scores for each SDH. Participants were then categorised into tertiles (favourable, medium, and unfavourable SDHgroups). Primary outcomes were life expectancy and mortality in both cohorts, and incidences of cardiovascular disease, diabetes-related microvascular disease, dementia, and cancer in the UK Biobank. Outcomes were obtained from disease registries up until Dec 31, 2021, in the UK Biobank and Dec 31, 2019, in the USNHANES cohorts. We included 17 321participants from the UK Biobank cohort (median age 61·0years [IQR 56·0-65·0]; 6028[34·8%] women and 11 293 [65·2%] men) and 7885participants from the NHANES cohort (mean age 59·2years [95% CI 58·7-59·6]; 3835 [49·1%, weighted] women and 4050 [50·9%, weighted] men) in our analysis. In the UKBiobank, 3235deaths (median follow-up 12·3years [IQR 11·5-13·2]), 3010incident cardiovascular disease (12·1years [10·8-13·0]), 1997 diabetes-related microvascular disease (8·0years [7·1-8·9]), 773dementia (12·6years [11·8-13·5]), and 2259cancer cases (11·3years [10·4-12·2]) were documented; and the US NHANES documented 2278deaths during a median follow-up of 7·0years (3·7-11·2). After multivariable adjustment, compared with the favourable SDH group, the hazard ratio was 1·33 (95% CI 1·21-1·46) in the medium SDH group and 1·89(1·72-2·07) in the unfavourable SDHgroup in the UK Biobank cohort; 1·51 (1·34-1·70) in the medium SDH group and 2·02 (1·75-2·33) in theunfavourable SDH group in the US NHANES cohort for all-cause mortality; 1·13 (1·04-1·24) in the medium SDHgroup and 1·40 (1·27-1·53) in the unfavourable SDH group for incident cardiovascular disease; 1·13(1·01-1·27) in the medium SDH group and 1·41 (1·26-1·59) in the unfavourable SDHgroup for incident diabetes-related microvascular disease; 1·35 (1·11-1·64) in the medium SDH group and 1·76 (1·46-2·13) in the unfavourable SDH group for incident dementia; and 1·02 (0·92-1·13) in the medium SDHgroup and 1·17 (1·05-1·30) in the unfavourable SDH group for incident cancer in the UK Biobank cohort (ptrend<0·010for each category). At the age of 45years, the mean life expectancy of participants was 1·6years (0·6-2·3) shorter in the medium SDH group and 4·4years (3·3-5·4) shorter in the unfavourable SDH group than in the favourable SDH group in the UK Biobank. In the US NHAHES cohort, the life expectancy was 1·7years (0·6-2·7) shorter in the medium SDH group and 3·0years (1·8-4·3) shorter in the unfavourable SDHgroup, compared with the favourable group. Combined unfavourable SDHs were associated with a greater loss of life expectancy and higher risks of developing future adverse health outcomes among adults with type 2diabetes. These associations were similar across two nationwide cohorts from varied social contexts, and were largely consistent across populations with different demographic, lifestyle, and clinical features. Thus, assessing the combined SDHs of individuals with type 2diabetes might be a promising approach to incorporate into diabetes care to identify socially vulnerable groups and reduce disease burden. The National Natural Science Foundation of China, the National Key R&D Program of China, and the Fundamental Research Funds for the Central Universities.

Does BioAge identify accelerated aging in individuals with bipolar disorder? An exploratory study in the FACE-BD cohort.

Individuals with bipolar disorders (BD) have an estimated loss of life expectancy around 10-15 years. Several laboratory-measured biomarkers of accelerated aging exist (e.g., telomere length), however with a questionable transferability to bedside. There is a need for easily and inexpensively measurable markers of aging, usable in routine practice, such as BioAge. We calculated BioAge that estimates biological age based on routine blood tests and a physical exam, in a sample of 2220 outpatients with BD. We investigated associations between BioAge Acceleration (BioAgeAccel), which is an indicator of accelerated aging, and sociodemographic variables, clinical variables, and current psychotropic medication use. Mean chronological age was 40.2 (±12.9). Mean BioAge was 39.1 (±12.4). Mean BioAgeAccel was 0.08 (±1.8). A minority of individuals (15%) had a BioAgeAccel above 2 years. Multivariable analyses suggested strong associations between a higher BioAgeAccel and younger age, male sex, overweight and sleep disturbances. Regarding current psychotropic medication use, discrepancies between univariate and multivariate analyses were observed. A minority of individuals with BD had an accelerated aging as measured by BioAge. We identified associations with potentially modifiable factors, such as higher body mass index and sleep disturbances, that are however nonspecific to BD. These results require replications in independent samples of individuals with BD, and comparisons with a control group matched for age and gender. Longitudinal studies are also required to test whether any change in metabolic health, or sleep might decrease BioAgeAccel.

Impact of cancer diagnosis on life expectancy by area-level socioeconomic groups in New South Wales, Australia: a population-based study.

Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy (LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status (SES). Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common cancers. Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years (95% CI: 2.5-3.2 years) vs. 1.6 years (95% CI: 1.3-1.9 years)] and breast cancer [1.6 years (95% CI: 1.4-1.8 years) vs. 1.2 years (95% CI: 1.0-1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years (95% CI: 16.1-16.8 years) vs. 16.2 years (95% CI: 15.7-16.7 years)] and liver cancer [15.5 years (95% CI: 15.0-16.0 years) vs. 14.7 years (95% CI: 14.0-15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years (95% CI: 0.4-1.4 years) vs. 0.6 years (95% CI: 0.2-1.0 years)] or melanoma [0.9 years (95% CI: 0.8-1.1 years) vs. 0.7 years (95% CI: 0.5-0.8 years)] had the lowest average LOLE. Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expectancy.

Quantifying work-related social inequalities in life expectancy: a methodological proof-of-concept.

Employment and working conditions are strong social determinants of health, yet many epidemiological studies fail to account for their impact on life expectancy calculations. Integration of working conditions into health estimates requires both valid methodology and data sources. Using the French National Health and Career Path survey and French life tables, we quantified the impact of four major work-related factors (lack of job control, job insecurity, unemployment, and occupational physical activity) in explaining socio-occupational inequalities in life expectancy. Using a formula-based approach, we computed work-related loss in life expectancy by socio-occupational group separately by sex. Based on life expectancy at age 35, we estimated a range from 1.3 to 3.3 years of life lost for men, and from 0.5 to 1.8 years for women are attributed to a combination of these four key factors. Although subject to sources of under- and over-estimation, the differential life expectancy at age 35 between senior executives and manual workers would substantially decrease, had these exposures been set at the theoretical minimum level. This proof-of-concept analysis demonstrates the utility of accounting for occupational factors and the potential to quantify the improvements in life expectancy by modifying working and employment conditions.

Excess Mortality and Loss of Life Expectancy After Myocardial Infarction: A Registry-Based Matched Cohort Study.

The effect of myocardial infarction (MI) on life expectancy is difficult to study because the prevalence of MI hinders direct comparison with the life expectancy of the general population. We sought to assess this in relation to age, sex, and left ventricular ejection fraction (LVEF) by comparing individuals with MI with matched comparators without previous MI. We included patients with a first MI between 1991 and 2022 from the nationwide SWEDEHEART registry (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies), each matched with up to 5 comparators on age, sex, and region of residence. Flexible parametric survival models were used to estimate excess mortality risk and mean loss of life expectancy (LOLE) depending on index year, age, sex, and LVEF, and adjusted for differences in characteristics. A total of 335 748 cases were matched to 1 625 396 comparators. A higher LOLE was observed in younger individuals, women, and those with reduced LVEF (<50%). In 2022, the unadjusted and adjusted mean LOLE spanned from 11.1 and 9.5 years in 50-year-old women with reduced LVEF to 5 and 3.7 months in 80-year-old men with preserved LVEF. Between 1992 and 2022, the adjusted mean LOLE decreased by 36% to 55%: from 4.4 to 2.0 years and from 3.3 to 1.9 years in 50-year-old women and men, respectively, and from 1.7 to 1.0 years and from 1.4 to 0.9 years in 80-year-old women and men, respectively. LOLE is higher in younger individuals, women, and those with reduced LVEF, but is attenuated when adjusting for comorbidities and risk factors. Advances in MI treatment during the past 30 years have almost halved LOLE, with no clear sign of leveling off to a plateau.

Sex differences in physical functioning among older adults: cross-sectional results from the OUTDOOR ACTIVE study

BackgroundMaintaining good functional ability is a key component of healthy ageing and a basic requirement for carrying out activities of daily living, staying independent, and delaying admission to a nursing home. Even though women have a higher life expectancy and slower age-related muscle mass loss than men, they often show a higher prevalence of limitations in physical functioning. However, the reasons behind these sex differences are still unclear. Therefore, the aims of this study were to investigate sex differences among older adults regarding physical functioning and to study which factors are explaining these sex differences.MethodsCross-sectional data from participants of the OUTDOOR ACTIVE study residing in Bremen, Germany, aged 65 to 75 years, were included in the analyses. Physical functioning was assessed via a self-administered questionnaire using the SF-36 10-item Physical Functioning Scale. Social, lifestyle, and health-related factors were also assessed using the questionnaire. Physical activity was measured objectively using wrist-worn accelerometers over seven consecutive days. Descriptive analyses with absolute and relative frequencies, means and standard deviations, as well as T-tests and chi-square tests were carried out. To test for associations between sex, physical functioning, and several individual factors, linear regressions were performed.ResultsData of 2 141 participants (52.1% female) were included in the study. Women and men showed statistically significant differences in physical functioning, with men perceiving fewer limitations than women. On average, women had a physical functioning score of 81.4 ± 19.3 and men 86.7 ± 17.0. Linear regression showed a statistically significant negative association between physical functioning score and sex (β: -0.15, 95% CL: -0.19, -0.10). The association remained statistically significant when adding individual factors to the model. All factors together were only able to explain 51% of the physical functioning-sex association with health indicators and the presence of chronic diseases being the most influential factors.ConclusionsWe found sex differences in physical functioning, with older women having more limitations than older men. The results showed that health-related factors and chronic diseases played the biggest roles in the different physical functioning scores of women and men. These findings contribute to future longitudinal, more in-depth research.Trial registrationGerman Clinical Trials Register DRKS00015117 (Date of registration 17-07-2018).

Excess deaths and loss of life expectancy attributed to long-term NO2 exposure in the Chinese elderly

BackgroundEvidence linking nitrogen dioxide (NO2) air pollution to life span of high-vulnerability older adults is extensively scarce in low- and middle-income countries. This study seeks to quantify mortality risk, excess deaths, and loss of life expectancy (LLE) associated with long-term exposure to NO2 among elderly individuals in China. MethodsA nationwide dynamic cohort of 20352 respondents ≥65 years old were enrolled from the China Longitudinal Health and Longevity Survey during 2005–2018. Residential exposures to NO2 and co-pollutants were assessed by well-validated spatiotemporal prediction models. A Cox regression model with time-dependent covariates was utilized to quantify the association of all-cause mortality with NO2 exposure, controlling for confounders such as demographics, lifestyle, health status, and ambient temperature. NO2-attributable deaths and LLE were evaluated for the years 2010 and 2020 based on the pooled NO2-mortality relation derived from multi-national cohort investigations. Decomposition analyses were conducted to dissociate net shift in NO2-related deaths between 2010 and 2020 into four primary contributing factors. ResultsA total of 14313 deaths were recorded during follow-up of approximately 100 hundred person-years (median 3.6 years). We observed an approximately linear relationship (nonlinear P = 0.882) of NO2 exposure with all-cause death across a broad range from 6.6 to 95.7 μg/m3. Every 10-μg/m3 rise in yearly average NO2 concentration was linked to a hazard ratio (HR) of 1.045 (95% confidence interval [CI]: 1.031–1.059). In the updated meta-analysis of this study and 9 existing cohorts, we estimated a pooled HR of 1.043 (95% CI: 1.023–1.063) for each 10-μg/m3 growth in NO2. Reaching a 10-μg/m3 counterfactual target of NO2 concentration in China could avoid 0.33 (95% empirical CI: 0.19–0.49) million premature deaths and an LLE of 0.40 (95% empirical CI: 0.23–0.59) years in 2010, which greatly dropped to 0.24 (95% empirical CI: 0.14–0.36) million deaths and 0.21 (95% empirical CI: 0.12–0.31) years of LLE in 2020. The net fall in NO2-attributable deaths (–26.8%) between 2010 and 2020 was primarily driven by the declines in both NO2 concentration (–41.6%) and mortality rate (–27.1%) under population growth (+41.0%) and age structure transition (+0.9%). ConclusionsOur findings provide national evidence for increased risk of premature death and loss of life expectancy attributed to later-life NO2 exposure among the elderly in China. In an accelerated aging society, strengthened clean air actions should be formulated to minimize the health burden and regional inequality in NO2-attributable mortality.

Impact of opioid overdoses on US life expectancy and years of life lost, by demographic group and stimulant co-involvement: a mortality data analysis from 2019 to 2022

The United States' opioid crisis is worsening, with the number of deaths reaching 81,806 in 2022 after more than tripling over the past decade. This study aimed to comprehensively characterize changes in burden of opioid overdose mortality in terms of life expectancy reduction and years of life lost between 2019 and 2022, including differential burden across demographic groups and the contribution of polysubstance use. Using life tables and counts for all-cause and opioid overdose deaths from the National Center for Health Statistics, we constructed cause-eliminated life tables to estimate mortality by age in the absence of opioid-related deaths. We calculated the loss in life expectancy at birth (LLE) and total years of life lost (YLL) due to opioid overdose deaths by state of residency, sex, racial/ethnic group, and co-involvement of cocaine and psychostimulants. Opioid-related deaths in the US led to an estimated 3.1 million years of life lost in 2022 (38 years per death), compared to 2.0 million years lost in 2019. Relative to a scenario with no opioid mortality, we estimate that opioid-related deaths reduced life expectancy nationally by 0.67 years in 2022 vs 0.52 years in 2019. This LLE worsened in all racial/ethnic groups during the study period: 0.76y-0.96y for white men, 0.36y-0.55y for white women, 0.59y-1.1y for Black men, 0.27y-0.53y for Black women, 0.31y-0.82y for Hispanic men, 0.19y-0.31y for Hispanic women, 0.62y-1.5y for American Indian/Alaska Native (AI/AN) men, 0.43y-1y for AI/AN women, 0.09y-0.2y for Asian men, and 0.08y-0.13y for Asian women. Nearly all states experienced an increase in years of life lost (YLL) per capita from 2019 to 2022, with YLL more than doubling in 16 states. Cocaine or psychostimulants with abuse potential (incl. methamphetamines) were involved in half of all deaths and years of life lost in 2022, with substantial variation in the predominant drug class by state and racial/ethnic group. The burden of opioid-related mortality increased dramatically in the US between 2019 and 2022, coinciding with the period of the COVID-19 pandemic and the associated disruptions to social, economic, and health systems. Opioid overdose deaths are an important contributor to decreasing US life expectancy, and Black, Hispanic, and Native Americans now experience mortality burdens approaching or exceeding white Americans. None.

Impaired thyroid hormone sensitivity exacerbates the effect of PM2.5 and its components on dyslipidemia in schizophrenia

BackgroundDyslipidemia in schizophrenia causes a serious loss of healthy life expectancy, making it imperative to explore key environmental risk factors. We aimed to assess the effect of PM2.5 and its constituents on dyslipidemia in schizophrenia, identify the critical hazardous components, and investigate the role of impaired thyroid hormones (THs) sensitivity in this association. MethodsWe collected disease data on schizophrenia from the Anhui Mental Health Center from 2019 to 2022. Logistic regression was constructed to explore the effect of average annual exposure to PM2.5 and its components [black carbon (BC), organic matter (OM), sulfate (SO42−), ammonium (NH4+), and nitrate (NO3−)] on dyslipidemia, with subgroup analyses for age and gender. The degree of impaired THs sensitivity in participants was reflected by the Thyroid Feedback Quantile-based Index (TFQI), and its role in the association of PM2.5 components with dyslipidemia was explored. ResultsA total of 5125 patients with schizophrenia were included in this study. Exposure to PM2.5 and its components (BC, OM, SO42−, NH4+, and NO3−) were associated with dyslipidemia with the odds ratios and 95 % confidence interval of 1.13 (1.04, 1.23), 1.16 (1.07, 1.26), 1.15 (1.06, 1.25), 1.11 (1.03, 1.20), 1.09 (1.00, 1.18), 1.12 (1.04, 1.20), respectively. Mixed exposure modeling indicated that BC played a major role in the effects of the mixture. More significant associations were observed in males and groups <45 years. In addition, we found that the effect of PM2.5 and its components on dyslipidemia was exacerbated as impaired THs sensitivity in the patients. ConclusionsExposure to PM2.5 and its components is associated with an increased risk of dyslipidemia in schizophrenia, which may be exacerbated by impaired THs sensitivity. Our results suggest a new perspective for the management of ambient particulate pollution and the protection of thyroid function in schizophrenia.

Projected Life Expectancy for Adolescents With HIV in the US

Life expectancy is a key measure of overall population health. Life expectancy estimates for youth with HIV in the US are needed in the current HIV care and treatment context to guide health policies and resource allocation. To compare life expectancy between 18-year-old youth with perinatally acquired HIV (PHIV), youth with nonperinatally acquired HIV (NPHIV), and youth without HIV. Using a US-focused adolescent-specific Monte Carlo state-transition HIV model, we simulated individuals from age 18 years until death. We estimated probabilities of HIV treatment and care engagement, HIV progression, clinical events, and mortality from observational cohorts and clinical trials for model input parameters. The simulated individuals were 18-year-old race and ethnicity-matched youth with PHIV, youth with NPHIV, and youth without HIV; 47%, 85%, and 50% were assigned male sex at birth, respectively. Individuals were categorized by US Centers for Disease Control and Prevention-defined HIV acquisition risk: men who have sex with men, people who ever injected drugs, heterosexually active individuals at increased risk for HIV infection, or average risk for HIV infection. Distributions were 3%, 2%, 12%, and 83% for youth with PHIV and youth without HIV, and 80%, 6%, 14%, and 0% for youth with NPHIV, respectively. Among the simulated youth in this analysis, individuals were 61% Black, 24% Hispanic, and 15% White, respectively. HIV status by timing of acquisition. Life expectancy loss for youth with PHIV and youth with NPHIV: difference between mean projected life expectancy under current and ideal HIV care scenarios compared with youth without HIV. Uncertainty intervals reflect varying adolescent HIV-related mortality inputs (95% CIs). Compared with youth without HIV (life expectancy: male, 76.3 years; female, 81.7 years), male youth with PHIV and youth with NPHIV had projected life expectancy losses of 10.4 years (95% CI, 5.5-18.1) and 15.0 years (95% CI, 9.3-26.8); female youth with PHIV and youth with NPHIV had projected life expectancy losses of 11.8 years (95% CI, 6.4-20.2) and 19.5 years (95% CI, 13.8-31.6), respectively. When receiving ideal HIV care, life expectancy losses were projected to improve for youth with PHIV (male: 0.5 years [95% CI, 0.3-1.8]: female: 0.6 years [95% CI, 0.4-2.1]) but were projected to persist for youth with NPHIV (male: 6.0 years [95% CI, 5.0-9.1]; female: 10.4 years [95% CI, 9.4-13.6]). This adolescent-focused microsimulation modeling analysis projected that youth with HIV would have shorter life expectancy than youth without HIV. Projected differences were larger for youth with NPHIV compared with youth with PHIV. Differences in mortality by sex at birth, sexual behavior, and injection drug use contributed to lower projected life expectancy among youth with NPHIV. Interventions focused on HIV care and social factors are needed to improve life expectancy for youth with HIV in the US.