Personal care products (PCPs) are widespread environmental exposures, yet their combined and system-wide effects on serum lipid profiles in the aging population remain poorly understood. This study aimed to comprehensively assess the association between exposure to multiple PCPs and serum lipid profiles in healthy older adults and to explore underlying molecular pathways and biological mechanisms. We conducted a prospective panel study with five monthly follow-up surveys between September 2018 and January 2019 among 76 healthy older adults (60-69 years) in Jinan, China. This study measured urinary concentrations of PCPs, serum lipid markers, and multiomics profiles (transcriptomics, lipidomics, and metabolomics). We employed linear mixed-effects models to analyze exposure-outcome associations and integrated multiomics data with causal inference testing and Ingenuity Pathway Analysis to identify mediating biomolecules and biological mechanisms. Additional analyses examined the relationships of PCP exposures with inflammatory cytokines, oxidative stress biomarkers, and electrocardiographic (ECG) parameters to provide functional support for the identified pathways and their associated phenotypic consequences. Four PCPs [Benzophenone-2 (BP-2), Benzophenone-3 (BP-3), 4-Hydroxy benzophenone (4-OHBP), and Ethyl p-Hydroxybenzoate (EtP)] were significantly associated with altered serum lipid profiles. Multiomics analyses suggested their convergence on a PPAR-centered immunometabolic network, with S100 signaling identified as a novel activation pathway. Specifically, BP-2 was associated with patterns consistent with IL-4/IL-13-mediated alternative macrophage activation, while PPAR appeared to be involved in inflammatory polarization and metabolic reprogramming. Cytokine analysis revealed associations between BP-2 and key inflammatory mediators (e.g., IL-1 beta), oxidative stress assessment linked BP-2 exposure to elevated markers of oxidative damage (e.g., 8-PGF2 alpha), and ECG analysis associated BP-2 exposure with altered cardiac electrophysiology (e.g., QRS duration). These multifaceted findings suggest associations between PCP exposures and serum lipid profiles, and highlight the potential contribution to cardiovascular risk. Our findings provide integrated, multilayered evidence suggesting associations between exposure to PCPs and alterations in serum lipid profiles in older adults, bridging exposure profiles, biomolecular perturbations, and subclinical functional changes. These results serve as a hypothesis-generating theoretical foundation that, pending confirmation in larger studies or experimental validation, advances the understanding of environmental metabolic disruption in aging populations.

Food insecurity is associated with increased mortality risk, but whether this association is modified by lifestyle behaviors in the general adult population remains unclear. We analyzed seven NHANES cycles (2005–2018) including 41,161 adults (≥ 18 years). Food security was categorized per USDA guidelines. Four lifestyle factors—smoking status, alcohol consumption, physical activity, and sleep duration (< 6.5, 6.5-<7.5, or ≥ 7.5 h/night)—were assessed via standardized questionnaires, and a healthy lifestyle score (0–4) was constructed by summing these four components. All-cause mortality was determined through linkage to the National Death Index through December 31, 2019. We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95

BACKGROUND:Frailty is a well-established clinical risk factor for dementia, but its underlying mechanisms remain poorly defined. We aimed to investigate whether proteomic signatures and individual proteins linked to frailty could predict and characterize the association between frailty and dementia. METHODS:We analyzed over 52,000 UK Biobank participants free of dementia at baseline, with plasma profiles of 2,915 proteins. Physical frailty (PF) and a 49-item frailty index (FI) were assessed. Proteomic signatures were derived using multivariable linear regression and 100 repeated LASSO selections. Incident dementia was ascertained via linkage to hospital and mortality records. Associations with incident dementia were assessed using multivariable Cox proportional hazards models, dose-response, and mediation analyses. RESULTS:During 13.6 years of follow-up, 1,437 participants developed dementia. Proteomic signatures for PF and FI were independently associated with dementia risk (hazard ratios [HRs] up to 2.80). Stratification by signature quintiles showed clear gradients in both absolute and relative dementia risk. For all-cause dementia, cumulative incidence ranged from 1.19% to 5.27% (HR up to 3.29), and for vascular dementia, from 0.16% to 1.19% (HR up to 4.53). Similar trends were observed for Alzheimer's dementia. Mediation analysis indicated that proteomic signatures statistically accounted for 46%-53% of the association between frailty and dementia risk. Key proteins, including GDF15, HPGDS, ITGAV, SPP1, CHGA, and LGALS4, were identified as top contributors and mapped to immune-inflammatory, neuroimmune, and extracellular matrix pathways. CONCLUSION:Frailty-related proteomic signatures and key proteins predict dementia risk and capture biological features beyond clinical frailty. These molecular markers may facilitate early risk stratification and support future research into prevention strategies.

AIMS:Longitudinal evidence is limited on how changes in insulin resistance (IR) indices-including estimated glucose disposal rate (eGDR), triglyceride-glucose index (TyG), metabolic score for insulin resistance (METS-IR), and lipid accumulation product (LAP)-relate to liver-related adverse outcomes. This study aims to assess their associations and the discriminative performance of IR indices. MATERIALS AND METHODS:IR indices were calculated from UK Biobank data at two surveys (2006-2010 and 2012-2013). Liver-related adverse outcomes, including liver disease, major adverse liver outcomes (MALO), and metabolic dysfunction-associated steatotic liver disease (MASLD), were identified via ICD-10 codes. K-means clustering defined four change patterns per index, and cumulative averages reflected long-term exposure. Cox regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs). Discriminative performance was assessed using receiver operating characteristic (ROC) curves. RESULTS:The participants were followed for a mean of 9.7 years. Compared with persistently low eGDR levels, the persistently high group was associated with significantly lower risks of liver-related adverse outcomes, with HRs of 0.52 (95% Cl: 0.35-0.77) for liver disease, 0.30 (0.19-0.49) for MALO, and 0.31 (0.17-0.55) for MASLD. In contrast, persistently high TyG, METS-IR, and LAP were associated with increased risks of liver-related adverse outcomes, with METS-IR showing the strongest association with MASLD (HR = 10.50, 4.00-27.58). Cumulative eGDR was inversely associated with liver-related adverse outcomes (per 1 SD increase: HRs ranged from 0.52 to 0.68), whereas TyG, METS-IR, and LAP were positively associated, with METS-IR showing the strongest link to MASLD (HR = 1.70, 1.48-1.96). LAP demonstrated the highest discriminative performance in ROC analysis, particularly in females and those under 60 (AUC for MALO in females: up to 0.813). CONCLUSIONS:Dynamic changes in IR indices are independently associated with liver-related adverse outcomes. Among these indices, LAP showed relatively stronger discriminative performance in females. Collectively, these indices may have potential utility as non-invasive markers for liver disease risk stratification.

The estimation of chronological age based on bone mineral density (BMD) metrics for specific anatomical sites is a critical task in forensic anthropology. Although dual-energy X-ray absorptiometry (DXA) scans of the distal 1/3 of radius and ulna are widely used in large-scale osteoporosis screenings, forensic studies leveraging such data remain scarce. This study utilized a retrospective dataset (spanning ages 12-96) of 5,134 DXA scans from the distal 1/3 radius and ulna. We analyzed these DXA scans with metadata, including sex, body mass index (BMI), and osteoporosis diagnoses, to train machine learning models. Linear regression (LR), support vector regression (SVR), random forest regression (RFR), XGBoost (XGB), and LightGBM (LGBM) models were optimized via Bayesian cross-validation. Results indicate that the simplest model constructed solely based on BMD data + Diagnoses showed good performance with a mean absolute error (MAE) of 2.40 years. The best-performing model was the RFR model built using the combination of Female + Diagnoses, with an MAE of 2.18 years. When only considering BMI, the best model was the RFR model for the Normal weight + Diagnoses combination, with an MAE of 2.54 years. These models have been integrated into the AgeMiner tool (https://github.com/Rarapie/AgeMiner), allowing forensic users to select the optimal model according to metadata of the tested person, thereby enabling fast and end-to-end chronological age estimation. In summary, AgeMiner and its integrated ML models provide an efficient, accurate, and customizable tool for forensic age estimation in adults and the elderly.

Evidence linking quaternary ammonium compounds (QACs) to cardiac function changes remains limited, particularly at the population level, and mechanistic insights are largely unexplored. To address this critical knowledge gap, we conducted a five-month longitudinal panel study that integrated epidemiological assessments with mechanistic multiomics analyses, involving 76 healthy elderly participants in Jinan, Shandong Province, China. Across five repeated measurement visits, participants underwent structured, face-to-face questionnaires, standardized physical examinations, and systematic biosample collection. Data on demographic characteristics, urinary QAC concentrations, and electrocardiogram (ECG) parameters were comprehensively gathered. Correlations between 9 QACs and 5 ECG parameters were assessed using a linear mixed-effects model (LMM), while interaction and stratified analyses examined body fat-related modulation of QAC-induced ECG disturbances. To elucidate the underlying biomolecular perturbations, multiomics analyses were further performed. Our results revealed that benzyltrimethylammonium bromide (BTMAC), dimethyldioctylammonium bromide (C8-DDAC), and diallyldimethylammonium chloride (DAD) were significantly associated with ECG alterations, suggesting potential cardiotoxicity in human populations. Specifically, both BTMAC and DAD were associated with prolonged QRS time, whereas C8-DDAC was related to increased QT interval, QTc interval, and RV5/SV1 amplitude, as well as a reduced QRS time. Interestingly, higher body fat content attenuated the adverse cardiac effects induced by QAC exposures, indicating a possible protective buffering mechanism. Moreover, the causal inference test (CIT) and ingenuity pathway analysis (IPA) collectively indicated that QAC-induced cardiac electrophysiological dysfunction may be associated with certain critical signaling pathways, particularly those involving tumor protein p53 (TP53), nucleosome assembly protein 1 like 1 (NAP1L1), dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), and peroxisome proliferator activated receptor alpha (PPARα) signaling. Taken together, this study provides the first population-based evidence of QAC-associated cardiotoxicity and proposes the underlying biomolecular alternations. These insights offer a scientific foundation for developing targeted strategies to prevent and mitigate environmentally induced cardiovascular risks in susceptible populations.

Frailty is a common geriatric syndrome associated with increased mortality, yet its underlying biological mechanisms and potential value for early risk stratification remain inadequately understood. In this large prospective cohort of more than 260,000 UK Biobank participants with plasma metabolomic profiling, we identified and validated metabolomic signatures of physical frailty and a 49-item frailty index using 50-times repeated 10-fold cross-validated elastic-net regression. The signatures demonstrated strong internal stability and geographic reproducibility and reflected coordinated alterations across lipid, amino acid, energy, and inflammatory pathways. Higher signature levels were significantly associated with increased risks of all-cause and cause-specific mortality, including cancer, cardiovascular, respiratory, and digestive deaths. Individuals in the highest-risk tertile had more than 2.5-fold higher risks of cardiovascular, respiratory, and digestive mortality. At age 60, individuals above the median signature level were estimated to have 4.1 fewer years of life expectancy. Mediation analyses indicated that the metabolomic signatures statistically explained up to 35% of the observed frailty-mortality association. Associations were stronger among younger individuals and differed by sex and BMI. These findings suggest that frailty-related plasma metabolomic signatures capture systemic metabolic correlates of biological aging and may support early mortality risk prediction and personalized prevention strategies in aging populations.

Background:Metabolic dysfunction-associated steatotic liver disease (MASLD) substantially elevates the risk of heart failure (HF). While large-scale proteomics improves HF prediction in general populations, its incremental predictive value beyond standard clinical models in MASLD remains unexplored. Objective:To identify plasma protein biomarkers for incident HF in MASLD and evaluate the predictive utility of integrating these signatures with the predicting risk of cardiovascular disease events (PREVENT) clinical model. Methods:We prospectively analyzed 17,091 individuals with MASLD at baseline. Multivariable and LASSO-Cox regressions were applied to 2911 plasma proteins to identify optimal predictors. Predictive discrimination and reclassification were assessed using Harrell's C-index, time-dependent area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Results:Over a median follow-up of 13.56 years, 953 incident HF events occurred. Integrating the PREVENT model with a 37-protein panel substantially improved predictive discrimination (C-index 0.805 vs. 0.723; ΔC-index 0.082, 95%CI: 0.064-0.100). Moreover, a parsimonious model containing only 5 proteins (NT-proBNP, WFDC2, LTBP2, BCAN, HAVCR1) delivered a meaningful incremental improvement over the PREVENT baseline (C-index 0.769 vs. 0.723; ΔC-index 0.046, 95%CI: 0.027-0.064). Pathway analyses indicated these proteins associating with systemic inflammation and extracellular matrix remodeling. Conclusions:Large-scale proteomics significantly enhances HF risk prediction in MASLD, providing a robust tool for identifying high-risk individuals who may benefit from intensive clinical monitoring and preventive strategies.

BACKGROUND:Insomnia symptoms are prevalent in older adults and linked to cardiovascular disease (CVD), but the role of long-term symptom trajectories remains unclear. We investigated associations between insomnia symptoms, their trajectories over time and incident CVD in a population-based cohort. METHODS:This longitudinal study included 12 102 participants aged ≥50 years without baseline CVD from the US Health and Retirement Study (2002-2018). Insomnia symptoms (non-restorative sleep, difficulty initiating/maintaining sleep, early awakening) were assessed at baseline; trajectories were modelled over 4 years (2002-2006) using latent class analysis. Cox models estimated HRs for incident CVD (heart disease or stroke), adjusted for sociodemographics, lifestyle and comorbidities. RESULTS:During a median of 10.2-year follow-up, 3962 incident CVD events occurred. Compared with no symptoms, participants with one, two, or three to four symptoms had higher CVD risk (HR 1.16, 95% CI 1.05 to 1.27; HR 1.16, 95% CI 1.05 to 1.28; HR 1.26, 95% CI 1.15 to 1.38, respectively). Four trajectories were identified: persistent low (56.3%), decreasing (27.1%), increasing (7.2%) and persistent high (9.5%). Compared with persistent low, increasing (HR 1.28, 95% CI 1.10 to 1.50) and persistent high (HR 1.32, 95% CI 1.15 to 1.50) trajectories were associated with elevated CVD risk. CONCLUSIONS:Greater burden of insomnia symptoms at baseline and trajectories over time were associated with higher CVD incidence in older adults.

Background:Tyrosine kinase inhibitors (TKIs) are a mainstay of therapy for advanced non-small-cell lung cancer (NSCLC) harboring actionable driver mutations. However, histologic transformation from NSCLC to small-cell lung cancer (SCLC) represents a particularly challenging mechanism of treatment resistance. This study aimed to characterize the incidence, timing, and clinical outcomes of SCLC transformation in this population in routine clinical practice. Methods:This multicenter real-world cohort study included consecutive patients with stage III-IV NSCLC treated at three hospitals in Sichuan Province, China, between January 2018 and December 2021. Eligible patients had pathologically confirmed NSCLC, driver mutations, baseline whole-body imaging, complete clinical data, and received TKIs. Re-biopsy was performed to evaluate histologic changes. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared with the log-rank test. Results:Among 387 enrolled patients, driver mutations included EGFR (73.4%), ALK (12.6%), ROS1 (8.3%), and HER2 (5.7%). First-line treatment was TKI monotherapy in 75.2% and TKI-based combinations in 24.8%. Of the 251 patients (64.9%) who underwent re-biopsy, SCLC transformation was identified in 36 patients (14.3%). Transformation occurred predominantly after first-line TKI therapy (27/36), with additional cases after second-line therapy (9/36). OS and PFS were significantly shorter in patients with transformed SCLC than in non-transformed patients. Conclusions:In this multicenter real-world cohort study of driver-mutated advanced NSCLC treated with TKIs, SCLC transformation was not rare among re-biopsied patients and occurred mainly after first-line therapy. These findings support a low threshold for repeat tissue sampling at disease progression to detect SCLC transformation and guide timely transition to SCLC-directed treatment.

We explored the association between frailty and respiratory infectious diseases (RIDs) through a large cohort of 423,691 participants in the UK Biobank. Participants without baseline RIDs were assessed by physical frailty and frailty index. A total of 16,848 participants had repeated assessments. We divided participants into non-frail, prefrail, and frail groups and categorized frailty changes as alleviation, maintenance, or aggravation. We estimated risk for RIDs, including influenza, pneumonia, and other acute lower respiratory infections. Compared with nonfrailty, prefrailty and frailty increased risk for RIDs 1.32-2.29 times. Each 0.1-point increase in frailty index per year raised risk for RIDs by 47%; each 1-point increase in physical frailty per year increased risk by 26%. Frailty worsening (e.g., aggravation of prefrailty) amplified risk by 2.31-4.16 times. Partial frailty improvement did not fully eliminate risk. Frailty is a modifiable, dynamic risk factor, underscoring the need for early frailty identification and intervention to reduce RIDs in high-risk populations.

In forensic cases, the accurate prediction of time since deposition (TsD) for body fluids plays a critical role in evaluating the relevance of biological evidence to criminal cases and reconstructing the timelines of criminal events. While transcriptomics offers avenues for TsD analysis, the environmental sensitivity of mRNA limits its practical utility. In contrast, miRNAs demonstrate superior potential as biomarkers due to their short sequences, high stability, and environmental resistance; however, their forensic application for TsD estimation remains underexplored. This study applied small RNA sequencing to analyze miRNA expression in semen samples from 10 donors across seven TsD intervals (0-48 h). Time-dependent miRNA expression modules were identified through Mfuzz clustering and weighted gene co-expression network analysis. We implemented a multi-stage feature selection pipeline, commencing with least absolute shrinkage and selection operator regression and random forest (RF) that selected 261 candidate miRNAs for model development, followed by recursive feature elimination with ElasticNet to refine the set to 12 miRNAs, and concluding with XGBoost-based multicollinearity reduction and exhaustive optimization to yield a minimal set of 7 miRNAs. The selected miRNA candidates were subsequently validated using reverse transcription-quantitative polymerase chain reaction on an independent sample set. Machine learning models constructed with the initial 261 miRNAs demonstrated that RF achieved optimal performance in the binary classification of early (0-12 h) versus late (24-48 h) TsD, with an accuracy of 0.76, F1-score of 0.75, and area under the curve of 0.82. In regression analysis, an ensemble model integrating partial least squares, ElasticNet, support vector machine, and Ridge attained a test mean absolute error of 6.76 h and an R 2 of 0.72. This research establishes a novel miRNA-based prediction framework for TsD estimation of semen, integrating dynamic expression patterns with machine learning for the advancement of forensic body fluid analysis.

Blood homocysteine (Hcy) concentrations have become a sensitive predictor of the development of cardiovascular disease. Few studies have reported the relationship between plasma vitamin E and Hcy. We aim to conduct an sex- and age-stratified investigation of the association between vitamin E status and Hcy concentrations in a large nationwide sample in China. We conducted a cross-sectional study including 15,842 Chinese adults. The exposure variable was plasma vitamin E. The outcome variables included Hcy concentrations and hyperhomocysteinemia. Multiple linear models and multivariable logistic regression were performed to evaluate the relation between plasma vitamin E and Hcy. Restricted cubic spline was conducted to examine the non-linear relationship. In men, the association between plasma vitamin E and Hcy concentrations suggested an approximately U-shaped pattern (p for nonlinearity < 0.001). Compared with men aged < 65 years with plasma vitamin E concentrations of 8.5–15.9 µg/mL, those with concentrations below 8.5 µg/mL or above 15.9 µg/mL had higher odds of hyperhomocysteinemia (OR: 1.33 (1.10,1.60), p = 0.002; OR: 1.77 (1.25, 2.50), p = 0.001, respectively). In men ≥ 65 years old, plasma vitamin E < 8.4 µg/mL was not significantly associated with hyperhomocysteinemia (OR: 1.06(0.86,1.30), p = 0.589). Among women, age-stratified spline curves generally suggested an L-shaped pattern, with higher plasma vitamin E concentrations associated with lower Hcy concentrations, followed by a plateau in the association. Sex-specific associations between plasma vitamin E and Hcy concentrations or hyperhomocysteinemia were found. The spline analyses suggested an approximately U-shaped pattern in men and an L-shaped pattern in women. In contrast to the sex-specific patterns, the association between vitamin E and Hcy were generally consistent across age groups.

BACKGROUND AND OBJECTIVES:Previous studies found that intrinsic capacity (IC) was an important risk factor for dementia. However, these studies focused on baseline IC, without considering the dynamic changes in IC. The study aimed to investigate the associations of changes in IC with cognitive decline and dementia and assess whether these associations varied by race. METHODS:A cohort study was conducted using data from the Health and Retirement Study. An IC deficit score was calculated by 7 factors reflecting 4 domains. Changes in IC were assessed by comparing the baseline IC status with that observed in the second survey. Cognitive decline was evaluated by computing a standardized z-score based on memory, executive function, and orientation. Dementia was diagnosed either through self-reported physician diagnosis or an alternative approach based on cognitive score. Linear mixed effects models and Cox models were performed to analyze the association of changes in IC with cognitive decline and dementia. RESULTS:A total of 7,744 participants (male: 42.4%, mean age: 75.6 years) were included. The median follow-up period was 8.9 years. Compared with participants who maintained robust IC status, those whose IC status progressed to deficit status showed accelerated global cognitive decline (β, -0.025; 95% CI -0.036 to -0.015) and increased risk of dementia (hazard ratio [HR], 1.38; 95% CI 1.10-1.72). Conversely, participants who recovered from IC deficit to robust status showed decelerated global cognitive decline (β, 0.010; 95% CI 0.001 to 0.019) and decreased risk of dementia (HR, 0.84; 95% CI 0.72-0.98) relative to those with stable IC deficit. In addition, the associations of baseline IC with cognitive decline and dementia appeared to be somewhat stronger among Black participants, relative to White participants (p for interaction = 0.011). Significantly decelerated global cognitive decline in IC deficit participants who recovered to robust status was observed exclusively among Black participants. DISCUSSION:The findings indicated that the progression of IC deficit status was associated with accelerated cognitive decline and increased risk of dementia. Conversely, recovery of IC deficit status was associated with a decelerated cognitive decline and decreased risk of dementia. Future studies with more measurement waves are warranted to validate these findings.

Objective:Elevated depressive symptoms are well-documented among geriatric adults with cardiovascular disease (CVD); however, few studies have accounted for long-term cumulative depressive symptom exposure. This study determined the relationship between cumulative depressive symptoms and CVD. Methods:Individual participant data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) and Health and Retirement Study (HRS). Eligible participants had access to assessment information on depressive symptoms and had no history of CVD at baseline. Long-term cumulative depressive symptoms were estimated by calculating the area under the curve based on the Center for Epidemiological Studies Depression Scale. Results:Herein, 8,861 participants from CHARLS (mean age: 58.58 years; male: 48.6%) and 7,284 from HRS (60.94 years; 35.0%) were enrolled. The median follow-up period was 5 years for the CHARLS and 10 years for the HRS. Compared with the first quartile of cumulative depressive symptoms, the HRs (95% CI) in the fourth quartile were 1.73 (1.48, 2.02) for predicting CVD ( P < 0.001), 1.83 (1.52, 2.19) for heart disease ( P < 0.001), 1.53 (95% CI: 1.17, 1.99) for stroke ( P = 0.002) in CHARLS. For HRS, the HRs (95% CI) were 1.41 (95% CI: 1.27, 1.57; P < 0.001), 1.42 (95% CI: 1.26, 1.59; P < 0.001), and 1.30 (95% CI: 1.06, 1.58; P = 0.010) respectively. Strong dose-response relationships were observed, with similar results for the two cohorts. Conclusion:Long-term cumulative depressive symptoms were significantly associated with incident CVD in middle-aged and older adults, providing insights into controlling long-term depressive symptoms to improve this cohort's health.

BACKGROUND:The relationship between intrinsic capacity (IC), genetic susceptibility, and CVD outcomes in individuals with diabetes remains unclear. METHODS:Data were obtained from 18 333 participants with diabetes (58.63 ± 7.54 years). The IC deficit score was categorised into five levels: 0, 1, 2, 3, and 4+. Outcomes included: hypertension, IHD, stroke, PAD, HF, and AF. Genetic risk scores (PRS) were constructed based on previously identified single nucleotide polymorphisms (SNPs) associated with these outcomes. RESULTS:Over a follow-up period of 9.91 to 13.43 years. Compared to those with an IC deficit score of 0, diabetes participants with a score of 4+ had significantly elevated risks, particularly for PAD (HR: 3.25, 95% CI: 2.44-4.33). The association between IC deficit score and IHD risk was stronger in individuals with low genetic risk. Notably, even among those with high genetic risk, an IC deficit score of 0 was linked to a lower risk of CVD outcomes. CONCLUSIONS:In individuals with diabetes, a higher IC deficit score is associated with an increased risk of hypertension, ischemic heart disease, stroke, PAD, HF, and AF.

INTRODUCTION:The association between social determinants of health, genetic susceptibility, and dementia risk remains unclear. This study investigates their relationship and the potential mediation by chronic conditions. METHODS:Data from 225,598 UK Biobank participants (220,847 for genetic analyses), with an average age of 55.07 years and 51.10% female, were analyzed. The data were collected during 2006-2010 and analyzed in 2025. Social determinants of health scores were weighted, combined, and categorized, and a polygenic risk score for dementia was constructed. Associations were assessed through Cox models, with mediation and sensitivity analyses conducted. RESULTS:Over a median follow-up of 13.5 years, 3,232 participants developed all-cause dementia; including 1,140 Alzheimer's disease; 545 vascular dementia; and 2,259 other dementias. Each 1-unit increase in the social determinants of health score was associated with a 13%, 9%, 16%, and 14% higher risk of all-cause dementia, Alzheimer's disease, vascular dementia, and other dementias, respectively. Compared with the favorable social determinants of health group, the medium and unfavorable social determinants of health groups had hazard ratios of 1.25 (95% CI=1.13, 1.37) and 1.69 (95% CI=1.53, 1.87) for all-cause dementia. Similar trends were observed for dementia subtypes. No significant interaction was found between social determinants of health and genetic susceptibility, but those with both unfavorable social determinants of health and high genetic risk had the highest dementia risk. The impact of social determinants of health on dementia was stronger in individuals aged <60 years. Diabetes, cardiovascular disease, and depression partially mediated this association, with depression accounting for the largest share (33.6%). CONCLUSIONS:Unfavorable social determinants of health was associated with an increased dementia risk, even in low genetic risk individuals, partly through chronic conditions. Modifying unfavorable social determinants of health may help reduce dementia risk in all populations.

OBJECTIVES:Serum 25-hydroxyvitamin D concentrations have been associated with the risk of dementia, but the results are inconsistent. Previous studies have reported that vitamin D metabolism is related to sleep characteristics. We investigated the association between serum 25-hydroxyvitamin D concentrations and the risk of dementia, as well as whether sleep characteristics and sleep patterns modified this association. STUDY DESIGN:In this prospective population-based cohort study, serum 25-hydroxyvitamin D concentrations were measured. Sleep characteristics, including sleep duration, chronotype, sleeplessness, snoring, and daytime sleepiness, were integrated to generate an overall sleep pattern. We used a multivariable adjusted Cox proportional hazards regression model to evaluate the association of serum 25-hydroxyvitamin D concentrations with the risk of incident dementia. RESULTS:Over a median follow-up of 13.7 years, there were 7030 cases of all-cause dementia, including 3089 of Alzheimer's disease and 1539 of vascular dementia in the cohort of 366,160 participants. Higher concentrations of serum 25-hydroxyvitamin D were associated with a lower risk of all-cause dementia, Alzheimer's disease and vascular dementia. We found a statistically significant interaction of modest magnitude between serum 25-hydroxyvitamin D concentrations and sleep patterns with the risk of vascular dementia (P interaction = 0.04). Among the sleep characteristics, an interaction was found between serum 25-hydroxyvitamin D concentrations and daytime sleepiness in their effect on the risk of vascular dementia (P interaction = 0.03). The protective hazard ratios for vascular dementia were more pronounced in individuals with low daytime sleepiness than in those with high daytime sleepiness. CONCLUSIONS:Serum 25-hydroxyvitamin D concentrations were inversely associated with the risks of all-cause dementia, Alzheimer's disease and vascular dementia. Sleep characteristics, particularly daytime sleepiness, may modify the association between serum 25-hydroxyvitamin D concentrations and the risk of vascular dementia.

With the rapid aging of China's population, the number of adults aged ≥ 80 years is rising, and their nutritional status and weight management have attracted growing attention. Body mass index (BMI) is a commonly used indicator for assessing body weight and nutritional status. However, existing BMI standards were mainly developed for the general adult population, and their applicability to the oldest old population remains uncertain. To provide guidance for BMI evaluation and weight management among the oldest old population in China, the National Health Commission issued the standard " Appropriate body mass index range and weight management standards for the oldest old (WS/T 868-2025)". Based on evidence from prospective cohort studies including the Chinese Longitudinal Healthy Longevity Survey and the Healthy Aging and Biomarkers Cohort Study, the standard recommends an appropriate BMI range of 22.0-26.9 kg/m 2 for adults aged ≥ 80 years and provides recommendations regarding BMI measurement, weight monitoring, and individualized weight management. The implementation of this standard provides scientific evidence for weight evaluation and health management in the oldest old population and contributes to promoting healthy aging.

Purpose Blood homocysteine (Hcy) levels have become a sensitive predictor of the development of cardiovascular disease. Few studies have reported the relationship between plasma vitamin E and Hcy. We aim to conduct an age- and sex-stratified investigation of the association between vitamin E status and Hcy levels in a large nationwide sample in China. Methods We conducted a cross-sectional study including 15,842 Chinese adults. The exposure variable was plasma vitamin E. The outcome variables included homocysteine level and hyperhomocysteinemia. Multiple linear models and multivariable logistic regression were performed to evaluate the relation between plasma vitamin E and homocysteine. Restricted cubic spline was conducted to examine the non-linear relationship. Results In men, the association between plasma vitamin E and homocysteine level followed a U-shape ( p for nonlinearity < 0.001). Compared with plasma vitamin E value of 8.5 ~ 15.9 ug/ml, the risk of hyperhomocysteinemia increased for values lower than 8.5 ug/ml (OR: 1.33 (1.10,1.60), p = 0.002) or higher than 15.9 ug/ml (OR: 1.77 (1.25, 2.50), p = 0.001) in < 65 year-old adults. In men ≥ 65 years old, participants with plasma vitamin E less than 8.3 ug/ml had no significantly associated with hyperhomocysteinemia (OR: 1.22 (1.04,1.43), p = 0.015). Among women, however, no nonlinear relationship was found regardless of age. ( p for nonlinearity > 0.05), the dose-response relationship between vitamin E and homocysteine showed an L-shape. Conclusions Sex-specific associations between plasma vitamin E and homocysteine levels or hyperhomocysteinemia were found. The relationship was U-shaped in men and L-shaped in women. In contrast to the differences observed between sexes, the association between vitamin Eand homocysteine remained consistent across age groups.