Background: The mental health impact of the COVID-19 pandemic is well documented. However, only a few studies investigated mental health in later phases of the pandemic and after its official end. Moreover, little is known about people's psychological burden related to the pandemic and other global crises post-pandemic.Objective: Study's first objective was to compare mental health outcomes in the general population over the course of the pandemic and ten months post-pandemic. The second objective was to explore people's psychological burden regarding the pandemic, in comparison to current wars, climate crises, inflation, and poor government management and/or corruption in the post-pandemic era.Method: Participants from the general population of Austria, Croatia, Germany, Greece, and Portugal (68.8% female, Mage = 41.55) were assessed online up to four times between June 2020 and March 2024 (baseline sample: N = 7913). Adjustment Disorder New Module - 8 (ADNM-8), Patient Health Questionnaire (PHQ-2), and World Health Organization-Five Well-Being Index (WHO-5) were used to measure adjustment disorder, depression, and well-being. Prevalence rates were calculated and repeated measures ANOVAs applied to assess mental health at four time points. One-way repeated measures ANOVA was run to explore how the different global crises were related to participants' burden.Results: Temporal variations in mental health were evident across four assessment waves, with highest levels of probable adjustment disorder and depression in winter 2020/2021 (T2). A slight improvement of mental health was found at later time points. Current wars and inflation were the greatest sources of psychological burden at the post-pandemic assessment, revealing some cross-country differences.Conclusion: Although mental health differences in the general population were not as pronounced as in the acute phase of the pandemic, psychosocial support is still needed post-pandemic. This is likely to be due to other global crises that take a toll on people's mental health.

Depression and social isolation are significant public health issues worldwide, characterized by a bidirectional relationship between the two. This study aims to evaluate the combined effects of depression and social isolation on cardiovascular disease (CVD) and mortality, as well as to assess the mediating role of cardiometabolic diseases in these associations.

This nationwide prospective cohort study utilized data from the China Health and Retirement Longitudinal Study. Depression was assessed using the 10-item Center for Epidemiologic Studies Depression Scale, while social isolation was measured using 4 dichotomized indicators. The outcomes were CVD and all-cause mortality. Logistic regression models and mediation analyses were conducted, and population attributable fractions (PAFs) were calculated.

8567 participants were included in the study, with a mean age of 59.2 (±10.0) years and 48.7 % being men. Among the participants, 5773 (67.4 %) reported neither depression nor social isolation, 1143 (13.3 %) had depression only, 1190 (13.9 %) experienced social isolation only, and 461 (5.4 %) had both depression and social isolation. Individuals with both conditions exhibited the highest odds of CVD (odds ratio (OR): 1.61; 95 % confidence interval (CI): 1.27, 2.04) and mortality (OR: 1.61; 95 % CI: 1.22, 2.12) (p for trend across groups <0.001). The estimated PAFs indicated that a significant number of CVD and mortality events could potentially be prevented by addressing depression and social isolation. Mediator analyses revealed significant indirect effects of hypertension and suboptimal BMI on the relationships between depression, social isolation, and the incidence of CVD and mortality.

Depression, social isolation, and outcomes were self-reported.

A significant combined effect of depression and social isolation on CVD and all-cause mortality was observed among middle-aged and older Chinese adults, underscoring the importance of preventing and managing depression and social isolation to alleviate the burden of CVD.

Traffic crash analyses are frequently challenged by incomplete documentation, particularly in standardised multi-party crash full records. Traditional imputation methods like MICE and KNN, while effective for single-category analyses, fail to address the complex interdependencies inherent in standardised crash records where different types of road user are present. This study introduces a novel graph-based imputation framework that integrates an Inexact Match Bipartite-Graph with Contrastive Learning in a Transformer-GNN architecture, providing a unified solution to handle missing data of various crash types in a complete crash record database. Testing on UK traffic crash records (2018-2022) demonstrates the robust performance of the imputation model, achieving imputation accuracy between 99.24% and 94.74% across missing data rates from 10% to 70%. In the downstream task of classifying the severity of the injury, our imputed data set proved to be highly reliable, achieving a Gmean score of 62.19% to identify levels of imbalanced severity, even under severe missing with a missing rate of 70%. Furthermore, explainable SHAP values demonstrated that data imputation preserved the most important contributing factors. These results validate our framework's effectiveness in maintaining both data integrity and essential relationship structures in standardised crash records, advancing the field of traffic safety analysis through improved imputation methodology.

There is increasing recognition that the pathophysiology of coronary microvascular dysfunction (CMD) plays a pivotal role in the development of heart failure with preserved ejection fraction (HFpEF). However, the mechanisms underlying this role are not known.

The Women's Ischemia Syndrome Evaluation Mechanisms of Coronary Microvascular Dysfunction Leading to Pre-Heart Failure With Preserved Ejection Fraction (WISE Pre-HFpEF) is a prospective cohort study enrolling 180 women and men undergoing clinically indicated invasive coronary angiography for suspected ischemia with no obstructive coronary artery disease. The study aims to investigate (1) CMD-related ischemia contribution to myocellular damage and impaired left ventricular (LV) relaxation as determined invasively by ultra-high sensitivity cardiac troponin I (u-hs-cTnI) measurements in the coronary sinus/great cardiac vein and LV pressure-volume loops, respectively, during provocative stress testing with isometric handgrip, and (2) CMD-related ischemic myocellular damage contribution to LV diastolic dysfunction progression as assessed using cardiac magnetic resonance imaging obtained at enrollment and 1-2 years later, along with prospectively repeated ambulatory u-hs-cTnI measurements.

The WISE pre-HFpEF study is designed to investigate whether ischemic myocardial damage secondary to CMD contributes to the progression of LV diastolic dysfunction. The findings from this study will provide new understanding of the role of CMD in HFpEF development as well as the potential benefits of CMD-directed therapies for the prevention and treatment of HFpEF.

ClilicalTrial.gov, NCT03876223.

Given evidence on the cardiovascular disease (CVD) risk conferred by comorbidity risk factors, the American Heart Association (AHA) recently introduced a novel staging construct, named cardiovascular-kidney-metabolic (CKM) syndrome. This study examined the association of CKM syndrome stages with all-cause and cardiovascular mortality among US adults.

Data were from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 at baseline linked to the 2019 National Death Index records. For each participant, the CKM syndrome was classified into five stages: stage 0 (no CKM risk factors), 1 (excess or dysfunctional adiposity), 2 (metabolic risk factors and chronic kidney disease), 3 (subclinical CVD), or 4 (clinical CVD). The main outcomes were all-cause and cardiovascular mortality.

Among 34,809 participants (mean age: 46.7 years; male: 49.2 %), the prevalence of CKM stages 0 to 4 was 13.2 %, 20.8 %, 53.1 %, 5.0 %, and 7.8 %, respectively. During a median follow-up of 8.3 years, compared to participants with CKM stage 0, those with higher stages had increased risks of all-cause mortality (stage 2: HR 1.43, 95 % 1.13-1.80; stage 3, HR 2.75, 95 % CI 2.12-3.57; stage 4, HR 3.02, 95 % CI 2.35-3.89). The corresponding hazard ratios (95 % confidence interval) of cardiovascular mortality risks were 2.96 (1.39-6.30), 7.60 (3.50-16.5), and 10.5 (5.01-22.2). The population-attributable fractions for advanced (stages 3 or 4) vs. CKM syndrome stages (stages 0, 1, or 2) were 25.3 % for all-cause mortality and 45.3 % for cardiovascular mortality.

Higher CKM syndrome stages were associated with increased risks of all-cause and cardiovascular mortality. These findings emphasize that primordial and primary prevention efforts on promoting CKM health should be strengthened to reduce mortality risk.

Lithology classification is crucial for efficient and sustainable resource exploration in the oil and gas industry. Missing values in well-log data, such as Gamma Ray (GR), Neutron Porosity (NPHI), Bulk Density (RHOB), Deep Resistivity (RS), Delta Time Compressional (DTCO), Delta Time Shear (DTSM), and Resistivity Deep (RD), significantly affect machine learning classification accuracy. This study applied three algorithms, extreme gradient boosting (XGBoost), K-nearest neighbours (KNN), and the artificial neural network (ANN), to handle missing values in well-log datasets, particularly datasets with extreme missing data (30 %). Results indicated that XGBoost was the most efficient and accurate, especially for RHOB, NPHI, DTCO, and DTSM, with the lowest Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The ANN also performed effectively, particularly on the GR, RS, and RD features, after the use of preprocessing techniques such as isolation forest and bias correction. However, the ANN can suffer from overfitting and requires large datasets for optimal performance. In contrast, KNN struggled with missing-not-at-random (MNAR) data due to its reliance on the k parameter and distance metric, making it less effective in mapping missing data relationships.•Missing values in well-log data can hinder lithology classification accuracy for efficient resource exploration in the oil and gas industry.•This research aims to address the problem of missing values in well-log datasets by applying machine learning algorithms such as XGBoost, ANN, and KNN to enhance classification performance.•XGBoost demonstrated superior performance in handling extreme missing data (30 %) in well-log datasets. ANN was effective but prone to overfitting for small datasets, while KNN struggled with missing-not-at-random (MNAR) data due to limitations in its distance-based approach.

Prenatal PFAS exposure and maternal psychological distress may adversely affect child neurodevelopment through shared biological pathways, such as hypothalamic-pituitary-adrenal (HPA) axis disruption and pro-inflammatory responses. However, whether psychological distress modifies PFAS-related neurodevelopmental risks remains unclear. Using data from the Shanghai Birth Cohort including 1779 mother-child pairs, we measured maternal PFAS levels during the first trimester and assessed maternal psychological distress (perceived stress, depression, and anxiety) during the second trimester. Child neurodevelopment was evaluated at 6 months of age using the Ages & Stages Questionnaires-Third Edition (ASQ-3). Multivariable regression models and quantile g-computation were conducted to evaluate the associations of ASQ-3 scores with individual and mixture PFAS. Stratified analyses were conducted between the psychological distress positive group (experienced any one type of stressor) and negative group (experienced no stressors). We found that 41 % of pregnant women experienced at least one type of psychological distress. Among the overall participants, maternal PFAS exposure was associated with reduced gross motor scores in children. Maternal psychological distress status modified the association between PFAS and gross motor scores. Specifically, the adverse associations of PFAS with gross motor development were only observed in the psychological distress positive group, while no association was found in the negative group. Significant interaction effects were observed between maternal psychological distress and most PFAS compounds (all P for interaction <0.1). Furthermore, the adverse associations of prenatal PFAS exposure with gross motor development intensified in women experiencing multiple types of psychological stressors. This study indicates that maternal psychological distress may increase the risk of PFAS-related adverse gross motor development in six-month-old children. Investigating maternal psychological distress could be crucial for identifying vulnerable populations and guiding intervention measures.

Prediction models can be used as simple evidence-based tools to identify fetuses at risk of perinatal death. Payne et al developed a prognostic model for perinatal death in women with hypertensive disorders of pregnancy, a leading cause of maternal/fetal morbidity and mortality.

This study aimed to externally validate the predictive performance of this model in pregnant women with hypertensive disorders of pregnancy admitted between 26 and 34 weeks of gestation in Ghana.

The perinatal model was applied in the SPOT (Severe Pre-eclampsia adverse Outcome Triage) study, a cohort of women with hypertensive disorders of pregnancy admitted between 26 and 34 weeks of gestation to referral facilities in Ghana. Predictive performance was assessed by calibration (calibration-in-the-large coefficient and calibration slope) and discrimination (based on the c-statistic).

Of the 543 women included in the validation analysis, 87 (16%) experienced perinatal death from delivery until hospital discharge. Predictive performance of the model was poor. The calibration-in-the-large coefficient was 1.12 (95% confidence interval, 0.87-1.36, 0 for good calibration), calibration slope was 0.08 (95% confidence interval, -0.21 to 0.36, 1 for good calibration), and c-statistic was 0.52 (95% confidence interval, 0.44-0.59).

This perinatal prediction model performed poorly in this cohort in Ghana. Possible reasons include differences in case mix, clinical management strategies, or data collection procedures between development and validation settings; suboptimal modeling strategies at development; or omission of important predictors. Given the burden of perinatal mortality and importance of risk stratification, new prediction model development and validation is recommended.

Lifestyle changes can effectively prevent diabetes onset in individuals with prediabetes. Although nurse-led interventions have proven to be cost-effective and feasible in the management of diabetes and hypertension in primary care, low-intensity lifestyle interventions for people with prediabetes led by nurses remain poorly evaluated.

To assess whether a low-intensity nurse-led telephone lifestyle intervention is effective in reducing fasting plasma glucose levels in individuals with prediabetes.

A two-arm, parallel, randomized controlled clinical.

Five Primary Care Centres in the Balearic Islands, Spain.

A total of 206 participants were enrolled, 103 in each group.

Consenting participants aged 25-75 years, with fasting plasma glucose levels of 100-125 mg/dL, and body mass index ≥27 and < 40 kg/m2 were randomly assigned (1:1) to either a 9-month nurse-led telephone lifestyle intervention (intervention) or short text messages with general lifestyle advice (control). Research staff and the statistician were masked to group allocation. The primary outcome was fasting plasma glucose at 9-month follow-up, analyzed per protocol and by intention-to-treat.

Among the 206 participants (103 in each group), 189 (91·8 %; n = 91 in the intervention group, n = 98 in the control group) completed the 4-month follow-up and 181 (87·9 %; n = 87 in the intervention group, n = 94 in the control group) completed the 9-month follow-up. Among the 206 randomized participants, 52.9 % were women, 73.8 % were obese, and 69.4 % were of Spanish nationality. Differences in fasting plasma glucose between groups at 9-months were not statistically significant (Intervention group n = 85 mean 103·4 mg/dL [SD 9·6] vs Control group n = 91 mean 104·8 mg/dL [SD 9·7]; adjusted mean difference 1·1 mg/dL [95 % CI -1·6 to 3·8]; p-value = 0·43). Difference in waist circumference at 9 months were statistically significant (Intervention group n = 85 mean 100.6 cm [SD 10.2] vs Control group n = 91 mean 104.0 cm [SD 10.2]; adjusted mean difference 1.9 cm [95 % CI 0.6 to 3.3]; p-value <0.01). At 9-month follow-up, diet quality improved in the intervention group (intervention group n = 86 mean 8.4 points [SD 2.0] vs control group n = 93 mean 7.5 points [SD 2.1], adjusted mean difference - 1.3 points [95 CI -1.7 to -0.7]; p-value <0.01). Likewise, sedentary behavior presented statistically significant differences at 9-month follow-up (intervention group n = 86 mean 5.4 H/d [SD 1.8] vs control group n = 93 mean 6.3 H/d [SD 1.9], adjusted mean difference 1.0 H/d [95 CI 0.5 to 1.4]; p-value <0.01).

These results do not support the effectiveness of a low-intensity nurse-led telephone lifestyle intervention in reducing fasting plasma glucose in individuals with prediabetes, although changes in diet quality and sedentary behavior were observed.

https://clinicaltrials.gov/study/NCT04735640?term=prediphone&rank=1NCT04735640. Registered 03/02/2021, first recruitment 13/04/2021.

A nurse-led phone intervention had no significant benefits on glucose levels in patients with prediabetes. @GlobalHealth_rg.

Given the paucity of age-specific data about biology, presentation, and treatment outcomes in adults with MZL, we sought to evaluate differences between younger (≤ 70 years) and older (> 70 years) patients with MZL in a large retrospective cohort treated in the contemporary era (2010 onwards). The primary objective was progression-free survival (PFS), while secondary objectives included the evaluation of overall survival (OS) and the cumulative incidence of transformation between the 2 groups. A total of 598 patients were included in the analysis and among these 32% were > 70 years of age. There were no age-based differences in the prevalence of NMZL, SMZL, and EMZL. Older patients had a higher incidence of adverse prognostic features at diagnosis such as worse performance status, advanced stage disease, and bone marrow involvement, yet were more likely to be treated with single-agent rituximab than chemoimmunotherapy. Age > 70 years was associated with inferior PFS and OS after controlling for clinically relevant risk factors and accounting for differences in first-line treatment. Receipt of rituximab monotherapy was associated with significantly inferior PFS overall, however, the type of first-line therapy did not impact OS in any group. Our data suggests that despite the development of new drugs for MZL, age remains an independent predictor of inferior outcomes. Investigation of targeted therapy combinations in the first-line setting may yield the required balance of efficacy and toxicity in older adults with MZL.

Mid-life vascular risk factors predict late-life cerebrovascular diseases and poor global brain health. Although endothelial dysfunction is hypothesized to contribute to this process, evidence of impaired neurovascular function in early stages remains limited. In this cross-sectional study of 31,934 middle-aged individuals from UK Biobank without established cerebrovascular disease, the overall 10-year risk of cardiovascular events was associated with reduced neurovascular coupling (p < 2 × 10-16) during a visual task with functional MRI, including in participants with no clinically apparent brain injury on MRI. Diabetes, smoking, waist-hip ratio, and hypertension were each strongly associated with decreased neurovascular coupling with the strongest relationships for diabetes and smoking, whilst in older adults there was an inverted U-shaped relationship with DBP, peaking at 70-80 mmHg DBP. These findings indicate that mid-life vascular risk factors are associated with impaired cerebral endothelial-dependent neurovascular function in the absence of overt brain injury. Neurovascular dysfunction, measured by neurovascular coupling, may play a role in the development of late-life cerebrovascular disease, underscoring the need for further longitudinal studies to explore its potential as a mediator of long-term cerebrovascular risk.

This study investigates the association between changes in TyG-BMI and the risk of diabetes mellitus (DM) in middle-aged and elderly adults in China, as prior research has mainly focused on single baseline measurements.

Data were obtained from CHARLS, a nationwide prospective cohort study. TyG-BMI changes (2011-2015) were analyzed using K-means clustering. Cox proportional hazards regression models assessed the relationship between TyG-BMI changes, cumulative TyG-BMI, and DM risk, with sensitivity and subgroup analyses ensuring robustness.

Compared to individuals with consistently low TyG-BMI (class 1), hazard ratios (HRs) for DM were 1.474, 2.250, and 3.142 for participants with moderately sustained and slowly increasing TyG-BMI (class 2), slowly increasing high level of TyG-BMI (class 3), and the highest and increasing TyG-BMI levels (class 4), respectively. △TyG-BMI2015-2011 (per 10-unit) yielded HRs of 1.064 for class 2, 1.108 for class 3, and 1.079 for class 4. Cumulative TyG-BMI (per 10-unit) had an HR of 1.029.

TyG-BMI changes and sustained exposure to high TyG-BMI levels are independently linked to increased DM risk. Monitoring long-term fluctuations in TyG-BMI could be an important strategy for preventing DM, and effectively controlling high TyG-BMI through various interventions may significantly reduce DM risk.

Earlier feeding practices may influence dietary preference. We evaluated if age of introduction to select complementary foods shape intake and diet quality as measured by the Youth Healthy Eating Index (YHEI) in childhood.

Parents from the Upstate KIDS cohort reported complementary food introduction of 4-12-month-old infants on food questionnaires. Children with information on infant feeding and diet at 30-36 m (n = 2826) and 7-9 years of age (n = 1449) were included. Associations of age of complementary food introduction with intake in childhood were modeled with Poisson regression and diet quality score with linear models, adjusting for sociodemographic factors.

Approximately 84 % (n = 2383) of mothers were non-Hispanic White and about 19 % (n = 526) of children were twins. At 30-36 months, compared to introducing fruits and vegetables between 5 and 8 months, introducing later was associated with 13 % lower daily intake of fruits and vegetables (aRR, 0.87; 95 %CI: 0.79, 0.95); while dairy and grains were associated with a 10 % and 17 % lower intake, respectively. Later introduction of protein was associated with 6 % (aRR, 0.94; 95 %CI: 0.90, 0.98) lower intake. For diet quality, introducing fruits and vegetables later (adjusted B: -4.01; 95 %CI: -7.42, -0.60) was associated with lower diet quality relative to 5-8 m. Later (adjusted B: -1.98; 95 %CI: -3.21, -0.74) introduction to dairy was associated with lower diet quality.

Timing of select complementary foods was associated with lower subsequent intake and lower diet quality in childhood. Further research is needed to evaluate feeding practices that may affect food preferences during infancy as a way to impact healthy dietary patterns and diet quality.

To examine the prospective association between psychological well-being related measures and severe obesity development in young and middle-aged UK adults.

A longitudinal analysis of two cohort studies.

We used data from the 1958 National Child Development Study (NCDS) and the 1970 British Cohort Study (BCS) to examine the association between baseline psychological well-being related measures (depressive symptoms, life satisfaction and self-efficacy) and severe obesity development (defined as body mass index - BMI ≥35 kg/m2) and residualized BMI change scores at follow-up. We analysed repeated measures of baseline and follow-up pairs with 6- to 7-year follow-up on average (n = 22,390 and 23,811 observations in NCDS and BCS, respectively) using panel data logistic and linear models controlling for sociodemographic factors. We conducted additional analyses using analytical sample sizes with longer follow-up (16-17 years).

Although a range of sociodemographic factors (e.g., being female, non-married) were associated with increased risk of severe obesity development, we found limited evidence that psychological well-being related measures were associated with severe obesity development across cohorts and pooled analyses. Depressive symptoms, life satisfaction and self-efficacy were, however, associated with relatively small changes in continuous BMI change across analyses, and this tended to be limited to participants without obesity (BMI 18.5 to <30 kg/m2) and not those already living with obesity (BMI 30 to <35 kg/m2) at baseline.

There is limited evidence that psychological well-being related measures prospectively predict the development of severe obesity. Poorer psychological well-being is associated with modest changes in body weight in individuals without obesity.

Early-life exposure to endocrine-disrupting chemicals, such as phenols and phthalates, is suspected to impact various dimensions of child health. Using a multi-outcome approach, this study aimed to estimate their cumulative effect on the child cardiometabolic, respiratory and neurodevelopmental health.

In 373 children of 3 years old from the SEPAGES cohort, a multi-domain health score was built from twenty-three health parameters. Fourteen metabolites of parabens, phenols, and phthalate/DINCH were measured several times during pregnancy (trimester 2 and 3) and infancy (2 and 12 months of age). Two mixture models, quantile g computation (q-gcomp) and Bayesian Kernel Machine Regression (BKMR), estimated associations between increased concentration of parabens, phenols, and phthalates/DINCH and the child health score.

Q-gcomp showed that the paraben mixture and the phthalate mixture were associated with a poorer health score (β = -0.11, 95% Confidence Interval (CI): -0.22, 0.00; β = -0.14, 95% CI: -0.27, -0.01, respectively), while no significant association was found for the mixture of phenols (β = -0.06, 95% CI: -0.18, 0.06). A trend for an association was observed between the whole mixture (parabens, phenols and phthalates combined) with a poorer health score (β = -0.14, 95% CI: -0.32, 0.04). Similar patterns of association, while subject to large uncertainty, have been observed with BKMR.

This study provides further evidence for the adverse health effects of early-life exposure to parabens and phthalates. Based on their potential impact on multiple areas of child health, public health policies targeting these chemical compounds are recommended.

Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.

Recent research suggests that bullying victimization increases the risk of handgun carrying among adolescents. Yet, little to no research has considered whether different types of bullying victimization (i.e., physical, verbal, cyber) shape handgun-carrying behaviors among youth. Understanding these relationships can, however, inform intervention efforts addressing youths' access to and motives for carrying handguns. The purposes of this study are twofold. First, we establish whether there is a relationship between bullying victimization and youth handgun carrying. Second, we seek to determine whether certain types of bullying victimization are associated more strongly with handgun carrying than others, using data from the 2022 Florida Youth Substance Abuse Survey (FYSAS, n = 47,572), a statewide representative sample of Florida middle school and high school students. The results from multinomial regression models indicate that physical bullying and cyberbullying victimization were associated with an elevated risk of carrying a handgun in the past 12 months. Interventions that underscore the importance of comprehensive anti-bullying interventions that not only address traditional physical aggression among adolescents but also mitigate the evolving challenges posed by unsupervised digital spaces may reduce the risk of handgun carrying.

Diabetes is associated with an increased risk of dementia, but it is still debated to which degree this risk depends on the presence of atherosclerotic cardiovascular disease (CVD). In this study, we hypothesize that patients with diabetes and coexisting coronary artery disease (CAD), as a marker of systemic atherosclerotic CVD, have a substantially higher risk of developing dementia.

Patients ≥65 years, who underwent coronary angiography, were stratified by diabetes and CAD. Outcomes were all-cause dementia, Alzheimer's dementia, and vascular dementia. We estimated adjusted hazard ratios (aHRs) using patients with neither diabetes nor CAD as a reference. A total of 103 859 patients were included. Of these, 23 189 (22%) had neither diabetes nor CAD, 3876 (4%) had diabetes, 61 020 (59%) had CAD, and 15 774 (15%) had diabetes and CAD. During a median follow-up of 6.3 years, 5592 (5.5%) patients were diagnosed with all-cause dementia. Patients with diabetes and CAD had the highest HR of all-cause dementia [aHR 1.37, 95% confidence interval (CI) 1.24-1.51], including Alzheimer's dementia (aHR 1.41, 95% CI 1.23-1.62) and vascular dementia (aHR 2.03, 95% CI 1.69-2.45). Patients with diabetes alone (aHR 1.14, 95% CI 0.97-1.33) or CAD alone (aHR 1.11, 95% CI 1.03-1.20) had a modestly increased rate of all-cause dementia.

The combination of diabetes and CAD is associated with an increased rate of dementia, in particular vascular dementia, suggesting that the diabetes-related risk of dementia is partly mediated through concomitant atherosclerotic CVD. This underscores the importance of atherosclerotic CVD prevention in diabetic patients to reduce cognitive decline.

Integrated care models enhanced by the clinical decision support system offer innovative approaches to managing the growing global burden of older adult care. However, their efficacy remains uncertain.

This study aimed to evaluate the efficacy of an intelligent and integrated older adult care model, termed the SMART (Sensors and scales [receptor], a Mobile phone autonomous response system [central nervous system in the spinal cord], a Remote cloud management center [central nervous system in the brain], and a Total care system [effector]) system, in improving the quality of life (QOL) for home-dwelling older adults.

In this stratified randomized controlled trial, we consecutively recruited older adults aged 65 years or older from November 1, 2020, to December 31, 2020. Eligible participants were randomly allocated 1:1 to either the SMART group, receiving routine discharge instructions and personalized integrated care interventions across 11 domains (decreased or lost self-care ability, falls, delirium, dysphagia, incontinence, constipation, urinary retention, cognitive decline, depression, impaired skin integrity, and common diseases) generated by the SMART system, or the usual care group, receiving only routine discharge instructions. The intervention lasted for 3 months. The primary end point was the percent change in QOL from baseline to the 3-month follow-up, assessed using the World Health Organization Quality of Life Instrument - Older Adults Module. Secondary end points included functional status at the 3-month follow-up and percent changes in health self-management ability, social support, and confidence in avoiding falling from baseline to the 3-month follow-up. Data were analyzed following the intention-to-treat principle, using covariance or logistic regression models, as appropriate. Subgroup and sensitivity analyses were conducted to assess result consistency and robustness.

In total, 94 participants were recruited, with 48 assigned to the SMART group. The personalized and integrated care by the SMART system significantly improved the QOL among the older adults, with an estimated intervention difference of 11.97% (95% CI 7.2%-16.74%, P<.001), and social support and health self-management ability as well, with estimated intervention differences of 6.75% (95% CI 3.19%-10.3%, P<.001) and 4.95% (95% CI 0.11%-10%, P=.003), respectively, while insignificantly improving in the Modified Falls Efficacy Scale score. Similarly, the SMART system had a 66% reduction in instrumental activities of daily living disability (odds ratio [OR] 0.34, 95% CI 0.11-0.83, P=.02). However, the SMART system did not significantly affect activities of daily living disability or the Modified Falls Efficacy Scale score. The subgroup and sensitivity analyses confirmed the robustness of the findings.

The personalized and integrated older adult care by the SMART system demonstrated significant efficacy in improving QOL, health self-management ability, and social support, while reducing instrumental activities of daily living disability among home-dwelling older adults.

Chinese Clinical Trial Registry ChiCTR-IOR-17010368; https://tinyurl.com/2zax24xr.

Cardiovascular disease (CVD) remains a major global health challenge, particularly affected by glucose metabolism status. However, the relationship between estimated glucose disposal rate (eGDR) and future CVD risk across different glucose metabolism status remains unclear.

We analyzed data from the China Health and Retirement Longitudinal Study (2011-2020) of participants aged ≥ 45 years. The eGDR was calculated using waist circumference, hypertension status, and HbA1c levels. CVD events (stroke or cardiac events) were the outcome. Participants were categorized by glucose metabolism status (normoglycemia, prediabetes, diabetes). Cox proportional hazards models and restricted cubic splines were used to assess associations and potential non-linear relationships.

Among 7,828 participants (52.84% male, mean age 59.01 ± 9.21 years) followed for an average of 8.29 years, 1,944 participants (24.83%) developed CVD. Higher eGDR was inversely associated with CVD risk across all glucose metabolism states. Below the inflection points (11.77, 11.15, and 11.56 mg/kg/min for normoglycemia, prediabetes, and diabetes, respectively), each 1-unit increase in eGDR reduced CVD risk by 14% (HR = 0.86, 95%CI: 0.83-0.89), 10% (HR = 0.90, 95%CI: 0.86-0.93), and 14% (HR = 0.86, 95%CI: 0.81-0.91), respectively.

The eGDR demonstrates a potentially non-linear inverse association with future CVD risk across different glucose metabolism states.

Hearing loss treatment delays cognitive decline in high-risk older adults. The preventive potential of addressing hearing loss on incident dementia in a community-based population of older adults, and whether it varies by method of hearing loss measurement, is unknown.

To calculate the population attributable fraction of incident dementia associated with hearing loss in older adults and to investigate differences by age, sex, self-reported race, and method of hearing loss measurement.

This prospective cohort study was part of the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) and had up to 8 years of follow-up (2011-2019). The 4 ARIC field centers in the study included Jackson, Mississippi; Forsyth County, North Carolina; the Minneapolis suburbs, Minnesota; and Washington County, Maryland. Community-dwelling older adults aged 66 to 90 years without dementia at baseline who underwent a hearing assessment at ARIC-NCS visit 6 (2016-2017) were included in the analysis. Data analysis took place between June 2022 and July 2024.

Hearing loss measured objectively (audiometric) and subjectively (self-reported).

The main outcome was incident dementia (standardized algorithmic diagnosis with expert panel review). The population attributable fractions of dementia from both audiometric and self-reported hearing loss were calculated in the same participants, which quantified the maximum proportion of dementia risk in the population that can be attributed to hearing loss.

Among 2946 participants (mean [SD] age, 74.9 [4.6] years; 1751 [59.4] female; 637 Black [21.6%] and 2309 White [78.4%] individuals), 1947 participants (66.1%) had audiometric hearing loss, and 1097 (37.2%) had self-reported hearing loss. The population attributable fraction of dementia from any audiometric hearing loss was 32.0% (95% CI, 11.0%-46.5%). Population attributable fractions were similar by hearing loss severity (mild HL: 16.2% [95% CI, 4.2%-24.2%]; moderate or greater HL: 16.6% [95% CI, 3.9%-24.3%]). Self-reported hearing loss was not associated with an increased risk for dementia, so the population attributable fraction was not quantifiable. Population attributable fractions from audiometric hearing loss were larger among those who were 75 years and older (30.5% [95% CI, -5.8% to 53.1%]), female (30.8% [95% CI, 5.9%-47.1%]), and White (27.8% [95% CI, -6.0% to 49.8%]), relative to those who were younger than 75 years, male, and Black.

This cohort study suggests that treating hearing loss might delay dementia for a large number of older adults. Public health interventions targeting clinically significant audiometric hearing loss might have broad benefits for dementia prevention. Future research quantifying population attributable fractions should carefully consider which measures are used to define hearing loss, as self-reporting may underestimate hearing-associated dementia risk.

Socioemotional competencies (SEC) such as prosocial behaviour and emotion regulation are important for successful social interactions and develop early in life. A high moral self-concept (MSC), that is, children's view of themselves as moral actors, can support the development and application of SEC. The transition from kindergarten to school represents a critical period requiring well-adjusted SEC and MSC, yet research on this phase remains limited. This longitudinal study assessed data of 500 German children (Mage_t1 = 60.97 months) and their teachers to examine the relation and stability of SEC and MSC over two years. After imputing data via multivariate imputation by chained equations due to missing ratings in teacher surveys, cross-lagged relations indicate that a stronger MSC in the last year of kindergarten can lead to greater SEC, which in turn can predict later MSC at the end of Grade 1. Both constructs showed stability over time, with significant correlations between SEC and MSC emerging only in primary school. Gender and socioeconomic differences for SEC and MSC were also observed. These findings enhance our understanding of the interplay between SEC and MSC and their development during the school transition.

The associations between systemic inflammation biomarkers and cardiovascular disease (CVD) remain not well explored. This study aimed to investigate associations between different systemic inflammation biomarkers and incident CVD and main CVD subtypes - ischaemic heart disease (IHD), stroke, and heart failure - explore dose-response relationships, and compare their predictive performance.

This prospective cohort study included 423,701 UK Biobank participants free of CVD at baseline. Baseline neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and system inflammation response index (SIRI) were derived. Cox-proportional regression models were used to investigate the associations.

NLR, PLR, SII, and SIRI was positively and LMR was negatively associated with all four of the outcomes investigated. The relationships were non-linear for all biomarkers with CVD and were linear for NLR, SII, and SIRI and non-linear for LMR and PLR with IHD, stroke and heart failure. Compared with the more established biomarkers, all four of the novel biomarkers had statistically superior predictive performance for three of the outcomes investigated (CVD, IHD and heart failure) and three of them were superior at predicting stroke. Compared to a model of CVD prediction with classical risk factors (C-index = 0.702), discrimination was improved on the addition of inflammation markers for CVD (C-index change 0.0069, 95% CI 0.0033 to 0.0107), IHD (C-index change 0.0054, 95% CI 0.0013 to 0.0095), and heart failure (C-index change 0.0153, 95% CI 0.0089 to 0.0218).

There were independent and dose-response relationships between the novel systemic inflammation biomarkers and CVD outcomes. Addition of the inflammation biomarkers including novel inflammation biomarkers showed improved discrimination of the traditional risk prediction model. With accumulated evidence, these biomarkers should be considered for inclusion in risk tools and prevention.

Frailty and social contact are significant factors influencing dementia risk. While previous studies have separately examined these factors, their combined impact on dementia remains underexplored.

This study included 338,567 UK biobank participants from 2006 to 2010, with follow-up until December 2022. Additionally, 30,408 participants with brain magnetic resonance imaging data were analyzed for hippocampal volume. Cox proportional hazards regression and linear regression models were used to assess associations.

The study followed 338,567 participants (mean [SD] age, 60.4 [5.2] years; 54.1 % men) for a median of 13.7 years, documenting 7362 cases of all-cause dementia. Both frailty and lower social contact independently increased the risk of all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD). Compared to individuals with non-frailty and high social contact, those with lower social contact and higher frailty had a significantly increased risk of all-cause dementia, with the highest risk observed in individuals with frailty and low social contact (HR = 2.65, 95 % CI: 2.27-3.11). Similar patterns were found for AD and VaD. Furthermore, hippocampal volume was significantly reduced in individuals with frailty and low social contact (β = -0.24, 95 % CI: -0.43 to -0.06) compared to those with non-frailty and high social contact.

The study predominantly included European descent individuals, with most frailty and social contact data based on baseline self-reports.

The combination of frailty and low social contact is associated with the highest risk of dementia. These findings suggest that both physiological and social factors should be simultaneously considered in dementia prevention strategies.

Low Apgar scores have been associated with an increased risk of brain injury and neurodevelopmental disorders in newborns with congenital heart defects (CHDs). However, the relation between CHD subtypes and low Apgar scores remains unknown. This study aimed to assess the association between major subtypes of CHD and low (<7) Apgar scores at 5 minutes.

This population-based study included 1 040 474 liveborn singletons in Denmark from 1997 to 2013. The association between CHD and low Apgar scores was estimated by confounder-adjusted, multivariable logistic regression. In mediation analyses, the underlying mechanisms were examined. Low Apgar scores were present in 3.0% of newborns with CHD and in 0.7% of newborns without CHD. Overall, CHD was associated with an increased risk of a low Apgar score (adjusted odds ratio, 2.5 [95% CI, 2.1-3.0]). CHD subtypes associated with the highest risks were anomalous pulmonary venous return (adjusted odds ratio, 5.7 [95% CI, 2.2-14.9]), hypoplastic left heart syndrome (adjusted odds ratio, 5.1 [95% CI, 2.2-11.8]), and transposition of the great arteries (adjusted odds ratio, 3.5 [95% CI, 1.7-7.4]). In mediation analyses, preterm birth explained 25.2% (95% CI, 11.8-38.6) of the association between CHD and low Apgar scores.

Nearly all CHD subtypes were associated with an increased risk of a low Apgar score. The association was most pronounced in severe and potentially cyanotic types of CHD. These findings suggest that CHD is associated with a complicated fetal-to-neonatal transition and highlight the potential for improvements of this process in infants with CHD.

Psychotic symptoms are common in adolescents and predictive of psychiatric disorders. Numerous risk factors have been shown to precede psychiatric disorders. However, investigating individual risk factors does not account for the cumulative effect these risk factors may have. Therefore, we combined well-researched environmental risk factors for psychotic disorder in a composite measure: the poly-environmental risk score (PERS).

Risk factors were assessed in a cohort of 801 adolescents (aged 15) at risk for psychopathology. Binarized risk factors included winter birth, low gestational age, low birth weight, ethnic minority status, urban living environment, cannabis use, victim of bullying, emotional abuse, physical abuse, sexual abuse, high paternal age, parental severe mental illness, parental divorce, and parental death. The PERS was weighted with the log odds derived from recent meta-analyses. At age 18, self-reported psychotic experiences (PE) and clinician-rated psychotic symptoms (PS) were assessed. This updated PERS was compared to previous PERS models, which included fewer risk factors and different weightings.

The PERS was associated with PE and PS. Specifically, a PERS between 3 and 4, and PERS > 4 corresponded with a 2.2- and 5.2-fold increase in the odds of psychotic symptoms in late adolescence. The updated 14-item PERS performed better compared to previous compositions of the PERS.

A composite score of childhood and adolescent risk factors measured at age 15 was associated with psychotic symptoms at age 18. Future research should consider the cumulative effect of risk factors when examining the determinants of psychopathology.

Engagement in positive experiences in everyday life has been associated with better long-term survival, but research assessing associations with other measures of long-term physical health is limited. In the current study, data collected from the Midlife in the US Study (N=1,182) in 2004-2017 were used to examine whether frequency of engagement in a range of positive experiences is associated with three domains of health (subjective, functional, and morbidity) over an average seven-year follow-up period. Potential cognitive-affective and physiological mediators of these associations were assessed. Greater positive experience frequency was associated with better self-rated health (SRH), less difficulty in performing basic activities of daily living (BADLs), and lower comorbidity (count of dichotomous indicators assessing history of lung-related, autoimmune, blood pressure, blood glucose, and neurological disorders). Cognitive-affective factors (positive affect, depression, and perceived stress) mediated the associations with SRH and BADLs. Positive experiences may impact long-term physical health and warrant further study.

The objective of this study was to examine the association of birth by Caesarean section (CS) with female offspring's risk of CS delivery.

We used data from the 3G Multigenerational Cohort, which includes women whose births and their own subsequent pregnancies and deliveries were recorded in the population-based Nova Scotia Atlee Perinatal Database. The current analysis was limited to the women's first delivery (n = 23,605). Confounding variables were identified using a directed acyclic graph. The association between birth by CS and later CS delivery was examined with Poisson regression adjusted for confounding variables.

Seventeen percent of women were born via CS, and 23 % delivered by CS. Compared to women born vaginally, women born by CS had an adjusted relative risk (RR) of 1.36 (95 % confidence interval [CI] 1.30, 1.43) for delivering by CS. Restricting the sample to women born to nulliparous mothers did not change the association (RR 1.35), while restriction to women born out of low-risk pregnancies weakened it slightly (RR 1.25).

Birth by CS is associated with a 36 % increased risk of women delivering their first child by CS. This increase is likely due to shared medical and socio-cultural factors.

While prior literature has documented the impact of housing quality on health, the long-lasting effects of poor housing conditions in adolescence on adult health remain understudied. This study employs an outcome-wide longitudinal approach to estimate the association between poor housing conditions in adolescence and a set of health outcomes in adulthood.

Data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a large-scale, nationally representative sample of US adolescents, were used. This study analysed 15 health outcomes encompassing physical and mental/cognitive health, and health behaviours. The Bonferroni correction was applied to adjust the significance level of multiple testing of the associations.

After applying the Bonferroni correction, poor housing conditions in adolescence were associated with seven adult health outcomes. These conditions were particularly strongly and robustly linked to mental health issues, including depression, suicidal ideation and perceived stress. Additionally, poor housing conditions were related to physical health outcomes such as cardiovascular disease risk and self-rated health, as well as health behaviours such as smoking and unhealthy eating behaviour.

Poor housing conditions during adolescence can act as an early risk factor for adult health, particularly mental health. These findings support the adoption of a life course approach and strengthen the case for housing interventions aimed at improving health outcomes.

To evaluate the cost utility of a 9-month supervised exercise program for patients with metastatic breast cancer (mBC), compared with control (usual care, supplemented with general activity advice and an activity tracker). Evidence on the cost-effectiveness of exercise for patients with mBC is essential for implementation in clinical practice and is currently lacking.

A cost-utility analysis was performed alongside the multinational PREFERABLE-EFFECT randomized controlled trial, conducted in 8 centers across Europe and Australia. Patients with mBC (N = 357) were randomly assigned to either a 9-month, twice-weekly, supervised exercise group (EG) or control group (CG). Costs of the exercise program were calculated through a bottom-up approach. Other health care resource use, productivity losses, and quality of life were collected using country-adapted, self-reported questionnaires. Analyses were conducted from a societal perspective with a time horizon of 9 months. Costs were collected and reported in 2021 Euros (€1 = $1.18 US dollars).

Compared with the CG, EG resulted in a quality-adjusted life-year (QALY) gain of 0.013 (95% CI, -0.02 to 0.05) over a 9-month period. The mean costs of the exercise program were €1,696 per patient with one-on-one supervision (scenario 1) and €609 with one-on-four supervision (scenario 2). These costs were offset by savings in health care and productivity costs, resulting in mean total cost differences of -€163 (scenario 1) and -€1,249 (scenario 2) in favor of EG. The probability of supervised exercise being cost-effective was 65% in scenario 1 and 91% in scenario 2 at a willingness-to-pay threshold of €20,000 per QALY.

Exercise for patients with mBC increases quality of life, decreases costs, and is likely to be cost-effective. Group-based supervision is expected to have even higher cost-savings. Our positive findings can inform reimbursement of supervised exercise interventions for patients with mBC.

Postoperative acute kidney injury (AKI) is a significant risk associated with surgeries under general anesthesia, often leading to increased mortality and morbidity. Existing predictive models for postoperative AKI are usually limited to specific surgical areas or require external validation.

We proposed to build a prediction model for postoperative AKI using several machine learning methods.

We conducted a retrospective cohort analysis of noncardiac surgeries from 2009 to 2019 at seven university hospitals in South Korea. We evaluated six machine learning models: deep neural network, logistic regression, decision tree, random forest, light gradient boosting machine, and naïve Bayes for predicting postoperative AKI, defined as a significant increase in serum creatinine or the initiation of renal replacement therapy within 30 days after surgery. The performance of the models was analyzed using the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, precision, sensitivity (recall), specificity, and F1-score.

Among the 239,267 surgeries analyzed, 7935 cases of postoperative AKI were identified. The models, using 38 preoperative predictors, showed that deep neural network (AUC=0.832), light gradient boosting machine (AUC=0.836), and logistic regression (AUC=0.825) demonstrated superior performance in predicting AKI risk. The deep neural network model was then developed into a user-friendly website for clinical use.

Our study introduces a robust, high-performance AKI risk prediction system that is applicable in clinical settings using preoperative data. This model's integration into a user-friendly website enhances its clinical utility, offering a significant step forward in personalized patient care and risk management.

Currently, benign breast disease (BBD) pathologic classification and invasive breast cancer (BC) risk assessment are based on qualitative epithelial changes, with limited utility for BC risk stratification for women with lower-risk category BBD (i.e., non-proliferative disease, NPD, and proliferative disease without atypia, PDWA). Herein, machine learning-based single-cell morphometry was used to characterize quantitative changes in epithelial nuclear morphology that reflect functional/structural decline (i.e., increasing nuclear size, assessed as epithelial nuclear area and nuclear perimeter), altered DNA chromatin content (i.e., increasing nuclear chromasia), and increased cellular crowding/proliferation (i.e., increasing nuclear contour irregularity). Cytomorphologic changes reflecting chronic stromal inflammation were assessed using stromal cellular density. Data and pathology materials were obtained from a case-control study (n=972) nested within a cohort of 15,395 women diagnosed with BBD at Kaiser Permanente Northwest (1971-2012). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations of cytomorphometric features with risk of subsequent BC were assessed using multivariable logistic regression. Over 55 million epithelial and 37 million stromal cells were profiled across 972 BBD images. Cytomorphometric features were individually predictive of subsequent BC risk, independently of BBD histological classification. However, cytomorphometric features of epithelial functional/structural decline were statistically significantly predictive of low-grade but not high-grade BC following PDWA [OR (95% CI) for low-grade BC per 1-standard deviation (1-SD) increase in nuclear area and nuclear perimeter =2.10 (1.26-3.49) and 2.22 (1.30-3.78), respectively], while stromal inflammation was predictive of high-grade but not low-grade BC following NPD [OR (95% CI) for high-grade BC per 1-SD increase in stromal cellular density =1.53 (1.13-2.08)]. Associations of nuclear chromasia and nuclear contour irregularity with subsequent tumor grade were context specific, with both features predicting low-grade BC risk following PDWA [OR (95% CI) per 1-SD =1.58 (1.06-2.35) and 2.21 (1.25-3.91) for nuclear chromasia and nuclear contour irregularity, respectively] and high-grade BC following NPD [OR (95% CI) per 1-SD =1.47 (1.11-1.96) and 1.29 (1.00-1.70) for nuclear chromasia and nuclear contour irregularity, respectively]. The results indicate that cytomorphometric features on BBD H&E images might help to refine BC risk estimation and potentially inform BC risk reduction strategies for BBD patients, particularly those currently designated as low-risk.

A poor prognosis within 1 year of discharge is important when making decisions affecting postoperative geriatric inpatients. Comprehensive geriatric assessment (CGA) plays an important role in guiding holistic assessment-based interventions. However, current prognostic models derived from CGA and clinical data are limited and have unsatisfactory performance. We aimed to develop an accurate 1-year mortality prediction model for patients discharged from the geriatric ward using CGA and clinical data.

This longitudinal cohort study analysed data from 816 consecutively assessed geriatric patients between January 1, 2018 and December 31, 2019. Models were constructed using Cox proportional hazards regression and their validity was assessed by analysing discrimination, calibration, and decision curves. The robustness of the model was determined using sensitivity analysis. A nomogram was developed to predict the 1-year probability of mortality, and the model was validated using C-statistics, Brier scores, and calibration curves.

During 644 patient-years of follow-up, 57 (11·7%) patients died. Clinical variables included in the final prediction model were activities of daily living, serum albumin level, Charlson Comorbidity Index, FRAIL scale, and Mini-Nutrition Assessment-Short Form scores. A C-statistic value of 0·911, a Brier score of 0·058, and a calibration curve validated the model.

Our risk stratification model can accurately predict prospective mortality risk among patients discharged from the geriatric ward. The functionality of this tool facilitates objective palliative care.

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with potential health risks. While the association between PFAS and dental health is under-researched, this study aims to address this gap by investigating prenatal PFAS exposure in relation to Developmental Defects of Enamel (DDE) and dental caries in children.

This study included 1,136 children from the Shanghai Birth Cohort, with maternal blood samples collected during early pregnancy to measure concentrations of 10 PFAS compounds. Oral health outcomes, assessed when the children were 4 years old, included the prevalence of DDE and dental caries, as well as DDE tooth count and the decayed, missing, and filled teeth (dmft) index. Logistic regression and zero-inflated negative binomial regression were used to examine associations between individual PFAS compounds and oral health outcomes. Restricted Cubic Splines (RCS) were used to explore potential nonlinear associations. Additionally, Bayesian Kernel Machine Regression (BKMR), Weighted Quantile Sum (WQS), and Quantile G-Computation (QGC) were employed to assess the joint effects of PFAS mixtures on the outcomes.

Individual PFAS compounds, particularly perfluorobutane sulfonate (PFBS) and perfluoroheptanoic acid (PFHpA), exhibited heterogeneous associations with DDE prevalence. PFBS was linked to an increased risk of DDE (OR: 1.37; 95%CI: 1.05, 1.80), while PFHpA showed a protective effect (OR: 0.72; 95%CI: 0.54, 0.97). No significant associations were observed between individual PFAS compounds and dental caries outcomes. Additionally, the study found a lack of significant associations between PFAS mixtures and the prevalence of DDE or dental caries, as well as the absence of any marked effects on DDE tooth count or dmft.

Although no overall association was observed between PFAS mixtures and oral health outcomes, certain short-chain PFAS compounds, such as PFBS and PFHpA, demonstrated distinct effects on enamel defects. Further research is warranted to clarify the biological mechanisms underlying these associations and to examine the role of PFAS exposure in other populations.

Children in foster care who have experienced abuse and neglect are at risk of poor long-term health and societal outcomes. Evidence on the costs, benefits and cost-effectiveness of early interventions aimed at improving the mental health of abused and neglected children is limited.

This study reports the within-trial economic evaluation alongside BEST?, a randomized controlled trial comparing the New Orleans Intervention Model (NIM) with services as usual (SAU), targeting children aged 0-60 months entering UK foster care.In line with guidance for conducting economic evaluations of complex and social care interventions, a cost-utility analysis (CUA) estimated incremental cost of NIM per quality-adjusted life year (QALY); a cost-effectiveness analysis estimated incremental cost per unit improvement in child mental health; and a cost-consequence analysis combined costs with broad-ranging outcomes.

NIM is significantly more costly than SAU (NIM: £10 002; SAU: £4336), with wide cost variations according to context. There are no significant differences between NIM and SAU in QALYs or child mental health.

Within the current UK care systems, NIM is not a cost-effective alternative to SAU. However, these results need to be interpreted with caution and within the prevailing service provision context.