To explore the mediating role of DNA methylation (DNAm) in the association between prenatal arsenic exposure and neonatal birth weight, and to identify DNAm-specific sites at different birth weight percentiles.

The data were obtained from the New Hampshire Birth Cohort Study (NHBCS), which included 270 mother-infant pairs. The quantitative correlation-based independent screening (QCSIS) method was combined with marginal quantitative regression analysis to identify DNA methylation (DNAm) sites associated with birth weight. After penalized estimation, the mediating effect analysis method was used to evaluate the mediating role of DNAm loci in the relationship between prenatal arsenic exposure and different birth weight percentiles.

After adjusting for maternal age, pre-pregnancy BMI, and other covariates, a total of 14 cytosine-phosphate-guanine pairs of nucleotides (CpG) sites with significant mediating effects were identified across 8 different birth weight quantiles. The eight birth weight percentiles were roughly divided into three groups: low, normal, and high birth weight, identifying 3, 3, and 8 CpG sites, respectively. The results showed that the cg17524924 site located in the ZNF542 gene significantly mediated the association between arsenic exposure and low birth weight (τ=0.3, ACME: -14.311，P=0.016) and (τ=0.4, ACME: -12.946, P=0.016); while the cg13486410 site located in the NDNF gene exhibited a positive mediating effect (τ=0.7, ACME: 14.041, P=0.030), suggesting that methylation at this site may partially offset the negative impact of prenatal arsenic exposure on neonatal birth weight.

This study finds that placental DNA methylation exerts quantile-specific mediating effects between arsenic exposure and neonatal birth weight. The results provide new insights into the mechanisms by which prenatal arsenic exposure affects fetal growth and development.

To explore the chain mediating role of emotional resilience and experiential avoidance in the relationship between parental psychological aggression and adolescent non-suicidal self-injury (NSSI), with particular attention to potential differences between fathers and mothers.

A cluster sampling method was employed. A total of 1 108 adolescents were surveyed using the Parent-Child Conflict Tactics Scale, Adolescents’ Emotional Resilience Questionnaire, Acceptance and Action Questionnaire-Ⅱ, and Adolescents Self-Harm Scale. Mediating effects were examined using a bias-corrected nonparametric percentile bootstrap method.

The prevalence of NSSI in this sample was 24.64%. In the separate models, both paternal and maternal psychological aggression positively predicted adolescent NSSI. Emotional resilience and experiential avoidance played a chain mediating role between both paternal and maternal psychological aggression and adolescent NSSI. In the integrated model including both paternal and maternal psychological aggression, the direct and indirect effects of maternal psychological aggression on adolescent NSSI remained statistically significant. The direct effect was 0.17(P<0.01), the independent mediating effect of emotional resilience was 0.012 (95% CI: 0.003-0.025), the independent mediating effect of experiential avoidance was 0.019 (95% CI: 0.007-0.038), and the chain mediating effect via emotional resilience and experiential avoidance was 0.015 (95% CI: 0.006-0.028). In contrast, both the direct and indirect effects of paternal psychological aggression on adolescent NSSI were not statistically significant.

Emotional resilience and experiential avoidance play a chain mediating role in the relationship between parental psychological aggression and adolescent NSSI, with maternal psychological aggression playing a dominant role.

To explore the relationship between body weight indicators and the TyG index (triglyceride-glucose index), as well as the combined indicators of these two factors, the triglyceride-glucose-weight index (TyG-BMI) and the triglyceride-glucose-waist circumference index (TyG-WC), and the risk of elevated blood pressure during follow-up among the adolescent population.

Using the convenient sampling method, students from the first, second and first-year senior grades of three schools in Sichuan Province were selected. A follow-up survey was conducted in March 2023, with an average follow-up period of 1.25 years and a dropout rate of 6.75%. The multivariate modified Poisson regression model was used to analyze the relationship between body mass index and TyG index, as well as the mixed indicators of the two (TyG-BMI and TyG-WC) and follow-up high blood pressure. The logistic regression model was used to explore the mediating effect of baseline TyG and follow-up TyG in the relationship between different body weight states and follow-up blood pressure levels.

Among the 812 teenagers who did not have high blood pressure at the baseline, the average age was 14 years old, and 40.30% were male. During the follow-up period, a total of 156 teenagers developed high blood pressure, with an incidence rate of 19.21%. In the multivariate adjusted Poisson regression analysis, both TyG-BMI and TyG-WC showed a positive correlation with elevated blood pressure at the follow-up (TyG-BMI: RR=1.009, P<0.05; TyG-WC: RR=1.004, P<0.05). In the mediating effect model, no mediating effect of baseline and follow-up TyG in the relationship between different weight statuses and follow-up high blood pressure was found.

We found that TyG-BMI and TyG-WC were associated with high blood pressure, but weight status played a key role in it.

To understand the epidemiological characteristics of falls among elderly patients with chronic diseases in the community, analyze the correlation between diabetes and fall outcomes, and provide a basis for identifying key intervention targets, reducing fall incidence, and developing fall intervention strategies.

A total of 1 198 elderly patients aged 60 and above were randomly selected from the chronic disease health management system as study subjects. Univariate and multivariate logistic regression analyses were employed to examine influencing factors of falls, as well as the association with diabetes.

Over the past year, the incidence of falls among elderly patients with chronic diseases was 25.96%, and the proportion of individuals at high risk of falls was 27.30%. Univariate analysis revealed that elderly patients with chronic diseases who had diabetes, poorer self-rated health status and sleep quality, reduced self-care and balance abilities, more severe depression, use of walking aids, a history of fractures, and abnormal gait exhibited significantly higher rates of falls (P<0.05). Multivariable logistic regression analysis showed that type 2 diabetes(OR=1.61, 95% CI: 1.14-2.27) was an independent risk factor for falls in older adults, good balance ability(OR=0.82, 95% CI: 0.75-0.89) was a protective factor(P<0.05), and depression(OR=1.28, 95% CI: 1.06-1.53) and history of previous fracture(OR=1.97, 95% CI: 1.44-2.71) were risk factors.

Elderly patients with diabetes in the community exhibit a higher incidence of falls and a greater proportion of fall risk. They should be paid close attention as a key population and it is essential to incorporate comprehensive assessments into their chronic disease management. Additionally, particular attention must be given to individuals with a history of fractures, impaired balance ability, or depression, through reinforced health education, rehabilitation, and psychological support, to mitigate fall risk ultimately.

To examine the impact of age on low health literacy level among residents in Fuyang District of Hangzhou, and to elucidate its interactive effect with other determinants.

A questionnaire survey was conducted among residents aged 15-69 years old by multi-stage stratified random sampling. Data on basic demographic characteristics and health literacy levels were collected. The associations were examined using the Mann-Whitney U test, Chi-square test, the restricted cubic splines (RCS) model, and multivariable-adjusted logistic regression models.Furthermore, multiplicative and additive interaction models were applied to explore the joint effects of age and other influencing factors on low health literacy.

Among the 640 respondents, 417 (65.16%) had a low health literacy level. After adjusting for potential confounders, the RCS model revealed a significant nonlinear dose-response relationship between age and the risk of low health literacy (P_nonlinear<0.01), with an inflection point at 51 years old. Subsequently, multivariate logistic regression analysis using this cut-off value demonstrated that individuals aged over 51 years old had a significantly higher risk of low health literacy (OR=3.377, 95% CI: 2.120-5.378, P<0.05). Regarding interaction effects, an additive interaction was observed between age and educational level (RERI=9.979, 95% CI: 0.389-19.569; AP=0.606, 95% CI: 0.368-0.843; SI=2.814, 95% CI: 1.442-5.492).

Age is an independent influencing factor of low health literacy levels among residents. Further interaction analysis reveals that individuals with advanced age and low educational attainment are identified as the key target population for health literacy promotion and intervention efforts.

To provide insights for optimizing social participation policies for older adults in China, to introduce a novel analytical perspective to policy research and to explore quantitative approaches to assess policy tools configuration.

Policy documents were collected from the websites of the State Council, the National Health Commission, and the PKULAW database using the literature collection method. The content of elderly policies was quantitatively analyzed using the policy tool classification theory and the PMC index, and the policies were evaluated using the four-quadrant method.

This study selected 17 policy documents as research objects. Specifically, there were 8 policies in Quadrant Ⅰ, 2 policies in Quadrant Ⅱ, 6 policies in Quadrant Ⅲ, and only 1 policy in Quadrant Ⅳ. Among the policy tools involved, there were 53 supply-side policy tools (57.0%), 23 demand-side policy tools (24.7%), and 17 environmental policy tools (18.3%). The average PMC index was 4.57, with the highest score being 7.17 and the lowest score being 2.87.

The structure of policy tools for social participation among older adults in China requires further optimization, with notable shortcomings in policy targeting, content richness, and innovation. The government should focus on refining the policy tool structure, clarifying policy goals, enriching policy content, and enhancing policy innovation to ensure the comprehensive and reasonable development of elderly policies and promote the implementation of the national strategy of active aging.

To analyze the coupling and coordination relationship between the elderly population and the supply of medical resources in Guangdong Province from 2000 to 2020, and to provide insights for optimizing regional medical resource allocation, improving health and well-being among the elderly, and proactively addressing population aging.

Using data from population censuses and statistical yearbooks, the entropy method and the coupling coordination degree model were applied to evaluate the coupling coordination and matching degree of the elderly system and medical resource supply system.

From 2000 to 2020, the matching degrees of the elderly population and medical resource supply in Guangdong Province evolved from mild mismatch to basic match. Spatially, all cities had reached a minimally matched level by 2020, however, significant regional disparities remained. The Pearl River Delta and western Guangdong regions exhibited higher matching degrees than eastern and northern Guangdong.

The matching degree between the elderly population and medical resource supply in Guangdong has improved overall, though regional gaps remain. It is recommended that regions tailor medical resource allocation according to local aging trends, while proactively addressing the structural service needs of the elderly, such as chronic disease management and rehabilitation nursing, to enhance the precision and adaptability of resource matching.

To evaluate the association between a body shape index (ABSI) and all-cause mortality in stroke patients.

Using data from 2005 to 2016 National Health and Nutrition Examination Survey (NHANES) and the National Death Index (NDI). The study involved 1 039 participants after applying exclusion criteria. The participants were divided into 5 groups. Continuous variables were expressed as （）, and the Kruskal-Wallis rank sum test was used. Categorical variables were expressed as n（%）, and Pearson’s χ² was used. Kaplan-Meier survival analysis, cox proportional hazards model and restricted cubic splines were utilized to estimate the association between ABSI and All-cause mortality in stroke patients.

The Kaplan-Meier survival analysis showed that the survival rate of patients with the high ABSI group was significantly lower than that of patients with the low ABSI group before and after weighting. Cox proportional hazards model showed that the high ABSI group(Q5) compared to the lowest quartile (Q1), was associated with a high incidence of all-cause mortality in stroke patients(before-weighting HR=2.41,95% CI:1.69-3.44; after-weighting HR=2.57,95% CI:1.62-4.07) after adjusting for potential confounders. Restricted cubic splines analysis showed that all-cause mortality in stroke patients increased significantly with ABSI exceeded a cutoff. Older adults and males are more susceptible to the ABSI. P<0.05 was considered as the difference was statistically significant.

The high ABSI group (Q5) is associated with a high incidence of all-cause mortality in stroke patients. ABSI is a risk factor for All-cause mortality in stroke patients.

To explore the long-term relationship between digital exclusion and depressive symptoms in middle-aged and older adults in China, to evaluate whether social participation serves as a mediator in this connection, and to guide interventions to reduce depression within this group.

A longitudinal analysis was conducted using data from the 2011-2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). Self-reported data were used to evaluate digital exclusion and social participation, while the presence of depressive symptoms was measured with the 10-item version of the Center for Epidemiologic Studies Depression Scale (CES-D 10). Differences in the incidence of depressive symptoms among groups were assessed using Kaplan-Meier estimates and the log-rank test. Cox proportional hazards models were used to analyze the longitudinal association between digital exclusion and depressive symptoms, and causal mediation analysis was employed to test the mediating effect.

A total of 8 808 participants were included in the study. At baseline, 8 334 (94.6%) individuals were classified as digital exclusion group. Over a median follow-up of 7.00 years, 3 969 participants developed depressive symptoms. The survival analysis revealed that the cumulative incidence of depressive symptoms was significantly higher in the digital exclusion group than that in the digital inclusion group (Log-rank P<0.05). After controlling for confounders, Cox regression analysis showed that digital exclusion remained an independent risk factor for depressive symptoms (HR=1.37, 95% CI: 1.11-1.69). The mediation analysis found that social participation partially mediated the association between digital exclusion and depressive symptoms.

Digital exclusion is associated with an increased　risk of depressive symptoms among middle-aged and older Chinese adults. This association may be partially mediated by social participation. Promoting digital inclusion and encouraging social engagement may be potential strategies for the prevention and intervention of depression in this vulnerable group.

To explore the relationship between social isolation and frailty trajectories, and to provide evidence for targeted interventions and healthy aging.

Based on four waves (2011-2018) of the China Health and Retirement Longitudinal Study, 7 805 adults aged 45 years and above were included. Latent Class Mixed Models (LCMM) wereapplied to identify longitudinal trajectories of social isolation and the frailty index.Multinomial logistic regression was used to analyze factors associated with each trajectory, and conditional and joint probabilities were calculated to evaluate the correspondence between social isolation and frailty trajectories.

Four trajectories of social isolation were identified: Low-isolation stable (36.0%), Low-isolation rapid increase (2.7%), Moderate-isolation stable(52.7%), andHigh-isolation slow increase(8.7%)—along with three frailty trajectories: Robust stable(27.0%), Prefrail stable (54.2%), and Frailty worsening (18.8%).Joint probabilities further indicated that the combination of Moderate-isolation stable and Prefrail-stable had the highest overall probability (π_jk=0.29).

Levels and temporal patterns of social isolation are strongly associated with frailty development. Middle-aged and older adults with higher or increasing isolation levels, as well as those at the prefrail stage, should be prioritized in community-based interventions aimed at strengthening social support, maintaining physical function, and improving psychological well-being to delay frailty progression and promote healthy aging.