To explore the impact of heatwave (HW) exposure on social participation among middle-aged and older adults, and provide empirical evidence for healthy aging intervention strategies under climate change.

Using two waves of data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 and 2018, the association between HW changes and decreased social participation was assessed via the generalized additive model combined with the generalized difference method. HW was defined by a city-specific threshold method: 12 HW definitions were constructed using the 90th, 92.5th, 95th, and 97.5th percentiles of daily maximum temperature as thresholds, combined with durations of ≥2, 3, and 4 days. Social participation was operationalized using social activity level, and sustained decline in social activity level and changes in social activity patterns were defined as different outcomes. Stratified analyses were conducted to examine the interaction effects of PM_2.5 and green space exposure.

In the analysis of sustained decline in social activity level, HW days (HW3: OR=1.130, 95% CI: 1.012-1.262; HW10: OR=1.056, 95% CI: 1.008-1.105) and HW events (HW10: OR=1.091, 95% CI: 1.013-1.175) were associated with sustained decline in social activity level. In the analysis of social activity pattern changes, HW days (HW1) were associated with increased risk of persistent low social activity (OR=1.069, 95% CI: 1.007-1.136). Stratified analysis showed that areas with slight decreases or increases in PM_2.5 concentration were more sensitive to HW impacts, with statistical associations observed when using HW events (HW9, P_Interaction=0.046) and HW days (HW1, P_Interaction=0.007) as exposure indicators. In contrast, areas with increased normalized difference vegetation index (NDVI) showed weakened HW impacts on social participation, with statistical associations observed when using HW events (HW3, P_Interaction=0.008) and HW days (HW9, P_Interaction=0.016) as exposure indicators.

HW is a key risk factor for reduced social participation among middle-aged and older adults. Thus, amid ongoing climate warming, integrating HW into public health and aging policies is of great significance.

To investigate the composition and distribution characteristics of bacterial communities in different parts of household air conditioners (ACs) in Chengdu, providing a basis for effective contamination control.

Using convenience sampling, 15 households in Chengdu were selected, with the most frequently used household air-conditioning unit from each household included in the study. Microbial samples were collected using sterile swabs from four key components of the air-conditioning system, including the air outlet, filter screen, heat sink, and condensate tray, resulting in a total of 60 samples. All samples underwent 16S rRNA sequencing, followed by bioinformatics analysis to assess α-diversity, β-diversity, and bacterial community composition. One-way analysis of variance (ANOVA) and the Kruskal-Wallis rank-sum test were employed to determine whether there were differences in α-diversity, β-diversity, and phenotypes among the four components.

Through high-throughput sequencing, the 60 samples collectively yielded 52 bacterial phyla and 1 618 bacterial genera. The differences in the sobs index, Simpson diversity index, and Shannon diversity index, representing the α-diversity of the four components, were all statistically significant (F=12.392, P=1.981×10^-5; F=6.290, P=1.898×10^-3; F=8.294, P=3.479×10^-4). Proteobacteria, Firmicutes, and Actinobacteria were the three dominant phyla across all samples, with Methylobacterium, Rhodococcus, Pseudomonas, and Sphingomonas being the predominant genera. Six categories of potential pathogenic genera were detected: Pseudomonas, Acinetobacter, Staphylococcus, Bacillus, Corynebacterium, and Streptococcus. PCoA analysis revealed that the bacterial community composition of air outlet samples was similar to that of filter screen samples, while the composition of heat sink samples resembled that of condensate tray samples. The differences in bacterial community composition, i.e., β-diversity, among the four components were statistically significant (H=41.135, P=3.469×10^-10). BugBase phenotypic intergroup difference testing showed that the bacteria from the four components of household air conditioners exhibited statistically significant differences in biofilm formation (H=25.772, P=7.663×10-7), stress tolerance (H=14.933, P=1.538×10^-3), pathogenic potential (H=17.606, P=2.169×10^-4), and the proportion of Gram-positive bacteria (H=17.882, P=1.737×10^-4).

High-throughput sequencing revealed differences in bacterial community composition and the distribution of potential pathogenic bacteria across four components of household ACs from 15 households sampled in Chengdu. These findings suggest that differentiated cleaning and disinfection strategies should be implemented for different components to reduce the risk of bacterial exposure.

To analyze the epidemiological characteristics of foodborne disease outbreaks caused by meat and meat products in Sichuan Province, so as to identify high-risk factors, and provide a scientific basis for developing targeted prevention and control strategies.

Based on outbreaks reported in the foodborne disease outbreak surveillance system (2010—2024) involving meat and meat products, a descriptive epidemiological analysis was conducted. Indicators such as composition ratio and rate were used for description, and χ² tests were employed to compare intergroup differences.

From 2010 to 2024, a total of 193 outbreaks caused by meat and meat products were reported in the province, involving 25 073 exposed individuals, 2 249 cases, 1 087 hospitalizations and 2 deaths. The attack rate was 8.97%, and the hospitalization rate was 48.33%. The Chengdu Plain Economic Zone reported the most outbreaks (52.85%). The highest number of outbreaks occurred in autumn (26.42%). Food service establishments were the most common settings (59.59%). Microbial pathogens were the primary causative agents (46.63%), with Salmonella being the most common (20.21%). One death each was caused by nitrite and botulinum toxin, accounting for 50.00% of fatalities respectively. Ready-to-eat meat products were implicated in the majority of outbreaks (98.96%).

Salmonella, nitrite, and botulinum toxin were the key pathogenic factors for prevention and control in our province. Summer and autumn were the key seasons, while Chengdu Plain Economic Zone and Chuannan Economic Zone were the key areas. Children and the elderly were the key populations. Health education should continue to be strengthened for key areas/places/populations during the summer and autumn seasons. The public should avoid consuming homemade or unidentified ready-to-eat meat products, and management of food service establishments should be strengthened.

To analyze the epidemiological characteristics of reported cases of Vibrio parahaemolyticus food poisoning in China, and to provide a basis for formulating prevention and control measures.

Data on Vibrio parahaemolyticus food poisoning incidents from 2015 to 2024 were extracted from the Public Health Emergency Reporting and Management System under the Chinese Disease Prevention and Control Information System. A descriptive epidemiological approach was adopted for analysis.

From 2015 to 2024, a total of 162 Vibrio parahaemolyticus food poisoning incidents were reported across 20 provinces in China, involving 7 721 poisoned individuals. The months of July to September were the peak period, accounting for 69.1% (112/162) of the total incidents and 64.5% (4 982/7 721) of the total poisoned population. The top 5 provinces with the highest number of reported incidents were all coastal provinces, contributing 56.2% (91/162) of the total incidents. Restaurants were the main responsible units, accounting for 61.1% (99/162) of all incidents, followed by canteens (29.6%, 48/162). Among the 93 incidents with identified suspicious contaminated foods, 69 involved single-food contamination. Among these, meat and meat products were the primary category, accounting for 22.8% (37/162), followed by aquatic products and their derivatives (14.8%, 24/162). Among the 78 incidents where the pollution causes were clearly identified, 59 were attributed to a single factor. Among these single-factor cases, cross-contamination between raw and cooked foods was the lead ing single factor, accounting for 45.8% (27/59); this was followed by improper storage (20.3%, 12/59) and improper processing (15.3%, 9/59).

The main contaminated foods in Vibrio parahaemolyticus food poisoning incidents are meat and meat products, as well as aquatic products and their derivatives. Catering service units are the main responsible entities, and cross-contamination between raw and cooked foods, improper storage, and improper processing are the key risk links. It is recommended that supervision over catering units in high-incidence areas be strengthened in summer, with strict implementation of operating standards. Specifically, seafood raw materials and cooked foods should be stored and processed separately, containers for raw and cooked foods should be distinguished, and the heating temperature and duration of food ingredients should meet safety standards.

To investigate influencing factors of influenza virus infection among hospitalized pregnant and postpartum women during influenza season in Suzhou City.

Based on the established active surveillance system for influenza-associated acute respiratory or febrile illness (ARFI) hospitalizations among the maternal population in Suzhou, we used rates/percentages to describe population distribution characteristics. Logistic regression analyses were performed to identify factors associated with laboratory-confirmed influenza infection in hospitalized pregnant and postpartum women during influenza season.

During 2018—2023 influenza seasons, 1 774 pregnant and postpartum women hospitalized with ARFI were included, with 479 cases (27.0%) testing positive and 1 295 negative by reverse transcription polymerase chain reaction (RT-PCR). Multivariable analysis confirmed that elevated risks persisted in first (aOR=2.49, 95% CI: 1.52-4.11) and third trimesters (aOR=1.83, 95% CI: 1.27-2.68). Influenza like illness (ILI) exposure increased risk by 86.0% (aOR=1.86, 95% CI: 1.36-2.55). Asthma was associated with an 83.0% lower risk (aOR=0.17, 95% CI: 0.03-0.56). Having ILI symptoms within the past 1 year (aOR=0.70, 95% CI: 0.51-0.94) and having children (aOR=0.77, 95% CI: 0.62-0.96) were also associated with a reduced risk of hospitalization with influenza infection.

Pregnant women in first and third trimesters should strengthen self-protection measures against seasonal influenza. Attention to health-related behaviors significantly reduces infection risks.

To explore the relationship between family functioning and non-suicidal self-injury (NSSI) among adolescents in a specific western region of China, and to examine the chain mediating role of internet addiction and depression in this relationship.

A cross-sectional study was conducted among 1 331 seventh and eighth-grade students from a middle school in a western region of China. Assessments were carried out using the Internet Addiction Test (IAT), the Center for Epidemiological Studies Depression Scale for Children (CES-DC), the Chinese version of the Family Assessment Instrument (C-FAI), and the Deliberate Self-Harm Inventory (DSHI).

The detection rate of NSSI among adolescents was 32.5%. Statistically significant differences in NSSI were found across gender (χ²=39.539), history of smoking (χ²=29.838), history of alcohol use (χ²=35.042), academic burden (χ²=49.824), and sleep duration (χ²=54.838), with all P<0.001. Mediation analysis indicated that family dysfunction not only directly influenced NSSI but also exerted indirect effects through three pathways: internet addiction alone (accounting for 13.2%), depression alone (accounting for 39.7%), and the sequential chain of internet addiction followed by depression (accounting for 7.4%). The total indirect effect accounted for 58.8% of the overall influence.

Family dysfunction is a significant risk factor for adolescent NSSI in the studied region. Its mechanism of action involves exerting influence through the chain mediating effects of internet addiction and depression. Interventions aimed at improving family functioning, promoting healthy internet use habits, and addressing depressive symptoms may help reduce the risk of NSSI among adolescents.

To investigate rural women's willingness to undergo cervical cancer screening and its influencing factors based on the Health Belief Model (HBM), and to provide theoretical support for improving screening participation rates in this population.

From April to May 2025, a multi-stage cluster sampling method was used to select rural women in Shimian County, Ya'an City, Sichuan Province for a questionnaire survey. The questionnaire collected information on sociodemographic characteristics, health beliefs related to cervical cancer screening, and screening willingness. Univariate analysis was used to examine associations between demographic variables, HBM dimensions, and screening willingness. Structural equation modeling (SEM) was employed to identify influencing factors and pathways affecting screening willingness.

Among the 431 valid questionnaires collected, 74.0% of respondents expressed willingness to participate in cervical cancer screening. Univariate analysis showed statistically significant differences in screening willingness across age, ethnicity, and occupation (P<0.05). SEM results indicated that self-efficacy (direct effect=0.541, P<0.001) and perceived susceptibility (direct effect=0.177, P<0.001) had direct positive effects on screening willingness. Cues to action (indirect effect=0.237), perceived severity (indirect effect=0.199), and perceived benefits (indirect effect=0.024) exerted indirect positive effects, while perceived barriers had an indirect negative effect (indirect effect=-0.164).

Based on the Health Belief Model, targeted measures should be implemented to improve rural women's perceptions of susceptibility, severity, and screening benefits, enhance cues to action and self-efficacy, and reduce perceived barriers, thereby increasing cervical cancer screening willingness.

To investigate the mediating effect of healthy lifestyle between personality traits and obesity among primary school students in grades 4-6, so as to provide evidence for targeted obesity interventions.

A cross-sectional survey and physical examinations were conducted among 3 519 primary school students in grades 4-6 from 14 schools in Changzhou in 2024 by stratified cluster random sampling method. The personality traits were measured by the Big Five Inventory-10. The healthy lifestyle was assessed across four dimensions: healthy diet, moderate exercise, adequate sleep and reasonable screen time. A structural equation model was constructed to analyze the association between personality traits and obesity in primary school students and the mediating effect of the healthy lifestyle.

The detection rate of obesity among primary school students in grades 4-6 was 20.60%, significantly higher in boys (25.16%) than girls (15.49%) (χ²=50.127, P<0.001). The detection rate of obesity decreased significantly with the increase of education level of father and mother (all P<0.05). The total score of healthy lifestyle and the score of conscientiousness were negatively correlated with obesity (r_s=-0.066, P<0.001; r_s=-0.058, P<0.001). After controlling for gender and parental education, the model results showed that the indirect effect of conscientiousness on obesity through healthy lifestyle was -0.010 (95% CI: -0.018~-0.002), and the mediating effect accounted for 18.87% of the total effect.

Conscientiousness can directly or indirectly affect obesity among primary school students in grades 4-6 in Changzhou through healthy lifestyle. Personalized intervention programs for childhood obesity should be designed in combination with personality traits to promote healthy lifestyle.

To examine the bidirectional dynamic relationship between activities of daily living (ADL) and depressive symptoms among older adults with dual sensory impairment (DSI), identify key driving symptoms, and provide targets for precision interventions.

This study used longitudinal data from the 2018 and 2020 waves of the China Health and Retirement Longitudinal Study (CHARLS), including 2 674 participants aged≥60 years with DSI. Depressive symptoms were assessed using the short form of the Center for Epidemiologic Studies Depression Scale, and ADL limitations were measured using the ADL scale. A cross-lagged panel network (CLPN) model was applied to examine time-lagged effects and symptom network characteristics.

A significant cross-lagged pathway was identified from ADL item A11 “Managing money” to depressive symptom A1 “Being bothered by little things” (OR=1.19, 95% CI: 1.07-1.28), followed by D3 “Felt depressed” to A4 “Getting in, out of bed” (OR=1.16, 95% CI: 1.00-1.32), and D2 “Felt fearful” to A1 “Dressing” (OR=1.14, 95% CI: 1.00-1.35). Centrality analysis revealed that D3 “Felt depressed” (BEI=0.73) and A11 “Managing money” (BEI=0.59) were key bridge symptoms. D3 “Felt depressed” showed the highest out-expected influence (OEI=1.03), while A10 “Taking medication” was most susceptible to influence (IEI=0.77).

In older adults with DSI, ADL limitations and depressive symptoms may influence each other through specific pathways, and the CLPN indicates reciprocal prospective predictive associations between them, potentially forming a bidirectional vicious cycle via these pathways. Targeted interventions focusing on core bridge symptoms may help disrupt this cycle, thereby improving functional independence, enhancing psychological well-being, promoting healthy aging, and carrying important public health significance.

To analyze the influencing factors of cognitive impairment and construct a risk assessment model for illiterate elderly individuals.

Based on the 2020 China Health and Retirement Longitudinal Study (CHARLS) database, illiterate elderly individuals aged≥60 years were taken as the research subjects. Ten-fold cross-validated LASSO regression was used to identify the optimal predictor variables. Logistic regression was further applied to explore the risk factors of cognitive impairment in this population, and an assessment model was further constructed. The performance of the model was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), sensitivity, specificity, Hosmer-Lemeshow test, calibration curve, decision curve analysis (DCA), categorical/continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

A total of 1 575 illiterate elderly individuals were included in this study, with a prevalence of cognitive impairment of 39.75%. Lasso regression screened potential predictor variables, including age, marital status, residence type, alcohol consumption, physical activity, social engagement, and internet use. Multivariable logistic regression analysis showed that advanced age (70-79 years: OR=1.509, 95% CI: 1.120-2.032; ≥80 years: OR=2.178, 95% CI: 1.341-3.537), rural residence (OR=1.631, 95% CI: 1.159-2.295) were the risk factors. In contrast, being married (OR=0.607, 95% CI: 0.450-0.817), alcohol consumption (OR=0.647, 95% CI: 0.471-0.888), social engagement (OR=0.683, 95% CI: 0.524-0.891), moderate-to-high intensity physical activity (moderate intensity: OR=0.633, 95% CI: 0.428-0.937; high intensity: OR=0.628, 95% CI: 0.439-0.898), internet use (OR=0.327, 95% CI: 0.184-0.581) were protective factors. An assessment model was established based on the seven factors. The areas under the ROC curves of the assessment model in the training and validation sets were 0.670 and 0.655, respectively. The Hosmer-Lemeshow χ²=11.977, P=0.152, and χ²=7.977, P=0.436. Brier scores were 0.216 and 0.227, respectively. The calibration curve revealed good consistency between the predicted values and the actual values, and the DCA indicated that the model had good net benefit and assessment accuracy. Additionally, the model showed a significant incremental improvement in terms of risk reclassification.

The risk assessment model for cognitive impairment in illiterate elderly individuals, based on seven influencing factors including age and residence type, can provide support for the early identification of cognitive impairment in this population.