To explore the childcare willingness of Guangxi families and its influencing factors under the support of childcare policies, so as to provide reference for the government to optimize childcare service policies and supporting measures.

Based on the data of the 7th National Health Service Survey in Guangxi in 2023, 336 families with infants aged 0-3 in three regions (northern, central and southern Guangxi) were selected by stratified sampling. Information such as family basic characteristics, economic status and social factors was collected through questionnaires. Chi-square test and multivariate Logistic regression were used to analyze the influencing factors of childcare willingness.

A total of 354 family questionnaires were distributed, 18 questionnaires with incomplete filling and logical errors were excluded, and 336 valid questionnaires were recovered. Among the respondents, 243 cases were willing to take childcare, and 93 cases had no such willingness. The overall childcare willingness rate of Guangxi families was 72.3%. Multivariate analysis showed that age, ethnicity, urban-rural distribution, number of children born, and occupation type were the influencing factors of family childcare willingness. The main reasons for the unwillingness to take childcare included infants’ adaptation problems, high prices of childcare institutions, and insufficient trust.

The childcare willingness of Guangxi families is affected by multiple factors such as ethnic culture, urban-rural resource allocation, and family care pressure. Strategies such as embedding ethnic culture, balancing urban-rural resources, and providing hierarchical services are needed to improve the accessibility of childcare services and family trust.

To explore the construction of an integrated monitoring platform for Healthy Life Expectancy (HLE) statistics and to conduct a preliminary evaluation of its application effectiveness.

Challenges were analyzed to define development goals. Multiple sources of health and medical big data were integrated, and advanced technologies such as blockchain and big data processing were applied to enable dynamic monitoring, automated calculation, and comprehensive analysis of HLE and its determinants.

The platform successfully connected with information systems from tertiary hospitals nationwide, multiple public health data platforms, and various disease registries. Data completeness improved significantly from an average of 65% to over 92%. A monitoring system comprising five categories and more than 30 HLE-related indicators was established, identifying over 20 key factors strongly associated with HLE. The average approval time for data-sharing applications was reduced from seven working days to three, enhancing both security and efficiency in data sharing.

The integrated monitoring platform for HLE statistics demonstrates substantial value in improving the efficiency of health data analysis, supporting policy formulation, and guiding health interventions. It provides robust data support and technological assurance for the advancement of the Healthy China initiative.

To explore the influencing factors of health poverty among the elderly in China and provide a basis for improving the health poverty situation of the elderly.

Based on the health ecology theory, this study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) in 2020, selecting the elderly aged 60 and above as the research subjects.The occurrence of health poverty among the elderly was taken as the dependent variable, and independent variables were included from five dimensions: personal traits, behavioral characteristics, interpersonal networks, family living environment, and policy systems. Chi-square tests and stratified Logistic regression analyses were conducted for statistical processing.

Age (70-79 years old, OR=1.416, 95% CI: 1.248-1.606; 80 years old and above, OR=1.583, 95% CI: 1.263-1.983), having three or more chronic diseases (OR=1.464, 95% CI: 1.300-1.649), self-rated health (fair, OR=0.449, 95% CI: 0.366-0.550; good, OR=0.335, 95% CI: 0.256-0.438; very good, OR=0.314, 95% CI: 0.238-0.415), drinking alcohol (OR=0.833, 95% CI: 0.735-0.944), marital status (married, OR=2.655, 95% CI: 2.062-3.419), family size (2 people, OR=0.567, 95% CI: 0.425-0.756; 3 people or more, OR=0.218, 95% CI: 0.163-0.292), per capita high income of the family (OR=0.782, 95% CI: 0.672-0.911), medical insurance type (urban and rural residents’ medical insurance, urban residents’ medical insurance, new rural medical insurance, OR=1.296, 95% CI: 1.052-1.596), and central region (OR=0.755, 95% CI: 0.643-0.887) were all important factors influencing the incidence of health poverty among the elderly.

The incidence of health poverty among the elderly in China is relatively high, and factors at different levels have significant impacts on the occurrence of health poverty among the elderly, with interactions among these factors. Therefore, it is necessary to take a multi-dimensional approach and comprehensively consider individual, family, social, and policy factors to effectively improve the health poverty situation of the elderly.

To investigate the association and dose–response relationship between leisure-time physical activity (LTPA) and the risk of incident common mental disorders.

This study included 388 559 participants without a history of mental disorders at baseline from the UK Biobank cohort. Weekly total energy expenditure from LTPA was calculated and categorized into four groups: inactive (0MET-h/week), insufficiently active (>0–7.49MET-h/week), sufficiently active (7.5–14.9MET-h/week), and highly active (≥15MET-h/week). Multivariable Cox proportional hazards models were used to calculate hazard ratios ( HR), and restricted cubic splines were applied to explore the dose–response patterns.

During a median follow-up of 12.71 years, 27 875 incident cases of mental disorders were documented. Compared with the inactive group, the risk of mental disorders was significantly reduced in the below recommended, meeting recommended, and above recommended groups, with HR of 0.84 (95% CI: 0.81–0.87), 0.76 (95% CI: 0.72–0.79), and 0.73 (95% CI: 0.70–0.76), respectively. Restricted cubic spline analysis demonstrated an L-shaped nonlinear association. LTPA was inversely associated with the risk of depression, anxiety disorders, and schizophrenia, while no significant associations were found for bipolar disorder or eating disorders.

LTPA is significantly inversely associated with the risk of developing mental disorders. Protective effects were observed even at activity levels below current recommendations, and a clear dose–response relationship was evident.

To investigate cognitive function and depression as mediators between exercise and falls in elderly chronic disease patients.

Using stratified and convenience sampling, this cross-sectional survey in Shandong included 1 433 elderly chronic disease patients via a self-designed questionnaire. Generalized structural equation modeling and Bootstrap testing were used.

Fall incidence was 18.8%. Exercisers had significantly lower fall incidence. Cognitive function scores were lower in fallers; depression scores were higher in fallers. Exercise, cognitive function, and depression significantly affected falls (P<0.05). Exercise negatively predicted falls (β=-0.376, 95% CI:-0.685- -0.067). Cognitive function (β=-0.037, 95% CI:-0.070--0.004) and depression (β=-0.124, 95% CI:-0.194- -0.055) had significant mediating effects. A chain-mediating effect existed via cognitive function and depression (β=-0.011, 95% CI:-0.021--0.001).

Exercise directly reduces falls and also reduces falls indirectly through the mediating effects of cognitive function and depression.

To explore the association of sleep duration and depression with Chronic lung disease (CLD) in middle-aged and elderly Chinese.

Using CHARLS public data (2011-2020), Cox regression and restricted cubic spline (RCS) analyses were performed to assess the associations and dose-response relationships of sleep duration and depression with CLD. Subgroup and interaction analyses was further conducted to evaluate effect heterogeneity, and sensitivity analyses to test the robustness of our results.

Among 6 011 respondents, 27.65% had short sleep, 63.85% had normal sleep, 8.50% had long sleep, and 35.63% had depression. Cox regression analysis showed that short sleep duration ( HR=1.23, 95% CI: 1.04-1.45, P=0.018) and depression ( HR=1.76, 95% CI: 1.50-2.05, P<0.001) significantly increased CLD risk. The results of RCS analysis showed that sleep duration (P-overall=0.009, P-non-linear=0.121) and depression (P-overall<0.001, P-non-linear=0.116) had a dose-response and linear relationship with CLD risk. The results of infled-point analysis showed that, when the sleep duration was <6.97 h or CES-D score was >7, the risk of CLD increased with the decrease of sleep or the increase of CES-D score. Subgroup analysis showed that the association between short sleep duration and the risk of CLD was more significant in women aged 45-59 years, with high school education or above, low physical activity, social participation, and non-diabetes. The interaction showed that with the increase of education level, the association between long sleep and CLD decreased by 29%, and the association between depression and CLD increased by 19%.

Short sleep duration and depression are important risk factors for CLD in middle-aged and elderly people, and their evaluation should be included in the CLD prevention system.

To analyze the factors influencing suicidal ideation in transgender individuals.

A study was conducted on transgender individuals from a medical institution. Participants were surveyed using a self-designed general information questionnaire, the Self-Concept Clarity Scale (SCCS), the Satisfaction with Life Scale (SWLS), and the Perceived Social Support Scale (PSSS). Logistic regression was used to analyze factors influencing suicidal ideation.

A total of 170 participants was included. The detection rate of suicidal ideation among transgender individuals was 54.7% (93/170). Risk factors for suicidal ideation included age ≥30 years (OR=3.35, 95% CI=1.31-8.56), experience of domestic violence (OR=2.97, 95% CI=1.16-7.61), low life satisfaction (OR=5.13, 95% CI=2.29-11.50), and low family support (OR=3.31, 95% CI=1.43-7.66). A higher education level (bachelor’s degree or above) was identified as a protective factor (OR=0.42, 95% CI=0.19-0.93).

Higher education (bachelor’s degree or above) serves as a protective factor against suicidal ideation in transgender individuals, while older age (≥30 years), experience of domestic violence, low life satisfaction, and lack of family support are risk factors.

To study the association of insufficient sleep and internet addiction with comorbid depressive and anxiety symptoms among middle school students in Chongqing, and to provide evidence for developing mental health intervention strategies.

A stratified cluster sampling method was employed to select 68 961 middle school students from 41 districts/counties in Chongqing. The Center for Epidemiologic Studies Depression Scale (CES-D) and the Generalized Anxiety Disorder 7-item scale (GAD-7) were used to assess symptoms of depression and anxiety, respectively. Chi-square tests were conducted to compare the detection rates of depression, anxiety, and comorbidity among different groups of students. Logistic regression models were utilized to analyze the associations between insufficient sleep, internet addiction, and the comorbidity of depression and anxiety.

The prevalence rates of insufficient sleep and internet addiction among middle school students were 67.2% and 4.0%, respectively. The detected rates of depression, anxiety, and comorbidity were 25.3%, 6.8%, and 6.0%, respectively, with significantly higher proportions observed in females, ethnic minorities, and high school students. Logistic regression analysis indicated that insufficient sleep (OR=1.492, 1.529, 1.562, all P<0.001) and internet addiction (OR=5.742, 4.600, 5.069, all P<0.001) are independent risk factors for depression, anxiety, and the comorbidity of depression and anxiety. The students exhibiting both risk factors demonstrate a significantly higher likelihood of developing depression, anxiety, and comorbidity compared to their peers without internet addiction and with sufficient sleep (OR=7.965, 6.481, 7.226, all P<0.001).

Insufficient sleep and internet addiction are significantly associated with increased risks of depressive symptoms, anxiety symptoms, and their comorbidity among middle school students in Chongqing. It is recommended to implement comprehensive interventions through sleep health education, regulation of internet usage, and targeted psychological counseling.

To analyze the drug resistance and genomic characteristics of Salmonella London isolates from Chengdu between 2019 and 2023.

Salmonella isolates from clinical and food sources in Chengdu during 2019-2023 were serologically identified, resulting in 72 Salmonella London strains. Drug susceptibility testing was performed using the microbroth dilution method. Whole-genome sequencing was conducted to analyze the core genome multilocus sequence typing (cgMLST) genetic characteristics and the presence of resistance genes.

The isolates showed the highest resistance to trimethoprim-sulfamethoxazole (76.39%, 55/72), followed by tetracycline (72.22%, 52/72), ampicillin (68.06%, 49/72), and chloramphenicol (62.50%, 45/72). All isolates were sensitive to ertapenem, ceftazidime/avibactam, tigecycline, meropenem, and amikacin. Among the 72 strains, 11 were sensitive to all 17 tested antibiotics. Multidrug resistance was observed in 70.83% (51/72) of the isolates, with the predominant resistance profile being AMP-AMS-CHL-SXT-TET (12.50%, 9/72). Of the 72 strains, 71 were identified as ST155, with 1 untyped. Some strains exhibited allele differences of ≤10, indicating high genetic homology.

The 72 Salmonella London isolates demonstrate high resistance rates and severe multidrug resistance, with the predominant resistance profile being AMP-AMS-CHL-SXT-TET. The high genetic homology among certain strains suggests the potential for foodborne illness outbreaks.