To explore the relationship between sleep quality and depression among elderly individuals in Shanghai’s communities, as well as the mediating role of physical activity.

A multi-stage cluster sampling method was employed to survey 2 500 elderly individuals aged 60 and above in Hongkou District, Shanghai. A self-developed demographic questionnaire, the Pittsburgh Sleep Quality Index (PSQI), the Physical Activity Scale for the Elderly (PASE), and the Geriatric Depression Scale (GDS) were used for data collection. Pearson correlation analysis and linear regression analysis were conducted to investigate the relationships among sleep quality, physical activity, and depression, while the mediating effect of physical activity was tested using the PROCESS macro in SPSS 27.0.

The average sleep quality score among community-dwelling elderly in Shanghai was 6.11±2.90, the physical activity level score was 156.23±96.67, and the depression score was 4.01±5.40. A positive correlation was identified between sleep quality and depression (r=0.488, P < 0.001), while a negative correlation existed between physical activity level and depressive symptoms (r=-0.414, P < 0.001). Physical activity partially mediated the relationship between sleep quality and depression, accounting for 8.79% of the total effect.

Sleep quality and depression are closely related among community-dwelling elderly in Shanghai, with physical activity playing a partial mediating role. Enhancing sleep quality and physical activity levels among the elderly may help prevent and alleviate depression.

To describe the changes in the burden of depression among Chinese residents from 1990 to 2021 and to forecast future trends, providing reference for the prevention and control of depression.

Based on the 2021 Global Burden of Disease data, indicators such as the number of cases, incidence rate, prevalence rate, and disability-adjusted life years (DALYs) along with DALYs rates were selected to calculate the rate of change. The Join point regression model was employed to calculate the annual percentage change (APC) and average annual percentage change (AAPC) to analyze the trend of disease burden. Future trends were predicted using R software combined with the GM (1,1) model.

In 2021, the total number of depression cases in China was approximately 42.36 million, with an incidence rate of 2 977.354 per 100 000 and a standardized incidence rate of 2 345.079 per 100 000. The total DALYs attributed to depression were 7.8659 million years, with a total DALYs rate of 552.87 per 100 000 and a standardized DALYs rate of 430.61 per 100 000. Compared to 1990, the standardized prevalence rates for the total population, males, and females decreased by 6.39%, 2.4%, and 9.17%, respectively; the standardized incidence rates decreased by 10.79%, 3.96%, and 14.93%; and the standardized DALYs rates decreased by 9.02%, 3.85%, and 12.43%. Join point regression analysis indicated that from 1990 to 1995 and from 2010 to 2015, the standardized incidence rate of depression among the total population in China showed an increasing trend (APC of 1.56% and 1.37%, respectively), while from 1995 to 2000 and 2005 to 2010, it exhibited a decreasing trend (APC of -2.74% and -1.45%,respectively). The standardized prevalence rates from 1990 to 1992, 1992 to 1995, and 2019 to 2021 all showed an upward trend (APC of 1.67%, 0.48%, and 0.96%, respectively), whereas from 1995 to 2000, 2000 to 2005, 2005 to 2010, and 2010 to 2019, they demonstrated a downward trend (APC of -1.06%, -0.22%, -1.02%, and -0.15%, respectively). The standardized DALYs rate increased from 1990 to 1994 (APC of 1.75%) and showed a decreasing trend from 1994 to 2000 and from 2000 to 2006 (APC of-1.55% and -0.46%, respectively).

The burden of depression among Chinese residents is increasing, with a higher burden observed in females. The risk of depression among the elderly should not be overlooked. Continued efforts are needed to enhance public awareness of depression-related health knowledge and implement preventive interventions.

To explore the mediating role of self-efficacy between social support and coping styles in female patients with stress urinary incontinence (SUI) and to provide a reference for clinical interventions.

A total of 128 female SUI patients admitted to the People’s Hospital of Xinjiang Uygur Autonomous Region from January 2022 to January 2024 were selected. General information was collected using a self-designed questionnaire. The Perceived Social Support Scale (PSSS) was used to assess social support, the General Self-Efficacy Scale (GSES) to evaluate self-efficacy, and the Simplified Coping Style Questionnaire (SCSQ) to measure coping styles. Correlation analysis and structural equation modeling were employed to analyze the mediating effect of self-efficacy.

Patients aged ≤60 years had higher GSES scores, positive SCSQ scores, total PSSS scores, and scores on its three subscales compared to those aged >60 years, while their negative SCSQ scores were lower (P < 0.05). Correlation analysis revealed that GSES scores were positively correlated with PSSS scores and positive SCSQ scores but negatively correlated with negative SCSQ scores in both age groups (r=-0.601, P < 0.05). PSSS scores were positively correlated with positive SCSQ scores (r=0.650, P < 0.05) and negatively correlated with negative SCSQ scores in both age groups. The Amos 24.0 maximum likelihood estimation method was used to construct a mediation model, showing that self-efficacy had a positive effect on positive coping styles (effect values: 0.62 and 0.56 for ≤60 and >60 years, respectively) and a negative effect on negative coping styles (effect values: -0.50 and -0.45, respectively). Social support positively influenced self-efficacy (effect values: 0.59 and 0.65, respectively), while positive coping styles positively influenced social support (effect values: 0.57 and 0.60, respectively), and negative coping styles negatively influenced social support (effect values: -0.40 and-0.51, respectively).

Self-efficacy mediates the relationship between social support and coping styles in female SUI patients, and age significantly affects self-efficacy and coping styles. Enhancing patients’ social support and self-efficacy can promote the adoption of positive coping styles, thereby improving clinical outcomes.

To understand the epidemiological characteristics of public health emergencies in Qinghai Province from 2009 to 2023, providing a basis for decision-making in the prevention and control of such events.

Data on incidents from 2009 to 2023 in Qinghai Province were collected and organized from the “Public Health Emergency Report Management Information System”. Descriptive epidemiological methods were used to analyze the characteristics of these incidents.

A total of 311 public health emergencies were reported in Qinghai Province from 2009 to 2023, with 9 099 cases of illness affecting a total of 480 213 individuals, resulting in 46 deaths. Join point analysis revealed a turning point in infectious disease incidents, with a statistically significant upward trend from 2012 to 2023 (P=0.001). In contrast, non-infectious disease incidents exhibited a notable downward trend, with an annual percentage change (APC) of -8.30% (95%CI: -14.91% to -2.86%, P=0.003). Global spatial autocorrelation results indicated that, except for 2015 when public health emergencies in Qinghai showed a spatial negative correlation (Moran’s I=-0.321, Z=-1.557, P=0.035), no statistical differences were observed in other years (P>0.05). Pearson correlation analysis revealed a positive correlation between the reporting time of incidents and the duration of infectious disease outbreaks (r=0.43, P<0.05), indicating that longer reporting intervals were associated with longer outbreak durations.

There is a correlation between incident reporting and outbreak duration in Qinghai Province. It is recommended to enhance the awareness of timely reporting among medical institutions at all levels and to strengthen epidemic monitoring in key gathering places, such as primary schools, to reduce the occurrence of public health emergencies.

To explore the correlation between complex multimorbidity and their influencing factors and to reveal the interactions between diseases and factors using network inference methods to identify high-risk populations.

Based on longitudinal data from 2016 to 2022 in the Urumqi public health surveillance database and electronic medical record information database, this study collected information on the occurrence of complex multimorbidity and related variables. The structure of the Bayesian network was learned using the maximum-minimum hill-climbing algorithm combined with prior knowledge, and parameter learning was conducted using Bayesian estimation. Directed acyclic graphs were employed to identify confounding factors and guide the construction of regression models.

A total of 6 938 participants were included in the study, of which 12.96% (899/ 6 938) developed complex multimorbidity over the seven-year period. After screening influencing factors, six predictors were selected for model construction, resulting in a model with 7 nodes and 10 directed edges. The results indicated that age, gender, source, and BMI weredirectly related to the occurrence of complex multimorbidity, all serving as parent nodes in the model. The results of logistic regression based on DAG guidelines showed that the risk of complex multimorbidity would increase by 8.70% [OR=1.087 (95%CI:1.077-1.098)] for each year of age increase in patients with chronic diseases; the OR of complex multimorbidity for rural residents compared to urban residents=0.274 (95%CI: 0.237-0.317); the OR of complex multimorbidity for obese people compared with thenormal weight people=1.019 (95%CI: 1.008-1.504).

Bayesian networks effectively identify the relationships between complex multimorbidity and influencing factors, as well as the interactions among these factors, thus enabling inference about the risk of complex multimorbidity occurrence. Prevention and control of complex multimorbidity requires attention to aging, urban environments, and obesity management.

To study the protective effect of melatonin on PM2.5-induced inflammation and lymphangiogenesis in the lung of ApoE^-/- mice.

Twenty-eight male ApoE^-/- mice were randomized into: control group, PM2.5 group, melatonin group and PM2.5+melatonin group. All mice were fed with western diet for 24 weeks. From the 25th week, mice in the melatonin group and PM2.5+melatonin group were daily orally gavage with melatonin (20 mg/kg·bw) for 8 weeks; mice in the PM2.5 group and PM2.5+melatonin group were exposed to PM2.5 by tracheal instillation (5mg/kg); and mice in the control group and melatonin group were instilled with saline at the same time. After 24 h of PM2.5 exposure, mice were euthanized and weight gain and lung weight/body weight ratio in four groups were analyzed. The concentrations of inflammatory cytokines (TNF-α and IL-6) in the lung tissue of mice were measured. Immunofluorescence staining of lung tissue was visualized the lymphatic marker LYVE1 expression. Western Blot was used to assess the protein expression levels of lymphangiogenesis markers PROX1 and LYVE1, lymphangiogenesis regulatory proteins VEGF-C and VEGFR-3 in lung tissues.

The levels of TNF-α and IL-6 and the protein expressions of PROX1, LYVE1, VEGF-C and VEGFR-3in lung tissues of PM2.5 group were significantly higher than the control group (P<0.05). Moreover, the levels of TNF-α, IL-6 and the protein expressions of PROX1, LYVE1, VEGF-C and VEGFR-3 in lung tissues of the PM2.5+melatonin group were significantly lower than the PM2.5 group (P<0.05).

Ambient PM2.5 exposure obviously increases lung inflammation of ApoE^-/- mice, and may increase lymphangiogenesis in lung through regulating the VEGF-C/VEGFR-3 signaling pathway in the lung tissues; melatonin markedly improves PM2.5-induced lung inflammation and reduces lymphangiogenesis in lung.

To explore the relationship between occupational physical activity and dyslipidemia among coal mine employees, providing reference for improving the prevention and control of dyslipidemia among coal mine employees and formulating health strategies.

This study was conducted in 2023 at Xishan coal electricity corporation occupational disease prevention and control institute. It was a cross-sectional study, with a total of 9 864 coal mine employees included in the analysis. We collected physical activity data using the International Physical Activity Questionnaire, and diagnosed dyslipidemia using the "Chinese Guidelines for the Prevention and Treatment of Adult Blood Lipid Disorders". We analyzed the relationship between occupational physical activity and dyslipidemia among coal mine employees using a multiple factor logistic regression model.

The proportion of low, medium, and high intensity occupational physical activities among coal mine employees were 38.42%, 35.75%, and 25.83%, respectively. There were intergroup differences (P<0.05) in the incidence of high TG and dyslipidemia among occupational physical activities of different intensities, but this difference was not observed in the incidence of high TC, low HDL, and high LDL (P>0.05). After adjusting for factors such as gender, age, and leisure time physical activity, the incidence of dyslipidemia was lower among coal miners engaged in moderate to high-intensity occupational physical activity compared to those engaged in low-intensity physical activity (OR=0.84, 95%CI:0.76-0.94; OR=0.77, 95%CI:0.69-0.87); The incidence of low HDL was also lower (OR=0.85, 95%CI:0.77-0.95; OR=0.83, 95%CI:0.73-0.93).

There is a negative correlation between occupational physical activity and dyslipidemia among coal mine employees. For coal mine workers engaged in low-intensity occupational physical activities, it is recommended to intervene in other modifiable behavioral risk factors related to dyslipidemia to maintain healthy blood lipid levels.

To investigate the associations between leisure screen time and theinsomnia symptoms among adolescents.

A random cluster sampling method was used to assess leisure screen time among adolescents aged 12-18 attending schools in Pidu District, Chengdu. Participants reported their screen time on school days and weekends via self-administered questionnaires. Insomnia symptoms were collected using the Insomnia Severity Index (ISI). Adolescents were categorized into two groups based on their ISI scores: the non-insomnia group (ISI score <7) and the insomnia group (ISI score ≥7). Logistic regression models, adjusted for multiple confounders, were used to estimate the association between leisure screen time and the occurrence of insomnia symptoms.

A total of 13 240 adolescents participated, comprising 6 581 boys (49.7%) and 6 659 girls (50.3%), with a mean age of 15.4 years (±1.57). Of these, 51.8% reported an average daily leisure screen time exceeding 2 h, and the prevalence of insomnia symptoms was 35.3%. After adjusting for all confounding factors, logistic regression analysis indicated that leisure screen time >2 h was a significant risk factor for insomnia symptoms (OR=1.13, 95%CI=1.03-1.23). Further analysis by quartiles of leisure screen time revealed that adolescents in Q3 (OR=1.15, 95%CI=1.02-1.28) and Q4 (OR=1.22, 95%CI=1.08-1.39) had significantly increased risks of insomnia, whereas no significant association was observed in the Q2 group. A clear dose-response relationship was observed between leisure screen time and insomnia (P_trend<0.001). Subgroup analyses by sex, region, economic status, single child, and caretaker did not reveal significant interactions (P_interaction>0.05).

Prolonged leisure screen time significantly increases the risk of insomnia symptoms among adolescents. Parents and schools should encourage physical activity and reduce electronic device usage to promote their well-being.

To analyze the influencing factors on the occurrence of anxiety and depression among secondary school students in Shanxi Province in 2023 based on the random forest algorithm and to construct a prediction model to provide a scientific basis for preventing and controlling the occurrence of negative emotions such as anxiety and depression among secondary school students.

In September 2023, 104 826 secondary school students in 11 cities of Shanxi Province were selected by stratified random whole-cluster sampling method for questionnaire survey, and the Generalized Anxiety Scale (GAD-7) and the Center for Streamlined Depression Scale (CES-D) were used to investigate anxiety and depression. Epidata was used for database establishment, chi-square test was used for between-group comparisons, logistic regression was used for influencing factor analysis, and Python 3.7 was used to establish a random forest prediction model and rank the importance of each variable.

The detection rates of anxiety and depression among secondary school students in Shanxi Province in 2023 were 33.26% and 23.72%, respectively, and were higher for girls than for boys, and higher for students in general and vocational high schools than for junior high school students. The results of multifactorial regression analysis showed that female students(OR: 1.846、1.655，95% CI: 1.794-1.901、1.602-1.710), high school(OR: 2.019、1.670，95% CI: 1.956-2.083、1.612-1.731), vocational high school(OR: 1.167、1.356，95% CI: 1.085-1.254、1.254-1.466), non-conventional family(OR: 1.105、1.248，95% CI: 1.072-1.140、1.206-1.292), living in school(OR: 1.102、1.117，95% CI: 1.070-1.136、1.080-1.155), eating fried food ≥1 time/day(OR: 1.296、1.375，95% CI: 1.227-1.369、1.297-1.457), being seriously injured(OR: 1.636、1.688，95% CI: 1.524-1.755、1.569-1.816), being bullied in school(OR: 2.315、3.411，95% CI: 2.150-2.492、3.165-3.677), being scolded by parents(OR: 2.881、3.191，95% CI: 2.766-3.001、3.059-3.328), smoking(OR: 1.344、1.435，95% CI: 1.266-1.427、1.349-1.527), drinking alcohol(OR: 2.062、2.113，95% CI: 1.978-2.151、2.022-2.208), and Internet addiction(OR: 3.635、3.976，95% CI: 3.289-4.016、3.611-4.377) were the risk factors for the detection of anxiety and depressive mood in secondary school students, and eating fresh fruits≥1 time/day(OR: 0.824、0.758，95% CI: 0.800-0.849、0.73-0.783), eating breakfast frequently(sometimes: OR: 0.843、0.715，95% CI: 0.781-0.910、0.661-0.773; daily: OR: 0.538、0.384，95% CI: 0.500-0.579、0.356-0.414), doing moderate to high-intensity exercise frequently(1-3 days/week: OR: 0.888、0.821，95% CI: 0.854-0.923、0.787-0.857; ≥4 days/week: OR: 0.931、0.848，95% CI: 0.893-0.971、0.810-0.887), and having a large number of physical education hours(2-3 sessions/week: OR: 0.826、0.859，95% CI: 0.801-0.853、0.829-0.890; ≥4 sessions/week: OR: 0.741、0.758，95% CI: 0.695-0.789、0.705-0.815) were the protective factors for the detection of anxiety and depressive protective factors for mood detection. Drinking sugary drinks≥1 time/day(OR: 1.198，95% CI: 1.122-1.279) and eating vegetables≥1 time/day(OR: 0.861，95% CI: 0.828-0.895) were independent risk factors and independent protective factors for the detection of depressed mood, respectively. The AUC of the Random Forest model predicting the risk of anxiety and depressed mood was 0.999 8 and 0.999 7, with a sensitivity of 99.53% and 99.67%, and a specificity of 99.47% and 98.98%, respectively. Being scolded by parents, Internet addiction and alcohol consumption were the common factors that had a greater degree of influence on anxiety and depression among secondary school students.

The detection rate of anxiety and depression among secondary school students in Shanxi Province is high, being scolded by parents, alcohol consumption and Internet addiction are the factors that have a greater influence on the occurrence of anxiety and depression, and the random forest model has a high predictive value.

To assess the association between the cardiometabolic index (CMI) and the risk of kidney stone prevalence, and to analyze its role across different population subgroups.

This cross-sectional study included health examination data from 76 624 adults. The association between CMI and the risk of kidney stones was evaluated using multivariable logistic regression models. Stratified analyses were conducted to explore the effect of different population characteristics. A piecewise linear regression model was used to assess the nonlinear relationship between CMI and kidney stone risk.

CMI levels were positively associated with the prevalence of kidney stones, with the prevalence increasing from 4.33% in the lowest tertile to 9.94% in the highest tertile (P<0.001). Even after adjusting for potential confounders, CMI remained significantly associated with an increased risk of kidney stones (OR = 1.15, 95% CI = 1.10-1.20, P<0.001). Stratified analyses showed that the effect of CMI on kidney stone risk was more pronounced in individuals aged ≥60 years (OR = 1.19, 95% CI = 1.08-1.32, P<0.001) and in males (OR = 1.16, 95% CI = 1.10-1.21, P<0.001), while no significant association was found in females (OR = 1.11, 95% CI = 0.96-1.28, P = 0.157). A nonlinear relationship was observed between CMI and kidney stone risk. Risk significantly increased when CMI was <0.73 (OR = 1.15, 95% CI = 1.10-1.20, P<0.001), while the risk plateaued for CMI ≥0.73 (OR = 1.09, 95% CI = 1.03-1.15, P = 0.002).

Elevated CMI is significantly associated with a higher risk of kidney stones, demonstrating a nonlinear threshold effect. As a comprehensive marker reflecting metabolic burden, CMI may be useful for screening and targeting interventions in high-risk populations for kidney stones.