To analyze the epidemiological distribution characteristics of chickenpox in Urumqi City from 2015 to 2023, to construct a prediction model by combining Baidu search keywords, and to explore the complementary application of Baidu index in chickenpox prevention and monitoring.

Descriptive epidemiological methods were used to analyze the characteristics of varicella case triple distribution in Urumqi City from 2015 to 2023. Chickenpox keywords were identified and a comprehensive Baidu search index was constructed. The models ARIMA and ARIMAX were constructed, the prediction effectiveness of the two models was evaluated by mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE).

The average annual reported incidence rate of varicella in Urumqi was 80.85/100 000, with a higher incidence in men than in women (χ²=1.136, P=0.287), there were statistically significant differences in incidence rates by age group (χ²=7 582.372, P<0.001), seven districts and one county had different average annual incidence rates (χ²=21.496, P<0.001), with the highest in the Toutunhe district (100.54/100 000). ARIMAX(1,1,0)(1,0,0) ₅₂ was selected as the best prediction model (prediction set MAE 12.04%, RMSE 13.80%, MASE 1.18%) with a good fitting effect.

The ARIMAX prediction model established based on the search term Baidu index has a certain degree of predictability and sensitivity, and can predict the epidemic trend of chickenpox in Urumqi in time, which can be used as a technical support and further expansion of the traditional monitoring and early warning system.

To explore the longitudinal relationship between sleep condition and physical & mental health among Chinese adults and to provide a basis for improving sleep condition and preventing related chronic diseases.

Based on China Family Panel Studies data, sleep condition index was constructed using self-reported sleep time, quality and daytime function. Physiological health was measured using self-rated health, chronic diseases, physical discomfort and BMI values. Mental health was measured using the Center for Epidemiological Studies Depression Scale. 15 187 adults in three periods (T0: 2016, T1: 2018, T2: 2020) were involved. Trend tests, Cross-lagged path models and robustness tests were used in this study.

There was a significant downward trend in the sleep time among Chinese adults (Z=-19.609, P<0.001). The rate of insufficient sleep showed a clear upward trend (Z=-11.542, P<0.001). Sleep quality (Z=8.594, P<0.001) and daytime function (Z=11.045, P<0.001) showed significant deterioration trends. Correlation analysis results showed that sleep condition at three time points was positively correlated with physical health (P<0.001) and mental health (P<0.001). Cross-lagged analysis results showed that T0 and T1 sleep condition positively predicted T1 and T2 physical health [β=0.108(95%CI:0.093-0.122), β=0.078(95%CI:0.063-0.092)] and mental health [β=0.113(95%CI:0.096-0.126), β=0.095(95%CI:0.105-0.136)], T0 and T1 physical health [β=0.111(95%CI:0.096-0.129), β=0.121(95%CI:0.078-0.111)] and mental health [β=0.132(95%CI:0.116-0.149), β=0.139 (95%CI:0.122-0.156)] each positively predicted T1 and T2 sleep condition. The cross-lagged analysis results were robust in subgroups.

There has been a significant and concerning decline in the sleep condition among Chinese adults. There is a bidirectional predictive relationship between sleep condition and physical & mental health across time points.

To investigate the dynamic developmental trajectories of early suicidal ideation among adolescents, and the influence of factors such as gender, left-behind status, only-child status, boarding status, and social support on the trajectories of suicidal ideation development.

A cluster sampling method was employed to conduct three follow-up surveys among 989 7th-grade students in a certain urban middle school in Hunan Province from March to December 2023. The adolescent suicidal ideation scale (PANSI) and adolescent social support scale (CASSS) were used for questionnaire surveys. A latent growth mixture model (LGMM) was utilized to analyze and explore different categories of early suicidal ideation among adolescents.

Four potential categories of developmental trajectories of early suicidal ideation among adolescents were identified, labeled as C1 group "high-risk-stable" (7.2%), C2 group "medium-risk-worsening" (8.8%), C3 group "medium-risk-stable" (11.1%) and C4 group "low-risk-stable" (72.9%). Being female, left-behind, and only-child were identified as risk factors for the developmental trajectories of early suicidal ideation (all P<0.05), while social support was identified as a protective factor for these trajectories.

The developmental trajectories of early suicidal ideation among adolescents exhibit significant heterogeneity among groups and individual differences.

To study the relationship between the cardiometabolic index (CMI) and hyperuricemia (HUA) in Guizhou minorities.

Based on the "China Multi-ethnic Cohort Study", 16 630 Miao, Dong and Bouyei population aged 30 to 79 years were included in the study. Logistic regression model was used to analyze the association between CMI and HUA, restricted cubic spline was used to analyze the dose-response relationship between CMI and HUA, and ROC curve was used to analyze the predictive value of CMI for HUA.

The overall detection rate of HUA was 22.8%, and those of Miao, Dong and Bouyei nationalities were 24.4%, 25.2% and 18.5%, respectively. In the total population, Miao, Dong and Bouyei populations, after adjusting for covariates, compared with Q1, the ORs for HUA were 4.39 (95%CI: 3.76-5.12), 3.96 (95%CI: 3.03-5.18), 4.28 (95%CI: 3.36-5.46), and 5.55 (95%CI: 4.08-7.54) in CMI Q4 group, respectively. There was a non-linear dose-response relationship between CMI and risk of HUA (P for nonlinear < 0.001). ROC curve analysis showed that, the area under the curve (the best cut-off value, sensitivity and specificity) of CMI for predicting the risk of HUA in the total population, Miao, Dong and Bouyei populations were 0.742 (0.641, 68.3%,68.8%), 0.724 (0.651, 63.8%, 70.8%) 0.741 (0.654, 68.5%, 68.1%), 0.775 (0.555, 68.8%, 73.0%).

CMI is associated with the increased risk of HUA in different ethnic populations, and can be used as an indicator for predicting HUA in ethnic minority populations in Guizhou province.

To explore the bidirectional association between metabolic syndrome(MS) and depression in middle-aged and elderly adults in China.

This study used participants aged 45 and above from publicly available longitudinal data from the China Health and Retirement Longitudinal Study(CHARLS) from 2011 to 2018. The baseline was based on 2011 data. Stage I studied the longitudinal association of baseline MS with follow-up depression, while Stage II studied the association of baseline depression with follow-up MS. Stage III further investigated the bidirectional association between MS and depression using a cross-lagged panel model, and the follow-up data for all three stages used 2015 data including blood routine examination and physical examinations.

There was a bidirectional association between the two diseases. The baseline MS and its components showed a positive correlation with the follow-up depression(β=0.052, P<0.01), and vice versa(β=0.305, P<0.01), but there were differences in gender subgroups.

There is a bidirectional correlation between MS and its components and depression in the middle-aged and elderly population in China. We should identify, monitor, and intervene in early MS and depression.

To understand the status quo of infectious disease reports automatically exchanged by secondary and above medical institutions in Sichuan province based on regional platform, and provide basis for improving the work on automatic exchange of infectious disease information reports in the next step.

Check and calculate the success rates of exchange and rough exchange through the system, the use of the infectious disease reporting management related systems was investigated by questionnaire survey. T-test and chi-square test were used for comparison between groups, and spearman correlation analysis was used for correlation.

From July to September 2023, the exchange success rate in 68 medical institutions was 92.67%, and the success rate of crude exchange reached 95.87%. Compared with other level medical institutions, municipal medical institutions had higher success rate of exchange and crude exchange, and longer time interval to realize automatic exchange. The exchange success rate was positively correlated with the time interval to realize automatic exchange (r=0.44, P<0.001) and the crude exchange success rate (r=0.51, P<0.001). More than 90% of the institutions had HIS, LIS, PACS. 77.94% of the institutions could automatically generate the report card, more than 80% had the report card management and information statistics query functions. 73.53% realized the automatic early warning of infectious disease report card, and 25% of the institutions reported the card forcibly after the early warning. 88.24% felt that the workload of infectious disease report was reduced after automatic exchange.

The success rate of automatic exchange and the success rate of crude exchange in medical institutions were higher overall, municipal medical institutions were higher than other levels of medical institutions. The construction rate of basic information system in medical institutions was high, but the basic functions of automatic exchange were not perfect. Automatic exchange improves the efficiency of reporting to some extent, but it still could not completely replace manual reporting.

To investigate the current distribution status and multimorbidity patterns of chronic diseases among the elderly population in China, and provide reference for formulating chronic disease management measures.

Based on the CHARLS database in 2020, a total of 10,635 elderly individuals aged 60 and above were included to investigate the prevalence trends of 15 common chronic diseases. The actual expected ratio (O/E) and agglomerative hierarchical clustering analysis were employed to explore the patterns of comorbidity.

The prevalence of chronic diseases among elderly people in China was 86.39%, with hypertension (48.49%), arthritis (43.12%), and stomach diseases (excluding tumors or cancer) (32.06%) being the main causes. The multimorbidity rate was 66.30%, and the top three coexisting diseases were "hypertension+arthritis" (22.28%, O/E=1.07), "hypertension+dyslipidemia" (20.25%, O/E=1.44), and "stomach disease+arthritis" (18.65%, O/E=1.35). The top three coexisting diseases were "hypertension+arthritis+dyslipidemia" (10.31%, O/E=1.70), "hypertension + dyslipidemia + heart disease" (9.70%, O/E=2.65), and "arthritis + stomach disease + hypertension" (9.49%, O/E=1.42). Agglomeration hierarchical cluster analysis was divided into clusters according to malignant tumors, emotional and mental diseases, " stroke + memory related diseases + Parkinson’s disease", "dyslipidemia + diabetes + hypertension + heart disease", "chronic lung disease + asthma + stomach disease + arthritis + liver disease +kidney disease", forming a multimorbidity model.

The overall prevalence of chronic diseases among elderly people in China is increasing year by year, and there is a clustering trend.

To master the information of patients with convulsion epilepsy in phenobarbital in rural epilepsy prevention and management project of Heilongjiang Province, understand the reasons for the withdrawal, analyze the influencing factors, and provide reference for improving the patient retention rate and work quality.

From 2011 to 2020, 3 890 convulsion epilepsy patients received phenobarbital treatment in Heilongjiang Province, of which 807 patients were enrolled. For 807 patients, EpiData, EXCEL and SPSS 19.0 software were used for data entry, processing and statistical analysis of the influencing factors in the withdrawal group, including analysis of variance, univariate analysis, and multivariate survival analysis.

3 890 patients with convulsive epilepsy enrolled in phenobarbital treatment group in rural epilepsy project of Heilongjiang Province, 807 cases dropped out successively, the dropout rate was 20.75%, the primary factors contributing to dropout were relocation, noncompliance with medication, and self-perceived or actual remission. Multivariate Cox regression analysis showed that female patients (HR=1.278, 95%CI:1.112-1.468) were the risk factors for dropping out, and the probability of dropping out in female patients was 1.278 times that of male patients.

The withdrawal rate of phenobarbital epilepsy treatment in rural areas of Heilongjiang Province is relatively high. In the later management work, the publicity and education of epilepsy prevention and treatment knowledge should be strengthened to provide personalized treatment programs and improve the treatment efficiency, especially for female epilepsy patients.

To explore the effects of social support and resilience on bullied secondary school students and non-suicidal self-injury, and analyze the association between social support and resilience, so as to provide reference for preventing school bullying. Method In March 2023, three middle schools in Jiangxi Province were used as site sites to investigate the current situation using self-made general situation questionnaire, Olweus Bully questionnaire, social support scale for adolescents，cognitive emotion regulation questionnaire (CERQ), Ottwa self-injury inventory questionnaire (OSI). To explore the role of social support and resilience in the chain mediation between bullying victimization and non-suicidal self-injury.

The report rate of bullying victimization was 18.56%, and the detection rate of non-suicidal self-injury was 34.4%. Bullying victimization and NSSI were negatively correlated with social support and resilience (r=-0.34 - -0.16, P<0.001), bullying victimization was positively correlated with NSSI (r=0.18, P<0.001), and social support was positively correlated with resilience (r=0.66, P<0.001). The results of mediating effect analysis showed that the simple mediating effect of social support between bullied and non-suicidal self-injury was 0.036 (95%CI:0.014-0.064), and the chain mediating effect of social support and resilience was 0.029 (95%CI: 0.011-0.056).

The bullying experience of secondary school students positively increases the risk of non-suicidal self-injury, and social support and resilience play chain mediating roles in this process. Improve the social support and resilience of secondary school students to reduce the non-suicidal self-injury behavior related to school bullying.

To construct a postpartum depression risk prediction model for multi-ethnic population in Yunnan Province of China, and identify predictive factors.

Women who were 42 days and within 1 year after childbirth were screened, and the Edinburgh Postnatal Depression Scale (EPDS≥9) was used for postpartum depression. 52 influencing factors from economics, social psychology, obstetrics, neonatology, spouse and family dynamics and other characteristics were included in the survey. A random forest algorithm was employed to construct a predictive model for postnatal depression risk in the multi-ethnic population of Yunnan Province. The model was evaluated on test sets with accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (Area Under Curve, AUC) to assess its performance.

A total of 459 women were analyzed, with a postpartum depression detection rate of 11.55%. Among them, the detection rates for Han, Zhuang and other ethnic minorities were 7.56%, 13.94% and 13.92%, respectively. The top 14 variables in terms of importance scores were: anxiety, history of previous negative emotions, marital relationship, family support level, physical and mental exhaustion in caring for newborns, pregnancy risk classification, mother-infant rooming-in, feeding mode, education level, spouse’s education level, frequency of nighttime newborn care, ethnicity, parity and age. The accuracy was 92.74%, specificity was 95.50%, sensitivity was 69.23%, positive predictive value was 64.29%, negative predictive value was 96.36%, and the AUC value was 0.925, using Han, Zhuang, and other ethnic minorities as validation sets respectively. The model also demonstrated good stability.

The random forest algorithm-based postpartum depression risk prediction model for the multi-ethnic population in Yunnan performed well, which can be utilized to predict risk factors for postpartum depression among women in minority ethnic areas, thereby facilitating targeted intervention measures.