To clarify the current status of diabetes management and services in primary healthcare institutions, explore the factors influencing their diabetes service capacity, and provide theoretical references for enhancing this capacity.

In-depth interviews were conducted involving 28 participants, including administrators, medical staff, and diabetic patients from four primary healthcare institutions in a district of Chengdu. Grounded theory was employed to summarize and refine the factors affecting diabetes service capacity in these institutions.

Through three-level coding, 24 initial categories, 7 main categories, and 3 core categories were identified, leading to the construction of a theoretical framework for the"Influencing Factors Model of Diabetes Service Capacity in Primary Healthcare Institutions." The current status of the sample institutions was analyzed across three dimensions: resource allocation, policy support, and daily operations.

The diabetes service capacity of primary healthcare institutions in the studied district of Chengdu is influenced by resource allocation, policy support, and daily operations. To enhance this capacity, measures such as strengthening daily operations, improving policy support mechanisms, and optimizing the allocation of human and material resources should be implemented.

To explore the effects of self-rated health and self-care ability, as well as their interaction, on depression symptoms in the elderly.

Based on data from the 2020 China Health and Retirement Longitudinal Study, relevant data from 8 948 individuals aged 65 and above were collected. Statistical analyses were conducted using chi-square tests and multivariate logistic regression, followed by interaction analysis using an additive model.

Among the elderly, 3 616 (40.41%) exhibited depression symptoms. After adjusting for gender, age, education level, marital status, living area, exercise habits, and sleep conditions, the regression model indicated that self-rated health (OR=2.60, 95%CI: 2.34-2.89) and self-care ability (OR=2.32, 95%CI: 2.10-2.56) were independent risk factors for depression symptoms in the elderly (P<0.001). The interaction analysis revealed a synergistic additive interaction between self-rated health and self-care ability (OR=5.98, 95%CI: 5.27-6.79),with the excess relative risk, attributable proportion of interaction, and interaction index being 1.92 (95%CI: 1.65-2.71), 0.32(95%CI: 0.21-0.41), and 1.63 (95%CI: 1.34-1.97), respectively.

Poor self-rated health and impaired self-care ability both increase the risk of depression in the elderly, and there is a synergistic additive interaction between the two. Efforts to prevent and treat depression in the elderly should focus on improving their self-rated health and self-care ability.

To explore the bidirectional relationship between depression symptoms and physical functional impairment trajectories in Chinese elderly individuals.

Utilizing data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, we employed group-based trajectory modeling to identify distinct trajectory groups for depression symptoms and physical functional impairment among the elderly. A dual trajectory model was then used to assess the degree of association between these trajectory groups.

The group-based trajectory model categorized depression symptoms into four groups: consistently low depression symptoms, decreasing depression symptoms, increasing depression symptoms, and consistently high depression symptoms. Physical functional impairment was classified into four groups: no physical functional impairment, worsening physical functional impairment, improving physical functional impairment, and high physical functional impairment. Dual trajectory analysis revealed that 44.86% of individuals in the decreasing depression symptoms group followed the improving physical functional impairment trajectory; conversely, 37.58% of individuals in the increasing depression symptoms group followed the worsening physical functional impairment trajectory. Among those in the worsening physical functional impairment group, 47.8% followed the increasing depression symptoms trajectory, while 41.9% of individuals in the improving physical functional impairment group followed the decreasing depression symptoms trajectory.

In most cases, there is a positive correlation between the trajectories of depression symptoms and physical functional impairment. A decrease in depression symptoms is typically associated with an improvement in physical functional impairment, while an increase in depression symptoms corresponds with a worsening of physical functional impairment, and vice versa.

To explore the association between blood pressure levels and the risk of stroke-related death in type 2 diabetic population.

A survey was carried out on 9 708 type 2 diabetic patients who participated in the chronic disease patient health management of basic public health services in Huai’an District and Qing jiang pu District (former Qing he District) of Huai’an city. Multivariate proportional-hazards Cox regression analysis was used to analyze the association between blood pressure levels and the risk of stroke-related death in type 2 diabetic patients, and further stratified analysis was carried out according to smoking, body mass index (BMI), central obesity, and dyslipidemia respectively. The follow-up duration was calculated from December 31, 2013 to December 31, 2020, and death from stroke (I60-I69) was defined as the end-point event.

The follow-up duration was 63 833.8 person-years, and the stroke death density was 5.4 per 1 000 person-years. After adjusting for relevant confounding factors, taking the normal blood pressure group as the reference, the HR value of the stroke-related death risk in the grade III hypertension group was 4.45 (95%CI: 2.09-9.48). The stratified analysis results showed that compared with the normal blood pressure group, among smokers, those with BMI ≥ 24.0 kg/m², those with central obesity, and those with dyslipidemia, the stroke-related death risks in the grade III hypertension group increased by 3.12 (HR=4.12, 95%CI:1.16-14.67), 1.97 (HR=2.97, 95%CI: 1.26-7.00), 3.19 (HR=4.19, 95%CI: 1.27-13.86), and 5.49 (HR=6.49, 95%CI: 1.97-21.43) times, respectively. Sensitivity analysis was carried out by excluding the baseline stroke patients, participants who died in the first year of follow-up, and those over 80 years old, and a significant positive relationship between blood pressure levels and the risk of stroke-related death was found.

Elevated blood pressure levels will increase the risk of stroke-related death in type 2 diabetic patients, and there is a positive relationship between blood pressure levels and the risk of death. Among type 2 diabetic patients, those with low BMI have a higher risk of stroke-related death than those with high BMI.

To analyze the trends and characteristics of the number of patients, prevalence, incidence, disability-adjusted life years (DALY), and years lived with disability (YLD) of depressive disorders among the Chinese population from 1990 to 2021, with the hope of providing a theoretical basis for early prevention, intervention, and clinical decision-making regarding depressive disorders.

Depressive disorders data from the GBD 2021 database (Global Burden of Disease Study 2021 Data Resources) were extracted to analyze the number of patients, incidence, prevalence, DALY and YLD in the Chinese population. The software STATA 14.0 and Joinpoint Regression Program 4.8.0.1 were utilized to analyze the incidence, prevalence, DALY, and YLD of depressive disorders across different genders and age groups. Furthermore, the average annual percent change (AAPC) in depressive disorders was calculated.

In 2021, there were 42.3602 million new cases of depressive disorders in China, an increase of 38.9% from 30.4910 million in 1990. The number of patients was 53.1147 million, an increase of 54.0% from 34.4794 million in 1990. Both the standardized incidence and prevalence showed a slow downward trend (the AAPC was -0.57% and -0.44%, respectively, P<0.001). The incidence of depressive disorders in people aged 10 to 24 showed a sudden increase in different years, and the incidence of depressive disorders in people over 65 also showed an accelerating upward trend. The DALY in 1990 and 2021 were 5.4267 million and 7.8659 million person-years, respectively, with a cumulative increase of 44.9%. The DALY rate increased from 461.27 /100 000 to 552.87 /100 000, with an increase of 19.8%. The standardized DALY and YLD rates decreased slowly with each year (the AAPC was -0.53% and -0.53%, respectively, P<0.001).

Depressive disorder is still one of the main causes of global disease burden and a major public health issue facing our country. There is an urgent need to actively explore and implement effective prevention and treatment strategies to reduce the disease burden of depressive disorders.

Toconstruct a Genetic Algorithm optimized Support Vector Machine (GA-SVM) model based on multi-source data predicting acute respiratory infectious diseases and toevaluate its predictive effectiveness, providing a reference for establishing an early warning system for respiratory infectious diseases.

Symptom surveillance cases, meteorological and atmospheric pollution, data and stringency index obtained from 2020 to 2022 were used as modeling and forecasting samples, respectively. By picking up the optimum lagging week number of the potential predictive variables and filter out the most important variables successively, the independent variables were obtained. Then the full time series data were divided into validation set and training set in a 1:4 ratio. The parameters were optimized by genetic algorithm. We used the weekly number of new cases of respiratory infectious diseases as the dependent variable to structure the GA-SVM model. The performance was evaluated based on the following metrics: root mean square error (RMSE), meansabsolute percentage error (MAPE), predictive correlation coefficient (PCC) and R-squared (R²).

The most important variables were stringency index with 2-weeks-lag, symptom surveillance cases with 1-week-lag, maximum temperature with 1-week-lag, school activities with 2-weeks-lag and O₃ index with 1-week-lag. The GA-SVM model performed best when C=18.04, γ=0.175 4 while average RMSE=6.362, average MAPE=24.59%, average PCC=0.896 and average R²=0.804.

The model showsgood predictive performance for the reported cases of acute respiratory infectious diseases in Xuhui District, which confirms the feasibility of applying GA-SVM to multi-source data based on symptom monitoring for predicting respiratory infectious diseases, providing methodological references for the application of multi-source data in the early warning of infectious diseases.

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 interaction between Body Mass Index (BMI) and sex on sleep quality of rural older adults in Chengdu, and to explore the differences in their sleep quality under different BMI and sex stratifications.

Based on the data of a cluster randomized controlled trial for rural older adults in Chengdu, 508 people aged 60 and above were involved. Questionnaires were administered using instruments such as the Pittsburgh Sleep Quality Index (PSQI) to collect information on sleep quality and demographics. Information of height and weight was obtained by physical measurements. Linear mixed models were used to analyze the interaction between BMI and sex on sleep quality, and stratified analyses were performed.

There was a significant interaction between BMI and sex on sleep quality (P<0.001). When stratified by sex, PSQI scores in the overweight and obese populations were significantly higher than the normal/underweight populationonly among the males. (difference=0.46, P=0.031; difference=1.53, P<0.001). When stratified by BMI, females had significantly higher PSQI scores than males in normal/underweight and overweight stratifications (difference=1.85, P<0.001; difference=2.17, P<0.001).

There is a significant interaction effect of BMI and sex on sleep quality among rural older adults. Comparing to males, females have poorer sleep quality in normal/underweight and overweight stratifications. Males have poorer sleep quality with higher BMI levels. Our study suggests that future sleep interventions and policy programs should be tailored according to different sex and BMI.

To explore the construction of the training system for preventive medical professionals and train high-level public health talents.

West China School of Public Health, Sichuan University, has deeply promoted the reform of talent education and teaching for undergraduate students in preventive medicine, exploring from aspects such as training objectives, curriculum and teaching material systems, practical ability training, and the cultivation of medical prevention integration capabilities. We have reconstructed the talent cultivation program, innovated the talent cultivation mode, and explored the new paradigm of cultivating top-notch and innovative talents for the preventive medicine specialty.

We have revised and completed the general training plan for public health and preventive medicine, constructed a modernized curriculum system of preventive medicine, strengthened the development and application of digital education, actively explored the in-depth cooperation with practice teaching bases, and taken the lead in the country in launching the innovative class of hospital infection management, the dual bachelor’s degree of preventive medicine and software engineering, and the micro-specialty of health insurance.

Under the strategic background of Healthy China, professional education of preventive medicine is the key path for the cultivation of public health talents in China. Colleges and universities should actively explore the innovation and development of the cultivation of preventive medicine professional talents, so as to contribute to the construction of Healthy China in the new era.

To explore the causal relationship between obstructive sleep apnea and atherosclerosis which is not clear through Mendelian randomization.

Genome-wide associations of different subtypes of obstructive sleep apnea and atherosclerosis were selected from the data published on the IEU Open GWAS (https://gwas.mrcieu.ac.uk/) website. Inverse variance weighting method (IVW), MR-Egger regression, simple model, weighted model and weighted median method were used to determine the causal correlation between them. A variety of sensitivity analysis and calculating F values were used to verify the accuracy of the results.

Five single nucleotide polymorphisms (Single nucleotide polymorphism, SNP) strongly associated with obstructive sleep apnea were included in the study, and the F values were all greater than 10. The results of IVW method showed that coronary atherosclerosis (OR:1.321,95%CI:1.150-1.518,P=8.3×10^-5) had significant statistical significance, while cerebral atherosclerosis(OR:0.331,95%CI:0.071-1.536,P=0.158) and peripheral atherosclerosis (OR:1.204,95%CI:0.962-1.508,P=0.106) had no statistical significance. The results of heterogeneity test, horizontal multiplicity analysis, sensitivity analysis and MR-PRESSO analysis made the causal relationship of Mendelian randomized analysis more reliable.

There is a causal correlation between obstructive sleep apnea and coronary atherosclerosis, and there is a positive correlation between obstructive sleep apnea and coronary atherosclerosis; there is no causal relationship between obstructive sleep apnea and cerebral atherosclerosis and peripheral atherosclerosis; reverse MR analysis found no causal correlation between selected atherosclerosis and obstructive sleep apnea.