Objective: To investigate the influencing factors of depressive symptoms and to construct and verify the prediction model of depressive symptoms in middle school students, so as to provide risk assessment tools for effectively screening depressive symptom. Methods: Physical examination and questionnaire survey were conducted among middle school students in one city in Guangdong Province from September to October in 2021 ( n =2 376) and from September to October in 2022 ( n =4 344) by a multistage cluster sampling method, and a nomographic prediction model of depressive symptoms in middle school student was constructed. The questionnaire survey was conducted using the student health status and influencing factors questionnaire (secondary school version) and the Center for Epidemiological Studies Depression Scale (CES-D) to measure the lifestyle and depressive symptom of middle school students. Results: The detection rate of depressive symptoms in 2021 was 23.3%. Multivariate Logistic regression analysis showed that irregular breakfast ( OR =2.64), school bullying ( OR =4.28), being beaten by parents ( OR =2.86), using mobile devices for a long time ( OR =1.08) and sitting for a long time ( OR =1.05) were positively related to depressive symptoms in middle school students ( P <0.05). Long sleep duration ( OR =0.78) and outdoor activity durations of 1-<2, 2-<3 and ≥3 h/d (compared with <1 h/d, OR =0.63, 0.61, 0.49) were negatively related to depressive symptoms in middle school students ( P < 0.05 ). Multivariate Logistic regression analysis showed that 7 statistically signifucant predictive factors constructed a nomogram, and the AUC of the nomogram was 0.77, which had been verified internally and externally with good differentiation and reliability. Conclusions The nomogram prediction model of depressive symptoms provides a convenient and effective risk assessment tool for depressive symptoms among middle school students. The life behavior, diet behavior and injury behavior of middle school students play an important role in the formation of depressive symptoms. It should pay attention to the impact of the behavioral factors on the mental health of middle school students.

BackgroundDementia seriously affects the quality of life and lifespan of elderly people， with Alzheimer's disease （AD） being the most common type of dementia. Previous studies have suggested that gout may reduce the risk of developing AD， but the causal relationship between the two still requires further research. ObjectiveTo investigate the potential causal relationship between gout and AD through a two-sample Mendelian randomization （MR） analysis， so as to provide references for the prevention and treatment of AD. MethodsData from Genome-Wide Association Studies （GWAS） extracted in 2024 were analyzed， using pooled data on gout （6 810 cases in the case group and 477 788 cases in the control group） published by UK Biobank in 2021 as the exposure variable， and data on AD （3 899 cases in the case group and 214 893 cases in the control group） published by FinnGen in the same year as the outcome variable. The inverse-variance weighted， MR-Egger regression， weighted median estimation， simple model and weighted model were used to analyze the potential causal relationship between gout and AD. Pleiotropic effects were assessed using MR-Egger regression. Heterogeneity assessment was conducted using Cochran's Q test. The leave-one-out analysis was carried out for sensitivity analysis. And a funnel plot was drawn to detect potential publication bias. ResultsThe inverse-variance weighted analysis demonstrated a negative causal relationship between gout and AD （OR=0.004， 95% CI： 0~0.700， P<0.05）. The plot resembled a symmetrical inversed funnel， indicating the absence of publication bias. No heterogeneity was detected by Cochran's Q test. The MR-Egger regression indicated no significant horizontal pleiotropy. Concerning the reverse directions， no significant associations between AD and gout were noted. ConclusionThere is a negative causal relationship between gout and AD， with gout potentially reducing the risk of developing AD. ［Funded by The Third Batch of Social Welfare and Basic Research Projects （Medical and Health） of Zhongshan City in 2022 （number， 2022B3017）］