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Background: Depressive symptoms are a serious public mental health problem, and dietary intake is often considered to be associated with depressive symptoms. However, the relationship between the quality of dietary carbohydrates and depressive symptoms remains unclear. Therefore, this study aimed to investigate the relationship between high and low-quality carbohydrates and depressive symptoms and to attempt to construct an integrated model using machine learning to predict depressive symptoms., Methods: A total of 4982 samples from the National Health and Nutrition Examination Survey (NHANES) were included in this study. Carbohydrate intake was assessed by a 24-h dietary review, and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ9). Variance inflation factor (VIF) and Relief-F algorithms were used for variable feature selection., Results: The results of multivariate linear regression showed a negative association between high-quality carbohydrates and depressive symptoms (β: -0.147, 95 % CI: -0.239, -0.056, p = 0.002) and a positive association between low-quality carbohydrates and depressive symptoms (β: 0.018, 95 % CI: 0.007, 0.280, p = 0.001). Subsequently, we used the XGboost model to produce a comprehensive depressive symptom evaluation model and developed a corresponding online tool (http://8.130.128.194:5000/) to evaluate depressive symptoms clinically., Limitations: The cross-sectional study could not yield any conclusions regarding causality, and the model has not been validated with external data., Conclusions: Carbohydrate quality is associated with depressive symptoms, and machine learning models that combine diet with socioeconomic factors can be a tool for predicting depression severity., Competing Interests: Declaration of competing interest We have no conflicts of interest to declare., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: According to data from the National Health Commission in 2018, more than 30 million children and adolescents in China suffered from mental health problems of varying degrees, with depression accounting for the largest proportion. Life events occur at every stage of child and adolescent development. Many studies have found a relationship between life events and depression in children and adolescents, but few studies have further explored the mediating and moderating variables that influence this relationship. Based on theoretical and empirical research on social support and cognitive styles, this study established a two-stage moderated mediating model to test whether social support mediates life events to depression, and cognitive style moderates the two mediating pathways., Methods: We recruited 3540 participants from primary and secondary schools in Chongqing and collected 2814 valid data. All the participants completed self-report measures of life events, depression, social support and cognitive styles. The moderated mediation model was examined using SPSS PROCESS model 58., Results: (1) There were significant positive correlations between life events and depression. (2) Social support mediates the relationship between life events and depression in children and adolescents. (3) Cognitive style moderates life events to social support and social support to depression., Limitations: This is a cross-sectional study and the questionnaire is self-reported., Conclusions: In children and adolescents, life events can influence depression through the mediating role of social support and cognitive styles could moderate its two mediating pathways., (© 2022. The Author(s).)

ObjectiveTo understand the relationship between depression and mental health literacy or the attitude towards mental illness among grassroots administrators， in order to provide a reference for further improving mental health services and building a psychosocial service system.MethodsIn October 2020， a total of 690 grassroots administrators from street offices in Licheng district of Ji'nan city were selected as the research subjects. Self-designed general situation questionnaire， mental health care knowledge questionnaire， mental illness related attitude questionnaire and Self-rating Depression Scale （SDS） were used to evaluate. Multi-factor linear stepwise regression analysis was used to explore the influencing factors of mental health literacy and attitude towards mental illness among the grassroots administrators.ResultsA total of 248 people （37.07%） were found to have depression. There were significant differences in the detection rate of depression among different ages （χ2=16.110）， education level （χ2=18.949）， marital status （χ2=8.611） and position （χ2=11.584） （P˂0.05 or 0.01）. In such personnel， the score of mental health care knowledge questionnaire was （15.20±2.77）， the awareness rate was 75.99%， and the score of mental illness related attitude questionnaire was 36（31~38）. The severity of depression was negatively correlated with the score of mental health care knowledge questionnaire （r=-0.379， P˂0.01）， and positively correlated with the scores of mental illness related attitude questionnaire （r=0.103， P=0.007）. Regression analysis showed that the education level （β=0.141， P˂0.01） and the severity of depression （β=-0.305， P˂0.01） were the influencing factors of mental health literacy. And the severity of depression （β=0.083， P=0.034） was the influencing factor of the attitude towards mental illness.ConclusionGrassroots administrators has a high detection rate of depression. And the more depressed they are， the lower the mental health literacy， but the attitude of mental illness is more positive.

Objective To explore the change trend and pattern of sleep quality in time dimension in high-altitude recruits during new training, and the longitudinal moderation of negative cognitive processing bias in the process of depression affecting sleep quality. Methods A self-designed demographic data questionnaire, Pittsburgh Sleep Quality Index (PQSI), Negative Cognitive Processing Bias Questionnaire and Self-Rating Depression Scale were used to survey 952 cluster-sampled military recruits during training period who served in high-altitude regions along the Qinghai-Tibet Supply Line. Group assessment was performed in 1, 2 and 3 months after new training. The score for depression at the first month and the score of negative cognitive processing bias at the second month were collected and used to predict the sleep quality at the end of the 3 months of new training. Results The military recruits had a mean score of PSQI of 4.45± 2.44, 4.01±2.15 and 4.45±2.54, respectively in the 3 time points, significantly higher than the national norms for Chinese (P < 0.01). Their sleep quality showed a trend of improving first and then decreasing with the extension of training time (P < 0.01). Nationality, age and educational level significantly affected the sleep quality (P < 0.05). The total PSQI score was positively correlated with educational level, depressed mood, negative cognitive processing bias and its dimensions among these individuals (r=0.131~0.330, P < 0.01). Regulatory effect analysis showed that negative memory bias could modulate the relationship between depression and sleep quality (t=2.498, P < 0.05), and explained 15.7% of the variance rate of sleep quality. Conclusion The recruits serving in high-altitude regions have a severe sleep quality. Nationality, age, educational level, depression and negative cognitive processing bias are important factors affecting the sleep quality in them during new training. Negative memory bias has a significant longitudinal moderate effect between depression and sleep quality and is a risk factor of depression affecting sleep quality, in long-term risk effectiveness.

Objective To explore the characteristics of the longitudinal changes of emotional regulation strategies and their value in predicting depression in military personnel serving in high-altitude regions. Methods We followed up 4 665 military personnel serving in high-altitude regions along the Qinghai-Tibet Supply Line for 3 consecutive years (2016-2018). Emotion Regulation Questionnaire for Armymen (AERTQ), Self-Rating Depression Scale (SDS), and Center for Epidemiologic Studies Depression Scale (CES-D) were used to assess the strategies of emotion regulation and the depressive state of these individuals. After excluding the individuals withdrawn from the study (due to mobilizations for missions, discharge from service or personal reasons), we recruited 202 subjects for data analysis. Results Among the military personnel, the scores for emotional regulation strategies were the highest for self-comfort, followed by seeking emotional help, cognitive attention and behavioral inhibition (P < 0.05); the scores were relatively stable over the 3-year period of the study. The scores for emotion regulation strategies increased year by year, and the score for enhanced emotion regulation recorded a significantly greater increase than that of weakened emotion regulation (P < 0.05). The degree of environmental adaptation was important factors affecting the strategies of emotional regulation (P < 0.05). The score for cognitive attention was capable of predicting a depressive state within 2 years, and the score of self-comfort had a predictive value within 1 year (P < 0.05). Conclusion Among the military personnel serving in high-altitude regions, emotional regulation shows a transition from a predominantly weakened to an enhanced strategy, suggesting a negative trend of changes. Adaptability affect the strategies adopted for emotional regulation, which can be predictive of the depressive state in these military personnel.

Objective To explore the trend and the pattern of temporal changes of depressive symptoms and the association of mental toughness and demographic characteristics with the severity of depression in military personnel serving in high-altitude regions. Methods In August of 2016, 2017 and 2018, we conducted 3 group assessments of 212 military personnel serving in high-altitude regions along the Qinghai-Tibet Supply Line by cluster sampling using a self-designed demographic data questionnaire, Center for Epidemiologic Studies Depression Scale and Mental Quality Questionnaire for Armymen. The scores for mental toughness of the subjects in the 2016 assessment and the demographic data collected in 2017 were used to predict the scores of depressive symptoms of the subjects in 2018. Results In the years of 2016, 2017, and 2018, the military personnel had mean depression symptom scores of 13.61±7.62, 13.65±6.36 and 21.87±10.61, respectively, significantly higher than the national norms for Chinese youth (P < 0.05). The incidence of depressive symptoms was significantly higher in these military personnel than the norm in Chinese soldiers (P < 0.01), and their depressive symptoms showed a significant trend of aggravation with the extension of military service time (P < 0.01). Age and the length of military service time significantly affected the depressive symptoms (P < 0.05); age, time of military service and mental toughness showed significant negative correlations with depressive symptom scores among these individuals (r=-0.245 to -0.287, P < 0.001). Regulatory effect analysis showed that age could modulate the relationship between mental toughness and depressive symptoms (t=-1.768, P < 0.05), and explained 17.1% of the variance rate of depressive symptoms. Conclusion The military personnel serving in high-altitude regions have a high incidence of depression and severe depressive symptoms. Age, time of military service and mental toughness are important factors affecting the depressive symptoms. Age can modulate the relationship between mental toughness and depressive symptoms, and an older age is associated with a better use of mental toughness to prevent depression, suggesting that improving mental toughness can alleviate depressive symptoms in these personnel.

Background: Depression is characterized by debilitating symptoms and high recurrence rates, and there are relatively few large-scale epidemiological surveys of depressive disorders conducted in Shandong since 2005. Data from the largest Epidemiological Survey of Mental Disorders conducted in 2015 in Shandong were collected to investigate the prevalence of depressive disorders and associated demographic characteristics in general adult population.Methods: A multi-stage stratified cluster sampling method was adopted to select residents and a two-stage screening and assessment process was used to define the prevalence and characteristics of depressive disorders. Respondents were initially screened using the General Health Questionnaire followed by a structured clinical interview using the DSM-IV criteria.Results: Among 27,489 respondents who completed the survey, 1277 respondents met the diagnostic criteria for depressive disorders. The adjusted prevalence in the last month was 4.86%, among which the prevalence of major depressive disorder, dysthymia, and unspecified depressive disorder were 2.32%, 1.78%, and 0.75%, respectively. 40.35% of depression patients had moderate or severe functional impairment and only 10.65% of patients had visited a psychiatric service. Univariate and multivariate analyses revealed that age, gender, occupation, education, marital status, and urban/rural living were associated with the prevalence.Limitations: The key limitation is that this is a cross-sectional survey therefore cannot draw any causal relationship between risk factors and disease progression.Conclusions: Findings from this largest epidemiological study reveal current prevalence of depressive disorders and associated demographic factors and offers opportunities for policy makers and health-care professionals to improve mental health provision in Shandong. [ABSTRACT FROM AUTHOR]