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Background: Exposure to heavy metals considered a major risk factor for mental health., Objective: Examining how heavy metals in blood are associated with depression in individuals of various body mass indexes., Methods: A total sample of 15,560 individuals was screened, with 4355 participants finally enrolled to study. The PHQ-9 was used to assess participants' depressive symptoms., Results: A logistic regression analysis was used to investigate the relationship between the levels of heavy metals in the blood and the depression. Serum cadmium levels were found to be associated with risk of depression, with an odds ratio of 2.247 (95 % CI: 1.584-3.244). However, no significant correlations were observed between depression and blood levels of lead, selenium, and manganese. Subgroup analysis was performed and found that higher Cd concentrations were associated with a greater risk of depression at the same BMI. With the same Cd concentration, the risk of depression was lowest when participants' BMI was ≥30 kg/m 2 and increased with increasing BMI when participants' BMI was <30 kg/m 2 ., Limitations: It is not possible to analyze the effect of external exposure to Cd., Conclusion: Cd in blood may be positively correlated with depression in American adults, and the effect of this trend is different in people with different body mass indices. With the increase in BMI, the risk gradually rises. However, it is lowest among obese people., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Internet addiction of adolescents has aroused social concern recently. The present study aims to identify predicting factors of internet addiction on adolescents., Methods: The demographic characteristics and psychological characteristics of 50, 855 middle school students were investigated through Internet Gaming Disorder Scale- Short Form(IGDS9-SF), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), Strengths and Difficulties Questionnaire-students (SDQS), 16-Item Version of the Prodromal Questionnaire (PQ-16), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), Multidimensional Peer Victimization Scale (MPVS), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and Connor-Davidson Resilience Scale (CD-RISC10) were used to analyze factors associated with internet addiction by Pearson correlation coefficient and multiple hierarchical regression., Results: IGDS9-SF, SABAS and BSMAS are positively correlated with SDQS, PQ-16, PHQ-9, GAD-7 and MPVS (r-values ranging from 0.180 to 0.488, p < 0.01). IGDS9-SF, SABAS and BSMAS are negatively correlated with WEMWB and CD-RISC (r-values ranging from -0.242 ~ -0.338, p < 0.01). Multiple hierarchical regression shown gender, one-child, twins, left-behind, rural, education (father), drink (father), smoke (father), CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 32.7 % of the variance in internet gaming disorder (IGD) (F = 1174.949, p < 0.001). Group (junior and senior), Gender, Age, One-Child, Twins, Village, Education (father), Drink (father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 28.9 % of the total variance in social media addiction (SMA) (F = 982.932, p < 0.001). Fifteen variables [Gender, Age, Twins, Left-behind, Residence, Residence, Education (mother), Drink(father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, PHQ-9, GAD-7 and MPVS] predicted 30.7 % of the variance in smartphone addiction (SA) (F = 1076.02, p < 0.001)., Conclusion: The present study found that demographic characteristics, family environment and psychosocial factors were associated with internet gaming addiction, social media addiction and smartphone addiction. Negative psychological factors (such as anxiety and depression) play an important role in different behavioral addictions., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD., Methods: A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3., Results: 25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm 3 , uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm 3 , uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions., Conclusion: Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD., (Copyright © 2022. Published by Elsevier B.V.)

Objectives: Previous studies have found that sleep problems are associated with psychotic experiences (PEs) across clinical designs, but many confounding factors from uncertain variables have been unclear in observational designs. The aim of the present study was to detect the genetic correlations and causal relationship between sleep-related traits and PEs using the largest current genome-wide association study (GWAS) summary statistics., Methods: GWAS results were obtained for positive PEs (N = 116,787-117,794) and sleep-related traits [insomnia complaints (N = 386,533), morningness (N = 345,552), sleep duration (N = 384,317), ease of getting up in the morning (N = 385,949), daytime napping (N = 386,577), daytime sleepiness (N = 386,548), and snoring (N = 359,916)]. Linkage disequilibrium score regression (LDSC) was used to investigate genetic correlations. Mendelian randomization (MR) was conducted on trait pairs with significant genetic associations., Results: We found that auditory hallucinations were significantly genetically correlated with insomnia complaints (rg = -0.27, p = 1.1 × 10 -3 ), sleep duration (rg = 0.21, p = 9.7 × 10 -3 ), and ease of getting up (rg = 0.31, p = 2 × 10 -4 ). Visual hallucinations and insomnia complaints were highly genetically correlated (rg = 0.36, p = 6.4 × 10 -5 ). Mendelian randomization indicated a unidirectional causal relationship between sleep duration with auditory hallucinations (β = -0.93, p = 7.9 × 10 -4 for sleep duration as the exposure). We used large GWAS summary statistics across the LDSC and MR programs to determine that sleep duration as exposure to increase the risk of auditory hallucinations., Conclusions: Taken together, these findings suggest that treatment of sleep problems should be considered as a higher priority for future mental health services., (Copyright © 2021. Published by Elsevier B.V.)