The prevalence of alcohol consumption and its related factors in adolescents: Findings from Global School-based Student Health Survey.

BACKGROUND: Alcohol consumption has become very common among adolescents in recent years and its prevalence varies in different countries. This study aimed to investigate the prevalence of alcohol consumption and related factors in adolescents aged 11 to 16 years. METHODS: This descriptive cross-sectional study was performed on 288385 adolescents (girls, 53.9% of total) aged 11 to 16 years. In the present study, the GSHS data (2003-2018) available to public on the websites of the US Centers for Disease Control and Prevention (CDC) and WHO was used. To investigate the factors affecting alcohol consumption, univariate and multivariate logistics models with 95% confidence limits were used. RESULTS: The overall prevalence of alcohol consumption in adolescents was 25.2%, which was 28.3% and 22.4% in boys and girls, respectively. Among the surveyed countries, the highest prevalence was in Seychelles (57.9%) and the lowest in Tajikistan (0.7). Multivariate analysis showed that the Age for 16 and more than 16 years old (OR = 3.08,95%CI: 2.54-3.74), truancy for more than 10 days (OR = 1.24, 95%CI: 1.08-1.43), loneliness at sometimes of the times (OR = 1.04, 95%CI: 1.01-1.07), insomnia at most of the times (OR = 1.85, 95%CI: 1.70-2.01), daily activity (OR = 1.03, 95%CI: 1.00-1.07), bullied for 1-9 Days in a month (OR = 1.24, 95%CI: 1.09-1.40), cigarette (OR = 4.01, 95%CI: 3.86-4.17), used marijuana for more than 10 days in a month (OR = 5.58, 95%CI: 4.59-7.78), had sex (OR = 2.76, 95%CI: 2.68-2.84), and suicide plan (OR = 1.48, 95%CI: 1.42-1.54) were important factors affecting drinking alcohol. (Table 4). In this study, the sensitivity, specificity, positive predictive value, and negative predictive value were 42.79%, 93.96%, 70.80%, and 82.75. CONCLUSIONS: According to the results of the present study, the prevalence of alcohol consumption among teenagers was high. Therefore, it is suggested that demographic, family, and psychological factors should be taken into consideration in health programs for the prevention and treatment of alcohol consumption in adolescents.

Identification of Risk Factors to Predict the Occurrences of Relapses in Individuals with Schizophrenia Spectrum Disorder in Iran.

Schizophrenia Spectrum Disorder (SSD) is a chronic psychiatric disorder with a modest treatment outcome. In addition, relapses are commonplace. Here, we sought to identify factors that predict relapse latency and frequency. To this end, we retrospectively analyzed data for individuals with SSD. Medical records of 401 individuals with SSD were analyzed (mean age: 25.51 years; 63.6% males) covering a five-year period. Univariate and multivariate Penalized Likelihood Models with Shared Log-Normal Frailty were used to determine the correlation between discharge time and relapse and to identify risk factors. A total of 683 relapses were observed in males, and 422 relapses in females. The Relapse Hazard Ratio (RHR) decreased with age (RHR = 0.99, CI: (0.98-0.998)) and with participants' adherence to pharmacological treatment (HR = 0.71, CI: 0.58-0.86). In contrast, RHR increased with a history of suicide attempts (HR = 1.32, CI: 1.09-1.60), and a gradual compared to a sudden onset of disease (HR = 1.45, CI: 1.02-2.05). Gender was not predictive. Data indicate that preventive and therapeutic interventions may be particularly important for individuals who are younger at disease onset, have a history of suicide attempts, have experienced a gradual onset of disease, and have difficulties adhering to medication.

Application of Sparse Linear Discriminant Analysis and Elastic Net for Diagnosis of IgA Nephropathy: Statistical and Biological Viewpoints

Background: IgA nephropathy (IgAN) is the most common primary glomerulonephritis diagnosed based on renal biopsy. Mesangial IgA deposits along with the proliferation of mesangial cells are the histologic hallmark of IgAN. Non-invasive diagnostic tools may help to prompt diagnosis and therapy. The discovery of potential and reliable urinary biomarkers for diagnosis of IgAN depends on applying robust and suitable models. Applying two multivariate modeling methods on a urine proteomic dataset were obtained from IgAN patients, and comparison of the results of these methods were the purpose of this study. Methods: Two models were constructed for urinary protein profiles of 13 patients and 8 healthy individuals, based on sparse linear discriminant analysis (SLDA) and elastic net (EN) regression methods. A panel of selected biomarkers with the best coefficients were proposed and further analyzed for biological relevance using functional annotation and pathway analysis. Results: Transferrin, α1-antitrypsin, and albumin fragments were the most important up-regulated biomarkers, while fibulin-5, YIP1 family member 3, prasoposin, and osteopontin were the most important down-regulated biomarkers. Pathway analysis revealed that complement and coagulation cascades and extracellular matrix-receptor interaction pathways impaired in the pathogenesis of IgAN. Conclusion: SLDA and EN had an equal importance for diagnosis of IgAN and were useful methods for exploring and processing proteomic data. In addition, the suggested biomarkers are reliable candidates for further validation to non-invasive diagnose of IgAN based on urine examination.