Sleep, social media use and mental health in female adolescents aged 12 to 18 years old during the COVID-19 pandemic

Abstract Background Adolescents with high social media (SM) use experienced poor sleep quality and high anxiety and depression levels. The study aimed to investigate the characteristics of sleep, use of SM, mental health in female aged 12 to 18 years old, and to assess the association between poor sleep, SM usage, and mental health. Methods In total, 219 Thai female adolescents were recruited between December 2019 and September 2020 and completed self-administrative questionnaires three periods of time (baseline, 3 months and 6 months later). The questionnaires included: the Pittsburgh Sleep Quality Index (PSQI), depression screening (PHQ-9), Screen for Child Anxiety Related Emotional Disorders (SCARED). Demographic and use of social media data were also included. Cochran’s Q test, correlation coefficient, and binary logistic regression were performed. Results Participants’ mean age was 14.52 (range 12–17) years. Average Thai-PSQI global scores did not differ during 3 periods (p = 0.13) but average time of sleep latency, sleep duration, and SM usage were significant different (p = 0.002, p = 0.001, and p = < 0.001, respectively). There were positive correlations between PSQI scores and total SM usage at baseline (r = 0.14; P < 0.05) and 6 months (r = 0.20; P < 0.05). Anxiety, depression, and self-perception of poor sleep were significantly related to poor sleep quality during the 3 periods. After adjusting for confounding factors, depression and self-reported poor sleep were the only significant factors predicting poor sleep quality. Conclusions Poor sleep was associated with SM usage, depression, and anxiety in this population. Time-limited SM usage should be implemented for Thai female adolescents to improve sleep-related outcomes

Long-term multiple metabolic abnormalities among healthy and high-risk people following nonsevere COVID-19

Abstract Few studies have identified the metabolic consequences of the post-acute phase of nonsevere COVID-19. This prospective study examined metabolic outcomes and associated factors in nonsevere, RT-PCR-confirmed COVID-19. The participants’ metabolic parameters, the prevalence of long-term multiple metabolic abnormalities (≥ 2 components), and factors influencing the prevalence were assessed at 1, 3, and 6 months post-onset. Six hundred individuals (mean age 45.5 ± 14.5 years, 61.7% female, 38% high-risk individuals) with nonsevere COVID-19 attended at least one follow-up visit. The prevalence of worsening metabolic abnormalities was 26.0% for BMI, 43.2% for glucose, 40.5% for LDL-c, 19.1% for liver, and 14.8% for C-reactive protein. Except for lipids, metabolic-component abnormalities were more prevalent in high-risk hosts than in healthy individuals. The prevalence of multiple metabolic abnormalities at the 6-month follow-up was 41.3% and significantly higher in high-risk than healthy hosts (49.2% vs 36.5%; P = 0.007). Factors independently associated with a lower risk of these abnormalities were being female, having dyslipidemia, and receiving at least 3 doses of the COVID-19 vaccine. These findings suggest that multiple metabolic abnormalities are the long-term consequences of COVID-19. For both high-risk and healthy individuals with nonsevere COVID-19, healthcare providers should monitor metabolic profiles, encourage healthy behaviors, and ensure complete vaccination