RESUMEN
Background: The relationship between daytime napping and depression remains debatable. Thus, a meta-analysis in this study was conducted to evaluate the relationship between daytime napping and depression. Methods: The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched up to February 2022, and the reference lists of the included studies were also retrieved. A random-effects model was used to estimate the combined effect size. Results: Nine studies with 649,111 participants were included in the final analysis. The pooled odds ratio (OR) was 1.15 (95% confidence interval: 1.01-1.31) with a significant heterogeneity (I 2 = 91.3%, P for heterogeneity <0.001), and the results demonstrated an increased risk of depressive symptoms among daytime nappers. Visual inspection of the funnel plot and Egger's and Begg's tests identified no obvious evidence of publication bias. Conclusion: This meta-analysis indicates that daytime naps are a predictor of depression. The effects of daytime napping on depression may vary depending on the characteristics of people, the pattern of naps, and the individual's sleep experience. The findings may have significant implications for future research on depression.
RESUMEN
Background: The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk. Methods: The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched for cohort studies up to May 2022, and the reference lists of the included studies were also retrieved. A random-effect model was used to estimate the combined effect size. Heterogeneity was assessed with the I 2 statistic. Potential publication bias was evaluated using a funnel plot and Begg's and Egger's tests. Results: The final analysis included 18 cohort studies with a combined total of 241,398 participants. The pooled risk ratio (RR) was 1.10 (95% confidence interval: 1.05-1.14), with significant heterogeneity (I 2 = 82.7%, P < 0.001). The results of subgroup analyses showed that the pooled RRs varied according to geographic locations, gender, age group, screen time in the control group, depression at the baseline, and whether the study was conducted during the COVID-19 pandemic. No obvious evidence of publication bias was found. Conclusion: This study indicates that screen time is a predictor of depressive symptoms. The effects of screen time on depression risk may vary based on the participant's age, gender, location, and screen time duration. The findings could have important implications for the prevention of depression.