Sexual violence against women remains problematic and highly prevalent around the world.

BACKGROUND: Sexual violence is far more prevalent in most societies than is usually suspected in daily life. However, no study has systematically summarized the global prevalence rate and the major outcomes of sexual violence against women. METHODS: We directed a wide-raging search in the PubMed, Embase, and Web of Science, catalogs since the beginning to December 2022 for relevant reports about the incidence of sexual fighting touching females. The occurrence frequency was assessed with a random-effects model. The heterogeneity was estimated with I 2 values. Differences by research features were assessed over subgroup evaluation and meta-regression. RESULTS: A total of 32 cross-sectional studies were included (a total of 19,125 participants). The pooled sexual violence rate was 0.29 (95% CI = 0.25-0.34). Subgroup analyses found that there was a higher rate of sexual violence against women in 2010-2019 period (0.33, 95% CI = 0.27-0.37), developing countries (0.32, 95% CI = 0.28-0.37), and interview (0.39, 95% CI = 0.29-0.49). The analysis found that more than half of women (0.56, 95% CI = 0.37-0.75) had post-traumatic stress disorder (PTSD) after experiencing sexual violence, and only a third of women considered seeking support (0.34, 95% CI = 0.13-0.55). CONCLUSIONS: Nearly one out of every three (29%) women around the world has been a victim of sexual violence in their life. This current study investigated the status and characteristics of sexual violence against women, which could provide an important reference for police and emergency health services management.

Tooth loss and the risk of cognitive decline and dementia: A meta-analysis of cohort studies.

Introduction: Epidemiological studies have shown that tooth loss may be associated with an increased risk of cognitive decline and dementia. However, some results do not show a significant association. Therefore, we performed a meta-analysis to evaluate this association. Methods: Relevant cohort studies were searched in PubMed, Embase, Web of Science (up to May 2022), and the reference lists of retrieved articles. The pooled relative risk (RR) and 95% confidence intervals were computed using a random-effects model (CI). Heterogeneity was evaluated using the I 2 statistic. Publication bias was evaluated using the Begg's and Egger's tests. Results: Eighteen cohort studies met the inclusion criteria. Original studies with 356,297 participants with an average follow-up of 8.6 years (ranging from 2 to 20 years) were included in this study. The pooled RRs of tooth loss on dementia and cognitive decline were 1.15 (95% CI: 1.10-1.20; P < 0.01, I 2 = 67.4%) and 1.20 (95% CI: 1.14-1.26; P = 0.04, I 2 = 42.3%), respectively. The results of the subgroup analysis showed an increased association between tooth loss and Alzheimer's disease (AD) (RR = 1.12, 95% CI: 1.02-1.23) and vascular dementia (VaD) (RR = 1.25, 95% CI: 1.06-1.47). The results of the subgroup analysis also showed that pooled RRs varied by geographic location, sex, use of dentures, number of teeth or edentulous status, dental assessment, and follow-up duration. None of the Begg's and Egger's tests or funnel plots showed evidence of publication bias. Discussion: Tooth loss is associated with a significantly increased risk of cognitive decline and dementia, suggesting that adequate natural teeth are important for cognitive function in older adults. The likely mechanisms mostly suggested include nutrition, inflammation, and neural feedback, especially deficiency of several nutrients like vitamin D.

Daytime naps and depression risk: A meta-analysis of observational studies.

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.

Screen time and depression risk: A meta-analysis of cohort studies.

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.