Observational studies suggest that insomnia might be associated with an increased risk of depression with inconsistent results. This study aimed at conducting a meta-analysis of prospective cohort studies to evaluate the association between insomnia and the risk of depression. Relevant cohort studies were comprehensively searched from the PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases (up to October 2014) and from the reference lists of retrieved articles. A random-effects model was used to calculate the pooled risk estimates and 95 % confidence intervals (CIs). The I 2 statistic was used to assess the heterogeneity and potential sources of heterogeneity were assessed with meta-regression. The potential publication bias was explored by using funnel plots, Egger’s test, and Duval and Tweedie trim-and-fill methods. Thirty-four cohort studies involving 172,077 participants were included in this meta-analysis with an average follow-up period of 60.4 months (ranging from 3.5 to 408). Statistical analysis suggested a positive relationship between insomnia and depression, the pooled RR was 2.27 (95 % CI: 1.89–2.71), and a high heterogeneity was observed (I 2 = 92.6 %, P < 0.001). Visual inspection of the funnel plot revealed some asymmetry. The Egger’s test identified evidence of substantial publication bias (P <0.05), but correction for this bias using trim-and-fill method did not alter the combined risk estimates. This meta-analysis indicates that insomnia is significantly associated with an increased risk of depression, which has implications for the prevention of depression in non-depressed individuals with insomnia symptoms.

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 I² 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 (I² = 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.

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 I² 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, I² = 67.4%) and 1.20 (95% CI: 1.14–1.26; P = 0.04, I² = 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.

Non-adherence to tuberculosis (TB) treatment threatens the success of treatment, increases the risk of TB spread, and leads to the development of drug resistance. The present study assessed non-adherence to anti-TB treatment among internal migrants with pulmonary TB living in Shenzhen, China, and examined risk factors for non-adherence in order to identify targets for intervention. A total of 794 internal migrants with TB treated at Bao’an Hospital for Chronic Disease Prevention and Cure, Shenzhen, were recruited. Structured questionnaires were used to collect data on these patients’ history and experiences with TB treatment. Ordinal logistic regression model were used to identify risk factors for non-adherence. The proportion of patients who had missed one dose of medication within two weeks was 93/794 (11.71%), and those who missed at least two doses of medication within two weeks was 167/794 (21.03%), with a total of 33.74% of patients not adhering to TB treatment. Lack of knowledge about TB treatment and longer travel time to the nearest community health centers are significant predictors for non-adherence. The present study shows that non-adherence is common among internal migrants with TB. Patients who lack knowledge about TB treatment or have to travel far to get treated are prone to miss one or more doses of medication. Interventions to improve health education and healthcare access are essential to reduce non-adherence to TB treatment among internal migrants.

Background: Empirical evidence on patients’ trust and the factors among primary care institutions (PCIs) in China is limited. This study aimed to investigate patients’ trust and explore some associated factors among PCIs in the central region of China. Methods: The data was collected through a multistage stratified sampling method with a structured self-administered questionnaire, which was distributed from January to March 2021 among 2,287 Chinese patients ever involved in seeking healthcare among PCIs. Patients’ trust was measured with the Chinese version of the Wake Forest Physician Trust Scale (C-WFPTS). Differences in C-WFPTS scores among groups were estimated by t-tests or ANOVA analyses. Multiple linear regression analysis was used to analyze influencing factors for patients’ trust in primary care physicians. Results: Based on the C-WFPTS with a full score of 50, the average score of patients’ trust was 34.19 (SD = 5.83). Multiple linear analyses indicated that the patients who were older aged, married, with education of higher level, living in urban regions, under better health status and with a family doctor contract reported a higher level of patients’ trust. Conclusion: Patients’ trust in primary care physicians was at a medium but slightly improved level in the central region of China. Age, marital status, education, residential area, health status, and a family doctor contract were significant predictors of patients’ trust.