Sha Sha

Background Pre-existing cognitive dysfunction and poor daily functioning are associated with the risk of developing dementia. However, the associations of specific cognitive domains and daily functioning with the incidence of dementia remain inadequately studied. This study examined the associations of cognitive function and daily functioning with subsequent development of dementia among older Chinese adults over an eight-year follow-up period. Method The study was based on the China Health and Retirement Longitudinal Study Life History Survey (CHARLS) data from 2013 to 2020. Cognitive function was assessed across executive function and episodic memory domains. Daily functioning was measured with five items adapted from the Instrumental activities of daily living (IADL) scale. The outcome was incident dementia identified during the follow-up period. Generalized logistic model and network outcome analysis were performed to examine the associations of specific cognitive functions and daily functioning with incident dementia. Result Among 9182 participants included in the study, the incidence of dementia was 5.3% during the follow-up period. Both decreased cognitive function [OR: 0.95 (95% CI: 0.92–0.99)] and daily functioning [OR: 0.70 (95% CI: 0.64–0.77)] at baseline were associated with increased risk of dementia. The network outcome analysis indicated that IADL2 (preparing hot meals), IADL5 (taking medicine), episodic memory, and IALD3 (shopping) negatively predicted subsequent development of dementia. Conclusion Older adults with decreased cognitive function and daily functioning have an increased risk of dementia in later life. Appropriate interventions to address IADL2, IADL3, IADL5 and episodic memory function may be potentially useful in reducing the risk of dementia.

Background The high prevalence of poor sleep quality (PSQ) in the general population leads to negative health outcomes. Since estimates of PSQ prevalence in the Chinese general population vary widely, this meta-analysis aimed to refine these estimates and to identify moderating factors. Methods A comprehensive literature search was undertaken in both international (PubMed, PsycINFO, Web of Science, and EMBASE) and Chinese (Wanfang, and the China National Knowledge Infrastructure databases) databases from inception to 23 November 2023. Studies were required to have used standard scales such as the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). The pooled prevalence of PSQ and 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup and meta-regression analyses were performed to identify sources of heterogeneity. Results In 32 studies with a combined 376,824 participants, the pooled prevalence of PSQ was 19.0% (95% CI 15.8–22.8%; range 6.6–43.6%). Across 22 studies that reported PSQI data, the pooled mean score was 4.32 (95%CI 3.82–4.81; SD = 0.502). The pooled mean sleep duration across 8 studies was 7.62 (95% CI 7.23–8.00; SD = 0.194) hours. Subgroup analyses showed that lower education (Q = 4.12, P = 0.042), living in less developed regions (Q = 60.28, P < 0.001), and lower PSQI cutoff values (Q = 9.80, P = 0.007) were significantly associated with PSQ. Meta-regression analyses showed that study quality was inversely associated with estimated PSQ prevalence (β = − 0.442, P = 0.004). Limitations Although measures such as subgroup and meta-regression analyses were performed, substantial heterogeneity remained. Information related to sleep quality, such as comorbid physical diseases or psychiatric disorders, substance use, occupational types, and employment status, were not reported in most studies. Conclusion One in five people in the general population of China may have PSQ and people with lower education or living in western regions may be more susceptible.

To assess the inter-relationships between residual depressive symptoms (RDS) and Internet addiction (IA) using network analysis among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. RDS and IA were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Internet Addiction Test (IAT), respectively. Central symptoms and bridge symptoms in the network model were examined. A total of 1,454 adolescents met the study criteria and were included in the analyses. The prevalence of IA was 31.2% (95% CI: 28.8%-33.6%). In the network analysis, the nodes IAT15 (“Preoccupation with the Internet”), PHQ2 (“Sad mood”), and PHQ1 (“Anhedonia”) were the most central symptoms in the IA-RDS network model. Bridge symptoms included IAT10 (“Sooth disturbing about your Internet use”), PHQ9 (“Suicide ideation”), and IAT3 (“Prefer the excitement online to the time with others”). Additionally, PHQ2 (“Sad mood”) was the main node linking “Anhedonia” to other IA clusters. Internet addiction was common among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. Core and bridge symptoms identified in this study could be prioritized as targets for the prevention and treatment of IA in this population.