Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities.

OBJECTIVE: Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities. METHOD: Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis. RESULT: The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects. CONCLUSION: The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

Bright light therapy has a positive effect on sleep quality in patients with cancer: A meta-analysis.

Cancer patients frequently encounter difficulties associated with suboptimal sleep quality. Bright Light Therapy (BLT), an innovative treatment approach, has shown promise in enhancing sleep quality. However, several literature reviews showed conflicting results, and more analysis should be conducted regarding detailed BLT settings on sleep. This meta-analysis was undertaken to comprehensively assess the impact of BLT on sleep quality among cancer patients. Twelve studies with 679 patients were included. Compared with the control group, BLT overall resulted in significant improvements in terms of sleep quality [g = -0.34], total sleep time [g = 0.24], wake after sleep onset [g = -0.80], and fatigue [g = -0.54]. However, it did not yield a statistically significant effect on sleep efficiency, sleep onset latency, and insomnia severity. Regarding light settings, interventions featuring light intensities >5000lux, intervention duration ≥4 weeks, spectral emission peak at 464∼465 nm, and using a lightbox demonstrated heightened efficacy in improving sleep. BLT may be considered a supplementary therapeutic option to improve sleep quality among cancer patients. However, more extensive and rigorous studies are necessary to determine the optimal timing of BLT delivery and its applicability to cancer patients across different age groups.

Role of remnant cholesterol in the relationship between physical activity and diabetes mellitus: an intermediary analysis.

Objective: The purpose of this investigation was to evaluate the potential link between physical activity (PA) and the heightened susceptibility to diabetes mellitus (DM), by examining whether remnant cholesterol (RC) might act as a mediator in this correlation. Methods: The research utilized data from the National Health and Nutrition Examination Survey, spanning from 2005 to 2018. Various statistical analyses were conducted for continuous and categorical variables, including the t-test, ANOVA, and χ2 test. Logistic regression was employed to analyze the association between PA and DM across three distinct models. Mediation analysis was also conducted to assess the potential mediation effects of RC. Results: The study encompassed a total of 9,149 participants, and it was observed that individuals with DM exhibited lower levels of PA. Furthermore, PA levels were found to be associated with all participant characteristics except poverty income ratio, fasting blood glucose, and HOMA-IR (p < 0.05). After adjusting for covariates (Model 3), individuals with high PA levels demonstrated a decreased likelihood of developing DM compared to those in the low PA group (OR: 0.73, 95%CI: 0.54-0.99). A significant dose-response relationship was identified (p < 0.05). No interaction between PA and RC in relation to DM risk was detected, and RC was found to serve as a mediator in the connection between PA and DM. After considering covariates, the mediating effect of RC between PA and DM weakens. Discussion: Our findings suggest that higher levels of PA are linked to a reduced risk of DM in U.S. adults, with RC likely playing a mediating role.

The interaction of financial toxicity and social support on social functioning in post-chemotherapy breast cancer patients: a cross-sectional study.

PURPOSE: To explore the correlation between financial toxicity, social support, and social functioning in post-chemotherapy breast cancer patients, as well as any possible interaction of financial toxicity and social support on social functioning. METHODS: Post-chemotherapy breast cancer patients admitted to the thyroid and breast surgery departments of three first-class general hospitals in East China from December 2020 to January 2022 were recruited by convenience sampling for a cross-sectional survey. The survey instruments included the general information form, the comprehensive scores for financial toxicity based on the patient-reported outcome measures (COST-PROM), the social roles and activity participation subscale from the patient-reported outcomes measurement system-breast-chemotherapy (PROMS-B-C) (score range: 8-40), and the social support subscale from PROMS-B-C (score range: 16-80). RESULTS: The results showed that low social functioning (low score) in post-chemotherapy breast cancer patients was positively correlated with high financial toxicity (low score) as well as poor economic resources (low score) and poor psychosocial responses (low score) (P<0.01) and negatively correlated with low economic expenditures (low score) (P<0.01); high social functioning (high score) was positively correlated with high social support (high score) (P<0.01). The interaction analysis results showed an additive interaction between financial toxicity and social support in social functioning. CONCLUSION: There was an additive interaction of financial toxicity and social support in the social functioning of post-chemotherapy breast cancer patients. Those patients with high financial toxicity and low social support are the most likely to benefit from relevant intervention measures compared to other breast cancer populations.