Multiple coronary heart diseases are risk factors for mental health disorders: A mendelian randomization study.

BACKGROUND: Previous observational studies have suggested associations between Coronary Heart Disease (CHD) and Mental Health Disorders (MHD). However, the causal nature of these relationships has remained elusive. OBJECTIVE: The purpose of this study is to elucidate the causal relationships between eight distinct types of CHD and six types of MHD using Mendelian randomization (MR) analysis. METHODS: The MR analysis employed a suite of methods including inverse variance-weighted (IVW), MR-Egger, weighted mode, weighted median, and simple mode techniques. To assess heterogeneity, IVW and MR-Egger tests were utilized. MR-Egger regression also served to investigate potential pleiotropy. The stability of IVW results was verified by leave-one-out sensitivity analysis. RESULTS: We analyzed data from over 2,473,005 CHD and 803,801 MHD patients, informed by instrumental variables from large-scale genomic studies on European populations. The analysis revealed a causal increase in the risk of Major Depressive Disorder and Mania associated with Coronary Artery Disease and Myocardial Infarction. Heart Failure was found to causally increase the risk for Bipolar Disorder and Schizophrenia. Atrial Fibrillation and Ischemic Heart Diseases were positively linked to Generalized Anxiety Disorder and Mania, respectively. There was no significant evidence of an association between Hypertensive Heart Disease, Hypertrophic Cardiomyopathy, Pulmonary Heart Disease, and MHD. Reverse MR analysis indicated that MHD do not serve as risk factors for CHD. CONCLUSIONS: The findings suggest that specific types of CHD may act as risk factors for certain MHDs. Consequently, incorporating psychological assessments into the management of patients with CHD could be advantageous.

Analysis of consumer product preference and news media based on data mining technology.

In order not to be eliminated by the market, enterprises must face various consumer preferences, design products that meet consumer preferences, and enhance competitiveness. This paper combines on-the-spot marketing to study the product preferences of consumers and the personality characteristics of media hosts. This paper introduces the data mining technology of news media into the research of consumer's preference for products. Based on the comprehensive use of media mining technology, customer research theory, and product background and foundation, the specific process of influencing consumers' product preference is established. It can be seen from the study that the personality of the anchor has a great relationship with the consumption level of consumers and the sales rate of products, with an impact of 78.53%. Through this study, we can see that there is a certain relationship between consumers' product preference and anchoring personality. Studying the basic characteristics of the phenomenon live broadcast commodity marketing model has important theoretical value for analyzing the live broadcast commodity marketing model. It points out the direction for the scientific, healthy, and sustainable development of the future live broadcast commodity marketing mode.