Identifying key factors of hypertension control using Bayesian networks in the 2021—2022 National Basic Public Health Service Project - LI Danying, GUO Xiaojing, ZHU Xiaolei, SI Xiang, ZHANG Xiaochang, WAN Xia (Jichu yixue yu linchuang)
Objective To explore factors affecting blood pressure control in chronic disease patients in China′s national basic public health service chronic disease patient management program and to find their relationships with Bayesian network(BN) model, in order to provide a scientific basis for comprehensive hypertension management. Methods 5 577 Hypertensive patients were selected from eight provinces(including autonomous regions) covering eastern, central and western parts of China during a survey from 2021 to 2022. Researchers collected individual and community-management data to screen influencing factors by Logistic regression, and to describe factor dependencies and to identify key determinants of blood pressure control with BN in. blood pressure control. Results Logistic regression revealed that urban/rural status, education, alcohol use, exercise, overweight/obesity and community-doctor advice on salt reduction, smoking cessation were significantly associated with blood pressure control(P＜0.05). The BN model identified 22 directed edges showing that urban residence and good hypertension knowledge were more correlated with better control, while community-doctor management and services directly affected patient lifestyle habits but not blood pressure control. Conclusions Research should focus more on urban-rural disparities and hypertension education. Additionally, improving patient habits and community-doctor services is essential for better blood pressure control.