Prediction Model for Non-pharmacological Treatment Implement of Hypertension based on Residential Area - Kim, Sulbin; Han, Myeunghee (KHD-Production, 2024)
This study aimed to construct a predictive model for the nonpharmacological treatment of hypertension according to residential area using the 2021 Community Health Survey (CHS). This cross-sectional study analyzed the data of 48,662 individuals diagnosed with hypertension. A decision tree analysis was conducted to create a predictive model. A split-sample test was conducted to verify the accuracy of the final model. Multiple logistic regression analysis was conducted to identify the factors related to the implementation of nonpharmacological treatment. The prediction model identified that subjects who lived in a “rural” area, did not complete hypertension management education, and did not respond to the written health information literacy question showed the lowest probability of performing nonpharmacological treatment at 10.2%. Conversely, those who lived in a “city”, had completed hypertension education, and had above-average life satisfaction were most likely to implement the program (45.0%). Multiple logistic regression results showed that those who live in a city, have a good subjective health level, quit smoking, a high level of understanding of written health information, participate in hypertension management education, engage in economic activities, and have a high level of education or of life satisfaction had a high possibility of implementing nonpharmacological treatment of hypertension. Providing customized hypertension management education by identifying education levels of individuals with hypertension and ensuring their comprehension of written medical information will be effective in improving the rate of nonpharmacological treatment of hypertension.