Ordinal Regression Model to Predict Hypertension

Abstract

Introduction: Hypertension in the world and Indonesia has been increasing every year. Hypertension can be prevented by controlling risky behaviors such as smoking, unhealthy diet, obesity, lack of physical activity, and excessive alcohol consumption. Aim: This study aims to predict hypertension using an ordinal regression model. Materials and Method: This research is an observational analytic study using a cross-sectional approach. The research was conducted in Jati Agung Subdistrict, South Lampung in 2021. The measuring instrument used a questionnaire and measured blood pressure. The study population was all people over 50 years of age, with a total sample of 92 people. The independent variables include age, gender, education, job status, consumption of fatty foods, physical activity, alcohol consumption, and smoking behavior. The dependent variable in this study was hypertension. The analysis used was univariate and multivariate using ordinal regression models. Results: The analysis found that most of the respondents were aged 61-70 years, women, elementary education level, did not work, rarely ate fatty foods, had enough physical activity, did not drink alcohol, did not smoke, and was categorized as level-1 hypertension. Multivariate analysis used regression. ordinal, it was found that the variables associated with hypertension were gender (p = 0.034) and consumption of fatty foods (p = 0.000). Conclusion: The variables associated with hypertension are gender and consumption of fatty foods.