Utilizing an apriori algorithm to examine attributes associated with hypertension and hypertension cardiovascular patients in Pakistan

Background: Hypertension (HTN) is a cardiovascular disease (CVD) that continues to grow and is the leading cause of death worldwide. More than 7 million people suffer from HTN and HTN-CVD each year. HTN is a modifiable risk factor for many severe health conditions, such as kidney disease, peripheral vascular disease, myocardial infarction, stroke, and congestive heart failure. Methods: This study uses apriori algorithm analysis to analyze data for HTN and HTN-CVD patients. It specifically aims to identify frequently occurring attributes related to lifestyle, symptoms, health status, genetic factors, socioeconomic status, and medication status. The implementation of market basket analysis using the apriori algorithm and Python 3.7. Results: Among the highest apriori, lifestyle attributes like meals per day, eating fruits and vegetables, eating legumes and meat, and following a high-fat diet are the most commonly observed items in the analysis. There are various related characteristics that can be grouped into symptom categories, like neck and jaw pain discomfort, headaches, and chest pain. When it comes to health status, high systolic blood pressure and diastolic blood pressure (SBP and DBP) are also commonly observed. Combinations of lifestyle attributes, symptoms, and health status, such as eating vegetables, high SBP, number of meals per day, and chest pain, exhibit a strong association with a support value and confidence of more than 0.70. Conclusions: Based on the market basket data analysis for HTN and HTN-CVD patients, it is clear that lifestyle, symptoms, and health factors are frequently associated among patients HTN and HTN-CVD.