PREDICTION OF HYPERTENSION USING ITS RISK FACTORS: A CASE CONTROL STUDY IN AZIZ BHATTI SHAHEED HOSPITAL

Abstract

Hypertension is becoming the major risk factor of the cardiovascular diseases. Hypertension is also known as “raised blood pressure” in medical terms. The main purpose of this study is to identify the potential risk factor of hypertension using chi-square test of association and also predict and classify the respondents into hypertension and healthy controls by Artificial Neural Network (ANN). A sample of 300 (150 cases and 150 controls) were selected using purposive sampling from Aziz Bhatti shaheed Hospital Gujrat, Pakistan. Data collected by interviewing the patients using well-designed questionnaire and checked their BP where cases considered as hypertension patients with (BP: 140/90) and healthy controls (BP: 120/80). High prevalence of hypertension is observed in males (54.7%) as compared to females (45.3%). Results also revealed that BMI, family income, age, extra salt intake and stress were the significant risk factors of hypertension in current study. ANN model showed good classification among hypertension and controls. It also predicted 98% chance of patient to have hypertension on the basis of age group 50-59 years, having normal weight, belongs to middle class family, presence of BP issue in family history, take stress and extra salt consumption in diet.