Journal d'informatique et de gestion de la santé

Modeling Risk Factors of High Blood Pressure in Women Using Multiple Logistic Regression

Nsien EF, Abam AO

This study employed the Multiple Logistic Regression (MLR) to model some risk factors of high blood pressure in women. Seven risk factors selected for this study were age, body mass index, waist circumference, skin fold thickness, pulse rate, mid arm circumference and hip circumference. Secondary data retrieved from the record unit of the University of Uyo Teaching Hospital, Uyo (UUTH) was used in this study. The risk factors were assessed from one hundred and ninety-three patients of the Hospital using MLR model. The findings revealed that there exist a significant influence of age and body mass index on high blood pressure. This result also showed that the higher the age of women, the more likely for them to have high blood pressure. The odds of high blood pressure in women who were obese were more than twelve times higher than women who were not obese. Other risk factors like waist circumference, skin fold thickness, pulse rate, mid arm circumference and hip circumference were not found to have significant influence on high blood pressure. Therefore, the result of the study showed that age and body mass index were the major risk factors of high blood pressure in women.