Exposition of Discriminatory Variables in a Family of Hypertensive and Non hypertensive Diabetic Patients: A Case Study of Komfo Anokye Teaching Hospital – Kumasi, Ghana

摘要

This study sought to expose variable(s) capable of predicting hypertensive status of diabetic patients. To this end, data on 260 diabetic patients at the Komfo Anokye Teaching Hospital’s Diabetic Centre in Ghana were collected using data extraction form. The majority (144) of the 260 diabetic patients representing about 55% were also hypertensive as against 116 (45%) who were not hypertensive. Frequency analysis also revealed female dominance as far as the two diagnoses (Diabetes with hypertension and diabetes without hypertension) were concerned. However, the percentage of females in diabetes with hypertension (77%) was greater than the percentage of females in diabetes without hypertension (67%). The minimum age of hypertensive diabetic patients was 30 years as against 11 years for those diagnosed as non-hypertensive diabetic. A discriminant analysis was adopted to expose the discriminatory variables as far as the two diagnoses were concerned. The study indicated a strong association between diagnosis (diabetes with hypertension and diabetes without hypertension) and body mass index (BMI), and to some extent, also between diagnosis and age. BMI and age were identified as principal discriminating variables for separating patients diagnosed with diabetes with hypertension from those with diabetes without hypertension. The index of discrimination (canonical correlation) associated with the resulting discriminant model was 0.42 (42%). This is good since it is greater than 30. The hit ratio, (or the percentage of cases correctly classified) is 0.654 or 65.4%. Also, leave-one-out cross-validation which was used instead of an independent holdout sample correctly classified 64.2% of the cases. Finally, it was concluded that ageing and extra BMI gained are risk factors for diabetic patients to develop hypertension. Therefore, the model was good for prediction.