Application of semiparametric model in modelling diabetic retinopathy among type II diabetic patients

Abstract

Background: The proportion of patients with diabetic retinopathy (DR) has grown with increasing number of diabetic mellitus patients in the world. It is among the top risk factors of blindness worldwide, especially those living in developing countries. The main objective of this study was to identify contributing risk factors of diabetic retinopathy among type II diabetic patients. Method: A sample of 191 type II diabetic patients was selected from the Black Lion Specialized Hospital diabetic unit from 1 March 2018 to 1 April 2018. A multivariate stochastic regression imputation technique was applied to impute the missing values. The response variable, diabetic retinopathy is a categorical variable with two outcomes. Based on the relationship derived from the exploratory analysis, the odds of diabetic retinopathy were not necessarily linearly related to the continuous predictors for this sample of patients. Therefore, a semiparametric model was proposed to identify the contributing factors of diabetic retinopathy. Result: From the sample of 191 type II diabetic patients, 98(51.3%) of them experienced diabetic retinopathy. The results of semiparametric regression model revealed that gender, hypertension, insulin treatment, and frequency of clinical visits had a significant linear relationships with the odds of diabetic retinopathy. In addition, the log-odds of DR has a significant nonlinear relation with the interaction of age by gender (for female patients), duration of diabetes, interaction of cholesterol level by gender (for female patients), haemoglobin A1c, and interaction of haemoglobin A1c by fasting blood glucose with degrees of freedom 3.2, 2.7, 3.6, 2.3 and 3.7, respectively. The interaction of age by gender and cholesterol level by gender appear non significant for male patients. The result from the interaction of haemoglobin A1c (HbA1c) by fasting blood glucose (FBG) showed that the risk of diabetic retinopathy is high when the level of HbA1c and FBG were simultaneously high. Conclusion: Clinical variables related to type II diabetic patients were strong predictive factors of diabetic retinopathy. Hence, health professionals should be cautious about the possible effects and complications of diabetic mellitus which can be caused by the clinical variables. Furthermore, to improve intervention strategies similar studies should be conducted across the country.