Identification of dietary patterns associated with poor glycemic control among free living adults with type 2 diabetes in Chennai (CURES-162)

Abstract

Aim: Diabetes is a chronic progressive disease. A healthy eating pattern is essential to achieve good glycemic control (HbA1c 7%) which aids in delaying and preventing diabetes-related complications. The pivotal role of diet, a modifiable risk factor for type 2 diabetes has not been understood completely especially in India where carbohydrate consumption is high. This study, therefore, aims to identify major dietary patterns associated with uncontrolled diabetes by using data reduction methods. Objective: To study and compare the association of dietary patterns with elevated HbA1c among known diabetic adults using three data reduction methods (principal component analysis (PCA), reduced rank regression (RRR), and partial least-squares (PLS) regression). Materials and Methods: The Chennai Urban Rural Epidemiological followed up study (CURES) was completed in 2410 adults. Adults with diabetes (both genders, aged >20years), 573 were selected for the present analysis. Dietary intake was assessed using food frequency questionnaire. Results: The PCA derived the non-vegetarian and vegetarian pattern. Both showed positive association with the risk of high HbA1c. The first pattern of RRR and PLS showed a positive association with many foods especially those contributing to increased intakes of total calories. Whereas the 2nd pattern of RRR and PLS scores both showed an inverse association with HbA1c especially with the reduction in rice-based recipes and total calories. Conclusions: The low intake of certain foods, especially white rice, directly decreased the total calories, total carbohydrate, glycemic load, and glycemic index which has a beneficial effect on glycemic control among those with diabetes.

Keywords

• asian indian
• data reduction methods
• dietary pattern
• hba1c
• type 2 diabetes