Macronutrient Recommendations for Remission and Prevention of Diabetes in Asian Indians Based on a Data-Driven Optimization Model: The ICMR-INDIAB National Study

Abstract

OBJECTIVE To derive macronutrient recommendations for remission and prevention of type 2 diabetes (T2D) in Asian Indians using a data-driven optimization approach. RESEARCH DESIGN AND METHODS Dietary, behavioral, and demographic assessments were performed on 18,090 adults participating in the nationally representative, population-based Indian Council of Medical Research–India Diabetes (ICMR-INDIAB) study. Fasting and 2-h postglucose challenge capillary blood glucose and glycosylated hemoglobin (HbA1c) were estimated. With HbA1c as the outcome, a linear regression model was first obtained for various glycemic categories: newly diagnosed diabetes (NDD), prediabetes (PD), and normal glucose tolerance (NGT). Macronutrient recommendations were formulated as a constrained quadratic programming problem (QPP) to compute optimal macronutrient compositions that would reduce the sum of the difference between the estimated HbA1c from the linear regression model and the targets for remission (6.4% for NDD and 5.6% for PD) and prevention of progression in T2D in PD and NGT groups. RESULTS Four macronutrient recommendations (%E- Energy) emerged for 1) diabetes remission in NDD: carbohydrate, 49–54%; protein, 19–20%; and fat, 21–26%; 2) PD remission to NGT: carbohydrate, 50–56%; protein,18–20%; fat, 21–27%; 3 and 4) prevention of progression to T2D in PD and NGT: carbohydrate, 54–57% and 56–60%; protein, 16–20% and 14–17%, respectively; and fat 20–24% for PD and NGT. CONCLUSIONS We recommend reduction in carbohydrates (%E) and an increase in protein (%E) for both T2D remission and for prevention of progression to T2D in PD and NGT groups. Our results underline the need for new dietary guidelines that recommend appropriate changes in macronutrient composition for reducing the burden due to diabetes in South Asia.

Sex-Based Differences in Clinical Profile and Complications among Individuals with Type 2 Diabetes Seen at a Private Tertiary Diabetes Care Centre in India

“…Evidence suggests that low-carbohydrate diets are effective in the management of diabetes, by significantly reducing body weight and also effectively improving HbA1c, fasting plasma glucose, blood lipid, and insulin resistance [43,44]. In addition, it has been shown that in individuals with diabetes, high-protein diets can significantly decrease HbA1c levels [45], and low-fat intake could improve total cholesterol and LDL cholesterol and lower HDL cholesterol [46]. The ICMR INDIAB national study reported that the total calorie intake was higher in males with newly diagnosed diabetes, while the carbohydrate, protein, and fat intake did not significantly differ by sex [47].…”

Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India

“…15 Guidelines call for individualization of meal planning, which is sometimes referred to as “Medical Nutritional Therapy”. Despite this, personalization of dietary plans are generally based upon broad constructs like age, activity level, health status and preferences, and, for all patients, tend to emphasize overall calorie reductions and minimization of carbohydrate, 16 especially added sugars and refined grains, in favor of the consumption of non-starchy vegetables and foods that are high in protein. 32…”

“…15 Guidelines call for individualization of meal planning, which is sometimes referred to as "Medical Nutritional Therapy". Despite this, personalization of dietary plans are generally based upon broad constructs like age, activity level, health status and preferences, and, for all patients, tend to emphasize overall calorie reductions and minimization of carbohydrate, 16 especially added sugars and refined grains, in favor of the consumption of non-starchy vegetables and foods that are high in protein. 32 However, emerging data demonstrates that there are marked inter-individual responses to food, 17 attributed to differences in physical activity, 33 gut microbiome, 18,19,34 and genetics 35 including in variations in skeletal glucose transporters related to insulin resistance.…”

“…15 Despite this, most dietary advice for individuals with DM2 remains generic emphasizing reductions in calories and minimization of carbohydrates. 16 However, there are marked inter-individual responses in post-prandial glucose response (PPGR). 17 A study conducted in Israel found substantial PPGR variability to standardized meals for individuals without diabetes.…”

Human Digital Twin for Personalized Elderly Type 2 Diabetes Management

“…This is mainly due to the fact that the MPC uses an approximate patient model to compute the insulin infusion and could embed real-time measurements in such computations. The role of an MPC to include aspects such as food influences and physical activity has been proposed in [ 12 , 13 , 14 ].…”