# Vegetables and Glycemic Index: Exploring Their Correlation and Health Implications

## TL;DR

This study explores how the fiber and carbohydrate content of vegetables affects their glycemic index, suggesting fiber ratios are better predictors than traditional methods.

## Contribution

The study introduces fiber ratios as a novel and more reliable predictor of glycemic index in vegetables compared to net carbohydrates.

## Key findings

- Fiber ratios are more reliable predictors of glycemic index than net carbohydrate measures.
- Total carbohydrates showed the strongest correlation with glycemic index when normalized to fiber.
- Traditional net carbohydrate methods may overlook the buffering effects of dietary fiber on blood glucose.

## Abstract

Background: Vegetables are consumed worldwide in various forms, including raw, as green leaves in salads, and as ingredients in a wide range of dishes, such as curries, sauces, and burgers. They are rich in carbohydrates and dietary fiber (DF), and also provide moderate amounts of protein, fat, oils, essential micronutrients, minerals, vitamins, and phytochemicals. Among their carbohydrate components, simple sugars such as monosaccharides/hexoses significantly influence postprandial blood glucose responses. The glycemic index (GI) is critical for managing chronic conditions, such as diabetes, obesity, hyperglycemia, and other metabolic diseases. The influence of individual carbohydrate fractions, such as hexoses, on GI and glycemic load (GL) has not been extensively investigated. Methods: This retrospective study analyzed the carbohydrates in vegetables (n = 65), focusing on hexoses and fibers, their carbohydrate-to-fiber ratio, and their effect on the GI and GL. Carbohydrate data were obtained from publicly accessible databases, including the U.S. Department of Agriculture (USDA), FooDB, European and Australian food databases, and PubMed. The study assessed total carbohydrates (TC), hexoses, dietary starch (DS), total sugars (TS), and DF, and examined their correlations with GI using regression analysis. Results: Our analysis revealed that fiber ratios are a more reliable predictor of GI than conventional net carbohydrate measures. Among the carbohydrates analyzed, TC exhibited the highest positive correlation with GI, both in absolute terms and when normalized to fiber, while TS showed a weak correlation. Among the ratios studied, TC demonstrated a stronger correlation with the GI, followed by DS. Conclusions: Comparative evaluation revealed that DF exerts a buffering effect on glycemic response (GR) and supports the use of fiber ratios as a more stable and intrinsic parameter for predicting GI than standard estimation methods. Traditional approaches that rely on net carbohydrates may overlook important factors affecting glycemic impact, particularly the buffering effects of dietary fiber. This study advocates for the incorporation of carbohydrate-to-fiber ratios into GI estimation models. Our research may help evaluate the carbohydrate content in vegetables for further in vitro and in vivo studies aimed at clarifying the mechanisms and validating these metrics in glycemic regulation.