Hostname: page-component-848d4c4894-p2v8j Total loading time: 0.001 Render date: 2024-05-29T06:51:03.379Z Has data issue: false hasContentIssue false

Postprandial glycaemic response to white and wholemeal bread consumption between normal weight and overweight/obese healthy adults

Published online by Cambridge University Press:  08 March 2023

A. Colombo
Affiliation:
School of Life Sciences, Coventry University, Coventry, UK
Y. Xu
Affiliation:
School of Life Sciences, Coventry University, Coventry, UK
H. Dong
Affiliation:
School of Health and Psychological Sciences, City, University of London, London, UK
Rights & Permissions [Opens in a new window]

Abstract

Type
Abstract
Copyright
Copyright © The Authors 2023

The impact of postprandial glucose response has been implicated in the development of chronic metabolic diseases, and obesity is an important risk factor(Reference Blaak, Antoine and Benton1). Few studies investigated the effect of body weight on postprandial glycaemic response. This study aimed to investigate the difference in postprandial glycaemic response to commonly consumed white and wholemeal bread in the UK(Reference Lockyer and Spiro2) between normal weight and overweight/obese adults, and to investigate the difference in postprandial glycaemic response between white and wholemeal bread consumption in adults. Wholemeal bread contains higher dietary fibre than white bread, therefore is regarded as a healthier choice(Reference Lužnik IV, Lužnik and Mateja Lušnic Polak3).

Twenty healthy adults were each given two slides of white or wholemeal bread alongside 150 ml of pure orange juice and 10 g butter on separate visits at random order after fasting for 12 hours. The white bread meal contains 369.5 kcal, 60 g carbohydrates, 17.8 g sugar and 3.6 g fibre, while the wholemeal bread meal contains 355.5 kcal, 48 g carbohydrates, 17.4 g sugar, and 5.6 g fibre. The blood glucose concentration was measured before taking meals, 30 min, 60 min, 90 min and 120 min postprandially by finger pricks using Biosen Blood Glucose/Lactate Analyser (EKF Diagnostics, Cardiff). Participants consumed the meal within 10 minutes and kept sedentary with only water consumption allowed during the study period. The participant information of age, sex, ethnicity, body weight and height, and fat composition measured by Tanita MC-980MA PLUS (Tanita Company, Tokyo) were collected on the first visit. The difference in the area under the curve and the peak value of the postprandial glycaemic response were analysed between different groups using the independent t-test or between different meals using paired t-test.

There was no significant difference in the area under the curve of postprandial glucose response between normal weight (n = 10) and overweight/obese (n = 10), between females (n = 12) and males (n = 8) or between white Caucasians (n = 13) and non-white (n = 7) participants, regardless of white or wholemeal bread consumption. However, the peak value was significantly higher in non-white than white participants (6.11 nmol/L vs 5.15 nmol/L, P = 0.015) after white bread consumption, while males showed a significantly higher peak value than females after the wholemeal bread consumption (6.22 nmol/L vs 4.78 nmol/L, P = 0.021). There was no significant difference in the area under the curve or peak values between white and wholemeal bread consumption.

The results indicated that body weight did not play significant role in postprandial glycaemic response to white or wholemeal bread consumption, and the dietary fibre content in the wholemeal bread used in the current study may not high enough to deliver the health benefit of postprandial glycaemic response. Further research is needed to include a larger sample size with power calculation to investigate the postprandial glycaemic response between sexes and different ethnicities.

Acknowledgments

Thanks for Nutrition Society to sponsor the summer studentship. Thanks for all participants in the study.

References

Blaak, EE, Antoine, JM, Benton, D, et al. (2012) Obes Rev 13(10), 923984.CrossRefGoogle Scholar
Lockyer, S & Spiro, A (2020) Nutr Bull 45(2), 133164.Google Scholar
Lužnik IV, I, Lužnik, A, Mateja Lušnic Polak, ML, et al. (2019) J Nutr Intermed Metab 16, 100097100103.CrossRefGoogle Scholar