Testing the carbohydrate-insulin model: Short-term metabolic responses to consumption of meals with varying glycemic index in healthy adults

The carbohydrate-insulin model predicts that meals with varying glycemic indices will elicit distinct metabolic and hunger responses, including greater intake at subsequent meals following high-glycemic-index meals. To test this, a randomized trial (NCT05804942) was conducted in healthy adults using intervention meals with low, medium, and high glycemic indices and a constant macronutrient composition. After intake of the intervention meals, glucose and insulin followed the predicted pattern, but subjective hunger did not. At the group level, low glycemic index meals led to lower energy intake changes. At the individual level, energy intake changes were unrelated to body fatness or levels of glucose, β-hydroxybutyrate, free fatty acids, L-lactate, leptin, adrenaline, glucagon-like peptide-1, glucagon, and insulin-glucagon ratio. A weak negative association was observed between energy intake changes and insulin or insulin-glucagon ratio at 300 min, opposite to the model's prediction. These data provide little support for the carbohydrate-insulin model.

Authors

Institutions

Publication Details

Journal
Cell Metabolism
Published
2025-03-01
DOI
https://doi.org/10.1016/j.cmet.2025.01.015
Citations
9
Primary Topic
Diet and metabolism studies
Type
article
Field-Weighted Citation Impact
10.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Testing the carbohydrate-insulin model: Short-term metabolic responses to consumption of meals with varying glycemic index in healthy adults

Xue Li, Huanan Zhang, Yinghua Yu, Chaochun Zou et al.
9 citations
Cell Metabolism
Diet and metabolism studies
10.48
article

Testing the carbohydrate-insulin model: Short-term metabolic responses to consumption of meals with varying glycemic index in healthy adults

Xue Li, Huanan Zhang, Yinghua Yu, Chaochun Zou, Chaoqun Niu, Yingtong Wu, Huihui Mei, John R. Speakman, Chuanli Cheng, Sumei Hu, Xueying Zhang, Xu Gao, Lu Wang, Ying Liu, Jie Liu, Lin Gao, Huijuan Li
article en
9 citations

Abstract

The carbohydrate-insulin model predicts that meals with varying glycemic indices will elicit distinct metabolic and hunger responses, including greater intake at subsequent meals following high-glycemic-index meals. To test this, a randomized trial (NCT05804942) was conducted in healthy adults using intervention meals with low, medium, and high glycemic indices and a constant macronutrient composition. After intake of the intervention meals, glucose and insulin followed the predicted pattern, but subjective hunger did not. At the group level, low glycemic index meals led to lower energy intake changes. At the individual level, energy intake changes were unrelated to body fatness or levels of glucose, β-hydroxybutyrate, free fatty acids, L-lactate, leptin, adrenaline, glucagon-like peptide-1, glucagon, and insulin-glucagon ratio. A weak negative association was observed between energy intake changes and insulin or insulin-glucagon ratio at 300 min, opposite to the model's prediction. These data provide little support for the carbohydrate-insulin model.

Cell MetabolismVol. 37(3)
Beijing Technology and Business University (CN), Shenzhen University (CN), Yantai University (CN), University of Aberdeen (GB), Chinese Academy of Sciences (CN), Institute of Genetics and Developmental Biology (CN), Shenzhen Institutes of Advanced Technology (CN), Shenzhen Technology University (CN), Shenzhen Second People's Hospital (CN), University of Chinese Academy of Sciences (CN), China Medical University (CN)
Zero hunger
Openalex Percentile: Top 2%
Diet and metabolism studies
10.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.