Individual glycemic responses scale predictably with the glycemic index: evidence against person-specific food...

Recent personalized nutrition research has reported large interindividual differences in postprandial glucose responses to identical foods, raising questions about whether these differences reflect food-specific personal effects or normal day-to-day variability in glucose tolerance.

This study aimed to quantify the relative contributions of measurement variability compared with person-specific effects to interindividual glycemic variation, and to define substitution thresholds for when glycemic index (GI) differences produce distinct physiological effects.

In this secondary analysis with simulated validation, data from 382 healthy adults (1022 glucose reference tests, 1116 food tests across 9 carbohydrate-rich foods) were analyzed using a direct comparison scaling model, in which an individual's food response equals their glucose reference response scaled by the food's mean GI. Sensitivity analyses included single-reference predictions, restriction to participants with ≥3 reference tests, and exclusion of a protocol-deviating food.

Predicted errors did not exceed the observed glucose reference test-retest variability [mean root mean square deviation: 0.78 compared with 1.02 mmol/L; Cohen's d = 0.54 (0.45, 0.63)], with ∼90% of predictions falling within each participant's own test-retest range. Bland-Altman analysis confirmed negligible systematic bias (-0.01 mmol/L). Synthetic datasets generated from glucose variability and mean GI values reproduced observed response distributions without person-specific parameters. GI differences of ≥15 units produced reliably distinguishable responses in a given individual. All sensitivity analyses yielded equal or stronger effect sizes.

In healthy adults under standardized conditions, interindividual variation in glycemic responses predominantly accounts for by variability in day-to-day glucose tolerance, propagating through the GI ratio. The GI concept performs within the reproducibility limits of input data.