Association between pre-exercise food ingestion timing and reactive hypoglycemia: insights from a large database of continuous glucose monitoring data.

Zignoli, Andrea; Fontana, Federico Y; Lipman, David J; Skroce, Kristina; Maturana, Felipe M; Zisser, Howard C (2023). Association between pre-exercise food ingestion timing and reactive hypoglycemia: insights from a large database of continuous glucose monitoring data. European journal of sport science, 23(12), pp. 2340-2348. Taylor & Francis 10.1080/17461391.2023.2233468

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Using a large database of continuous glucose monitoring (CGM) data, this study aimed to gain insights into the association between pre-exercise food ingestion timing and reactive hypoglycemia. A group of 6,761 users self-reported 48,799 pre-exercise food ingestion events and logged minute-by-minute CGM, which was used to detect reactive hypoglycemia (<70 mg/dL) in the first 30 minutes of exercise. A linear and a non-linear binomial logistic regression model was used to investigate the association between food ingestion timing and the probability of experiencing reactive hypoglycemia. An analysis of variance was conducted to compare the predictive ability of the models. On average, reactive hypoglycemia was detected in 8.34 ± 3.04% of the total events, with <15% of individuals experiencing hypoglycemia in >20% of their events. The majority of the reactive hypoglycemia events were found with pre-exercise food timing between ∼30 and ∼90 minutes, with a peak at ∼60 minutes. The superior accuracy (62.05 vs 45.1%) and F-score (0.75 vs 0.59) of the non-linear vs the linear model were statistically superior (P < 0.0001). These results support the notion of an unfavourable 30-to-90 minutes pre-exercise food ingestion time window which can significantly impact the likelihood of reactive hypoglycemia in some individuals.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Endocrinology, Diabetology and Clinical Nutrition

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1746-1391

Publisher:

Taylor & Francis

Language:

English

Submitter:

Pubmed Import

Date Deposited:

11 Jul 2023 09:06

Last Modified:

30 Nov 2023 00:12

Publisher DOI:

10.1080/17461391.2023.2233468

PubMed ID:

37424300

Uncontrolled Keywords:

binomial logistic regression observational study real-time glucose tracking system

BORIS DOI:

10.48350/184638

URI:

https://boris.unibe.ch/id/eprint/184638

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