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Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach

Physical activity (PA) provides numerous health benefits for individuals with type 1 diabetes (T1D). However, the threat of exercise-induced hypoglycemia may impede the desire for regular PA. Therefore, we aimed to study the association between three common types of PA (walking, running, and cycling...

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Autores principales: Prasanna, Sahana, Barua, Souptik, Siller, Alejandro F., Johnson, Jeremiah J., Sabharwal, Ashutosh, DeSalvo, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237013/
https://www.ncbi.nlm.nih.gov/pubmed/37274763
http://dx.doi.org/10.3389/fdgth.2023.1142021
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author Prasanna, Sahana
Barua, Souptik
Siller, Alejandro F.
Johnson, Jeremiah J.
Sabharwal, Ashutosh
DeSalvo, Daniel J.
author_facet Prasanna, Sahana
Barua, Souptik
Siller, Alejandro F.
Johnson, Jeremiah J.
Sabharwal, Ashutosh
DeSalvo, Daniel J.
author_sort Prasanna, Sahana
collection PubMed
description Physical activity (PA) provides numerous health benefits for individuals with type 1 diabetes (T1D). However, the threat of exercise-induced hypoglycemia may impede the desire for regular PA. Therefore, we aimed to study the association between three common types of PA (walking, running, and cycling) and hypoglycemia risk in 50 individuals with T1D. Real-world data, including PA duration and intensity, continuous glucose monitor (CGM) values, and insulin doses, were available from the Tidepool Big Data Donation Project. Participants' mean (SD) age was 38.0 (13.1) years with a mean (SD) diabetes duration of 21.4 (12.9) years and an average of 26.2 weeks of CGM data available. We developed a linear regression model for each of the three PA types to predict the average glucose deviation from 70 mg/dl for the 2 h after the start of PA. This is essentially a measure of hypoglycemia risk, for which we used the following predictors: PA duration (mins) and intensity (calories burned), 2-hour pre-exercise area under the glucose curve (adjusted AUC), the glucose value at the beginning of PA, and total bolus insulin (units) within 2 h before PA. Our models indicated that glucose value at the start of exercise and pre-exercise glucose adjusted AUC (p < 0.001 for all three activities) were the most significant predictors of hypoglycemia. In addition, the duration and intensity of PA and 2-hour bolus insulin were weakly associated with hypoglycemia for walking, running, and cycling. These findings may provide individuals with T1D with a data-driven approach to preparing for PA that minimizes hypoglycemia risk.
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spelling pubmed-102370132023-06-03 Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach Prasanna, Sahana Barua, Souptik Siller, Alejandro F. Johnson, Jeremiah J. Sabharwal, Ashutosh DeSalvo, Daniel J. Front Digit Health Digital Health Physical activity (PA) provides numerous health benefits for individuals with type 1 diabetes (T1D). However, the threat of exercise-induced hypoglycemia may impede the desire for regular PA. Therefore, we aimed to study the association between three common types of PA (walking, running, and cycling) and hypoglycemia risk in 50 individuals with T1D. Real-world data, including PA duration and intensity, continuous glucose monitor (CGM) values, and insulin doses, were available from the Tidepool Big Data Donation Project. Participants' mean (SD) age was 38.0 (13.1) years with a mean (SD) diabetes duration of 21.4 (12.9) years and an average of 26.2 weeks of CGM data available. We developed a linear regression model for each of the three PA types to predict the average glucose deviation from 70 mg/dl for the 2 h after the start of PA. This is essentially a measure of hypoglycemia risk, for which we used the following predictors: PA duration (mins) and intensity (calories burned), 2-hour pre-exercise area under the glucose curve (adjusted AUC), the glucose value at the beginning of PA, and total bolus insulin (units) within 2 h before PA. Our models indicated that glucose value at the start of exercise and pre-exercise glucose adjusted AUC (p < 0.001 for all three activities) were the most significant predictors of hypoglycemia. In addition, the duration and intensity of PA and 2-hour bolus insulin were weakly associated with hypoglycemia for walking, running, and cycling. These findings may provide individuals with T1D with a data-driven approach to preparing for PA that minimizes hypoglycemia risk. Frontiers Media S.A. 2023-05-19 /pmc/articles/PMC10237013/ /pubmed/37274763 http://dx.doi.org/10.3389/fdgth.2023.1142021 Text en © 2023 Prasanna, Barua, Siller, Johnson, Sabharwal and DeSalvo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Prasanna, Sahana
Barua, Souptik
Siller, Alejandro F.
Johnson, Jeremiah J.
Sabharwal, Ashutosh
DeSalvo, Daniel J.
Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
title Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
title_full Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
title_fullStr Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
title_full_unstemmed Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
title_short Hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
title_sort hypoglycemia risk with physical activity in type 1 diabetes: a data-driven approach
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237013/
https://www.ncbi.nlm.nih.gov/pubmed/37274763
http://dx.doi.org/10.3389/fdgth.2023.1142021
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