Cargando…

Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index

BACKGROUND: There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. METHODS: This cross-sectional study was carried out within our ethics committee-approved study called “Exploring the impact of nu...

Descripción completa

Detalles Bibliográficos
Autores principales: Kashiwagi, Kazuhiro, Inaishi, Jun, Kinoshita, Shotaro, Wada, Yasuyo, Hanashiro, Sayaka, Shiga, Kiko, Kitazawa, Momoko, Tsutsumi, Shiori, Yamakawa, Hiroyuki, Irie, Junichiro, Kishimoto, Taishiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550127/
https://www.ncbi.nlm.nih.gov/pubmed/37792730
http://dx.doi.org/10.1371/journal.pone.0291923
_version_ 1785115467350802432
author Kashiwagi, Kazuhiro
Inaishi, Jun
Kinoshita, Shotaro
Wada, Yasuyo
Hanashiro, Sayaka
Shiga, Kiko
Kitazawa, Momoko
Tsutsumi, Shiori
Yamakawa, Hiroyuki
Irie, Junichiro
Kishimoto, Taishiro
author_facet Kashiwagi, Kazuhiro
Inaishi, Jun
Kinoshita, Shotaro
Wada, Yasuyo
Hanashiro, Sayaka
Shiga, Kiko
Kitazawa, Momoko
Tsutsumi, Shiori
Yamakawa, Hiroyuki
Irie, Junichiro
Kishimoto, Taishiro
author_sort Kashiwagi, Kazuhiro
collection PubMed
description BACKGROUND: There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. METHODS: This cross-sectional study was carried out within our ethics committee-approved study called “Exploring the impact of nutrition advice on blood sugar and psychological status using continuous glucose monitoring (CGM) and wearable devices”. Prediabetes was defined by the HbA1c level of 5.7–6.4% and /or fasting glucose level of 100–125 mg/dL. Glucose levels and daily steps were measured for 40 participants using Free Style Libre and Fitbit Inspire 2 under normal conditions for 14 days. Dietary intakes and eating behaviors were assessed using a brief-type self-administered dietary history questionnaire and a modified questionnaire from the Obesity Guidelines. RESULTS: All indices of GV were higher in the prediabetes group than in the healthy group, but a significant difference was observed only in mean amplitude of glycemic excursions (MAGE). In the multivariate analysis, only the presence of prediabetes showed a significant association with the risk of higher than median MAGE (Odds, 6.786; 95% CI, 1.596–28.858; P = 0.010). Additionally, the underweight (BMI < 18.5) group had significantly higher value in standard deviation (23.7 ± 3.5 vs 19.8 ± 3.7 mg/dL, P = 0.038) and coefficient variability (22.6 ± 4.6 vs 18.4 ± 3.2%, P = 0.015), compared to the normal group. This GV can be partially attributed to irregularity of eating habits. On the contrary, the overweight (BMI ≥ 25) group had the longest time above the 140 or 180 mg/dL range, which may be due to eating style and taking fewer steps (6394 ± 2337 vs 9749 ± 2408 steps, P = 0.013). CONCLUSIONS: Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.
format Online
Article
Text
id pubmed-10550127
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-105501272023-10-05 Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index Kashiwagi, Kazuhiro Inaishi, Jun Kinoshita, Shotaro Wada, Yasuyo Hanashiro, Sayaka Shiga, Kiko Kitazawa, Momoko Tsutsumi, Shiori Yamakawa, Hiroyuki Irie, Junichiro Kishimoto, Taishiro PLoS One Research Article BACKGROUND: There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. METHODS: This cross-sectional study was carried out within our ethics committee-approved study called “Exploring the impact of nutrition advice on blood sugar and psychological status using continuous glucose monitoring (CGM) and wearable devices”. Prediabetes was defined by the HbA1c level of 5.7–6.4% and /or fasting glucose level of 100–125 mg/dL. Glucose levels and daily steps were measured for 40 participants using Free Style Libre and Fitbit Inspire 2 under normal conditions for 14 days. Dietary intakes and eating behaviors were assessed using a brief-type self-administered dietary history questionnaire and a modified questionnaire from the Obesity Guidelines. RESULTS: All indices of GV were higher in the prediabetes group than in the healthy group, but a significant difference was observed only in mean amplitude of glycemic excursions (MAGE). In the multivariate analysis, only the presence of prediabetes showed a significant association with the risk of higher than median MAGE (Odds, 6.786; 95% CI, 1.596–28.858; P = 0.010). Additionally, the underweight (BMI < 18.5) group had significantly higher value in standard deviation (23.7 ± 3.5 vs 19.8 ± 3.7 mg/dL, P = 0.038) and coefficient variability (22.6 ± 4.6 vs 18.4 ± 3.2%, P = 0.015), compared to the normal group. This GV can be partially attributed to irregularity of eating habits. On the contrary, the overweight (BMI ≥ 25) group had the longest time above the 140 or 180 mg/dL range, which may be due to eating style and taking fewer steps (6394 ± 2337 vs 9749 ± 2408 steps, P = 0.013). CONCLUSIONS: Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals. Public Library of Science 2023-10-04 /pmc/articles/PMC10550127/ /pubmed/37792730 http://dx.doi.org/10.1371/journal.pone.0291923 Text en © 2023 Kashiwagi et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kashiwagi, Kazuhiro
Inaishi, Jun
Kinoshita, Shotaro
Wada, Yasuyo
Hanashiro, Sayaka
Shiga, Kiko
Kitazawa, Momoko
Tsutsumi, Shiori
Yamakawa, Hiroyuki
Irie, Junichiro
Kishimoto, Taishiro
Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
title Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
title_full Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
title_fullStr Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
title_full_unstemmed Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
title_short Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
title_sort assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550127/
https://www.ncbi.nlm.nih.gov/pubmed/37792730
http://dx.doi.org/10.1371/journal.pone.0291923
work_keys_str_mv AT kashiwagikazuhiro assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT inaishijun assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT kinoshitashotaro assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT wadayasuyo assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT hanashirosayaka assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT shigakiko assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT kitazawamomoko assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT tsutsumishiori assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT yamakawahiroyuki assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT iriejunichiro assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex
AT kishimototaishiro assessmentofglycemicvariabilityandlifestylebehaviorsinhealthynondiabeticindividualsaccordingtothecategoriesofbodymassindex