Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index
There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. This cross-sectional study was carried out within our ethics committee-approved study called "Exploring the impact of nutrition advice o...
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| creator | Kashiwagi, Kazuhiro Inaishi, Jun Kinoshita, Shotaro Wada, Yasuyo Hanashiro, Sayaka Shiga, Kiko Kitazawa, Momoko Tsutsumi, Shiori Yamakawa, Hiroyuki Irie, Junichiro Kishimoto, Taishiro |
| description | There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. 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. 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 [greater than or equal to] 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). Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals. |
| doi_str_mv | 10.1371/journal.pone.0291923 |
| format | Article |
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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. 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 [greater than or equal to] 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). Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0291923</identifier><identifier>PMID: 37792730</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Behavior ; Biology and Life Sciences ; Blood sugar ; Blood sugar monitoring ; Body mass ; Body mass index ; Body size ; Body weight ; Cardiovascular disease ; Clinical trials ; Complications and side effects ; Consumer electronics industry ; Diabetes ; Diagnosis ; Diet ; Eating ; Eating behavior ; Ethical standards ; Food habits ; Food intake ; Glucose ; Glucose monitoring ; Glycosylated hemoglobin ; Health aspects ; Hyperglycemia ; Medicine and Health Sciences ; Monitoring ; Multivariate analysis ; Nutrition research ; Obesity ; Overweight ; Physical Sciences ; Prediabetic state ; Questionnaires ; Regression analysis ; Sensors ; Social Sciences ; Software ; Type 2 diabetes ; Underweight ; Wearable computers ; Wearable technology</subject><ispartof>PloS one, 2023-10, Vol.18 (10), p.e0291923-e0291923</ispartof><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Kashiwagi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Kashiwagi et al 2023 Kashiwagi et al</rights><rights>2023 Kashiwagi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c670t-6030040ba859c97e6da24d3285d925d4bca238d760a77b9b8e4ee0232c85f3393</citedby><cites>FETCH-LOGICAL-c670t-6030040ba859c97e6da24d3285d925d4bca238d760a77b9b8e4ee0232c85f3393</cites><orcidid>0000-0002-6301-1466 ; 0000-0003-2662-4121</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550127/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550127/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids></links><search><creatorcontrib>Kashiwagi, Kazuhiro</creatorcontrib><creatorcontrib>Inaishi, Jun</creatorcontrib><creatorcontrib>Kinoshita, Shotaro</creatorcontrib><creatorcontrib>Wada, Yasuyo</creatorcontrib><creatorcontrib>Hanashiro, Sayaka</creatorcontrib><creatorcontrib>Shiga, Kiko</creatorcontrib><creatorcontrib>Kitazawa, Momoko</creatorcontrib><creatorcontrib>Tsutsumi, Shiori</creatorcontrib><creatorcontrib>Yamakawa, Hiroyuki</creatorcontrib><creatorcontrib>Irie, Junichiro</creatorcontrib><creatorcontrib>Kishimoto, Taishiro</creatorcontrib><title>Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index</title><title>PloS one</title><description>There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. 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. 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 [greater than or equal to] 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). Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.</description><subject>Behavior</subject><subject>Biology and Life Sciences</subject><subject>Blood sugar</subject><subject>Blood sugar monitoring</subject><subject>Body mass</subject><subject>Body mass index</subject><subject>Body size</subject><subject>Body weight</subject><subject>Cardiovascular disease</subject><subject>Clinical trials</subject><subject>Complications and side effects</subject><subject>Consumer electronics industry</subject><subject>Diabetes</subject><subject>Diagnosis</subject><subject>Diet</subject><subject>Eating</subject><subject>Eating behavior</subject><subject>Ethical standards</subject><subject>Food habits</subject><subject>Food intake</subject><subject>Glucose</subject><subject>Glucose monitoring</subject><subject>Glycosylated hemoglobin</subject><subject>Health aspects</subject><subject>Hyperglycemia</subject><subject>Medicine and Health Sciences</subject><subject>Monitoring</subject><subject>Multivariate analysis</subject><subject>Nutrition research</subject><subject>Obesity</subject><subject>Overweight</subject><subject>Physical Sciences</subject><subject>Prediabetic state</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Sensors</subject><subject>Social Sciences</subject><subject>Software</subject><subject>Type 2 diabetes</subject><subject>Underweight</subject><subject>Wearable computers</subject><subject>Wearable 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one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kashiwagi, Kazuhiro</au><au>Inaishi, Jun</au><au>Kinoshita, Shotaro</au><au>Wada, Yasuyo</au><au>Hanashiro, Sayaka</au><au>Shiga, Kiko</au><au>Kitazawa, Momoko</au><au>Tsutsumi, Shiori</au><au>Yamakawa, Hiroyuki</au><au>Irie, Junichiro</au><au>Kishimoto, Taishiro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index</atitle><jtitle>PloS one</jtitle><date>2023-10-04</date><risdate>2023</risdate><volume>18</volume><issue>10</issue><spage>e0291923</spage><epage>e0291923</epage><pages>e0291923-e0291923</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. 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. 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 [greater than or equal to] 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). Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>37792730</pmid><doi>10.1371/journal.pone.0291923</doi><tpages>e0291923</tpages><orcidid>https://orcid.org/0000-0002-6301-1466</orcidid><orcidid>https://orcid.org/0000-0003-2662-4121</orcidid><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2023-10, Vol.18 (10), p.e0291923-e0291923 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2872779743 |
| source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Behavior Biology and Life Sciences Blood sugar Blood sugar monitoring Body mass Body mass index Body size Body weight Cardiovascular disease Clinical trials Complications and side effects Consumer electronics industry Diabetes Diagnosis Diet Eating Eating behavior Ethical standards Food habits Food intake Glucose Glucose monitoring Glycosylated hemoglobin Health aspects Hyperglycemia Medicine and Health Sciences Monitoring Multivariate analysis Nutrition research Obesity Overweight Physical Sciences Prediabetic state Questionnaires Regression analysis Sensors Social Sciences Software Type 2 diabetes Underweight Wearable computers Wearable technology |
| title | Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T23%3A16%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessment%20of%20glycemic%20variability%20and%20lifestyle%20behaviors%20in%20healthy%20nondiabetic%20individuals%20according%20to%20the%20categories%20of%20body%20mass%20index&rft.jtitle=PloS%20one&rft.au=Kashiwagi,%20Kazuhiro&rft.date=2023-10-04&rft.volume=18&rft.issue=10&rft.spage=e0291923&rft.epage=e0291923&rft.pages=e0291923-e0291923&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0291923&rft_dat=%3Cgale_plos_%3EA767746539%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2872779743&rft_id=info:pmid/37792730&rft_galeid=A767746539&rft_doaj_id=oai_doaj_org_article_bde794bcb7024767afee5c980cebf074&rfr_iscdi=true |