Cargando…
Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes
BACKGROUND: Continuous glucose monitors (CGMs) provide high-frequency information regarding daily glucose variation and are recognised as effective for improving glycaemic control in individuals living with diabetes. Despite increased use in individuals with non-diabetic blood glucose concentrations...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635370/ https://www.ncbi.nlm.nih.gov/pubmed/37961419 http://dx.doi.org/10.21203/rs.3.rs-3469475/v1 |
_version_ | 1785146334730256384 |
---|---|
author | Bermingham, Kate M. Smith, Harry A. Gonzalez, Javier T. Duncan, Emma L Valdes, Ana M. Franks, Paul W. Delahanty, Linda Dashti, Hassan S. Davies, Richard Hadjigeorgiou, George Wolf, Jonathan Chan, Andrew T. Spector, Tim D. Berry, Sarah E. |
author_facet | Bermingham, Kate M. Smith, Harry A. Gonzalez, Javier T. Duncan, Emma L Valdes, Ana M. Franks, Paul W. Delahanty, Linda Dashti, Hassan S. Davies, Richard Hadjigeorgiou, George Wolf, Jonathan Chan, Andrew T. Spector, Tim D. Berry, Sarah E. |
author_sort | Bermingham, Kate M. |
collection | PubMed |
description | BACKGROUND: Continuous glucose monitors (CGMs) provide high-frequency information regarding daily glucose variation and are recognised as effective for improving glycaemic control in individuals living with diabetes. Despite increased use in individuals with non-diabetic blood glucose concentrations (euglycemia), their utility as a health tool in this population remains unclear. OBJECTIVES: To characterise variation in time in range (TIR) and glycaemic variability in large populations without diabetes or impaired glucose tolerance; describe associations between CGM-derived glycaemic metrics and metabolic and cardiometabolic health traits; identify key diet and lifestyle factors associated with TIR and glycaemic variability. DESIGN: Glycaemic variability (coefficient of variation) and time spent in both the ADA secondary target range (TIR(ADA); 3.9–7.8 mmol/L) and a more stringent range (TIR(3.9–5.6); 3.9–5.6 mmol/L) were calculated during free-living in PREDICT 1, PREDICT 2, and PREDICT 3 euglycaemic community-based volunteer cohorts. Associations between CGM derived glycaemic metrics, markers of cardiometabolic health, diet (food frequency questionnaire and logged diet records), diet-habits, and lifestyle were explored. RESULTS: Data from N=4135 participants (Mean SD; Age: 47 12 y; Sex: 83% Female, BMI: 27 6 kg/m(2)). Median glycaemic variability was 14.8% (IQR 12.6–17.6%), median TIR(ADA) was 95.8% (IQR 89.6–98.6%) and TIR(3.9–5.6) was 75.0% (IQR 64.6–82.8%). Greater TIR(3.9–5.6) was associated with lower HbA1c, ASCVD 10y risk and HOMA-IR (all p < 0.05). Lower glycaemic variability was associated with lower % energy derived from carbohydrate (r(s): 0.17, p < 0.01), ultra-processed foods (NOVA 4, % EI; r(s): 0.12, p = 0.01) and a longer overnight fasting duration (r(s): −0.10, p = 0.01). CONCLUSIONS: A stringent TIR target provides sensitivity to detect changes in HOMA-IR, ASCVD 10 y risk and HbA1c that were not detected using ADA secondary targets. Associations among TIR, glycaemic variability, dietary intake (e.g. carbohydrate and protein) and habits (e.g. nocturnal fasting duration) highlight potential strategic targets to improve glycaemic metrics derived from continuous glucose monitors. |
format | Online Article Text |
id | pubmed-10635370 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-106353702023-11-13 Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes Bermingham, Kate M. Smith, Harry A. Gonzalez, Javier T. Duncan, Emma L Valdes, Ana M. Franks, Paul W. Delahanty, Linda Dashti, Hassan S. Davies, Richard Hadjigeorgiou, George Wolf, Jonathan Chan, Andrew T. Spector, Tim D. Berry, Sarah E. Res Sq Article BACKGROUND: Continuous glucose monitors (CGMs) provide high-frequency information regarding daily glucose variation and are recognised as effective for improving glycaemic control in individuals living with diabetes. Despite increased use in individuals with non-diabetic blood glucose concentrations (euglycemia), their utility as a health tool in this population remains unclear. OBJECTIVES: To characterise variation in time in range (TIR) and glycaemic variability in large populations without diabetes or impaired glucose tolerance; describe associations between CGM-derived glycaemic metrics and metabolic and cardiometabolic health traits; identify key diet and lifestyle factors associated with TIR and glycaemic variability. DESIGN: Glycaemic variability (coefficient of variation) and time spent in both the ADA secondary target range (TIR(ADA); 3.9–7.8 mmol/L) and a more stringent range (TIR(3.9–5.6); 3.9–5.6 mmol/L) were calculated during free-living in PREDICT 1, PREDICT 2, and PREDICT 3 euglycaemic community-based volunteer cohorts. Associations between CGM derived glycaemic metrics, markers of cardiometabolic health, diet (food frequency questionnaire and logged diet records), diet-habits, and lifestyle were explored. RESULTS: Data from N=4135 participants (Mean SD; Age: 47 12 y; Sex: 83% Female, BMI: 27 6 kg/m(2)). Median glycaemic variability was 14.8% (IQR 12.6–17.6%), median TIR(ADA) was 95.8% (IQR 89.6–98.6%) and TIR(3.9–5.6) was 75.0% (IQR 64.6–82.8%). Greater TIR(3.9–5.6) was associated with lower HbA1c, ASCVD 10y risk and HOMA-IR (all p < 0.05). Lower glycaemic variability was associated with lower % energy derived from carbohydrate (r(s): 0.17, p < 0.01), ultra-processed foods (NOVA 4, % EI; r(s): 0.12, p = 0.01) and a longer overnight fasting duration (r(s): −0.10, p = 0.01). CONCLUSIONS: A stringent TIR target provides sensitivity to detect changes in HOMA-IR, ASCVD 10 y risk and HbA1c that were not detected using ADA secondary targets. Associations among TIR, glycaemic variability, dietary intake (e.g. carbohydrate and protein) and habits (e.g. nocturnal fasting duration) highlight potential strategic targets to improve glycaemic metrics derived from continuous glucose monitors. American Journal Experts 2023-10-30 /pmc/articles/PMC10635370/ /pubmed/37961419 http://dx.doi.org/10.21203/rs.3.rs-3469475/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Bermingham, Kate M. Smith, Harry A. Gonzalez, Javier T. Duncan, Emma L Valdes, Ana M. Franks, Paul W. Delahanty, Linda Dashti, Hassan S. Davies, Richard Hadjigeorgiou, George Wolf, Jonathan Chan, Andrew T. Spector, Tim D. Berry, Sarah E. Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
title | Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
title_full | Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
title_fullStr | Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
title_full_unstemmed | Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
title_short | Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
title_sort | glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635370/ https://www.ncbi.nlm.nih.gov/pubmed/37961419 http://dx.doi.org/10.21203/rs.3.rs-3469475/v1 |
work_keys_str_mv | AT berminghamkatem glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT smithharrya glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT gonzalezjaviert glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT duncanemmal glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT valdesanam glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT frankspaulw glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT delahantylinda glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT dashtihassans glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT daviesrichard glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT hadjigeorgiougeorge glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT wolfjonathan glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT chanandrewt glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT spectortimd glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes AT berrysarahe glycaemicvariabilityassessedwithcontinuousglucosemonitorsisassociatedwithdietlifestyleandhealthinpeoplewithoutdiabetes |