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Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics

BACKGROUND: Since both dietary carbohydrate and fatty acids separately affect carbohydrate metabolism, how dietary macronutrients distribution may have different effects on carbohydrate metabolism pathways and regulation of blood glucose especially in diabetic patients. METHODS: In this cross-sectio...

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Autores principales: Shadman, Zhaleh, Khoshniat, Mohsen, Poorsoltan, Nooshin, Akhoundan, Mahdieh, Omidvar, Maryam, Larijani, Bagher, Hoseini, Saeed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3891984/
https://www.ncbi.nlm.nih.gov/pubmed/23767760
http://dx.doi.org/10.1186/2251-6581-12-27
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author Shadman, Zhaleh
Khoshniat, Mohsen
Poorsoltan, Nooshin
Akhoundan, Mahdieh
Omidvar, Maryam
Larijani, Bagher
Hoseini, Saeed
author_facet Shadman, Zhaleh
Khoshniat, Mohsen
Poorsoltan, Nooshin
Akhoundan, Mahdieh
Omidvar, Maryam
Larijani, Bagher
Hoseini, Saeed
author_sort Shadman, Zhaleh
collection PubMed
description BACKGROUND: Since both dietary carbohydrate and fatty acids separately affect carbohydrate metabolism, how dietary macronutrients distribution may have different effects on carbohydrate metabolism pathways and regulation of blood glucose especially in diabetic patients. METHODS: In this cross-sectional study 750 type 2 diabetic patients (261 men and 489 women, aged 35–65 years),who at least two years were followed in Diabetes and Metabolic disease Clinic of Tehran University of Medical Sciences, were recruited according to inclusion and exclusion criteria by simple sampling. Dietary data were collected by a validated food frequency questionnaire. Other variables were anthropometric measurements, Stress, physical activity level, Biochemical analyses including fasting and postprandial plasma glucose, Glycated hemoglobin, total cholesterol, low and high density lipoproteins, triglycerides and 25-hydoxy D(3). Linear regression models were used to assess the association of covariates with the mean concentrations of HbA(1C) in quintiles and multivariate linear regression model was used to distinguish the impacts of dietary macronutrient composition of the diet. RESULTS: Carbohydrate and dietary fiber intakes were inversely (P: < 0.0001 and 0.003 respectively) and dietary amount and proportion of saturated, mono-unsaturated and poly-unsaturated fatty were positively (P: < 0.0001, 0.03, 0.01 and 0.01 respectively) associated with HbA(1C) concentrations. Multivariate linear regression macronutrient density model that controlled for age, sex, diabetes duration and calorie intake showed that carbohydrate was inversely associated with HbA(1C) (P < 0.0001, R(2) = 15%). Results were also the same in the other three models adjusted for stress and exercise levels in model 2, waist circumference and sum of meals in model 3 and serum triglyceride and 25-hydroxy vitamin D in model 4(P < .0001, <.0001 and 0.0003 respectively). Calorie intake of 25 Kcal/body weight was identified as a cut of point of the negative effect of dietary carbohydrate and 30 for the positive effect of fat on HbA1c respectively (P = 0.04 and 0.03). Moreover, carbohydrate intake was positively (β = 0.08, P = 0.01) and protein (β = −0.04, P < 0.0001), SAFA (β = −0.04, P < 0.0001) and MUFA (β = −0.02, 0.07) proportion were negatively associated with increment in calorie intake. CONCLUSION: This study showed that the substitution of fat for carbohydrate is associated with low concentrations of HbA1c in high calorie consuming type 2 diabetic patients.
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spelling pubmed-38919842014-01-15 Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics Shadman, Zhaleh Khoshniat, Mohsen Poorsoltan, Nooshin Akhoundan, Mahdieh Omidvar, Maryam Larijani, Bagher Hoseini, Saeed J Diabetes Metab Disord Research Article BACKGROUND: Since both dietary carbohydrate and fatty acids separately affect carbohydrate metabolism, how dietary macronutrients distribution may have different effects on carbohydrate metabolism pathways and regulation of blood glucose especially in diabetic patients. METHODS: In this cross-sectional study 750 type 2 diabetic patients (261 men and 489 women, aged 35–65 years),who at least two years were followed in Diabetes and Metabolic disease Clinic of Tehran University of Medical Sciences, were recruited according to inclusion and exclusion criteria by simple sampling. Dietary data were collected by a validated food frequency questionnaire. Other variables were anthropometric measurements, Stress, physical activity level, Biochemical analyses including fasting and postprandial plasma glucose, Glycated hemoglobin, total cholesterol, low and high density lipoproteins, triglycerides and 25-hydoxy D(3). Linear regression models were used to assess the association of covariates with the mean concentrations of HbA(1C) in quintiles and multivariate linear regression model was used to distinguish the impacts of dietary macronutrient composition of the diet. RESULTS: Carbohydrate and dietary fiber intakes were inversely (P: < 0.0001 and 0.003 respectively) and dietary amount and proportion of saturated, mono-unsaturated and poly-unsaturated fatty were positively (P: < 0.0001, 0.03, 0.01 and 0.01 respectively) associated with HbA(1C) concentrations. Multivariate linear regression macronutrient density model that controlled for age, sex, diabetes duration and calorie intake showed that carbohydrate was inversely associated with HbA(1C) (P < 0.0001, R(2) = 15%). Results were also the same in the other three models adjusted for stress and exercise levels in model 2, waist circumference and sum of meals in model 3 and serum triglyceride and 25-hydroxy vitamin D in model 4(P < .0001, <.0001 and 0.0003 respectively). Calorie intake of 25 Kcal/body weight was identified as a cut of point of the negative effect of dietary carbohydrate and 30 for the positive effect of fat on HbA1c respectively (P = 0.04 and 0.03). Moreover, carbohydrate intake was positively (β = 0.08, P = 0.01) and protein (β = −0.04, P < 0.0001), SAFA (β = −0.04, P < 0.0001) and MUFA (β = −0.02, 0.07) proportion were negatively associated with increment in calorie intake. CONCLUSION: This study showed that the substitution of fat for carbohydrate is associated with low concentrations of HbA1c in high calorie consuming type 2 diabetic patients. BioMed Central 2013-06-14 /pmc/articles/PMC3891984/ /pubmed/23767760 http://dx.doi.org/10.1186/2251-6581-12-27 Text en © Shadman et al.; licensee BioMed Central Ltd. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Shadman, Zhaleh
Khoshniat, Mohsen
Poorsoltan, Nooshin
Akhoundan, Mahdieh
Omidvar, Maryam
Larijani, Bagher
Hoseini, Saeed
Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
title Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
title_full Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
title_fullStr Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
title_full_unstemmed Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
title_short Association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
title_sort association of high carbohydrate versus high fat diet with glycated hemoglobin in high calorie consuming type 2 diabetics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3891984/
https://www.ncbi.nlm.nih.gov/pubmed/23767760
http://dx.doi.org/10.1186/2251-6581-12-27
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