The association between deficiency of nutrient intake and resting metabolic rate in overweight and obese women: a cross-sectional study

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Abstract

Objective

The double burden of malnutrition is an emerging public health concern nowadays which a correlation with obesity. This study aimed to examine the relationship between resting metabolic rate (RMR) and dietary intake of zinc, vitamin C, and riboflavin in overweight and obese women.

Results

The RMR/FFM showed a significant association with riboflavin (β = 1.59; 95% CI 1.04–23.26, P = 0.04) and zinc (β = 0.78; 95% CI 1.04–4.61, P = 0.03) in the crude model. Moreover, differences in vitamin C and RMR/FFM was marginal significant (β = 0.75; 95% CI 0.95–4.77, P = 0.06). After adjusting for confounders the riboflavin association change to marginal significance (β = 1.52; 95% CI 0.91–23.04, P = 0.06). After controlling for potential confounders, the associations change between zinc and RMR/FFM (β = 0.66; 95% CI 0.78–4.86, P = 0.15) and between RMR/FFM and vitamin C (β = 0.48; 95% CI 0.66–3.96, P = 0.28). Our study showed a significant association between dietary intake of zinc, riboflavin, and vitamin C and change in RMR/FFM in overweight and obese women.

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Most cited references 36

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Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

D. Matthews, J Hosker, A Rudenski … (1985)

The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.

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Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

S Nambi, K Mather, A. Katz … (2000)

Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.

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Dietary pattern analysis: a new direction in nutritional epidemiology.

Frank Hu (2002)

Recently, dietary pattern analysis has emerged as an alternative and complementary approach to examining the relationship between diet and the risk of chronic diseases. Instead of looking at individual nutrients or foods, pattern analysis examines the effects of overall diet. Conceptually, dietary patterns represent a broader picture of food and nutrient consumption, and may thus be more predictive of disease risk than individual foods or nutrients. Several studies have suggested that dietary patterns derived from factor or cluster analysis predict disease risk or mortality. In addition, there is growing interest in using dietary quality indices to evaluate whether adherence to a certain dietary pattern (e.g. Mediterranean pattern) or current dietary guidelines lowers the risk of disease. In this review, we describe the rationale for studying dietary patterns, and discuss quantitative methods for analysing dietary patterns and their reproducibility and validity, and the available evidence regarding the relationship between major dietary patterns and the risk of cardiovascular disease.

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Author and article information

Contributors

Seyedeh Forough Sajjadi: frq.sajadi@gmail.com

Atieh Mirzababaei: ati_babaee@yahoo.com

Afsoun Abdollahi: mirzaei_kh@sina.tums.ac.ir

Farideh Shiraseb: farideh_shiraseb@yahoo.com

Khadijeh Mirzaei:

ORCID: http://orcid.org/0000-0002-7554-8551

mirzaei_kh@tums.ac.ir

Journal

Journal ID (nlm-ta): BMC Res Notes

Journal ID (iso-abbrev): BMC Res Notes

Title: BMC Research Notes

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-0500

Publication date (Electronic): 12 May 2021

Publication date PMC-release: 12 May 2021

Publication date Collection: 2021

Volume: 14

Electronic Location Identifier: 179

Affiliations

[1 ]GRID grid.411705.6, ISNI 0000 0001 0166 0922, Department of Community Nutrition, School of Nutritional Sciences and Dietetics, , Tehran University of Medical Sciences (TUMS), ; P.O. Box: 14155-6117, Tehran, Iran

[2 ]GRID grid.169077.e, ISNI 0000 0004 1937 2197, Department of Nutrition Science, , Purdue University, ; West Lafayette, IN 47907 USA

Author information

Khadijeh Mirzaei http://orcid.org/0000-0002-7554-8551

Article

Publisher ID: 5582

DOI: 10.1186/s13104-021-05582-z

PMC ID: 8117621

PubMed ID: 33980283

SO-VID: 0009332d-120a-481f-b6fc-c1733a9d36a2

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 28 November 2020

Date accepted : 22 April 2021

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ScienceOpen disciplines: Medicine

Keywords: resting metabolic rate,fat-free mass,obesity,overweight,the double burden of malnutrition,nutrient adequacy ratio

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ScienceOpen disciplines: Medicine

Keywords: resting metabolic rate, fat-free mass, obesity, overweight, the double burden of malnutrition, nutrient adequacy ratio

The association between deficiency of nutrient intake and resting metabolic rate in overweight and obese women: a cross-sectional study

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Abstract

Objective

Results

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Karger: Nutrition and Dietetics

Most cited references 36

Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

Dietary pattern analysis: a new direction in nutritional epidemiology.

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