Danesi, F, Mengucci, C, Vita, S et al. (10 more authors) (2021) Unveiling the Correlation between Inadequate Energy/Macronutrient Intake and Clinical Alterations in Volunteers at Risk of Metabolic Syndrome by a Predictive Model. Nutrients, 13 (4). 1377. ISSN 2072-6643
Abstract
Although lifestyle-based interventions are the most effective to prevent metabolic syndrome (MetS), there is no definitive agreement on which nutritional approach is the best. The aim of the present retrospective analysis was to identify a multivariate model linking energy and macronutrient intake to the clinical features of MetS. Volunteers at risk of MetS (F = 77, M = 80) were recruited in four European centres and finally eligible for analysis. For each subject, the daily energy and nutrient intake was estimated using the EPIC questionnaire and a 24-h dietary recall, and it was compared with the dietary reference values. Then we built a predictive model for a set of clinical outcomes computing shifts from recommended intake thresholds. The use of the ridge regression, which optimises prediction performances while retaining information about the role of all the nutritional variables, allowed us to assess if a clinical outcome was manly dependent on a single nutritional variable, or if its prediction was characterised by more complex interactions between the variables. The model appeared suitable for shedding light on the complexity of nutritional variables, which effects could be not evident with univariate analysis and must be considered in the framework of the reciprocal influence of the other variables.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | metabolic syndrome; energy intake; macronutrient intake; penalised models; feature shrinkage; prevention |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Food Science and Nutrition (Leeds) > FSN Nutrition and Public Health (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Jun 2021 13:08 |
Last Modified: | 22 Jun 2021 13:08 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/nu13041377 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:175138 |