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Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial

Advances in web and mobile technologies have created efficiencies relating to collection, analysis and interpretation of dietary intake data. This study compared the impact of two levels of nutrition support: (1) low personalization, comprising a web-based personalized nutrition feedback report gene...

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Autores principales: Rollo, Megan E., Haslam, Rebecca L., Collins, Clare E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693517/
https://www.ncbi.nlm.nih.gov/pubmed/33138210
http://dx.doi.org/10.3390/nu12113334
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author Rollo, Megan E.
Haslam, Rebecca L.
Collins, Clare E.
author_facet Rollo, Megan E.
Haslam, Rebecca L.
Collins, Clare E.
author_sort Rollo, Megan E.
collection PubMed
description Advances in web and mobile technologies have created efficiencies relating to collection, analysis and interpretation of dietary intake data. This study compared the impact of two levels of nutrition support: (1) low personalization, comprising a web-based personalized nutrition feedback report generated using the Australian Eating Survey(®) (AES) food frequency questionnaire data; and (2) high personalization, involving structured video calls with a dietitian using the AES report plus dietary self-monitoring with text message feedback. Intake was measured at baseline and 12 weeks using the AES and diet quality using the Australian Recommended Food Score (ARFS). Fifty participants (aged 39.2 ± 12.5 years; Body Mass Index 26.4 ± 6.0 kg/m(2); 86.0% female) completed baseline measures. Significant (p < 0.05) between-group differences in dietary changes favored the high personalization group for total ARFS (5.6 points (95% CI 1.3 to 10.0)) and ARFS sub-scales of meat (0.9 points (0.4 to 1.6)), vegetarian alternatives (0.8 points (0.1 to 1.4)), and dairy (1.3 points (0.3 to 2.3)). Additional significant changes in favor of the high personalization group occurred for proportion of energy intake derived from energy-dense, nutrient-poor foods (−7.2% (−13.8% to −0.5%)) and takeaway foods sub-group (−3.4% (−6.5% to 0.3%). Significant within-group changes were observed for 12 dietary variables in the high personalization group vs. one variable for low personalization. A higher level of personalized support combining the AES report with one-on-one dietitian video calls and dietary self-monitoring resulted in greater dietary change compared to the AES report alone. These findings suggest nutrition-related web and mobile technologies in combination with personalized dietitian delivered advice have a greater impact compared to when used alone.
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spelling pubmed-76935172020-11-28 Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial Rollo, Megan E. Haslam, Rebecca L. Collins, Clare E. Nutrients Article Advances in web and mobile technologies have created efficiencies relating to collection, analysis and interpretation of dietary intake data. This study compared the impact of two levels of nutrition support: (1) low personalization, comprising a web-based personalized nutrition feedback report generated using the Australian Eating Survey(®) (AES) food frequency questionnaire data; and (2) high personalization, involving structured video calls with a dietitian using the AES report plus dietary self-monitoring with text message feedback. Intake was measured at baseline and 12 weeks using the AES and diet quality using the Australian Recommended Food Score (ARFS). Fifty participants (aged 39.2 ± 12.5 years; Body Mass Index 26.4 ± 6.0 kg/m(2); 86.0% female) completed baseline measures. Significant (p < 0.05) between-group differences in dietary changes favored the high personalization group for total ARFS (5.6 points (95% CI 1.3 to 10.0)) and ARFS sub-scales of meat (0.9 points (0.4 to 1.6)), vegetarian alternatives (0.8 points (0.1 to 1.4)), and dairy (1.3 points (0.3 to 2.3)). Additional significant changes in favor of the high personalization group occurred for proportion of energy intake derived from energy-dense, nutrient-poor foods (−7.2% (−13.8% to −0.5%)) and takeaway foods sub-group (−3.4% (−6.5% to 0.3%). Significant within-group changes were observed for 12 dietary variables in the high personalization group vs. one variable for low personalization. A higher level of personalized support combining the AES report with one-on-one dietitian video calls and dietary self-monitoring resulted in greater dietary change compared to the AES report alone. These findings suggest nutrition-related web and mobile technologies in combination with personalized dietitian delivered advice have a greater impact compared to when used alone. MDPI 2020-10-29 /pmc/articles/PMC7693517/ /pubmed/33138210 http://dx.doi.org/10.3390/nu12113334 Text en © 2020 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rollo, Megan E.
Haslam, Rebecca L.
Collins, Clare E.
Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial
title Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial
title_full Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial
title_fullStr Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial
title_full_unstemmed Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial
title_short Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial
title_sort impact on dietary intake of two levels of technology-assisted personalized nutrition: a randomized trial
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693517/
https://www.ncbi.nlm.nih.gov/pubmed/33138210
http://dx.doi.org/10.3390/nu12113334
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