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Non-Nutritive (Artificial) Sweetener Knowledge among University Students

This study determined non-nutritive sweetener (NNS; artificial sweetener) depth of knowledge among university health and science students. An online survey was delivered to 1248 science students and completed by 493 respondents (19.0 ± 2.2 years old), evaluating ability to provide an NNS description...

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Detalles Bibliográficos
Autores principales: Wilson, Ted, Murray, Breanna, Price, Tamara, Atherton, Denzel, Hooks, Tisha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769725/
https://www.ncbi.nlm.nih.gov/pubmed/31547360
http://dx.doi.org/10.3390/nu11092201
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author Wilson, Ted
Murray, Breanna
Price, Tamara
Atherton, Denzel
Hooks, Tisha
author_facet Wilson, Ted
Murray, Breanna
Price, Tamara
Atherton, Denzel
Hooks, Tisha
author_sort Wilson, Ted
collection PubMed
description This study determined non-nutritive sweetener (NNS; artificial sweetener) depth of knowledge among university health and science students. An online survey was delivered to 1248 science students and completed by 493 respondents (19.0 ± 2.2 years old), evaluating ability to provide an NNS description/definition, examples of NNS from memory, and evaluate NNS word familiarity with a click-drag-box to identify six NNS by chemical name (CN) and six NNS by trade name (TN), relative to six decoy NNS, six caloric sweeteners, and six food items (mean ± standard deviation). NNS definitions contained 1.1 ± 1.1 of four previously defined elements suggestive of knowledge depth, with highest scores among self-described non-NNS users and food ingredient label users. Knowledge depth was not correlated with gender, age, American College Test score, or history of weight loss attempts. Without prompting, respondents could name 0.9 ± 1.1 NNS from memory, with highest scores among self-described non-NNS users (1.4 ± 0.8) and food ingredient label users (1.4 ± 0.8). NNS example memory was not correlated with gender, age, ACT score, or history of weight loss attempts. With the click-drag-box exercise, NNS were correctly identified 4.9 ± 1.0 times by TN and significantly less by CN (3.9 ± 1.9 times). Decoy NNS were incorrectly identified as being a real NNS 4.7 ± 1.3 times, while caloric sweeteners and food items were incorrectly identified as NNS 1.7 ± 1.7 times and 1.0 ± 1.5 times, (TN and Decoy NNS > CN > caloric sweetener and food item). NNS knowledge among university students may be inadequate for understanding what NNS are, if they consume NNS, or whether NNS are important for dietary health.
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spelling pubmed-67697252019-10-30 Non-Nutritive (Artificial) Sweetener Knowledge among University Students Wilson, Ted Murray, Breanna Price, Tamara Atherton, Denzel Hooks, Tisha Nutrients Communication This study determined non-nutritive sweetener (NNS; artificial sweetener) depth of knowledge among university health and science students. An online survey was delivered to 1248 science students and completed by 493 respondents (19.0 ± 2.2 years old), evaluating ability to provide an NNS description/definition, examples of NNS from memory, and evaluate NNS word familiarity with a click-drag-box to identify six NNS by chemical name (CN) and six NNS by trade name (TN), relative to six decoy NNS, six caloric sweeteners, and six food items (mean ± standard deviation). NNS definitions contained 1.1 ± 1.1 of four previously defined elements suggestive of knowledge depth, with highest scores among self-described non-NNS users and food ingredient label users. Knowledge depth was not correlated with gender, age, American College Test score, or history of weight loss attempts. Without prompting, respondents could name 0.9 ± 1.1 NNS from memory, with highest scores among self-described non-NNS users (1.4 ± 0.8) and food ingredient label users (1.4 ± 0.8). NNS example memory was not correlated with gender, age, ACT score, or history of weight loss attempts. With the click-drag-box exercise, NNS were correctly identified 4.9 ± 1.0 times by TN and significantly less by CN (3.9 ± 1.9 times). Decoy NNS were incorrectly identified as being a real NNS 4.7 ± 1.3 times, while caloric sweeteners and food items were incorrectly identified as NNS 1.7 ± 1.7 times and 1.0 ± 1.5 times, (TN and Decoy NNS > CN > caloric sweetener and food item). NNS knowledge among university students may be inadequate for understanding what NNS are, if they consume NNS, or whether NNS are important for dietary health. MDPI 2019-09-12 /pmc/articles/PMC6769725/ /pubmed/31547360 http://dx.doi.org/10.3390/nu11092201 Text en © 2019 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 Communication
Wilson, Ted
Murray, Breanna
Price, Tamara
Atherton, Denzel
Hooks, Tisha
Non-Nutritive (Artificial) Sweetener Knowledge among University Students
title Non-Nutritive (Artificial) Sweetener Knowledge among University Students
title_full Non-Nutritive (Artificial) Sweetener Knowledge among University Students
title_fullStr Non-Nutritive (Artificial) Sweetener Knowledge among University Students
title_full_unstemmed Non-Nutritive (Artificial) Sweetener Knowledge among University Students
title_short Non-Nutritive (Artificial) Sweetener Knowledge among University Students
title_sort non-nutritive (artificial) sweetener knowledge among university students
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769725/
https://www.ncbi.nlm.nih.gov/pubmed/31547360
http://dx.doi.org/10.3390/nu11092201
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