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Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study

BACKGROUND: Nutrition knowledge is an important determinant of diet-related behaviour; however, the use of disparate assessment tools creates challenges for comparing nutrition knowledge levels and correlates across studies, geographic contexts, and populations. Using the Food Processing Knowledge (...

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Autores principales: Bhawra, Jasmin, Kirkpatrick, Sharon I., Hall, Marissa G., Vanderlee, Lana, White, Christine M., Hammond, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018957/
https://www.ncbi.nlm.nih.gov/pubmed/36922823
http://dx.doi.org/10.1186/s12937-023-00844-x
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author Bhawra, Jasmin
Kirkpatrick, Sharon I.
Hall, Marissa G.
Vanderlee, Lana
White, Christine M.
Hammond, David
author_facet Bhawra, Jasmin
Kirkpatrick, Sharon I.
Hall, Marissa G.
Vanderlee, Lana
White, Christine M.
Hammond, David
author_sort Bhawra, Jasmin
collection PubMed
description BACKGROUND: Nutrition knowledge is an important determinant of diet-related behaviour; however, the use of disparate assessment tools creates challenges for comparing nutrition knowledge levels and correlates across studies, geographic contexts, and populations. Using the Food Processing Knowledge (FoodProK) score – a measure of nutrition knowledge based on consumers’ ability to understand and apply the concept of food processing in a functional task – nutrition knowledge levels and associated correlates were assessed in five countries. METHODS: Adults, aged ≥18 years, were recruited through the Nielsen Consumer Insights Global Panel in Australia (n = 3997), Canada (n = 4170), Mexico (n = 4044), the United Kingdom (UK) (n = 5363), and the United States (US) (n = 4527). Respondents completed web-based surveys in November–December 2018. Functional nutrition knowledge was measured using the FoodProK score. Linear regression models examined associations between FoodProK score and sociodemographic, dietary behaviours, and knowledge-related characteristics. RESULTS: FoodProK scores (maximum, 8 points) were highest in Canada (mean: 5.1) and Australia (5.0), followed by the UK (4.8), Mexico (4.7), and the US (4.6). Health literacy and self-rated nutrition knowledge were positively associated with FoodProK scores (p < .001). FoodProK scores were higher among those who reported vegetarian/other dietary practices (p < .001); made efforts to consume less sodium, trans fats, or sugars (p < .001); ≥60 years (p = 0.002), female (p < .001), and ‘majority’ ethnic group respondents in their respective countries (p < .001). CONCLUSIONS: This study found differences in consumers’ ability to distinguish levels of food processing for common foods, with somewhat lower levels of nutrition knowledge in countries with the highest intake of highly processed foods. Nutrition knowledge differences based on consumer characteristics highlight the need for accessible policy interventions that support uptake of healthy eating efforts across populations to avoid exacerbating nutrition-related disparities. Tools such as the FoodProK can be used to evaluate the impact of policies targeting nutrition knowledge across contexts.
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spelling pubmed-100189572023-03-17 Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study Bhawra, Jasmin Kirkpatrick, Sharon I. Hall, Marissa G. Vanderlee, Lana White, Christine M. Hammond, David Nutr J Research BACKGROUND: Nutrition knowledge is an important determinant of diet-related behaviour; however, the use of disparate assessment tools creates challenges for comparing nutrition knowledge levels and correlates across studies, geographic contexts, and populations. Using the Food Processing Knowledge (FoodProK) score – a measure of nutrition knowledge based on consumers’ ability to understand and apply the concept of food processing in a functional task – nutrition knowledge levels and associated correlates were assessed in five countries. METHODS: Adults, aged ≥18 years, were recruited through the Nielsen Consumer Insights Global Panel in Australia (n = 3997), Canada (n = 4170), Mexico (n = 4044), the United Kingdom (UK) (n = 5363), and the United States (US) (n = 4527). Respondents completed web-based surveys in November–December 2018. Functional nutrition knowledge was measured using the FoodProK score. Linear regression models examined associations between FoodProK score and sociodemographic, dietary behaviours, and knowledge-related characteristics. RESULTS: FoodProK scores (maximum, 8 points) were highest in Canada (mean: 5.1) and Australia (5.0), followed by the UK (4.8), Mexico (4.7), and the US (4.6). Health literacy and self-rated nutrition knowledge were positively associated with FoodProK scores (p < .001). FoodProK scores were higher among those who reported vegetarian/other dietary practices (p < .001); made efforts to consume less sodium, trans fats, or sugars (p < .001); ≥60 years (p = 0.002), female (p < .001), and ‘majority’ ethnic group respondents in their respective countries (p < .001). CONCLUSIONS: This study found differences in consumers’ ability to distinguish levels of food processing for common foods, with somewhat lower levels of nutrition knowledge in countries with the highest intake of highly processed foods. Nutrition knowledge differences based on consumer characteristics highlight the need for accessible policy interventions that support uptake of healthy eating efforts across populations to avoid exacerbating nutrition-related disparities. Tools such as the FoodProK can be used to evaluate the impact of policies targeting nutrition knowledge across contexts. BioMed Central 2023-03-16 /pmc/articles/PMC10018957/ /pubmed/36922823 http://dx.doi.org/10.1186/s12937-023-00844-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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.
spellingShingle Research
Bhawra, Jasmin
Kirkpatrick, Sharon I.
Hall, Marissa G.
Vanderlee, Lana
White, Christine M.
Hammond, David
Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
title Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
title_full Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
title_fullStr Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
title_full_unstemmed Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
title_short Patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
title_sort patterns and correlates of nutrition knowledge across five countries in the 2018 international food policy study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018957/
https://www.ncbi.nlm.nih.gov/pubmed/36922823
http://dx.doi.org/10.1186/s12937-023-00844-x
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