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A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data

BACKGROUND: Examination of meal intakes can elucidate the role of individual meals or meal patterns in health not evident by examining nutrient and food intakes. To date, meal-based research has been limited to focus on population rather than individual intakes, without considering portions or nutri...

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Autores principales: O'Hara, Cathal, O'Sullivan, Aifric, Gibney, Eileen R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535445/
https://www.ncbi.nlm.nih.gov/pubmed/35816468
http://dx.doi.org/10.1093/jn/nxac151
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author O'Hara, Cathal
O'Sullivan, Aifric
Gibney, Eileen R
author_facet O'Hara, Cathal
O'Sullivan, Aifric
Gibney, Eileen R
author_sort O'Hara, Cathal
collection PubMed
description BACKGROUND: Examination of meal intakes can elucidate the role of individual meals or meal patterns in health not evident by examining nutrient and food intakes. To date, meal-based research has been limited to focus on population rather than individual intakes, without considering portions or nutrient content when characterizing meals. OBJECTIVES: We aimed to characterize meals commonly consumed, incorporating portions and nutritional content, and to determine the accuracy of nutrient intake estimates using these meals at both population and individual levels. METHODS: The 2008–2010 Irish National Adult Nutrition Survey (NANS) data were used. A total of 1500 participants, with a mean ± SD age of 44.5 ± 17.0 y and BMI of 27.1 ± 5.0 kg/m(2), recorded their intake using a 4-d weighed food diary. Food groups were identified using k-means clustering. Partitioning around the medoids clustering was used to categorize similar meals into groups (generic meals) based on their Nutrient Rich Foods Index (NRF9.3) score and the food groups that they contained. The nutrient content for each generic meal was defined as the mean content of the grouped meals. Seven standard portion sizes were defined for each generic meal. Mean daily nutrient intakes were estimated using the original and the generic data. RESULTS: The 27,336 meals consumed were aggregated to 63 generic meals. Effect sizes from the comparisons of mean daily nutrient intakes (from the original compared with generic meals) were negligible or small, with P values ranging from <0.001 to 0.941. When participants were classified according to nutrient-based guidelines (high, adequate, or low), the proportion of individuals who were classified into the same category ranged from 55.3% to 91.5%. CONCLUSIONS: A generic meal–based method can estimate nutrient intakes based on meal rather than food intake at the sample population and individual levels. Future work will focus on incorporating this concept into a meal-based dietary intake assessment tool.
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spelling pubmed-95354452022-10-07 A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data O'Hara, Cathal O'Sullivan, Aifric Gibney, Eileen R J Nutr Methodology and Mathematical Modeling BACKGROUND: Examination of meal intakes can elucidate the role of individual meals or meal patterns in health not evident by examining nutrient and food intakes. To date, meal-based research has been limited to focus on population rather than individual intakes, without considering portions or nutrient content when characterizing meals. OBJECTIVES: We aimed to characterize meals commonly consumed, incorporating portions and nutritional content, and to determine the accuracy of nutrient intake estimates using these meals at both population and individual levels. METHODS: The 2008–2010 Irish National Adult Nutrition Survey (NANS) data were used. A total of 1500 participants, with a mean ± SD age of 44.5 ± 17.0 y and BMI of 27.1 ± 5.0 kg/m(2), recorded their intake using a 4-d weighed food diary. Food groups were identified using k-means clustering. Partitioning around the medoids clustering was used to categorize similar meals into groups (generic meals) based on their Nutrient Rich Foods Index (NRF9.3) score and the food groups that they contained. The nutrient content for each generic meal was defined as the mean content of the grouped meals. Seven standard portion sizes were defined for each generic meal. Mean daily nutrient intakes were estimated using the original and the generic data. RESULTS: The 27,336 meals consumed were aggregated to 63 generic meals. Effect sizes from the comparisons of mean daily nutrient intakes (from the original compared with generic meals) were negligible or small, with P values ranging from <0.001 to 0.941. When participants were classified according to nutrient-based guidelines (high, adequate, or low), the proportion of individuals who were classified into the same category ranged from 55.3% to 91.5%. CONCLUSIONS: A generic meal–based method can estimate nutrient intakes based on meal rather than food intake at the sample population and individual levels. Future work will focus on incorporating this concept into a meal-based dietary intake assessment tool. Oxford University Press 2022-07-11 /pmc/articles/PMC9535445/ /pubmed/35816468 http://dx.doi.org/10.1093/jn/nxac151 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology and Mathematical Modeling
O'Hara, Cathal
O'Sullivan, Aifric
Gibney, Eileen R
A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data
title A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data
title_full A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data
title_fullStr A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data
title_full_unstemmed A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data
title_short A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data
title_sort clustering approach to meal-based analysis of dietary intakes applied to population and individual data
topic Methodology and Mathematical Modeling
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535445/
https://www.ncbi.nlm.nih.gov/pubmed/35816468
http://dx.doi.org/10.1093/jn/nxac151
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