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Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents

Large portion sizes and a high eating rate are associated with high energy intake and obesity. Most individuals maintain their food intake weight (g) and eating rate (g/min) rank in relation to their peers, despite food and environmental manipulations. Single meal measures may enable identification...

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Autores principales: Langlet, Billy, Fagerberg, Petter, Delopoulos, Anastasios, Papapanagiotou, Vasileios, Diou, Christos, Maramis, Christos, Maglaveras, Nikolaos, Anvret, Anna, Ioakimidis, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471169/
https://www.ncbi.nlm.nih.gov/pubmed/30897833
http://dx.doi.org/10.3390/nu11030672
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author Langlet, Billy
Fagerberg, Petter
Delopoulos, Anastasios
Papapanagiotou, Vasileios
Diou, Christos
Maramis, Christos
Maglaveras, Nikolaos
Anvret, Anna
Ioakimidis, Ioannis
author_facet Langlet, Billy
Fagerberg, Petter
Delopoulos, Anastasios
Papapanagiotou, Vasileios
Diou, Christos
Maramis, Christos
Maglaveras, Nikolaos
Anvret, Anna
Ioakimidis, Ioannis
author_sort Langlet, Billy
collection PubMed
description Large portion sizes and a high eating rate are associated with high energy intake and obesity. Most individuals maintain their food intake weight (g) and eating rate (g/min) rank in relation to their peers, despite food and environmental manipulations. Single meal measures may enable identification of “large portion eaters” and “fast eaters,” finding individuals at risk of developing obesity. The aim of this study was to predict real-life food intake weight and eating rate based on one school lunch. Twenty-four high-school students with a mean (±SD) age of 16.8 yr (±0.7) and body mass index of 21.9 (±4.1) were recruited, using no exclusion criteria. Food intake weight and eating rate was first self-rated (“Less,” “Average” or “More than peers”), then objectively recorded during one school lunch (absolute weight of consumed food in grams). Afterwards, subjects recorded as many main meals (breakfasts, lunches and dinners) as possible in real-life for a period of at least two weeks, using a Bluetooth connected weight scale and a smartphone application. On average participants recorded 18.9 (7.3) meals during the study. Real-life food intake weight was 327.4 g (±110.6), which was significantly lower (p = 0.027) than the single school lunch, at 367.4 g (±167.2). When the intra-class correlation of food weight intake between the objectively recorded real-life and school lunch meals was compared, the correlation was excellent (R = 0.91). Real-life eating rate was 33.5 g/min (±14.8), which was significantly higher (p = 0.010) than the single school lunch, at 27.7 g/min (±13.3). The intra-class correlation of the recorded eating rate between real-life and school lunch meals was very large (R = 0.74). The participants’ recorded food intake weights and eating rates were divided into terciles and compared between school lunches and real-life, with moderate or higher agreement (κ = 0.75 and κ = 0.54, respectively). In contrast, almost no agreement was observed between self-rated and real-life recorded rankings of food intake weight and eating rate (κ = 0.09 and κ = 0.08, respectively). The current study provides evidence that both food intake weight and eating rates per meal vary considerably in real-life per individual. However, based on these behaviours, most students can be correctly classified in regard to their peers based on single school lunches. In contrast, self-reported food intake weight and eating rate are poor predictors of real-life measures. Finally, based on the recorded individual variability of real-life food intake weight and eating rate, it is not advised to rank individuals based on single recordings collected in real-life settings.
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spelling pubmed-64711692019-04-25 Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents Langlet, Billy Fagerberg, Petter Delopoulos, Anastasios Papapanagiotou, Vasileios Diou, Christos Maramis, Christos Maglaveras, Nikolaos Anvret, Anna Ioakimidis, Ioannis Nutrients Article Large portion sizes and a high eating rate are associated with high energy intake and obesity. Most individuals maintain their food intake weight (g) and eating rate (g/min) rank in relation to their peers, despite food and environmental manipulations. Single meal measures may enable identification of “large portion eaters” and “fast eaters,” finding individuals at risk of developing obesity. The aim of this study was to predict real-life food intake weight and eating rate based on one school lunch. Twenty-four high-school students with a mean (±SD) age of 16.8 yr (±0.7) and body mass index of 21.9 (±4.1) were recruited, using no exclusion criteria. Food intake weight and eating rate was first self-rated (“Less,” “Average” or “More than peers”), then objectively recorded during one school lunch (absolute weight of consumed food in grams). Afterwards, subjects recorded as many main meals (breakfasts, lunches and dinners) as possible in real-life for a period of at least two weeks, using a Bluetooth connected weight scale and a smartphone application. On average participants recorded 18.9 (7.3) meals during the study. Real-life food intake weight was 327.4 g (±110.6), which was significantly lower (p = 0.027) than the single school lunch, at 367.4 g (±167.2). When the intra-class correlation of food weight intake between the objectively recorded real-life and school lunch meals was compared, the correlation was excellent (R = 0.91). Real-life eating rate was 33.5 g/min (±14.8), which was significantly higher (p = 0.010) than the single school lunch, at 27.7 g/min (±13.3). The intra-class correlation of the recorded eating rate between real-life and school lunch meals was very large (R = 0.74). The participants’ recorded food intake weights and eating rates were divided into terciles and compared between school lunches and real-life, with moderate or higher agreement (κ = 0.75 and κ = 0.54, respectively). In contrast, almost no agreement was observed between self-rated and real-life recorded rankings of food intake weight and eating rate (κ = 0.09 and κ = 0.08, respectively). The current study provides evidence that both food intake weight and eating rates per meal vary considerably in real-life per individual. However, based on these behaviours, most students can be correctly classified in regard to their peers based on single school lunches. In contrast, self-reported food intake weight and eating rate are poor predictors of real-life measures. Finally, based on the recorded individual variability of real-life food intake weight and eating rate, it is not advised to rank individuals based on single recordings collected in real-life settings. MDPI 2019-03-20 /pmc/articles/PMC6471169/ /pubmed/30897833 http://dx.doi.org/10.3390/nu11030672 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 Article
Langlet, Billy
Fagerberg, Petter
Delopoulos, Anastasios
Papapanagiotou, Vasileios
Diou, Christos
Maramis, Christos
Maglaveras, Nikolaos
Anvret, Anna
Ioakimidis, Ioannis
Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
title Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
title_full Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
title_fullStr Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
title_full_unstemmed Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
title_short Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
title_sort predicting real-life eating behaviours using single school lunches in adolescents
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471169/
https://www.ncbi.nlm.nih.gov/pubmed/30897833
http://dx.doi.org/10.3390/nu11030672
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