Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents.
Cohen’s kappa
confidence interval
eating behaviour
meal duration
novel technology
nutrition
overweight
recording frequency
reliability
sensory science
Journal
Nutrients
ISSN: 2072-6643
Titre abrégé: Nutrients
Pays: Switzerland
ID NLM: 101521595
Informations de publication
Date de publication:
20 Mar 2019
20 Mar 2019
Historique:
received:
30
01
2019
revised:
13
03
2019
accepted:
13
03
2019
entrez:
23
3
2019
pubmed:
23
3
2019
medline:
6
8
2019
Statut:
epublish
Résumé
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 (
Identifiants
pubmed: 30897833
pii: nu11030672
doi: 10.3390/nu11030672
pmc: PMC6471169
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : FP7 Information and Communication Technologies
ID : 610746
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