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Titre : | Fourth-Grade Childrens Reporting Accuracy for Amounts Eaten at School-Provided Meals : Insight from a Reporting-Error-Sensitive Analytic Approach Applied to Validation Study Data (2017) |
Auteurs : | Suzanne Baxter ; David Hitchcock ; J. Royer ; et al. |
Type de document : | Article |
Dans : | Journal of the academy of nutrition and dietetics (vol 116, n° 12, 2016) |
Langues: | Anglais |
Descripteurs : |
HE Vinci Ecole ; Enfant (6-12 ans) ; Enquête alimentaire ; Etudes de validation ; Repas |
Résumé : |
Background
Validation studies that have directly assessed reporting accuracy for amounts eaten have provided results in various ways. Objective To analyze amount categories of a reporting-error-sensitive approach for insight concerning reporting accuracy for amounts eaten. Design For a cross-sectional validation study, children were observed eating school-provided breakfast and lunch, and randomized to one of eight 24-hour recall conditions (two retention intervals [short and long] crossed with four prompts [forward, meal name, open, and reverse]). Participants/setting Data collected during 3 school years (2011-2012 to 2013-2014) on 455 children from 10 schools (four districts) in a southern US state. Main outcome measures Items were classified as matches (observed and reported), omissions (observed but unreported), or intrusions (unobserved but reported). Within amount categories (matches [corresponding, overreported, and underreported], intrusions [overreported], and omissions [underreported]), item amounts were converted to kilocalories. Statistical analyses performed A multilevel model was fit with food-level explanatory variables (amount category and meal) and child-level explanatory variables (retention interval, prompt, sex, and race/ethnicity). To investigate inaccuracy differences, t tests on three contrasts were performed. Results Inaccuracy differed by amount category (P Conclusions Amount categories provide a standard way to analyze validation study data on reporting accuracy for amounts eaten, and compare results across studies. Multilevel analytic models reflecting the data structure are recommended for inference. To enhance reporting accuracy for amounts eaten, focus on increasing reports of correct items, thereby yielding more matches with fewer intrusions and omissions. |
Disponible en ligne : | Non |
Exemplaires (1)
Cote | Support | Localisation | Section | Disponibilité |
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REV | Périodique papier | Woluwe | Espace revues | Consultation sur place uniquement Exclu du prêt |