Abstract
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<0.001; in order from largest to smallest: omission, intrusion, underreported match, and overreported match), meal (P=0.01; larger for breakfast), retention interval (P=0.003; larger for long), sex (P=0.004; larger for boys), race/ethnicity (P=0.045; largest for non-Hispanic whites), and amount category×meal interaction (P=0.046). Overreported amounts were larger for intrusions than overreported matches (P<0.0001). Underreported amounts were larger for omissions than underreported matches (P<0.0001). Overall underreported amounts (from omissions and underreported matches) exceeded overall overreported amounts (from intrusions and overreported matches) (P<0.003). 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.