Identifying sources of reporting error using measured food intake.

OBJECTIVE: To investigate the magnitude and relative contribution of different sources of measurement errors present in the estimation of food intake via the 24-h recall technique.
DESIGN: We applied variance decomposition methods to the difference between data obtained from the USDA's Automated Multiple Pass Method (AMPM) 24-h recall technique and measured food intake (MFI) from a 16-week cafeteria-style feeding study. The average and the variance of biases, defined as the difference between AMPM and MFI, were analyzed by macronutrient content, subject and nine categories of foods.
SUBJECTS: Twelve healthy, lean men (age, 39+/-9 year; weight, 79.9+/-8.3 kg; and BMI, 24.1+/-1.4 kg/m2).
RESULTS: Mean food intakes for AMPM and MFI were not significantly different (no overall bias), but within-subject differences for energy (EI), protein, fat and carbohydrate intakes were 14, 18, 23 and 15% of daily intake, respectively. Mass (incorrect portion size) and deletion (subject did not report foods eaten) errors were each responsible for about one-third of the total error. Vegetables constituted 8% of EI but represented >25% of the error across macronutrients, whereas grains that contributed 32% of EI contributed only 12% of the error across macronutrients.
CONCLUSIONS: Although the major sources of reporting error were mass and deletion errors, individual subjects differed widely in the magnitude and types of errors they made.