Identifying sources of reporting error using measured food intake

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.

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.

Twelve healthy, lean men (age, 39+/-9 year; weight, 79.9+/-8.3 kg; and BMI, 24.1+/-1.4 kg/m2).

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.

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.