Although every food frequency questionnaire (FFQ) requires a nutrient database to produce nutrient intake estimates, it is often unclear how a particular database has been generated. Moreover, alternative methods for constructing a database have not been rigorously evaluated. Using 24-hour recalls from the 1994-1996 Continuing Survey of Food Intake by Individuals, the authors categorized 5,261 individual foods reported by 10,019 adults into 170 food groups consistent with line items on an FFQ. These food groups were used to generate 10 potential nutrient databases for a FFQ that varied by whether the authors 1) used means or medians, 2) did or did not consider age, 3) incorporated collapsing strategies for small age-gender-portion size cells, 4) excluded outliers in a regression, and 5) used weighted median nutrient density x age-gender-portion size-specific median gram weights (Block method). Mean error, mean squared error, and mean absolute error were calculated and compared across methods, with error being the difference in total observed (from recalls for each individual) and total estimated intake (from each of the 10 methods) for seven nutrients. Mean methods for assigning nutrients to food groups were superior to median approaches for all measurements. Among the mean methods, no single variation was consistently better.