The objective of this paper was to develop a set of food groups for use in a self-administered, computer-assisted diet history interview for use in Australia by combining foods into groups so as to minimise database error in the macronutrient values for the food groups. The program needs to appropriately balance the level of detail used with the burden load on respondents and errors associated with categorisation of foods into groups. Various statistical techniques were utilised to aggregate a large number of food items into compositionally and conceptually similar groups. Exploratory statistical analysis, cluster analysis, stepwise regression analysis and association rule analysis were performed. A database containing 433 food groups was created which minimised the level of database error in the resulting data collection. Although some database error was introduced by aggregating food items into groups, the magnitude of the errors was reasonable considering other error sources. These findings are useful when applied to collection of food intake information for an individual's diet history and measurement of energy and macronutrient intake.