We examined differences in nutrient data across food composition databases (FCDBs) using three non-consecutive 24-hour dietary recalls. All foods consumed were recorded and weighed, and nutrient values were obtained from the Greek, Belgian, and FoodCentral US databases via FoodExplorer. The main objective was to highlight challenges when using the “wrong” database for a given population. Variations in composition can arise from differences in plant or animal varieties, environmental conditions, food processing, cooking methods, and industrial formulations. Analytical approaches and database structures also contribute to inconsistencies, as some databases present mean values, ranges, or calculated estimates (Greenfield & Southgate, 2003).

An Excel database was developed to document foods, portion sizes, and nutrient values, which were adjusted to reflect intakes. Some foods were missing in the selected databases, although every item appeared in at least one source. For example, the Belgian database lacked values for omelet, baked chicken, and grapes, while the Greek database was missing orange juice, milk chocolate, eggs, Gouda cheese, Bolognese sauce, and grapes.  In all the databases, composite dishes were generally analyzed according to their main ingredients (e.g., pasta with minced meat), except for certain traditional Greek meals, such as peas with potatoes, which were recorded as single complete dishes only in the Greek database, simplifying the analysis. In contrast, the US data provided more complete coverage of ingredients.

Nutrient intake were calculated proportionally and compared against dietary reference values using a Canadian analytical tool based on the Canadian food composition dataset. Results showed that macronutrients — carbohydrates, protein, and fat — were relatively consistent across databases, with only minor differences (e.g., protein in eggs and poultry varied by a few grams). In contrast, micronutrients such as vitamins A and C, calcium, and iron displayed much greater discrepancies, reflecting differences in data sources, analytical methods, food origin, and coding conventions. These findings confirm observations that micronutrient values are especially sensitive to methodological and environmental variation.

In conclusion, while macronutrient data are generally comparable across countries, micronutrient values vary considerably. Recognising and accounting for these differences is essential for accurate dietary assessment and for interpreting nutrient intakes in cross-national research. Careful database selection, supported by harmonisation tools, is crucial to ensure reliable and meaningful nutritional analysis, otherwise results risk undermine research and policies they are meant to support. When used carefully — with attention to context and source — they become a powerful resource for understanding diets, improving public health, and making more informed choices.