Background: In nutritional epidemiology, it is often of interest to disentangle the risk of disease associated with related foods or nutrients, where the food items are in a nested arrangement within a larger group. To compare odds ratios (OR) derived from a standard quantile-based analysis can be misleading since the amounts consumed may differ substantially for different dietary components.
Methods: The authors applied different logistic regression models on a case-control study concerning the risk of colorectal adenomas due to meat and its different subsets such as white meat, red meat and well-done red meat.
Results: By calculating OR for a fixed amount of intake, the authors suggest a method for partitioning the risk of one dietary item into that associated with increasingly detailed sub-components. A graph is presented for illustrating such partitions in terms of both addition and substitution effects.
Conclusions: Odds ratios based on upper versus lower quantiles or percentiles are useful as they compare the risk between the upper and lower ends of the consumption range. A complimentary set of OR are those based on fixed amounts of consumption. These allow for direct comparisons between nested subgroups of dietary components, in order to disentangle the risk linked to specific groups of foods or nutrients.