Effects of food variability on expected satiety

Meals are often planned in advance and eaten in their entirety. Computer-based assessments of expected satiety (ES) are excellent predictors of portion size. However, making judgements about ES depends on prior experience. Increasingly, foods are available in different varieties that differ considerably in energy density. Consequently, people are likely to have eaten several different versions and experienced different post-ingestive outcomes for the same food. In addition, processed foods tend to be more ambiguous/amorphous and contain more components than unprocessed foods. The impact of this ‘food variability’ on judgements of ES is unknown. Here, we tested the hypothesis that variability increases uncertainty about ES and that this leads to the use of a cognitive shortcut – judgements of ES tend to be based on perceived volume. ES was assessed for 12 meals (shown in equicaloric portions). Six of these meals were “high variable” (processed ready meals), and six were “low variable” (unprocessed foods). We paired meals to match energy density across our high- and low-variable food groups. Additional measures of appetite, expected satiation, expected liking, familiarity and perceived volume were also taken. We predicted that for high-variable meals, ratings of ES will differ more across different energy densities than for the low variable meals (indicating that participants are relying on perceived volume). This research was part supported by the BBSRC (ref:BB/I012370/1) and part supported by the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement 607310 (Nudge-it).