Searching for individual multi-sensory fingerprints and their links with adiposity-New insights from meta-analyses and empirical data

Understanding how human senses are linked to eating behaviour and adiposity has been a key topic in sensory science, and a source of substantial controversy. Despite strong correlations in sensitivity across different sensory modalities, the fundamental question of whether individuals possess a 'generalised sensitivity' across senses remains unanswered. A better understanding of the relationships between multiple senses and eating behaviour is needed to tackle the current obesity epidemic. The present study synthesises published data regarding sensory sensitivities across modalities and presents new empirical findings. Specifically, we synthesise findings from 115 publications, including meta-analyses of 26 studies. These data reveal strong yet complex links between senses, highlighting the potential of multi-sensory analyses to better characterise sensory variations. In the empirical study, 98 Caucasian males (25.9 +/- 5.8 years of age; body mass index: 26.8 +/- 5.1 kg.m(-2)) are tested for their supra-threshold sensory sensitivities (d') to 11 food-related mono-modal stimuli across olfaction, gustation, vision, and audition. Canonical correlations on d' for each modality reveal significant positive correlations between olfaction and gustation (p < 0.001), vision and audition (p < 0.001), as well as olfaction and audition (p = 0.008). Additionally, K-means cluster analysis identifies three broad groups of individuals with distinct multi sensory fingerprints. Intriguingly, individuals in separate clusters are shown to have significantly different adiposity measures (body mass index: p = 0.01; body fat percentages: p = 0.05). Overall, this study sheds important new light on multi-sensory 'fingerprints', and their links to obesity.

Automated summary

This study synthesizes data from 115 publications and reveals strong yet complex links between senses. The study also identifies distinct multi-sensory fingerprints and finds significant differences in adiposity measures among individuals with different fingerprints.