Version 1
: Received: 3 December 2021 / Approved: 6 December 2021 / Online: 6 December 2021 (15:59:17 CET)
How to cite:
Cheung, M.; Kramer, M.; Beauchamp, G.; Wise, P. Characterizing Individual Differences in Sweet Taste Hedonics: Test Methods, Locations, and Stimuli. Preprints2021, 2021120091. https://doi.org/10.20944/preprints202112.0091.v1
Cheung, M.; Kramer, M.; Beauchamp, G.; Wise, P. Characterizing Individual Differences in Sweet Taste Hedonics: Test Methods, Locations, and Stimuli. Preprints 2021, 2021120091. https://doi.org/10.20944/preprints202112.0091.v1
Cheung, M.; Kramer, M.; Beauchamp, G.; Wise, P. Characterizing Individual Differences in Sweet Taste Hedonics: Test Methods, Locations, and Stimuli. Preprints2021, 2021120091. https://doi.org/10.20944/preprints202112.0091.v1
APA Style
Cheung, M., Kramer, M., Beauchamp, G., & Wise, P. (2021). Characterizing Individual Differences in Sweet Taste Hedonics: Test Methods, Locations, and Stimuli. Preprints. https://doi.org/10.20944/preprints202112.0091.v1
Chicago/Turabian Style
Cheung, M., Gary Beauchamp and Paul Wise. 2021 "Characterizing Individual Differences in Sweet Taste Hedonics: Test Methods, Locations, and Stimuli" Preprints. https://doi.org/10.20944/preprints202112.0091.v1
Abstract
Sweetness drives consumption of added sugars, so understanding how individuals differ is important for developing strategies to lower sugar intake. However, methods to assess hedonic response to sweetness vary, making results across studies difficult to integrate. We compared methods to measure optimal sucrose concentration in 21 healthy adults (1) using paired-comparison preference tracking vs. ratings of liking, (2) with participants in the laboratory vs. at home, and (3) using aqueous solutions vs. vanilla milk. Tests were replicated on separate days to assess test-retest reliability. Test-retest reliability was similar between laboratory and home testing, but tended to be better for vanilla milk and preference tracking. Optimal sucrose concentration was virtually identical between laboratory and home, slightly lower when estimated via preference tracking, and about 50% lower in vanilla milk. However, individual optimal sucrose concentration correlated strongly between Methods, test Locations, and Stimuli. More than 50% of the variability in optimal sucrose concentration could be attributed to consistent differences among individuals while much less variability was attributable to differences in Methods, test Locations or Stimuli. These results demonstrate convergent validity between measures of preference and liking, support testing at home to lower participant burden, and suggest that aqueous solutions can be useful proxies for some commonly consumed beverages for measuring individual differences.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
