Data-Driven Clustering Approach to Derive Taste Perception Profiles from Sweet, Salt, Sour, Bitter, and Umami Perception Scores: An Illustration among Older Adults with Metabolic Syndrome.

The Journal of Nutrition
Julie E GervisAlice H Lichtenstein

Abstract

Current approaches to studying relations between taste perception and diet quality typically consider each taste-sweet, salt, sour, bitter, umami-separately or aggregately, as total taste scores. Consistent with studying dietary patterns rather than single foods or total energy, an additional approach may be to study all 5 tastes collectively as "taste perception profiles." We developed a data-driven clustering approach to derive taste perception profiles from taste perception scores and examined whether profiles outperformed total taste scores for capturing individual variability in taste perception. The cohort included 367 community-dwelling adults [55-75 y; 55% female; BMI (kg/m2): 32.2 ± 3.6] with metabolic syndrome from PREDIMED-Plus, Valencia. Cluster analysis identified subgroups of individuals with similar patterns in taste perception (taste perception profiles); quantitative criteria were used to select the cluster algorithm, determine the optimal number of clusters, and assess the profiles' validity and stability. Goodness-of-fit parameters from adjusted linear regression evaluated the individual variability captured by each approach. A k-means algorithm with 6 clusters best fit the data and identified the following t...Continue Reading

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Citations

Jul 6, 2021·The Journal of Nutrition·Beverly J Tepper

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