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.

Background: 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 addit...

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Publicado en:Journal of Nutrition Vol. 151; no. 9; pp. 2843 - 2852
Autores principales: Gervis, Julie E, Chui, Kenneth K H, Ma, Jiantao, Coltell, Oscar, Fernández-Carrión, Rebeca, Sorlí, José V, Barragán, Rocío, Fitó, Montserrat, González, José I, Corella, Dolores, Lichtenstein, Alice H
Formato: clinical trial research tables/charts Journal Article
Publicado: Elsevier B.V. Sep2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2021
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      pub: Elsevier B.V.
      place: New York, New York
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        atl: 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.
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        au:
          Gervis, Julie E
          Chui, Kenneth K H
          Ma, Jiantao
          Coltell, Oscar
          Fernández-Carrión, Rebeca
          Sorlí, José V
          Barragán, Rocío
          Fitó, Montserrat
          González, José I
          Corella, Dolores
          Lichtenstein, Alice H
        affil: Cardiovascular Nutrition Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University , Boston, MA, USA
      sug:
        subj:
          Taste
          Female
          Cluster Analysis
          Aged
          Sodium Chloride
          Male
          Comparative Studies
          Multicenter Studies
          Evaluation Research
          Funding Source
          Clinical Trials
          Human
          Aged: 65+ years
          Female
          Male
      ab: Background: 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."Objective: 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.Methods: 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.Results: A k-means algorithm with 6 clusters best fit the data and identified the following taste perception profiles: Low All, High Bitter, High Umami, Low Bitter & Umami, High All But Bitter and High All But Umami. All profiles were valid and stable. Compared with total taste scores, taste perception profiles explained more variability in bitter and umami perception (adjusted R2: 0.19 vs. 0.63, respectively; 0.40 vs. 0.65, respectively) and were comparable for sweet, salt, and sour. In addition, taste perception profiles captured differential perceptions of each taste within individuals, whereas these patterns were lost with total taste scores.Conclusions: Among older adults with metabolic syndrome, taste perception profiles derived via data-driven clustering may provide a valuable approach to capture individual variability in perception of all 5 tastes and their collective influence on diet quality. This trial was registered at https://www.isrctn.com/ as ISRCTN89898870.
      pubtype: Academic Journal
      doctype:
        clinical trial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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