26 research outputs found
Editorial: Rising stars in nutrition, psychology and brain health: chemosensory signals, nutrition, and eating behavior
The association between sweet taste function, anthropometry, and dietary intake in adults
Variation in ability to detect, recognize, and perceive sweetness may influence food consumption, and eventually chronic nutrition-related conditions such as overweight and obesity. The aim of this study was to investigate the associations between sweet taste function, anthropometry, and dietary intake in adults. Participants\u27 (n = 60; mean age in years = 26, SD = ±7.8) sweet taste function for a range of sweeteners (glucose, fructose, sucrose, sucralose, erythritol, and Rebaudioside A) was assessed by measuring detection and recognition thresholds and sweetness intensity. Height, weight, and waist circumference were also measured, and participants also completed a Food Frequency Questionnaire. There was large inter-individual variation in detection, recognition and sweetness intensity measures. Pearson\u27s correlation coefficient revealed no robust correlations between measures of sweet taste function, anthropometry, and dietary intake, with the exception of suprathreshold intensity, which was moderately correlated with total energy intake (r = 0.23-0.40). One-way analysis of variance revealed no significant differences between the most and least sensitive participants in terms of BMI, waist circumference, and dietary intake for all measures of sweet taste function and sweeteners (all p > 0.01). When stratified into BMI categories, there were no significant differences in any measure of sweet taste function between the normal weight and overweight/obese participants (all p > 0.01). Results show that that sweet taste function is not associated with anthropometry and sweetness intensity measures are the most appropriate measure when assessing links between sweet taste and food consumption
Corrigendum: Psychophysical evaluation of sweetness functions across multiple sweeteners
Evidence supporting oral sensitivity to complex carbohydrates independent of sweet taste sensitivity in humans.
Compared to simple sugars, complex carbohydrates have been assumed invisible to taste. However, two recent studies proposed that there may be a perceivable taste quality elicited by complex carbohydrates independent of sweet taste. There is precedent with behavioural studies demonstrating that rats are very attracted to complex carbohydrates, and that complex carbohydrates are preferred to simple sugars at low concentrations. This suggests that rats may have independent taste sensors for simple sugars and complex carbohydrates. The aim of this paper is to investigate oral sensitivities of two different classes of complex carbohydrates (a soluble digestible and a soluble non-digestible complex carbohydrate), and to compare these to other caloric and non-nutritive sweeteners in addition to the prototypical tastes using two commonly used psychophysical measures. There were strong correlations between the detection thresholds and mean intensity ratings for complex carbohydrates (maltodextrin, oligofructose) (r = 0.94, P 0.05). However, moderate correlations were observed between perceived intensities of complex carbohydrates and sweeteners (r = 0.48-0.61, P < 0.05). These data provide evidence that complex carbohydrates can be sensed in the oral cavity over a range of concentrations independent of sweet taste sensitivity at low concentrations, but with partial overlap with sweet taste intensity at higher concentrations
The associations between sweet taste function, oral complex carbohydrate sensitivity, liking and consumption of ad libitum sweet and non-sweet carbohydrate milkshakes among female adults
Associations between sweet taste function, oral complex carbohydrate sensitivity, liking and consumption of ad libitum sweet and non-sweet carbohydrate milkshakes among female adults
Spearman rank correlations between detection thresholds (DTs) of complex carbohydrates and sweeteners.
<p>(1) Spearman rank correlations between detection thresholds of maltodextrin and oligofructose. (2a-d) Correlations between detection thresholds of maltodextrin and caloric sweeteners: (2a) glucose; (2b) fructose; (2c) sucrose; (2d) erythritol. (2e-h) Correlations between detection thresholds of oligofructose and caloric sweeteners: (2e) glucose; (2f) fructose; (2g) sucrose; (2h) erythritol. (3a, 3b) Correlations between detection thresholds of maltodextrin and non-nutritive sweeteners: (3a) sucralose; (3b) Rebaudioside A. (3c, 3d) Correlations between detection thresholds of oligofructose and non-nutritive sweeteners: (3c) sucralose; (3d) Rebaudioside A. *<i>P</i> < 0.05; **<i>P</i> < 0.001.</p
Psychophysical curves of the group mean and examples of a participant who experienced high intensity and a participant who experienced low intensity.
<p>(a) Maltodextrin (b) Oligofructose. Included in each graph is the mean psychophysical curve as well as an example of a participant who experienced high intensity (highest curve) and a participant who experienced low intensity (lowest curve) for that complex carbohydrate. The y-axis is a numerical measure of intensity perception from the gLMS. The x-axis is the actual concentration in % <i>w/v</i>.</p
Spearman rank correlations of suprathreshold intensity ratings (STs) between complex carbohydrates and sweeteners.
<p>Spearman rank correlations of intensity ratings between maltodextrin and oligofructose. (2a-d) Correlations between intensity ratings of maltodextrin and caloric sweeteners: (2a) glucose; (2b) fructose; (2c) sucrose; (2d) erythritol. (2e-h) Correlations between intensity ratings of oligofructose and caloric sweeteners: (2e) glucose; (2f) fructose; (2g) sucrose; (2h) erythritol. (3a, 3b) Correlations between intensity ratings of maltodextrin and non-nutritive sweeteners: (3a) sucralose; (3b) Rebaudioside A. (3c, 3d) Correlations between intensity ratings of oligofructose and non-nutritive sweeteners: (3c) sucralose; (3d) Rebaudioside A. **<i>P</i> < 0.001.</p