The degree to which consumers expect foods to satisfy hunger, referred to as expected satiation, has been reported to predict food intake. Yet this relationship has not been established precisely, at a quantitative level. We sought to explore this relationship in detail by determining whether expected satiation predicts the actual intake of semi-solid desserts. Two separate experiments were performed: the first used variations of a given food (eight apple purées), while the second involved a panel of different foods within a given category (eight desserts). Both experiments studied the consumption of two products assigned to volunteers based on their individual liking and expected satiation ratings, given ad libitum at the end of a standardised meal. A linear model was used to find predictors of food intake and included expected satiation scores, palatability scores, BMI, age, sex, TFEQ-R, TFEQ-D, water consumption during the meal, reported frequency of eating desserts, and reported frequency of consuming tested products as explanatory variables. Expected satiation was a significant predictor of actual food intake in both experiments (apple purée: F(1,97) = 18.60, P < .001; desserts: F(1,106) = 9.05, P < .01), along with other parameters such as product palatability and the volunteers’ age, sex and food restriction (variation explained by the model/expected satiation in the experiments: 57%/23% and 36%/17%, respectively). However, we found a significant gap between expected and actual consumption of desserts, on group and on individual level. Our results confirm the importance of expected satiation as a predictor of subsequent food intake, but highlight the need to study individual consumption behaviour and preferences in order to fully understand the role of expected satiation.
Appetite – Elsevier
Published: Apr 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera