Is Obesity Caused by Calorie Underestimation? A Psychophysical Model of Meal Size Estimation

Chandon, Pierre; Wansink, Brian

doi:10.1509/jmkr.44.1.84

Cited by 212 publications

(220 citation statements)

References 39 publications

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“…However, the perception of excessiveness could also result in increased consumption throughout the day if dietary disinhibition occurs (29) . It was interesting that the energy estimations were more often overestimations than underestimations, as this contradicts previous research (17) . The health halo effect describes the tendency to underestimate the energy content of food claimed to be healthy, such as Subway (30) .…”

Section: Discussioncontrasting

confidence: 61%

Perceptions of portion size and energy content: implications for strategies to affect behaviour change

Brindal

Wilson

Mohr

et al. 2011

Public Health Nutr.

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Objective: To assess Australian consumers' perception of portion size of fast-food items and their ability to estimate energy content. Design: Cross-sectional computer-based survey. Setting: Australia. Subjects: Fast-food consumers (168 male, 324 female) were asked to recall the items eaten at the most recent visit to a fast-food restaurant, rate the prospective satiety and estimate the energy content of seven fast-food or 'standard' meals relative to a 9000 kJ Guideline Daily Amount. Nine dietitians also completed the energy estimation task. Results: Ratings of prospective satiety generally aligned with the actual size of the meals and indicated that consumers perceived all meals to provide an adequate amount of food, although this differed by gender. The magnitude of the error in energy estimation by consumers was three to ten times that of the dietitians. In both males and females, the average error in energy estimation for the fast-food meals (females: mean 3911 (SD 1998) kJ; males: mean 3382 (SD 1957) kJ) was significantly (P , 0?001) larger than for the standard meals (females: mean 2607 (SD 1623) kJ; males: mean 2754 (SD 1652) kJ). In women, error in energy estimation for fast-food items predicted actual energy intake from fast-food items (b 5 0?16, P , 0?01). Conclusions: Knowledge of the energy content of standard and fast-food meals in fast-food consumers in Australia is poor. Awareness of dietary energy should be a focus of health promotion if nutrition information, in its current format, is going to alter behaviour.

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Section: Discussioncontrasting

confidence: 61%

Perceptions of portion size and energy content: implications for strategies to affect behaviour change

Brindal

Wilson

Mohr

et al. 2011

Public Health Nutr.

View full text Add to dashboard Cite

show abstract

“…BMI itself does not predict accuracy or bias in this data, similar to Blake et al [21] and Chandon and Wansink [25], but contrary to studies showing that overweight and obese individuals consistently under-report calorie intake to a greater degree than non-overweight individuals [14,42]. However, BMI does significantly interact with energy density in predicting percent error (η, P=.002, R 2 =.57), such that the higher a participant's BMI, the more they exaggerated the calorie content of calorierich foods.…”

Section: Does Bmi Predict Estimation Errors?supporting

confidence: 88%

Calorie Estimation From Pictures of Food: Crowdsourcing Study (Preprint)

Jun¹,

Bell²,

Nusrat³

et al. 2017

Preprint

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Background: Software to accurately estimate food calories from still images could help users and health professionals more efficiently identify dietary patterns and food choices associated with health and health risks. However, calorie estimation from images is difficult, and no publicly available software can do so accurately while minimizing the burden associated with data collection and analysis. Objective: The aim of this study is to determine the accuracy of crowdsourced annotations of calorie content in food images, and to identify and quantify sources of bias and noise as a function of respondent characteristics and food qualities (e.g., energy density). Methods: We invited adult social media users to provide calorie estimates for 20 food images (for which ground truth calorie data were known) using a custom-built webpage that administers an online quiz. The images were selected to provide a range of food types and energy density. Participants optionally provided age range, gender, and their height and weight. Additionally, five nutrition experts provided annotations for the same data to form a basis of comparison. We examined estimate accuracy on the basis of expertise, demographic data, and food qualities using linear mixed effects models with participant and image index as random variables. We also analyzed the advantage of aggregating nonexpert estimates. Results: 2028 respondents agreed to participate in the study (males: 770 [38%], mean body mass index: 27.5). Average accuracy was 5 out of 20 correct guesses, where "correct" was defined as a number within 20% of the ground truth. Even a small crowd of 10 individuals achieved an accuracy of 7, exceeding the average individual's and expert annotator's accuracy of 5. Women were more accurate than men (P<.001), and younger people were more accurate than older people (P<.001). The calorie content of energy-dense foods was overestimated (P=.024). Participants did not perform better when images contained reference objects (such as credit cards) for scale. Conclusions: Our findings provide new information about the way we process food information, which can inform the design of future calorie-estimation applications.

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“…Eating out is related to higher intakes of energy and fat (3)(4)(5)(6)(7)(8)(9) and to higher rates of overweight and obesity (10) . Evidence suggests that Americans consistently underestimate the energy content (number of calories) of restaurant foods (11)(12)(13)(14)(15)(16) . Menu labelling, such as posting energy (caloric) content of foods at the point of purchase in restaurants, has been proposed as one strategy to allow consumers to make informed food purchases.…”

mentioning

confidence: 99%

Adolescents’ awareness and use of menu labels in eating establishments: results from a focus group study

Evans¹,

Weiss²,

Meath³

et al. 2015

Public Health Nutr.

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Objective: Menu labelling has been identified as a potential strategy to help individuals make healthier choices when eating out. Although adolescents eat out often, little research involving menu labelling has been conducted with this population. The objectives of the present study were to: (i) gather qualitative information from adolescents regarding use of menu labels when eating out; (ii) gather adolescents' suggestions for optimal ways to design menu labels; and (iii) examine differences between adolescents living in communities of different socio-economic status. Design: Qualitative. Five focus groups of five to ten participants.

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Is Obesity Caused by Calorie Underestimation? A Psychophysical Model of Meal Size Estimation

Cited by 212 publications

References 39 publications

Perceptions of portion size and energy content: implications for strategies to affect behaviour change

Perceptions of portion size and energy content: implications for strategies to affect behaviour change

Calorie Estimation From Pictures of Food: Crowdsourcing Study (Preprint)

Adolescents’ awareness and use of menu labels in eating establishments: results from a focus group study

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