Food-Cal: development of a controlled database of high and low calorie food matched with non-food pictures
Industrialization has led to more varied and attractive high-calorie foods. Health problems such as obesity and diabetes are partially attributed to eating-related self-regulation difficulties that may be caused by increasingly frequent cues for highly palatable foods. Research studies aim at understanding the factors underlying responses to food cues. This has led to the development of food stimuli databases. However, they present some limitations.
This study aimed at providing a controlled set of pictures, including 40 food pictures with high- and low-calorie stimuli, matched with 40 non-food pictures. The second objective was to provide a ready-to-use database with normative data regarding responses and associations between demographic, anthropometric and eating-related characteristics, and picture ratings.
A sample of 264 participants rated the total set of pictures.
Attractiveness, arousal and palatability were assessed for each picture, as well as participant’s current type of diet, BMI, hunger levels and eating behaviors (uncontrolled and emotional eating).
Image characteristics (shape, colors, luminance) were comparable between food and matched non-food pictures. Positive correlations were found between hunger levels and attractiveness, arousal and palatability of food. Uncontrolled and emotional eating was positively correlated with high-calorie food palatability, and uncontrolled eating was positively correlated with high-calorie food attractiveness. Participants who did not report any specific diet rated high-calorie foods as more attractive and arousing, whereas vegan and vegetarian participants assessed low-calorie foods as more attractive and palatable.
The Food-Cal controlled set of picture database can be considered as a useful tool for experimental research.
Level of evidence
Level V, cross-sectional descriptive study.
KeywordsPicture database High-calorie foods Low-calorie foods Controlled food pictures Eating behaviors
Compliance with ethical standards
Conflict of interest
The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.
All procedures performed in the study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments.
All participants signed an informed consent before completing the study.
- 2.Ares G, Varela P (2018) Methods in consumer research, volume 2: alternative approaches and special applications. Elsevier, CambridgeGoogle Scholar
- 6.Cappelleri JC, Bushmakin AG, Gerber RA, Leidy NK, Sexton CC, Lowe MR, Karlsson J (2009) Psychometric analysis of the Three-Factor Eating Questionnaire-R21: results from a large diverse sample of obese and non-obese participants. Int J Obes 33:611–620. https://doi.org/10.1038/ijo.2009.74 CrossRefGoogle Scholar
- 12.Foster MT, Warne JP, Ginsberg AB, Horneman HF, Pecoraro NC, Akana SF, Dallman MF (2009) Palatable foods, stress, and energy stores sculpt corticotropin-releasing factor, adrenocorticotropin, and corticosterone concentrations after restraint. Endocrinology 150(5):2325–2333. https://doi.org/10.1210/en.2008-1426 CrossRefGoogle Scholar
- 17.Goldstone AP, Prechtl de Hernandez CG, Beaver JD, Muhammed K, Croese C, Bell G, Durighel G, Hughes E, Waldman A, Frost G, Bell JD (2009) Fasting biases brain reward systems towards high-calorie foods. Eur J Neurosci 30(8):1625–1635. https://doi.org/10.1111/j.1460-9568.2009.06949.x CrossRefGoogle Scholar
- 20.Holsen LM, Lawson EA, Christensen K, Klibanski A, Goldstein JM (2014) Abnormal relationships between the neural response to high- and low-calorie foods and endogenous acylated ghrelin in women with active and weight-recovered anorexia nervosa. Psychiatry Res Neuroimaging 223:94–103. https://doi.org/10.1016/j.pscychresns.2014.04.015 CrossRefGoogle Scholar
- 30.Miccoli L, Delgado R, Guerra P, Versace F, Rodríguez-Ruiz S, Fernández-Santaella MC (2016) Affective pictures and the open library of affective foods (OLAF): tools to investigate emotions toward food in adults. PLoS ONE 11(8):e0158991. https://doi.org/10.1371/journal.pone.0158991 CrossRefGoogle Scholar
- 34.Payson S (1994). Using historical information to identify consumer concerns about food safety, vol 1835. Technological Bulletin, US Department of Agriculture, pp 1–19Google Scholar
- 37.Siep N, Roefs A, Roebroeck A, Havermans R, Bonte ML, Jansen A (2009) Hunger is the best spice: an fMRI study of the effects of attention, hunger, and calorie content on food reward processing in the amygdala and orbitofrontal context. Behav Brain Res 198:148–158. https://doi.org/10.1016/j.bbr.2008.10.035 CrossRefGoogle Scholar