Background: Modern food items often contain high proportions of saturated fats and refined carbohydrates. Such dietary compositions contribute to the prevalence of obesity and metabolic disease. Food images are a valuable tool to study these diet effects on eating behavior and obesity development. Aims: Creating and validating a novel food picture set to facilitate studies on food choice and eating behavior for the Finnish population called “FinnFoodPics”. Material & Methods: We photographed 72 commonly consumed Finnish food items and classified them into one of three macronutrient categories: high in carbohydrates, high in fat, or high in carbohydrates and fat (combo). Sixty-two participants rated these items for liking, familiarity, frequency of consumption, expected satiety, perceived healthiness, energy content, and energy density. We used Bayesian ANOVAs to provide information on food characteristics, visual properties, and participant ratings across categories. Results: We found strong evidence of differences across macronutrient categories for all assessed parameters except for familiarity, which showed moderate uniformity across categories. Notably, foods in the carbohydrate category had higher fiber, and those in the fat category had higher protein content. Conclusion: “FinnFoodPics” provides a robust tool for local researchers to study food-related behavior and facilitates the replicability and comparability of studies using visual snack food stimuli in Finland.
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Kanyamibwa et al. (2024) studied this question.
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