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Cited by 167

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Adaptiveness of food learning and food aversions in children

Cashdan, Elizabeth·1998·Social Science Information

Abstract

This paper uses an evolutionary perspective to explain features of food learning in human children. Data from Western parents indicate that (1) children are least picky about foods when they are between one and two years of age, (2) vegetables are frequently refused by children, and (3) children have a tendency to eat foods one at a time rather than mixed together. Adaptive explanations for these patterns are suggested, together with supporting evidence from studies of the ontogeny of human and non-human primate diet choice. The following arguments are made: (1) age difference in receptiveness to new foods is consistent with the existence of a sensitive period for learning about food; (2) since leaves and other non-fruit plant parts often contain toxic secondary compounds and young animals are less able to detoxify these chemicals than are adults, an initial dislike of vegetables may function to protect young children against the risk of poisoning; (3) a preference for easily identifiable foods eaten separately may be an evolved preference that aids in identification of the food and the consequences of eating it.

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Metadata

Authors
Cashdan, E.
Venue
Social Science Information
Published
1998-12
Volume
37
Issue
4
Pages
613-632
ISSN
  • 0539-0184 (ISSN-L)
  • 1461-7412
OpenAlex
W2071920408
Cited by
167
References
1
FWCI
0.25
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Adaptiveness of food learning and food aversions in children. https://app.cochat.ai/papers/10.1177/053901898037004003
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Cashdan, E. (1998). Adaptiveness of food learning and food aversions in children. Social Science Information. https://doi.org/10.1177/053901898037004003

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.