Article

How do looking patterns, anti-fat bias, and causal weight attributions relate to adults’ judgements of child weight?

Details

Citation

Evans EH, Tovée MJ, Hancock PJ & Cornelissen PL (2023) How do looking patterns, anti-fat bias, and causal weight attributions relate to adults’ judgements of child weight?. Body Image, 44, pp. 9-23. https://doi.org/10.1016/j.bodyim.2022.11.001

Abstract
Prevailing weight-normative approaches to health pressure adults to visually categorise children’s weight, despite little understanding of how such judgements are made. There is no evidence this strategy improves child health, and it may harm children with higher weights. To understand decision-making processes and identify potential mechanisms of harm we examined perceptual and attitudinal factors involved in adults’ child weight category judgements. Eye movements of 42 adults were tracked while categorizing the weight of 40 computer-generated images of children (aged 4–5 & 10–11 years) varying in size. Questionnaires assessed child-focused weight bias and causal attributions for child weight. Participants’ eye movement patterns resembled those previously reported for adult bodies. Categorisation data showed a perceptual bias towards the ‘mid-range’ category. For higher weight stimuli, participants whose category judgements most closely matched the stimulus’s objective weight had higher child-focused anti-fat bias and weaker genetic attributions for child weight – i.e,. adults who ‘label’ higher weight in children in line with BMI categories report more stigmatising beliefs about such children, suggesting a possible mechanism of harm. Overall, adults’ judgements reflect both unalterable perceptual biases and potentially harmful attitudinal factors, calling into question the feasibility and appropriateness of public health efforts to promote visual child weight categorisation.

Keywords
Child weight; Weight stigma; Eye-tracking; Perception

Journal
Body Image: Volume 44

StatusPublished
Publication date31/03/2023
Publication date online19/11/2022
Date accepted by journal01/11/2022
URLhttp://hdl.handle.net/1893/34790
PublisherElsevier BV
ISSN1740-1445
eISSN1873-6807

People (1)

People

Professor Peter Hancock

Professor Peter Hancock

Professor, Psychology