Beyond BMI for self-estimates of body size and shape: A new method for developing stimuli correctly calibrated for body composition
Open accessAbstract
Accurate self-assessment of body shape and size plays a key role in the prevention, diagnosis, and treatment of both obesity and eating disorders. These chronic conditions cause significant health problems, reduced quality of life, and represent a major problem for health services. Variation in body shape depends on two aspects of composition: adiposity and muscularity. However, most self-assessment tools are unidimensional. They depict variation in adiposity only, typically quantified by the body mass index. This can lead to substantial, and clinically meaningful, errors in estimates of body shape and size. To solve this problem, we detail a method of creating biometrically valid body stimuli. We obtained high-resolution 3D body shape scans and composition measures from 397 volunteers (aged 18-45 years) and produced a statistical mapping between the two. This allowed us to create 3D computer-generated models of bodies, correctly calibrated for body composition (i.e., muscularity and adiposity). We show how these stimuli, whose shape changes are based on change in composition in two dimensions, can be used to match the body size and shape participants believe themselves to have, to the stimulus they see. We also show how multivariate multiple regression can be used to model shape change predicted by these 2D outcomes, so that participants' choices can be explained by their measured body composition together with other psychometric variables. Together, this approach should substantially improve the accuracy and precision with which self-assessments of body size and shape can be made in obese individuals and those suffering from eating disorders.
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The techniques of Maalin et al. (2021) allow creation of 3D computer-generated models of bodies that substantially improve the accuracy and precision with which assessments of body size and shape can be made.
“This allows the creation of 3D computer-generated models of bodies that substantially improve the accuracy and precision with which assessments of body size and shape can be made.”
From The degree to which the cultural ideal is internalized predicts judgments of male and female physical attractiveness (2022) · cites this paper as Maalin et al. (2021)
The Abstract (page unavailable) says the method creates 3D computer-generated bodies and that the approach *should* substantially improve the accuracy and precision of self-assessments in obese individuals and people with eating disorders. The citing sentence presents that anticipated improvement as established and omits those population limits. The Methods comparison (page unavailable) shows better 3D-shape prediction than a BMI model, not a measured improvement in assessment accuracy or precision. (LLM, conf=0.87)
Experimental — accuracy not yet measuredIn any reasonably large sample of men or women, muscle mass and body fat show a positive correlation across the sample, but within narrow BMI bands the relationship between muscle and adipose mass inverts and becomes negatively correlated.
“In any reasonably large sample of men or women, this relationship shows a positive correlation across the sample. However, if the data are subdivided into narrow ranges of BMI, then the direction of the relationship between muscle and adipose mass, within each narrow BMI band, inverts and becomes negatively correlated.”
From The degree to which the cultural ideal is internalized predicts judgments of male and female physical attractiveness (2022) · cites this paper as Maalin et al., 2021
The sets of stimuli were created using techniques that produce bodies biometrically calibrated for body composition.
“The sets of stimuli were created using the techniques outlined by Maalin et al. (2021), which produces bodies biometrically calibrated for body composition.”
From The degree to which the cultural ideal is internalized predicts judgments of male and female physical attractiveness (2022) · cites this paper as Maalin et al. (2021)
The overall sample size of scanned bodies used by Maalin et al. (2021) would ideally be larger and cover a wider range of body composition.
“First, the overall sample size of scanned bodies used by Maalin et al. (2021) would ideally be larger and cover a wider range of body composition.”
From The degree to which the cultural ideal is internalized predicts judgments of male and female physical attractiveness (2022) · cites this paper as Maalin et al., 2021
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References 53 · Cited by 25
Research works printed but not linked: 1
- Wright, S. P. (1998). Multivariate Analysis Using the MIXED Procedure. Retrieved from https://support.sas.com/resources/papers/proceedings/proceedings/sugi23/Stats/p229.pdf
- Authors
- Maalin, N., Mohamed, S., Kramer, R. S. S., Cornelissen, P. L., Martin, D., & Tovée, M. J.
- Affiliations
- University of Lincoln (GB)
- Northumbria University (GB)
- Corresponding author
- Tovée, Martin J.
- ORCID
- Venue
- Behavior Research Methods
- Published
- 2020-10-13
- Volume
- 53
- Issue
- 3
- Pages
- 1308-1321
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- PMC
- PMC8219570
- OpenAlex
- W3090430922
- Cited by
- 25
- References
- 53
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 7 · 2023: 3 · 2022: 4 · 2021: 3 · 2020: 1
- FWCI
- 1.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Behavior Research Methods (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lincoln Repository (University of Lincoln) (acceptedVersion)
- Northumbria Research Link (Northumbria University) (acceptedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Northumbria University
- Topics
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Keywords
- body image, body size perception, body shape perception, body composition, adiposity, muscularity, body mass index, 3D body scans, stimulus calibration, self-assessment, obesity, eating disorders, multivariate multiple regression
- MeSH terms
- Body Composition, Health Services, Humans, Quality of Life, Body Mass Index, Body Size
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