Race, Ethnicity, Sex, and Obesity: Is It Time to Personalize the Scale?
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Standard BMI categories can lead to misclassification bias when considering age, ethnicity, race, sex, or metabolic disease risks for certain disorders.
“Standard BMI categories can lead to misclassification bias when considering age, ethnicity, race, sex, or metabolic disease risks for certain disorders [51].”
From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [51]
In “To the Editor” (page not supplied), the authors argue that a single BMI threshold can underdiagnose or overdiagnose obesity across race/ethnicity and sex groups, and propose cutoffs linked to metabolic risk factors. The passages do not address age-based misclassification, so that part of the claim is unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measuredEliminating individuals from the analysis on the basis of factors such as smoking history or occult disease can plausibly create biases.
“However, eliminating individuals from the analysis on the basis of such factors can plausibly create biases.45,46”
From Definition and diagnostic criteria of clinical obesity (2025) · cites this paper as [46]
The paper’s “To the Editor” section discusses recalibrating BMI thresholds by race, ethnicity, and sex, but does not address excluding people from an analysis because of smoking history or occult disease. Searches for those factors and for exclusion or selection bias found no relevant passage in our copy. (LLM, conf=0.76)
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References 7 · Cited by 61
Research works printed but not linked: 6
- [1]Pandey A, Patel KV, Lavie CJ. Obesity, central adiposity, and fitness: understanding the obesity paradox in the context of other cardiometabolic parameters. Mayo Clin Proc. 2018; 93(6): 676– 678. 29866278
- [2]WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403): 157– 163. Erratum in Lancet. 2004; 363(9412):902. 14726171
- [3]He X, Liu C, Chen Y, He J, Dong Y. Overweight without central obesity, cardiovascular risk, and all-cause mortality. Mayo Clin Proc. 2018; 93(6): 709– 720. 29656788
- [4]Carbone S, Lavie CJ, Arena R. Obesity and heart failure: focus on the obesity paradox. Mayo Clin Proc. 2017; 92(2): 266– 279. 28109619
- [5]Komaroff M. For researchers on obesity: historical review of extra body weight definitions. J Obes. 2016; 2016: 2460285. 27313875 PMC4904092
- [7]Kahan SI. Practical strategies for engaging individuals with obesity in primary care. Mayo Clin Proc. 2018; 93(3): 351– 359. 29502565
- Authors
- Stanford, F. C., Lee, M., & Hur, C.
- Affiliations
- Harvard University (US)
- Massachusetts General Hospital (US)
- Venue
- Mayo Clinic Proceedings
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 94
- Issue
- 2
- Pages
- 362-363
- ISSN
- 0025-6196 (ISSN-L)
- PMC
- PMC6818706
- OpenAlex
- W2913751187
- Cited by
- 61
- References
- 7
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 14 · 2023: 17 · 2022: 9 · 2021: 3 · 2020: 1
- FWCI
- 2.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Mayo Clinic Proceedings (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
- Keywords
- obesity, body mass index, racial and ethnic disparities, sex differences, Asian Americans, metabolic disorders, BMI cutoffs
- MeSH terms
- Adult, Cardiovascular Diseases, Ethnicity, Female, Humans, Male, Morbidity, Obesity, Sex Factors, United States, Body Mass Index, Survival Rate, Racial Groups
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