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Cited by 191Body Composition Measurement TechniquesObesity, Physical Activity, DietDiabetes, Cardiovascular Risks, and Lipoproteins

Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999–2006

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Lee, Dong Hoon, Keum, NaNa, Hu, Frank B., Orav, E. John, Rimm, Eric B., Sun, Qi, Willett, Walter C., Giovannucci, Edward L.·2017·British Journal of Nutrition
DOI 10.1017/s0007114517002665
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Abstract

Quantification of lean body mass and fat mass can provide important insight into epidemiological research. However, there is no consensus on generalisable anthropometric prediction equations to validly estimate body composition. We aimed to develop and validate practical anthropometric prediction equations for lean body mass, fat mass and percent fat in adults (men, n 7531; women, n 6534) from the National Health and Nutrition Examination Survey 1999–2006. Using a prediction sample, we predicted each of dual-energy X-ray absorptiometry (DXA)-measured lean body mass, fat mass and percent fat based on different combinations of anthropometric measures. The proposed equations were validated using a validation sample and obesity-related biomarkers. The practical equation including age, race, height, weight and waist circumference had high predictive ability for lean body mass (men: R2=0·91, standard error of estimate (SEE)=2·6 kg; women: R2=0·85, SEE=2·4 kg) and fat mass (men: R2=0·90, SEE=2·6 kg; women: R2=0·93, SEE=2·4 kg). Waist circumference was a strong predictor in men only. Addition of other circumference and skinfold measures slightly improved the prediction model. For percent fat, R2 were generally lower but the trend in variation explained was similar. Our validation tests showed robust and consistent results with no evidence of substantial bias. Additional validation using biomarkers demonstrated comparable abilities to predict obesity-related biomarkers between direct DXA measurements and predicted scores. Moreover, predicted fat mass and percent fat had significantly stronger associations with obesity-related biomarkers than BMI did. Our findings suggest the potential application of the proposed equations in various epidemiological settings.

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  • Cisgender women demonstrate 31% lower lean body mass, 36% lower hand-grip strength, and 35% lower knee extension strength than cisgender men.

    “cisgender women demonstrating 31% lower LBM,59 36%60 lower hand-grip strength and 35%61 lower knee extension strength than cisgender men”

    From How does hormone transition in transgender women change body composition, muscle strength and haemoglobin? Systematic review with a focus on the implications for sport participation (2021) · cites this paper as [59]

    The Results report that men had, on average, 18 kg more lean body mass than women, supporting the direction of the comparison. Our copy does not give the cited 31% figure or establish that participants were cisgender. The hand-grip and knee-extension figures have separate citations and are not attributed to this paper. (LLM, conf=0.82)

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  • Males have reduced fat mass and different distribution of body fat and lean muscle mass compared with females, which increases power to weight ratios and upper to lower limb strength.

    “reduced fat mass, and different distribution of body fat and lean muscle mass, which increases power to weight ratios and upper to lower limb strength in sports where this may be a crucial determinant of success”

    From Transgender Women in the Female Category of Sport: Perspectives on Testosterone Suppression and Performance Advantage (2021) · cites this paper as [28]

    The Results (page unavailable) report that men had lower fat mass and higher lean body mass than women; the Discussion (page unavailable) describes a possible sex difference in where fat accumulates. The paper does not establish differences in limb-specific muscle distribution or show that these body-composition differences increase power-to-weight ratios, upper-to-lower limb strength, or sporting success. (LLM, conf=0.88)

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  • Males have longer and larger skeletal structure than females, creating advantages in sports where levers influence force application, longer limb/digit length is favorable, and height, mass and proportions are directly responsible for performance capacity.

    “longer and larger skeletal structure, which creates advantages in sports where levers influence force application, where longer limb/digit length is favorable, and where height, mass and proportions are directly responsible for performance capacity”

    From Transgender Women in the Female Category of Sport: Perspectives on Testosterone Suppression and Performance Advantage (2021) · cites this paper as [28]

    Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.

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  • Males have larger and denser muscle mass, and stiffer connective tissue, with associated capacity to exert greater muscular force more rapidly and efficiently than females.

    “Males have: larger and denser muscle mass, and stiffer connective tissue, with associated capacity to exert greater muscular force more rapidly and efficiently”

    From Transgender Women in the Female Category of Sport: Perspectives on Testosterone Suppression and Performance Advantage (2021) · cites this paper as [28]

    The Results (page not available in our copy) report that men had, on average, 18 kg more lean body mass than women. Lean body mass is not a direct measure of muscle size or density, and the paper does not establish the claimed differences in connective-tissue stiffness or the speed and efficiency of force production. (LLM, conf=0.87)

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  • Transwomen likely retain a strength advantage over cisgender women after 12-36 months of GAHT.

    “the small decrease in strength in transwomen after 12–36 months of GAHT suggests that transwomen likely retain a strength advantage over cisgender women.”

    From How does hormone transition in transgender women change body composition, muscle strength and haemoglobin? Systematic review with a focus on the implications for sport participation (2021) · cites this paper as [59]

    The Results section compares lean body mass in men and women in NHANES, while the prediction and validation section addresses equations for estimating body composition. Neither addresses strength in transwomen after GAHT or a comparison with cisgender women; searches for the 12–36-month claim and gender-affirming hormone therapy found no relevant passage. (LLM, conf=0.76)

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Research works printed but not linked: 1

  1. Al-Gindan YY, Hankey CR, Leslie W, et al. (2014) Predicting muscle mass from anthropometry using magnetic resonance imaging as reference: a systematic review. Nutr Rev 72, 113-126.

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Authors
Lee, D. H., Keum, N., Hu, F. B., Orav, E. J., Rimm, E. B., Sun, Q., Willett, W. C., & Giovannucci, E. L.
Affiliations
  • Harvard University (US)
  • Brigham and Women's Hospital (US)
Corresponding author
Giovannucci, Edward L.
ORCID
Venue
British Journal of Nutrition
Publisher
Cambridge University Press (CUP)
Published
2017-11-07
Volume
118
Issue
10
Pages
858-866
ISSN
  • 0007-1145 (ISSN-L)
  • 1475-2662
DOI
10.1017/s0007114517002665
OpenAlex
W2767288521
Cited by
191
References
30
Citations by year
2026: 15 · 2025: 30 · 2024: 23 · 2023: 37 · 2022: 28 · 2021: 17 · 2020: 20 · 2019: 16 · 2018: 4
FWCI
8.09
Type
journal article
Language
en
Open access
Licence
www.cambridge.org/core/terms (unspecified)
Locations
  • British Journal Of Nutrition (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Keywords
anthropometric equations, lean body mass, fat mass, body fat percentage, body composition, dual-energy X-ray absorptiometry, waist circumference, skinfold thickness, NHANES, adults, sex differences
MeSH terms
Adipose Tissue, Adult, Aged, Anthropometry, Body Composition, Body Fluid Compartments, Body Weight, Female, Humans, Male, Middle Aged, Models, Biological, Nutrition Surveys, Obesity, Sex Factors, Skinfold Thickness, Absorptiometry, Photon, Body Mass Index, Body Size, Adiposity, Waist Circumference, Young Adult

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