Prediction of body fat by anthropometry in older Chinese people

Obesity Research
T KwokE Lau

Abstract

To derive regression equations for fat percentage by using simple anthropometric measurements applicable in normal and immobile (cannot stand or walk) older people. The study population comprised 352 females and 261 males, apparently well and community-dwelling, aged 69 to 82 years. Fifty-one females and 27 males were recruited for external validation. Body weight, standing height, arm span, triceps and biceps skinfold thicknesses (SFTs), and midarm circumference were measured. The reference method of total body fat percentage was dual-energy X-ray densitometry. Predictive equations for fat percentages were derived by stepwise multiple linear regression on anthropometric indices and gender. Upper-limb SFTs, body mass index, and gender yielded the more predictive equation. The SEE was 4.1% weight. There was a significant trend of underestimation in overweight subjects, especially in females. The equation using SFTs and midarm circumference was less reliable but more applicable to older immobile people and those with significant kyphoscoliosis. The combination of body mass index and upper-limb SFTs gives reliable prediction of fat percentages in older Chinese people, except in the obese.

References

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Citations

Feb 24, 2009·Applied Physiology, Nutrition, and Metabolism = Physiologie Appliquée, Nutrition Et Métabolisme·Simi KohliScott A Lear
Nov 19, 2010·The Journal of Nutrition, Health & Aging·R S GuerraM T Restivo
Apr 21, 2010·Clinica Chimica Acta; International Journal of Clinical Chemistry·T KwokP C Leung
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Mar 13, 2014·IEEE Journal of Biomedical and Health Informatics·Bum Ju LeeJong Yeol Kim
Feb 16, 2019·Public Health Nutrition·Lilia V Castro-PorrasMalaquías López-Cervantes
Feb 27, 2010·Physiotherapy Research International : the Journal for Researchers and Clinicians in Physical Therapy·Maryam M Al-Mandeel, Tim Watson
Sep 28, 2004·The American Journal of Clinical Nutrition·Arupendra Mozumdar, Subrata K Roy
Apr 22, 2020·Obesity Science & Practice·Zachary MerrillRakié Cham

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