التفاصيل البيبلوغرافية
| العنوان: |
Body composition indices of a load-capacity model: gender- and BMI-specific reference curves. |
| المؤلفون: |
Siervo, Mario (AUTHOR), Prado, Carla M (AUTHOR), Mire, Emily (AUTHOR), Broyles, Stephanie (AUTHOR), Wells, Jonathan Ck (AUTHOR), Heymsfield, Steven (AUTHOR), Katzmarzyk, Peter T (AUTHOR), Wells, Jonathan C K1 (AUTHOR) |
| المصدر: |
Public Health Nutrition. May2015, Vol. 18 Issue 7, p1245-1254. 10p. |
| مستخلص: |
Objective: Fat mass (FM) and fat-free mass (FFM) are frequently measured to define body composition phenotypes. The load-capacity model integrates the effects of both FM and FFM to improve disease-risk prediction. We aimed to derive age-, gender- and BMI-specific reference curves of load-capacity model indices in an adult population (≥18 years).Design: Cross-sectional study. Dual-energy X-ray absorptiometry was used to measure FM, FFM, appendicular skeletal muscle mass (ASM) and truncal fat mass (TrFM). Two metabolic load-capacity indices were calculated: ratio of FM (kg) to FFM (kg) and ratio of TrFM (kg) to ASM (kg). Age-standardised reference curves, stratified by gender and BMI (<25.0 kg/m2, 25.0-29.9 kg/m2, ≥30.0 kg/m2), were constructed using an LMS approach. Percentiles of the reference curves were 5th, 15th, 25th, 50th, 75th, 85th and 95th.Setting: Secondary analysis of data from the 1999-2004 National Health and Nutrition Examination Survey (NHANES).Subjects: The population included 6580 females and 6656 males.Results: The unweighted proportions of obesity in males and females were 25.5 % and 34.7 %, respectively. The average values of both FM:FFM and TrFM:ASM were greater in female and obese subjects. Gender and BMI influenced the shape of the association of age with FM:FFM and TrFM:ASM, as a curvilinear relationship was observed in female and obese subjects. Menopause appeared to modify the steepness of the reference curves of both indices.Conclusions: This is a novel risk-stratification approach integrating the effects of high adiposity and low muscle mass which may be particularly useful to identify cases of sarcopenic obesity and improve disease-risk prediction. [ABSTRACT FROM AUTHOR] |
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