Mario Siervo1, Carla M Prado2, Emily Mire3, Stephanie Broyles3, Jonathan C K Wells4, Steven Heymsfield3, Peter T Katzmarzyk3. 1. 1Human Nutrition Research Centre,Institute of Cellular Medicine,Newcastle University,Campus of Ageing and Vitality,Newcastle upon Tyne NE4 5PL,UK. 2. 2Department of Agricultural,Food and Nutritional Science,Division of Human Nutrition,University of Alberta,Edmonton,Alberta,Canada. 3. 3Pennington Biomedical Research Center,Baton Rouge,LA,USA. 4. 4Childhood Nutrition Research Centre,UCL Institute of Child Health,London,UK.
Abstract
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.
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.
Authors: Sarah A Purcell; Camila L P Oliveira; Michelle Mackenzie; Paula Robson; John D Lewis; Carla M Prado Journal: Adv Nutr Date: 2022-08-01 Impact factor: 11.567
Authors: Isabella P Carneiro; Sarah A Elliott; Mario Siervo; Raj Padwal; Simona Bertoli; Alberto Battezzati; Carla M Prado Journal: Adv Nutr Date: 2016-05-16 Impact factor: 8.701
Authors: Eleonora Poggiogalle; Carla Lubrano; Lucio Gnessi; Stefania Mariani; Andrea Lenzi; Lorenzo Maria Donini Journal: PLoS One Date: 2016-01-07 Impact factor: 3.240