Grace L Rose1, Morgan J Farley1, Gary J Slater2, Leigh C Ward3, Tina L Skinner1, Shelley E Keating1, Mia A Schaumberg1,2,4. 1. School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Australia. 2. School of Health and Behavioral Sciences, University of the Sunshine Coast, Sippy Downs, Australia. 3. School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia. 4. Sunshine Coast Health Institute, Birtinya, Australia.
Abstract
BACKGROUND: Reliability of body composition measurement techniques is essential to the accurate reporting of intervention outcomes. However, the between-day precision error of commonly used techniques, as well as the reference multi-compartment model, in a population-representative sample are currently unknown. OBJECTIVES: To quantify technical and biological precision error of body composition techniques in comparison to the referent 4-compartment (4C) model. METHODS: Men and women (1:1 ratio; 18-85 years old; n = 90) completed 2 consecutive-day body composition testing sessions, including individual components of the referent 4C model. Testing was undertaken in accordance with best practice guidance for each technique, including standardized presentation and a consistent time of day. Repeat measurements were conducted on day 1 for technical precision, and between-day measurements were conducted for biological precision quantification. RESULTS: On average, all measurements met acceptable error limits and presented typically low technical and biological error [<2% fat-free mass (FFM) and < 3% fat mass (FM) precision error]. For technical precision of FFM, all techniques met a priori cut points (80%; CV = 0.45-0.81%). For FM, all techniques were equivalent to the best-rating method on average (CV = 0.78-1.35%), except air displacement plethysmography (CV = 2.13%). For biological precision, only 3-compartment (3C) and 4C equations sufficiently met the a priori determined cut point for estimates for FFM (CV = 0.77-0.79%), and only DXA met the 80% cut point (CV = 1.17%) for FM. CONCLUSIONS: The primary purpose of a study design is imperative when deciding on body composition assessment techniques used for longitudinal measurements. If reliable longitudinal assessments of FFM are central, a 3C or 4C model may be indicated. If FM is a primary outcome, DXA may be preferable. However, considering the low error rates presented within the current study across a broad age span of healthy adults with implementation of best-practice guidelines, any technique assessed here may be used, provided that strict protocols are adhered to.
BACKGROUND: Reliability of body composition measurement techniques is essential to the accurate reporting of intervention outcomes. However, the between-day precision error of commonly used techniques, as well as the reference multi-compartment model, in a population-representative sample are currently unknown. OBJECTIVES: To quantify technical and biological precision error of body composition techniques in comparison to the referent 4-compartment (4C) model. METHODS:Men and women (1:1 ratio; 18-85 years old; n = 90) completed 2 consecutive-day body composition testing sessions, including individual components of the referent 4C model. Testing was undertaken in accordance with best practice guidance for each technique, including standardized presentation and a consistent time of day. Repeat measurements were conducted on day 1 for technical precision, and between-day measurements were conducted for biological precision quantification. RESULTS: On average, all measurements met acceptable error limits and presented typically low technical and biological error [<2% fat-free mass (FFM) and < 3% fat mass (FM) precision error]. For technical precision of FFM, all techniques met a priori cut points (80%; CV = 0.45-0.81%). For FM, all techniques were equivalent to the best-rating method on average (CV = 0.78-1.35%), except air displacement plethysmography (CV = 2.13%). For biological precision, only 3-compartment (3C) and 4C equations sufficiently met the a priori determined cut point for estimates for FFM (CV = 0.77-0.79%), and only DXA met the 80% cut point (CV = 1.17%) for FM. CONCLUSIONS: The primary purpose of a study design is imperative when deciding on body composition assessment techniques used for longitudinal measurements. If reliable longitudinal assessments of FFM are central, a 3C or 4C model may be indicated. If FM is a primary outcome, DXA may be preferable. However, considering the low error rates presented within the current study across a broad age span of healthy adults with implementation of best-practice guidelines, any technique assessed here may be used, provided that strict protocols are adhered to.
Authors: Grace L Rose; Morgan J Farley; Nicole B Flemming; Tina L Skinner; Mia A Schaumberg Journal: Front Physiol Date: 2022-08-22 Impact factor: 4.755
Authors: Belinda M Thompson; Heidi L Hillebrandt; Dean V Sculley; Laura Barba-Moreno; Xanne A K Janse de Jonge Journal: Eur J Appl Physiol Date: 2021-07-22 Impact factor: 3.078