Development and Validation of a Simple Equation to Predict Fat-Free Mass in the Adult Population.
Bioimpedance
Body composition
Equations
Estimate
Fat-free mass
Journal
Iranian journal of public health
ISSN: 2251-6093
Titre abrégé: Iran J Public Health
Pays: Iran
ID NLM: 7505531
Informations de publication
Date de publication:
Feb 2023
Feb 2023
Historique:
received:
12
10
2021
accepted:
19
12
2021
medline:
24
4
2023
pubmed:
24
4
2023
entrez:
24
04
2023
Statut:
ppublish
Résumé
Estimating Fat-Free Mass (FFM) is an integral part of Body composition measurements, so obtaining an accurate estimation for evaluating FFM is critical for researchers and specialists. We aimed to develop and validate a simple equation for predicting FFM in the adult population. Participants were 1996 adults (1085 men and 911 women), and 18 to 69 years old from Ahvaz City, southern Iran. They were randomly divided into the derivation (n=1396) and the validation (n=600) groups with no significant differences from Jan 2018 to Feb 2020. FFM was measured by Bioelectrical Impedance Analyzer (BIA) (InBody 770©; Biospace, Seoul, South Korea). Based on the demographic variables retrieved from the Derivation group, 8 FFM predictive equations were developed using multiple regression; finally, the most accurate model (using the coefficient of determination (R2)) was chosen and then validated on the Validation group for more evaluation. The best equation derived from demographic characteristics was: "FFM= 0.28 × Weight (kg) + 0.57×Height (cm)+7.35×Sex (M=1, F=0)+0.03×Age (years)-70.61"; where sex = 1 for male and 0 for female. R=0.94, R2=0.89, standard error of the estimate=4.04 kg. Our developed and cross-validated anthropometric prediction equation for fat-free mass estimation using BIA attained a high coefficient of determination, a low standard error of the estimate, and the lowermost coefficient of variation. Predictive equations may be reliable and valuable alternative methods for the clinical evaluation of fat-free mass in the adult population.
Sections du résumé
Background
UNASSIGNED
Estimating Fat-Free Mass (FFM) is an integral part of Body composition measurements, so obtaining an accurate estimation for evaluating FFM is critical for researchers and specialists. We aimed to develop and validate a simple equation for predicting FFM in the adult population.
Methods
UNASSIGNED
Participants were 1996 adults (1085 men and 911 women), and 18 to 69 years old from Ahvaz City, southern Iran. They were randomly divided into the derivation (n=1396) and the validation (n=600) groups with no significant differences from Jan 2018 to Feb 2020. FFM was measured by Bioelectrical Impedance Analyzer (BIA) (InBody 770©; Biospace, Seoul, South Korea). Based on the demographic variables retrieved from the Derivation group, 8 FFM predictive equations were developed using multiple regression; finally, the most accurate model (using the coefficient of determination (R2)) was chosen and then validated on the Validation group for more evaluation.
Results
UNASSIGNED
The best equation derived from demographic characteristics was: "FFM= 0.28 × Weight (kg) + 0.57×Height (cm)+7.35×Sex (M=1, F=0)+0.03×Age (years)-70.61"; where sex = 1 for male and 0 for female. R=0.94, R2=0.89, standard error of the estimate=4.04 kg.
Conclusion
UNASSIGNED
Our developed and cross-validated anthropometric prediction equation for fat-free mass estimation using BIA attained a high coefficient of determination, a low standard error of the estimate, and the lowermost coefficient of variation. Predictive equations may be reliable and valuable alternative methods for the clinical evaluation of fat-free mass in the adult population.
Identifiants
pubmed: 37089154
doi: 10.18502/ijph.v52i2.11892
pii: IJPH-52-389
pmc: PMC10113572
doi:
Types de publication
Journal Article
Langues
eng
Pagination
389-398Informations de copyright
Copyright © 2023 Saboor et al. Published by Tehran University of Medical Sciences.
Déclaration de conflit d'intérêts
Conflict of interest The authors declare that there is no conflict of interests.
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