Development of an equation to estimate fat-free mass in mountain Guides and Porters

• Jorge TORRES-MEJÍAS ^[1] ; Evangelina RIVAROLA ^[2] ; Erick DIAZ ^[4] ; Gabriela SALAZAR ^[4] ; Daniela TORO ^[5] ; Felipe VILLEGAS ^[5] ; Rossana GÓMEZ ^[1] ; Marcos COSSIO ^[1] ; Miguel ÁNGEL-LÓPEZ ^[3] ; Eugenio MERELLANO-NAVARRO ^[1]
  1. [1] Universidad Católica del Maule

     Universidad Católica del Maule

     Provincia de Talca, Chile

     
  2. [2] Universidad Nacional de Córdoba

     Universidad Nacional de Córdoba

     Argentina

     
  3. [3] Universidad Adventista de Chile

     Universidad Adventista de Chile

     Chillan, Chile

     
  4. [4] Laboratory of Energy Metabolism and Stable Isotopes, INTA. Chile
  5. [5] Andesgear, Chile.

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• Localización: Nutrición clínica y dietética hospitalaria, ISSN 0211-6057, Vol. 44, Nº. 3, 2024, págs. 174-180
• Idioma: inglés
• DOI: 10.12873/443cavalcante
• Enlaces
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• Resumen

  • Body composition (BC) is a crucial component in the monitoring of athletes, not only as a variable related to physical performance, but also as a follow-up of dietary interventionand training.

    Objective: To propose regression equations from bodyvsurface area (BSA) to estimate fat-free mass (FFM) of mountain guides and porters using deuterium oxide dilution (MDD) as a criterion method.

    Methods: Cross-sectional study in 23 young and adultmen working as mountain guides and porters on Aconcagua(Argentina). The volunteers ranged in age from 20 to 50years. Weight, height, body mass index (BMI) and BSA were assessed by eight regression equations.

    Results: Three linear regression equations were generated considering chronological age and ASC as predictors: Model 1 (FFM = - 25.287 - (0.260 * age) + (49.014 * ASC1),R2 = 63.0%), model 2 (FFM = -20.736 - (0.191 * age) +(45.523 * ASC2), R2 = 62.0%) and model 3 (FFM = -28.592- (0.244 * age) + (52.499 * ASC3), R2 = 63.0). The three equations presented tolerance indices (T) and variance inflation values (VIF) within limits; more evidence of absence of autocorrelation.

    Conclusion: Three predictive models based on age and BSA were generated that allow estimating the FFM in a validand reliable way. The results suggest their use and application for monitoring before, during and after expeditions.

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