Author(s): BENITO PEINADO, P., ARMERO-SOTILLO, A., BENÍTEZ-MUÑOZ, J.A., RAMOS-CAMPO, D.J., GUISADO-CUADRADO, I., MARTÍNEZ-GUARDADO, I., ROJO-TIRADO, M.A., TORRES-SANTIAGO, M., RODRÍGUEZ-REDONDO, B., CUPEIRO, R., CASTRO, E.A., PEINADO, A.B., Institution: UNIVERSIDAD POLITÉCNICA DE MADRID, Country: SPAIN, Abstract-ID: 1357

INTRODUCTION:
Body mass index (BMI) is one of the most widely used methods for assessing a person's physical condition. This is mainly due to its simplicity, as it only requires the subject's weight and height. Whilevery practical, it also has its limitations, such as not knowing which components (predominantly fat and muscle mass), make up that weight. Therefore, when assessing body composition or health status based on a person's weight, it is advisable to use complementary techniques such as anthropometry, Dual-Energy X-ray Absorptiometry (DXA) or bioelectrical impedance analysis, among others (1). Furthermore, the literature has already described a direct, but not proportional, relationship between BMI and body fat percentage (2). This has allowed for the creation of weight status classifications associated not only with BMI but also with body fat percentage (3). Therefore, this study aimed to examine the relationship between body weight and muscle mass across different classification criteria, including body mass index and body fat percentage.
METHODS:
A total of 1,126 participants [433 women (45.9±16 years, 71.5±14 kg, and 162±7 cm) and 693 men (43.6±14 years, 83.0±15 kg, and 175±7 cm)] underwent DXA; (GE Lunar Prodigy) to assess body composition. The device was calibrated every two days using the manufacturer-provided phantom. The total sample was classified according to the World Health Organization BMI criteria (4), adiposity was classified using DXA-derived percent body fat (%BF) according to the cut-points proposed by Potter et al. (3).
RESULTS:
A strong correlation was observed between body weight and BMI (women: r=0.903, p<0.001; men: r=0.903, p<0.001). The correlation was moderate with fat-free mass (FFM) (women: r=0.554, p<0.001; men: r=0.541, p<0.001) and appendicular muscle mass (AMM) (women: r=0.597, p<0.001; men: r=0.505, p<0.001). The ANCOVA showed that a higher BMI classification was associated with increases in FFM (F(4)=37.4, p=0.01, η_p^2=0.972) and AMM (F(4)=42.6, p=0.01, η_p^2=0.975), adjusted for age and height; however, when body weight was included as a covariate, the association disappeared for both FFM (F(4)=1.9, p=0.184, η_p^2=0.434) and AMM (F(4)=0.414, p=0.794, η_p^2=0.220). Similar results were obtained when using FFM and AMM in relation to body fat percentage classification.
CONCLUSION:
In summary, individuals with a higher BMI tended to have greater FFM and AMM, primarily because they weighed more. When body weight was considered, BMI no longer showed a clear relationship with lean mass. Therefore, BMI should not be used as an indicator of muscle mass, and results based on BMI categories should be interpreted in conjunction with body weight and, ideally, with direct measurements of body composition (e.g., DXA).