Associations of Skeletal Muscle Index, Body Mass Index, and Body Fat in a Primarily Hispanic Population

Authors

Kassandra Reyes, The University of Texas Rio Grande ValleyFollow
Emmanuel Franco, The University of Texas Rio Grande ValleyFollow
Maria Quezada, The University of Texas Rio Grande ValleyFollow
Yuliana Sanchez-Trinidad, The University of Texas Rio Grande ValleyFollow
Aylin Barrera, The University of Texas Rio Grande ValleyFollow
Allison de la Vina, The University of Texas Rio Grande ValleyFollow
Samuel R. Buchanan, The University of Texas Rio Grande ValleyFollow

Abstract

Despite criticism of body mass index (BMI) in the classification of weight status, it is still a commonly used metric. BMI may still serve a purpose in the identification of low muscle status. PURPOSE: This study associated skeletal muscle index (SMI), BMI, and body fat percentage (PBF) in a population of mostly Hispanic individuals. METHODS: 47 adults, aged 18+, were assessed for total body composition using a four-compartment model (4C) with bone mineral content from a Lunar iDXA (GE Healthcare, Madison WI), total body water via the InBody 770 (InBody, Seoul, South Korea), and ADP from a BodPod GS-X (COSMED, Rome, Italy). Participants were instructed to arrive hydrated, with manufacturer suggested clothing, for testing after a minimum 4-hour fast and abstain from exercise for the previous 12 hours. Hydration was assessed before testing using a urine refractometer with an acceptable range between 1.004-1.029. Participants repeated the testing protocol on a separate day within a two-week period for reliability measures. 4C PBF was calculated with the Fuller equation embedded in the BodPod software. Pearson correlations were used to assess the relationship between BMI, PBF, and the SMIs. The sample was also divided by sex and overweight status with the same correlational analyses. Overweight was defined as BMI>30 or PBF > 25% in men or > 32% in women. Statistical analyses were conducted using SPSS v28 (IBM Corporation, New York, USA) and alpha was set at 0.05. RESULTS: Total sample BMI was significantly correlated with SMI from DXA (r=0.719, p<0.001), SMI from InBody (r=0.734, p<0.001), and PBF (r=0.419, p<0.01). Women’s BMI (n=22) was significantly correlated with SMI from DXA (r=0.831, p<0.001), SMI from InBody (r=0.777, p<0.001), and PBF (r=0.89, p<0.001). For men (n=25) BMI was significantly correlated with SMI from DXA (r=0.671, p<0.001), SMI from InBody (r=0.774, p<0.001), and PBF (r=0.644, p<0.001). Overweight (n=17) BMI was significantly correlated with SMI from DXA (r=0.721, p<0.001), SMI from InBody (r=0.719, p<0.001), but not for PBF (r=0.429, p= 0.09). CONCLUSION: BMI has been criticized for classifying weight status. The lack of an association for BMI with PBF in our overweight sample seems to support the criticism. There is some potential for prescreening with BMI as an indicator for low muscle mass, though a follow-up assessment in an older population would be advised before utilizing BMI in this manner.

Recommended Citation

Reyes, Kassandra; Franco, Emmanuel; Quezada, Maria; Sanchez-Trinidad, Yuliana; Barrera, Aylin; de la Vina, Allison; and Buchanan, Samuel R. (2025) "Associations of Skeletal Muscle Index, Body Mass Index, and Body Fat in a Primarily Hispanic Population," International Journal of Exercise Science: Conference Proceedings: Vol. 2: Iss. 17, Article 109.
Available at: https://digitalcommons.wku.edu/ijesab/vol2/iss17/109