Prediction Equation of Arm Lean Mass from Grip Strength in Law Enforcement Officers
Major
Kinesiology and Allied Health
Submission Type
Poster
Area of Study or Work
Exercise Science
Faculty Advisor
Daniel Dodd
Faculty Advisor
Marc Tiritilli
Location
CNS Atrium
Start Date
4-11-2026 8:30 AM
End Date
4-11-2026 9:45 AM
Abstract
In law enforcement officers (LEOs), adequate grip strength is critical for tasks involving suspect control, lifting, and carrying equipment and reflects upper-body muscular capacity. Grip strength may provide a practical alternative for estimating upper-body lean mass when technologies such as dual-energy X-ray absorptiometry (DEXA) are not accessible. PURPOSE: To develop prediction equations between maximal isometric hand grip strength (HGS) and arm lean mass in male police officers. METHODS: Thirty-one male LEOs (age: 36.6 ± 9.1 years, body mass: 96.8 ± 15.2 kg, and height 1.8 ± 0.1 m) participated in the study. Maximal HGS was measured using a calibrated hand dynamometer. Lean mass of each arm was determined using DEXA. Pearson’s product correlations assessed relationships between HGS and arm lean mass. Linear regression analyses predicted lean mass from HGS, with goodness of fit evaluated using the coefficient of determination (r²). Significance was set at p ≤ 0.05. RESULTS: Left maximal HGS was strongly, positively correlated with left arm lean mass (r = .740, p < .001), explaining 55% of the variance (r² = .55, SEE: .59 kg). The regression equation was: Left Arm Lean Mass = 973.2 + 67.5 × Best Left HGS (kg). Right maximal HGS showed a moderate positive correlation with right arm lean mass (r = .49, p = .005), accounting for 24.0% of the variance (r² = .24, SEE: .7 kg). The regression equation was: Right Arm Lean Mass = 2370 + 45 × Best Right HGS (kg). CONCLUSION: Maximal HGS was positively associated with arm lean mass in LEOs, with greater predictive accuracy observed for the left arm. Side-to-side differences suggesting that dominance or neuromuscular factors may affect the relationship between grip force and lean mass. These findings support grip strength as a simple field-based method for estimating upper-extremity lean mass when DEXA is unavailable.
Prediction Equation of Arm Lean Mass from Grip Strength in Law Enforcement Officers
CNS Atrium
In law enforcement officers (LEOs), adequate grip strength is critical for tasks involving suspect control, lifting, and carrying equipment and reflects upper-body muscular capacity. Grip strength may provide a practical alternative for estimating upper-body lean mass when technologies such as dual-energy X-ray absorptiometry (DEXA) are not accessible. PURPOSE: To develop prediction equations between maximal isometric hand grip strength (HGS) and arm lean mass in male police officers. METHODS: Thirty-one male LEOs (age: 36.6 ± 9.1 years, body mass: 96.8 ± 15.2 kg, and height 1.8 ± 0.1 m) participated in the study. Maximal HGS was measured using a calibrated hand dynamometer. Lean mass of each arm was determined using DEXA. Pearson’s product correlations assessed relationships between HGS and arm lean mass. Linear regression analyses predicted lean mass from HGS, with goodness of fit evaluated using the coefficient of determination (r²). Significance was set at p ≤ 0.05. RESULTS: Left maximal HGS was strongly, positively correlated with left arm lean mass (r = .740, p < .001), explaining 55% of the variance (r² = .55, SEE: .59 kg). The regression equation was: Left Arm Lean Mass = 973.2 + 67.5 × Best Left HGS (kg). Right maximal HGS showed a moderate positive correlation with right arm lean mass (r = .49, p = .005), accounting for 24.0% of the variance (r² = .24, SEE: .7 kg). The regression equation was: Right Arm Lean Mass = 2370 + 45 × Best Right HGS (kg). CONCLUSION: Maximal HGS was positively associated with arm lean mass in LEOs, with greater predictive accuracy observed for the left arm. Side-to-side differences suggesting that dominance or neuromuscular factors may affect the relationship between grip force and lean mass. These findings support grip strength as a simple field-based method for estimating upper-extremity lean mass when DEXA is unavailable.