Resting Metabolic Rate Prediction Equation Accuracy in Structural Firefighters

Area of Science:

• Exercise Physiology
• Occupational Health
• Nutritional Science

Background:

• Accurate estimation of resting metabolic rate (RMR) is crucial for determining energy requirements in occupational groups.
• Firefighters have unique physiological demands that may affect metabolic rate.
• The accuracy of existing RMR predictive equations in this population is not well-established.

Purpose of the Study:

• To evaluate the accuracy of six common RMR prediction equations in male firefighters.
• To compare the performance of Cunningham, De Lorenzo, Harris-Benedict, Mifflin-St Jeor, Nelson, and Jagim equations.

Main Methods:

• Twenty-six male firefighters underwent RMR measurement and body composition assessment.
• Six predictive RMR equations were applied to the study participants.
• Repeated measures ANOVA and linear regression analyses were used to compare measured RMR with predicted RMR values.

Main Results:

• All tested equations, except Jagim, significantly underestimated measured RMR in firefighters (p<0.001).
• The Harris-Benedict and De Lorenzo equations showed the closest agreement with measured RMR.
• The Nelson equation exhibited the highest prediction error (RMSE = 412 kcal, %RMSE = 18.6%).

Conclusions:

• Current RMR prediction equations may not accurately reflect the energy expenditure of firefighters.
• Underestimation of RMR by predictive equations could lead to inadequate caloric intake recommendations.
• Further research is needed to develop or validate RMR equations specific to firefighter populations.