COMPARISON OF MEASURED RESTING METABOLIC RATE WITH PREDICTIVE EQUATIONS IN DIVISION III ATHLETES

Knowledge of resting metabolic rate is important for athletes, but it is cumbersome to measure resting metabolic rates. Prediction equations for resting metabolic rate have been developed but may not be accurate for all athletes. PURPOSE: To measure resting metabolic rate in Division III athletes and compare the results to thirteen previously developed prediction equations. METHODS: Twenty-two Division III athletes (four males, eighteen females, mean age 20.1 ± 0.3, wt 68.4 ± 9.9 kg, ht 168.5 ± 8.8 cm, 21.0 ± 9.1 %BF) from various sports were asked to report to the laboratory after abstaining from strenuous exercise for at least 24 hr and caffeine and food for at least 12 hr. Subjects were allowed to rest for 15 minutes, then resting metabolic rate measurement commenced using a Parvo Medics TrueOne 2400 metabolic cart with canopy system in a quiet, dimly lit, thermoneutral room. Thirty minutes of data was collected with the first ten minutes and last five minutes discarded. Body composition was measured using a BodPod. A Dunnett’s test (SPSS software) was used for statistical analysis (each prediction equation result being compared to actual measured resting metabolic rate). RESULTS: Measured resting metabolic rate (6183 ± 920 kJ/24 hr; 1478 ± 220 kcal/24 hr) did not significantly differ from Watson (6083 ± 635; 1454 ± 152; p > 0.325), Nelson (6117 ± 954; 1462 ± 228; p > 0.219), Ten Haff (6518 ± 611; 1558 ± 146; p > 0.138) and Maffies (5983 ± 494; 1430 ± 118; p > 0.187) prediction equations. Measured resting metabolic rate was significantly different from Harris Benedict (6995 ± 695; 1672 ± 166; p < 0.005), Owen (6791 ± 833; 1623 ± 199; p < 0.005), Mifflin St Jeor (7259 ± 828; 1735 ± 198; p < 0.005), WHO (6702 ± 996; 1602 ± 238; p < 0.005), Altman Dittmer (7912 ± 707; 1891 ± 169; p < 0.005), Tinsley (7063 ± 1351; 1688 ± 323; p < 0.005) and Johnstone (4540 ± 996; 1085 ± 238; p < 0.005) prediction equations. CONCLUSION: In a variety of Division III athletes, the prediction equations of Watson, Nelson, Ten Haaf, and Maffies were not significantly different from measured resting metabolic rate. Note, however, that the Watson, and Nelson equations require measurement of fat and fat-free mass. We thus conclude the Ten Haaf and Maffies equations are the most useful in predicting resting metabolic rate easily in Division III athletes.

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Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001052616.90636.55
Primary Topic
Adipose Tissue and Metabolism
Type
article
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article

COMPARISON OF MEASURED RESTING METABOLIC RATE WITH PREDICTIVE EQUATIONS IN DIVISION III ATHLETES

Gabrielle Moore, E. M. Konrad, Matt Beekley
Medicine & Science in Sports & Exercise
Adipose Tissue and Metabolism
article

COMPARISON OF MEASURED RESTING METABOLIC RATE WITH PREDICTIVE EQUATIONS IN DIVISION III ATHLETES

Gabrielle Moore, E. M. Konrad, Matt Beekley
article en

Abstract

Knowledge of resting metabolic rate is important for athletes, but it is cumbersome to measure resting metabolic rates. Prediction equations for resting metabolic rate have been developed but may not be accurate for all athletes. PURPOSE: To measure resting metabolic rate in Division III athletes and compare the results to thirteen previously developed prediction equations. METHODS: Twenty-two Division III athletes (four males, eighteen females, mean age 20.1 ± 0.3, wt 68.4 ± 9.9 kg, ht 168.5 ± 8.8 cm, 21.0 ± 9.1 %BF) from various sports were asked to report to the laboratory after abstaining from strenuous exercise for at least 24 hr and caffeine and food for at least 12 hr. Subjects were allowed to rest for 15 minutes, then resting metabolic rate measurement commenced using a Parvo Medics TrueOne 2400 metabolic cart with canopy system in a quiet, dimly lit, thermoneutral room. Thirty minutes of data was collected with the first ten minutes and last five minutes discarded. Body composition was measured using a BodPod. A Dunnett’s test (SPSS software) was used for statistical analysis (each prediction equation result being compared to actual measured resting metabolic rate). RESULTS: Measured resting metabolic rate (6183 ± 920 kJ/24 hr; 1478 ± 220 kcal/24 hr) did not significantly differ from Watson (6083 ± 635; 1454 ± 152; p > 0.325), Nelson (6117 ± 954; 1462 ± 228; p > 0.219), Ten Haff (6518 ± 611; 1558 ± 146; p > 0.138) and Maffies (5983 ± 494; 1430 ± 118; p > 0.187) prediction equations. Measured resting metabolic rate was significantly different from Harris Benedict (6995 ± 695; 1672 ± 166; p < 0.005), Owen (6791 ± 833; 1623 ± 199; p < 0.005), Mifflin St Jeor (7259 ± 828; 1735 ± 198; p < 0.005), WHO (6702 ± 996; 1602 ± 238; p < 0.005), Altman Dittmer (7912 ± 707; 1891 ± 169; p < 0.005), Tinsley (7063 ± 1351; 1688 ± 323; p < 0.005) and Johnstone (4540 ± 996; 1085 ± 238; p < 0.005) prediction equations. CONCLUSION: In a variety of Division III athletes, the prediction equations of Watson, Nelson, Ten Haaf, and Maffies were not significantly different from measured resting metabolic rate. Note, however, that the Watson, and Nelson equations require measurement of fat and fat-free mass. We thus conclude the Ten Haaf and Maffies equations are the most useful in predicting resting metabolic rate easily in Division III athletes.

Medicine & Science in Sports & ExerciseVol. 56(10S)
DePauw University (US)
Openalex Percentile: Top 78%
Adipose Tissue and Metabolism
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