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PREDICTING HULA DANCING ACTIVITY ENERGY EXPENDITURE WITH ACCELEROMETRY-BASED ACTIVITY MONITORS

Abstract

C.Z. Heil1, D.E. Lankford, FACSM2, J.D. Reece3, D.P. Heil, FACSM1

1Montana State University, Bozeman, MT; 2Brigham Young University - Idaho, Rexburg, ID; 3Brigham Young University - Hawaii, Laie, HI

Many forms of dance, such as the Hawaiian Hula, have been used with high risk populations to improve measures of health and physical fitness, but quantifying the dose (IntensityxTime) of dance-related exercise is needed to better understand dose-response relationships. Wearable accelerometry-based activity monitors (AMs, counts/min), for instance, can be used to indirectly quantify the metabolic intensity (i.e., the activity energy expenditure, or AEE, in kcals/kg/min) of specific types of dance, but this technique has never been validated directly against indirect calorimetry for dancing. PURPOSE: This study evaluated whether generalized (for 24/7 free-living AEE assessment) or newly derived Hula-specific dance AM algorithms could accurately predict AEE for Hula dancing. METHODS: 15 women (Mean±SD: 24±2 yrs, 25.4±3.4 kg/m2) and 6 men (27±2 yrs, 25.5±3.8 kg/m2), all professional Polynesian dancers, performed 5 mins of modern or traditional Hula dancing while AEE was assessed using indirect calorimetry. AM data was simultaneously collected at the hip (AMH), wrist (AMW), and ankle (AMA) using standard procedures. Steady-state measures of AEE, AMH, AMW, and AMA were then combined with select demographic measures (gender, age, BMI) to generate least-squares best-fit regression equations predicting dance-specific AEE (overall α=0.05). Measured AEE was then compared to predicted AEE from each new equation, as well as predicted AEE from published generalized equations (non-dance specific) using 1-factor RM ANOVA (α=0.05). RESULTS: Simple linear equations using the hip (AEE= 0.0551 + 6.10E-05xAWH; R2=0.76, SEE=±0.0221 kcals/kg/min; P<0.001) and ankle AMs (AEE= 0.0418 + 1.77E-05xACA; R2=0.64, SEE=±0.0271 kcals/kg/min; P<0.001), but not the wrist, were derived without use of demographic variables. Measured AEE (0.0840±0.0441) did not differ significantly (P>0.05) from predicted AEE with either ACH (0.0840±0.0384) or ACA dance equations (0.0839±0.0352), while both generalized equations for the hip and ankle AMs significantly underpredicted AEE (P<0.05). CONCLUSION: These results suggest that these Hula-specific dance AEE prediction equations from either hip or ankle AMs will provide more accurate prediction of AEE, as well as the dose of Hula dancing exercise, over use of generalized equations.

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