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Published on: August 17, 2022
Wrestlers' minimal weight: anthropometry, bioimpedance, and hydrostatic weighing compared
R A Oppliger1, D H Nielsen, C G Vance
1Physical Therapy Education, University of Iowa, Iowa City 52242.
Medicine and Science in Sports and Exercise
|February 1, 1991
Summary
Accurate minimal weight (MW) assessment for wrestlers is crucial. Bioelectrical impedance (BIA) and anthropometric methods like skinfolds (SF) show validity, with SF and Berkeley Medical Research (BMR) BIA being most accurate for interscholastic wrestlers.
Area of Science:
- Sports Medicine
- Human Physiology
- Anthropometry
Background:
- Accurate minimal weight (MW) assessment is vital for interscholastic wrestlers' health and performance.
- While anthropometric methods are validated, research on bioelectrical impedance (BIA) accuracy and comparisons between BIA systems is limited.
Purpose of the Study:
- To compare the validity of anthropometric methods and BIA systems for predicting MW in interscholastic wrestlers.
- To evaluate differences between various BIA devices (Berkeley Medical Research (BMR), RJL, Valhalla (VAL)) and anthropometric techniques.
Main Methods:
- Compared three anthropometric methods (skinfolds (SF), two skeletal dimensions equations) and three BIA systems (BMR, RJL, VAL) against hydrostatic weighting (HW) in 57 wrestlers.
- Analyzed correlations, standard errors of estimate (SEE), total errors of prediction (E), and mean differences between methods.
Main Results:
- All methods showed high correlations with HW (r > 0.92).
- SF and BMR BIA demonstrated nonsignificant differences with HW and smaller prediction errors (E = 1.8 and 2.3 kg) compared to RJL and VAL (E = 4.4 and 3.9 kg).
- BMR BIA showed significant differences from RJL and VAL systems.
Conclusions:
- Skinfolds (SF) and Berkeley Medical Research (BMR) BIA are the most valid methods for determining minimal weight in interscholastic wrestlers.
- RJL and VAL BIA systems may have potential but require further refinement, possibly by incorporating anthropometric data.
- Future research should focus on enhancing prediction equation utility for diverse athletic populations.

