# Respiratory Muscle Strength as a Predictor of VO2 max and Aerobic Endurance in Competitive Athletes
## 3 Results
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Characteristics** & **X** & **SD** & **B** & **SE** & **B** & **T** & \(p\) & **Zero-Order** & **Partial** \\ \hline (Constant) & & & 2314.699 & 1392.589 & & 1.662 & 0.107 & & \\ MIP (cm\(/\)H\({}_{2}\)O) & 99.08 & 29.70 & \(-\)10.586 & 5.195 & \(-\)0.314 & \(-\)2.038 & **0.050** & 0.279 & \(-\)0.349 \\ MEP (cm\(/\)H\({}_{2}\)O) & 130.95 & 42.82 & 14.358 & 3.810 & 0.614 & 3.769 & **0.001** & 0.590 & 0.567 \\ MAC (cm) & 91.40 & 10.720 & \(-\)193.217 & 130.677 & \(-\)2.069 & \(-\)1.479 & 0.150 & 0.588 & \(-\)0.261 \\ ACI (cm) & 95.20 & 10.216 & 17.688 & 74.215 & 0.181 & 0.238 & 0.813 & 0.590 & 0.043 \\ ACE (cm) & 89.13 & 10.827 & 154.760 & 104.521 & 1.674 & 1.481 & 0.149 & 0.593 & 0.261 \\ MSC (cm) & 78.82 & 10.454 & 116.701 & 85.326 & 1.219 & 1.368 & 0.182 & 0.614 & 0.242 \\ SCI (cm) & 82.95 & 9.462 & \(-\)104.461 & 54.177 & \(-\)0.987 & \(-\)1.928 & **0.043** & 0.547 & \(-\)0.332 \\ SCE (cm) & 76.63 & 10.505 & 28.444 & 74.737 & 0.299 & 0.381 & 0.706 & 0.618 & 0.069 \\ MVV & 135.63 & 38.39 & 4.590 & 3.977 & 0.176 & 1.154 & 0.257 & 0.527 & 0.206 \\ \hline \hline \multicolumn{10}{l}{MIP: Maximum inspiratory pressure, MEP: Maximum expiratory pressure, MVV: Maximum voluntary ventilation, MAC: Mid-Avilla Circumference, ACI: Avilla Circumference On Inspiration, ACE: Avilla Circumference On Expiration, MSC: Mid-Subcostal Circumference, SCI: Subcostal Circumference On Inspiration, SCE: Subcostal Circumference On Expiration, X: Mean, SD: Standard Deviation, SE: Standard Error, B: Regression Coefficient, \(\beta\): Standardized Regression Coefficient, T: t-Statistic, \(p\): \(p\):Value, Zero-order: Bivariate Correlation Values, Partial: Partial Correlation Values.} \\ \end{tabular}
\end{table} 
Table 5: Regression analysis results regarding VCO\({}_{2}\) (Mean \(\pm\) S.D. = 4301.27 \(\pm\) 0.1001 mL) prediction of the parameters. Figure 3: Regression analysis results predicting VO2 from various parameters. In Table 6, a multiple linear regression analysis with interaction terms was conducted to explore the relationship between VO2 max (VO2/kg) and respiratory muscle strength (MIP, MEP), along with physiological factors (VE, VO2, and VCO2). The model was statistically significant and explained approximately 89.9% of the variance in VO2 max (R2 = 0.899, adjusted R2 = 0.859, F(11, 28) = 22.60, \(p\) < 0.001). The interaction between MIP and VE was found to be significant (\(\beta\) = \(-\)0.084, \(p\) = 0.006), indicating that the effect of inspiratory muscle strength on VO2 max is moderated by ventilatory efficiency. Specifically, as VE increases, the impact of MIP on VO2 max becomes more pronounced. Additionally, the interaction between MEP and VE was also significant (B = 0.072, \(p\) = 0.012), suggesting that expiratory muscle strength interacts positively with VE to influence VO2 max. However, other interaction terms, such as MIP with VO2 (B = 0.002, \(p\) = 0.315) and MIP with VCO2 (B = 0.001, \(p\) = 0.608), were not statistically significant. Similarly, no significant interactions were found between MEP with VO2 or VCO2. This suggests that while respiratory muscle strength interacts with ventilatory efficiency, it does not interact significantly with oxygen consumption or carbon dioxide production to affect VO2 max.