## 3 Results
### Injury Type--Predictors  
The multinomial logistic regression results show that the addition of the predictors time spent on PA of moderate intensity (likelihood ratio chi-square test: \(\chi^{2}(2)=6.701\), \(p=0.035\)) and bone age (likelihood ratio chi-square test: \(\chi^{2}(2)=7.196\), \(p=0.027\)) to a model that contained only the intercept significantly improved the fit between the model and data (likelihood ratio chi-square test: \(\chi^{2}(4)=19.377\), \(p=0.001\)). [PERSON]'s (\(\chi^{2}(82)=81.956\), \(p=0.481\)) and deviance (\(\chi^{2}(82)=76.424\), \(p=0.653\)) chi-square goodness of fit tests indicated that the model fitted the data. The model pseudo R-squares (Cox and Snell R-square = 0.356; Nagelkerke R-square = 0.402; McFadden R-square = 0.202) showed that the model has reasonable predictive power. The predictors bone age and moderate PA intensity were significant in distinguishing both strains and fractures from sprains. The odds of having a strain or a fracture compared to having a sprain increased 1.04 times per unit increment  
Figure 3: Injured body areas.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**PA Intensity (Minutes)**} \\  & **Moderate (\({}^{\textbf{4}}\))** & **Vigorous** & **Very Vigorous** & **Total MVPA (\({}^{\textbf{5}}\))** \\  & **_M (SD)_** & **_M (SD)_** & **_M (SD)_** & **_M (SD)_** \\ \hline Injury Occurrence (\({}^{\textbf{1}}\)) & & & & \\ No (\(N=70\)) & 110.47 (38.63) & 17.97 (13.97) & 4.47 (13.53) & 135.1 (6.67) \\ Yes (\(N=51\)) & 108.37 (30.23) & 19.35 (15.95) & 6.9 (12.75) & 133.84 (38.3) \\ \(p\) & 0.747 & 0.612 & 0.319 & 0.897 \\ Body Area Injury Location (\({}^{\textbf{2}}\)) & & & & \\ Lower limbs (\(N=31\)) & 110.98 (31.52) & 21.75 (18.25) & 7.28 (13.71) & 140.01 (37.95) \\ Upper limbs (\(N=12\)) & 98.46 (22.51) & 13.81 (9.73) & 5.06 (11.18) & 114.0 (31.12) \\ \(p\) & 0.217 & 0.162 & 0.534 & 0.041 \({}^{\star}\) \\ Injury Type (\({}^{\textbf{3}}\)) & & & & \\ Strains (\(N=17\)) & 118.02 (29.91) & 25.11 (21.55) & 5.22 (9.24) & 148.36 (40.24) \\ Sprains (\(N=15\)) & 88.98 18.21) & 19.47 (15.1) & 12.3 (19.18) & 118.38 (34.04) \\ Fractures (\(N=12\)) & 117.38 (32.92) & 15.30 (8.82) & 4.25 (4.44) & 136.93 (37.91) \\ \(p\) & 0.005 ** & 0.508 & 0.578 & 0.084 \\ Injury Rate & 108.37 (30.23) & 19.35 (15.95) & 6.9 (12.75) & 133.84 (38.3) \\ \hline \hline \end{tabular}  
* \(p<0.05\); **\({}^{\star}p<0.01\). (\({}^{\textbf{1}}\)) The jury occurrence differences were evaluated using independent-samples \(t\)-tests.
* \({}^{\textbf{2}}\) The body area injury location differences were evaluated using independent-samples \(t\)-tests, except for very vigorous PA intensity, for which the Mann–Whitney test was used. (\({}^{\textbf{3}}\)) The injury type differences were evaluated using ANOVA tests and [PERSON]’s HSD post hoc tests, except for vigorous and very vigorous PA intensities, for which the Kruskal-Wallis test and Dunn–Bonferroni post hoc tests were used. (\({}^{\textbf{4}}\)) For moderate PA intensity, there were significant differences between strains and the other two types of injury. (\({}^{\textbf{6}}\)) For total moderate to vigorous PA intensity, there were significant differences between lower limbs and upper limbs.  
\end{table}
Table 3: Mean (_M_) and standard deviation (_SD_) of time spent (minutes) on PA at each intensity level—moderate, vigorous, very vigorous and total MVPA (moderate to very vigorous)—by injury occurrence, body area injury location, injury type and injury rate.  
(minute) in the time spent on moderate PA. Likewise, the odds of having a strain or a fracture compared to having a strain decreased by 1.7 times per unit increment (year) in bone age (strain: 1/0.577 = 1.733; fracture: 1/0.574 = 1.742). The results can be seen in Table 4. The variable time spent on MVPA, decimal age and maturity offset, which were significant predictors in the preliminary analysis, lost significance in the final multinomial logistic regression model.