## 4 Discussion
### Fat Mass and Bone Tissue
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Dependent Variables** & **Predictors** & **Unstandardized B** & **Standardized** & **95\% CI** & **SE for B** & \(P\) & **R2** & **Adjusted R2** & **Durbin- Watson** & **T** \\ \hline \hline \multicolumn{10}{c}{**Non-obese men**} \\ \hline \multirow{3}{*}{**SOS (m/s)**} & Age & 11.613 & 0.233 & 4.624-18.602 & 3.542 & 0.001 * & & & 0.994 \\ \cline{2-10}  & V visceral FM & 1.546 & 0.218 & 0.550-2.543 & 0.505 & 0.003 * & & & 0.994 \\ \hline \hline \multicolumn{10}{c}{The least significant variables: smoking status, alcohol consumption, coffee drinking, sweetened beverages consumption, physical activity, Ca intake, vitamin D intake, BMI, PBF, FM in the trunk (\%), and FM in the arm (\%)} \\ \hline \hline \multicolumn{10}{c}{**Non-obese women**} \\ \hline \multirow{3}{*}{**SOS (m/s)**} & Age & 16.634 & 0.328 & 11.034-22.234 & 2.845 & \(<\)0.001 * & & & 0.937 \\ \cline{2-10}  & \multirow{2}{*}{FM arm, \%} & \multirow{2}{*}{0.637} & \multirow{2}{*}{0.115} & 0.037-1.238 & 0.305 & 0.038 * & 0.156 & 0.147 & 1.715 & 0.967 \\ \cline{2-10}  & Vitamin D & & & 0.815-51.299 & 12.824 & 0.043 * & & & 0.910 \\ \hline \hline \multicolumn{10}{c}{The least significant variables: smoking status, alcohol consumption, coffee drinking, sweetened beverages consumption, physical activity, Ca intake, vitamin D intake, BMI, PBF, FM in the trunk (\%), and visceral FM} \\ \hline \hline \multicolumn{10}{c}{**Obese women**} \\ \hline \multirow{3}{*}{**SOS (m/s)**} & Age & 13.463 & 0.296 & 7.469-19.457 & 0.296 & \(<\)0.001 * & & & 1.000 \\ \cline{2-10}  & V visceral FM & \(-\)0.406 & \(-\)0.166 & \(-\)0.728-0.084 & \(-\)0.166 & 0.014 * & & & 1.000 \\ \hline \hline \multicolumn{10}{c}{The least significant variables: smoking status, alcohol consumption, coffee drinking, sweetened beverages consumption, physical activity, Ca intake, vitamin D intake, BMI, PBF, FM in the trunk (\%), and FM in the arm (\%)} \\ \hline \hline \multicolumn{10}{c}{Note: * Marks statistical significance \(p\) \(<\) 0.05. Abbreviations: B, beta coefficient; CI, Confidence Interval; \(p\), value of statistical significance (linear regression analysis, forward method); R2, coefficient of determination; SE, Standard Error; SOS, speed of sound; T, tolerance (collinearity statistics), BMI, Body Mass Index; PBE, Percent Body Fat; FM, Fat Mass.} \\ \end{tabular}
\end{table} 
Table 3: Association of SOS with FM—associated parameters in various body segments after adjustment for age, behavioral, and lifestyle factors. Thus, the above data highlight the importance of controlling fat distribution to optimize bone tissue quality, particularly in obese individuals, and suggest that interventions should focus on reducing excess FM while considering the potential benefits of moderate fat content. The relationship between total FM and BMD varies across demographic categories, including age, ethnicity, and bone sites. In adults, the impact of FM on BMD appears to exhibit sex-specific differences [41]. In postmenopausal women, a positive correlation was observed between FM and BMD at various bone sites, including the spine, femur, and total body. This finding suggests that higher FM may be associated with higher BMD [42]. However, in older men, higher total adiposity correlates with lower cortical BMD, whereas a higher percentage of subcutaneous adipose tissue is associated with higher cortical and trabecular BMD [43]. Contrary to these findings, [PERSON] et al. [44] showed that total body fat was positively associated with BMD in younger girls but inversely associated with BMD in older boys, with abdominal adiposity being associated with lower BMD in both older boys and girls. [PERSON] et al. [43] reported that different fat deposits may have different associations with bone mass, with total adiposity correlating with lower cortical BMD, while a higher percentage of subcutaneous adipose tissue is associated with higher cortical and trabecular BMD.