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formatted: 1) 4M model = - 69 + (4.602 x PBF) + (-16.481 x BFMI) + (25.572 x PMI) + (0.671 x FFMI); and 2) 3M model = -69.64 + (4.840 x PBF) + (-17.182 x BFMI) + (28.796 x PMI).
1) &plain 25% of the variability in EPFS, where the majority of the variability (24.4%) is determined by PBF, BFMI and PMI (Fig.
Next to PBF, a widely used measure of body fatness, BFMI, PMI and FFMI entered the prediction model.
Conversely, the negative association of PBF, BFMI and IH was highest in PU, RU and SU, respectively, suggesting that good quality of muscle mass may be very important for physical performance, especially knowing that PO tend to be fattier by time spent in service (Lagestad et al.).
Descriptive statistics for all variables Variables Mean SD Min Max Age 31.61 4.79 22.00 52.00 BH (cm) 172.97 6.09 156.00 190.00 BM (kg) 77.53 11.66 48.30 115.30 BMI (kg/[m.sup.2]) 25.86 3.26 18.80 35.59 PBF (%) 23.59 6.59 8.03 37.37 PSMM (%) 43.13 3.93 34.77 52.36 BFMI (kg/[m.sup.2]) 6.23 2.24 1.70 11.80 SMMI (kg/[m.sup.2]) 11.09 1.27 7.78 14.23 PMI (kg/[m.sup.2]) 3.91 0.41 2.87 4.91 IH (%/kg x [m.sup.2]) 0.91 0.22 0.35 1.51 FFMI (kg/[m.sup.2]) 19.64 2.31 12.33 25.65 RUN (sec) 1084.46 136.22 724.00 1509.00 PU (No) 3 5.09 13.86 0.00 65.00 SITUP (No) 41.19 11.05 11.00 80.00 EPFS 50.00 16.67 4.12 98.15
Partialization of the contractile and ballast tissue variables with respect to longitudinality revealed that the mean value for the respondents' body skeletal muscle index (SSMI) was 10.34 kg/[m.sup.2], their body protein mass index (PMI) was 3.62 kg/[m.sup.2], their lean mass index (FFMI) was 18.27 kg/[m.sup.2], while their total body fat mass index (BFMI) was 2.85 kg/[m.sup.2].
The associations between railway noise and BFMI were not statistically significant in all models, but showed similar tendencies of increased estimates for the highly exposed.
We also found evidence of effect modification by comorbidity, with no association between road traffic noise and BMI and BFMI among participants with comorbidity, and a positive association among those without comorbidity (e.g., for BMI, 0.017; 95% CI: -0.17, 0.20; and 0.21; 95% CI: 0.14, 0.28, respectively, interaction p-value 0.04).
In this large cross-sectional study of middle-aged Danish men and women, we found consistent and statistically significant positive associations between road traffic noise and waist circumference, BMI, BFMI, and LBMI.
LBMI and BFMI were positively correlated in this study ([R.sub.s] = 0.75 among women and [R.sub.s] = 0.70) as well as in other studies (Bosy-Westphal and Muller 2015).
Road traffic noise was not associated with BMI or BFMI among participants classified as having comorbidity based on the Charlson comorbidity index.
We found associations between road traffic noise and BMI, waist circumference, and BFMI to be strongest among participants exposed to > 60 dB railway noise.
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