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There was a significant relationship between change in body weight and increase in gluteal AT-LPL activity (r=0.89, P<0.05, Figure 2), but no relationship between change in weight and increase in abdominal AT-LPL activity (r=0.54, P=0.35).
At hour 24, there was a weak correlation between change in body weight and UOP (r = -0.381), and minimal correlation between body weight change and dyspnea relief (r = -0.096).
Furthermore, the link between change in body mass index and fracture risk is unknown.
There was a moderate correlation between change in body weight and change in ALT (regression coefficient=0.38).
Furthermore, there was a weak but significant correlation between change in body fat and change in HOMA-IR (r = 0.35, p = 0.042).
The scatter-plot along with the regression line exhibits the linear dependence between change in body weight and change in A1C, which was found to be weak overall.
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Thus, the relationship between changes in body size, morphological proportions and performance capacity directly affects how organisms function in their natural environment4,8,9.
And finally, the relationship between changes in body mass may not accurately reflect changes in total body water in field settings although runners should never gain body mass (indicative of overhydration) during exercise.
Although body mass is another variable that changes within individuals over time, we did not uncover a correlation between changes in body mass and changes in carotenoid concentrations over time (F1,20.24 = 0.11, P>0.74, controlling for gender: (F1,19.85 = 2.57, P>0.13), days between sampling events (F1,20.31 = 1.11, P>0.30), and site differences).
No statistically significant univariate correlation was found between changes in body weight and other biomarkers.
No relationship has been observed between changes in body composition and cytokine levels.
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between change in hormone
between change in energy
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