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Multiple linear regression identified exercise capacity and BMI as significant predictors of BMD.
The reports also identified exercise periods, eating food when drinking, and self-reported sweating (Swift and Swette 1992).
The percentage of correctly identified exercise intensity increased in all groups, but the improvements did not reach statistical significance.
At baseline, the percentage of correctly identified exercise intensity was 25%, 23%, and 10% in the manual pulse, pedometer, and HR monitor groups, respectively.
Interestingly, our study identified exercise intensity as the strongest predictor for the increase of cTnI levels, but also for a positive cTnI test.
Logistic regression analysis identified exercise intensity (P < 0.001), but not BMI, body fat percentage or waist circumference to significantly relate to positive troponin tests.
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Their analyses provided candidate genes that are related to horse racing performance: six previously identified exercise-associated genes and 91 early regulated transcription factors that are differentially expressed by exercise, three genes that display high SNV density, and four alternatively expressed splicing variants.
Health economic evidence is uniquely suited to provide valuable information when making decisions about scarce resources, but was not explicitly considered in the majority of the identified exercises.
As exercise challenge tests are quite insensitive to identify exercise induced bronchoconstriction in elite athletes [ 3], easier but also standardized tests would be needed.
Further research is required to identify exercise training programs effective for improving specific gait characteristics such as gait variability in people with dementia.
While pulmonary rehabilitation is practiced as a multi-disciplinary therapy, evidence-based analysis identifies exercise training as the most effective component [ 15].
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