ArticleInternational journal of environmental research and public health2023
Effect of Noninvasive Static Human Data on Maximum Data in Exercise.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Maximum data in exercise (Max-Ex), including maximum heart rate (HRmax), peak oxygen uptake (VO2pk), maximum power (MaxP), etc., are frequently used, whether it is for the determination of exercise intensity, the measurement of an athlete’s performance, assessment of recovery from disease, and so on. However, very often this choice does not take into account the targeted individual. We recruited 32 males and 29 females to undergo an incremental graded exercise test (GXT). Therefore, our study seeks to determine variations in Max-Ex, according to the noninvasive static human data (Non-In data). Data showed a significant relationship (p < 0.001) between body composition and Max-Ex. Of the 41 types of Non-In data we collected in communities, the body composition generally showed high correlation (maximum r = 0.839). 57.5% of the data, of which r > 0.6 were about body composition. The muscle-related body composition data had a greater effect on power, and the fat-related ones had a greater effect on HRmax and VO2pk. For some types of Max-Ex, the older and younger ones showed specific differences. Therefore, these results can be employed to adequately prescribe personalized health promotion programs according to diversity and availability, and have some reference value for other studies using Max-Ex.
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