2020
DOI: 10.3390/ijerph17155391
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The Association between Body Mass Index and Physical Fitness of Normal Weight/Overweight/Obese University Students

Abstract: This study aimed to apply longitudinal data (in four waves) to examine relationships between body mass index (BMI), flexibility, muscular endurance, and explosive power, and employed a random-intercept panel model (RIPM) to divide the variations of different waves into between- and within-person variations. Furthermore, a multi-group model test was conducted to explore whether an interaction effect existed between sex and these relationships. The data were collected from a university in Taiwan between August 2… Show more

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Cited by 6 publications
(9 citation statements)
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“…In particular, the goodness-of-fit statistics include the comparative fit index (CFI) ≥ 0.95 [ 38 ], root mean square error of approximation (RMSEA) ≤ 0.08 [ 34 ], non-normed fit index (NNFI) > 0.95 [ 39 ], and standardized root mean square residual (SRMR) ≤ 0.08 [ 40 ]. Values of correlation coefficients between BMI, explosive power, flexibility, and cardiorespiratory endurance less than 0.24 were considered as representing low correlation, while values of correlation coefficients exceeding 0.24 indicated a moderate correlation [ 36 ].…”
Section: Methodsmentioning
confidence: 99%
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“…In particular, the goodness-of-fit statistics include the comparative fit index (CFI) ≥ 0.95 [ 38 ], root mean square error of approximation (RMSEA) ≤ 0.08 [ 34 ], non-normed fit index (NNFI) > 0.95 [ 39 ], and standardized root mean square residual (SRMR) ≤ 0.08 [ 40 ]. Values of correlation coefficients between BMI, explosive power, flexibility, and cardiorespiratory endurance less than 0.24 were considered as representing low correlation, while values of correlation coefficients exceeding 0.24 indicated a moderate correlation [ 36 ].…”
Section: Methodsmentioning
confidence: 99%
“…One potential study, though, after testing a sample of Taiwanese students for explosive power, flexibility, and muscular endurance, Kung, Chang, Hwang, and Chi [ 36 ] explored the connections between the participants’ BMI results. The collected data were organized using the random-intercept panel model (RIPM) to display the variations in participant test results for both between- and within-person data sets.…”
Section: Introductionmentioning
confidence: 99%
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