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Preventive medicine · Jul 2016
Differential association of cardiorespiratory fitness and central adiposity among US adolescents and adults: A quantile regression approach.
- Samantha M McDonald, Andrew Ortaglia, Matteo Bottai, and Christina Supino.
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States. Electronic address: mcdona84@email.sc.edu.
- Prev Med. 2016 Jul 1; 88: 1-7.
AbstractPrevious studies assessing the association between cardiorespiratory fitness (CRF) and waist circumference (WC) have often restricted their evaluation to the association of CRF on average WC. Consequently, the assessment of important variations in the relationship of CRF across the WC distribution was precluded. The purpose of this study was to comprehensively evaluate the association between CRF and the distribution of WC using quantile regression. Secondary data analysis was conducted using data from the 1999-2004 NHANES. Participants (n=8260) aged 12-49years with complete data on estimated maximal oxygen consumption and WC were included. Quantile regression models were performed to assess the association between CRF and the 10th, 25th, 50th, 75th and 90th WC percentiles and were adjusted for age and race/ethnicity. For male and female adolescents with high CRF compared to low-fit counterparts, significant negative estimates (2.8 to 20.2cm and 2.3 to 11.2cm, respectively) were observed across most WC percentiles. Similarly, among male and female adults, high CRF was associated with significant reductions in WC across all percentiles (9.5 to 12.0cm and 3.7 to 9.2cm, respectively). For both populations, an increasing trend in the magnitude of the association of high CRF across the WC percentiles was observed. CRF appears to have a differential relationship across the WC distribution with the largest reductions in WC were found among high-fit individuals with the greatest amount of central adiposity (WC≥90th percentile). Additionally, this differential association highlights the significant limitations of statistical techniques used in previous analyses which focused on the center of the distribution.Copyright © 2016 Elsevier Inc. All rights reserved.
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