Abstract

IntroductionCompositional data analysis is one appropriate method for co-dependent data, even when data are collected for a subdivision of the 24-hour period, such as the waking day. Objectives were to use compositional analyses to examine the combined and relative associations of sedentary time (ST), light-intensity physical activity (LPA), moderate-intensity physical activity (MPA), and vigorous-intensity physical activity (VPA) with cardiometabolic biomarkers in a representative sample of children and youth.MethodsThis cross-sectional study included 2544 participants aged 6–17 years from the 2003–2006 United States National Health and Nutrition Examination Survey. ST (<100 counts per minute), LPA (100 counts per minute to <4 METs; Freedson age-specific equation), MPA (4 to <7 METs), and VPA (≥7 METs) were accelerometer-derived. Cardiometabolic biomarkers included waist circumference, body mass index (BMI) z-score, HDL-cholesterol, C-reactive protein, and blood pressure. Triglycerides, glucose, insulin, and LDL-cholesterol were measured in a fasting sub-sample of adolescents (n = 670). Compositional linear regression models were conducted.ResultsThe composition of ST, LPA, MPA, and VPA was significantly associated with BMI z-score, log waist circumference, systolic and diastolic blood pressure, HDL-cholesterol, and log plasma glucose (variance explained: 1–29%). Relative to the other three behaviors, VPA was negatively associated with BMI z-score (γVPA = -0.206, p = 0.005) and waist circumference (γVPA = -0.03, p = 0.001). Conversely, ST was positively associated with waist circumference (γST = 0.029, p = 0.013). ST and VPA were also positively associated with diastolic blood pressure (γST = 2.700, p = 0.018; γVPA = 1.246, p = 0.038), relative to the other behaviors, whereas negative associations were observed for LPA (γLPA = -2.892, p = 0.026). Finally, VPA was positively associated with HDL-cholesterol, relative to other behaviors (γVPA = 0.058, p<0.001).ConclusionsThe ST and physical activity composition appears important for many aspects of cardiometabolic health in children and youth. Compositions with more time in higher-intensity activities may be better for some aspects of cardiometabolic health.

Highlights

  • ObjectivesData collected for a subdivision of the 24-hour period still represents a finite amount of time making compositional analysis an appropriate method.[7]. the objectives of this study were to use

  • Compositional data analysis is one appropriate method for co-dependent data, even when data are collected for a subdivision of the 24-hour period, such as the waking day

  • The composition of sedentary time (ST), light-intensity physical activity (LPA), moderate-intensity physical activity (MPA), and vigorous-intensity physical activity (VPA) was significantly associated with body mass index (BMI) z-score, log waist circumference, systolic and diastolic blood pressure, HDL-cholesterol, and log plasma glucose

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Summary

Objectives

Data collected for a subdivision of the 24-hour period still represents a finite amount of time making compositional analysis an appropriate method.[7]. the objectives of this study were to use. Data collected for a subdivision of the 24-hour period still represents a finite amount of time making compositional analysis an appropriate method.[7]. The objectives of this study were to use. The objectives of this paper were to use compositional analyses to examine the combined and relative associations of ST, LPA, MPA, VPA with cardiometabolic biomarkers in a representative sample of 6–17 year-olds living in the United States

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