The multivariate physical activity signature associated with metabolic health in children

Eivind Aadland, Olav Martin Kvalheim, Sigmund Alfred Anderssen, Geir Kåre Resaland, Lars Bo Andersen, Eivind Aadland, Olav Martin Kvalheim, Sigmund Alfred Anderssen, Geir Kåre Resaland, Lars Bo Andersen

Abstract

Background: Physical activity is a cornerstone for promoting good metabolic health in children, but it is heavily debated which intensities (including sedentary time) are most influential. A fundamental limitation to current evidence for this relationship is the reliance on analytic approaches that cannot handle collinear variables. The aim of the present study was to determine the physical activity signature related to metabolic health in children, by investigating the association pattern for the whole spectrum of physical activity intensities using multivariate pattern analysis.

Methods: We used a sample of 841 children (age 10.2 ± 0.3 years; BMI 18.0 ± 3.0; 50% boys) from the Active Smarter Kids study, who provided valid data on accelerometry (ActiGraph GT3X+) and several indices of metabolic health (aerobic fitness, abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure) that were used to create a composite metabolic health score. We created 16 physical activity variables covering the whole intensity spectrum (from 0-100 to ≥ 8000 counts per minute) and used multivariate pattern analysis to analyze the data.

Results: Physical activity intensities in the vigorous range (5000-7000 counts per minute) were most strongly associated with metabolic health. Moderate intensity physical activity was weakly related to health, and sedentary time and light physical activity were not related to health.

Conclusions: This study is the first to determine the multivariate physical activity signature related to metabolic health in children across the whole intensity spectrum. This novel approach shows that vigorous physical activity is strongest related to metabolic health. We recommend future studies adapt a multivariate analytic approach to further develop the field of physical activity epidemiology.

Trial registration: The study was registered in Clinicaltrials.gov (www.clinicaltrials.gov) 7th of April 2014 with identification number NCT02132494 .

Keywords: Accelerometer; Childhood; Intensity; Metabolic risk factors; Multivariate pattern analysis; Pediatric.

Conflict of interest statement

Ethics approval and consent to participate

The South-East Regional Committee for Medical Research Ethics approved the study protocol (reference number 2013/1893). We obtained written informed consent from each child’s parents or legal guardian and from the responsible school authorities prior to all testing.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
The multivariate PA signature associated with a composite metabolic health score in children displayed as a selectivity ratio (SR) plot. The PLS regression model includes 3 components, R2 = 13.3%, and is adjusted for age and sex. The SR for each variable is calculated as the ratio of explained to residual variance on the predictive (target projected) component. A negative bar implies that increased PA are associated with better metabolic health
Fig. 2
Fig. 2
The multivariate PA signature associated different risk factors in children displayed as a selectivity ratio (SR) plot. The models (PLS regression) is adjusted for age and sex. WC:height ratio = waist circumference to height ratio (3 components, R2 = 13.6%); TG = triglyceride (1 component, R2 = 2.2%); TC:HDL ratio = total to high-density lipoprotein cholesterol ratio (1 component, R2 = 3.1%); HOMA = homeostasis model assessment (2 components, R2 = 6.6%); Andersen test (3 components, R2 = 21.0%). The SR for each variable is calculated as the ratio of explained to residual variance on the predictive (target projected) component. A negative bar implies that increased PA are associated with better metabolic health
Fig. 3
Fig. 3
The unweighted target projection loadings for PA intensity intervals on the composite metabolic health vector in children. The figure shows the relative importance of the different PA intensity intervals for a given duration (minutes/day) of change. A negative bar implies that increased PA are associated with better metabolic health

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