Affiliations 

  • 1 Centre for Exercise, Nutrition, and Health Sciences, School for Policy Studies, University of Bristol, 8 Priory Road, Bristol BS8 1TZ, UK
  • 2 MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield Grove, Bristol BS8 2BN, UK
  • 3 Centre for Population Health, (CePH), Department of Paediatrics, Social and Preventive Medicine, Faculty of Medicine, University of Malaya 59100, 50603, Kuala Lumpur 50603, Malaysia
  • 4 Department of Paediatrics, Faculty of Medicine, University Malaya, Kuala Lumpur 59100, Malaysia
PMID: 31766777 DOI: 10.3390/ijerph16234662

Abstract

Patterns of physical activity (PA) that optimize both fitness and fatness may better predict cardiometabolic health. Reduced rank regression (RRR) was applied to identify combinations of the type (e.g., football vs. skipping), location and timing of activity, explaining variation in cardiorespiratory fitness (CRF) and Body Mass Index (BMI). Multivariable regressions estimated longitudinal associations of PA pattern scores with cardiometabolic health in n = 579 adolescents aged 13-17 years from the Malaysian Health and Adolescent Longitudinal Research Team study. PA pattern scores in boys were associated with higher fitness (r = 0.3) and lower fatness (r = -0.3); however, in girls, pattern scores were only associated with higher fitness (r = 0.4) (fatness, r = -0.1). Pattern scores changed by β = -0.01 (95% confidence interval (CI) -0.04, 0.03) and β = -0.08 (95% CI -0.1, -0.06) per year from 13 to 17 years in boys and girls respectively. Higher CRF and lower BMI were associated with better cardiometabolic health at 17 years, but PA pattern scores were not in either cross-sectional or longitudinal models. RRR identified sex-specific PA patterns associated with fitness and fatness but the total variation they explained was small. PA pattern scores changed little through adolescence, which may explain the limited evidence on health associations. Objective PA measurement may improve RRR for identifying optimal PA patterns for cardiometabolic health.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.