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Cardiometabolic Risk Factors and Physical Activity Patterns Maximizing Fitness and Minimizing Fatness Variation in Malaysian Adolescents: A Novel Application of Reduced Rank Regression

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 cardiorespirator...

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Published in:International journal of environmental research and public health 2019-11, Vol.16 (23), p.4662
Main Authors: Toumpakari, Zoi, Jago, Russell, Howe, Laura D, Majid, Hazreen Abdul, Papadaki, Angeliki, Mohammadi, Shooka, Jalaludin, Muhammad Yazid, Dahlui, Maznah, Mohamed, Mohd Nahar Azmi, Su, Tin Tin, Johnson, Laura
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description 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.
doi_str_mv 10.3390/ijerph16234662
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subjects Activity patterns
Adolescent
Behavior
Blood pressure
Body mass
Body Mass Index
Body size
Cardiorespiratory Fitness
Cardiovascular Diseases - etiology
Child development
Cholesterol
Correlation analysis
Cross-Sectional Studies
Diet
Disease
Energy expenditure
Energy intake
Exercise
Female
Health risks
Humans
Hypotheses
Longitudinal Studies
Low density lipoprotein
Malaysia
Male
Obesity
Physical activity
Physical Fitness
Public health
Risk analysis
Risk Factors
Studies
Teenagers
Triglycerides
title Cardiometabolic Risk Factors and Physical Activity Patterns Maximizing Fitness and Minimizing Fatness Variation in Malaysian Adolescents: A Novel Application of Reduced Rank Regression
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