1. Longitudinal associations of physical activity and sedentary time with cardiometabolic risk factors in children
- Author
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Kate Westgate, Hanna-Maaria Lakka, Panu Karjalainen, Timo A. Lakka, Soren Brage, Eero A. Haapala, David E. Laaksonen, Ulf Ekelund, Juuso Väistö, Tuomas O. Kilpeläinen, Anna Viitasalo, and Theresia M. Schnurr
- Subjects
Blood Glucose ,Male ,Cross-sectional study ,physical activity ,Blood Pressure ,liikunta ,030204 cardiovascular system & hematology ,Body fat percentage ,chemistry.chemical_compound ,0302 clinical medicine ,Heart Rate ,Risk Factors ,Insulin ,Orthopedics and Sports Medicine ,Longitudinal Studies ,Prospective Studies ,Child ,ta315 ,Prospective cohort study ,Finland ,Anthropometry ,riskitekijät ,Lipids ,Cardiovascular Diseases ,Female ,lipids (amino acids, peptides, and proteins) ,Waist Circumference ,fyysinen aktiivisuus ,medicine.medical_specialty ,Waist ,Physical Therapy, Sports Therapy and Rehabilitation ,pitkittäistutkimus ,ta3111 ,Article ,03 medical and health sciences ,Metabolic Diseases ,children ,Internal medicine ,Heart rate ,medicine ,Humans ,Exercise ,lapset ,Cholesterol ,business.industry ,terveydentila ,030229 sport sciences ,cardiometabolic risk factors ,Cross-Sectional Studies ,Blood pressure ,chemistry ,Sedentary Behavior ,business - Abstract
BACKGROUND There are few prospective studies on the associations of changes in objectively measured vigorous physical activity (VPA∆ ), moderate-to-vigorous physical activity (MVPA∆ ), light physical activity (LPA∆ ), and sedentary time (ST∆ ) with changes in cardiometabolic risk factors (∆ ) in children. We therefore investigated these relationships among children. METHODS The participants were a population sample of 258 children aged 6-8 years followed for 2 years. We assessed PA and ST by a combined heart rate and movement sensor; computed continuous age- and sex-adjusted z-scores for waist circumference, blood pressure, and fasting insulin, glucose, triglycerides, and high-density lipoprotein (HDL) cholesterol; and constructed a cardiometabolic risk score (CRS) of these risk factors. Data were analyzed using linear regression models adjusted for age, sex, the explanatory and outcome variables at baseline, and puberty. RESULTS VPA∆ associated inversely with CRS∆ (β = -0.209, P = 0.001), body fat percentage (BF%)∆ (β = -0.244, P = 0.001), insulin∆ (β = -0.220, P = 0.001), and triglycerides∆ (β = -0.164, P = 0.012) and directly with HDL cholesterol∆ (β = 0.159, P = 0.023). MVPA∆ associated inversely with CRS∆ (β = -0.178, P = 0.012), BF%∆ (β = -0.298, P =
- Published
- 2018
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