Literature DB >> 30276872

Longitudinal associations of physical activity and sedentary time with cardiometabolic risk factors in children.

Juuso Väistö1,2, Eero A Haapala1,3, Anna Viitasalo1, Theresia M Schnurr4, Tuomas O Kilpeläinen4, Panu Karjalainen1, Kate Westgate5, Hanna-Maaria Lakka1, David E Laaksonen6, Ulf Ekelund5,7, Søren Brage5, Timo A Lakka1,8,9.   

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 = <0.001), and insulin∆ (β = -0.213, P = 0.006) and directly with HDL cholesterol∆ (β = 0.184, P = 0.022). LPA∆ only associated negatively with CRS∆ (β = -0.163, P = 0.032). ST∆ associated directly with CRS∆ (β = 0.218, P = 0.003), BF%∆ (β = 0.212, P = 0.016), and insulin∆ (β = 0.159, P = 0.049).
CONCLUSIONS: Increased VPA and MVPA and decreased ST were associated with reduced overall cardiometabolic risk and major individual risk factors. Change in LPA had weaker associations with changes in these cardiometabolic risk factors. Our findings suggest that increasing at least moderate-intensity PA and decreasing ST decrease cardiometabolic risk in children.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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Year:  2018        PMID: 30276872      PMCID: PMC6485341          DOI: 10.1111/sms.13315

Source DB:  PubMed          Journal:  Scand J Med Sci Sports        ISSN: 0905-7188            Impact factor:   4.221


  49 in total

1.  Reliability and validity of the combined heart rate and movement sensor Actiheart.

Authors:  S Brage; N Brage; P W Franks; U Ekelund; N J Wareham
Journal:  Eur J Clin Nutr       Date:  2005-04       Impact factor: 4.016

2.  Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure.

Authors:  Søren Brage; Niels Brage; Paul W Franks; Ulf Ekelund; Man-Yu Wong; Lars Bo Andersen; Karsten Froberg; Nicholas J Wareham
Journal:  J Appl Physiol (1985)       Date:  2003-09-12

3.  Features of the metabolic syndrome are associated with objectively measured physical activity and fitness in Danish children: the European Youth Heart Study (EYHS).

Authors:  Søren Brage; Niels Wedderkopp; Ulf Ekelund; Paul W Franks; Nicholas J Wareham; Lars Bo Andersen; Karsten Froberg
Journal:  Diabetes Care       Date:  2004-09       Impact factor: 19.112

4.  Metabolic syndrome in childhood predicts adult metabolic syndrome and type 2 diabetes mellitus 25 to 30 years later.

Authors:  John A Morrison; Lisa Aronson Friedman; Ping Wang; Charles J Glueck
Journal:  J Pediatr       Date:  2007-11-05       Impact factor: 4.406

5.  Objectively measured time spent sedentary is associated with insulin resistance independent of overall and central body fat in 9- to 10-year-old Portuguese children.

Authors:  Luis B Sardinha; Lars Bo Andersen; Sigmund A Anderssen; Ana L Quitério; Rui Ornelas; Karsten Froberg; Chris J Riddoch; Ulf Ekelund
Journal:  Diabetes Care       Date:  2007-12-10       Impact factor: 19.112

6.  Associations between physical activity, body fat, and insulin resistance (homeostasis model assessment) in adolescents: the European Youth Heart Study.

Authors:  Nico S Rizzo; Jonatan R Ruiz; Leila Oja; Tomas Veidebaum; Michael Sjöström
Journal:  Am J Clin Nutr       Date:  2008-03       Impact factor: 7.045

7.  Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study).

Authors:  Lars Bo Andersen; Maarike Harro; Luis B Sardinha; Karsten Froberg; Ulf Ekelund; Søren Brage; Sigmund Alfred Anderssen
Journal:  Lancet       Date:  2006-07-22       Impact factor: 79.321

8.  TV viewing and physical activity are independently associated with metabolic risk in children: the European Youth Heart Study.

Authors:  Ulf Ekelund; Søren Brage; Karsten Froberg; Maarike Harro; Sigmund A Anderssen; Luis B Sardinha; Chris Riddoch; Lars Bo Andersen
Journal:  PLoS Med       Date:  2006-12       Impact factor: 11.069

9.  Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity.

Authors:  Søren Brage; Ulf Ekelund; Niels Brage; Mark A Hennings; Karsten Froberg; Paul W Franks; Nicholas J Wareham
Journal:  J Appl Physiol (1985)       Date:  2007-04-26

10.  Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study.

Authors:  U Ekelund; S A Anderssen; K Froberg; L B Sardinha; L B Andersen; S Brage
Journal:  Diabetologia       Date:  2007-07-20       Impact factor: 10.122

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  12 in total

1.  Cardiorespiratory Fitness, Physical Activity, and Insulin Resistance in Children.

Authors:  Eero A Haapala; Petri Wiklund; Niina Lintu; Tuomo Tompuri; Juuso Väistö; Taija Finni; Ina M Tarkka; Titta Kemppainen; Alan R Barker; Ulf Ekelund; Soren Brage; Timo A Lakka
Journal:  Med Sci Sports Exerc       Date:  2020-05

2.  Validity of traditional physical activity intensity calibration methods and the feasibility of self-paced walking and running on individualised calibration of physical activity intensity in children.

Authors:  Eero A Haapala; Ying Gao; Anssi Vanhala; Timo Rantalainen; Taija Finni
Journal:  Sci Rep       Date:  2020-07-03       Impact factor: 4.379

3.  Longitudinal associations of physical activity and pubertal development with academic achievement in adolescents.

Authors:  Eero A Haapala; Henna L Haapala; Heidi Syväoja; Tuija H Tammelin; Taija Finni; Noona Kiuru
Journal:  J Sport Health Sci       Date:  2019-07-12       Impact factor: 7.179

4.  The trajectory of patterns of light and sedentary physical activity among females, ages 14-23.

Authors:  Deborah A Cohen; Bing Han; Lisa Kraus; Deborah Rohm Young
Journal:  PLoS One       Date:  2019-11-06       Impact factor: 3.240

5.  Associations of physical activity, sedentary time, and cardiorespiratory fitness with heart rate variability in 6- to 9-year-old children: the PANIC study.

Authors:  Aapo Veijalainen; Eero A Haapala; Juuso Väistö; Marja H Leppänen; Niina Lintu; Tuomo Tompuri; Santeri Seppälä; Ulf Ekelund; Mika P Tarvainen; Kate Westgate; Søren Brage; Timo A Lakka
Journal:  Eur J Appl Physiol       Date:  2019-09-18       Impact factor: 3.078

6.  Longitudinal changes in moderate-to-vigorous-intensity physical activity in children and adolescents: A systematic review and meta-analysis.

Authors:  Abdulaziz Farooq; Anne Martin; Xanne Janssen; Mathew G Wilson; Ann-Marie Gibson; Adrienne Hughes; John J Reilly
Journal:  Obes Rev       Date:  2019-10-23       Impact factor: 9.213

7.  Parent perceptions of their child's and their own physical activity after treatment for childhood cancer.

Authors:  Lauren Ha; Claire E Wakefield; Joanna Fardell; Richard J Cohn; David Simar; Christina Signorelli; David Mizrahi
Journal:  Support Care Cancer       Date:  2022-08-01       Impact factor: 3.359

8.  A 2 year physical activity and dietary intervention attenuates the increase in insulin resistance in a general population of children: the PANIC study.

Authors:  Timo A Lakka; Niina Lintu; Juuso Väistö; Anna Viitasalo; Taisa Sallinen; Eero A Haapala; Tuomo T Tompuri; Sonja Soininen; Panu Karjalainen; Theresia M Schnurr; Santtu Mikkonen; Mustafa Atalay; Tuomas O Kilpeläinen; Tomi Laitinen; David E Laaksonen; Kai Savonen; Soren Brage; Ursula Schwab; Jarmo Jääskeläinen; Virpi Lindi; Aino-Maija Eloranta
Journal:  Diabetologia       Date:  2020-08-20       Impact factor: 10.122

9.  Home and Neighborhood Physical Activity Location Availability among African American Adolescent Girls Living in Low-Income, Urban Communities: Associations with Objectively Measured Physical Activity.

Authors:  Ann Pulling Kuhn; Alexandra Cockerham; Nicole O'Reilly; Jacob Bustad; Victor Miranda; Tatiana V Loboda; Maureen M Black; Erin R Hager
Journal:  Int J Environ Res Public Health       Date:  2021-05-09       Impact factor: 3.390

10.  Fat-free/lean body mass in children with insulin resistance or metabolic syndrome: a systematic review and meta-analysis.

Authors:  Diana Paola Córdoba-Rodríguez; Iris Iglesia; Alejandro Gomez-Bruton; Gerardo Rodríguez; José Antonio Casajús; Hernan Morales-Devia; Luis A Moreno
Journal:  BMC Pediatr       Date:  2022-01-22       Impact factor: 2.125

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