Associations of Sitting Behavior Patterns With Cardiometabolic Risk in Children: The Sit Less for Health Cross-Sectional Study

in Journal of Physical Activity and Health
Restricted access

Purchase article

USD $24.95

Student 1 year subscription

USD $115.00

1 year subscription

USD $153.00

Student 2 year subscription

USD $218.00

2 year subscription

USD $285.00

Background: The objective of this study was to investigate the associations between sedentary behavior patterns and cardiometabolic risk in children using a monitor that accurately distinguishes between different postures. Methods: In this cross-sectional study, 118 children (67 girls) aged 11–12 years had adiposity, blood pressure, lipids, and glucose measured, and then they wore an activPAL device to record sitting, standing, and stepping for 7 consecutive days. Data were analyzed using multiple linear regression. Results: After adjustment for potential confounders and moderate to vigorous physical activity, the number of breaks in sitting was significantly negatively associated with adiposity (standardized β ≥ −0.546; P ≤ .001) and significantly positively associated with high-density lipoprotein cholesterol (β = 0.415; P ≤ .01). Time in prolonged sitting bouts was significantly negatively associated with adiposity (β ≥ −0.577; P ≤ .001) and significantly positively associated with high-density lipoprotein cholesterol (β = 0.432; P ≤ .05). Standing time was significantly negatively associated with adiposity (β ≥ −0.270; P ≤ .05) and significantly positively associated with high-density lipoprotein cholesterol (β = 0.312; P ≤ .05). Conclusions: This study suggests that increasing the number of breaks in sitting and increasing standing time are beneficially associated with cardiometabolic risk and should be considered in health promotion interventions in children.

Stockwell, Smith, Weaver, Hankins, and Bailey are with the School of Sport Science and Physical Activity, Institute for Sport and Physical Activity Research, University of Bedfordshire, Polhill Avenue, Bedford, Bedfordshire, United Kingdom. Stockwell is with the Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, Cambridge, Cambridgeshire, United Kingdom; and the Faculty of Health, Social Care and Education, Anglia Ruskin University, Cambridge, Cambridgeshire, United Kingdom.

Bailey (daniel.bailey@beds.ac.uk) is corresponding author.
Journal of Physical Activity and Health
Article Sections
References
  • 1.

    Kavey R-EWDaniels SRLauer RMAtkins DLHayman LLTaubert K. American heart association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. Circulation. 2003;107(11):15621566. PubMed ID: 12654618 doi:10.1161/01.CIR.0000061521.15730.6E

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Morrison JAFriedman LAGray-McGuire C. Metabolic syndrome in childhood predicts adult cardiovascular disease 25 years later: the Princeton lipid research clinics follow-up study. Pediatrics. 2007;120(2):340345. PubMed ID: 17671060 doi:10.1542/peds.2006-1699

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Isomaa BAlmgren PTuomi Tet al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care. 2001;24(4):683689. PubMed ID: 11315831 doi:10.2337/diacare.24.4.683

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Tremblay MSAubert SBarnes JDet al. Sedentary Behavior Research Network (SBRN)–terminology consensus project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):75. PubMed ID: 28599680 doi:10.1186/s12966-017-0525-8

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Bailey DPBoddy LMSavory LADenton SJKerr CJ. Associations between cardiorespiratory fitness, physical activity and clustered cardiometabolic risk in children and adolescents: the happy study. Eur J Pediatr. 2012;171(9):13171323. PubMed ID: 22419363 doi:10.1007/s00431-012-1719-3

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Verloigne MVan Lippevelde WMaes Let al. Self-reported TV and computer time do not represent accelerometer-derived total sedentary time in 10 to 12-year-olds. Eur J Public Health. 2013;23(1):3032. PubMed ID: 22544913 doi:10.1093/eurpub/cks047

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Basterfield LAdamson AJFrary JKParkinson KNPearce MSReilly JJ. Longitudinal study of physical activity and sedentary behavior in children. Pediatrics. 2011;127(1):e24e30. PubMed ID: 21173005 doi:10.1542/peds.2010-1935

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Carson VJanssen I. Volume, patterns, and types of sedentary behavior and cardio-metabolic health in children and adolescents: a cross-sectional study. BMC Public Health. 2011;11(1):274. doi:10.1186/1471-2458-11-274

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Colley RCGarriguet DJanssen Iet al. The association between accelerometer-measured patterns of sedentary time and health risk in children and youth: results from the Canadian Health Measures Survey. BMC Public Health. 2013;13(1):200. doi:10.1186/1471-2458-13-200

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Bailey DPCharman SJPloetz TSavory LAKerr CJ. Associations between prolonged sedentary time and breaks in sedentary time with cardiometabolic risk in 10–14-year-old children: The happy study. J Sports Sci. 2017;35(22):21642171. PubMed ID: 27892780 doi:10.1080/02640414.2016.1260150

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Cliff DPJones RABurrows TLMorgan PJCollins CEBaur LA. Volumes and bouts of sedentary behavior and physical activity: associations with cardiometabolic health in obese children. Obesity. 2014;22:e112e118. PubMed ID: 24788574 doi:10.1002/oby.20698

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Ekelund UAnderssen SAFroberg KSardinha LBAndersen LBBrage S. Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study. Diabetologia. 2007;50:18321840. PubMed ID: 17641870 doi:10.1007/s00125-007-0762-5

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Healy GNMatthews CEDunstan DWWinkler EAOwen N. Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003–06. Eur Heart J. 2011;32(5):590597. PubMed ID: 21224291 doi:10.1093/eurheartj/ehq451

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Altenburg TMde Niet MVerloigne Met al. Occurrence and duration of various operational definitions of sedentary bouts and cross-sectional associations with cardiometabolic health indicators: the energy-project. Prev Med. 2015;71:101106. PubMed ID: 25535676 doi:10.1016/j.ypmed.2014.12.015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Saunders TJChaput J-PGoldfield GSet al. Prolonged sitting and markers of cardiometabolic disease risk in children and youth: a randomized crossover study. Metabolism. 2013;62(10):14231428. PubMed ID: 23773981 doi:10.1016/j.metabol.2013.05.010

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Saunders TJTremblay MSMathieu MEet al. Associations of sedentary behavior, sedentary bouts and breaks in sedentary time with cardiometabolic risk in children with a family history of obesity. PLoS ONE. 2013;8(11):e79143. PubMed ID: 24278117 doi:10.1371/journal.pone.0079143

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Carson VStone MFaulkner G. Patterns of sedentary behavior and weight status among children. Pediatr Exerc Sci. 2014;26(1):95102. PubMed ID: 24092774 doi:10.1123/pes.2013-0061

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Cooper ARGoodman APage ASet al. Objectively measured physical activity and sedentary time in youth: the International Children’s Accelerometry Database (ICAD). Int J Behav Nutr Phys Act. 2015;12(1):113. doi:10.1186/s12966-015-0274-5

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Janssen XMann KDBasterfield Let al. Development of sedentary behavior across childhood and adolescence: longitudinal analysis of the gateshead millennium study. Int J Behav Nutr Phys Act. 2016;13(1):88. doi:10.1186/s12966-016-0413-7

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Tanner JM. Growth at Adolescence: With a General Consideration of the Effects of Hereditary and Environmental Factors Upon Growth and Maturation from Birth to Maturity. Oxford, UK: Blackwell Scientific Publications; 1962.

    • Search Google Scholar
    • Export Citation
  • 21.

    Department for Communities and Local Government. English indices of deprivation 2015. 2015; www.imd-by-postcode.opendatacommunities.org. Accessed 30 June 2017.

    • Search Google Scholar
    • Export Citation
  • 22.

    Cole TJFreeman JVPreece MA. Body mass index reference curves for the UK, 1990. Arch Dis Child. 1995;73(1):2529. PubMed ID: 7639544 doi:10.1136/adc.73.1.25

  • 23.

    Parikh PMochari HMosca L. Clinical utility of a fingerstick technology to identify individuals with abnormal blood lipids and high-sensitivity C-reactive protein levels. Am J Health Promot. 2009;23(4):279282. PubMed ID: 19288850 doi:10.4278/ajhp.071221140

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Ahrens WMoreno LAMarild Set al. Metabolic syndrome in young children: definitions and results of the IDEFICS study. Int J Obes. 2014;38:S4S14. doi:10.1038/ijo.2014.130

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Ragland DR. Dichotomizing continuous outcome variables: dependence of the magnitude of association and statistical power on the cutpoint. Epidemiology. 1992;3(5):434440. PubMed ID: 1391136 doi:10.1097/00001648-199209000-00009

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Zimmet PAlberti KGKaufman Fet al. The metabolic syndrome in children and adolescents—an IDF consensus report. Pediatr Diabetes. 2007;8(5):299306. PubMed ID: 17850473 doi:10.1111/j.1399-5448.2007.00271.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    National Cholesterol Education Program Expert Panel on Blood Cholesterol Levels in Children and Adolescents. National Cholesterol Education Program (NCEP): highlights of the report of the expert panel on blood cholesterol levels in children and adolescents. Pediatrics. 1992;89(3):495501.

    • Search Google Scholar
    • Export Citation
  • 28.

    Cook SWeitzman MAuinger PNguyen MDietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988–1994. Arch Pediatr Adolesc Med. 2003;157(8):821827. PubMed ID: 12912790 doi:10.1001/archpedi.157.8.821

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Harrington DMDowd KPBourke AKDonnelly AE. Cross-sectional analysis of levels and patterns of objectively measured sedentary time in adolescent females. Int J Behav Nutr Phys Act. 2011;8:120. PubMed ID: 22035260 doi:10.1186/1479-5868-8-120

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Ryan CGGrant PMTigbe WWGranat MH. The validity and reliability of a novel activity monitor as a measure of walking. Br J Sports Med. 2006;40(9):779784. PubMed ID: 16825270 doi:10.1136/bjsm.2006.027276

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Aminian SHinckson EA. Examining the validity of the ActivPAL monitor in measuring posture and ambulatory movement in children. Int J Behav Nutr Phys Act. 2012;9:119.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Winkler EABodicoat DHHealy GNet al. Identifying adults’ valid waking wear time by automated estimation in activPAL data collected with a 24 h wear protocol. Physiol Meas. 2016;37(10):16531668. PubMed ID: 27652827 doi:10.1088/0967-3334/37/10/1653

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Altenburg TMChinapaw MJ. Bouts and breaks in children’s sedentary time: currently used operational definitions and recommendations for future research. Prev Med. 2015;77:13. PubMed ID: 25937587 doi:10.1016/j.ypmed.2015.04.019

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Department of Health. Start Active, Stay Active: a report on physical activity for health from the four home countries’ Chief Medical Officers. 2011. www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/documents/digitalasset/dh_128210.pdf. Accessed 14 July 2011.

    • Export Citation
  • 35.

    Rocha NPMilagres LCLongo GZRibeiro AQNovaes JF. Association between dietary pattern and cardiometabolic risk in children and adolescents: a systematic review. J Pediatr. 2017;93(3):214222. doi:10.1016/j.jped.2017.01.002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36.

    Rauber FCampagnolo PDBHoffman DJVitolo MR. Consumption of ultra-processed food products and its effects on children’s lipid profiles: a longitudinal study. Nutr Metab Cardiovasc Dis. 2015;25(1):116122. PubMed ID: 25240690 doi:10.1016/j.numecd.2014.08.001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Mann KDHowe LDBasterfield Let al. Longitudinal study of the associations between change in sedentary behavior and change in adiposity during childhood and adolescence: gateshead Millennium study. Int J Obes. 2017;41(7):10421047. doi:10.1038/ijo.2017.69

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 38.

    Chastin SFGranat MH. Methods for objective measure, quantification and analysis of sedentary behaviour and inactivity. Gait Posture. 2009;31:8286. PubMed ID: 19854651 doi:10.1016/j.gaitpost.2009.09.002

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
Article Metrics
All Time Past Year Past 30 Days
Abstract Views 68 68 68
Full Text Views 6 6 6
PDF Downloads 3 3 3
Altmetric Badge
PubMed
Google Scholar