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Does adiposity mediate the relationship between physical activity and biological risk factors in youth?: a cross-sectional study from the International Children’s Accelerometry Database (ICAD)

International Journal of Obesity volume 42, pages 671–678 (2018)Cite this article

Subjects

Abstract

Background/Objectives:

To model the association between accumulating 60 daily minutes of moderate-to-vigorous physical activity and a composite score of biological risk factors into a direct and an indirect effect, using abdominal obesity as the mediator.

Subjects/Methods:

Cross-sectional data from the International Children’s Accelerometry Database (ICAD) including 6–18-year-old children and adolescents (N=3412) from 4 countries providing at least 3 days of accelerometry-assessed physical activity. A standardized composite risk score was calculated from systolic blood pressure and fasting blood samples of insulin, glucose, triacylglycerol and inverse HDL-cholesterol. Abdominal obesity was assessed by the waist-circumference:height ratio. Two-stage regression analysis, allowing for exposure–mediator interaction, was used for the effect decomposition.

Results:

Participants achieving 60 daily minutes of moderate-to-vigorous physical activity had a 0.31 (95% CI: −0.39, −0.23) standard deviations lower composite risk score than those achieving less than 60 min. Modelling the associations suggested that 0.24 standard deviations (95% CI: −0.32, −0.16) was attributed to the direct effect and −0.07 (95% CI: −0.11, −0.02) to the indirect effect indicating that 22% of the total effect was mediated by central adiposity. Modelling 30 and 90 min of moderate-to-vigorous physical activity per day resulted in changes in the direct but not the indirect effect.

Conclusions:

One hour of daily moderate-to-vigorous physical activity was associated with clinically relevant differences in metabolic control compared to engagement in less than this minimally recommended amount. The majority of the difference was explained by the direct effect of physical activity.

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References

  1. Arem H, Moore SC, Patel A, Hartge P, Berrington de Gonzalez A, Visvanathan K et al. Leisure time physical activity and mortality: a detailed pooled analysis of the dose-response relationship. JAMA Intern Med 2015; 175: 959–967.

    Article  Google Scholar 

  2. Kyu HH, Bachman VF, Alexander LT, Mumford JE, Afshin A, Estep K et al. Physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events: systematic review and dose-response meta-analysis for the Global Burden of Disease Study 2013. Bmj 2016; 354: i3857.

    Article  Google Scholar 

  3. Friedemann C, Heneghan C, Mahtani K, Thompson M, Perera R, Ward AM . Cardiovascular disease risk in healthy children and its association with body mass index: systematic review and meta-analysis. Bmj 2012; 345: e4759.

    Article  Google Scholar 

  4. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120: 1640–1645.

    Article  CAS  Google Scholar 

  5. Magnussen CG, Koskinen J, Chen W, Thomson R, Schmidt MD, Srinivasan SR et al. Pediatric metabolic syndrome predicts adulthood metabolic syndrome, subclinical atherosclerosis, and type 2 diabetes mellitus but is no better than body mass index alone: the Bogalusa Heart Study and the Cardiovascular Risk in Young Finns Study. Circulation 2010; 122: 1604–1611.

    Article  Google Scholar 

  6. Berenson GS, Srinivasan SR, Bao W, Newman WP 3rd, Tracy RE, Wattigney WA . Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl j med 1998; 338: 1650–1656.

    Article  CAS  Google Scholar 

  7. Global Burden of Metabolic Risk Factors for Chronic Diseases C, Lu Y, Hajifathalian K, Ezzati M, Woodward M, Rimm EB et al. Metabolic mediators of the effects of body-mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet 2014; 383: 970–983.

    Article  Google Scholar 

  8. Pescatello LS, Kulikowich JM . The aftereffects of dynamic exercise on ambulatory blood pressure. Med sci sports exerc 2001; 33: 1855–1861.

    Article  CAS  Google Scholar 

  9. Benatti FB, Ried-Larsen M . The effects of breaking up prolonged sitting time: a review of experimental studies. Med sci sports exerc 2015; 47: 2053–2061.

    Article  Google Scholar 

  10. Stamatakis E, Coombs N, Tiling K, Mattocks C, Cooper A, Hardy LL et al. Sedentary time in late childhood and cardiometabolic risk in adolescence. Pediatrics 2015; 135: e1432–e1441.

    Article  Google Scholar 

  11. Marques A, Minderico C, Martins S, Palmeira A, Ekelund U, Sardinha LB . Cross-sectional and prospective associations between moderate to vigorous physical activity and sedentary time with adiposity in children. Int J Obes (Lond) 2016; 40: 28–33.

    Article  CAS  Google Scholar 

  12. Collings PJ, Wijndaele K, Corder K, Westgate K, Ridgway CL, Sharp SJ et al. Objectively measured physical activity and longitudinal changes in adolescent body fatness: an observational cohort study. Pediatr Obes 2016; 11: 107–114.

    Article  CAS  Google Scholar 

  13. Wilks DC, Sharp SJ, Ekelund U, Thompson SG, Mander AP, Turner RM et al. Objectively measured physical activity and fat mass in children: a bias-adjusted meta-analysis of prospective studies. PloS one 2011; 6: e17205.

    Article  CAS  Google Scholar 

  14. Brage S, Wedderkopp N, Ekelund U, Franks PW, Wareham NJ, Andersen LB et al. Features of the metabolic syndrome are associated with objectively measured physical activity and fitness in Danish children: the European Youth Heart Study (EYHS). Diabetes care 2004; 27: 2141–2148.

    Article  Google Scholar 

  15. Rizzo NS, Ruiz JR, Oja L, Veidebaum T, Sjostrom M . Associations between physical activity, body fat, and insulin resistance (homeostasis model assessment) in adolescents: the European Youth Heart Study. Am J Clin Nutr 2008; 87: 586–592.

    Article  CAS  Google Scholar 

  16. Ekelund U, Luan J, Sherar LB, Esliger DW, Griew P, Cooper A et al. Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents. JAMA 2012; 307: 704–712.

    Article  CAS  Google Scholar 

  17. Steele RM, Brage S, Corder K, Wareham NJ, Ekelund U . Physical activity, cardiorespiratory fitness, and the metabolic syndrome in youth. J appl physiol 2008; 105: 342–351.

    Article  Google Scholar 

  18. Sherar LB, Griew P, Esliger DW, Cooper AR, Ekelund U, Judge K et al. International children's accelerometry database (ICAD): design and methods. BMC publ health 2011; 11: 485.

    Article  Google Scholar 

  19. Eiberg S, Hasselstrom H, Gronfeldt V, Froberg K, Svensson J, Andersen LB . Maximum oxygen uptake and objectively measured physical activity in Danish children 6–7 years of age: the Copenhagen school child intervention study. Br j sports med 2005; 39: 725–730.

    Article  CAS  Google Scholar 

  20. Riddoch C, Edwards D, Page A, Froberg K, Anderssen SA, Wedderkopp N et al. The European Youth Heart Study—cardiovascular disease risk factors in children: rationale, aims, study design, and validation of methods. J phys act health 2005; 2: 115–129.

    Article  Google Scholar 

  21. Mark AE, Janssen I . Influence of bouts of physical activity on overweight in youth. Am J Prev Med 2009; 36: 416–421.

    Article  Google Scholar 

  22. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA . Comparison of accelerometer cut points for predicting activity intensity in youth. Med sci sports exerc 2011; 43: 1360–1368.

    Article  Google Scholar 

  23. Patry-Parisien J, Shields M, Bryan S . Comparison of waist circumference using the World Health Organization and National Institutes of Health protocols. Health Rep 2012; 23: 53–60.

    PubMed  Google Scholar 

  24. VanderWeele TJ . Explanation in Causal Inference: Methods for Mediation and Interaction. Oxford University Press, 2015.

    Google Scholar 

  25. Liu SH, Ulbricht CM, Chrysanthopoulou SA, Lapane KL . Implementation and reporting of causal mediation analysis in 2015: a systematic review in epidemiological studies. BMC Res Notes 2016; 9: 354.

    Article  Google Scholar 

  26. Robins JM, Greenland S . Identifiability and exchangeability for direct and indirect effects. Epidemiology 1992; 3: 143–155.

    Article  CAS  Google Scholar 

  27. Pearl J . Direct and Indirect effects. Proceedings of the seventeenth conference on uncertainty in artificial intelligence. Morgan Kaufmann: San Francisco, 2001.

    Google Scholar 

  28. VanderWeele TJ . A three-way decomposition of a total effect into direct, indirect, and interactive effects. Epidemiology 2013; 24: 224–232.

    Article  Google Scholar 

  29. Cole TJ . Sympercents: symmetric percentage differences on the 100log(e) scale simplify the presentation of log transformed data. Stat Med 2000; 19: 3109–3125.

    Article  CAS  Google Scholar 

  30. Magnussen CG, Cheriyan S, Sabin MA, Juonala M, Koskinen J, Thomson R et al. Continuous and dichotomous metabolic syndrome definitions in youth predict adult type 2 diabetes and carotid artery intima media thickness: the cardiovascular risk in Young Finns Study. J pediatr 2016; 171: 97–103 e1-3.

    Article  Google Scholar 

  31. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R, Prospective Studies C. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet 2002; 360: 1903–1913.

    Article  Google Scholar 

  32. Hayashi T, Wojtaszewski JF, Goodyear LJ . Exercise regulation of glucose transport in skeletal muscle. Am J Physiol 1997; 273 (6 Pt 1): E1039–E1051.

    CAS  PubMed  Google Scholar 

  33. Butte NF, Puyau MR, Adolph AL, Vohra FA, Zakeri I . Physical activity in nonoverweight and overweight Hispanic children and adolescents. Med sci sports exerc 2007; 39: 1257–1266.

    Article  Google Scholar 

  34. Nassis GP, Papantakou K, Skenderi K, Triandafillopoulou M, Kavouras SA, Yannakoulia M et al. Aerobic exercise training improves insulin sensitivity without changes in body weight, body fat, adiponectin, and inflammatory markers in overweight and obese girls. Metabolism 2005; 54: 1472–1479.

    Article  CAS  Google Scholar 

  35. Dela F, Larsen JJ, Mikines KJ, Ploug T, Petersen LN, Galbo H . Insulin-stimulated muscle glucose clearance in patients with NIDDM. Effects of one-legged physical training. Diabetes 1995; 44: 1010–1020.

    Article  CAS  Google Scholar 

  36. Ekelund U, Ward HA, Norat T, Luan J, May AM, Weiderpass E et al. Physical activity and all-cause mortality across levels of overall and abdominal adiposity in European men and women: the European Prospective Investigation into Cancer and Nutrition Study (EPIC). Am J Clin Nutr 2015; 101: 613–621.

    Article  CAS  Google Scholar 

  37. Horta BL, Schaan BD, Bielemann RM, Vianna CA, Gigante DP, Barros FC et al. Objectively measured physical activity and sedentary-time are associated with arterial stiffness in Brazilian young adults. Atherosclerosis 2015; 243: 148–154.

    Article  CAS  Google Scholar 

  38. Richmond RC, Davey Smith G, Ness AR, den Hoed M, McMahon G, Timpson NJ . Assessing causality in the association between child adiposity and physical activity levels: a Mendelian randomization analysis. PLoS Med 2014; 11: e1001618.

    Article  Google Scholar 

  39. VanderWeele TJ, Valeri L, Ogburn EL . The role of measurement error and misclassification in mediation analysis: mediation and measurement error. Epidemiology 2012; 23: 561–564.

    Article  Google Scholar 

  40. Lawlor DA, Benfield L, Logue J, Tilling K, Howe LD, Fraser A et al. Association between general and central adiposity in childhood, and change in these, with cardiovascular risk factors in adolescence: prospective cohort study. Bmj 2010; 341: c6224.

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank all participants and funders of the original studies that contributed data to ICAD. We also gratefully acknowledge the contribution of Professor Chris Riddoch, Professor Ken Judge, Professor Ashley Cooper and Dr Pippa Griew to the development of ICAD. The ICAD Collaborators include: Prof LB Andersen, University of Southern Denmark, Odense, Denmark (Copenhagen School Child Intervention Study (CoSCIS)); Prof S Anderssen, Norwegian School for Sport Science, Oslo, Norway (European Youth Heart Study (EYHS), Norway); Dr AJ Atkin, MRC Epidemiology Unit & Centre for Diet and Activity Research, University of Cambridge, UK; Prof G Cardon, Department of Movement and Sports Sciences, Ghent University, Belgium (Belgium Pre-School Study); Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), Hyattsville, MD USA (National Health and Nutrition Examination Survey (NHANES)); Dr R Davey, Centre for Research and Action in Public Health, University of Canberra, Australia (Children’s Health and Activity Monitoring for Schools (CHAMPS)); Prof U Ekelund, Norwegian School of Sport Sciences, Oslo, Norway & MRC Epidemiology Unit, University of Cambridge, UK; Dr DW Esliger, School of Sports, Exercise and Health Sciences, Loughborough University, UK; Dr P Hallal, Postgraduate Program in Epidemiology, Federal University of Pelotas, Brazil (1993 Pelotas Birth Cohort); Dr BH Hansen, Norwegian School of Sport Sciences, Oslo, Norway; Prof KF Janz, Department of Health and Human Physiology, Department of Epidemiology, University of Iowa, Iowa City, USA (Iowa Bone Development Study); Prof S Kriemler, Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Switzerland (Kinder-Sportstudie (KISS)); Dr N Møller, University of Southern Denmark, Odense, Denmark (European Youth Heart Study (EYHS), Denmark); Ms L Molloy, School of Social and Community Medicine, University of Bristol, UK (Avon Longitudinal Study of Parents and Children (ALSPAC)); Dr A Page, Centre for Exercise, Nutrition and Health Sciences, University of Bristol, UK (Personal and Environmental Associations with Children’s Health (PEACH)); Prof R Pate, Department of Exercise Science, University of South Carolina, Columbia, USA (Physical Activity in Pre-school Children (CHAMPS-US) and Project Trial of Activity for Adolescent Girls (Project TAAG)); Dr JJ Puder, Service of Endocrinology, Diabetes and Metabolism, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland (Ballabeina Study); Prof J Reilly, Physical Activity for Health Group, School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK (Movement and Activity Glasgow Intervention in Children (MAGIC)); Prof J Salmon, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia (Children Living in Active Neigbourhoods (CLAN)); Prof LB Sardinha, Exercise and Health Laboratory, Faculty of Human Movement, Universidade de Lisboa, Lisbon, Portugal (European Youth Heart Study (EYHS), Portugal); Dr LB Sherar, School of Sports, Exercise and Health Sciences, Loughborough University, UK; Dr A Timperio, Centre for Physical Activity and Nutrition Research, Deakin University Melbourne, Australia (Healthy Eating and Play Study (HEAPS)); Dr EMF van Sluijs, MRC Epidemiology Unit & Centre for Diet and Activity Research, University of Cambridge, UK (Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people (SPEEDY)). JT was funded by TrygFonden (Grant Number: 11683), the University of Southern Denmark, and received financial support from ‘Christian og Ottilia Brorsons Rejselegat’ while contributing to this work. The pooling of the data was funded through a grant from the National Prevention Research Initiative (Grant Number: G0701877) (http://www.mrc.ac.uk/research/initiatives/national-prevention-research-initiative-npri/). The funding partners relevant to this award are: British Heart Foundation; Cancer Research UK; Department of Health; Diabetes UK; Economic and Social Research Council; Medical Research Council; Research and Development Office for the Northern Ireland Health and Social Services; Chief Scientist Office; Scottish Executive Health Department; The Stroke Association; Welsh Assembly Government and World Cancer Research Fund. This work was additionally supported by the Medical Research Council (MC_UU_12015/3; MC_UU_12015/7), The Research Council of Norway (249932/F20), Bristol University, Loughborough University and Norwegian School of Sport Sciences. The study sponsors were not involved in the design of the study; the collection, analysis and interpretation of data; writing the report; or the decision to submit the report for publication.

Author contributions

JT conceived the study, performed the analysis, led the analysis and writing of the manuscript. AB conceived the study, analyzed the data and critically revised the manuscript. NCM conceived the study, analyzed the data, critically revised the manuscript and is an ICAD Collaborator. LBA conceived the study, analyzed the data, critically revised the manuscript and is an ICAD Collaborator. LBS analyzed the data, critically revised the manuscript and is an ICAD Collaborator. UE analyzed the data, critically revised the manuscript and is an ICAD Collaborator. SB analyzed the data and critically revised the manuscript. All authors approved the final version of the manuscript. JT is the guarantor of this work.

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Authors and Affiliations

  1. Department of Sports Science and Clinical Biomechanics, Research Unit for Exercise Epidemiology, Centre of Research in Childhood Health, University of Southern Denmark, Odense, Denmark

    J Tarp, A Bugge & N C Møller

  2. Department of Teacher Education and Sport, Western Norway University of Applied Sciences, Sogndal, Norway

    L B Andersen

  3. Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway

    L B Andersen & U Ekelund

  4. Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Cruz-Quebrada, Portugal

    L B Sardinha

  5. Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK

    U Ekelund & S Brage

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On behalf of the International Children’s Accelerometry Database (ICAD) Collaborators

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Correspondence to J Tarp.

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Tarp, J., Bugge, A., Andersen, L. et al. Does adiposity mediate the relationship between physical activity and biological risk factors in youth?: a cross-sectional study from the International Children’s Accelerometry Database (ICAD). Int J Obes 42, 671–678 (2018). https://doi.org/10.1038/ijo.2017.241

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