Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Does body mass index modify the association between physical activity and screen time with cardiometabolic risk factors in adolescents? Findings from a country-wide survey



Moderate and vigorous physical activity (MVPA) and screen time (ST) have been associated with cardiometabolic health in youth. However, previous studies are conflicting whether these associations are independent of each other and it is unknown if they are modified by adiposity. We aimed to examine the independent and joint associations between MVPA and ST with cardiometabolic risk across body mass index (BMI) categories.


A total of 36 956 Brazilian adolescents (12–17 years) from the Study of Cardiovascular Risks in Adolescents were included. Information on time spent in MVPA and ST were assessed by self-reports. Blood pressure, Homeostasis Model Assessment of Insulin Resistance, triglycerides, high-density lipoprotein-cholesterol and waist circumference were used to calculate a cardiometabolic risk score (sex-age-specific top-risk quintile for each biomarker). Ordered logistic regression was used to examine the associations.


In final adjusted models, both higher MVPA (proportional odds ratio (POR)=0.80; 95% confidence interval (CI): 0.67–0.95) and ST (POR=1.23; 95% CI: 1.10–1.37) were independently associated with cardiometabolic risk. After stratification by normal weight vs overweight/obese, the inverse independent association for MVPA remained unchanged, whereas ST was positively associated with cardiometabolic risk only in overweight/obese adolescents (POR=1.62; 95% CI: 1.18–2.22). Participants who met the recommendations for both MVPA and ST had lower odds for cardiometabolic risk, especially if they were overweight/obese (POR=0.46; 95% CI: 0.31–0.68).


MVPA and ST are independently associated with cardiometabolic risk; the association with ST, however, appears modified by BMI. Normal-weight adolescents should be encouraged to increase MVPA, whereas a combination of increasing MVPA and decreasing ST is recommended in those who are overweight or obese.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others


  1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384: 766–781.

    Article  Google Scholar 

  2. May AL, Kuklina EV, Yoon PW . Prevalence of cardiovascular disease risk factors among US adolescents, 1999-2008. Pediatrics 2012; 129: 1035–1041.

    Article  Google Scholar 

  3. Lim S, Jang HC, Park KS, Cho SI, Lee MG, Joung H et al. Changes in metabolic syndrome in American and Korean youth, 1997–2008. Pediatrics 2013; 131: e214–e222.

    Article  Google Scholar 

  4. Roth GA, Nguyen G, Forouzanfar MH, Mokdad AH, Naghavi M, Murray CJ . Estimates of global and regional premature cardiovascular mortality in 2025. Circulation 2015; 132: 1270–1282.

    Article  Google Scholar 

  5. Palve KS, Pahkala K, Magnussen CG, Koivistoinen T, Juonala M, Kahonen M et al. Association of physical activity in childhood and early adulthood with carotid artery elasticity 21 years later: the cardiovascular risk in Young Finns Study. J Am Heart Assoc 2014; 3: e000594.

    Article  Google Scholar 

  6. Ekelund U, Luan J, Sherar LB, Esliger DW, Griew P, Cooper A . 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 

  7. Chaput JP, Saunders TJ, Mathieu ME, Henderson M, Tremblay MS, O'Loughlin J et al. Combined associations between moderate to vigorous physical activity and sedentary behaviour with cardiometabolic risk factors in children. Appl Physiol Nutr Metab 2013; 38: 477–483.

    Article  CAS  Google Scholar 

  8. Ekelund U, Brage S, Froberg K, Harro M, Anderssen SA, Sardinha LB et al. TV viewing and physical activity are independently associated with metabolic risk in children: the European Youth Heart Study. PLoS Med 2006; 3: e488.

    Article  Google Scholar 

  9. Ullrich-French SC, Power TG, Daratha KB, Bindler RC, Steele MM . Examination of adolescents' screen time and physical fitness as independent correlates of weight status and blood pressure. J Sports Sci 2010; 28: 1189–1196.

    Article  Google Scholar 

  10. Young DR, Hivert M-F, Alhassan S, Camhi SM, Ferguson JF, Katzmarzyk PT et al. Sedentary behavior and cardiovascular morbidity and mortality. Circulation 2016; 134: e262–e279.

    Article  Google Scholar 

  11. Chomistek AK, Manson JE, Stefanick ML, Lu B, Sands-Lincoln M, Going SB et al. Relationship of sedentary behavior and physical activity to incident cardiovascular disease: results from the Women's Health Initiative. J Am Coll Cardiol 2013; 61: 2346–2354.

    Article  Google Scholar 

  12. World Health Organization Global Recommendations on Physical Activity for Health. World Health Organization: Geneva, Switzerland, 2010.

  13. American Academy of Pediatrics.. Children, adolescents, and the media. Pediatrics 2013; 132: 958–961.

    Article  Google Scholar 

  14. Laurson KR, Eisenmann JC, Welk GJ, Wickel EE, Gentile DA, Walsh DA . Combined influence of physical activity and screen time recommendations on childhood overweight. J Pediatr 2008; 153: 209–214.

    Article  Google Scholar 

  15. Eisenmann JC, Bartee RT, Smith DT, Welk GJ, Fu Q . Combined influence of physical activity and television viewing on the risk of overweight in US youth. Int J Obes (Lond) 2008; 32: 613–618.

    Article  CAS  Google Scholar 

  16. Bai Y, Chen S, Laurson KR, Kim Y, Saint-Maurice PF, Welk GJ . The associations of youth physical activity and screen time with fatness and fitness: The 2012 NHANES National Youth Fitness Survey. PLoS One 2016; 11: e0148038.

    Article  Google Scholar 

  17. Rendo-Urteaga T, de Moraes AC, Collese TS, Manios Y, Hagstromer M, Sjostrom M et al. The combined effect of physical activity and sedentary behaviors on a clustered cardio-metabolic risk score: The Helena Study. Int J Cardiol 2015; 186: 186–195.

    Article  Google Scholar 

  18. Heshmat R, Qorbani M, Shahr Babaki AE, Djalalinia S, Ataei-Jafari A, Motlagh ME et al. Joint association of screen time and physical activity with cardiometabolic risk factors in a national sample of Iranian adolescents: The CASPIANIII Study. PLoS One 2016; 11: e0154502.

    Article  Google Scholar 

  19. Tarp J, Brønd JC, Andersen LB, Møller NC, Froberg K, Grøntved A . Physical activity, sedentary behavior, and long-term cardiovascular risk in young people: A review and discussion of methodology in prospective studies. J Sport Health Sci 2016; 5: 145–150.

    Article  Google Scholar 

  20. 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 

  21. The InterAct Consortium. Physical activity reduces the risk of incident type 2 diabetes in general and in abdominally lean and obese men and women: the EPIC–InterAct Study. Diabetologia 2012; 55: 1944–1952.

    Article  Google Scholar 

  22. Bloch KV, Szklo M, Kuschnir MC, Abreu Gde A, Barufaldi LA, Klein CH et al. The Study of Cardiovascular Risk in Adolescents—ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents. BMC Public Health 2015; 15: 94.

    Article  Google Scholar 

  23. Vasconcellos MT, Silva PL, Szklo M, Kuschnir MC, Klein CH, Abreu Gde A et al. Sampling design for the Study of Cardiovascular Risks in Adolescents (ERICA). Cad Saude Publica 2015; 31: 921–930.

    Article  Google Scholar 

  24. Silva TL, Klein CH, Souza Ade M, Barufaldi LA, Abreu Gde A, Kuschnir MC et al. Response rate in the Study of Cardiovascular Risks in Adolescents - ERICA. Rev Saude Publica 2016; 50 (Suppl 1): 1s–13s.

    Article  Google Scholar 

  25. Sallis JF, Strikmiller PK, Harsha DW, Feldman HA, Ehlinger S, Stone EJ et al. Validation of interviewer- and self-administered physical activity checklists for fifth grade students. Med Sci Sports Exerc 1996; 28: 840–851.

    Article  CAS  Google Scholar 

  26. de Farias Jr JC, Lopes Ada S, Mota J, Santos MP, Ribeiro JC, Hallal PC . Validity and reproducibility of a physical activity questionnaire for adolescents: adapting the Self-Administered Physical Activity Checklist. Rev Bras Epidemiol 2012; 15: 198–210.

    Article  Google Scholar 

  27. Cureau FV, da Silva TL, Bloch KV, Fujimori E, Belfort DR, de Carvalho KM et al. ERICA: leisure-time physical inactivity in Brazilian adolescents. Rev Saude Publica 2016; 50 (Suppl 1): 4s.

    Article  Google Scholar 

  28. Stergiou GS, Yiannes NG, Rarra VC . Validation of the Omron 705 IT oscillometric device for home blood pressure measurement in children and adolescents: the Arsakion School Study. Blood Press Monit 2006; 11: 229–234.

    Article  Google Scholar 

  29. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J . Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 2007; 85: 660–667.

    Article  Google Scholar 

  30. Associação Brasileira de Empresas de Pesquisa (ABEP). Critério de classificação econômica Brasil, 2013. Available at: (last accessed 14 September 2015).

  31. Warren CW, Jones NR, Peruga A, Chauvin J, Baptiste JP, Costa de Silva V et al. Global youth tobacco surveillance, 2000–2007. MMWR Surveill Summ 2008; 57: 1–28.

    PubMed  Google Scholar 

  32. Williams R . Generalized ordered logit/partial proportional odds models for ordinal dependent variables. Stata J 2006; 6: 58–82.

    Article  Google Scholar 

  33. Fullerton AS . A conceptual framework for ordered logistic regression models. Sociol Method Res 2009; 38: 306–347.

    Article  Google Scholar 

  34. Szklo M, Javier Nieto F . Epidemiology Beyond the Basics, 2nd edn. Jones & Bartlett Publishers: Burlington, MA, USA, 2007.

    Google Scholar 

  35. Wennberg P, Gustafsson PE, Howard B, Wennberg M, Hammarstrom A . Television viewing over the life course and the metabolic syndrome in mid-adulthood: a longitudinal population-based study. J Epidemiol Community Health 2014; 68: 928–933.

    Article  Google Scholar 

  36. Zhang G, Wu L, Zhou L, Lu W, Mao C . Television watching and risk of childhood obesity: a meta-analysis. Eur J Public Health 2015; 26: 13–18.

    Article  CAS  Google Scholar 

  37. Andersen LB, Harro M, Sardinha LB, Froberg K, Ekelund U, Brage S et al. Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study). Lancet 2006; 368: 299–304.

    Article  Google Scholar 

  38. Lipsky LM, Iannotti RJ . Associations of television viewing with eating behaviors in the 2009 Health Behaviour in School-aged Children Study. Arch Pediatr Adolesc Med 2012; 166: 465–472.

    Article  Google Scholar 

  39. Thosar SS, Bielko SL, Mather KJ, Johnston JD, Wallace JP . Effect of prolonged sitting and breaks in sitting time on endothelial function. Med Sci Sports Exerc 2015; 47: 843–849.

    Article  Google Scholar 

  40. Cleland VJ, Schmidt MD, Dwyer T, Venn AJ . Television viewing and abdominal obesity in young adults: is the association mediated by food and beverage consumption during viewing time or reduced leisure-time physical activity? Am J Clin Nutr 2008; 87: 1148–1155.

    Article  CAS  Google Scholar 

  41. de Moraes AC, Carvalho HB, Rey-Lopez JP, Gracia-Marco L, Beghin L, Kafatos A et al. Independent and combined effects of physical activity and sedentary behavior on blood pressure in adolescents: gender differences in two cross-sectional studies. PLoS One 2013; 8: e62006.

    Article  Google Scholar 

Download references


ERICA project was supported by Funding Authority for Studies and Projects (FINEP) (grant: 01090421); Brazilian National Counsel of Technological and Scientific Development (CNPq) (grants: 565037/2010-2, 405009/2012-7 and 457050/2013-6). FVC is supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) with sandwich PhD scholarship (process: BEX 9556/14-1). KVB (process: 304595/2012-8) and BS (process: 305116/2012-6) were partially supported by CNPq. UE was partly funded by the UK Medical Research Council Grant MC_UU_2015/3 and by the Norwegian Research Council (249932/F20).

Author information

Authors and Affiliations


Corresponding author

Correspondence to F V Cureau.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on International Journal of Obesity website

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cureau, F., Ekelund, U., Bloch, K. et al. Does body mass index modify the association between physical activity and screen time with cardiometabolic risk factors in adolescents? Findings from a country-wide survey. Int J Obes 41, 551–559 (2017).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links