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Modeling the dynamics of BMI changes during adolescence. The Oporto Growth, Health and Performance Study

Abstract

Objectives:

The aims of this study were twofold: (i) to model changes in body mass index (BMI) of 10–18-year-old adolescents, and (ii) to investigate the effects of total physical activity (TPA), physical fitness (PF), sleep duration and fruit/vegetable consumption in BMI trajectories across time.

Methods:

Data were obtained from the Oporto Growth, Health and Performance Study and comprised 6894 adolescents (3418 girls) divided into four age cohorts (10, 12, 14 and 16 years) measured annually for 3 years. BMI was computed using the standard formula (kg m−2); TPA was estimated with the Baecke questionnaire; PF measures included 1-mile run/walk, 50 yard dash (50YD), standing long jump (SLJ), handgrip strength (HGr) and agility shuttle run. Longitudinal changes in BMI were analyzed using the multilevel modeling approach.

Results:

The average BMI at age of peak of height velocity was 20.7±0.07 kg m−2 for girls (P<0.001) and 20.58±0.06 kg m−2 for boys (P<0.001). The annual increment in BMI was 1.36±0.04 kg m−2, P<0.001 and 1.23±0.03 kg m−2, P<0.001 for girls and boys, respectively. PF were related to BMI trajectories in both sexes (Girls: β1mile=0.12±0.02, P<0.001; βSLJ=-0.01±0.00, P<0.001; β50YD=0.28±0.05, P<0.001; βHGr=−8.91±0.54, P<0.001; Boys: β1mile=0.18±0.02, P<0.001; βSLJ=−0.01±0.00, P<0.001; β50YD=0.26±0.04, P<0.001; and βHGr=-8.15±0.45, P<0.001). TPA only showed significant, but positive, association with girls’ BMI trajectories (β=0.10±0.03, P=0.001). After adjusting for the covariates, sleep duration and fruit/vegetable intake did not show any significant association with BMI trajectories either sex.

Conclusions:

BMI increased linearly with age in both gender. PF levels are negatively associated with BMI across time in both boys and girls. Therefore, promotion of PF in the adolescent years seems to be effective in the early prevention of obesity.

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References

  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. Spruijt MR . Etiology, treatment and prevention of obesity in childhood and adolescence: a decade in review. J Res Adolesc 2011; 21: 129–152.

    Article  Google Scholar 

  3. Marques A, Gaspar De Matos M . Trends and correlates of overweight and obesity among adolescents from 2002 to 2010: A three-cohort study based on a representative sample of Portuguese adolescents. Am J Hum Biol 2014; 26: 844–849.

    Article  Google Scholar 

  4. Sardinha LB, Santos R, Vale S, Silva AM, Ferreira JP, Raimundo AM et al. Prevalence of overweight and obesity among Portuguese youth: a study in a representative sample of 10-18-year-old children and adolescents. Int J Pediatr Obes 2011; 6: e124–e128.

    Article  Google Scholar 

  5. Janssen I, Katzmarzyk PT, Boyce WF, Vereecken C, Mulvihill C, Roberts C et al. Comparison of overweight and obesity prevalence in school-aged youth from 34 countries and their relationships with physical activity and dietary patterns. Obes Rev 2005; 6: 123–132.

    Article  CAS  Google Scholar 

  6. Dietz WH . Critical periods in childhood for the development of obesity. Am J Clin Nutr 1994; 59: 955–959.

    Article  CAS  Google Scholar 

  7. Singh AS, Mulder C, Twisk JW, van Mechelen W, Chinapaw MJ . Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev 2008; 9: 474–488.

    Article  CAS  Google Scholar 

  8. Chaput JP, Perusse L, Despres JP, Tremblay A, Bouchard C . Findings from the Quebec Family Study on the etiology of obesity: genetics and environmental highlights. Curr Obes Rep 2014; 3: 54–66.

    Article  Google Scholar 

  9. Kimm SY, Glynn NW, Obarzanek E, Kriska AM, Daniels SR, Barton BA et al. Relation between the changes in physical activity and body-mass index during adolescence: a multicentre longitudinal study. Lancet 2005; 366: 301–307.

    Article  Google Scholar 

  10. Must A, Bandini LG, Tybor DJ, Phillips SM, Naumova EN, Dietz WH . Activity, inactivity, and screen time in relation to weight and fatness over adolescence in girls. Obesity (Silver Spring) 2007; 15: 1774–1781.

    Article  Google Scholar 

  11. Elgar FJ, Roberts C, Moore L, Tudor-Smith C . Sedentary behaviour, physical activity and weight problems in adolescents in Wales. Public Health 2005; 119: 518–524.

    Article  CAS  Google Scholar 

  12. Kemper HC, Post GB, Twisk JW, van Mechelen W . Lifestyle and obesity in adolescence and young adulthood: results from the Amsterdam Growth And Health Longitudinal Study (AGAHLS). Int J Obes Relat Metab Disord 1999; 23: S34–S40.

    Article  Google Scholar 

  13. Malina RM . Top 10 research questions related to growth and maturation of relevance to physical activity, performance, and fitness. Res Q Exerc Sport 2014; 85: 157–173.

    Article  Google Scholar 

  14. Gulias-Gonzáles R, Martinez-Vizcaíno V, García-Pietro J, Díez-Fernandez A, Olivas-Bravo A, Sánchez-Lopez M . Excess of weight, but not underweight, is associated with poor physical fitness in children and adolescents from Castilla-La Mancha, Spain. Eur J Pediatr 2014; 173: 727–735.

    Article  Google Scholar 

  15. Huang YC, Malina RM . Body mass index and individual physical fitness tests in Taiwanese youth aged 9-18 years. Int J Pediatr Obes 2010; 5: 404–411.

    Article  Google Scholar 

  16. Deforche B, Lefevre J, De Bourdeaudhuij I, Hills AP, Duquet W, Bouckaert J . Physical fitness and physical activity in obese and nonobese Flemish youth. Obes Res 2003; 11: 434–441.

    Article  Google Scholar 

  17. Kim J, Must A, Fitzmaurice GM, Gillman MW, Chomitz V, Kramer E et al. Relationship of physical fitness to prevalence and incidence of overweight among schoolchildren. Obes Res 2005; 13: 1246–1254.

    Article  Google Scholar 

  18. Mitchell JA, Rodriguez D, Schmitz KH, Audrain-McGovern J . Sleep duration and adolescent obesity. Pediatrics 2013; 131: e1428–e1434.

    Article  Google Scholar 

  19. Ham E, Kim HJ . Evaluation of fruit intake and its relation to body mass index of adolescents. Clin Nutr Res 2014; 3: 126–133.

    Article  Google Scholar 

  20. Lohman TG, Roche AF, Martorell R . Antropometric standardization reference manual: Champaign 1988.

  21. Mirwald RL, Baxter-Jones AD, Bailey DA, Beunen GP . An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc 2002; 34: 689–694.

    Google Scholar 

  22. Fitnessgram. The Prudencial Fitnessgram Test Administration Manual. Dallas, Texas U.S.A: he Cooper Institute for Aerobics Research 1994.

  23. (AAHPER) AAfHPEaR. Youth Fitness Test Manual. Washington, DC: AAHPER 1976.

  24. Malina R, Bouchard C, Bar-Or C . Growth, Maturation and Physical Activity 2º EditionChampaign, Illinois: Champaign, Illinois: Human Kinetics, 2004.

    Google Scholar 

  25. Baecke J, Burema J, Frijters J . A short questionnaire for the measurenment of habitual physical activity in epidemiological studies. Am J Clin Nutr 1982; 36: 936–942.

    Article  CAS  Google Scholar 

  26. Miller DJ, Freedson PS, Kline GM . Comparison of activity levels using the Caltrac accelerometer and five questionnaires. Med Sci Sports Exerc 1994; 26: 376–382.

    CAS  PubMed  Google Scholar 

  27. Philippaerts RM, Westerterp KR, Lefevre J . Doubly labelled water validation of three physical activity questionnaires. Int J Sports Med 1999; 20: 284–289.

    Article  CAS  Google Scholar 

  28. Katzmarzyk PT, Barreira TV, Broyles ST, Champagne CM, Chaput JP, Fogelholm M et al. The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): design and methods. BMC Public Health 2013; 13: 900.

    Article  Google Scholar 

  29. Currie C, Zanotti C, Morgan A, Currie D, Looze M, Roberts C et al. Social determinants of health and well-being among young people Health Behaviour in School-Aged Children (HBSC) study: international report from the 2009/2010 survey Health Police for Children and Adolescents, 2012. Copenhagen: WHO Regional Office for Europe: Copenhagen.

  30. Bryk A, Raudenbush S . Application of hierarchical linear models to assessing change. Psychol Bull 1987; 101: 147–158.

    Article  Google Scholar 

  31. Raudenbush S, Bryk A, Cheong Y, Congdon R, du Toit M . HLM 7. Hierarchical Linear & Nonlinear Modeling 2011. SSI, Scientific Software International: Lincolnwood, IL.

    Google Scholar 

  32. Raudenbush S . Hierarchical linear models to study the effects of social context on development. Gottman J. The Analysis of Change. Lawrence Erlbaum Associates, Publishers: Mahwah, New Jersey, 1995; 165–202.

    Google Scholar 

  33. Hedeker D, Gibbons R . Longitudinal Data Analysis. New Jersey: Wiley-Interscience, 2006.

    Google Scholar 

  34. Hox J . Multilevel Analysis: Technics and Applications. East Sussex: Routledge, 2010.

    Book  Google Scholar 

  35. Kuczmarski R, Ogden C, Grummer-Strawn L, Flegal K, Guo S, Wei R et al. CDC growth charts: United States: Adv Data 2000.

  36. 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 

  37. Chaves R, Baxter-Jones A, Souza M, Santos D, Maia J . Height, weight, body composition, and waist circumference references for 7-17 year old children from rural Portugal. J Comp Hum Biol 2015 doi:10.1016/j.jchb.2014.03.007.

    Article  CAS  Google Scholar 

  38. Heroux M, Onywera V, Tremblay MS, Adamo KB, Lopez Taylor J, Jauregui Ulloa E et al. The relation between aerobic fitness, muscular fitness, and obesity in children from three countries at different stages of the physical activity transition. ISRN Obes 2013; 2013: 134835.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Elliott SA, Davidson ZE, Davies PS, Truby H . Accuracy of parent-reported energy intake and physical activity levels in boys with Duchenne muscular dystrophy. Nutr Clin Pract 2014; 30: 297–304.

    Article  Google Scholar 

  40. Dyremyhr AE, Diaz E, Meland E . How adolescent subjective health and satisfaction with weight and body shape are related to participation in sports. J Environ Public Health 2014; 2014: 851932.

    Article  Google Scholar 

  41. Rizzo NS, Ruiz JR, Hurtig-Wennlof A, Ortega FB, Sjostrom M . Relationship of physical activity, fitness, and fatness with clustered metabolic risk in children and adolescents: the European youth heart study. J Pediatr 2007; 150: 388–394.

    Article  Google Scholar 

  42. Ruiz JR, Rizzo NS, Hurtig-Wennlof A, Ortega FB, Warnberg J, Sjostrom M . Relations of total physical activity and intensity to fitness and fatness in children: the European Youth Heart Study. Am J Clin Nutr 2006; 84: 299–303.

    Article  CAS  Google Scholar 

  43. Calamaro CJ, Park S, Mason TB, Marcus CL, Weaver TE, Pack A et al. Shortened sleep duration does not predict obesity in adolescents. J Sleep Res 2010; 19: 559–566.

    Article  Google Scholar 

  44. Golley RK, Maher CA, Matricciani L, Olds TS . Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI in children and adolescents. Int J Obes (Lond) 2013; 37: 546–551.

    Article  CAS  Google Scholar 

  45. Olds TS, Maher CA, Matricciani L . Sleep duration or bedtime? Exploring the relationship between sleep habits and weight status and activity patterns. Sleep 2011; 34: 1299–1307.

    Article  Google Scholar 

  46. te Velde SJ, Twisk JW, Brug J . Tracking of fruit and vegetable consumption from adolescence into adulthood and its longitudinal association with overweight. Br J Nutr 2007; 98: 431–438.

    Article  CAS  Google Scholar 

  47. Field AE, Gillman MW, Rosner B, Rockett HR, Colditz GA . Association between fruit and vegetable intake and change in body mass index among a large sample of children and adolescents in the United States. Int J Obes Relat Metab Disord 2003; 27: 821–826.

    Article  CAS  Google Scholar 

  48. Ferreira J, Marques A, Maia J . Physical fitness, physical activity and health in young population from Viseu- A study in children and youngsters of both gender from 10 to 18 years old, 2002. Viseu: Departamento Cultural - Instituto Superior Politécnico de Viseu: Viseu.

  49. Vasconcelos M, Maia J . Is there a decline in physical activity? A cross-sectional study in children and youngsters of both gender from 10 to 19 years old. Portuguese Journal Sports Science 2001; 1: 44–52.

    Google Scholar 

  50. Malina RM, Katzmarzyk PT . Validity of the body mass index as an indicator of the risk and presence of overweight in adolescents. Am J Clin Nutr 1999; 70 (1 Part 2): 131S–136S.

    Article  CAS  Google Scholar 

  51. Duncan S, Duncan T . Accelerated longitudinal designs. Laursen B, Litlle T, Card N. Handbook of Developmental Research Methods. New York: The Guilford Press: New York, 2012.

    Google Scholar 

  52. Yun J . Statistical issues on studies of mixed longitudinal designs. PhD dissertation. University of Texas: School of Public Health 2011.

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Correspondence to M C de Souza.

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MS collected the data, undertook the data analysis and interpretation, and led the writing of the article. JE supervised data management and contributed to drafting the paper. DS and RC collected the data and contributed to drafting the paper. CF and JM organized and supervised data collection and management, and contributed to drafting the paper. All authors read and approved the final manuscript.

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de Souza, M., Eisenmann, J., e Santos, D. et al. Modeling the dynamics of BMI changes during adolescence. The Oporto Growth, Health and Performance Study. Int J Obes 39, 1063–1069 (2015). https://doi.org/10.1038/ijo.2015.60

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