Canadian Journal of Public Health

, Volume 109, Issue 1, pp 61–69 | Cite as

Dieting predicts engagement in multiple risky behaviours among adolescent Canadian girls: a longitudinal analysis

  • Amanda Raffoul
  • Scott T. Leatherdale
  • Sharon I. Kirkpatrick
Quantitative Research

Abstract

Objectives

We investigated associations between dieting and other health-compromising behaviours among adolescent girls, both cross-sectionally and longitudinally. The behaviours considered included smoking, binge drinking, and breakfast-skipping, and clusters of these.

Methods

Data for 3386 adolescent Ontario girls were drawn from COMPASS, a school-based study, which collects self-reported measures of weight, dieting, and other health-related factors. Multilevel logistic regression models were used to investigate relationships between dieting at baseline and smoking, binge drinking, and breakfast-skipping, as well as clusters of these behaviours at baseline and 2 years later.

Results

Baseline dieters were at an elevated risk of smoking and binge drinking (RR = 1.8 and 1.5, respectively) by follow-up compared to non-dieters. Further, dieting was associated with combinations of these behaviours, with the highest risks for smoking/breakfast-skipping (RR = 1.64) and smoking/binge drinking (RR = 1.55). Over one in two (58%) girls reported dieting at baseline and four in five baseline dieters reported dieting 2 years later. Seven in ten girls were dieting at one or both time points. Baseline dieters were more likely to engage in a greater number of risky behaviours, regardless of what the actual behaviours were.

Conclusion

Dieting is longitudinally associated with engagement in other risky behaviours among adolescent girls. These findings suggest that dieting may be an early risk factor for engagement in other risky behaviours and highlight the need for comprehensive prevention strategies to target shared underlying drivers. In addition, attention is needed to the potential for well-meaning weight-related initiatives to promote dieting.

Keywords

Adolescence Dieting Binge drinking Smoking Breakfast Longitudinal 

Résumé

Objectifs

Nous avons étudié les associations transversales et longitudinales entre le fait de suivre un régime et d’autres comportements compromettants pour la santé chez les adolescentes. Les comportements étudiés étaient le tabagisme, l’hyperalcoolisation rapide et la pratique de sauter le petit-déjeuner, ainsi que les grappes de ces comportements.

Méthode

Les données de 3386 adolescentes ontariennes ont été extraites de COMPASS, une étude en milieu scolaire qui recense les mesures autodéclarées du poids, du suivi d’un régime et d’autres facteurs liés à la santé. Des modèles de régression logistique multiniveaux ont servi à explorer les relations entre le suivi d’un régime au départ et le tabagisme, l’hyperalcoolisation rapide, la pratique de sauter le petit-déjeuner, et les grappes de ces comportements au départ et deux ans plus tard.

Résultats

Les filles qui suivaient un régime au départ couraient un risque plus élevé de tabagisme et d’hyperalcoolisation rapide (RT = 1,8 et 1,5, respectivement) deux ans plus tard que les filles qui ne suivaient pas de régime. De plus, le suivi d’un régime était associé aux combinaisons de ces comportements, les risques les plus élevés étant le tabagisme/la pratique de sauter le petit-déjeuner (RT = 1,64) et le tabagisme/l’hyperalcoolisation rapide (RT = 1,55). Plus d’une fille sur deux (58%) a déclaré suivre un régime au départ, et quatre filles sur cinq qui suivaient un régime au départ en suivaient toujours un deux ans plus tard. Sept filles sur dix suivaient un régime au départ, au suivi ou les deux. Les filles qui suivaient un régime au départ étaient susceptibles de se livrer à un plus grand nombre de comportements à risque, tous comportements confondus.

Conclusion

Suivre un régime est longitudinalement associé aux comportements à risque chez les adolescentes. Ces constatations indiquent que suivre un régime peut être un facteur de risque précoce de se livrer à d’autres comportements à risque, d’où la nécessité d’avoir des stratégies de prévention globales pour cibler les vecteurs communs sous-jacents. En outre, il faut envisager la possibilité que des initiatives bien intentionnées liées au poids incitent à se mettre au régime.

Mots-clés

Adolescence régime alimentaire hyperalcoolisation rapide tabagisme petit-déjeuner étude longitudinale 

Notes

Acknowledgements

Dr. Jess Haines of the University of Guelph provided valuable feedback on data analysis and interpretation. Amanda Raffoul was funded by a Queen Elizabeth II Graduate Scholarship in Science and Technology. Scott Leatherdale is a Chair in Applied Public Health Research funded by the Public Health Agency of Canada (PHAC) in partnership with Canadian Institutes of Health Research (CIHR). At the time that the analyses were conducted, Sharon Kirkpatrick was funded by a Capacity Development Award from the Canadian Cancer Society Research Institute (702855). The COMPASS study was supported by a bridge grant from the CIHR Institute of Nutrition, Metabolism, and Diabetes (INMD) through the “Obesity—Interventions to Prevent or Treat” priority funding award (OOP-110788; awarded to S. Leatherdale) and an operating grant from the CIHR Institute of Population and Public Health (IPPH) (MOP-114875; awarded to S. Leatherdale).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Arbour-Nicitopoulos, K. P., Faulkner, G. E., & Leatherdale, S. T. (2010). Learning from non-reported data: interpreting missing body mass index values in young children. Measurement in Physical Education and Exercise Science, 14(4), 241–251.  https://doi.org/10.1080/1091367X.2010.520243.CrossRefGoogle Scholar
  2. Austin, S. B., & Gortmaker, S. L. (2001). Dieting and smoking initiation in early adolescent girls and boys: a prospective study. American Journal of Public Health, 91(3), 446–450.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Crow, S., Eisenberg, M. E., Story, M., & Neumark-Sztainer, D. (2006). Psychosocial and behavioral correlates of dieting among overweight and non-overweight adolescents. The Journal of Adolescent Health, 38(5), 569–574.  https://doi.org/10.1016/j.jadohealth.2005.05.019.CrossRefPubMedGoogle Scholar
  4. DeWit, D. J., Adlaf, E. M., Offord, D. R., & Ogborne, A. C. (2000). Age at first alcohol use: a risk factor for the development of alcohol disorders. The American Journal of Psychiatry, 157(5), 745–750.  https://doi.org/10.1176/appi.ajp.157.5.745.CrossRefPubMedGoogle Scholar
  5. Field, A. E., Austin, S. B., Frazier, A. L., Gillman, M. W., Camargo Jr., C. A., & Colditz, G. A. (2002). Smoking, getting drunk, and engaging in bulimic behaviors: in which order are the behaviors adopted? Journal of the American Academy of Child and Adolescent Psychiatry, 41(7), 846–853.  https://doi.org/10.1097/00004583-200207000-00018.CrossRefPubMedGoogle Scholar
  6. Findlay, S. (2004). Dieting in adolescence. Paediatrics & Child Health, 9(7), 487–491.CrossRefGoogle Scholar
  7. Giles, E. L., & Brennan, M. (2014). Between healthy food, alcohol and physical activity behaviours. BMC Public Health, 14(1), 1231.  https://doi.org/10.1186/1471-2458-14-1231. CrossRefPubMedPubMedCentralGoogle Scholar
  8. Golden, N. H., Schneider, M., & Wood, C. (2016). Preventing obesity and eating disorders in adolescents. Pediatrics, 138(3), e20161649.  https://doi.org/10.1542/peds.2016-1649.CrossRefPubMedGoogle Scholar
  9. Hale, D. R., & Viner, R. M. (2012). Policy responses to multiple risk behaviours in adolescents. Journal of Public Health (Oxford, England), 34(Suppl. 1), i11–i19.  https://doi.org/10.1093/pubmed/fdr112.CrossRefGoogle Scholar
  10. Health Canada. (2014). Youth Smoking Survey: Table 2. Smoking status, by sex and grouped grades, Canada, 2012–2013. http://healthycanadians.gc.ca/publications/healthy-living-vie-saine/youth-smoking-survey-tables-2012-2013-tableaux-enquete-jeunes-tabagisme/index-eng.php. Published 2014.
  11. Institute of Medicine. (2012). Accelerating progress in obesity prevention. Washington, D.C.: National Academies Press; . doi: https://doi.org/10.17226/13275.
  12. Johnston, L. M., Matteson, C. L., & Finegood, D. T. (2014). Systems science and obesity policy: a novel framework for analyzing and rethinking population-level planning. American Journal of Public Health, 104(7), 1270–1278.  https://doi.org/10.2105/AJPH.2014.301884.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Larson, N. I., Neumark-Sztainer, D., & Story, M. (2009). Weight control behaviors and dietary intake among adolescents and young adults: longitudinal findings from project EAT. Journal of the American Dietetic Association, 109(11), 1869–1877.  https://doi.org/10.1016/j.jada.2009.08.016.CrossRefPubMedGoogle Scholar
  14. Leatherdale, S. T. (2015). An examination of the co-occurrence of modifiable risk factors associated with chronic disease among youth in the COMPASS study. Cancer Causes & Control, 26(4), 519–528.  https://doi.org/10.1007/s10552-015-0529-0.CrossRefGoogle Scholar
  15. Leatherdale, S. T., & Rynard, V. A. (2013). Cross-sectional examination of modifiable risk factors for chronic disease among a nationally representative sample of youth: are Canadian students graduating high school with a failing grade for health? BMC Public Health, 13(1), 569.  https://doi.org/10.1186/1471-2458-13-569. CrossRefPubMedPubMedCentralGoogle Scholar
  16. Leatherdale, S. T., Brown, K. S., Carson, V., et al. (2014). The COMPASS study: a longitudinal hierarchical research platform for evaluating natural experiments related to changes in school-level programs, policies and built environment resources. BMC Public Health, 14(1), 331.  https://doi.org/10.1186/1471-2458-14-331. CrossRefPubMedPubMedCentralGoogle Scholar
  17. Liang, K. Y., & Zeger, S. L. (1986). Longitudinal data analysis using generalized linear models. Biometrika, 73(1), 13–22.  https://doi.org/10.1093/biomet/73.1.13.CrossRefGoogle Scholar
  18. Loth, K. A., Maclehose, R., Bucchianeri, M., Crow, S., & Neumark-Sztainer, D. (2014). Predictors of dieting and disordered eating behaviors from adolescence to young adulthood. The Journal of Adolescent Health, 55(5), 705–712.  https://doi.org/10.1016/j.jadohealth.2014.04.016.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Patte, K. A., & Leatherdale, S. T. (2016). A cross-sectional analysis examining the association between dieting behaviours and alcohol use among secondary school students in the COMPASS study. Journal of Public Health (Oxford, England), 1–9.  https://doi.org/10.1093/pubmed/fdw034.
  20. Penney, T. L., & Kirk, S. F. L. (2015). The health at every size paradigm and obesity: missing empirical evidence may help push the reframing obesity debate forward. American Journal of Public Health, 105(5), e38–e42.  https://doi.org/10.2105/AJPH.2015.302552. CrossRefPubMedPubMedCentralGoogle Scholar
  21. Pirkle, E. C., & Richter, L. (2006). Personality, attitudinal and behavioral risk profiles of young female binge drinkers and smokers. The Journal of Adolescent Health, 38(1), 44–54.  https://doi.org/10.1016/j.jadohealth.2004.09.012.CrossRefPubMedGoogle Scholar
  22. Polivy, J., & Herman, C. P. (1985). Dieting and binging. A causal analysis. The American Psychologist, 40(2), 193–201.  https://doi.org/10.1037/0003-066X.40.2.193.CrossRefPubMedGoogle Scholar
  23. Ramos, S. X. (2015). The ineffectiveness and unintended consequences of the public health war on obesity. Canadian Journal of Public Health, 106(2), e79–e81.Google Scholar
  24. Seo, D. C., & Jiang, N. (2009). Associations between smoking and extreme dieting among adolescents. Journal of Youth and Adolescence, 38(10), 1364–1373.  https://doi.org/10.1007/s10964-009-9421-0.CrossRefPubMedGoogle Scholar
  25. Storey, K., Hanning, R., Lambraki, I., Driezen, P., Fraser, S., & McCargar, L. (2009). Determinants of diet quality among Canadian adolescents. Canadian Journal of Dietetic Practice and Research, 70(2), 58–65.CrossRefPubMedGoogle Scholar
  26. U.S. Department of Health and Human Services. (2012). Preventing Tobacco Use Among Youth and Young Adults: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.Google Scholar
  27. Woodruff, S. J., Hanning, R. M., Lambraki, I., Storey, K. E., & McCargar, L. (2008). Healthy eating index-C is compromised among adolescents with body weight concerns, weight loss dieting, and meal skipping. Body Image, 5(4), 404–408.  https://doi.org/10.1016/j.bodyim.2008.04.006.CrossRefPubMedGoogle Scholar
  28. Woodruff, S. J., Hanning, R. M., McGoldrick, K., & Brown, K. S. (2010). Healthy eating index-C is positively associated with family dinner frequency among students in grades 6–8 from southern Ontario, Canada. European Journal of Clinical Nutrition, 64(5), 454–460.  https://doi.org/10.1038/ejcn.2010.14.CrossRefPubMedGoogle Scholar
  29. World Health Organization. (2015). Global database on body mass index: BMI classification. http://apps.who.int/bmi/index.jsp?introPage=intro_3.html. Published 2015. Accessed May 10, 2017.

Copyright information

© The Canadian Public Health Association 2018

Authors and Affiliations

  • Amanda Raffoul
    • 1
  • Scott T. Leatherdale
    • 1
  • Sharon I. Kirkpatrick
    • 1
  1. 1.School of Public Health and Health SystemsUniversity of WaterlooWaterlooCanada

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