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

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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.

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Raffoul, A., Leatherdale, S. T., & Kirkpatrick, S. I. (2018). Dieting predicts engagement in multiple risky behaviours among adolescent Canadian girls: a longitudinal analysis. Canadian Journal of Public Health, 109(1), 61–69. https://doi.org/10.17269/s41997-018-0025-x

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