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The authors assessed individual, social, and school correlates of multiple chronic disease behavioral risk factors (physical inactivity, sedentary behavior, tobacco smoking, alcohol drinking, and high body mass index) in a representative sample of Canadian youth aged 10-15 years (mean = 12.5 years) attending public schools. Cross-sectional data (n = 1,747) from cycle 4 (2000-2001) of the National Longitudinal Survey of Children and Youth were used. Ordinal regression models were constructed to investigate associations between selected covariates and multiple behavioral risk-factor levels (0/1, 2, 3, or 4/5 risk factors). Older age (odds ratio (OR) = 1.95, 95% confidence interval (CI): 1.21, 3.13), caregiver smoking (OR = 1.49, 95% CI: 1.09, 2.03), reporting that most/all of one's peers smoked (OR = 7.31, 95% CI: 4.00, 13.35) or drank alcohol (OR = 3.77, 95% CI: 2.18, 6.53), and living in a lone-parent family (OR = 1.94, 95% CI: 1.31, 2.88) increased the likelihood of having multiple behavioral risk factors. Youth with high self-esteem (OR = 0.92, 95% CI: 0.85, 0.99) and youth from families with postsecondary education (OR = 0.58, 95% CI: 0.41, 0.82) were less likely to have a higher number of risk factors. Although several individual and social characteristics were associated with multiple behavioral risk factors, no school-related correlates emerged. These variables should be considered when planning prevention programs.

Objective: We assessed the prevalence, socioeconomic distribution and clustering of five major chronic disease behavioral risk factors (physical inactivity, sedentary behavior, tobacco smoking, alcohol drinking and high body mass index) in a representative sample of Canadian children and adolescents aged 10-17 years., Methods: Cross-sectional data (n=4724) from Cycle 4 (2000/2001) of the National Longitudinal Survey of Children and Youth were used. Clustering was assessed using an observed to expected ratio method., Results: Overall, 65% of Canadian youth had two or more behavioral risk factors compared to only 10% with none of the five risk factors. The prevalence of having multiple behavioral risk factors was greater among older youth and those from low socioeconomic status families. Behavioral risk factors clustered in multiple combinations. Specifically, the simultaneous occurrence of all five risk factors was 120% greater in males (Observed/Expected ratio: 2.20; 95% CI: 1.31-3.09) and 94% greater in females (Observed/Expected ratio: 1.94; 95% CI: 1.24-2.64) than expected. Ever smoking and ever drinking showed the strongest association among the pairwise clusters., Conclusions: Multiple chronic disease behavioral risk factors are frequent and occur more often than expected among Canadian children and adolescents. Early prevention programs targeting clusters of behavioral risk factors in youth are needed.

Cardiovascular disease (CVD) is the leading cause of mortality in women. In fact, CVD is responsible for a third of all deaths of women worldwide and half of all deaths of women over 50 years of age in developing countries. The prevalence of CVD risk factor precursors is increasing in children. Retrospective analyses suggest that there are some clinically relevant differences between women and men in terms of prevalence, presentation, management and outcomes of the disease, but little is known about why CVD affects women and men differently. For instance, women with diabetes have a significantly higher CVD mortality rate than men with diabetes. Similarly, women with atrial fibrillation are at greater risk of stroke than men with atrial fibrillation. Historically, women have been underrepresented in clinical trials. The lack of good trial evidence concerning sex-specific outcomes has led to assumptions about CVD treatment in women, which in turn may have resulted in inadequate diagnoses and suboptimal management, greatly affecting outcomes. This knowledge gap may also explain why cardiovascular health in women is not improving as fast as that of men. Over the last decades, mortality rates in men have steadily declined, while those in women remained stable. It is also becoming increasingly evident that gender differences in cultural, behavioural, psychosocial and socioeconomic status are responsible, to various degrees, for the observed differences between women and men. However, the interaction between sex-and gender-related factors and CVD outcomes in women remains largely unknown.