ASSOCIATION BETWEEN CLUSTERING OF LIFESTYLE RISK BEHAVIOURS AND RISK OF BEING OVERWEIGHT OR OBESE AMONG CHILDREN AND ADOLESCENTS WITH CONGENITAL HEART DISEASE ENROLLED IN A NOVEL PEDIATRIC EXERCISE MEDICINE PROGRAM

Children and adolescents with congenital heart disease (CHD) are at a higher risk of being overweight or obese. Lifestyle risk behaviours are prevalent in this population and limited information is known about how the clustering of unhealthy lifestyle behaviours impact patients’ weight status. Objective: To determine the association between unhealthy lifestyle behaviours and risk of being overweight or obese in pediatric patients with CHD.

We performed a cross-sectional analysis of children and adolescents (ages 8-17 years) referred from outpatient cardiology clinics who successfully enrolled in the Exercise Medicine (EM) Program at the Hospital for Sick Children between January 2018 – February 2020. Patients’ demographic characteristics, medical history, anthropometry, and lifestyle behaviour data were retrospectively collected. CHD severity status was classified as simple, moderate, and severe based on the Bethesda Classification. The exposure variable was clustering of lifestyle risk behaviours (physical inactivity, excessive screen time, unhealthy dietary intake, and poor sleep hygiene). Participants were categorized into two groups: lesser clustering (one or two lifestyle risk behaviours) or greater clustering (three or four lifestyle risk behaviours). The outcome variable was body mass index z-score (zBMI) and patients were categorized into either normal body weight (-2 < zBMI < 2) or overweight/obese (>2 zBMI). Final multivariable logistic model was adjusted for age, sex, and CHD severity. There were 53 CHD patients included in the analysis. The mean age was 13±3 years, 27 (49%) were male, 19 (36%) were taking cardiac medication, and 30 (57%) had documented comorbidities. The proportion of simple, moderate, and severe CHD was 15%, 42%, and 43%, respectively. The proportion of patients with normal body weight was 72%, while 28% were overweight/obese. Of the 53 patients, 21 (53%) had greater clustering of unhealthy lifestyle patterns while 25 (48%) had lesser clustering. In our final multivariable logistic model, participants with greater clustering of lifestyle risk behaviours had 7.4 times the odds of being overweight/obese (95% CI 1.5, 54.4, P=0.025) than those participants with lesser clustering of lifestyle risk behaviours (Table 1). Age, sex, and CHD severity were not associated with weight status.

Clustering of multiple unhealthy lifestyle behaviour patterns are prevalent among children with CHD and this is associated with increased risk of being overweight/obese. Timely identification of lifestyle risk behaviours and targeted intervention through personalized lifestyle counseling and physical activity promotion may be an effective strategy to optimize body weight.