Temporal trends in severe obesity prevalence in children and youth from primary care electronic medical records in Ontario: a repeated cross-sectional study

<h3>Background:</h3> There are no current estimates of severe obesity in Canadian children. The objectives of this study were to determine the prevalence of severe obesity in children aged 18 years or less in Ontario and to determine temporal trends from 2004 to 2015. <h3>Methods:</h3> This was a repeated cross-sectional study using height/length and weight of children aged 18 years or less from the Electronic Medical Record Administrative data Linked Database (EMRALD), a database of primary care electronic medical records in Ontario. We calculated body mass index (for age and sex) z-scores (zBMI). Two years of data (2014 and 2015) were used to determine the period prevalence of severe obesity. We used multivariable linear regression generalized estimating equations to estimate the association of calendar year and mean zBMI. <h3>Results:</h3> In total, 55 233 children were included. The prevalence of severe obesity (zBMI &gt; 3) increased with increasing age: it was 0.9% (95% confidence interval [CI] 0.7% to 1.0%) among children less than 5 years of age, 2.7% (95% CI 2.3% to 3.1%) among 5- to 9-year-olds, 2.9% (95% CI 2.4% to 3.3%) among 10- to 14-year-olds and 3.7% (95% CI 3.1% to 4.3%) among those aged 15–18. Boys aged 5–9 years had a significantly higher prevalence of severe obesity than their female counterparts (3.5% [95% CI 2.9% to 4.2%] v. 1.7% [95% CI 1.3% to 2.2%]). From 2004 to 2015, the mean zBMI decreased by 0.015 (95% CI −0.018 to −0.012) units per year, with the overall prevalence of severe obesity in all ages highest in 2005 (3%) and a decrease to 2% in 2015. <h3>Interpretation:</h3> The prevalence of severe obesity among children and adolescents in Ontario is consistent with that in other developed countries with the exception of the United States. There is evidence of plateauing of estimates and a small decrease in zBMI over time. Further understanding of the impact of prevention efforts on these estimates is an important next step.