Edmonton Obesity Staging System – Pediatrics (EOSS-P) Regular readers are by now familiar with the Edmonton Obesity Staging System (EOSS), that classifies individuals with obesity based on its impact on physical, mental and functional health. Now, Stasia Hadjiyannakis and colleagues present an adaptation of EOSS for kids, published in Pediatrics and Child Health. The evidence-informed paediatric clinical obesity staging system (EOSS-P), builds on EOSS for adults and captures the severity of disease, as well as factors that complicate management, within four domains of health most commonly encountered in obesity: The EOSS-P assesses four main domains that are impacted by obesity and can impact responsiveness to weight management – metabolic, mechanical, mental, milieu: Metabolic Metabolic complications of paediatric obesity include glucose dysregulation (including type 2 …

This weekend sees the start of the XIII International Congress on Obesity (ICO), hosted by the World Obesity Federation in partnership with the Canadian Obesity Network (CON) in Vancouver, Canada. As this year’s Congress President, together with World Obesity Federation President Dr. Walmir Coutinho, it will be our pleasure to welcome delegates from around the world to what I am certain will be a most exciting and memorable event in one of the world’s most beautiful and livable cities. The program committee, under the excellent leadership of Dr. Paul Trayhurn, has assembled a broad and stimulating program featuring the latest in obesity research ranging from basic science to prevention and management. I can also attest to the fact that the committed staff both at the …

Much of the research on the contribution of screen time, sedentariness, food consumption and other factors comes from cross-sectional or longitudinal studies, where researchers essentially describe correlations and statistical “effect sizes”. To be at all meaningful, analyses in such studies need to be adjusted for known (or at least likely) confounders (or at least the confounders that happen to available). No matter how you turn and wind the data, such studies by definition cannot prove causality or (even less likely) predict the outcome of actual intervention studies. Nevertheless, such studies can be helpful in generating hypotheses. Thus, for example, I read with interest the recent paper by Lei Shang and colleagues from the University of Laval, Quebec, Canada, published in Preventive Medicine Reports. The researchers …