ESPE2024 Rapid Free Communications Fat, Metabolism and Obesity 2 (6 abstracts)
1Faculty of Medecine, Université de Montréal, Montreal, Canada. 2Research Center of Sainte Justine Hospital University Center, Montreal, Canada. 3School of Public Health, Université de Montréal, Montreal, Canada. 4Department of Population Medecine, Harvard Pilgrim Health Care Institute/Harvard Medical School, Boston, USA. 5Department of Physical Education, Université de Laval, Quebec, Canada. 6Department of Mathematics and Statistics, Concordia University, Montreal, Canada. 7Department of Psychology, Concordia University, Montreal, Canada. 8Ingram School of Nursing, McGill University, Montreal, Canada. 9Children's Hospital of Eastern Ontario, Ottawa, Canada. 10Department of Pediatrics, Faculty of Medecine, Ottawa University, Ottawa, Canada. 11Department of Family Medicine, Faculty of Medicine, McGill University, Montreal, Canada. 12Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada. 13Department of Pediatrics, Faculty of Medecine, Université de Montréal, Montreal, Canada
Introduction: The EOSS is a clinical tool to assess the burden of obesity and has been shown in adults to predict later morbidity and mortality. We found that the pediatric version (EOSS-P) appears to predict later cardiometabolic outcomes, however whether it is a better predictor than anthropometrics alone remains unclear.
Objectives: To compare associations between EOSS-P stage at 8-10 years and cardiometabolic outcomes at 15-17 years to associations observed between anthropometric measures (BMI z-score (obj. 1), waist-to-height ratio (obj. 2), body fat percentage (obj. 3)) at 8-10 y and cardiometabolic health outcomes at 15-17 years.
Methods: Data stem from the QUALITY cohort of children recruited at 8-10 years in three major urban centers in QC, Canada (n = 630). EOSS-P staging was completed among 72 children with obesity ranging from stage 0 (no abnormalities across domains) to stage 3 (significant impairment). Measures of cardiometabolic health included: fasting and 2-hours post load glucose and insulin, HDL, LDL, triglycerides, HOMA-IR, blood pressure, HbA1c, fitness, body mass index z-score (BMIz), body fat percentage (DEXA), insulin sensitivity (Matsuda-ISI), 1st and 2nd phase insulin secretion (area under the curve of insulin/glucose over first 30 minutes (AUC30) and 120 minutes (AUC120) of OGTT). Multivariable linear regressions were adjusted for age and sex.
Results: Compared to stage 1, belonging to EOSS-P stage 3 at 8-10 yrs was associated with: a 1.1 mmol/L increase in 2-hour glucose [95% CI: 0.2, 1.4], 62.3% increase in 2-hour insulin [95% CI: 12.6, 112.0], 51.2% decrease in Matsuda-ISI [95% CI: -97.6, -4.9], 28.4% increase in AUC30 [95% CI: 3.5, 53.3], and 30.9% increase in AUC120 [95% CI: 7.8, 54.1] at 15-17 years. No associations were found when comparing belonging to EOSS-P stage 2 compared to stage 1. While similar associations were found between BMIz at 8-10 years and cardiometabolic outcomes at 15-17 years when considering the full spectrum of BMIz in the entire QUALITY cohort, no meaningful associations were found in the subset of children with obesity. Findings were similar using waist-to-height ratio and body fat percentage instead of BMIz.
Conclusion: The EOSS-P tool more effectively identifies later adverse cardiometabolic health outcomes among youth with obesity, especially glucose homeostasis, when compared to measures of adiposity alone. Therefore, relying solely on traditional anthropometric measures may not be optimal for identifying at-risk youth with obesity.