Hayyah Clairman1,2, Elizabeth Dettmer3, Annick Buchholz4, Kristina Cordeiro5, Quazi Ibrahim6, Katerina Maximova7, Alene Toulany8, Valerie H Taylor9, Debra K Katzman1,8, Katherine M Morrison10, Jill Hamilton11,12, Geoff Ball2, Jean-Pierre Chanoine13, Josephine Ho14, Laurent Legault15, Pam Mackie6, Lehana Thabane6,16, Ian Zenlea17,18. 1. Institute of Medical Science, University of Toronto, Toronto, Canada. 2. Department of Pediatrics, University of Alberta, Alberta, Canada. 3. Department of Psychology, The Hospital for Sick Children, Toronto, Canada. 4. Children's Hospital of Eastern Ontario, Ottawa, Canada. 5. Department of Psychology, York University, Toronto, Canada. 6. Population Health Research Institute, McMaster University, Hamilton, Canada. 7. School of Public Health, University of Alberta, Alberta, Canada. 8. Division of Adolescent Medicine, Department of Pediatrics, The Hospital for Sick Children, Toronto, Canada. 9. Department of Psychiatry, Women's College Hospital, Toronto, Canada. 10. Division of Endocrinology, Department of Pediatrics, McMaster Children's Hospital, McMaster University, Hamilton, Canada. 11. Institute of Medical Science, University of Toronto, Toronto, Canada. jill.hamilton@sickkids.ca. 12. Division of Endocrinology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Canada. jill.hamilton@sickkids.ca. 13. Department of Pediatrics, University of British Columbia, Vancouver, Canada. 14. Department of Pediatrics, University of Calgary, Calgary, Canada. 15. Department of Pediatrics, McGill University, Montreal, Canada. 16. Department of Pediatrics, McMaster University, Hamilton, Canada. 17. Credit Valley Hospital, Toronto, ON, Canada. 18. Department of Pediatrics, University of Toronto, Toronto, ON, Canada.
Abstract
BACKGROUND: Paediatric obesity management remains generalised to dietary and exercise modifications with an underappreciation for the contributions of eating behaviours and appetitive traits in the development of obesity. OBJECTIVES: To determine whether treatment-seeking children and adolescents with obesity cluster into phenotypes based on known eating behaviours and appetitive traits ("eating correlates") and how socio-demographic and clinical characteristics associate with different phenotypes. METHODS: A cross-sectional, multi-centre questionnaire was administered between November 2015 and March 2017 examining correlates of eating in children and adolescents attending weight-management programmes in Canada. Latent profile analysis was used to cluster participants based on seven eating correlate scores obtained from questionnaires. Analysis of variance (ANOVA) was used to determine phenotype differences on socio-demographic and clinical characteristics. Multinomial logistic regression models assessed relative risk of specific characteristics associating with a disordered eating phenotype. RESULTS: Participants were 247 children and adolescents (45.3% male, mean BMI z-score = 3.4 ± 1.0 kg/m2) from six paediatric weight management centres in Canada. Seven eating correlates clustered into three distinct phenotypes: (1) loss of control eating, emotional eating, external eating, hyperphagia, impulsivity ("Mixed-Severe"; n = 42, 17%), (2) loss of control eating, emotional eating, external eating, hyperphagia ("Mixed-Moderate"; n = 138, 55.9%), and (3) impulsivity ("Impulsive"; n = 67; 27.1%). Social functioning scores and body esteem were significantly different across groups, with the Mixed-Severe participants having the poorest social functioning and lowest body esteem. Low body esteem indicated a greater risk of being in a multi-correlate group compared to the Impulsive group, while poor social function had a greater risk of clustering in the Mixed-Severe than Impulsive phenotype. CONCLUSIONS: Distinct eating phenotypes were found in treatment-seeking children and adolescents with obesity. Empirical evidence is needed, but these data suggest that tailored treatment approaches could be informed by these classifications to improve weight-management outcomes.
BACKGROUND: Paediatric obesity management remains generalised to dietary and exercise modifications with an underappreciation for the contributions of eating behaviours and appetitive traits in the development of obesity. OBJECTIVES: To determine whether treatment-seeking children and adolescents with obesity cluster into phenotypes based on known eating behaviours and appetitive traits ("eating correlates") and how socio-demographic and clinical characteristics associate with different phenotypes. METHODS: A cross-sectional, multi-centre questionnaire was administered between November 2015 and March 2017 examining correlates of eating in children and adolescents attending weight-management programmes in Canada. Latent profile analysis was used to cluster participants based on seven eating correlate scores obtained from questionnaires. Analysis of variance (ANOVA) was used to determine phenotype differences on socio-demographic and clinical characteristics. Multinomial logistic regression models assessed relative risk of specific characteristics associating with a disordered eating phenotype. RESULTS: Participants were 247 children and adolescents (45.3% male, mean BMI z-score = 3.4 ± 1.0 kg/m2) from six paediatric weight management centres in Canada. Seven eating correlates clustered into three distinct phenotypes: (1) loss of control eating, emotional eating, external eating, hyperphagia, impulsivity ("Mixed-Severe"; n = 42, 17%), (2) loss of control eating, emotional eating, external eating, hyperphagia ("Mixed-Moderate"; n = 138, 55.9%), and (3) impulsivity ("Impulsive"; n = 67; 27.1%). Social functioning scores and body esteem were significantly different across groups, with the Mixed-Severe participants having the poorest social functioning and lowest body esteem. Low body esteem indicated a greater risk of being in a multi-correlate group compared to the Impulsive group, while poor social function had a greater risk of clustering in the Mixed-Severe than Impulsive phenotype. CONCLUSIONS: Distinct eating phenotypes were found in treatment-seeking children and adolescents with obesity. Empirical evidence is needed, but these data suggest that tailored treatment approaches could be informed by these classifications to improve weight-management outcomes.
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