Johanna Roche1, Flavia C Corgosinho2, Ana R Dâmaso3, Laurie Isacco4, Maud Miguet5, Alicia Fillon5, Aurore Guyon6, Gustavo A Moreira7, Marcia Pradella-Hallinan7, Sergio Tufik8, Marco Túlio de Mello9, Valérie Gillet10, Bruno Pereira11, Martine Duclos12, Yves Boirie13, Julie Masurier14, Patricia Franco6, David Thivel15, Fabienne Mougin4. 1. EA3920, Exercise Performance Health Innovation platform, University of Franche-Comte, Besançon, France; Sleep and Health Medicine Center Ellipse, Franois, France; Laboratory of the Metabolic Adaptations to Exercise under Physiological and Pathological Conditions (AME2P), UE3533, Clermont Auvergne University, Clermont-Ferrand, France; Wits Sleep Laboratory, Brain Function Research Group, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. Electronic address: johanna.roche@wits.ac.za. 2. Universidade Federal de Goiás - Faculdade de Nutrição - Programa de Pos-Graduação em Nutrição, Sao Paulo, Brazil. 3. Universidade Federal de São Paulo - Escola Paulista de Medicina, Programa de Pos-Graduação em Nutrição, Sao Paulo, Brazil. 4. EA3920, Exercise Performance Health Innovation platform, University of Franche-Comte, Besançon, France. 5. Laboratory of the Metabolic Adaptations to Exercise under Physiological and Pathological Conditions (AME2P), UE3533, Clermont Auvergne University, Clermont-Ferrand, France. 6. Sleep Pediatric Unit, Woman Mother Child Hospital, Hospices Civils de Lyon, Lyon1 University, F-69500, France; Physiology of Brain Arousal System Research Laboratory, CRNL, INSERM-U1028, CNRS UMR5292, Lyon1 University, Lyon, France. 7. Universidade Federal de São Paulo - Escola Paulista de Medicina, Programa de Pos-Graduação em Nutrição, Sao Paulo, Brazil; Universidade Federal de São Paulo - Escola Paulista de Medicina - Departameno de Psicobiologia, Sao Paulo, Brazil. 8. Universidade Federal de São Paulo - Escola Paulista de Medicina - Departameno de Psicobiologia, Sao Paulo, Brazil. 9. Universidade Federal de Minas Gerais - Programa de Pós-Graduação em Educação Física - Minas Gerais, Brazil. 10. Sleep and Health Medicine Center Ellipse, Franois, France. 11. Clermont-Ferrand University Hospital, Biostatistics Unit (DRCI), Clermont-Ferrand, France. 12. University Clermont 1, UFR Medicine, Clermont-Ferrand, France; INRA, UMR, 1019, Clermont-Ferrand, France; CRNH-Auvergne, Clermont-Ferrand, France; Department of Sport Medicine and Functional Explorations, Clermont-Ferrand University Hospital, G. Montpied Hospital, Clermont-Ferrand, France. 13. University Clermont 1, UFR Medicine, Clermont-Ferrand, France; INRA, UMR, 1019, Clermont-Ferrand, France; CRNH-Auvergne, Clermont-Ferrand, France; Department of Human Nutrition, Clermont-Ferrand University Hospital, G. Montpied Hospital, Clermont-Ferrand, France. 14. UGECAM Nutrition Obesity Ambulatory Hospital, Clermont-Ferrand, France. 15. Laboratory of the Metabolic Adaptations to Exercise under Physiological and Pathological Conditions (AME2P), UE3533, Clermont Auvergne University, Clermont-Ferrand, France; CRNH-Auvergne, Clermont-Ferrand, France.
Abstract
BACKGROUND AND AIMS: Pediatric obesity and sleep-disordered breathing (SDB) are associated with cardiometabolic risk (CMR), but the degree of severity at which SDB affects cardiometabolic health is unknown. We assessed the relationship between the CMR and the apnea-hypopnea index (AHI), to identify a threshold of AHI from which an increase in the CMR is observed, in adolescents with obesity. We also compared the clinical, cardiometabolic and sleep characteristics between adolescents presenting a high (CMR+) and low CMR (CMR-), according to the threshold of AHI. METHODS AND RESULTS: 114 adolescents with obesity were recruited from three institutions specialized in obesity management. Sleep and SDB as assessed by polysomnography, anthropometric parameters, fat mass (FM), glucose and lipid profiles, and blood pressure (BP) were measured at admission. Continuous (MetScoreFM) and dichotomous (metabolic syndrome, MetS) CMR were determined. Associations between MetScoreFM and AHI adjusted for BMI, sex and age were assessed by multivariable analyses. Data of 82 adolescents were analyzed. Multivariable analyses enabled us to identify a threshold of AHI = 2 above which we observed a strong and significant association between CMR and AHI (Cohen's d effect-size = 0.57 [0.11; 1.02] p = 0.02). Adolescents with CMR+ exhibited higher MetScoreFM (p < 0.05), insulin resistance (p < 0.05), systolic BP (p < 0.001), sleep fragmentation (p < 0.01) and intermittent hypoxia than CMR- group (p < 0.0001). MetS was found in 90.9% of adolescents with CMR+, versus 69.4% in the CMR- group (p < 0.05). CONCLUSIONS: The identification of a threshold of AHI ≥ 2 corresponding to the cardiometabolic alterations highlights the need for the early management of SDB and obesity in adolescents, to prevent cardiometabolic diseases. CLINICAL TRIALS: NCT03466359, NCT02588469 and NCT01358773.
BACKGROUND AND AIMS: Pediatric obesity and sleep-disordered breathing (SDB) are associated with cardiometabolic risk (CMR), but the degree of severity at which SDB affects cardiometabolic health is unknown. We assessed the relationship between the CMR and the apnea-hypopnea index (AHI), to identify a threshold of AHI from which an increase in the CMR is observed, in adolescents with obesity. We also compared the clinical, cardiometabolic and sleep characteristics between adolescents presenting a high (CMR+) and low CMR (CMR-), according to the threshold of AHI. METHODS AND RESULTS: 114 adolescents with obesity were recruited from three institutions specialized in obesity management. Sleep and SDB as assessed by polysomnography, anthropometric parameters, fat mass (FM), glucose and lipid profiles, and blood pressure (BP) were measured at admission. Continuous (MetScoreFM) and dichotomous (metabolic syndrome, MetS) CMR were determined. Associations between MetScoreFM and AHI adjusted for BMI, sex and age were assessed by multivariable analyses. Data of 82 adolescents were analyzed. Multivariable analyses enabled us to identify a threshold of AHI = 2 above which we observed a strong and significant association between CMR and AHI (Cohen's d effect-size = 0.57 [0.11; 1.02] p = 0.02). Adolescents with CMR+ exhibited higher MetScoreFM (p < 0.05), insulin resistance (p < 0.05), systolic BP (p < 0.001), sleep fragmentation (p < 0.01) and intermittent hypoxia than CMR- group (p < 0.0001). MetS was found in 90.9% of adolescents with CMR+, versus 69.4% in the CMR- group (p < 0.05). CONCLUSIONS: The identification of a threshold of AHI ≥ 2 corresponding to the cardiometabolic alterations highlights the need for the early management of SDB and obesity in adolescents, to prevent cardiometabolic diseases. CLINICAL TRIALS: NCT03466359, NCT02588469 and NCT01358773.
Authors: Johanna Roche; Dale E Rae; Kirsten N Redman; Kristen L Knutson; Malcolm von Schantz; F Xavier Gómez-Olivé; Karine Scheuermaier Journal: J Clin Sleep Med Date: 2021-07-01 Impact factor: 4.324