Claudia Börnhorst1, Paola Russo2, Toomas Veidebaum3, Michael Tornaritis4, Dénes Molnár5, Lauren Lissner6, Staffan Marild7, Stefaan De Henauw8, Luis A Moreno9, Timm Intemann10,11, Maike Wolters10, Wolfgang Ahrens10,11, Anna Floegel10. 1. Leibniz Institute for Prevention Research and Epidemiology - BIPS, Department of Biometry and Data Management, Bremen, Germany. 2. Institute of Food Sciences, National Research Council, Avellino, Italy. 3. National Institute for Health Development, Estonian Centre of Behavioral and Health Sciences, Tallinn, Estonia. 4. Research and Education Institute of Child Health, Strovolos, Cyprus. 5. Department of Pediatrics, Medical School, University of Pécs, Pécs, Hungary. 6. Section for Epidemiology and Social Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 7. Department of Paediatrics, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden. 8. Department of Public Health, Ghent University, Ghent, Belgium. 9. GENUD (Growth, Exercise, Nutrition and Development) Research Group, Faculty of Health Sciences, Universidad de Zaragoza, Zaragoza, Spain. 10. Leibniz Institute for Prevention Research and Epidemiology - BIPS, Epidemiological Methods and Etiological Research, Bremen, Germany. 11. Institute of Statistics, Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany.
Abstract
BACKGROUND: This study aimed to investigate metabolic status in children and its transitions into adolescence. METHODS: The analysis was based on 6768 children who participated in the European IDEFICS/I.Family cohort (T0 2007/2008, T1 2009/2010 and/or T3 2013/2014; mean ages: 6.6, 8.4 and 12.0 years, respectively) and provided at least two measurements of waist circumference, blood pressure, blood glucose and lipids over time. Latent transition analysis was used to identify groups with similar metabolic status and to estimate transition probabilities. RESULTS: The best-fitting model identified five latent groups: (i) metabolically healthy (61.5%; probability for group membership at T0); (ii) abdominal obesity (15.9%); (iii) hypertension (7.0%); (iv) dyslipidaemia (9.0%); and (v) several metabolic syndrome (MetS) components (6.6%). The probability of metabolically healthy children at T0 remaining healthy at T1 was 86.6%; when transitioning from T1 to T3, it was 90.1%. Metabolically healthy children further had a 6.7% probability of developing abdominal obesity at T1. Children with abdominal obesity at T0 had an 18.5% probability of developing several metabolic syndrome (MetS) components at T1. The subgroup with dyslipidaemia at T0 had the highest chances of becoming metabolically healthy at T1 (32.4%) or at T3 (35.1%). Only a minor proportion of children showing several MetS components at T0 were classified as healthy at follow-up; 99.8% and 88.3% remained in the group with several disorders at T1 and T3, respectively. CONCLUSIONS: Our study identified five distinct metabolic statuses in children and adolescents. Although lipid disturbances seem to be quite reversible, abdominal obesity is likely to be followed by further metabolic disturbances.
BACKGROUND: This study aimed to investigate metabolic status in children and its transitions into adolescence. METHODS: The analysis was based on 6768 children who participated in the European IDEFICS/I.Family cohort (T0 2007/2008, T1 2009/2010 and/or T3 2013/2014; mean ages: 6.6, 8.4 and 12.0 years, respectively) and provided at least two measurements of waist circumference, blood pressure, blood glucose and lipids over time. Latent transition analysis was used to identify groups with similar metabolic status and to estimate transition probabilities. RESULTS: The best-fitting model identified five latent groups: (i) metabolically healthy (61.5%; probability for group membership at T0); (ii) abdominal obesity (15.9%); (iii) hypertension (7.0%); (iv) dyslipidaemia (9.0%); and (v) several metabolic syndrome (MetS) components (6.6%). The probability of metabolically healthy children at T0 remaining healthy at T1 was 86.6%; when transitioning from T1 to T3, it was 90.1%. Metabolically healthy children further had a 6.7% probability of developing abdominal obesity at T1. Children with abdominal obesity at T0 had an 18.5% probability of developing several metabolic syndrome (MetS) components at T1. The subgroup with dyslipidaemia at T0 had the highest chances of becoming metabolically healthy at T1 (32.4%) or at T3 (35.1%). Only a minor proportion of children showing several MetS components at T0 were classified as healthy at follow-up; 99.8% and 88.3% remained in the group with several disorders at T1 and T3, respectively. CONCLUSIONS: Our study identified five distinct metabolic statuses in children and adolescents. Although lipid disturbances seem to be quite reversible, abdominal obesity is likely to be followed by further metabolic disturbances.
Authors: Ramona Moosburger; Clarissa Lage Barbosa; Marjolein Haftenberger; Anna-Kristin Brettschneider; Franziska Lehmann; Anja Kroke; Gert B M Mensink Journal: J Health Monit Date: 2020-03-04