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Joisten C, Wessely S, Prinz N, Wiegand S, Gohlke B, Keiser S, Moliterno P, Nielinger J, Torbahn G, Wulff H, Holl RW. BMI Z-Score (SDS) versus Calculated Body Fat Percentage: Association with Cardiometabolic Risk Factors in Obese Children and Adolescents. Ann Nutr Metab 2023; 80:29-36. [PMID: 38128491 PMCID: PMC10857797 DOI: 10.1159/000535216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 11/10/2023] [Indexed: 12/23/2023]
Abstract
INTRODUCTION BMI or BMI-standardized deviation score (SDS) in children and adolescents is still the standard for weight classification. [BMJ. 2019;366:4293] developed a formula to calculate body fat percentage (%BF) based on age, sex, height, weight, and ethnicity. Using data from the German/Austrian APV registry, we investigated whether the calculated %BF is superior to BMI-SDS in predicting arterial hypertension, dyslipidaemia, and impaired glucose metabolism. METHODS 94,586 children and adolescents were included (12.5 years, 48.3% male). Parental birth country (BC) was used to depict ethnicity (15.8% migration background); 95.67% were assigned to the ethnicity "white." %BF was calculated based on the Hudda formula. The relationship between BMI-SDS or %BF quartiles and outcome variables was investigated by logistic regression models, adjusted for age, sex, and migration background. Vuong test was applied to analyse predictive power. RESULTS 58.4% had arterial hypertension, 33.5% had dyslipidaemia, and 11.6% had impaired glucose metabolism. Boys were significantly more often affected, although girls had higher calculated %BF (each p < 0.05). After adjustment, both models revealed significant differences between the quartiles (all p < 0.001). The predictive power of BMI-SDS was superior to %BF for all three comorbidities (all p < 0.05). DISCUSSION The prediction of cardiometabolic comorbidities by calculated %BF was not superior to BMI-SDS. This formula developed in a British population may not be suitable for a central European population, which is applicable to this possibly less heterogeneous collective. Additional parameters, especially puberty status, should be taken into account. However, objective determinations such as bioimpedance analysis may possibly be superior to assess fat mass and cardiometabolic risk than calculated %BF.
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Affiliation(s)
- Christine Joisten
- Department for Physical Activity in Public Health, Institute of Movement and Neurosciences, German Sport University Cologne, Cologne, Germany
| | - Stefanie Wessely
- Department for Physical Activity in Public Health, Institute of Movement and Neurosciences, German Sport University Cologne, Cologne, Germany
| | - Nicole Prinz
- Institute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Susanna Wiegand
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, And Berlin Institute of Health, Berlin, Germany
| | - Bettina Gohlke
- Pediatric Endocrinology and Diabetology Division, Children’s Hospital, University of Bonn, Bonn, Germany
| | - Sabine Keiser
- Elisabeth-Krankenhaus Rheydt, Center for Child and Youth Medicine, Moenchengladbach, Germany
| | - Paula Moliterno
- Austrian Academic Institute for Clinical Nutrition, Vienna, Austria
| | - Jens Nielinger
- CJD Nord Fachklinik für Kinder und Jugendliche, Garz, Germany
| | - Gabriel Torbahn
- Department of Pediatrics, Paracelsus Medical University, Klinikum Nürnberg, Nurnberg, Germany
- AdieuPositas, Ambulante Therapie für Kinder und Jugendliche, Munich, Germany
| | - Hagen Wulff
- Institute of Exercise and Public Health, University of Leipzig, Leipzig, Germany
| | - Reinhard W. Holl
- Institute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - for the APV initiative
- Department for Physical Activity in Public Health, Institute of Movement and Neurosciences, German Sport University Cologne, Cologne, Germany
- Institute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, And Berlin Institute of Health, Berlin, Germany
- Pediatric Endocrinology and Diabetology Division, Children’s Hospital, University of Bonn, Bonn, Germany
- Elisabeth-Krankenhaus Rheydt, Center for Child and Youth Medicine, Moenchengladbach, Germany
- Austrian Academic Institute for Clinical Nutrition, Vienna, Austria
- CJD Nord Fachklinik für Kinder und Jugendliche, Garz, Germany
- Department of Pediatrics, Paracelsus Medical University, Klinikum Nürnberg, Nurnberg, Germany
- AdieuPositas, Ambulante Therapie für Kinder und Jugendliche, Munich, Germany
- Institute of Exercise and Public Health, University of Leipzig, Leipzig, Germany
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