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Updated: Jul 7, 2025

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
BMI Z-Score (SDS) versus Calculated Body Fat Percentage: Association with Cardiometabolic Risk Factors in Obese
Christine Joisten1, Stefanie Wessely1, Nicole Prinz2,3
1Department for Physical Activity in Public Health, Institute of Movement and Neurosciences, German Sport University Cologne, Cologne, Germany.
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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