Supplementary Material for: BMI Z-score (SDS) versus calculated body fat percentage: Association with cardiometabolic risk factors in obese children and adolescents
posted on 2023-12-21, 14:04authored byJoisten C., Wessely S., Prinz N., Wiegand S., Gohlke B., Keiser S., Moliterno P., Nielinger J., Torbahn G., Wulff H., Holl R.W., for the APV initiative
Introduction
BMI or BMI-standardized deviation score (SDS) in children and adolescents is still the standard for weight classification. Hudda et al. (2019) developed a formula to calculate body fat percentage (�) based on age, sex, height, weight, and ethnicity. Using data from the German/Austrian APV registry, we investigated whether the calculated � is superior to BMI-SDS in predicting arterial hypertension, dyslipidaemia and impaired glucose metabolism.
Methods
94,586 children and adolescents were included (12.5yrs., 48.3% male). Parental birth country (BC) was used to depict ethnicity (15.8% migration background); 95.67% were assigned to the ethnicity “white”. � was calculated based on the Hudda formula. The relationship between BMI-SDS or � quartiles and outcome variables were 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% dyslipidaemia and 11.6% impaired glucose metabolism. Boys were significantly more often affected although girls had higher calculated � (each p<0.05). After adjustment, both models reveiled significant differences between the quartiles (all p<0.001). The predictive power of BMI-SDS was superior to � for all three comorbidities (all p<0.05).
Discussion/Conclusion
The prediction of cardiometabolic comorbidities by calculated � 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, esp. 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 �.