A height-weight formula to measure body fat in childhood obesity

• Published in: Italian journal of pediatrics Vol. 48; no. 1; pp. 1 - 106
• Main Authors: Licenziati, Maria Rosaria, Ballarin, Giada, Iannuzzo, Gabriella, Lonardo, Maria Serena, Di Vincenzo, Olivia, Iannuzzi, Arcangelo, Valerio, Giuliana
• Format: Journal Article
• Language: English
• Published: Pisa BioMed Central 21-06-2022; BMC
• Subjects: Age; Bioimpedance analysis; Body composition; Body fat; Body height; Body mass index; Children; Children & youth; Fat-free body mass; Gender; Girls; Height-weight equation; Obesity; Overweight; Participation; Pediatrics; Prediction models; Statistical analysis; Teenagers; Variables; Weight control; United Kingdom > UK; Italy
• ISSN: 1824-7288; 1720-8424; 1824-7288
• DOI: 10.1186/s13052-022-01285-8

Background The assessment of body composition is central in diagnosis and treatment of paediatric obesity, but a criterion method is not feasible in clinical practice. Even the use of bioelectrical impedance analysis (BIA) is limited in children. Body mass index (BMI) Z-score is frequently used as a proxy index of body composition, but it does not discriminate between fat mass and fat-free mass. We aimed to assess the extent to which fat mass and percentage of body fat estimated by a height-weight equation agreed with a BIA equation in youths with obesity from South Italy. Furthermore, we investigated the correlation between BMI Z-score and fat mass or percentage of body mass estimated by these two models. Methods One-hundred-seventy-four youths with obesity (52.3% males, mean age 10.8 ± 1.9) were enrolled in this cross-sectional study. Fat mass and percentage of body fat were calculated according to a height-weight based prediction model and to a BIA prediction model. Results According to Bland–Altman statistics, mean differences were relatively small for both fat mass (+ 0.65 kg) and percentage of body fat (+ 1.27%) with an overestimation at lower mean values; the majority of values fell within the limits of agreement. BMI Z-score was significantly associated with both fat mass and percentage of body fat, regardless of the method, but the strength of correlation was higher when the height-weight equation was considered (r = 0.82; p < 0.001). Conclusions This formula may serve as surrogate for body fat estimation when instrumental tools are not available. Dealing with changes of body fat instead of BMI Z-score may help children and parents to focus on diet for health.