Background/Objective: With increasing obesity prevalence in children globally, accurate and practical methods for quantifying body fat are critical for effective monitoring and prevention, particularly in high risk settings. No population is at higher risk of obesity than Pacific Islanders, including children living in the independent nation of Samoa. We developed and validated sex-specific prediction models for fat mass in Samoan children.
Subjects/Methods: Dual x-ray absorptiometry (DXA) assessments of fat mass and weight, height, circumferences, and skinfolds were obtained from 356 children aged 7-9 years old in the Ola Tuputupua’e “Growing Up” study. Sex-specific models were developed from a randomly selected model development sample (n=118 females, n=120 males) using generalized linear regressions. In a validation sample (n=59 females; n=59 males), Lin’s concordance and Bland-Altman limits-of-agreement (LoA) of DXA-derived and predicted fat mass from this study and other published models were examined to assess precision and accuracy.
Results: Models to predict fat mass in kilograms were: e^[(-0.0034355*Age8-0.0059041*Age9+1.660441*l n(Weight(kg))-0.0087281 *Height(cm)+0.1393258 *ln[Suprailiac(mm)]-2.661793)] for females and e^[-0.0409724 *Age8-0.0549923*Age9+336.8575*[Weight(kg)]^(-2)-22.34261 *l n(Weight(kg)) [Weight(kg)]^(-1)+0.0108696*Abdomen(cm)+ 6.811015 *〖Subscapular (mm)〗^(-2)-8.642559 *l n(Subscapular(mm)) 〖Subscapular(mm)〗^(-2)-1.663095 *Tricep(mm)^(-1) +3.849035] for males, where Age8=Age9=0 for children at age 7 years, Age8 =1 and Age9=0 at 8 years, Age8 =0 and Age9 = 1 at 9 years. Models showed high predictive ability, with substantial concordance (ρ_C>0.96), and agreement between DXA-derived and model-predicted fat mass (LoA female= -0.235, 95% CI:-2.924-2.453; male= -0.202, 95% CI:-1.977-1.572).
Only one of four existing models, developed in a non-Samoan sample, accurately predicted fat mass among Samoan children.
Conclusions: We developed models that predicted fat mass in Samoans aged 7-9 years old with greater precision and accuracy than the majority of existing models that were tested. Monitoring adiposity in children with these models may inform future obesity prevention and interventions.</p
