Non-linear association of body composition and its components with bone density in Iranian children and adolescents

Predictive factors of bone strength variation in adolescent girls according to body composition

PURPOSE

This study examined correlations among anthropometric parameters, body composition, bone parameters and predictive factors of bone mass in adolescent girls with different body fat percentages (%fat).

METHODS

A total of 129 females aged 15-18 years were categorized into 3 groups using %fat-for-age at the 50th and 95th percentiles as cutoff points (normal, over, and excess %fat groups). We recorded anthropometric data and measured the speed of sound at the tibia and radius using quantitative ultrasound. Dual-energy x-ray absorptiometry (DXA) was used to measure body composition and bone parameters, including bone mineral density (BMD), bone mineral content (BMC), and the BMD-z-score (z-score) in the lumbar spine (LS) and whole body (WB). These parameters were compared among the 3 groups using bivariate and multivariate correlation analyses.

RESULTS

There were strong correlations among all anthropometric parameters, body composition, and DXA in the over %fat group. Lean parameters strongly correlated with LS and WB in the normal %fat group, whereas both lean mass (LM) and fat mass (FM) were positively correlated with BMC in the excess %fat group. The predictive factors of bone mass differed among the groups, as follows: lean body mass was predictive of BMD and BMC at both sites in the normal and over %fat groups; LM and body weight were predictive of LS-BMC and WB-bones, respectively, in the over %fat group; and FM was predictive of WB-bones in the excess %fat group. Body fat and waist circumference were negative predictors of bone mass.

CONCLUSION

Predictive factors of bone strength appear to depend on the amount of body fat in adolescent girls.

Probabilistic prediction of segmental body composition in Iranian children and adolescents

Background

Adolescents' body composition is considered an important measure to evaluate health status. An examination of any of the segmental compartments by anthropometric indices is a more usable method than direct methods.

Objectives

To propose a method based on the network approach for predicting segmental body composition components in adolescent boys and girls using anthropometric measurements.

Methods

A dual-energy X-ray absorptiometry (DXA) dataset in the south of Iran, including 476 adolescents (235 girls and 241 boys) with a range of 9–18 years, was obtained. Several anthropometric prediction models based on the network approach were fitted to the training dataset (TRD 80%) using bnlearn, an R add-in package. The best fitted models were applied to the validation dataset (VAD 20%) to assess the prediction accuracy.

Results

Present equations consisting of age, weight, height, body mass index (BMI), and hip circumference accounted for 0.85 (P < 0.001) of the variability of DXA values in the corresponding age groups of boys. Similarly, reasonable estimates of DXA values could be obtained from age, weight, height, and BMI in girls over 13 years, and from age, weight, height, BMI, and waist circumference in girls under 13 years, respectively, of 0.77 and 0.83 (P < 0.001). Correlations between robust Gaussian Bayesian network (RGBN) predictions and DXA measurements were highly significant, averaging 0.87 for boys and 0.82 for girls (P < 0.001).

Conclusions

The results revealed that, based on the present study’s predictive models, adolescents' body composition might be estimated by input anthropometric information. Given the flexibility and modeling of the present method to test different motivated hypotheses, its application to body compositional data is highly appealing.