External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis.

OBJECTIVE: To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings. DESIGN: Individual participant data meta-analysis. SETTING: 19 countries. PARTICIPANTS: 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment). MAIN OUTCOME MEASURES: The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R2, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves. RESULTS: The model showed good predictive ability in non-UK populations of children and adolescents, providing R2 values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R2, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (-0.02 to 0.04), respectively. Heterogeneity was evident in the R2 and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use. CONCLUSION: The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years.

Assessment of bone mineral status in children with Marfan syndrome.

Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder with skeletal involvement. It is caused by mutations in fibrillin1 (FBN1) gene resulting in activation of TGF-ß, which developmentally regulates bone mass and matrix properties. There is no consensus regarding bone mineralization in children with MFS. Using dual-energy X-ray absorptiometry (DXA), we evaluated bone mineralization in 20 children with MFS unselected for bone problems. z-Scores were calculated based on age, gender, height, and ethnicity matched controls. Mean whole body bone mineral content (BMC) z-score was 0.26±1.42 (P=0.41). Mean bone mineral density (BMD) z-score for whole body was -0.34±1.4 (P=0.29) and lumbar spine was reduced at -0.55±1.34 (P=0.017). On further adjusting for stature, which is usually higher in MFS, mean BMC z-score was reduced at -0.677±1.37 (P=0.04), mean BMD z-score for whole body was -0.82±1.55 (P=0.002) and for lumbar spine was -0.83±1.32 (P=0.001). An increased risk of osteoporosis in MFS is controversial. DXA has limitations in large skeletons because it tends to overestimate BMD and BMC. By adjusting results for height, age, gender, and ethnicity, we found that MFS patients have significantly lower BMC and BMD in whole body and lumbar spine. Evaluation of diet, exercise, vitamin D status, and bone turnover markers will help gain insight into pathogenesis of the reduced bone mass. Further, larger longitudinal studies are required to evaluate the natural history, incidence of fractures, and effects of pharmacological therapy.

Body-composition assessment in infancy: air-displacement plethysmography compared with a reference 4-compartment model.

BACKGROUND: A better understanding of the associations of early infant nutrition and growth with adult health requires accurate assessment of body composition in infancy. OBJECTIVE: This study evaluated the performance of an infant-sized air-displacement plethysmograph (PEA POD Infant Body Composition System) for the measurement of body composition in infants. DESIGN: Healthy infants (n = 49; age: 1.7-23.0 wk; weight: 2.7-7.1 kg) were examined with the PEA POD system. Reference values for percentage body fat (%BF) were obtained from a 4-compartment (4-C) body-composition model, which was based on measurements of total body water, bone mineral content, and total body potassium. RESULTS: Mean (+/- SD) reproducibility of %BF values obtained with the PEA POD system was 0.4 +/- 1.3%. Mean %BF obtained with the PEA POD system (16.9 +/- 6.5%) did not differ significantly from that obtained with the 4-C model (16.3 +/- 7.2%), and the regression between %BF for the 4-C model and that for the PEA POD system (R2 = 0.73, SEE = 3.7%BF) did not deviate significantly from the line of identity (y = x). CONCLUSIONS: The PEA POD system provided a reliable, accurate, and immediate assessment of %BF in infants. Because of its ease of use, good precision, minimum safety concerns, and bedside accessibility, the PEA POD system is highly suitable for monitoring changes in body composition during infant growth in both the research and clinical settings.