Nutritional status of children with cystic fibrosis measured by total body potassium as a marker of body cell mass: Lack of sensitivity of anthropometric measures

Objective: To investigate measures aimed at defining the nutritional status of cystic fibrosis (CF) populations, this study compared standard anthropometric measurements and total body potassium (TBK) as indicators of malnutrition

Development of height-weight based equation for assessment of body composition in Sri Lankan children

Objective To develop a height and weight based equation to estimate total body water (TBW) in Sri Lankan children. Methods Cross sectional descriptive study done involving 5–15 year old healthy children. Height and weight were measured. TBW was assessed using isotope dilution method (D2O) and fat free mass (FFM) calculated. Multiple regression analysis was used to develop prediction equation and validated using PRESS statistical technique. Height, weight and sex code (male=1; female=0) were used as prediction variables. Results This study provides height and weight equation for the prediction of TBW in Sri Lankan children. To the best of our knowledge there are no published height weight prediction equations validated on South Asian populations. Conclusion Results of this study need to be affirmed by more studies on other closely related populations by using multicomponent body composition

Use of Skin-Fold Thickness in Sri Lankan Children: Comparison of Several Prediction Equations

Objective: There are many prediction equations available in the literature for the assessment of body composition from skinfold thickness (SFT). This study aims to cross validate some of those prediction equations to determine the suitability of their use on Sri Lankan children. Methods: Height, weight and SFT of 5 different sites were measured. Total body water was assessed using the isotope dilution method (DO). Percentage Fat mass (%FM) was estimated from SFT using prediction equations described by five authors in the literature. Results: Five to 15 year old healthy, 282 Sri Lankan children were studied. The equation of Brook gave Ihe lowest bias but limits of agreement were high. Equations described by Deurenberg et al gave slightly higher bias but limits of agreement were narrowest and bias was not influence by extremes of body fat. Although prediction equations did not estimate %FM adequately, the association between %FM and SFT measures, were quite satisfactory. Conclusion: We conclude that SFT can be used effectively in the assessment of body composition in children. However, for the assessment of body composition using SFT, either prediction equations should be derived to suit the local populations or existing equations should be cross-validated to determine the suitability before its application

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

Peer reviewed: TrueAcknowledgements: We thank John Reilly for his advice on data sources and data access; Cara L Eckhardt, Josephine Avila, Igor Y Kon, and Jinzhong Wang from the Eckhardt et al study23; and all staff involved in recruitment and data collection from the included studies. Data gathered from South Africa was supported by South Africa Medical Research Council and National Research Foundation.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. Co nclusion 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 year

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