10 research outputs found

    Genetic variants and physical activity interact to affect bone density in Hispanic children

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    Background: Our aim was to investigate if moderate to vigorous physical activity (MVPA), calcium intake interacts with bone mineral density (BMD)-related single nucleotide polymorphisms (SNPs) to influence BMD in 750 Hispanic children (4-19y) of the cross-sectional Viva La Familia Study. Methods: Physical activity and dietary intake were measured by accelerometers and multiple-pass 24 h dietary recalls, respectively. Total body and lumbar spine BMD were measured by dual energy X-ray absorptiometry. A polygenic risk score (PRS) was computed based on SNPs identified in published literature. Regression analysis was conducted with PRSs, MVPA and calcium intake with total body and lumbar spine BMD. Results: We found evidence of statistically significant interaction effects between the PRS and MVPA on total body BMD and lumbar spine BMD (p \u3c 0.05). Higher PRS was associated with a lower total body BMD (β = − 0.040 ± 0.009, p = 1.1 × 10− 5 ) and lumbar spine BMD (β = − 0.042 ± 0.013, p = 0.0016) in low MVPA group, as compared to high MVPA group (β = − 0.015 ± 0.006, p = 0.02; β = 0.008 ± 0.01, p = 0.4, respectively). Discussion: The study indicated that calcium intake does not modify the relationship between genetic variants and BMD, while it implied physical activity interacts with genetic variants to affect BMD in Hispanic children. Due to limited sample size of our study, future research on gene by environment interaction on bone health and functional studies to provide biological insights are needed

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

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    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

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    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

    Dual Energy X-ray Absorptiometry Interpretation and Reporting in Children and Adolescents: The 2007 ISCD Pediatric Official Positions

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    The International Society for Clinical Densitometry Official Positions on reporting of densitometry results in children represent an effort to consolidate opinions to assist healthcare providers determine which skeletal sites should be assessed, which adjustments should be made in these assessments, appropriate pediatric reference databases, and elements to include in a dual energy X-ray absorptiometry (DXA) report. Skeletal sites recommended for assessment are the lumbar spine and total body less head, the latter being valuable as it provides information on soft tissue, as well as bone. Interpretation of DXA findings in children with growth or maturational delay requires special consideration; adjustments are required to prevent erroneous interpretation. Normative databases used as a reference should be based on a large sample of healthy children that characterizes the variability in bone measures relative to gender, age, and race/ethnicity, and should be specific for each manufacturer and model of densitometer and software. Pediatric DXA reports should provide relevant demographic and health information, technical details of the scan, Z-scores, and should not include T-scores. The rationale and evidence for development of the Official Positions are provided. Given the sparse data currently available in many of these areas, it is likely that these positions will change over time as new data become available. © 2008 The International Society for Clinical Densitometry
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