Lean body mass is the strongest anthropometric predictor of left ventricular mass in the obese paediatric population.

BACKGROUND: Indexing left ventricular mass to body surface area or height2.7 leads to inaccuracies in diagnosing left ventricular hypertrophy in obese children. Lean body mass predictive equations provide the opportunity to determine the utility of lean body mass in indexing left ventricular mass. Our objectives were to compare the diagnostic accuracy of predicted lean body mass, body surface area, and height in detecting abnormal left ventricle mass in obese children. METHODS: Obese non-hypertensive patients aged 4-21 years were recruited prospectively. Dual-energy X-ray absorptiometry was used to measure lean body mass. Height, weight, sex, race, and body mass index z-score were used to calculate predicted lean body mass. RESULTS: We enrolled 328 patients. Average age was 12.6 ± 3.8 years. Measured lean body mass had the strongest relationship with left ventricular mass (R2 = 0.84, p < 0.01) compared to predicted lean body mass (R2 = 0.82, p < 0.01), body surface area (R2 = 0.80, p < 0.01), and height2.7 (R2 = 0.65, p < 0.01). Of the clinically derived variables, predicted lean body mass was the only measure to have an independent association with left ventricular mass (ß = 0.90, p < 0.01). Predicted lean body mass was the most accurate scaling variable in detecting left ventricular hypertrophy (positive predictive value = 88%, negative predictive value = 99%). CONCLUSIONS: Lean body mass is the strongest predictor of left ventricular mass in obese children. Predicted lean body mass is the most accurate anthropometric scaling variable for left ventricular mass in left ventricular hypertrophy detection. Predicted lean body mass should be considered for clinical use as the body size correcting variable for left ventricular mass in obese children.

Assessing truncal obesity in predicting cardiometabolic risk in children: clinical measures versus dual-energy X-ray absorptiometry.

AIM: The objectives of this study were to 1) compare the accuracy of waist:hip ratio (WHR) and waist:height ratio (WHtR) by determining their association with reference-standard measures derived from dual-energy X-ray absorptiometry (DXA) and 2) assess the relationship of DXA, WHR and WHtR to measures of dyslipidemia, insulin resistance and inflammation in children. METHODS: Subjects aged four to 21 were prospectively recruited. Truncal obesity by DXA was defined as the trunk fat:height ratio and trunk fat:nontrunk fat ratio. Three hundred and eight subjects were studied, and 246 (80%) were obese. RESULTS: There was a strong correlation between WHtR and trunk fat:height (r = 0.84, p < 0.01). DXA measures of truncal obesity had stronger correlations with measures of cardiometabolic risk than WHR and WHtR. Upon multivariable regression, only WHtR had independent associations with cholesterol/HDL, HOMA-IR and high-sensitivity c-reactive protein. CONCLUSION: WHtR is an accurate measure of truncal obesity. WHtR showed stronger associations with measures of insulin resistance and truncal obesity than WHR.

Sex-specific lean body mass predictive equations are accurate in the obese paediatric population.

BACKGROUND: The clinical assessment of lean body mass (LBM) is challenging in obese children. A sex-specific predictive equation for LBM derived from anthropometric data was recently validated in children. AIM: The purpose of this study was to independently validate these predictive equations in the obese paediatric population. SUBJECTS AND METHODS: Obese subjects aged 4-21 were analysed retrospectively. Predicted LBM (LBMp) was calculated using equations previously developed in children. Measured LBM (LBMm) was derived from dual-energy x-ray absorptiometry. Agreement was expressed as [(LBMm-LBMp)/LBMm] with 95% limits of agreement. RESULTS: Of 310 enrolled patients, 195 (63%) were females. The mean age was 11.8 ± 3.4 years and mean BMI Z-score was 2.3 ± 0.4. The average difference between LBMm and LBMp was -0.6% (-17.0%, 15.8%). Pearson's correlation revealed a strong linear relationship between LBMm and LBMp (r = 0.97, p < 0.01). CONCLUSION: This study validates the use of these clinically-derived sex-specific LBM predictive equations in the obese paediatric population. Future studies should use these equations to improve the ability to accurately classify LBM in obese children.

Lean body mass may explain apparent racial differences in carotid intima-media thickness in obese children.

BACKGROUND: Racial differences in carotid intima-media thickness (cIMT) have been suggested to be associated with the disproportionally high prevalence of cardiovascular disease in black adults. The objective of this study was to evaluate the effects of cardiovascular risk factors on the racial differences seen in cIMT in obese children. METHODS: Obese subjects aged 4 to 21 years were recruited prospectively. Height, weight, blood pressure, fasting insulin, glucose, lipid panel, high-sensitivity C-reactive protein, and body composition by dual-energy x-ray absorptiometry were obtained. B-mode carotid imaging was analyzed by a single blinded physician. RESULTS: A total of 120 subjects (46 white, 74 black) were enrolled. Black subjects exhibited greater cIMT (0.45 ± 0.03 vs 0.43 ± 0.02 cm, P < .01) and higher lean body mass index (19.3 ± 3.4 vs 17.3 ± 3.2 kg/m², P = .02) than white subjects. Simple linear regression revealed modest associations between mean cIMT and race (R = 0.52, P < .01), systolic blood pressure (R = 0.47, P < .01), and lean body mass (R = 0.51, P < .01). On multivariate regression analysis, lean body mass remained the only measure to maintain a statistically significant relationship with mean cIMT (P < .01). CONCLUSIONS: Black subjects demonstrated greater cIMT than white subjects. The relationship between race and cIMT disappeared when lean body mass was accounted for. Future studies assessing the association of cardiovascular disease risk factors to cIMT in obese children should include lean body mass in the analysis.