Association of total body fat and fat distribution with bone mineral density among children and adolescents aged 6-17 years from Guangzhou, China.

This study aimed to assess the associations of total body fat and fat distribution with bone mineral density (BMD) among children and adolescents in this cross-sectional study. A total of 1032 boys and 897 girls aged 6-17 years were enrolled between May 2019 and June 2019 in Guangzhou, China. BMD, total body fat (fat mass index [FMI] and body fat percentage [BF%]), and fat distribution (trunk-to-limb and android-to-gynoid ratios) were measured by dual-energy X-ray absorptiometry. Inverse probability of treatment weighting regression was used to explore the association between fat and BMD. Traditional regression of covariate adjustment was applied as sensitivity analysis. Regression with inverse probability weighting suggested BF% and android-to-gynoid ratio were negatively associated with BMD in boys (ß = - 0.12 and - 0.16, respectively; P < 0.05). Android-to-gynoid ratio was also inversely associated with BMD in girls (ß = - 0.08, P < 0.05). When stratified by age, the negative associations were retained in boys aged 12-17 years (ß = - 0.23 and - 0.25, respectively; P < 0.001). But for girls, it showed a positive association of FMI with BMD in the 6-9 years group (ß = 0.33, P < 0.001) and a negative association between the android-to-gynoid ratio and BMD in the 10-17 years group (ß = - 0.10, P < 0.05). Traditional regression supported the robustness of the results.  Conclusion: Total body fat is positively associated with BMD in younger girls but inversely associated in older boys. As for abdominal adipose, it is associated with lower BMD in both older boys and girls. What is Known: • The lean mass has been consistently positively associated with bone mineral density (BMD) among children and adolescents. However, the impact of fat mass on BMD remained controversial. • Beyond total body fat, site-specific fat mass, especially abdominal adiposity, might impede bone formation. What is New: • The associations of total body fat and fat distribution with BMD in children and adolescents were gender- and age-specific. • More attention should be paid to the abdominal fat accumulation to promote bone health in older children.

Association of body composition with pubertal timing in children and adolescents from Guangzhou, China.

Objective: An ongoing debate surrounds the relationship between body composition and pubertal timing, in particular for boys. This cross-sectional study aimed to investigate the association of body composition with pubertal timing among children and adolescents. Methods: A total of 1,493 boys and 1,261 girls who entered puberty were enrolled in Guangzhou, China. Tanner stages were evaluated by examination of breast development for girls and testicular volume for boys. Fat mass (FM) and fat-free mass (FFM) were determined by bioelectrical impedance analysis. Parameters for body composition were transformed into age-and gender-specific Z-scores. The association of body composition with pubertal timing was examined using multinomial logistic regression with inverse probability weighting (IPW) based on the propensity score. Results: For boys, IPW analysis showed Z-scores of body fat percentage (BF%) and FM index (FMI) were negatively associated with early puberty (OR = 0.75, 95% CI = 0.64-0.87; OR = 0.74, 95% CI = 0.63-0.88). As for girls, in contrast to boys, positive associations were seen between BF% and FMI with early puberty (OR = 1.39, 95% CI = 1.19-1.64; OR = 1.59, 95% CI = 1.33-1.90). With respect to appendicular skeletal muscle mass index (ASMI), there was a positive association with early puberty and a negative one with late puberty in boys (OR = 1.26, 95% CI = 1.07-1.49; OR = 0.82, 95% CI = 0.69-0.99). Conclusion: There is a positive association of FM with early puberty for girls while negative for boys. FFM yields a positive association with early puberty and a negative one with late puberty in boys, but not in girls. Our findings highlight the gender differences in the connection between body composition and pubertal onset.

Comparative analysis of bone mineral content measured by bioelectrical impedance analysis and dual energy X ray absorption among children and adolescents / 中国学校卫生

Objective@#To compare bioelectrical impedance analysis (BIA) and dual energy X ray absorptiometry (DXA) for measuring body mineral content (BMC) of children and adolescents, and to provide a basis for BIA to accurately measure BMC in children and adolescents.@*Methods@#By using the convenience sampling method, among 1 469 children and adolescents aged 7-17 were recruited in Guangzhou from April to May 2019, the BMC was measured by DXA and BIA. The intraclass correlation coefficient ( ICC ) and Bland Altman analysis were used to evaluate the agreement between BIA and DXA. Bland Altman analysis was performed on log transformed data. The BMC was categorized into age and specific tertiles, and the agreement between methods was evaluated based on the kappa coefficients. Treating the BMC with DXA as the dependent variable, a prediction model was constructed for correcting the BIA measure.@*Results@#The ICC s were 0.93 and 0.94 for boys and girls, respectively. In Bland Altman analysis, the limits of agreements for the BIA to DXA ratio were wide in boys and girls, ranging from 0.27-0.76 and 0.17-0.72, respectively. The kappa coefficients for categorized BMC levels were 0.57 and 0.45 for boys and girls, respectively, showing a fair to good degree of agreement. When sub grouped by BMI, the kappa coefficients for all BMI groups of boys and overweight girls were all >0.75 , with an excellent agreement. The prediction models for boys and girls were as follows: BMC DXA =-0.51+0.44× BMC BIA + 0.06× Age +0.02× BMI ; and BMC DXA =-0.55+0.43× BMC BIA +0.06× Age +0.02× BMI , respectively. The R 2 for models of boys and girls were 0.87 and 0.87, respectively.@*Conclusion@#The agreement between BIA and DXA was poor for measuring BMC, but acceptable when evaluating the categorized BMC levels, suggesting the BIA may be applied in assessment of the BMC levels when compared to the age and gender specific population. Additionally, the prediction model for correcting BMC by BIA fis well to the measurement by DXA.