Muscle mass is the main somatic growth indicator associated with increasing blood pressure with age in children and adolescents

Fat-free mass may play a dominant role in the association between systolic blood pressure and body composition in children and adolescents

Systolic blood pressure (SBP) is significantly associated with body composition in children and adolescents. However, which one of the components of body composition is the dominant contributor to SBP in children and adolescents remains unclear. We, therefore, aimed to determine the dominant contributor to SBP among components of body composition in a large cohort of American children and adolescents derived from the National Health and Nutrition Examination Survey with cross-sectional analysis. In total, 13 618 children and adolescents (median age 13 years; 6107 girls) with available data on whole-body dual-emission X-ray absorptiometry measurements were included. Multiple linear regression showed that SBP was associated with higher total fat-free mass in boys (β = 0·49, P < 0·001) and girls (β = 0·47, P < 0·001) and with higher total fat mass only in boys (β = 0·12, P < 0·001) after adjustment for covariates. When taking fat distribution into consideration, SBP was associated with higher trunk fat mass (boys: β = 0·28, P < 0·001; girls: β = 0·15, P < 0·001) but negatively associated with leg fat mass (Boys: β = -0·14, P < 0·001; Girls: β = -0·11, P < 0·001), in both boys and girls. Dominance analysis showed that total fat-free mass was the dominant contributor to SBP (boys: 49 %; girls: 55·3 %), followed by trunk fat mass (boys: 32·1 %; girls: 26·9 %); leg fat mass contributed the least to SBP in boys (18·9 %) and girls (17·8 %). Our findings indicated that total fat-free mass was not only associated with SBP but also the most dominant contributor to SBP variation in American children and adolescents.

Role of muscle mass in the association between handgrip strength and blood pressure in children and adolescents

Studies have reported conflicting results on the association between handgrip strength (HGS) and blood pressure during childhood and adolescence. High multicollinearity involving somatic components that influence both HGS and blood pressure might be an important source of bias. This study sought to investigate the independent effects of HGS and muscle mass on blood pressure levels in children and adolescents. Muscle mass and fat mass (Multifrequency Electrical Bioimpedance) and systolic (SBP) and diastolic (DBP) blood pressure (Automatic oscillometric device) were assessed in 833 volunteers aged 6-18 years, of both sexes. Handgrip strength-for-age quartiles were calculated and participants were assigned to groups by HGS quartiles. Analysis of covariance was conducted to address the linear association between HGS and SBP adjusted for height, muscle mass, and fat mass. To test for linear trend, contrast analysis was conducted. Partial eta-squared was used to confirm or rule out a small significant effect of the independent variables on SBP. The effect size of HGS on SBP was not significant in both sexes. In girls, 1.7% of the between-groups variance in SBP was accounted for by muscle mass (P = 0.016). In boys, 2.3% and 1.8% of the between-groups variance in SBP was accounted for by muscle mass (P = 0.001) and height (P = 0.005), respectively. In conclusion, children with a more advanced physical maturity for their age, that is, who are taller, stronger, and have greater fat-free mass, may be nearly reaching the physiological parameters of adulthood, and consequently have higher systolic blood pressure.

Body composition predicts hypertension using machine learning methods: a cohort study

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35-70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting, and Stacking to classify the investigated cases and find the most relevant features to hypertension. FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. AutoMLP, stacking and voting methods had the best performance for hypertension prediction achieving an accuracy rate of 90%, 84% and 83%, respectively. By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with acceptable accuracy.

Effects of Crawling before Walking: Network Interactions and Longitudinal Associations in 7-Year-Old Children

BACKGROUND

To study the impact of crawling before walking (CBW) on network interactions among body composition, the cardiovascular system, lung function, motor competence and physical fitness, at age 7, and to assess the longitudinal association between CBW and body composition, the cardiovascular system, lung function, motor competence, physical fitness and physical activity parameters, at age 7.

METHOD

CBW, body composition, cardiovascular system, lung function, motor competence, physical fitness and physical activity were assessed in seventy-seven healthy Caucasian children.

RESULTS

Network analyses revealed that the crawling group had a greater number of links among all the studied variables compared with the non-crawling group. In the longitudinal study, using multiple regression analyses, crawling was independently associated with fat mass (%), fat-to-muscle ratio and systolic blood pressure, with models explaining up to 56.3%, 56.7% and 29.9% of their variance, respectively.

CONCLUSIONS

CBW during child's development is a possible modulator in the network interactions between body systems and it could influence future metabolic and cardiovascular health.

A sex-related mediating effect of uric acid in the association between body composition and blood pressure in children and adolescents

The increase in blood pressure (BP) during somatic growth might have direct determinants but also mediating factors. We investigated whether uric acid (UA) and other metabolic factors would mediate the association between body composition components and BP. A cross-sectional study was conducted in 928 children and adolescents (aged 6-18 years), in which body composition and blood biochemistry were evaluated. Structural equation modeling was performed to test the direct and indirect pathways between systolic blood pressure (SBP) and body composition parameters. Muscle mass (MM) showed a strong direct effect on BP, regardless of sex. In girls, a mediating pathway through UA was not significant, but the association between fat mass (FM) and MM with SBP was mediated by the cluster of metabolic factors. In boys, both MM and FM were associated with SBP through a mediating pathway via UA, but not via the cluster of metabolic factors. The association between body composition and BP in children and adolescents has a complex design and also has a sex-specific mediating component. The increase in the UA levels may affect BP levels early in boys. Also, metabolic changes elicited by FM contribute to the increase in BP at an early age in girls. Novelty: MM showed a strong direct effect on BP, regardless of sex. In girls, the association between FM and MM with SBP was mediated by the cluster of metabolic factors. In boys, both MM and FM were associated with SBP through a mediating pathway via UA.