Body composition, nutritional status, and endothelial function in physically active men without metabolic syndrome – a 25 year cohort study

Abstract

BackgroundThe purpose of this analysis was to investigate the relationship between body composition, metabolic parameters and endothelial function among physically active healthy middle-aged and older men.MethodsOut of 101 asymptomatic men prospectively tracked for traditional cardiovascular risk factors (mean observation period 25.1 years), 55 metabolically healthy individuals who maintained stable leisure time physical activity (LTPA) level throughout the observation and agreed to participate in the body composition assessment were recruited (mean age 60.3 ± 9.9 years). Body composition and raw bioelectrical parameters were measured with bioelectrical impedance analysis (BIA). Microvascular endothelial function was evaluated by means of the reactive hyperemia index (RHI) using Endo-PAT2000 system.ResultsStrong correlations were observed between lifetime physical activity (PA), aerobic fitness and most of analyzed body composition parameters. The strongest inverse correlation was found for fat mass (p < 0.01) while positive relationship for fat-free mass (p < 0.01), total body water (p < 0.05 for current aerobic capacity and p < 0.01 for historical PA), body cell mass (p < 0.001), muscle mass (p < 0.001), calcium and potassium (p < 0.01 and p < 0.001 for current aerobic capacity and p < 0.001 and p < 0.01 for historical PA, respectively) and glycogen mass (p < 0.001). Among metabolic parameters, HDL cholesterol (HDL-C) and uric acid were significantly associated with most body composition indicators. Regarding endothelial function, a negative correlation was found for RHI and body mass (p < 0.05) while positive relationship for RHI and body cell mass (p < 0.05), calcium (p < 0.05) and potassium mass (p < 0.05). Impaired endothelial function was observed among 8 subjects. Among bioelectrical parameters, impedance (Z) and resistance (R) normalized for subjects’ height were negatively related with body mass, body mass index (BMI) and waist circumference (p < 0.001); while reactance (Xc) normalized for patients’ height was negatively related with body mass (p < 0.05). The mean phase angle value was relatively high (8.83 ± 1.22) what reflects a good level of cellularity and cell function. Phase angle was positively related with body mass and BMI (p < 0.05).ConclusionsBoth fat mass and muscle mass components are important predictors of metabolic profile. Maintaining regular high PA level and metabolically healthy status through young and middle adulthood may have beneficial influence on body composition parameters and may prevent age-related decrease of fat-free mass and endothelial dysfunction.

High C-reactive protein instead of metabolic syndrome is associated with lower bioimpedance phase angle in individuals clinically screened for a lifestyle modification program

“…However, even though the CRP were associated with PhA, as demonstrated, PhA values were not associated with the increasing number of MetS components and with other blood biomarkers. Recently, a cohort study also did not find association between some MetS components and PhA values [36], reinforcing our findings. Therefore, our data suggests that PhA values could be associated with an unspecific pro-inflammatory process and may be a useful tool for indirectly accessing it, independently of the presence of MetS.…”

Nutritional Status Plays More Important Role in Determining Functional State in Older People Living in the Community than in Nursing Home Residents

“…In addition, a higher PA level, especially training that increases muscle mass, may lead to an increase in ICW and influence muscle quality [ 46 ]. Therefore, active seniors tend to display lower R and higher PhA [ 47 , 48 , 49 ]. Older people living in institutions are usually characterized by a lower level of PA in comparison with CD subjects [ 50 ].…”

Reactive Hyperemia Index in Patients on Maintenance Hemodialysis: Cross-sectional Data from a Cohort Study

“…However, it should be noted that the R 2 of the model was only 0.07 and the regression coefficient for DBP is particularly low, suggesting that the associations were essentially clinically non-significant, and that this index is largely determined by unknown non-traditional clinical variables. In fact, studies on the determinants of RHI yielded widely varied and sometimes conflicting results and the abilities of their regression models for variance predicting were usually unsatisfied141517181920. Hence more potent determinants of RHI, especially disease-specific factors, warrant further exploring.…”