Barboza-González, Paola

Background: The functional fitness of older people may be associated with their nutritional status. Aim: To assess the association between of anthropometric measures with functional fitness in older people. Material and Methods: Cross-sectional study conducted in 75 participants aged 65 to 89 years. Body mass index (BMI), waist-to-height ratio (WHtR), fat mass (FM) and skeletal muscle mass index (SMI) were calculated from anthropometric measures. The functional fitness was determined using the Senior Fitness Test battery. Results: BMI and FM indicated obesity, and WHtR indicated cardiometabolic risk in 49%, 55% and 83% of participants, respectively. SMI indicated a low muscle mass in 91% of females. Performance standards of chair stand, arm curl, 2-min step test and 8-foot up-and-go tests were met in 1%, 8%, 1% and 89% of participants, respectively. Significant negative correlations were found between 2-min step test and BMI, WHtR and FM (r = −0.26, −0.31 and −0.48 respectively). Back scratch had a negative correlation with BMI (r = −0.23) and SMI (rho = −0.28). Significant positive correlations were found between 8-foot up-and-go, WHtR (rho = 0.28) and FM (rho = 0.23), and between 2-min step test and SMI (rho = 0.28). The coefficient of determination (R2) between 2-min step test with BMI, WHtR and FM were 0.05, 0.08 and 0.22, respectively, while the R2 between back scratch and BMI was 0.04. Multiple regression models indicated that FM affected the 2-min step test independently of BMI and WHtR (adjusted R2 = 0.22), however age and sex negatively influenced these associations. Conclusions: Functional fitness of older adults is influenced by nutritional anthropometric measures, particularly BMI, WHtR and FM for aerobic capacity, and BMI for upper limb flexibility.

This aims of this study were (I) to determine the velocity variable and regression model which best fit the load-velocity relationship during the free-weight prone bench pull exercise, (II) to compare the reliability of the velocity attained at each percentage of the one-repetition maximum (1RM) between different velocity variables and regression models, and (III) to compare the within- and between-subject variability of the velocity attained at each %1RM. Eighteen men (14 rowers and four weightlifters) performed an incremental test during the free-weight prone bench pull exercise in two different sessions. General and individual load-velocity relationships were modelled through three velocity variables (mean velocity [MV], mean propulsive velocity [MPV] and peak velocity [PV]) and two regression models (linear and second-order polynomial). The main findings revealed that (I) the general (Pearson’s correlation coefficient [r] range = 0.964–0.973) and individual (median r = 0.986 for MV, 0.989 for MPV, and 0.984 for PV) load-velocity relationships were highly linear, (II) the reliability of the velocity attained at each %1RM did not meaningfully differ between the velocity variables (coefficient of variation [CV] range = 2.55–7.61% for MV, 2.84–7.72% for MPV and 3.50–6.03% for PV) neither between the regression models (CV range = 2.55–7.72% and 2.73–5.25% for the linear and polynomial regressions, respectively), and (III) the within-subject variability of the velocity attained at each %1RM was lower than the between-subject variability for the light-moderate loads. No meaningful differences between the within- and between-subject CVs were observed for the MV of the 1RM trial (6.02% vs. 6.60%; CV ratio = 1.10), while the within-subject CV was lower for PV (6.36% vs. 7.56%; CV ratio = 1.19). These results suggest that the individual load-MV relationship should be determined with a linear regression model to obtain the most accurate prescription of the relative load during the free-weight prone bench pull exercise.