Fat–Fit Patterns, Drug Consumption, and Polypharmacy in Older Adults: The EXERNET Multi-Center Study

Background: Physical fitness levels and the amount of accumulated adipose tissue (fatness) relate to current and future individuals’ heath status. Nevertheless, the interrelationships of their combined patterns with polypharmacy and the types of medications consumed have not been sufficiently investigated. Methods: This cross-sectional study was carried out in six Spanish regions between 2008 and 2009 with a sample of older community-dwelling adults (≥65 years old) without dementia or cancer. Fitness was measured with one-leg balance and senior fitness tests, as well as by measuring weight and fat mass with a bioelectrical impedance analyzer. Polypharmacy was defined as the use of five or more medications. An analysis of variance was performed for comparisons between the physical fitness and fatness patterns and the medication consumed. Results: A total of 1709 elders were included in the study (72.1 ± 5.2 years). The two unfit patterns were those with the highest drug consumption. The High-Fat–Unfit pattern was the one that had the most significant consumption and had the highest percentage of polymedicated subjects. The Low-Fat–Fit pattern had a significantly lower percentage of people that did not consume any medications. The highest percentages of drug consumption in 7 of the 10 groups that were included were concentrated in the two unfit patterns. Conclusions: This study highlights the importance of fitness in older adults, as it is at least as important as the avoidance of accumulation of excess fat with respect to the consumption of a smaller number of medicines.

Association between Change in Regional Phase Angle and Jump Performance: A Pilot Study in Serie A Soccer Players

Purpose: This observational longitudinal investigation aimed to investigate whether change in bioelectrical regional phase angle (PhA) is a predictor of change in vertical jump performance in elite soccer players. Methods: Fifteen soccer players (age: 28.7 ± 5.0 years, body weight: 82.4 ± 6.8 kg, height: 186.0 ± 0.1 cm, body mass index: 23.8 ± 1.2 kg/m2) competing in the first Italian division (Serie A) were included in this study and tested before the pre-season period and after the first half of the championship. Whole body and lower hemisoma PhA were obtained with a phase-sensitive 50 kHz bioelectrical impedance analyzer and legs lean soft tissue was estimated using specific bioimpedance-based equation developed for athletes. Vertical jump performance was assessed using the countermovement jump (CMJ). Results: The major findings of the study are that changes in lower hemisoma PhA are more strongly related with changes in jump performance (r2 = 0.617, p = 0.001) than changes in whole-body PhA (r2 = 0.270, p = 0.047), even after adjusting for legs lean soft tissue and for body mass index (β = 5.17, p = 0.004). Conclusions: These data suggest that changes in lower hemisoma PhA might be used as a tool for evaluating performance related parameters in sports where specific body segments are involved, in preference to the whole-body measured value.

Bioimpedance Vector Patterns according to Age and Handgrip Strength in Adolescent Male and Female Athletes

Bioelectric Impedance Vector Analysis (BIVA) can be used to qualitatively compare individuals’ hydration and cell mass independently of predictive equations. This study aimed to analyze the efficiency of BIVA considering chronological age and handgrip strength in adolescent athletes. A total of 273 adolescents (male; 59%) engaged in different sports were evaluated. Bioelectrical impedance (Z), resistance (R), reactance (Xc), and phase angle (PhA) were obtained using a single-frequency bioelectrical impedance analyzer. Fat-free mass (FFM) and total body water were estimated using bioimpedance-based equations specific for adolescents. Female showed higher values of R (5.5%, p = 0.001), R/height (3.8%, p = 0.041), Z (5.3%, p = 0.001), and fat mass (53.9%, p = 0.001) than male adolescents. Male adolescents showed higher values of FFM (5.3%, p = 0.021) and PhA (3.1%, p = 0.033) than female adolescents. In both stratifications, adolescents (older > 13 y or stronger > median value) shifted to the left on the R-Xc graph, showing patterns of higher hydration and cell mass. The discrimination of subjects older than 13 years and having higher median of handgrip strength values was possibly due to maturity differences. This study showed that BIVA identified age and strength influence in vector displacement, assessing qualitative information and offering patterns of vector distribution in adolescent athletes.

Wrist-wearable bioelectrical impedance analyzer with miniature electrodes for daily obesity management

Bioelectrical impedance analysis (BIA) is used to analyze human body composition by applying a small alternating current through the body and measuring the impedance. The smaller the electrode of a BIA device, the larger the impedance measurement error due to the contact resistance between the electrode and human skin. Therefore, most commercial BIA devices utilize electrodes that are large enough (i.e., 4 × 1400 mm2) to counteract the contact resistance effect. We propose a novel method of compensating for contact resistance by performing 4-point and 2-point measurements alternately such that body impedance can be accurately estimated even with considerably smaller electrodes (outer electrodes: 68 mm2; inner electrodes: 128 mm2). Additionally, we report the use of a wrist-wearable BIA device with single-finger contact measurement and clinical test results from 203 participants at Seoul St. Mary’s Hospital. The correlation coefficient and standard error of estimate of percentage body fat were 0.899 and 3.76%, respectively, in comparison with dual-energy X-ray absorptiometry. This result exceeds the performance level of the commercial upper-body portable body fat analyzer (Omron HBF-306). With a measurement time of 7 s, this sensor technology is expected to provide a new possibility of a wearable bioelectrical impedance analyzer, toward obesity management.

Association Between Circadian Rhythm with Resting Metabolic Rate in Overweight\Obese Women

Aim: The aim of this study was to investigate the association between circadian rhythm with resting metabolic rate (RMR) in overweight\obese women Methods: This cross-sectional study included 232 obese and overweight women. Morningness-Eveningness Questionnaire (MEQ) was used to assess the level of circadian rhythm. RMR was measured by indirect calorimetry after a 10-12 hour overnight fasting period by a trained nutritionist. We assessed body composition using multi-frequency bioelectrical impedance analyzer (BIA). Results: The percentage of overweight and obese women were 48.7% (113) and 51.3% (119), respectively. The number of participants who were morningness, intermediate and eveningness was 28(12.1%), 135(58.2%) and 69(29.7%) respectively. A significant relationship was found between MEQ and RMR.normal (p=0.011). According to linear regression model non-eveningness participants had 81.92 higher RMR compared to eveningness participants (p=0.027). Conclusion: We found that non-eveningness participants had higher RMR compared to eveningness participants that can lead to obesity, diabetes type2 and other health disorders.

ANTHROPOMETRIC MEASUREMENT OF METABOLIC AGE USING NECK CIRCUMFERENCE

Excessive fat accumulation in the obese body causes chronic low-grade inflammation. The continuous occurrence will affect health, which may lead to damage to cell metabolism related to metabolic age. Therefore, anthropometric application by measuring neck circumference (NC) and body mass index (BMI) was performed. The aim of this study was to determine NC cut-off which can be used to identify the increase of metabolic age in an individual. This study is a diagnostic study using cross sectional design using subjects who met the criteria needed for this study (n = 82). BMI and NC anthropometric measurements were performed in this study. Metabolic age was measured using Bioelectrical Impedance Analyzer (BIA). Data were analyzed using 2 x 2 diagnostic table and Receiver Operating Characteristic (ROC) curve to obtain Area Under Curve (AUC). The results showed that the highest BMI was obese (65.8%) with the most common age of 30-57 years old. The result of ROC-AUC NC on metabolic age showed that AUC value of NC measurement was 0.77, cut-off ≥ 33 cm, sensitivity 71.2%, and specificity 69.6%. This study concludes that the cut-off value of NC in predicting the increase of metabolic age had good sensitivity and specificity.