RESUMEN
BACKGROUND: 3D laser-based photonic scanners are increasingly used in health studies to estimate body composition. However, too little is known about whether various 3D body scan measures estimate body composition better than single standard anthropometric measures, and which body scans best estimate it. Furthermore, little is known about differences by sex and age. METHODS: 105 men and 96 women aged between 18 and 90 years were analysed. Bioelectrical Impedance Analysis was used to estimate whole relative fat mass (RFM), visceral adipose tissue (VAT) and skeletal muscle mass index (SMI). An Anthroscan VITUSbodyscan was used to obtain 3D body scans (e.g. volumes, circumferences, lengths). To reduce the number of possible predictors that could predict RFM, VAT and SMI backward elimination was performed. With these selected predictors linear regression on the respective body compositions was performed and the explained variations were compared with models using standard anthropometric measurements (Body Mass Index (BMI), waist circumference (WC) and waist-to-height-ratio (WHtR)). RESULTS: Among the models based on standard anthropometric measures, WC performed better than BMI and WHtR in estimating body composition in men and women. The explained variations in models including body scan variables are consistently higher than those from standard anthropometrics models, with an increase in explained variations between 5% (RFM for men) and 10% (SMI for men). Furthermore, the explained variation of body composition was additionally increased when age and lifestyle variables were added. For each of the body composition variables, the number of predictors differed between men and women, but included mostly volumes and circumferences in the central waist/chest/hip area and the thighs. CONCLUSIONS: 3D scan models performed better than standard anthropometric measures models to predict body composition. Therefore, it is an advantage for larger health studies to look at body composition more holistically using 3D full body surface scans.
RESUMEN
The present study investigates behavioral and electrophysiological auditory and cognitive-related plasticity in three groups of healthy older adults (60-77 years). Group 1 was moderately hearing-impaired, experienced hearing aid users, and fitted with new hearing aids using non-linear frequency compression (NLFC on); Group 2, also moderately hearing-impaired, used the same type of hearing aids but NLFC was switched off during the entire period of study duration (NLFC off); Group 3 represented individuals with age-appropriate hearing (NHO) as controls, who were not different in IQ, gender, or age from Group 1 and 2. At five measurement time points (M1-M5) across three months, a series of active oddball tasks were administered while EEG was recorded. The stimuli comprised syllables consisting of naturally high-pitched fricatives (/sh/, /s/, and /f/), which are hard to distinguish for individuals with presbycusis. By applying a data-driven microstate approach to obtain global field power (GFP) as a measure of processing effort, the modulations of perceptual (P50, N1, P2) and cognitive-related (N2b, P3b) auditory evoked potentials were calculated and subsequently related to behavioral changes (accuracy and reaction time) across time. All groups improved their performance across time, but NHO showed consistently higher accuracy and faster reaction times than the hearing-impaired groups, especially under difficult conditions. Electrophysiological results complemented this finding by demonstrating longer latencies in the P50 and the N1 peak in hearing aid users. Furthermore, the GFP of cognitive-related evoked potentials decreased from M1 to M2 in the NHO group, while a comparable decrease in the hearing-impaired group was only evident at M5. After twelve weeks of hearing aid use of eight hours each day, we found a significantly lower GFP in the P3b of the group with NLFC on as compared to the group with NLFC off. These findings suggest higher processing effort, as evidenced by higher GFP, in hearing-impaired individuals when compared to those with normal hearing, although the hearing-impaired show a decrease of processing effort after repeated stimulus exposure. In addition, our findings indicate that the acclimatization to a new hearing aid algorithm may take several weeks.