Physical activity brings significant health benefits to middle-aged adults, although the research to date has been focused on late adulthood. This study aims to examine how ageing affects the self-reported and accelerometer-derived measures of physical activity levels in middle-aged adults. We employed the data recorded in the UK Biobank and analysed the physical activity levels of 2,998 participants (1381 men and 1617 women), based on self-completion questionnaire and accelerometry measurement of physical activity. We also assessed the musculoskeletal health of the participants using the dual-energy X-ray absorptiometry (DXA) measurements provided by the UK Biobank. Participants were categorised into three groups according to their age: group I younger middle-aged (40 to 49 years), group II older middle-aged (50 to 59 years), and group III oldest middle-aged (60 to 69 years). Self-reported physical activity level increased with age and was the highest in group III, followed by group II and I (P?<?0.05). On the contrary, physical activity measured by accelerometry decreased significantly with age from group I to III (P?<?0.05), and the same pertained to the measurements of musculoskeletal health (P?<?0.05). It was also shown that middle-aged adults mostly engaged in low and moderate intensity activities. The opposing trends of the self-reported and measured physical activity levels may suggest that middle-aged adults over-report their activity level as they age. They should be aware of the difference between their perceived and actual physical activity levels, and objective measures would be useful to prevent the decline in musculoskeletal health.
Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm3. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation. 相似文献
