BackgroundThigh tissue thickness has not been examined in older females living in extended care in UK as an indicator of musculoskeletal health. This study examined the feasibility of using ultrasound imaging to measure the thickness of superficial (fat) and deep layers (muscle) of the thigh in older females living in extended care.MethodsIn ten older females in extended care (aged 80–98 years, mean 88 ± 6.8; body mass: 56.5 ± 12.6 kg) images of the anterior thigh (dominant) were taken in supine using B-mode ultrasound imaging. Superficial and deep layers were measured and percentage thickness was calculated. Independent t tests compared data from those in extended care to ten sedentary females living independently (aged 80–90 years, mean 84 ± 3.6; body mass: 61.6 ± 10.0 kg).ResultsThickness of the superficial layers was not significantly different between the two groups (CI −0.017 to 0.815, p = 0.059). However, those living in extended care had greater (p < 0.001) muscle thickness (mean 2.75 ± 0.48 cm) than those living independently (mean 1.83 ± 0.3 cm), which was similarly significant when normalised for body mass (extended care 0.51 ± 0.16; independent living 0.30 ± 0.06).ConclusionsThese novel findings showed it is feasible to use ultrasound to measure muscles in older females in extended care and that muscle thickness was larger than in those living independently. The reason for the difference seen between groups would need to be confirmed by a larger study that also examined factors related to risk of sarcopenia and frailty, such as nutrition and physical activity levels.

Within the framework of the financial industry, when representing relationships between assets, correlation is typically used. However, academics have long since questioned this method due to the plethora of issues that plague it. Indeed, it is thought that cointegration is a natural replacement in some of the cases as it is able to represent the physical reality of these assets better. However, despite this general academic consensus, financial practitioners refuse to accept cointegration as a better tool, or even the lesser of two evils. This technical report attempts to explain this bias, specifically focusing on the various consequences of model selection considering the new and challenging regulatory environment and suggests a practical replacement hybrid alternative to both cointegration and correlation.