Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

Towards a Bourdieusian analysis of the disabled body and practice: embodying negative symbolic capitals and the uneasy experience of hysteresis

Within the last few years, disabled people have become the target of government austerity measures through drastic cuts to welfare justified through the portrayal of benefit claimants as inactive, problem citizens who are wilfully unemployed. For all that is wrong with these cuts, they are one of many aspects of exclusion that disabled people face. Attitudes towards disability are deteriorating (Scope, 2011) and disabled people are devalued and negatively positioned in a myriad of ways, meaning that an understanding of the perceptions and positioning of disability and the power of disabling practices is critical. This thesis will examine how Bourdieu’s theoretical repertoire may be applied to the area of Disability Studies in order to discern how society produces oppressive and exclusionary systems of classification which structures the social position and perceptions of disability. The composite nature of disability and multiple forms of exclusion and inequality associated with it benefits from a multipronged approach which acknowledges personal, embodied and psychological aspects of disability alongside socio-political and cultural conceptualisations. Bourdieu’s approach is one in which the micro and macro aspects of social life are brought together through their meso interplay and provides a thorough analysis of the many aspects of disability.

Searches for two-body charmless baryonic B0 decays at LHCb

The results of two separate searches for the rare two-body charmless baryonic decays B0 -> p pbar and B0s -> p pbar at the LHCb experiment are reported in this thesis. The first analysis uses a data sample, corresponding to an integrated luminosity of 0.9 fb^-1, of proton-proton collision data collected by the LHCb experiment at a centre-of-mass energy of 7 TeV. An excess of B0 -> p pbar candidates with respect to background expectations is seen with a statistical significance of 3.3 standard deviations. This constitutes the first evidence for a two-body charmless baryonic B0 decay. No significant B0s -> p pbar signal was observed. However, a small excess of B0s -> p pbar events allowed the extraction of two sided confidence level intervals for the B0s -> p pbar branching fraction using the Feldman-Cousins frequentist method. This improved the upper limit on the B0s -> p pbar branching fraction by three orders of magnitude over previous bounds. The 68.3% confidence level intervals on the branching fractions were measured to be BF(B0 -> p pbar) = ( 1.47 ^{+0.62}_{-0.51} ^{+0.35}_{-0.14} ) x 10^-8, BF(B0s -> p pbar) = ( 2.84 ^{+2.03}_{-1.68} ^{+0.85}_{-0.18} ) x 10^-8, where the first uncertainty is statistical and the second is systematic. The second analysis followed on from the first LHCb result and included the full 2011 and 2012 samples of proton-proton collision data at centre of mass energies of 7 and 8 TeV, corresponding to a total integrated luminosity of 3.122 fb^-1.