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Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, “Micro-impact of Domain” and “Contribution of Domain”, to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles. [ABSTRACT FROM AUTHOR]

Introduction: People with Multiple Sclerosis are known to have a relatively high prevalence of both anxiety and depression. Studies of the relationship between physical disability and mental health in people with MS have reported mixed results, showing the need for further work. Methods: Between May 2011 and April 2012, 4516 people completed the MSIS-29 (v.1) and HADS scales via the dedicated internet site of the UK MS Register within a 7 day time window. These responses were linked with basic demographic and descriptive data and analysed in SPSS (v.20). Results: The proportions of people experiencing anxiety or depression increased with physical disability such that 38.0% of respondents with low, and 66.7% with high disability reported at least mild anxiety, and 17.1% of people with low, and 71.7% with high disability experienced at least mild depression. The multiple regression model explained 18.4% of the variance in anxiety with MSIS-29-PHYS score being the strongest predictor of anxiety. The model for depression explained 37.8% of the variance with MSIS-29-PHYS score being the strongest predictor. Some of the other variables included showed negative associations with anxiety and depression, indicating that the influence of physical disability on mental wellbeing could be underestimated. Conclusions: This study indicates that there is a positive relationship between physical disability and anxiety and depression, that physical disability impacts on anxiety and depression to differing extents, and that the effects vary with gender, age, disease course and disease duration. We have shown that physical disability is a predictor of anxiety and depression, and that other factors may mask the extent of this effect. Whether the causes of anxiety and depression are reactive, organic or a combination, it is essential that mental wellbeing is given due attention in caring for people with MS so that all their health needs can be met. [ABSTRACT FROM AUTHOR]

Introduction: The EQ-5D is a widely-used, standardised, quality of life measure producing health profiles, indices and states. The aims of this study were to assess the role of various factors in how people with Multiple Sclerosis rate their quality of life, based on responses to the EQ-5D received via the web portal of the UK MS Register. Methods: The 4516 responses to the EQ-5D (between May 2011 and April 2012) were collated with basic demographic and descriptive MS data and the resulting dataset was analysed in SPSS (v.20). Results: The mean health state for people with MS was 59.73 (SD 22.4, median 61), compared to the UK population mean of 82.48 (which is approximately 1SD above the cohort mean). The characteristics of respondents with high health states (at or above +1SD) were: better health profiles (most predictive dimension: Usual Activities), higher health indices, younger age, shorter durations of MS, female gender, relapsing-remitting MS, higher educational attainment and being in paid employment (all p-values<0.001). Conversely, the characteristics of respondents with low health states (at or below -1SD) were: poorer health profiles (most predictive dimension: Mobility), lower health indices, older age, longer durations of MS, male gender, progressive MS, lower educational attainment and having an employment status of sick/disabled (p = 0.0014 for age, all other p-values<0.001). Particular living arrangements were not associated with either the high or low health status groups. Conclusions: This large-scale study has enabled in-depth analyses on how people with MS rate their quality of life, and it provides new knowledge on the various factors that contribute to their self-assessed health status. These findings demonstrate the impact of MS on quality of life, and they can be used to inform care provision and further research, to work towards enhancing the quality of life of people with MS. [ABSTRACT FROM AUTHOR]