An application of multilevel modelling techniques to the study of geographical variations in health outcome measures

In the UK there has been an extensive amount of research in the field of geographical disparities in health. However, this has primarily concentrated on urban settings, with relatively few studies explicitly concerned with issues of rural health. Furthermore, focusing on simple urban-rural comparisons is inappropriate as inequalities may be hidden within rural areas with differing socio-economic and geographical characteristics. This thesis is based in the South West of England incorporating two health outcomes; all-cause mortality and Limiting Long Term Illness (LLTI). It aims to investigate the nature of spatial differentials in these outcomes, examining urban-rural and intra-rural comparisons, and to identify possible determinants for these inequalities, incorporating area characteristics, socio-economic deprivation factors and access to general practitioner surgeries and district general hospitals into the analysis. A number of methodological constraints need consideration when looking at health in rural areas. No universally agreed definition of what constitutes 'rural' exists and this thesis shows that the choice of definition can influence the research findings. The highly significant nearest neighbour classification of local isolation indicates a u-shape relationship between LLTI and urbanisation. Population density, however, indicates a gradient of decreasing LLTI with decreasing urbanisation, and fails to be significantly related to the geographical pattern of morbidity. A lot of research analysing inequalities in health adjusts for socio-economic deprivation using generic deprivation indices as proxy measures for deprivation. Assuming a strong relationship between premature ill-health and deprivation this thesis shows that in contrast to urban areas these are inadequate measures of rural deprivation. The relationships between the generic deprivation indices are also weaker in rural than urban areas, suggesting that the choice of measure will have a greater impact on the relative levels of deprivation and therefore resource allocation. The prediction of the health outcome measures is improved by the computation of the customised measures based on census indicators. This indicates that there are more accurate ways of measuring rural deprivation but further work is needed to explore alternative data sources and indicators. There is conflict between researchers over the best level of aggregation to use in rural health research. Rural areas are more heterogeneous than urban areas, with the affluent living alongside the poor. Therefore area-based approaches to measuring deprivation average out levels of deprivation and conceal pockets of deprivation. This case argues for analysis at the small area level. In contrast, there are relatively small numbers of health events at the small area level in rural areas making analysis statistically unreliable and pressing for analysis at higher levels of aggregation. This thesis shows the difficulty of modelling mortality at the small area level by the inability of the measure to form relationships with any of the explanatory variables in rural areas. The relationship between the geographical patterns of mortality and LLTI is weaker in rural than urban areas. The marked differences in the picture of health status between the two measures indicate that the choice of health outcome has important implications for health needs assessment and resource allocation. Higher levels of LLTI in isolated rural populations are not reflected in mortality rates, therefore this may be a more appropriate measure of poor health during the lifetime of rural populations. However, the self-reported LLTI measure does not reflect any specific medical diagnosis and requires further investigation.