Background Worldwide, healthcare systems face common challenges, such as aging populations, multimorbidity and the increasing global burden of chronic diseases. Inequalities in health are often attributed to the social and economic environments in which individuals live and neighbourhoods may be a relevant concept because of the potential links between their characteristics and ill health. Spatial analysis can provide useful information on the effects of neighbourhood contextual factors on health with the use of sophisticated techniques and advanced statistical methods. Aims The aim of this thesis was to answer the following two empirical research questions: 1. To examine at a geographical âneighbourhoodâ level how âcontextualâ factors including quality of Primary Care, deprivation, social fragmentation, rurality and other population characteristics affect prevalence of mental illness, suicides and admissions for ambulatory care sensitive conditions using an ecological analysis framework for the Primary Care population of England. 2. To identify spatial patterns of disease for the three outcome measures across England using disease mapping, identification of disease clusters and by assessing the degree of spatial autocorrelation of disease and area measures. Methods The thesis uses routinely collected data from a range of sources and performs several statistical analyses which in combination with spatial analyses methods (identification of clusters, spatial autocorrelation, and spatial maps) at a very low geographical level for the whole of England to answer important policy and epidemiological questions. Results Quality of Primary Care had a very small impact on the patient outcomes examined in this thesis and other area and population characteristics were more important drivers of outcome variation. Those living in the most deprived parts of the country appeared to experience worse health across all outcomes. Those living in the most socially fragmented parts of the country appeared more likely to have elevated risk of suicide and have a serious mental illness. There was substantial variation in health outcomes across England with large disease clusters indicating that some areas experience higher levels of health inequality. Conclusions Neighbourhood level contextual factors can provide useful information to policy makers and commissioners who aim to tackle inequalities in health at the local area level. To understand the complex spatial patterning of health and address health inequalities it is likely that a combination of strategies and interventions is needed. The methods outlined in this thesis can be particularly useful as they can be applied across a range of health care settings. The socioeconomic environments in which individuals live are prominently modifiable by policy, thus social and economic interventions may have a potential positive impact on health.