Using a Complex Systems Approach to Understanding Population Mental Health.

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There is a growing consensus that it is not just individual characteristics and behaviours that influence health and wellbeing, but the types of neighbourhoods we live in, and the opportunities they afford us. This consensus is reflected by published evidence of inequalities in people's life chances between different places, the Marmot review "Fair Society Healthy Lives" demonstrates by association that neighbourhoods that are more deprived also tend to have populations with lower life expectancies.The overall evidence for neighbourhood effects is somewhat limited, only recently has research begun to demonstrate an unambiguous association between neighbourhood and health. Health outcomes and behaviours studied have particularly focused on diet and physical activity, which have been linked to a range of neighbourhood contextual factors including access to green space, places to buy fresh fruit and vegetables (or conversely fast-food), and the 'walkability' of the built environment. Mental health and wellbeing has received markedly less focus, although some high quality studies have looked at the relationship between neighbourhood green space and wellbeing. Emerging epidemiological evidence has benefitted from researchers working across disciplines, particularly with geographers, in order to produce robust study designs. Nonetheless, evidence of a causal link between our changing neighbourhoods, and our changing health is rather less forthcoming, owing to the complexity of the social-ecological processes hypothesised to be taking place.This research project aims to make a significant contribution to empirical evidence for neighbourhood effects by applying 'systems thinking.' This means treating neighbourhoods as complex, dynamic multi-factorial processes, where existing research treats them as simple, stationary snapshots with limited depth. Specific training in 'Urban Informatics' will greatly augment my existing expertise in Geographic Information Science and Social Epidemiology, and give me the tools required to operationalise dynamic, rather than static, representations of neighbourhoods. Capturing how neighbourhoods change over time alongside how individuals change over time is fundamental to unpicking causality.In particular, the research will focus on the effects on mental health and wellbeing of people moving, expecting to move, or preferring to move, at both the neighbourhood scale, and the individual scale. We know that neighbourhoods are not equal, and yet in terms of population movement - people moving into or out of a neighbourhood - we tend to treat them equally. Studies have suggested that failing to account for this dynamic neighbourhood process - the residential movement of people - can have implications on our expectations for people's health through what are termed 'selection effects'. These neighbourhood compositional factors will be studied alongside contextual aspects of neighbourhoods, notably neighbourhood crime and disorder and neighbourhood economic insecurity, in order to explain how mental health and wellbeing is affected by neighbourhood social and environmental changes.This type of research is only just becoming possible, due to a range of complementary factors. Firstly, world-class training at New York University's Centre for Urban Science and Progress (NYU CUSP). Secondly, the availability of the UK's rich longitudinal "Understanding Society" survey data. Thirdly, the proliferation of open, and free government administrative data, and finally, the growing support from research councils in promoting 'Big Data' and informatics approaches. This fellowship takes advantage of all of these factors, with the hope of producing world-leading research on neighbourhoods and health.