Abstract

Significant differences in health status between inhabitants of different commune types of the Geneva area have recently been established in a study relying on a large health database managed by the Unit of Population Epidemiology of the Hôpitaux Universitaires de Genève (HUG). For instance, the mean Body Mass Index is lower in richer communes than in other urban areas. Moreover, suburban residents and commuting populations have a higher hypertension prevalence than other communities. Though socio-economic status appears to be an essential driver for quality of life and health, specific knowledge is lacking to define which variables are of main concern. Besides, the relationship between socio-economic conditions and neighbouring living environment is only implicit. The objective of the present study is to detail the spatial differences coarsely observed previously. More particularly, it aims to determine to which extent landscape indicators are related to health risk factors and to identify areas where prevalence of health risk factors is potentially high on a fine scale basis. The study reuses the “Bus santé” database containing health-related information for more than 10'000 participants collected since 1998.Stratified sampling by age and by gender was used for the survey to be representative of the population. Samples were geocoded so that they can be analysed in a Geographic Information System (GIS). The Geneva canton has been divided into some 1600 homogeneous zones called Microregions based on the number of inhabitants, jobs, buildings and dwellings. Demographic, socio-economic and landscape variables such as the proportion of built-in surface and volume or the Shannon land use diversity index inform each of the Microregions. Significant factors characterising them are identified using factor analysis in order to make a spatial typology. A multiple regression is applied to assess the relationship between a set of health variables (including blood pressure and hypertension, glucose level and diabetes) from the sampled individuals contained within the Microregions and the factors describing these. Results of this fine scale analysis show the importance of income and socio-cultural membership as primary variables related to lifestyle and potential health status. The chosen landscape composition and structure variables come as complementary explanatory factors of neighbourhood counting for well-being or on the contrary stress-related illness. As an environmental health research, this study directly contributes to address land planning issues and inform on how landscape design potentially impacts quality of life and population health. Moreover, it serves to identify spatial types where risk factors are high and locate them in the geographical space.

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