Suchergebnisse

In 2003, 'Neighborhoods and Health' codified the idea that a neighbourhood's social and physical makeup can influence the health of people who live in it. More than a decade later, with the relationship between place and health firmly entrenched at the centre of how we understand public health (and as its own scientific discipline, spatial epidemiology), this second edition of the landmark text offers another giant leap forward for the field.

AbstractThe racial/ethnic and income composition of neighborhoods often influences local amenities, including the potential spatial distribution of trees, which are important for population health and community wellbeing, particularly in urban areas. This ecological study used spatial analytical methods to assess the relationship between neighborhood socio-demographic characteristics (i.e. minority racial/ethnic composition and poverty) and tree density at the census tract level in Boston, Massachusetts (US). We examined spatial autocorrelation with the Global Moran'sIfor all study variables and in the ordinary least squares (OLS) regression residuals as well as computed Spearman correlations non-adjusted and adjusted for spatial autocorrelation between socio-demographic characteristics and tree density. Next, we fit traditional regressions (i.e. OLS regression models) and spatial regressions (i.e. spatial simultaneous autoregressive models), as appropriate. We found significant positive spatial autocorrelation for all neighborhood socio-demographic characteristics (Global Moran'sIrange from 0.24 to 0.86, allP=0.001), for tree density (Global Moran'sI=0.452,P=0.001), and in the OLS regression residuals (Global Moran'sIrange from 0.32 to 0.38, allP<0.001). Therefore, we fit the spatial simultaneous autoregressive models. There was a negative correlation between neighborhood percent non-Hispanic Black and tree density (rS=−0.19; conventionalP-value=0.016; spatially adjustedP-value=0.299) as well as a negative correlation between predominantly non-Hispanic Black (over 60% Black) neighborhoods and tree density (rS=−0.18; conventionalP-value=0.019; spatially adjustedP-value=0.180). While the conventional OLS regression model found a marginally significant inverse relationship between Black neighborhoods and tree density, we found no statistically significant relationship between neighborhood socio-demographic composition and tree density in the spatial regression models. Methodologically, our study suggests the need to take into account spatial autocorrelation as findings/conclusions can change when the spatial autocorrelation is ignored. Substantively, our findings suggest no need for policy intervention vis-à-vis trees in Boston, though we hasten to add that replication studies, and more nuanced data on tree quality, age and diversity are needed.