The land cover paradox: Characteristics of blue- and green spaces within and beyond high-risk suicide clusters

Abstract

Purpose

Urban suicide rates are rising, with disproportionate impacts on communities of color. While social determinants of suicide are well-established, the role of overlapping social, natural, and built environments remains underexamined.

Methods

We integrated National Land Cover Database (NLCD) data on developed open space, tree canopy, blue space, and a novel measure of land cover diversity with indicators of tree and park equity, built environment features, and socioeconomic vulnerability. Bayesian spatial Poisson models were used to estimate associations between these socioenvironmental variables and suicide risk at the Census Block Group (CBG) level in Chicago. We also identified and compared spatial clusters of high and low suicide risk using Local Moran's I.

Results

Blue space and developed, open spaces were associated with reduced suicide risk, with estimated decreases of 17.9 % and 15.1 %, respectively. In contrast, greater land cover diversity was associated with a 32.1 % increase in suicide risk. Suicide risk exhibited spatial structuring, with nearly half of the total variance explained by between-CBG differences (γ = 0.4971). Although spatial variability was modest (σS = 0.0214), suicide deaths were significantly clustered, with 261 spatial clusters identified—59 high-risk and 202 low-risk (p < 0.05). Socio-environmental characteristics differed significantly across cluster types, indicating that place-based exposures intersect with population-level vulnerabilities to shape suicide risk.

Conclusions

The findings reveal that the mental health impacts of environmental features are context-dependent and spatially patterned. While access to green and blue space may offer protective effects, these benefits are not uniformly experienced across urban neighborhoods. Suicide prevention efforts should consider not only individual and socioeconomic risk factors, but also spatial disparities in environmental quality and neighborhood-level disadvantage.