Abstract

OPS 30: Green space and morbidity, Room 110, Floor 1, August 27, 2019, 1:30 PM - 3:00 PM Background/Aim: The evidence of a relationship between green spaces and self-perceived health is moderate and the socioeconomic inequalities underlying this relationship remain unclear. We assessed the relationship between green spaces and self-perceived health in the Brussels Capital Region (BCR) in Belgium, examining whether patterns of association differ according to the intersection between age, gender, socioeconomic status and migrant background. Methods: Information on socioeconomic indicators, perceived green quality and self-perceived health of all registered population in Belgium is available at the individual level from the 2001 Belgian Census. We included 496,450 individuals older than 15 and living in BCR in 2001. Quantity of green (percentage of green spaces within a 600m buffer), obtained from the 2006 CORINE Landcover dataset, and 2015 mean annual concentrations of PM10 were available at the statistical ward level. Multilevel logistic regression models were conducted to obtain adjusted odds ratios (aOR) and their confidence intervals (95%CI) of the association between the quantity and quality of green spaces and poor self-perceived health. Models were adjusted by age, PM10, gender, socioeconomic status, migrant background, neighbourhood socioeconomic indicators and area of the statistical ward. Interaction and stratification analyses were then performed by age, gender, educational level and migrant background. Results: We found an inverse association between good perceived green quality and poor self-perceived health (aOR: 0.78, 95%CI: 0.76–0.79) consistent across different population groups. Quantity of green spaces was not related to poor self-perceived health after adjusting by neighbourhood socioeconomic indicators. Greater odds of reporting poor self-perceived health when living in greener areas was found among women (aOR: 1.02, 95%CI: 1.00–1.04), the lower educated and the Turkish (aOR: 1.16, 95%CI: 1.04–1.29). Conclusions: The unexpected results might be related to specific spatial distribution of socioeconomic inequalities within the BCR. Further analyses including other urban agglomerations in Belgium may help understand our results.

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