Using crowdsourced data to assess the relationship between neighbourhood-level deprivation and the availability of inclusive leisure programmes in Canadian cities

Abstract

ABSTRACT Monitoring neighbourhood-level access to resources can inform improved urban health. Big data approaches have shown some promise in capturing access to spatial resources such as green spaces, housing, amongst others. However, it is often difficult to capture resources that are not spatially observable such as programmes. For this project, we linked data from a digital listing of inclusive leisure programmes to data on neighbourhood-level deprivation, to explore the relationship between both factors, and how to strengthen approaches for capturing access to health-promoting programmes. Using cross-sectional secondary data analysis, we linked information on material and social deprivation levels in three major census metropolitan areas of Canada to information on the availability of adaptive leisure programmes as listed on the Jooay App (www.jooay.com). Higher availability of inclusive leisure programmes was directly linked to higher social deprivation and inversely linked to higher material deprivation. Inclusive leisure programmes were more available for populations with physical and intellectual impairments and autism spectrum disorders, than sensory and behavioural challenges. Our study suggests potentially differing relationships between forms of deprivation and the availability of inclusive programs and a need for stronger consideration of disability diversity. We also note considerations for using big data to inform urban health.