Walkability, Cycling Infrastructure, and Chronic Disease: A Neighbourhood-Level Analysis of Integrated Care Needs in Toronto

Background: Toronto has faced a policy debate about removing bike lanes to reduce traffic congestion. This study examines the relationship between neighbourhood walkability, cycling infrastructure, and chronic disease rates across 69 Toronto neighbourhoods.

 

Method: This study used two publicly available datasets: (1) neighbourhood health indicators from the Ontario Community Health Profiles Partnership (2021-22 data), including age-standardized rates of diabetes, hypertension, and asthma, plus socioeconomic indicators (material deprivation index quintiles, racialized/newcomer population quintiles, age/labour force participation, emergency department use rates, and primary care attachment rates); and (2) Walk Score® (a website that rates the walkability, transit access, and bikeability of specific addresses and neighbourhoods on a 0–100 scale).

 

Multiple regression analyses examined associations between active transportation infrastructure and chronic disease rates, both unadjusted and adjusted. Interaction terms tested whether cycling infrastructure provides more benefits in low-walkability neighbourhoods. Analyses were conducted in jamovi (v2.7; open-source).

 

Results: Unadjusted correlations showed walkability inversely associated with diabetes (r = -0.51) and hypertension (r = -0.62), but minimal association with asthma (r = -0.13). After adjusting for confounders, material deprivation emerged as the dominant predictor, 15-23× stronger than walkability (adjusted R² = 84-89%). However, modest independent effects persisted: each 10-point Walk Score increase was associated with 0.71 percentage point (pp) lower diabetes rate and 1.07 pp lower hypertension rate. Bike Score showed similar patterns.

 

Interaction analyses found that cycling infrastructure provided slightly more protection in car-dependent neighbourhoods (diabetes: -0.20 pp extra per 10 points; hypertension: -0.13 pp extra).

Applied to real-world scenarios, a 50% improvement in Bike Score across Toronto's 10 lowest-walkability neighbourhoods (combined population 221,000) could prevent approximately 1,680 diabetes cases and 2,270 hypertension cases with estimated annual healthcare savings of 32 million Canadian dollars.

Implications: This research provides evidence-based context for transportation policy debates.

1) Neighbourhood walkability and cycling infrastructure should be considered in population health planning, especially for cardiovascular conditions.

2) Communities with low walkability may benefit disproportionately from cycling infrastructure investment.

3) Addressing material deprivation, housing, and healthcare access will have a much bigger impact than built environment interventions alone.

 

This study has important limitations that should be considered. Since it is a cross-sectional analysis, it demonstrates association, not causation so we should be careful attributing disease rates to infrastructure. Also, residual confounding may exist even after adjusting for multiple socioeconomic and health factors. Walk Score® data was not available for all of Toronto's neighbourhoods, which may impact estimates and reduce generalizability. Real-world impact of new bike lanes faces challenges including weather, safety concerns, and the need for sustained behaviour change. Even with limitations, this research can inform policy discussions

 

Importantly, this work demonstrates the democratization of health research. Both datasets used are freely accessible online. The analysis was conducted by a high school student using free open-source user friendly online statistical tools. Ordinary citizens can now use open data and research tools to advocate for evidence-informed policies affecting their communities. Integrated care strategies will benefit from empowered community members who can participate meaningfully in health policy debates.