Exploring the Impact of Active Transport Amenities on Lifestyle-Related Health Risks
TRB 2026 poster. Click to open the full-resolution version.
At a glance
- Question: Are walking and cycling amenities linked to diabetes, and through what pathway?
- Data: 32 local government areas (LGAs) in Victoria, Australia, combining OpenStreetMap, the VISTA travel survey, and PHIDU health data
- Method: Partial least squares structural equation modeling (PLS-SEM) with mediation analysis
- Finding: No direct effect. Amenities matter for health through behaviour: more active travel → lower health risks → lower diabetes prevalence.
- Presented: Poster session, TRB 105th Annual Meeting, Washington, D.C., January 2026
Motivation
Type 2 diabetes is strongly tied to physical inactivity, and active transport is one of the few ways cities can build physical activity into everyday life. Many studies link the built environment to physical activity, or to health outcomes, but few model the full chain between them empirically. Existing pathway frameworks (e.g., Frank et al., 2019) remain largely conceptual.
This study tests that chain quantitatively, and it uses objective amenity measures instead of the self-reported perceptions common in prior work.
Approach
Building on the behavioural pathway in Frank et al. (2019), I modeled four linked constructs:
| Construct | Indicators | Source |
|---|---|---|
| Active Transport Amenities | Density of footpaths, bicycle lanes, recreational opportunities, rest areas, and safety features | OpenStreetMap (Overpass) |
| Active Transport Usage | Daily active travel time: elderly, working-age, and total | VISTA |
| Health Risks | Obesity rate, psychological distress rate | PHIDU |
| Physical Health | Diabetes prevalence | PHIDU |
I chose PLS-SEM over covariance-based SEM because it handles small samples and non-normal data. Both apply at the LGA level (n = 32). Models were estimated in SmartPLS 4. A second specification controls for the share of elderly residents to check for confounding by age.
Key Findings
- Amenities → active travel. LGAs with denser walking and cycling amenities show substantially more active travel (β = 0.63, p < .001).
- Active travel → health risks. More active travel is associated with lower obesity and psychological distress (β = −0.27, p = .012; −0.41 after controlling for age).
- Health risks → diabetes. Health risks strongly predict diabetes prevalence (β = 0.61, p < .001).
- Indirect-only mediation. The direct path from amenities to diabetes is not significant (β = −0.05, p = .84), but the sequential indirect path is (β = −0.107, 95% CI [−0.234, −0.017]).
Why it matters: Walking and cycling infrastructure is unlikely to improve health on its own. Its benefit depends on whether people actually use it. This supports the WHO’s call to invest in walking and cycling, and suggests planners should evaluate amenities by the behaviour they generate, not just by how much is built.
Limitations & Next Steps
This is an ecological, cross-sectional analysis of 32 areas, so the results describe area-level pathways rather than individual causal effects. Next steps I’m interested in: individual-level and longitudinal data, and additional mediators such as perceived safety, social cohesion, and accessibility.
My Role
First author. I conceptualized the study, developed the conceptual model and hypotheses, collected and processed the OpenStreetMap amenity data, specified and estimated the PLS-SEM models, and wrote the original draft. Co-authors supervised the work and contributed data curation (Y. Wang) and review and editing (both).