Development of a neighborhood drivability index and its association with transportation behavior in Toronto.

BACKGROUND
Car driving is a form of passive transport that is associated with an increase in physical inactivity, obesity, air pollution and noise. Built environment characteristics may influence transport mode choice, but comprehensive indices for built environment characteristics that drive car use are still lacking, while such an index could provide tangible policy entry points.


OBJECTIVE
We developed and validated a neighbourhood drivability index, capturing combined dimensions of the neighbourhood environment in the City of Toronto, and investigated its association with transportation choices (car, public transit or active transport), overall, by trip length, and combined for residential neighbourhood and workplace drivability.


METHODS
We used exploratory factor analysis to derive distinct factors (clusters of one or more environmental characteristics) that reflect the degree of car dependency in each neighbourhood, drawing from candidate variables that capture density, diversity, design, destination accessibility, distance to transit, and demand management. Area-level factor scores were then combined into a single composite score, reflecting neighbourhood drivability. Negative binomial generalized estimating equations were used to test the association between driveability quintiles (Q) and primary travel mode (>50% of trips by car, public transit, or walking/cycling) in a population-based sample of 63,766 Toronto residents enrolled in the Transportation Tomorrow Survey (TTS) wave 2016, adjusting for individual and household characteristics, and accounting for clustering of respondents within households.


RESULTS
The drivability index consisted of three factors: Urban sprawl, pedestrian facilities and parking availability. Relative to those living in the least drivable neighbourhoods (Q1), those in high drivability areas (Q5) had a significantly higher rate of car travel (adjusted Risk Ratio (RR): 1.80, 95%CI: 1.77-1.88), and lower rate of public transit use (RR: 0.90, 95%CI: 0.85-0.94) and walking/cycling (RR: 0.22, 95%CI: 0.19-0.25). Associations were strongest for short trips (<3 km) (RR: 2.72, 95%CI: 2.48-2.92), and in analyses where both residential and workplace drivability was considered (RR for car use in high/high vs. low/low residential/workplace drivability: 2.18, 95%CI: 2.08-2.29).


CONCLUSION
This novel neighbourhood drivability index predicted whether local residents drive or use active modes of transportation and can be used to investigate the association between drivability, physical activity, and chronic disease risk.


Background:
This study aimed to determine which neighbourhood-and individual-level characteristics were associated with car driving in adults of five urban areas across Europe, and to determine the percentage of variance in car driving explained by characteristics at both levels.

Methods:
Neighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n = 4,258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model.

Conclusions:
Residential density and land-use mix were consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual-and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas.

Key messages:
Both individual and neighbourhood level characteristics contributed equally to explained variation in car driving, across Europe. Higher residential density and land-use mix are consistently associated with lower care use.

Background:
To develop and validate a drivability index for the City of Toronto and examine its association with transportation mode choice.

Methods:
We used exploratory factor analysis to derive distinct factors (clusters of one or more environmental characteristics) that reflect the degree of car dependency in each neighborhood, drawing from candidate variables that capture density, diversity, design, destination accessibility, distance to transit, and demand management. Area-level factor scores were then combined into a single composite score, reflecting neighborhood drivability. Negative binomial generalized estimating equations were used to test the association between driveability quintiles (Q) and primary travel mode (>50% of trips by car, public transit, or walking/cycling) in a population-based sample of 63,766 Toronto residents enrolled in the Transportation Tomorrow Survey (TTS), adjusting for individual and household characteristics, and accounting for clustering of respondents within households.

Results:
The drivability index consisted of three factors: Urban sprawl, pedestrian facilities and parking availability. Relative to those living in the least drivable neighborhoods (Q1), those in high drivability areas (Q5) had a significantly higher rate of car travel (adjusted rate ratio (

Conclusions:
This novel neighborhood drivability index predicted whether local residents drive or use active modes of transportation and can be used to investigate the association between drivability, physical activity, and chronic disease risk.

Key messages:
The association between neighborhood drivability and car use was strongest for short trips. The drivability of the neighborhood where people work is a strong determinant of car use.
Urban green infrastructure size, quality and proximity and health outcomes in older populations