The association of the built environment with how people travelled to work in Halton Region in 2006:

Transcription

1 The association of the built environment with how people travelled to work in Halton Region in 2006: a geographical area level analysis Halton Region Health Department September

2 Author Fabio Cabarcas, Senior Policy Analyst, Chronic Disease Prevention, Health Department, Halton Region Acknowledgements Dr. Monir Taha, Associate Medical Officer of Health and Director of Chronic Disease Prevention and Oral Health, Health Department, Halton Region Helen Ross, Manager Chronic Disease Prevention, Health Department, Halton Region Emma Tucker, Senior Epidemiologist, Health Department, Halton Region (peer review and methodological advice) Kendra Willard, Health Promoter, Chronic Disease Prevention, Health Department, Halton Region (peer review) Ahalya Mahendra, Epidemiologist, Public Health Capacity and Knowledge Management, Public Health Agency of Canada (external peer review) 2

3 Table of Contents List of Figures... 4 List of Tables... 4 Executive summary INTRODUCTION... 6 Background 6 About this report 6 Overview of Methodology 6 Report structure and highlights of main findings 7 2. WALKING OR CYCLING TO WORK AND BUILT ENVIRONMENT... 8 Walkability, land-use mix and active commute 9 Intersection density and active commute 9 Cycling and walking separately 9 3. PRIVATE MOTOR VEHICLE COMMUTE AND BUILT ENVIRONMENT Walkability, land-use mix, proximity to transit and lower private motor vehicle commute 12 Effect of proximity to transit on walkability and private motor vehicle use TRANSIT COMMUTE AND BUILT ENVIRONMENT (Burlington and Oakville) Higher walkability and commute by transit 14 Proximity to transit and commute by transit 14 Commute by transit and the combination of proximity to transit and walkability 14 Income quintile areas and transit to work use DISCUSSION Built environment features associated with travel to work mode in Halton Region 16 Older age and income: key characteristics that need further analysis 16 Residential density combined with land-use mix and connectivity 16 Safe cycling infrastructure 16 Halton as a relatively homogeneous suburban community 17 Main limitations CONCLUSION A1. APPENDIX 1. GLOSSARY OF TERMS A2. APPENDIX 2. DETAILS OF METHODOLOGICAL APPROACH A3. APPENDIX 3. DESCRIPTIVE OVERVIEW OF DATA A4. REFERENCES

4 List of Figures Figure 1. Percentages of residents aged 15 and over who walked or cycled to work and walkability, land-use mix and intersection density in urban dissemination areas with at least some active commute, Halton Region, Figure 2. Percentage of urban dissemination areas according to whether at least some residents aged 15 or older cycled or walked to work, by land-use mix and walkability factor, Halton Region, Figure 3. Percentage of urban dissemination areas according to their percentage of residents aged 15 or older who walked or cycled to work by walkability and land-use mix category, Halton Region, Figure 4. Percentages of residents aged 15 and over who used private motor vehicles to go to work by walkability, land-use mix and intersection density in urban dissemination areas, Halton Region, Figure 5. Percentage of residents aged 15 and over who commuted to work as drivers or passengers of private motor vehicles, by proximity to transit stops, in urban dissemination areas, Halton Region, Figure 6. Percentage of residents aged 15 and over who commuted to work in private motor vehicles and the proportion of population within 400 meters of a transit stop, by walkability, in urban dissemination areas, Halton Region, Figure 7. Percentages of residents aged 15 and over who commuted by public transit by walkability and proximity to transit stops, urban dissemination areas, Burlington and Oakville, Figure 8. Percentage of residents aged 15 and over who commuted by public transit and walkability, by proportion of residents in proximity to transit stops, urban dissemination areas, Burlington and Oakville, Figure 9. Percentages of residents aged 15 and over who commuted by public transit by income quintiles, urban dissemination areas, Burlington and Oakville, List of Tables Table 1. Definition and data source of outcome, explanatory and confounding variables Table 2. High and potential multicollinearity cases and methodological approach to address them Table 3. Five point distribution summary of the main variables in the analysis, urban dissemination areas, Halton Region, Table 4. Frequency distribution of urban dissemination areas according to income quintile (QAIPPE), Halton Region, Table 5. Frequency distribution of urban dissemination areas according to their percentage of active transportation to work, Halton Region,

5 Executive summary The purpose of this report was to determine if the literature on built environment and associated transportation modes applies to Halton Region, which has traditionally been a relatively suburban region characterized by its low density as compared to some of its surrounding areas. This is important because it provides the first known local evidence about community features previously identified in academic research as likely to support increased active transportation (e.g. walking or cycling) and transit use. Walking, cycling and public transit use can further contribute to the prevention of the leading causes of mortality in the Halton Region: cancer, heart disease and stroke. Within this context, the objective of this report was to assess the association between built environment features and the use of walking or cycling, private motor vehicle or public transit to travel to work in urban dissemination areas in the Halton Region in A descriptive area level analysis of urban dissemination area data was conducted. The 2006 percentages of residents aged 15 years and over using different modes of transportation to commute to work i was compared to selected built environment variables (2007 and 2010). ii Factor analysis was conducted to obtain a summary factor for land-use mix (summarizing residents proximity to 16 diverse uses) and walkability (combining population density, land-use mix and intersection density). A total of 601 urban geographical units (Census dissemination areas) in Halton Region were used for active transportation and private motor vehicle use models. Analysis of transit use to work was performed only in Burlington and Oakville because other areas did not have a comparable transit system in Logistic and multiple linear regression models were used to examine associations, including assessment of income quintile and the age profile of the areas as confounding variables. The results found significant associations between: more walkability and 1. more walking or cycling to work (Halton Region) 2. lower private motor vehicle use to commute (Halton Region) 3. higher use of public transit to commute (Burlington and Oakville) - Subgroup analysis also showed that only in areas where at least 80% of the population lived in proximity to transit, walkability was associated with lower private motor vehicle and higher transit use. more land-use mix and o more walking or cycling to work (Halton Region) o lower private motor vehicle use to commute (Halton Region) more residents within 400 meters of transit stops and o lower private motor vehicle use to go to work (Halton Region) o higher use of public transit to commute (Burlington and Oakville) more intersection densities and o more walking or cycling to work in areas where at least some walking and cycling occurred - Subgroup analysis also showed significance only in areas where land-use mix was above the median. The findings above were statistically significant even when controlling for potentially confounding variables, which included other built environment features, area income quintile and population age profiles for young and older adults. The results are consistent with associations reported in research conducted in other jurisdictions, in particular suggesting that at a geographical level built environment features such as higher walkability, land-use mix, connectivity and proximity to transit stops were associated with increased active transportation, decreased private motor vehicle use and increased public transit use for transportation to work. i Statistics Canada. (2007). Halton Regional Health Unit, Ontario (Code3536) (table) Community Profiles Census. Statistics Canada Catalogue no XWE. Ottawa. Released March 13, ii Data from GIS section within Halton Region s Planning Services or

6 1. INTRODUCTION Background Replacing private motor vehicle trips with sustainable transportation modes such as walking, cycling and public transit use can contribute to the prevention of the leading causes of mortality in Halton Region: cancer, heart disease and stroke. 1, 2 Over the last few decades, there has been an increasing amount of international research literature reporting associations between sustainable transportation modes and built environment features such as higher land-use mix, higher residential density, proper infrastructure for cycling and walking and other design features. Reviews of the literature have found enough weight of evidence in favor of supportive land use policies. 3, 4 Building on public health evidence, the Halton Region Health Department had in 2007 and 2009 already identified the importance of promoting communities supportive of transit and active transportation, defined as any form of human-powered transportation, including walking and cycling. This entails adequate densities, landuse mix, and design features such as connected streets with sidewalks and cycling infrastructure. 5 The Ontario Chief Medical Officer of Health 2013 strategic plan also included the development of supportive built environments as one of its collective areas of focus and goals to promote physical activity, improve air quality, reduce injuries and promote healthy living. 6 Analysis of the Canadian population 7 and in other local jurisdictions, including the City of Toronto 8, 9, 10 and Peel Region, 11 has shown consistent results with the literature on that supportive built environment features are associated with increased active transportation modes. Given that Halton Region has traditionally been a suburban region with relative low density, this report is important because it uses the best available information to provide local evidence in favour of the applicability of this research literature to the Halton Region context. About this report The objective of this report was to assess the association between built environment features and the use of active transportation, private motor vehicle or public transit to travel to work in urban dissemination areas in the Halton Region in The report summarized the descriptive analysis of urban dissemination area level data according to their 2006 percentages of residents aged 15 years and over using different modes of transportation to commute to work and selected built environment variables ( ). Overview of Methodology Detailed methods are described in Appendix 2. Some highlights of the methodology include: The geographical level analysis used all 601 Census 2006 urban dissemination areas identified in Halton Region. A dissemination area is the smallest standard geographic area for which all census data are disseminated, and generally has 400 to 700 residents. 12 An area was defined as urban if having a minimum population density of 400 people per square kilometre. 13 The analysis included the Halton Region s four local municipalities: Halton Hills, Milton, Oakville, and Burlington. For transit analysis, only data from Oakville and Burlington was considered as their municipal transit systems were better developed in Outcome and confounding variables were calculated using 2006 Census of Canada information. 14 Outcome variables included the main mode of transportation to commute to work of employed labour force 15 years and over (i.e. area percentages of residents who reported using cycling or walking, public transit or private motor-vehicles). 14 Confounding variables included the percentage of residents aged 65 and over, the percentage of residents aged 15 to 24 in dissemination areas and QAIPPE income group (the quintile of annual income per person equivalent for each dissemination area as calculated by Statistics Canada). 6

7 Built environment (explanatory) measures were identified from the literature and adapted according to local data availability and feasibility, 15, 16 with details available in Appendix 2. Measures included: o Residents by total area in square kilometers by dissemination area (source: Census 2006 data). o Number of intersections per square kilometer (source: GIS section within Halton Region s Planning Services, 2010). o Percentage of residential population within 400m Transit Stops (source: GIS section within Halton Region s Planning Services, 2010). o Percentage of residential population 1500m Elementary Schools (source: GIS section within Halton Region s Planning Services, 2010). o Land-use mix: Common factor of proportion of residents in proximity to 16 diverse uses. Factor analysis, a statistical technique commonly used for data reduction purposes, was conducted to obtain the single latent factor that best explained their distribution (source: calculated from data by the GIS section within Halton Region s Planning Services, 2010). iii o Walkability: Common factor of residential density, land-use mix and intersection density (factor analysis calculated from data by the GIS section within Halton Region s Planning Services, 2010). iv o Km of bike paths by square kilometer (GIS section within Halton Region s Planning Services, 2007). Unfortunately, at the time of this analysis, there were no readily available data sources for job densities, sidewalks, transit routes and frequency, and proximity to open spaces and parks. Consistent with common research practice, an alpha value of 0.05 was used to assess statistical significance. Ordinal logistic regression was used for outcome variables with low percentages and high number of zeros (i.e. proportion of residents who used active walked or cycled to work). Multiple linear regression was used to model private motor vehicle, transit use, and active commute to work in areas with values above zero. All model assumptions were tested, including multicollinearity, a common issue with observational data in which the explanatory variables are associated among themselves. Variables with high multicollinearity (land-use mix with intersection density; proximity to a transit stop with local municipality) were not tested simultaneously to avoid errors in the analysis. For other cases in which multicollinearitiy was suspected, models with and without the associated variables were developed to assess their stability and consistency. Report structure and highlights of main findings This report represents the first known geographical area analysis of built environment and transportation patterns in Halton Region. With additional details in the appendices, the sections below provide further support to the following associations found in the literature: higher levels of walking and cycling to go work were associated with living in neighbourhoods with higher walkability, land-use mix, and intersection density. lower percentage of private motor vehicle commute was associated with higher walkability, land-use mix and proportion of residents within 400 meters of a transit stop. higher percentages of transit commute to work in Burlington and Oakville were associated with higher walkability and a higher proportion of residents in proximity to transit. iii Factor loadings are the weights and correlations between each original variable and the common factor (variables better represented by a factor will have a higher load). The land-use mix loadings were appropriate according to common research practices: % residents 400m Grocery Stores=0.74; % residents 400m Convenience Stores=0.64; % residents population 800m Postal Services=0.65; % residents 800m Merchandise Stores=0.64; % residents 800m Apparel and Accessory Stores=0.80; % residents 800m Home Furniture, Furnishings and Equipment Stores=0.79; % residents 800m Eating and Drinking Places=0.80; % residents 800m Miscellaneous Retail=0.85; % residents 800m Depository Institutions=0.71; % residents 800m Amusement and Recreation Services=0.70; % residents 800m Health Services=0.76. A well-known approach to obtain non-correlated factors was adopted (i.e. Varimax rotation). Factor eigenvalue = 8.2 (better above 1). iv Factor loadings as follows: residential density= 0.81; land-use mix= 0.64; intersection density= Factor eigenvalue =

8 2. WALKING OR CYCLING TO WORK AND BUILT ENVIRONMENT The use of walking or cycling to go to work, also referred to as active commute in this report, is a form of active transportation, defined as any human-powered transportation (usually for non-recreational purposes). Active commute is measured in this report as the proportion of residents aged 15 or over who reported either walking or cycling to work in Research literature has associated higher active transportation with built environment factors such as higher walkability (usually measured as a combination of residential density, land-use mix and street connectivity), 8, 10, 17, 18, 19 land-use mix (usually measured as proximity to points of interest or ratios of land use types), 10, 18, 20, 21 street connectivity (usually measured as intersection density), 8, 18, 22 proximity to transit, 7, 10 higher population densities, 23 and safe active transportation infrastructure (e.g. kilometers of 8, 24, 25, 26 sidewalks or cycling facilities). A Summary of significant results consistent with research in other jurisdictions In 2006, urban areas with higher percentage of walking or cycling to work, or active commute, were associated with: higher walkability (Figure 1A). more land-use mix (Figure 1B) more intersection density in areas where at least some active transportation occurred (i.e. with higher land-use mix) (Figure 1C). These associations were significant even when other factors such as age, income quintile and other built environment variables were held constant. B C Figure 1. Percentages of residents aged 15 and over who walked or cycled to work and walkability, land-use mix and intersection density in urban dissemination areas with at least some active commute, Halton Region, 2006 Figure notes: - Walkability: land use walkability factor (land-use mix, population density and intersection density). - Land-use mix: common factor of proportion of residents in proximity to diverse uses of interest. - All associations in the figure are significant (p<0.05). Source: active transportation: Census 2006; Source built environment measures: GIS section within Halton Region s Planning Services and factor analysis. 8

9 Walkability, land-use mix and active commute The proportion of residents walking or cycling to work increased significantly as walkability and land-use mix also increased (p<0.05), even when all other variables were held constant (Figures 1, 2 and 3). Other variables associated with higher active commute were also areas with higher percentage of residents aged 65 and over and lower income (p<0.05). However, the association between active commute to work, walkability and land-use mix was still significant after adjusting for age and income. Individual level data is needed to better understand the active commute patterns according to age and income. No other built environment variables were significant, except for intersection density as described below. Burlington, Halton Hills, Milton and Oakville were not significantly different from each other. Furthermore, the associations remained, even after separating out the analysis by area profile of residents aged 65 and over, income, and intersection density in areas where with at least some walking or cycling to work (p<0.05). Intersection density and active commute Intersection density had a small but significant correlation with active commute in areas where at least some walking and cycling to work occurred, although it was not associated with whether areas had active commute or not. This association was significant even when other factors where accounted for (p<0.05). When examining within subgroups of areas, intersection density was significantly associated with active commute in all built environment, age, and income profile areas. The only exception was in areas of lower than median land-use mix, where no significant association was found (p>0.05). Cycling and walking separately For both cycling and walking taken separately, the general distribution of urban dissemination areas according to land use variables is for the most part consistent with the findings for active commute (cycling and walking together) (Figure 2). A B Figure 2. Percentage of urban dissemination areas according to whether at least some residents aged 15 or older cycled or walked to work, by land-use mix and walkability factor, Halton Region, 2006 Figure Notes: - Walkability: common factor of land-use mix, population density and intersection density. - Land-use mix: common factor of proportion of residents in proximity to diverse uses of interest. - For either walkability or land-use mix: low is the lowest third of the data and high is the highest third of ordered observations. - Black lines: 95% confidence limits. - Differences statistically significant for higher walkability and land use mix (p<0.05), with lower walkability and lower land-use mix as reference values. Source: active transportation: Census 2006; Source built environment measures: GIS section- Halton Region s Planning Services and factor analysis. 9

10 A B Figure 3. Percentage of urban dissemination areas according to their percentage of residents aged 15 or older who walked or cycled to work by walkability and land-use mix category, Halton Region, 2006 Figure Notes: - Walkability: common factor loading population density, land-use mix, and intersection density. - Land-use mix: common factor of proportion of residents in proximity to diverse uses of interest. - For either walkability or land-use mix: low is the lowest third of the data and high is the highest third of ordered observations. - Black lines: 95% confidence limits. - Significant associations for all groups (p<0.05) in land-use mix and walkability ordinal regression models, even when controlling by other variables. Source: active transportation: Census 2006; Source built environment measures: GIS section- Halton Region s Planning Services and factor analysis. 10

11 3. PRIVATE MOTOR VEHICLE COMMUTE AND BUILT ENVIRONMENT The use of private motor vehicle is assessed in this report as the proportion of residents aged 15 year old and over who travelled as a driver or passenger to work in 2006, which is sometimes referred to as private car commute. In general, higher private motor vehicle use has been associated in the literature with built environment factors such as: lower walkability (usually a combination of residential density, land use mix and street connectivity), 9 lower land-use mix (usually measured as proximity to points of interest or ratios of land use types), 18 lower population 18, 27, 28 densities, low street connectivity (usually measured as intersection density) 18, 28 and, although less consistently, poor availability of transit. 29 This report was unable to assess other factors quoted in the literature, such as availability of parking, 30, 31 job density, 27 gas prices or taxes, 32 road pricing and road capacity. 33 A. Summary of significant results consistent with research in other jurisdictions Areas with lower percentages of motor vehicle use were associated with: higher walkability, in particular in areas where 80% or more residents were within 400 meters of a transit stop (Figure 4. A). more land-use mix in proximity to residents (Figure 4. B). higher proportion of residents within 400 meters of a transit stop (Figure 4. C). These associations were significant even when other factors such as age, income quintile and other built environment variables were held constant. B C Figure 4. Percentages of residents aged 15 and over who used private motor vehicles to go to work by walkability, land-use mix and intersection density in urban dissemination areas, Halton Region, 2006 Figure notes: - Walkability: common factor loading population density, landuse mix, and intersection density. - Land-use mix: common factor of proportion of residents in proximity to diverse uses of interest. - % Pop. = % of population within 400 meters of a transit stop. - All associations in the figure are significant (p<0.05). Source: vehicle use: Census 2006; built environment measures: GIS section within Halton Region s Planning Services. 11

12 Walkability, land-use mix, proximity to transit and lower private motor vehicle commute Areas with low use of private motor vehicles to commute to work were significantly associated with having either higher walkability, higher landuse mix or higher proportion of residents within 400 meters of transit stops (p<0.05), even when other significant factors such as age and income quintile where held constant. While differences across Burlington, Halton Hills, Milton and Oakville were significant (p<0.05), analysis within each municipality also showed significant association between higher walkability or higher land-use mix areas and low private motor vehicle commute. The trend of lower levels of motor vehicle use with more residents in proximity to transit stops was also observed in analysis within Burlington, Halton Hills, Milton and Oakville, although it was only significant for Milton and Burlington (p<0.05). A lower number of observations and co-variation between proximity transit stops and municipality made it difficult to further assess municipal differences. Fewer motor-vehicle trips to work also occurred in very low income areas (quintiles 1 and 2 vs. quintiles 3-5) and areas with more residents aged 65 year old and over (p<0.05). However, income and proportion residents aged 65 year old and over were not significantly associated with motor vehicle travel when land-use mix was controlled for (p>0.05). Individual level data are needed to fully assess the impact of age and income in motor vehicle use. Effect of proximity to transit on walkability and private motor vehicle use There was evidence to suggest that having more than 80% of population in proximity to transit favoured walkability s association with lower private motor vehicle use to go to work. In effect, in subgroup analysis in areas where the proportion of residents within 400 meters of transit stops was below 80%, the association between higher walkability and lower motor vehicle use was not significant (p>0.05). However, in areas where 80% or more of the population was close to a transit stop, the association between walkability and lower private motor vehicle use was significant and stronger (p<0.05) (Figure 5). By contrast, a higher proportion of residents in proximity to transit was associated with low use of private motor vehicle commute regardless of the walkability level. This was demonstrated in subgroup analysis within lower, medium and higher walkability areas (p<0.05) (Figure 6). Figure 6. Percentage of residents aged 15 and over who commuted to work in private motor vehicles and the proportion of population within 400 meters of a transit stop, by walkability, in urban dissemination areas, Halton Region, 2006 Figure 5. Percentage of residents aged 15 and over who commuted to work as drivers or passengers of private motor vehicles, by proximity to transit stops, in urban dissemination areas, Halton Region, 2006 Figure 5 and 6 notes: - % Pop. = % of population within 400 meters of a transit stop, categorized as <80% (249 observations) and >=80 (345 observations) in Figure 5. - Walkability: common factor loading population density, landuse mix, and intersection density. In figure 6, lower is the lowest third of the walkability scores, medium is the second third, and higher is the highest third of ordered walkability observations. - Solid line: significant association within subgroup (p<0.05). Source: private motor vehicle use to work: Census 2006; Source built environment measures: GIS section within Halton Region s Planning Services and factor analysis. 12

13 4. TRANSIT COMMUTE AND BUILT ENVIRONMENT (Burlington and Oakville) This section assesses the proportion of residents aged 15 and over who used public transit to cover the longest distance of their trip to work in 2006 (also referred to as transit commute). This analysis was conducted in Burlington and Oakville because other municipalities did not have comparable transit system at the time. Research literature in other jurisdictions has found associations between higher rates of transit use and higher residential densities, 34, 35 higher land-use mix (usually measured as proximity to points of interest or ratios of land use type), 18, 35 proximity to transit services, 18, 36 and street connectivity (usually measured as road intersection density). 18, 34 This report was not able to assess other factors referenced in the literature, 34, 35 such as frequency of service, fares 36 employment densities, 34 34, 37 and car ownership. A Summary of significant results consistent with research in other jurisdictions In 2006 in Burlington and Oakville, urban areas with higher rates of transit commute to work had a small but significant association with higher walkability, in particular in areas with more access to transit stops (Figure 7A). a higher proportion of residents within 400 meters of transit stops (unable to fully assess differences between Burlington and Oakville) (Figure 7B). These associations were significant even when other factors such as age, income quintile and other built environment variables were held constant. In effect, high transit use to go to work was similar in both the highest and the lowest income group areas. B Figure 7. Percentages of residents aged 15 and over who commuted by public transit by walkability and proximity to transit stops, urban dissemination areas, Burlington and Oakville, 2006 Figure notes: - Walkability: common factor loading population density, land-use mix, and intersection density. - % Pop. = % of population within 400 meters of a transit stop. - All associations shown in the figures are statistically significant (p<0.05). Source: transit use and income: Census 2006; built environment: GIS section in Halton Region s Planning Services and factor analysis. 13

14 Higher walkability and commute by transit Higher walkability was associated with higher use of public transit to commute in urban dissemination areas of Burlington and Oakville in 2006, even when adjusting by other significant factors such as proximity to transit stops, income group and municipality (p<0.05). Public transit use to go to work was significantly different between Burlington and Oakville (p<0.05). However, the association between walkability and percentage of residents commuting by transit was also significant when analysis was conducted for Burlington and Oakville separately (p<0.05). Proximity to transit and commute by transit Albeit small, there was a significant association showing that the higher proportion of residents within 400 meters of a transit stop was, more residents commuted by transit, even when income group and built environment factors such as walkability were held constant (p<0.05) (Figure 7). Differences between Burlington and Oakville were significant for percentage of commute by transit (p<0.05). However, subgroup analysis showed the same general trend for all areas in Burlington and the half more walkable areas in Oakville (above the median walkability). With low walkability areas in Oakville being the only potential exception to this trend, caution is needed to interpret subgroup analysis as fewer observations lead to reduced capacity to test associations. In addition, the association between the proportion of residents within 400 meters of a transit stop and municipality makes it difficult to further assess differences between Burlington and Oakville. Commute by transit and the combination of proximity to transit and walkability Similar to what was found for lower private motor vehicle use, there was evidence to suggest that having more than 80% of population in proximity to transit favoured walkability s association with higher transit use to go to work. When the proportion of residents within 400 meters of transit stops was less than 80%, the association between high walkability and high transit commute to work was not significant. However, for areas with 80% or more of their residents in proximity to transit stops, this association was significant (Figure 8). In general, these results are suggestive of a higher proportion of residents in proximity to transit as a favourable condition for the association between walkability and commute to work by public transit or private motor vehicles. Figure 8. Percentage of residents aged 15 and over who commuted by public transit and walkability, by proportion of residents in proximity to transit stops, urban dissemination areas, Burlington and Oakville, 2006 Figure notes: - Walkability: common factor loading population density, landuse mix, and intersection density. - % Pop. = % of population within 400 meters of a transit stop, categorized as <80% (249 observations) and >=80 (345 observations). - Solid line: significant association within subgroup analysis (p<0.05) Source: transit commute: Census 2006; built environment: GIS section in Halton Region s Planning Services and factor analysis. 14

15 Income quintile areas and transit to work use Incidental findings suggest that public transit use to commute was used across high and low income area income groups. Figure 9 shows that high transit use to go to work was similar in both the highest and the two lowest income group areas. Transit use in the highest income group area (#5) was not statistically different from the second lowest income quintile (#2) and significantly higher than income quintiles 3 and 4. Only the lowest income quintile areas (#1), which were not very frequent in Burlington and Oakville, had significantly higher rates than all the rest. These results are incidental because the methodology of this analysis was not planned to draw conclusions about individual level characteristics such as income level, included as a potentially confounding factor to control for. In general, individual level data are required to assess if high or low income groups were the ones commuting by public transit in these areas. Figure 9. Percentages of residents aged 15 and over who commuted by public transit by income quintiles, urban dissemination areas, Burlington and Oakville, 2006 Figure notes: - Income quintile (QAIPPE): 1 = lowest, and 5 = highest - Confidence intervals are identified as black lines. - Transit use in the highest income group area (#5) was not statistically different from the second lowest income quintile (#2) (p>0.05). It was however significantly higher than income quintiles 3 and 4 (p<0.05). - Figure 7 requires caution as it is based on area level information. Source: transit use and income: Census 2006; built environment: GIS section in Halton Region s Planning Services and factor analysis. 15

16 5. DISCUSSION Built environment features associated with travel to work mode in Halton Region The main findings of this report are: Areas that were either more walkable or have more land-use mix were associated with a higher percentage of active transportation, and lower private motor vehicle use to commute in Halton Region, and higher use of public transit to go to work in Burlington and Oakville. o However, in areas with less than 80% of residents lived in proximity to transit, walkability was not equally associated with lower private motor vehicle commute in Halton Region and higher transit use to go to work in Burlington and Oakville. This may suggest a mediating role of higher access to transit as a favouring condition to support walkability for reducing private car trips and increasing transit use to commute. In areas where at least some walking and cycling to work occurred, higher intersection density was positively associated with higher percentages of active commute to work. Areas with a higher proportion of residents within 400 meters of transit stops were consistently associated with lower private motor vehicle commute in Halton Region and higher use of public transit to go to work in Burlington and Oakville. 3, 7, 8, 10 The associations found in this report are consistent with international literature and other Ontario reports. Older age and income: key characteristics that need further analysis While the findings reported above remain significant even when adjusted for age profile and income quintile of the areas, the following results require further investigation: Areas within the two lowest income quintiles were also associated in some models with higher active transportation to work and potentially lower private motor vehicle commute in Halton Region. Transit use to work was however high in both low and high income areas in Burlington and Oakville. Areas with higher land-use mix and higher active transportation to work were also areas with higher concentration of older adults. Individual level data is nonetheless needed to better understand commute patterns by age and income. Residential density combined with land-use mix and connectivity Residential density alone, when it is not combined with higher land-use mix and higher intersection density, was not significantly associated with travel behaviour. However, when combined with higher land-use mix and intersection density, it was significantly associated. This is consistent with a meta-analysis of 200 articles, which also found that population density alone was not as consistently associated as other factors such as land-use mix. 18 It is however also central to highlight that even when not directly associated with travel behavior, higher residential density is core to the sustainability of transit provision, as pointed out by the Ontario Ministry of Transportation Transit Supportive Guidelines. 38 Furthermore, appropriate densities are also a key factor to support a vibrant business community and diverse land use services. Safe cycling infrastructure Exclusive cycling infrastructure has been associated with higher cycling rates in evaluation of multiple urban centres in North America. 39 However, in Halton Region in 2006, urban areas with above average walkability had approximately 70% less odds of having at least some cycling infrastructure (p<0.05, odds ratio = 0.7). This may explain why areas with higher density of cycling infrastructure in 2007 were not associated with higher rates of cycling to work in Further research would be needed to assess if efforts since 2006 to provide cycling infrastructure have been associated with increased ridership. However, more importantly, adequate 16

17 cycling infrastructure is central to reducing injuries and fatalities. 26, 40 To this extent, this report s finding that higher rates of cycling in areas where land-use mix is higher is suggestive of the need of providing safe cycling infrastructure in areas where this is more needed, in particular as land-use mix increases overtime. Halton as a relatively homogeneous suburban community This report did not intend to assess other areas in the Greater Toronto and Hamilton (GTAH) region whose comparatively high walkability and land-use mix would likely have shown stronger associations with transportation modes to work than those observed in Halton. In this report, high walkability and land-use mix represent the highest values within the Halton context. However, compared with the GTAH in 2006, Halton was a suburban region whose built environment was characterized by its relative low density. 41, 42 Other reports in 8, 9, 10, 11 the GTAH area have shown associations between travel modes and built environments. Main limitations One of the main limitations of this report was that it was based on area level data, although this was the best available data in Halton Region. Although the report found associations between individual attributes such as age and income and transportation modes, it is unable to assess if these groups are effectively the ones walking, cycling or taking transit to work in these areas. This is important because for instance individual level surveys conducted by the Halton Region Health Department have identified no statistical differences in walking or cycling for reasons other than fitness as age increases. 43 Similarly, physical activity (recreational or utilitarian) has been reported to be lower in Halton s low income male population. 44 Further work may be needed to assess whether older adults or low income residents (or a subgroup of them) have different travel behavior in high walkability and high land-use mix areas, and, in particular, assessing the transportation needs of particular groups: youth, older adults, and low income residents. The assessment of change over time is another area for future work. In effect, while some built environment and transportation literature has suggested that built environment characteristics change people behavior, more evidence is still required to assess whether or not walkable areas attract people who would use active 45, 46, 47 transportation or transit anyways (known as self-selection). However, emerging evidence from longitudinal studies suggests that built environments do have an impact on utilitarian travel behaviour. 48, 49, 50 In the GTAH, cross-sectional evidence assessing neighbourhood or travel preference also suggests that selfselection, while probably being a factor for a minority of the population, does not fully explain associations between travel behaviour and walkability. 51 The importance of removing barriers for making active transportation and public transit choices the easiest option has also been highlighted. Furthermore, from a service planning view, either scenario would result in higher numbers of active transportation or transit users. Further studies are needed to assess variables such as proximity to open spaces, job densities, directness and frequency of transit service, the availability of pedestrian infrastructure, and the availability of off-road pedestrian connections, which were not available for this analysis. 6. CONCLUSION Through an area-level descriptive analysis of commute patterns in 2006 and built environment measures such as walkability, land-use mix, connectivity and proximity to transit, the findings support the existence of associations between walkable environments and increased active transportation, transit ridership and reduced private motor vehicle to go to work. As the first available Halton specific small area data analysis on built environment measures, this report provides evidence of the relevance of reports from other jurisdictions to Halton s context. In particular, higher walkability (factor capturing population density, land-use mix and intersection density together), higher land-use mix, better connectivity, and more proportion of residents in proximity to transit stops were associated with sustainable and healthier travel behaviours, which include active transportation, public transit use and reduced reliance on private motor vehicles to go to work. 17

18 A1. APPENDIX 1. GLOSSARY OF TERMS Active transportation: any form of human-powered transportation, including walking, cycling, roller-blading, skateboarding and moving with mobility devices. In this report, it refers to the proportion of residents who reported walking or cycling to work to cover the longest distance of their commute in Active commute: the use of active transportation to go to work. Built environment: Comprises urban design, land use, and the transportation system, and encompasses patterns of human activity within the physical environment. This report assesses measures such as walkability, land-use mix, street connectivity, and proportion of residents within 400 meters of a transit stop. Confidence intervals: the range of values with a given chance of including a true estimate. In this report 95% confidence intervals are represented in the figures as error bars (black lines in bar chart figures). Connectivity: the directness of travel to destinations. A highly connected network allows people many possible routes between destinations. In this report, it is assessed through the number of intersections in the road network by squared kilometer. However, the analysis was unable to capture pedestrian only connections. Dissemination area (DA): a small, relatively stable geographic unit composed of one or more adjacent dissemination blocks. It is the smallest standard geographic area for which all census data are disseminated. 12 It is also the basic unit of analysis for this report (also referred to as area (s)). For descriptive purposes, they are referred to as neighbourhoods in some sections of the text. Ecological fallacy: a potential bias when an inference about an individual based on aggregate data for a group. The ecological fallacy may arise because the process of aggregating data may conceal the variations that are not visible at the larger aggregate level. 55 Employment density: number of job positions per square kilometre/mile. This report does not assess employment density. Income group: in this report, it refers to the dissemination area quintile of annual income per person equivalent according to the 2006 national census of Canada (QAIPPE). Land use: the geographical distribution of uses of land space, including the location and density of different activities, where activities are grouped into relatively coarse categories such as residential, commercial, office, industrial and other activities. Land-use mix: a form of land use in which there is diversity or variety of development types. It is usually refers to development that combines two or more of the types of development: residential, commercial, office, industrial or institutional. In this report it is measured as the proportion of residents in proximity to 16 diverse land uses of interest and the common factor derived from their distribution. Odds Ratio (OR): comparison of the probability that a result of interest occurs against the probability that it does not. The ratio is often expressed as a decimal number in which a value higher than 1 shows a higher probability of having an event, while an OR lower than 1 shows a lower probability. An OR of 1 shows that the variables in analysis are not associated. 56 It is reported in ordinal logistic regression models used in this report. p- value or alpha value (p< or p>): represent how likely a result would occur by chance. If the p-value is lower than expected, it is assumed that the results are statistically significant. Consistent with common practice in research literature, an alpha value of 0.05 was used. Percentiles: the proportion of values in an ordered distribution that a specific value is greater than or equal to. 55 QAIPPE: Quintile of annual income per person equivalent according to the 2006 national census of Canada. Statistics Canada calculates this average income per person for each dissemination area. QAIPPE #1 is the lowest income quintile, and QAIPPE #5 is the highest income quintile. The following categories are defined used in the text. - Very low income group: QAIPPE groups #1 and 2 grouped together. 18

19 - Low income group: QAIPPE groups #1, 2 and 3 grouped together. - High income group: QAIPPE groups #4 and 5 grouped together. - Highest income group: QAIPPE group #5. Residential density: number of residents per square kilometre/mile. In this report, it refers to gross density, understood as the total population of a given area divided by the total amount of land. Significance, Significance level, Statistical significance: the chance that the test erroneously rejects the null hypothesis when the null hypothesis is true. Walkability: The extent to which the built environment is friendly to the presence of people living, shopping, visiting, enjoying or spending time in an area. Factors captured under walkability as measured in this report include land-use mix, connectivity and residential density. 19

20 Explanatory variables Outcome variables A2. APPENDIX 2. DETAILS OF METHODOLOGICAL APPROACH The unit of analysis was Census 2006 urban dissemination areas in the Halton Region. A dissemination area is a small, relatively stable geographic unit composed of one or more adjacent dissemination blocks. It is the smallest standard geographic area for which all census data are disseminated, and generally has 400 to 700 residents. 12 All 601 urban dissemination areas identified in Halton Region were used in the analysis (an urban area is defined as having a minimum population density of 400 people per square kilometre). 13 The analysis included the Halton Region s four local municipalities: Halton Hills, Milton, Oakville, and Burlington. Analysis of transit use to work was performed only in Burlington and Oakville because other areas did not have a comparable transit system in Definition of variables Table 1 summarizes the outcome and predictor variables included in this study. Mode of transportation to commute to work (outcome) used 2006 Census of Canada information, as done in other reports for active transportation measures. 8, 9 Given the low percentages and high number of zeros, the percentages of residents who walked and cycled to work were combined into a single variable to show the percentage of active transportation to work. This is an appropriate approach used in other reports. 8 Census 2006 mode of transportation to work information remains among the best quality sources for transportation modes at a dissemination area level. Table 1. Definition and data source of outcome, explanatory and confounding variables Variable Percentage of employed labour force 15 years and over who walked or cycled to work (also active transportation/commute to work) Percentage of employed labour force 15 years and over who bicycled to work Percentage of employed labour force 15 years and over who used private car as a driver or passenger to commute to work Percentage of employed labour force 15 years and over who used public transit Percentage of employed labour force 15 years and over who walked Residential Density (Density) Land-use mix Walkability factor (residential density, land-use mix and intersection density) Km of bike paths square kilometer (sq. km) Percentage of residential population 1500m Elementary Schools Definition (source) Total residents who walked plus residents who cycled divided by the population in the area and multiplied by 100. The questions do not allow to double count residents as they are mutually exclusive. The age 15 year and over is set by the census questionnaire (calculated from Census 2006 data) a Total residents who cycled divided by the population in the area and multiplied by 100 (calculated from Census 2006 data) a Total residents who drove plus those who travelled as passenger in private motor vehicles, divided by the population in the area and multiplied by 100 (calculated from Census 2006 data) a Total residents who used in public transit, divided by the population in the area and multiplied by 100. Transit includes bus, street car train, commuter train, subway (calculated from Census 2006 data). a Total residents who walked divided by the population in the area and multiplied by 100 (calculated from Census 2006 data) a Residents by total area in square kilometers by dissemination area (calculated from Census 2006 data) Common factor of proportion of residents in proximity to 16 diverse uses. Calculated with factor analysis (GIS section within Halton Region s Planning Services, 2010) b, d Common factor of residential density, land-use mix and intersection density. Calculated with factor analysis (GIS section within Halton Region s Planning Services, 2010) c, d Km of Bike Path (off road and on road infrastructure along regional or local roads)/ Area in sq. Km. It excludes trails (GIS section within Halton Region s Planning Services 2007) d, e Number of residents in the catchment area of point of interest (calculated by property parcel data assigning person per unit estimates for residential units). Traveled distances along the road network were used (GIS section within 20