City and Regional Residential Preference Survey Results for Toronto and Vancouver: A CLASP Final Report

Size: px
Start display at page:

Download "City and Regional Residential Preference Survey Results for Toronto and Vancouver: A CLASP Final Report"

Transcription

1 City and Regional Residential Preference Survey Results for Toronto and Vancouver: A CLASP Final Report Prepared for: Toronto Public Health Prepared by: Project: Dr. Larry Frank, President Mr. Jim Chapman Ms. Suzanne Kershaw Ms. Sarah Kavage Urban Design 4 Health, Ltd. Coalitions Linking Action and Science for Prevention (CLASP) Initiative Residential Preference Survey Date: March 7, 2012

2 Contents Acknowledgements... v 1.0 Introduction Data Collection/Recruitment Sampling Plan/Survey Survey Design/Recruitment Demographic Eligibility Sampling Plan Stratification Walkability Income Stratification Matrix Potential Recruit Counts Sampling Results Participant Descriptives Demographics regional level Demographics city and suburban level Descriptive Results Physical Activity and Transport (self-reported) Travel Behaviour Travel to work Travel to school Walking to various destinations - occurrence Important Factors in Neighbourhood Selection Neighbourhood Trade-off Descriptives Trade-off #1: Lot size, Proximity of Commercial Services, Travel Options, Commute Distance, Transit Options Trade-off #2: Walkability and Proximity of Commercial Services Trade-off #3: Level of Activity and Mix of Housing Trade-off #4: Home Size and Travel Options Trade-off #5: Lot Size and Commute Distance Trade-off #6: Street Design and Travel Options Trade-off #7: Public Recreation Opportunities and Lot Size Trade-off #8: Access to and Size of Food Outlets Comparing Neighbourhood Trade-off Responses by Participant Sub-region (City & Suburbs) Latent demand using objectively measured data Conclusions from Neighbourhood Trade-offs Analytical Methods and Results Methods & Outcomes of Principal Component Analysis Relationship between Current Neighbourhood and Physical Activity/Travel Outcomes Comparing City & Suburb Current Neighbourhood with Physical Activity/Health Outcomes Alignment between Neighbourhood Preference and Current Neighbourhood (Choice) Preference/current & physical activity/travel outcomes City of Toronto -- physical activity/travel outcomes & objective walkability data Summary of Findings i

3 Appendix A Online Surveying Appendix B CLASP Residential Preference Survey Appendix C Correlations of Variables Used in Principle Component Analysis Appendix D City of Toronto Walkability Index Tables Table 1: Built Environment Variables at the FSA Level... 4 Table 2: FSA Level Walkability Crossed with Income... 5 Table 3: GTA Ipsos Reid Potential Recruit Count... 5 Table 4: GVRD -- Ipsos Reid Potential Recruit Count... 6 Table 5: Count of Survey Responses by Region... 7 Table 6: Number of Participant Locations Successfully Mapped... 7 Table 7: Ethnicity Table 8: Descriptive Statistics for GTA Participants Table 9: Descriptive Statistics for GVRD Participants Table 10: Descriptive Statistics for City of Toronto and GTA Suburb Participants Table 11: Descriptive Statistics for City of Vancouver and GVRD Suburb Participants18 Table 12: BMI, Physical Activity and Transport GTA & GVRD Table 13: BMI, Physical Activity and Transport city & suburbs Table 14: Mode of Transportation to Work (Percent by each mode) Table 15: How do your children typically travel to school/work? Table 16: Percent of Participants Walking to Destinations At Least Once in a Typical Month Table 17: Important Factors in Moving to One's Current Neighbourhood Table 18: Neighbourhood Trade-off # Table 19: Q1A. Assuming that there are no differences between the s apart from the ones we mentioned, which do you think you d rather live in? Table 20: Q1B. How do you think you'd feel about living in Neighbourhood "A"? Table 21: Q1C. How do you think you'd feel about living in Neighbourhood "B"? Table 22: GTA Q1D & Q1E Table 23: GVRD Q1D & Q1E Table 24: GTA Trade-Off #2 -- Q2A, Q2B & Q2C Table 25: GVRD Trade-Off #2 Q2A, Q2B & Q2C Table 26: GTA Trade-off #3 -- Q3A, Q3B & Q3C Table 27: GVRD Trade-off #3 -- Q3A, Q3B & Q3C Table 28: Trade-off #4: Home Size and Travel Options Table 29: GTA Trade-off #4 Q4A, Q4B & Q4C Table 30: GVRD Trade-off #4 Q4A, Q4B & Q4C Table 31: GTA Trade-off #5 -- Q5A, Q5B & Q5C Table 32: GVRD Trade-off #5 -- Q5A, Q5B & Q5C Table 33: GTA Trade-off #6 -- Q6A, Q6B & Q6C Table 34: GVRD Trade-off #6 Q6A, Q6B & Q6C Table 35: GTA Trade-off #7 -- Q7A, Q7B & Q7C Table 36: GVRD Trade-off #7 -- Q7A, Q7B & Q7C Table 37: GTA Trade-off #8 Q8A, Q8B & Q8C Table 38: GVRD Trade-off #8 -- Q8A, Q8B & Q8C Table 39: Participant responses by preference by sub-region Table 40: Participant responses by current (self-described) by subregion ii

4 Table 41: Walk Index Quartile Frequencies for City of Toronto Participants Using Citywide Range Table 42: City of Toronto survey participants preferences compared to current Table 43: Latent demand for more pedestrian/transit-oriented or auto-oriented s using City of Toronto walkability index Table 44: GTA Current Neighbourhood Factor Total Variance Explained Table 45: GVRD Current Neighbourhood Factor Total Variance Explained Table 46: GTA Neighbourhood Preference Factor Total Variance Explained Table 47: GVRD Neighbourhood Preference Factor Total Variance Explained Table 48: Factor Extraction Component Matrix for Current Neighbourhood (Question B) Table 49: Factor Extraction Component Matrix for Neighbourhood Preference (Question A) Table 50: Participant Counts by Current (Self-described) Neighbourhood Walkability Quartiles Based on Region Specific Walkability Quartiles Table 51: Participant Counts by Current (Self-described) Neighbourhood Walkability Quartiles Table 52: Participant Counts by Preferred Neighbourhood Walkability Quartiles Based on Region Specific Walkability Quartiles Table 53: Participant Counts by Preferred Neighbourhood Walkability Quartiles Based on Region Specific Walkability Quartiles Table 54: Mean Walk Trips, VKT & BMI by Current Neighbourhood Walkability (selfdescribed) Quartile (GTA) Table 55: Mean Walk Trips, VKT & BMI by Current Neighbourhood Walkability (selfdescribed) Quartile (GVRD) Table 56: F-test Summary Results for Mean Walk Trips, Vehicle km Travelled, and BMI by Current Neighbourhood Walkability (self-described) Quartile by Sub-Region71 Table 57: Mean Number of Days Traveled in a Car, in a Typical Week (7 Days), or Other Private Motor Vehicle (Q: E1_1) Table 58: Mean Number of days in a typical week (7 days) walked for at least 10 minutes at a time to travel to and from work/school, to do errands, or to go from place to place (utilitarian) (Q: E16_1) Table 59: - Mean amount of time (minutes) usually spent on one day, of the days which included walking from place to place (utilitarian) (Q; E17_1) Table 60: Mean number of days in a typical week (7 days) walked for at least 10 minutes at a time solely for relaxation, recreation and/or exercise (Q: E26_1) Table 61: Mean amount of time (minutes) usually spent per day walking for solely relaxation, recreation and/or exercise (Q: E27_1) Table 62: Mean number of day in a typical week (7 days) traveled in a bus, train (such as commuter/light rail, streetcar, subway) or other public transit vehicle (Q: E6_1_75 Table 63: Mean number of days in a typical week (7 days) walking was done for at least 10 minutes at a time for utilitarian and/or recreational purposes (walk for any purpose, combination of Q: E16_1 and E26_1) Table 64: Mean number of days in a typical week (7 days) bicycled for at least 10 minutes at a time for utilitarian and/or recreational purposes (bicycle for any purpose) Table 65: Mean amount of vehicle kilometres traveled in a typical week (7 days) (Q: F32_weekly) Table 66: Mean body mass index (BMI) Table 67: GTA Cross of Low/High Preferred/Current Neighbourhood Walkability Table 68: GVRD Cross of Low/High Preferred/Current Neighbourhood Walkability 80 iii

5 Table 69: Household income frequencies by preference/current cohort - GTA Table 70: Average household income by preference/current cohort - GVRD Table 71: GTA ANOVA analyses between preference/selection cohorts85 Table 72: GVRD ANOVA analyses between preference/selection cohorts Table 73: ANOVA based on objective current (City of Toronto participants only) Table 74: Mean Age & Income across quartiles of objective current (City of Toronto participants only) Table 75: GTA & GVRD Correlations of Variables Used in Principle Component Analysis Current Neighbourhood Table 76: GTA & GVRD Correlations of Variables Used in Principle Component Analysis Preferred Neighbourhood Figures Figure 1: GTA Survey Participant Home, Work and School Locations... 8 Figure 2: GVRD Survey Participant Home, Work and School Locations... 9 Figure 3: How many years have you lived in Canada? Figure 4: What Type of Dwelling Participants Live in Figure 5: Trade-Off #2 -- Walkability and Proximity of Commercial Services Figure 6: Trade-Off #3 -- Level of Activity and Mix of Housing Figure 7: Trade-Off #5 -- Lot Size and Commute Distance Figure 8: Trade-Off #6 -- Street Design and Travel Options Figure 9: Trade-off #7 -- Public Recreation Opportunities and Lot Size Figure 10: Trade-off #8 -- Access to and Size of Food Outlets Figure 11: GTA Walk Frequency and Automobile Travel Frequency by Participant s Current Neighbourhood Factor Score Figure 12: GVRD Walk Frequency and Automobile Travel Frequency by Participant s Current Neighbourhood Factor Score Figure 13: Mean BMI by Participant s Current Neighbourhood Type Figure 14: GTA--Alignment of Preference and Current Neighbourhood Figure 15: GVRD--Alignment of Preference and Current Neighbourhood Figure 16: GTA Participant Home Locations by Neighbourhood Preference/Current Neighbourhood Cohort Figure 17: GVRD Participant Home Locations by Neighbourhood Preference/Current Neighbourhood Cohort iv

6 ACKNOWLEDGEMENTS This project has been made possible through financial and/or in-kind contributions from Health Canada, through the Canadian Partnership Against Cancer s CLASP initiative, as well as the Heart and Stroke Foundation, Toronto Public Health, Peel Public Health, Fraser Health, and Vancouver Coastal Health. The views expressed in this presentation represent the views of the Healthy Canada by Design CLASP initiative and do not necessarily represent the views of the project funders. The following Advisory Committee Members provided invaluable input into the Residential Preference Survey: Allyson Friesen, Planning/Policy Supervisor, City of Coquitlam Ciara De Jong, Manager Research & Policy Development, Toronto Environment Office Dr. Helena Swinkels, Medical Health Officer, Fraser Health Authority Dr. Monica Campbell, Director, Healthy Public Policy, Toronto Public Health Elana Horowitz, (formerly) Senior Associate, Partnerships and Consultation, Ontario Growth Secretariat, Ministry of Energy and Infrastructure George McKibbon, Canadian Institute of Planner s Healthy Communities Sub- Committee Gordon Price, Director, City Program, Simon Fraser University Janet Lo, Project Officer, Transportation Services Division, Public Realm Section, Toronto City Hall Jessica Wu, (formerly) Planning Policy & Research Division, Corporate Services, Region of Peel Mara Samardzic, Planning and Policy Analyst, Building Industry and Land Development Association Michael Alexander, Board Member, San Francisco Planning and Urban Research Association Nick Chancellor, Ipsos Reid Bhavna Sivanand, Project Specialist, Peel Public Health Gayle Bursey, Director, Peel Public Health Alice Miro, Project Manager, CLASP Healthy Canada by Design Initiative Tracy Wall, Governor, Real Estate Institute of BC Data files from the following agencies were used in this project: Toronto Public Health Ipsos-Reid Public Affairs City of Toronto Open Data Repository (Toronto.ca/open) Municipal Property Assessment Corporation Statistics Canada v

7 1.0 INTRODUCTION This is the final report of the residential preference results from the survey conducted as part of the Coalitions Linking Action and Science for Prevention (CLASP) initiative. The overall purposes of the CLASP residential preference survey are to document the demand for different types of residential community environments ranging from walkable to auto oriented settings, and to document people s satisfaction with their current residential community design within the Greater Toronto Area (GTA) and the Greater Vancouver Regional District (GVRD). The results presented here are at both the regional and sub-regional (city and suburbs) levels. This report is organized in the following way: Section 2.0 provides an overview of survey data collection and sampling results. Section 3.0 provides descriptive statistics for participant demographics, and comparison with census data Section 4.0 provides descriptive statistics related to participant physical activity and transport, travel behaviour, relative importance of factors influencing selection, and trade-offs questions. Section 5.0 describes statistical analysis methods and results related to: o variations in physical activity, travel and body mass index across participant s self-described current level of walkability, o determining participants levels of satisfaction (alignment of choice and preference) with their current self-described type, o assessing how preferences and current type are associated with behaviour, and o variations in physical activity, travel, and body mass index across City of Toronto participant s objectively described current walkability. Section 6.0 provides a summary of findings 1

8

9 2.0 DATA COLLECTION/RECRUITMENT SAMPLING PLAN/SURVEY The previously submitted report called, Residential Preference Survey: Interim Report on Data Analysis, June 15, 2011 provided details on survey design and data collection. An excerpt is provided here to provide context for this report. 2.1 Survey Design/Recruitment The survey firm Ipsos-Reid Public Affairs conducted participant recruitment in 2011, under contract to Toronto Public Health. The pool of potential survey participants came from Ipsos Reid s i-say panel and are recruited to voluntarily join the panel using a variety of methods to ensure Ipsos Reid is drawing from a representative pool. Generally, recruitment is done online via websites, but Ipsos-Reid may also conduct supplemental telephone recruitment to build up the size of the online panel. Please see Appendix A for additional details supplied by Ipsos- Reid Public Affairs. People who opted into the Ipsos-Reid i-say consumer panel and who live in eligible areas of the Greater Toronto Area (GTA) or the Greater Vancouver Regional District (GVRD) were randomly recruited to participant in the residential preference survey. Participants completed the survey online through an Ipsos-Reid website. The Word document version of the survey used to create the web-based version is in Appendix B. 2.2 Demographic Eligibility Eligible participants were 25 years or older. Only one eligible participant per household was allowed. 2.3 Sampling Plan Stratification In order to assure that the final set of survey respondents was drawn from the range of walkability and incomes present in each region, recruitment of the sample was stratified. The sample was stratified based on the Forward Sortation Areas (FSAs) containing the participants home addresses. FSAs were the most detailed level at which a potential recruit s home location is known prior to their completing the survey. The details for each of the stratification criteria are described below Walkability Walkability values were calculated for each FSA in each region based on the following built environment measures: residential density, intersection density, and walk scores from The FSA level values of these measures were normalized within each region and summed to produce a walkability index. Please see Table 1 below for more details. 3

10 Table 1: Built Environment Variables at the FSA Level Variable Formula Variables Used Data Source(s) Residential Density Intersection Density Walk score Walkability Index Income # of housing units divided by FSA area #intersections divided by FSA area Walk score values were determined for points spaced evenly (every 1km) across each region. Sum of normalized (by region) values of the above four variables. # of housing units FSA area # of intersections FSA area Median walk score of points within each FSA. In the cases when an FSA did not have a point in it (from the 1km grid) the walkscore for the centroid was used. Residential density, intersection density, median walk score StatCan 2006 Census h/census06/data/popdwell/tabl e.cfm?t=1201&sr=1&s=0&o=a &RPP=9999&PR=0&CMA=0. Canadian FSA polygon shapefile from Canadian road network shapefile from Canadian FSA polygon shapefile from The above variables. FSA level income was based on 2005 Census household median income data. These data were purchased by UD4H from Tetrad Computer Applications Inc. ( Tetrad estimated the FSA level 2005 household level median income based on Census income data at smaller geometries. 2.4 Stratification Matrix Ipsos Reid supplied UD4H with FSA level counts of potential recruits. Combining these counts with the FSA level walkability and income values allowed for an iterative stratification matrix development process. The goal was to identify a set of walkability and income categories which also had sufficient potential numbers of recruits. In the end each FSA was categorized into one of four walkability categories and one of three income categories. Table 2 below shows the walkability categories crossed with income categories. Cells were numerically coded from 1 to 12 for tracking and reporting purposes. 4

11 Table 2: FSA Level Walkability Crossed with Income Note: Numeric Values in the Cells of Walkability/Income Correspond to the coding used for the variable called walk_income_cat_ ) Income Walkability Index <$50k $50k - $70k >$70k 1 (lower walkability) (higher walkability) Potential Recruit Counts Table 3 and Table 4 were created using FSA-level potential recruit counts provided by Ipsos-Reid and the walkability/income sampling matrix created by UD4H. The cells in the table contain the number of potential recruits Ipsos-Reid has in all the FSAs in each walk/income cell, for the GTA and GVRD regions. Table 3: GTA Ipsos Reid Potential Recruit Count (walk 4 by income 3) Note: The counts in the cells are the number of potential Ipsos recruits (people). Yellow cells indicate lower counts. The red cell has no potential recruits. Income 1 Walkability Index 2 <$50k $50k - $70k >$70k Sum 1 (lower walkability) 375 4,653 11,713 16, ,924 2, , , ,580 4 (higher walkability) Total 4,657 8,940 12,637 26,234 1 UD4H variable 2 UD4H variable information, and numeric ranges: UD4Hwi1a_ _recoded_4range. GTA -- RECODE UD4Hwi1a_ (-3.35 thru 0.37=1) ( thru 2.81=2) ( thru 7.81=3) ( thru 11.53=4) INTO UD4Hwi1a_ _recoded_4range. 5

12 Table 4: GVRD -- Ipsos Reid Potential Recruit Count (walk 4 by income 3) Note: The counts in the cells are the number of potential Ipsos recruits (people). Yellow cells indicate lower counts. The red cell has no potential recruits. Income 3 Walkability Index 4 <$50k $50k - $70k >$70k Sum 1 (lower walkability) 967 3,412 1,804 6, , , ,197 4 (higher walkability) Total 2,631 5,843 1,876 10,350 As shown in the tables above, the distribution of potential recruits is not equal across the 12 possible cells, and not all cells contained potential recruits. In both regions, there are no potential recruits in the high walk (4) and high income (>$70,000) cell. In the GVRD, there are also no potential recruits in walkability category 3, and high income (>$70,000). The absence of potential recruits in these cells was unexpected and has been identified as a potential limitation to the ability of this sample to accurately represent the population in each region. To best assure survey participants are recruited from all possible walkability/income cells a minimum and maximum number of completed surveys per cell were required. Initially, a minimum of 50 completed surveys in each walk/income cell was specified, and a maximum of 200. Toward the end of recruitment low counts of potential recruits in some cells necessitated reducing the minimum count requirement to Sampling Results A total of 1,525 surveys were completed in the GTA, which meets the sampling plan requirement of 1,500. In the GVRD, 1,223 surveys have been completed, 290 fewer than the sampling plan requirement of 1,500 for that region. Of the 2,748 survey responses collected by Ipsos-Reid between 30 and 200 completed surveys (as required by the sampling plan) were collected for 10 of 11 walkability/income cells with potential GTA recruits 8 of 10 walkability/income cells with potential GVRD recruits Survey respondents provided home, work (if applicable), and school (if applicable) postal codes. If the participant did not feel comfortable 3 UD4H variable 4 UD4H variable information and numeric ranges: UD4Hwi1a_ _recoded_4range. GVRD -- RECODE UD4Hwi1a_ (-3.39 thru -0.22=1) ( thru 2.81=2) ( thru 5.72=3) ( thru 8.76=4) INTO UD4Hwi1a_ _recoded_4range. 6

13 providing a postal code, they could enter the nearest intersection instead. Table 5 shows the number of valid responses for each location (home, work, school). All participants in both regions provided a valid home location. In the GTA, work and school locations were provided for 63.3 percent and 6.8 percent of participants respectively not all participants work or go to school. In the GVRD, work and school locations were given for 60.1 percent and 6.8 percent of participants respectively. Table 5: Count of Survey Responses by Region All responses GTA City of Toronto GVRD # participants 2,748 1,525 1,133 1, # provided work 1,724 (62.7%) 978 (64.1%) 746 (60.9%) location # provided school location 189 (6.8%) 105 (6.8%) 84 (6.8%) City of Vancouver Home, work, and school locations for each participant were mapped with ESRI s 2010 North American address locator using either the postal code or intersection provided (participants were only permitted to provide one). If the postal code provided for a participant s home location did not exist, the postal code used to recruit the participant was used. For work and school responses with invalid postal codes, a postal code with the nearest alphabetic match was used (i.e. L9S1S9 (invalid) replaced with L9S1S7 (valid)). If a location match was not found using the given intersection, the X/Y coordinates of the intersection were looked up online and used to map the location. Table 6 shows the number of participant locations that were successfully mapped given all valid responses (some participants provided intersections or postal codes that were invalid or did not exist). All home locations in the GTA (n=1,525) and GVRD (n=1,223) were spatially located and mapped. Table 6: Number of Participant Locations Successfully Mapped GTA GVRD # participant responses # responses located # participant responses # responses located Home locations 1,525 1,525 1,223 1,223 Work locations School locations The geographic location of survey participants for the GTA (n=1,525) are shown in Figure 1. The location points are coded by home, work, and school locations. The same set of participant responses for the GVRD (n=1,223) are mapped in Figure 2. 7

14 Figure 1: GTA Survey Participant Home, Work and School Locations 8

15 Figure 2: GVRD Survey Participant Home, Work and School Locations 9

16

17 3.0 PARTICIPANT DESCRIPTIVES This section summarizes selected participant level survey variables in each region and sub-region for three major topics demographics, physical activity and health, and travel behaviour. Please see Appendix B for a copy of the full survey instrument used to collect these data. 3.1 Demographics regional level Survey participant demographics are described below GTA and GVRD The average GTA (GVRD) survey participant is 50 (51) years old and owns their dwelling. In the GTA 47.9 percent are married with 0.4 children on average, as compared to 44.4 percent in the GVRD and 0.3 children. In both regions participants have an average income between $40,000 and $60,000, and 44.9 percent (40.5 percent) of GTA (GVRD) participants have a university degree. On average they have lived in Canada for over 43 years. 51percent of respondents identify with North American or European ethnic origin, while 10 to 11 percent have an Asian, African, Latin, or Caribbean ethnic origin and 23 (27.6) percent (GTA/GVRD) claim multiple ethnic origins. Additional details are provided in Table 7, Figure 3 and Figure 4. The top three ethnicities for regional, city and suburban groupings shown in Table 7 are British Isles European, and East and Southeast Asian. Table 7: Ethnicity We all live in Canada but our ancestors come from different parts of the world GTA (n=1,5 25) GVRD (n=1,223) City of Toronto (n=1,133) GTA suburbs (n=392) City of Vancouver (n=512) GVRD suburbs (n=711) British Isles (English/Scottish/Irish) 30.9 % 31.2% French 0.8% 1.6% European (Italian, Dutch, German, Ukrainian, Polish, Greek, Portuguese) 12.4% 10% Arab 0.6% 0.3% West Asian (Jewish, West Asian) 3.7% 1.8% South Asian 4.5% 0.7% East and Southeast Asian (Chinese, 5.8% 10.3% Korean, Vietnamese, Filipino) African (Black African or African American) 0.7% 0.2% Latin, Central, South American (Hispanic) 0.9% 0.7% Caribbean (Caribbean or from West Indies) 2.8% 0.2% Canadian 7% 7.8% Other 6.8% 6.6% Multiple origins 23% 27.6%

18 Approximately 15 percent of survey participants in each region have lived in Canada less than 25 years. Please see Figure 3 for more details. Figure 3: How many years have you lived in Canada? (n_gta=1525, N_GVRD=1223) >51 yrs yrs 41% 40% 45% 44% yrs 6-10 yrs 3% 4% 8% 9% GVRD GTA 0-5 yrs 3% 3% 0% 10% 20% 30% 40% 50% In both regions the largest percentage of participants lives in detached homes, followed by apartments/condos. In the GTA it is more common for the survey participants to live in an apartment/condo that is part of a building five or more stories high, while in GVRD living in a building one to four stories high is more common. Please see Figure 4 for more details. Figure 4: What Type of Dwelling Participants Live in (n_gta=1503, N_GVRD=1193) Apartment/condo (5 or more stories) 16% 32% Apartment/condo (1 to 4 stories) 10% 29% Duplex/triplex/quadplex Row/townhouses 3% 1% 11% 8% GVRD GTA Semi-detached house 1% 11% Detached house 40% 38% 0% 10% 20% 30% 40% 50% 12

19 Table 8 for the GTA and Table 9 for the GVRD show participant demographics and socio-economic characteristics are highly similar between the regions. The tables also contain census based values to facilitate comparison of the sample population to the census population. Census statistics are also provided for the Toronto CMA 5 and the GVRD to evaluate how representative participant demographics are compared to the population. In the GTA, the marital status, dwelling type, average household size, income, and employment variables among survey participants are all comparable to the census. For survey participants, the percentage of males is 5.3% lower, while the percentage with a university degree 6 is 11.3% higher and the percentage of immigrants is 11.4% lower compared to the census. In the GVRD, dwelling type, income, and employment among survey participants are comparable with the census. As in the GTA, the percentage of males in the survey is lower (8.6%) than in the census; the same is true of the marital status (5.9% lower) and immigration (7% lower) variables. The percent with a university degree is 9.8% higher among GVRD participants compared to the census. 5 Statistics Canada community profiles are not available for the Greater Toronto Area. The Toronto CMA community profile is used as a surrogate. The Toronto CMA and the GTA are similar in size and population, but have different administrative boundaries. The GTA is larger (7, km 2 ) than the Toronto CMA (5, km 2 ), and has a larger population (5,555,912 in 2006). The Toronto CMA does not include the municipalities of Brock, Scugog, Whitby, Oshawa, or Clarington in Durham Region, or Burlington in Halton Region. The Toronto CMA does include the following municipalities which are not part of the GTA -- Bradford West Gwillimbury, New Tecumseth, and Mono in Simcoe County. 6 The education variable definition in the survey is % with university degree (bachelor or graduate). In the 2006 census, the most similar variable is % University certificate diploma or degree. While similar, the designations may not be exactly comparable. Furthermore, educational attainment data are only provided for those <65 years in the census community profiles. 13

20 Table 8: Descriptive Statistics for GTA Participants Variable GTA (n=1,525) Toronto CMA 2006 Census Statistics 7 Mean (SD) / Min Max Variable Toronto CMA Percent Population in ,113,149 Age 50 (13.3) (median=51) Median age % male 43.3 % male 48.6 % married 47.9 % married 52.3 % living in single % living in single 37.8 detached dwelling detached dwelling 41.7 % own dwelling 59.9 % own dwelling 67.6 Average household size Average household size 2.8 # of children <18 years 0.4 (0.8) 0 6 Income category (1.9) (median=5) [where category 4=$40,000-59,999 & 5=$60,000-79,999] 1 8 % with university degree 44.9 % employed 64.6 % immigrated to Canada 34.3 # years living in Canada 43.2 (18.0) 0 87 Median income in All private households ($) (before-tax) % University certificate, diploma or degree (Age 25-64) % employed (among population 15+) % immigrated to Canada 64, Source: Statistics Canada, 2006 Census of Population. 8 Median age based on entire age range in the Census, as compared to the survey s age range beginning at 25 years. 9 Income ranges: 1=<$10,000, 2=$10,000-19,999; 3=$20,000-39,999; 4=$40,000-59,999; 5=$60,000-79,999; 6=$80,000-99,999; 7=$100,000-$119,999; 8=$120,

21 Table 9: Descriptive Statistics for GVRD Participants Variable GVRD (n=1,223) GVRD 2006 Census Statistics 10 Mean (SD) / Min Max Variable GVRD Percent Population in ,116,581 Age 51 (14.3) Median age 11 (median=52) 39.1 % male 40.1 % male 48.7 % married 44.4 % married 50.3 % living in single 39.3 % living in single detached dwelling detached dwelling 35.5 % own dwelling 59.9 % own dwelling 65.1 Average household size Average household size 2.6 # of children <18 years 0.3 (0.7) 0 9 Income category (1.8) (median=4) [where category 4=$40-59,999] Percent with university degree 1 8 Median income in All private households ($) (before-tax) 40.5 % University certificate, diploma or degree (Age 25-64) % employed 61.1 % employed (among population 15+) % immigrated to Canada 32.6 % immigrated to Canada # years living in Canada 44.6 (18.3) , Regional level similarities between survey participants and the census population include household income, dwelling type, and percent employed. Differences between survey participants and the census population, include fewer immigrants in the survey, more females in the survey (~60% compared to ~50% respectively), and higher levels of education in the survey Source: Statistics Canada, 2006 Census of Population. 11 Median age based on entire age range in the Census, as compared to the survey s age range beginning at 25 years. 12 Income ranges: 1=<$10,000, 2=$10,000-19,999; 3=$20,000-39,999; 4=$40,000-59,999; 5=$60,000-79,999; 6=$80,000-99,999; 7=$100,000-$119,999; 8=$120, It should be noted that the Census education statistic for people over 65 years old are not included in census community profiles. 15

22 3.2 Demographics city and suburban level Table 10 and Table 11 show the same descriptives as above but at the city and suburb levels for GTA and GVRD participants. Census statistics are provided for the City of Toronto and City of Vancouver in order to facilitate comparison between survey participants and the census. Aggregated census data were not available only for the GTA suburbs or the GVRD suburbs. In the GTA, the average age and employment status of survey participants were similar for city and suburban dwellers. In the suburbs, as compared to participants in the city, there are a higher percentage of married couples, more participants living in single-detached dwelling, and larger average household size. The percentage of males in the survey was lower in the city, while the percentage with a university degree and immigration was higher. When comparing City of Toronto survey participants to the census, marital status, dwelling type, household size, income, and employment are all comparable. The percentage of immigrants is 12.7% lower among City of Toronto survey participants compared to the census, while the percentage with a university degree is 9.5% higher. Similar differences between city and suburban participants are observed in Table 11 for the GVRD. More suburban, as compared to city, participants are married and live in a single-detached dwelling, while fewer suburban participants have a university degree, are employed, or have immigrated to Canada. Household income levels between the two sub-regions are identical. The percentage of males is 8.9% lower in the City of Vancouver compared to the census. Fewer City of Vancouver participants immigrated to Canada, while a higher percentage are married, live in a single-detached dwelling, and have a university degree than in the census. Income and home ownership are comparable. 16

23 Table 10: Descriptive Statistics for City of Toronto and GTA Suburb Participants City of Toronto (n=1,133) GTA suburbs (n=392) City of Toronto 2006 Census Statistics 14 Variable Mean (SD) / Percent Min Max Mean (SD) / Percent Min Max Variable City of Toronto Population in 2,503,281 Age 49.9 (13.7) (median=51) (12.2) (median=50.5) Median age % male % male 48.1 % married % married 46.8 % living in % living in single single detached detached 27.3 dwelling dwelling % own dwelling Average household size # of children <18 years (1.3) Income 4.7 category 16 (1.9) (median=4) [where category 4=$40,000-59,999] (1.3) (0.7) (0.9) (1.7) (median=5) [where category 5=$60,000-79,999] % with university degree % employed % immigrated to Canada # years living in Canada (18.5) (16.2) 0 81 % own dwelling Average household size Median income in All private households ($) (before-tax) % University certificate, diploma or degree (Age 25-64) % employed (among population 15+) % immigrated to Canada , Source: Statistics Canada, 2006 Census of Population. 15 Median age based on entire age range in the Census, as compared to the survey s age range beginning at 25 years. 16 Income ranges: 1=<$10,000, 2=$10-19,999; 3=$20-39,999; 4=$40-59,999; 5=$60-79,999; 6=$80-99,999; 7=$100, ,999; 8=$120,

24 Variable City of Toronto (n=1,133) GTA suburbs (n=392) Mean (SD) Min Max Mean (SD) / / Percent Percent City of Toronto 2006 Census Statistics 14 Min Max Variable City of Toronto % visible 46.9 minority population Table 11: Descriptive Statistics for City of Vancouver and GVRD Suburb Participants City of Vancouver (n=512) GVRD suburbs (n=711) City of Vancouver 2006 Census Statistics 17 Variable Mean (SD) / Percent Min Max Mean (SD) / Percent Min Max Variable City of Vancouver Age 47.7 (13.854) (median=47) (14.2) (median=55) Population in , Median age % male % male 48.9 % married % married 41.8% % living in % living in single single detached detached 19.1 dwelling dwelling % own dwelling Average household size # of children <18 years Income category (1.9) (median=4) [where category 4=$40-59,999] % with university degree (1.1) (1.1) (0.6) (0.8) (1.75) (median=4) % own 48.1% dwelling Average household size 2.2 Median income in All private households ($) (beforetax) % University certificate, diploma or degree (Age 47, Source: Statistics Canada, 2006 Census of Population. 18 Median age based on entire age range in the Census, as compared to the survey s age range beginning at 25 years. 19 Income ranges: 1=<$10,000, 2=$10-19,999; 3=$20-39,999; 4=$40-59,999; 5=$60-79,999; 6=$80-99,999; 7=$100, ,999; 8=$120,

25 Variable Mean (SD) / Percent % employed % immigrated to Canada # years living in Canada City of Vancouver (n=512) GVRD suburbs (n=711) Min Max Mean (SD) / Percent (17.6) (18.1) 0 88 City of Vancouver 2006 Census Statistics 17 Min Max Variable City of Vancouver 25-64) % employed (among population 15+) 62.4 % immigrated to Canada 45.6 % visible minority population When comparing survey sample and census demographics there is not complete comparability between them. This is to be expected since survey sampling was not explicitly done in a way to replicate census level demographics. However, it is important to note that across the various demographics provided for survey participants there are a wide-range of people represented in the participant pool. This diversity makes this sample set an important one to understand residential preferences in the regions

26 4.0 DESCRIPTIVE RESULTS This section provides detailed results about participant responses to major survey topics. Results are split out by the participant s region (GTA or GVRD) and sub-region (city vs. suburbs). 4.1 Physical Activity and Transport (self-reported) A higher percent of survey participants are obese 20 in GTA than in GVRD (18 percent vs.16.5 percent). GTA participants also walk less, with 4.5 days per week of walking for any purposes compared to 4.7 in the GVRD. However, GTA participants bicycle slightly more (0.56 vs days per week in the GVRD). Even though GTA participants report using transit more days per week (1.87 vs days per week) they sill drive longer distances than their GVRD counterparts (235 vs. 218 kilometres per week). Table 12 shows these results and other. Table 12: BMI, Physical Activity and Transport GTA & GVRD GTA GVRD Variable N Mean (SD) Min Max N Mean Min Max or Percent (SD) or Percent Percent Obese (BMI 30) 1, n/a n/a 1, n/a n/a Walk for exercise days 1, (2.6) 0 7 1, per week (2.6) Walk for utilitarian 1, (2.7) 0 7 1, purposes days per week (2.7) Walk for any purpose 1, (2.7) 0 7 1, days per week (2.6) Bicycle for any purpose 1, (2.2) 0 7 1, days per week (2.1) Use public transit days 1, (2.4) 0 7 1, per week (2.2) Automobile travel days 1, (2.8) 0 7 1, per week (2.7) Weekly vehicle kilometres 1, (238) traveled Vehicle-licensed driver ratio (239) 1, (0.5) , (0.5) Obesity calculations are based on body mass index values are calculated from self-reported height and weight values. 20

27 Table 13 splits the above results down further allowing comparisons to be made between city and suburban participants within each region. Below are some highlights shown in the table. In the GTA region: Obesity is more prevalent in the suburbs (24.6%) as compared to participants in the City of Toronto (18.2%) Weekly frequency of walking for exercise is almost equal between participants in the city and suburbs, but participants in the city walk twice as much for utilitarian purposes as compared to suburban participants. Suburban participants weekly automobile travel frequency is 1.7 times higher compared to City of Toronto participants. GTA suburban participants accumulate 1.8 times more weekly VKT. Bicycle travel for any purpose is nearly equal among participants in the two areas Weekly public transit use is 3.6 times higher in the City of Toronto compared to the suburbs In the GVRD region: Obesity rates are higher in the suburbs (22%) as compared to the City of Vancouver (12.6%) Walking for exercise is virtually equal between city and suburban participants City of Vancouver participants walk 1.8 times more for utilitarian purposes as compared to GVRD participants who live in the suburbs Bicycle usage is slightly higher in the City of Vancouver (1.4 days/week) as compared to the suburbs (0.9 days/week) Suburban participants travel in an automobile 1.5 times more per week than City of Vancouver participants; they also drive 1.9 times as far. City participants use public transit twice as much as suburban participants. It is also noted that walk frequency for recreational purposes, utilitarian purposes, and public transit usage is higher in the City of Vancouver compared to the City of Toronto, and higher in the GVRD suburbs compared to the GTA suburbs, while weekly automobile travel is higher in the GTA suburbs and the City of Toronto, compared to the GVRD suburbs and City of Vancouver respectively. 21

28 Table 13: BMI, Physical Activity and Transport city & suburbs Variable City of Toronto GTA suburbs City of Vancouver GVRD suburbs Percent Obese (BMI 30) Walk for exercise days per week Walk for utilitarian purposes days per week Walk for any purpose days per week Bicycle for any purpose days per week Use public transit days per week Automobile travel days per week Weekly vehicle kilometres traveled Vehicle/licensed driver ratio N Mean / Percent (SD) Min Max N Mean / Percent (SD) Min Max N 1, n/a n/a n/a n/a 1, (2.6) (2.5) 0 7 1, (2.7) (2.4) 0 7 1, (2.6) (2.8) 0 7 1, (2.3) (2.1) 0 7 1, (2.5) (1.7) 0 7 1, (2.8) (1.9) (201.6) 0.7 (0.4) (283.8) (0.4) Mean / Percent (SD) Min Max N Mean / Percent (SD) Min Max 12.6 n/a n/a n/a n/a 3.11 (2.6) 3.73 (2.7) (2.5) (2.5) (2.5) (2.7) (2.4) (1.9) (2.4) (1.9) (2.8) (2.4) (165.4) (268.9) (0.5) (0.4)

29 4.2 Travel Behaviour Travel to work The travel to work mode split is the same for both regions. Most people drive alone. The next largest group commutes by walking or bicycling to public transit, followed by similar percentages of respondents that work from home or walk (Table 14). However, when comparing city and suburban participants, travel mode split is quite different. Among GTA suburban participants reporting a work trip, 70.2% drive alone, while only 3.0% walk and 14.4% take public transit. By contrast, just 28.3% of City of Toronto participants drive alone, while 11.5% walk and 38.9% take public transit. Mode split differences are less extreme in the GVRD, but still exist. Almost twice as many GVRD suburban participants drive alone to work (55.2%) as City of Vancouver participants, while 5.8% walk and 19.1% take public transit. In the City of Vancouver, 18.9% walk and 30.3% take public transit. Among suburban participants, more participants in the GVRD suburbs walk or take public transit to work compared to GTA suburb participants, while 15% (70.2% vs. 55.2%) more GTA suburban participants drive alone to work. Table 14: Mode of Transportation to Work (Percent by each mode) Note: only those reporting a trip to work GTA GVRD (n total (n total work work trips=747) trips=985) City of Toronto (n=720) GTA suburbs (n=265) City of Vancouver (n=350) GVRD suburbs (n=397) Walk Bicycle Walk/bicycle to public transit Drive or are driven to public transit Drive alone Car/vanpool Other Work from home Travel to school The travel to school mode-split is the same for both regions. Most survey participant s children walk to school, followed by school bus in the GTA and being driven in GVRD. The third most common way to travel to school is to be driven in GTA and to drive alone in GVRD. Please see Table 15 for more details. 23

30 The proportion of survey participant s children that walk to school is slightly higher among those who live in their respective region s cities. School bus travel is higher among suburban participant s children in both regions, as well as being driven to school/work. Table 15: How do your children typically travel to school/work? Note: those reporting a child s trip to school/work Mode of Travel GTA (n=283) GVRD (n =175) City of Toronto GTA suburbs (n=92) City of Vancouver (n=60) GVRD suburbs (n=115) (n=191) School bus Walk Bicycle Driven Walk/bicycle to public transit 4.3 Driven or are driven to public transit 5.2 Drive alone Multiple responses Walking to various destinations - occurrence In both regions, for the regions cities and suburbs (except where noted), the three destinations with the highest percent of participants reporting walking there at least once in a typical month are: Shops or services (such as a post office, bank, pharmacy, and/or dry cleaner) Public open space (e.g. public parks, green space) Small to medium sized grocery stores, fruit and vegetable stands, and/or specialty food stores o In the GTA suburbs and City of Vancouver supermarkets rather than this category rounded out the top three destinations. Restaurants were also in the top three for City of Vancouver participants. Please see Table 16 for details on additional destinations. When participants in the cities and suburbs of the two regions are compared the following are noted: In the GTA, the rate of participants in the City of Toronto who walk to a public train station or cultural/entertainment venue is 6.6 and 4 times higher respectively than for GTA suburban participants. Shops or services in the most walked to destination among City of Toronto participants (80%), while public open space is the most walked to destination in the GTA suburbs (65.3%). While 80% of City of Toronto participants walk to shops or services at least once a month, only 45.6% of GTA suburban participants do so. Similarly, 75.1% of City of Toronto participants walk to small/medium- 24

31 sized grocery stores at least once a month, compared to just 40.1% of GTA suburban participants The difference between City and Vancouver and GVRD suburban participants is not quite as strong as observed in the GTA. For example, 2.5 times more City of Vancouver participants walk to a public train station and 2.4 times more walk to a cultural/entertainment venue compare to GVRD suburban participants. Walking to shops or services is the most walked to destination in the City of Vancouver (82.6%), while public open space is the most walked to destination in the GVRD suburbs (70.5%). Walking to a small/medium-sized grocery store is more common in the City of Vancouver (84%) compared to the GVRD suburbs (55.8%), although the percentages in both these regions are higher than their counterparts in the GTA 25

32 Table 16: Percent of Participants Walking to Destinations At Least Once in a Typical Month Note: yellow highlights indicate the highest percentage for that area, green the second highest and blue the third highest. Destination Percent of Participants Who Walk to Destination At Least Once in a Typical Month GTA (n=1.525) GVRD (n=1.223) City of Toronto (n=1,133) GTA suburbs (n=392) City of Vancouver (n=512) Shops or services (such as a post office, bank, pharmacy, and/or dry cleaner) Your workplace Supermarket Restaurant Place of worship Public open space (e.g. public parks, green space) Recreation centre, gym / fitness facility Public bus stop Public train station/stop(commuter/light rail, streetcar, subway) Elementary school or child care location Other schools (including middle/high schools, colleges, universities, etc.) Small to medium sized grocery stores, fruit and vegetable stands, and/or specialty food stores. Cultural/entertainment venue (art gallery, museum, music, cinemas, clubs, bars etc.) GVRD suburbs (n=711)

33 4.3 Important Factors in Neighbourhood Selection Participants were asked to rate the importance of various factors in moving to their current (e.g. access to transit, proximity to commercial services) on a scale of 1 (not at all important) to 4 (very important)21. The relative importance of one factor over another is determined by taking the mean of the participant responses for each individual factor. In the GTA, 'affordability/value' was the most important factor in participants moving to their current (mean value = 3.5), followed by 'ease of walking' (3.2), 'closeness to shops and services' (3.1), 'convenient access to work and other destinations on public transit' (3.1), 'the amount of interior space in your home' (3.1), and 'closeness to a wide range of small to medium sized grocery stores' (3.0). In the GVRD, 'affordability/value' was also the most important factor (3.5), followed by 'ease of walking' (3.2), 'the 'amount of interior space in your home' (3.1), 'closeness to shops and services' (3.0), 'closeness to a wide range of small to medium sized grocery stores' (2.9), and 'closeness to public open space' (2.9). Closeness to a particular cultural/ethnic community was the least important factor in both regions (GTA=1.7; GVRD=1.6). Closeness to elementary school or child care or early learning centre was the second least important factor for both regions (GTA=2.0; GVRD=1.8). Affordability/value was the most important factor for GTA/GVRD suburb participants and City of Toronto/Vancouver participants. For City of Vancouver participants, ease of walking was also the most important, with the same score as affordability/value. The amount of interior space in one s home was the second most important factor for GTA suburb (3.2) and GVRD suburb (3.2) participants. Convenient access to work and other destinations on public transit was the third most important factor for both City of Toronto (3.3) and City of Vancouver participants (3.2). 21 Survey question: Please rate how important each of the following reasons was in your decision to move to your current. For each reason, please select a number between 1 and 4, where 1= not at all important and 4 = very important. 27

34 Table 17: Important Factors in Moving to One's Current Neighbourhood Note: (Cell format -- mean values (standard deviation)). Yellow highlights indicate the highest percentage for that area, green the second highest and blue the third highest. GTA (n=1,525) GVRD (n=1,223) City of Toronto GTA suburbs City of GVRD Vancouver suburbs (n=1,133) (n=392) (n=512) (n=711) B1. Affordability/Value 3.5 (0.7) 3.5 (0.7) 3.5 (0.7) 3.5 (0.6) 3.4 (0.8) 3.5 (0.7) B2. Closeness to public open space (e.g. public parks, green space) 2.9 (0.9) 2.9 (0.9) 3.0 (0.9) 2.9 (1.0) 3.0 (0.9) 2.8 (0.9) B3. Closeness to job or school 2.8 (1.1) 2.6 (1.1) 2.9 (1.1) 2.7 (1.1) 2.8 (1.1) 2.5 (1.1) B4. Closeness to a bus stop (1.1) 2.7 (1.1) 3.1 (1.0) 3.0 (1.0) 2.4 (1.1) (1.1) B5. Closeness to a train (such as commuter/light rail, streetcar, subway) station or stop B6. Convenient access to work and other destinations on public transit B7. Closeness to a wide range of small to medium sized grocery stores, fruit and vegetable stands, and/or specialty food stores. 2.8 (1.1) 2.3 (1.1) 3.1 (1.0) 2.1 (1.0) 2.6 (1.1) 2.2 (1.1) 3.1 (1.0) 2.8 (1.1) 3.37 (1.0) 2.5 (1.1) 3.2 (1.0) 2.6 (1.1) 3.0 (0.9) 2.9 (0.9) 3.1 (0.9) 2.7 (1.0) 3.1 (0.8) 2.8 (0.9) B8. Closeness to restaurants 2.4 (1.0) 2.3 (1.0) 2.5 (1.0) 2.1 (0.9) 2.6 (1.0) 2.3 (0.9) B9. Closeness to shops and services (such as a post office, bank, pharmacy, and/or dry cleaner) 3.1 (0.8) 3.0 (0.9) 3.2 (0.8) 2.8 (0.9) 3.1 (0.9) 2.9 (0.9) B10. Ease of walking 3.2 (0.9) 3.2 (0.9) 3.4 (0.8) 2.9 (0.9) 3.4 (0.8) 3.1 (0.9) B11. Ease of bicycling 2.1 (1.1) 2.0 (1.1) 2.2 (1.1) 2.1 (1.0) 2.2 (1.1) 1.9 (1.0) B14. Quality of schools 2.2 (1.3) 2.0 (1.2) 2.2 (1.3) 2.4 (1.2) 1.8 (1.1) 2.1 (1.2) B15. Closeness to public recreation space for swimming, walking, jogging, running trails, social interaction, sports and playgrounds B18. Closeness to cultural/ entertainment venues (theatre, art gallery, museum, music, cinemas, clubs, etc.) B21. Closeness to elementary school or child care or early learning centre B22. Closeness to friends and family B23. Closeness to particular cultural/ethnic community 2.6 (1.0) 2.7 (0.9) 2.7 (1.0) 2.5 (1.0) 2.8 (0.9) 2.7 (0.9) 2.3 (1.0) 2.2 (0.9) 2.4 (1.0) 2.0 (0.9) 2.5 (1.0) 2.0 (0.9) 2.0 (1.2) 1.8 (1.1) 2.0 (1.2) 2.2 (1.2) 1.7 (1.0) 1.9 (1.2) 2.5 (1.0) 2.5 (1.0) 2.5 (1.0) 2.5 (1.0) 2.4 (1.0) 2.5 (1.0) 1.7 (0.9) 1.6 (0.9) 1.8 (1.0) 1.4 (0.7) 1.7 (0.9) 1.5 (0.8) 28

35 B25. The amount of interior space in your home 3.1 (0.8) 3.1 (0.8) 3.1 (0.8) 3.2 (0.8) 3.1 (0.9) 3.2 (0.8) B26. The size of your yard 2.3 (1.1) 2.2 (1.1) 2.1 (1.1) 2.7 (1.0) 1.8 (1.0) 2.4 (1.1) B27. The noise from traffic 2.7 (1.0) 2.8 (0.9) 2.7 (1.0) 2.9 (1.0) 2.8 (1.0) 2.9 (0.9) B28. Highway/freeway access from your home 2.5 (1.0) 2.2 (1.0) 2.5 (1.1) 2.8 (1.0) 1.8 (0.9) 2.4 (1.0) 4.4 Neighbourhood Trade-off Descriptives This section summarizes participant responses to eight trade-off questions. Each comparison describes two contrasting s one more walkable, one more auto dependent. In each comparison a pair of real-world trade-offs of types is presented (e.g. proximity to commercial services versus travel options, and access to public versus private recreation space). Six of the trade-offs are accompanied by images of the contrasting types. The other two trade-offs only use descriptive text to define each. Participants are asked three questions for each trade-off: a) Which they would prefer; b) What their current is more like; and c) Compared to their current, which they would hope to find if they were to move. For each trade-off, participant responses are summarized separately for the GTA and GVRD. Cross-tabulations were then performed between a participant s self-described current (question b) and their desire for change compared to their current (question c) for the purpose of determining latent demand. Latent demand refers to participants who are not currently living in the type of they actually prefer. There is a latent or unfilled demand for the type of they prefer. For example, participants may self-describe their current as autooriented but would prefer, if they were to move, a more pedestrian/transit-oriented than their current location. For each region, descriptive statistics related to the trade-off topic are provided below. Neighbourhood trade-off responses indicating strong preference for a pedestrian/transit-oriented or auto-oriented are summarized for city compared to suburb participants for the GTA and GVRD at the end of this section Trade-off #1: Lot size, Proximity of Commercial Services, Travel Options, Commute Distance, Transit Options The first trade-off question encompasses several factors including housing type, proximity of commercial services, travel options, and proximity to transit. This question was designed to gain an overall sense of the participant's preference towards several factors that relate 29

36 to walkability. The survey respondent was presented with the descriptions shown in Table 18 below and the following introductory text: First, we d like you to imagine moving to a new. Please read the descriptions below and then answer the four questions that follow. For anything we do not refer to in the description below, such as school quality, public safety, or housing costs, please assume that it is exactly the same as where you live now. To begin, please carefully read the descriptions of the s below. Table 18: Neighbourhood Trade-off #1 Neighbourhood A Neighbourhood B Within 1 kilometre or ½ mile of my home (a 10 minute walk) there is a mix of single family detached houses on smaller lots, town homes, semi-detached houses/duplexes, and mid-rise apartments and condominiums. Destinations such as shopping, a restaurant, a public library and a school are within a few blocks of my home. kilometres of my home. Local destinations are close enough that I can either walk or drive there. Parking there is limited. My one-way commute to work or school is 5 kilometres / 3 miles or less (a 10 minute drive; a 15 minute bicycle or transit trip). minute transit trip). Bus and/or train (such as commuter/light rail, streetcar, subway) stops are close enough that I can either walk or drive there. 30 Within 1 kilometre or ½ mile of my home (a 10 minute walk) there are only single-family houses on large lots. Destinations such as shopping, a restaurant, a public library and a school are within a few Destinations are far enough it is necessary to drive to there. Parking there is abundant. My one-way commute to work or school is 20 kilometres / 12 miles or more (a 30 minute drive; a 60 minute bicycle ride; a 50 Bus and/or train (such as commuter/light rail, streetcar, subway) stops are far enough it is necessary to drive to there. Respondents were then asked the following questions related to this comparison: Q1A. Assuming that there are no differences between the s apart from the ones we mentioned, which do you think you d rather live in, A or B? Q1B. How do you think you'd feel about living in Neighbourhood "A"? o Dislike very much (0, on a 0-10 Likert scale) o Like very much (10, on a 0-10 Likert scale) Q1C. How do you think you'd feel about living in Neighbourhood "B"? o Dislike very much (0, on a 0-10 Likert scale) o Like very much (10, on a 0-10 Likert scale) Q1D: Your current is (Select one) o More like A (0, on 0-10 Likert scale) o Equally like A & B (5), o More like B (10). Q1E: If you were to move, the you d hope to find would be

37 o More like A than your current (0 on 0-10 Likert scale), o Like your current (5), o More like B than your current (10). Responses between the two regions are very similar. When given the choice between only A or B just over 80 percent of participants would rather live in Neighbourhood A, a pedestrian/transit friendly (Table 19). However, a large percentage (over 50 percent) in both regions responded they felt neutral about the idea of living in B (Table 21). Over 60 percent in both regions indicated they would very much like to live in A (Table 20), as compared to 18.1 and 16 percent (GTA/GVRD) saying the same thing about B. Table 19: Q1A. Assuming that there are no differences between the s apart from the ones we mentioned, which do you think you d rather live in? GTA GVRD Frequency Percent Frequency Percent Neighbourhood A Neighbourhood B Table 20: Q1B. How do you think you'd feel about living in Neighbourhood "A"? GTA GVRD Frequency Percent Frequency Percent Dislike very much (0-2 on the Likert scale) Neutral (3-7 on the Likert scale) Like very much (8-10 on the Likert scale) Table 21: Q1C. How do you think you'd feel about living in Neighbourhood "B"? GTA GVRD Frequency Percent Frequency Percent Dislike very much (0-2 on the Likert scale) Neutral (3-7 on the Likert scale) Like very much (8-10 on the Likert scale) More than half of respondents in each region said their current is more like A, and more than 60 percent that the they would hope find (if moving ) would be similar to their current one (Table 22 and Table 23). More than 30 percent of 31

38 participants in both regions said their current is similar to both A and B. Table 22: GTA Q1D & Q1E Neighbourhood A Pedestrian/transitfriendly Q1d. Your current is more like 22 : Q1e. Neighbourhood you d hope to find 23 : 54.6% (883) More like A 25.4% (387) More like A than current Table 23: GVRD Q1D & Q1E Neighbourhood A Pedestrian/transitfriendly Q1d. Your current is more like 24 : Q1e. Neighbourhood you d hope to find 25 : 55.7% (681) More like A 27.7% (339) More like A than current Neighbourhood B Automobile friendly 12.1% (185) More like B 9.5% (145) More like B than current Neighbourhood B Automobile friendly 13.9% (170) More like B 9.2% (113) More like B than current 33.2% (507) similar to both A and B 65.1% (993) similar to current 30.4% (372) similar to both A and B 63.0% (771) similar to current When examined more closely, some additional observations between the two regions can be made. Looking only at the 185 people in the GTA who said in Question Q1d their current is more like B (the more auto-oriented ), 24 (13.0 percent) said they would very much like to find a more walkable like A (Question Q1e). In the GVRD, this percentage is higher percent (34 of 170) of the people who said their is more like B would very much like to find a more like A compared to their 22 Original responses along a Likert scale: 0= More Like A, 5= Equally like A & B, and 10= More Like B. Responses reported here were recoded to: More Like A = 0 to 2, Similar to Both A and B = 3 to 7, and 'More Like B = 8 to Original responses along a Likert scale: 0= More like A than your current, 5= Like your current and 10= More Like B than your current. Responses reported here were recoded to: More like A than your current = 0 to 2, Like your current = 3 to 7, and ' More Like B than your current = 8 to Original responses along a Likert scale: 0= More Like A, 5= Equally like A & B, and 10= More Like B. Responses reported here were recoded to: More Like A = 0 to 2, Similar to Both A and B = 3 to 7, and 'More Like B = 8 to Original responses along a Likert scale: 0= More like A than your current, 5= Like your current and 10= More Like B than your current. Responses reported here were recoded to: More like A than your current = 0 to 2, Like your current = 3 to 7, and ' More Like B than your current = 8 to

39 current. Of the 883 people in the GTA who said their is more like A, 38 (4.6 percent) said they would hope to find a more like B. Of the 681 people in the GVRD who said their is more like A, 38 (5.6 percent) said they would hope to find a more like B. Unlike the above comparison, the next seven comparisons focus on only two attributes. The pairings, which include a pedestrian/transit-oriented option and an automobile-oriented option, are intended to reflect common, real-world tradeoffs. In other words, it would not be common for the extremes of both presented attributes to be present in one. By forcing a trade-off, these pairings help to understand which attribute is more valued by the participant. These next seven trade-offs have the following three questions, with responses on a 0 to 10 Likert scale 26 : Question A: Your preference is: o 0= Strongly prefer A, o 3= Somewhat prefer A, o 5= Neutral, o 7= Somewhat prefer B, o 10= Strongly prefer B. Question B: Please indicate whether your current is more like A or B : o 0= More like A, o 5= Equally like A & B, o 10= More like B Question C: Regarding [the described attributes], the you d hope to find would be: o 0= More like A than your current, o 5= Like your current, o 10= More like B than your current. 26 Each comparison question uses the same questions and 0-11 Likert scale. However, in the survey itself, the order (left/right, right/left) of the more walkable and automobile dependency scenario was changed for each question. It is due to this that the more auto-oriented end of the Likert scale is either 0-2 or 8-10, and similarly for the more walkable oriented. 33

40 Trade-off #2: Walkability and Proximity of Commercial Services In this question participants were asked about their preferences regarding walkability and proximity to commercial services (Figure 5). Figure 5: Trade-Off #2 -- Walkability and Proximity of Commercial Services In both the GTA and GVRD, about half of the respondents strongly prefer Neighbourhood B, where they can walk to nearby shops and services, while just 12.4 percent and 14.0 percent respectively prefer a where commercial and residential s are kept separate (Table 24 and Table 25). Half of the respondents in both regions also say that their current is more like Neighbourhood B. Table 24: GTA Trade-Off #2 -- Q2A, Q2B & Q2C Neighbourhood A Commercial and residential areas are separate Q2A. Your preference is: Q2B. Your current is more like: Q2C. Neighbourhood you d hope to find: 12.4% (189) Prefer A 15.1% (230) More like A 7.5% (115) More like A than 34 Neighbourhood B Can walk to nearby shops and services 52.9% (807) Prefer B 49.9% (761) More like B 30.0% (457) More like B than 34.7% (529) Equally like A and B 35.0% (534) similar to both A and B 62.5% (953) similar to current

41 current current Table 25: GVRD Trade-Off #2 Q2A, Q2B & Q2C Neighbourhood A Neighbourhood B Commercial and Can walk to nearby residential areas are shops and services separate Q2A. Your preference is: Q2B. Your current is more like: Q2C. Neighbourhood you d hope to find: 14.0% (171) Prefer A 17.4% (213) More like A 8.5% (104) More like A than current 48.9% (598) Prefer B 47.8% (584) More like B 27.7% (339) More like B than current 37.1% (454) Equally like A and B 34.8% (426) similar to both A and B 63.8% (780) similar to current Of the 230 people in the GTA who said their is more like A (Q2B: commercial and residential areas are separate), 36 (15.7 percent) said that they would hope to find a more like B (Q2 C) (Table 24). In the GVRD, 23.0 percent (49 of 213) who said their is more like A would hope to find a more like B than their current (Table 25). Of the 761 people in the GTA who said their is more like B, 18 (2.4 percent) said they would hope to find a more like A. Of the 584 people in the GVRD who said their is more like B, 12 (2.1 percent) said they would hope to find a more like A. 35

42 Trade-off #3: Level of Activity and Mix of Housing Figure 6: Trade-Off #3 -- Level of Activity and Mix of Housing In both the GTA and GVRD, about 40 percent of participants strongly prefer a lively and active with a mix of housing types (Neighbourhood A ), while approximately 37 percent in both regions prefer characteristics from both Neighbourhood A and Neighbourhood B (Table 26 and Table 27). Over 40 percent of participants in both regions say their current is more like Neighbourhood A. Two-thirds of participants in both regions were satisfied with their current with respect to housing type and level of activity they would move to a similar to their current one. Table 26: GTA Trade-off #3 -- Q3A, Q3B & Q3C Neighbourhood A Neighbourhood B Lively and active; mix Single-detached of housing types homes; not very lively Q3A. Your preference is: Q3B. Your current is more like: Q2C. Neighbourhood you d hope to find: 39.9% (609) Prefer A 43.8% (668) More like A 19.7% (301) More like A than current or active 22.2% (339) Prefer B 16.9% (257) More like B 13.3% (203) More like B than current % (577) Equally prefer A and B 39.3% (600) similar to both A and B 67.0% (1,021) similar to current

43 Table 27: GVRD Trade-off #3 -- Q3A, Q3B & Q3C Neighbourhood A Neighbourhood B Lively and active; mix Single-detached of housing types homes; not very lively Q3A. Your preference is: Q3B. Your current is more like: Q3C. Neighbourhood you d hope to find: 41.0% (501) Prefer A 42.4% (519) More like A 19.0% (232) More like A than current or active 22.0% (269) Prefer B 18.9% (231) More like B 12.9% (158) More like B than current 37.0% (453) Equally prefer A and B 38.7% (473) similar to both A and B 68.1% (833) similar to current When considering the 257 people in the GTA who said their is more like B (single-detached homes; not very lively or active), 28 (10.9 percent) said that they would hope to find a more like A. Similarly, 10.4 percent (24 of 231) of the people in the GVRD who said their is more like B would hope to find a that is more lively and active and has a mix of housing types compared to their current. Of the 668 people in the GTA who said their is more like A, 53 (7.9 percent) said they would hope to find a more like B. Of the 519 people in the GVRD who said their is more like A, 41 (7.9percent) said they would hope to find a more like B Trade-off #4: Home Size and Travel Options Table 28: Trade-off #4: Home Size and Travel Options Neighbourhood A Neighbourhood B With larger homes with more interior living Where I can walk, cycle, or take public space, where the commercial areas are transit for some of my trips because distant (over 5 kilometres/3 miles or more commercial areas are nearby (within a 1 than a 45 minute walk away) from the kilometre/half mile or 10 minute-walk), even houses, even if this means I have to drive for if this means the homes are smaller with less all my trips. interior living space In the GTA, 46.1 percent of participants strongly prefer a where they can walk, cycle, or take public transit for some of their trips because commercial areas are nearby, even if it means living in a smaller home (Table 29). In the GVRD, 41.6 percent of participants prefer such a (Table 30). Just 11.5 percent in the GTA strongly prefer a with larger homes where it is necessary to drive to commercial areas; 12.7 percent prefer this type of in the GVRD. 37

44 In GTA (GVRD) 45 percent (43 percent) of participants say their current is more like Neighbourhood B, while 46.6 percent and 45.7 percent of participants in the GTA and GVRD respectively say their current is similar to both s A and B. A large majority of participants in both regions (about 70 percent) say that if they were to move, they would hope to find a similar to their current one in terms of house size and proximity to commercial areas. Table 29: GTA Trade-off #4 Q4A, Q4B & Q4C Neighbourhood A Larger homes with commercial areas more than a 45 min walk away min) Q4A. Your preference is: Q4B. Your current is more like: Q4C. Neighbourhood you d hope to find: 11.5% (176) Prefer A 8.1% (123) More like A 9.0% (137) More like A than current 38 Neighbourhood B Smaller homes with commercial areas in walking distance ( % (703) Prefer B 45.4% (692) More like B 20.3% (310) More like B than current Table 30: GVRD Trade-off #4 Q4A, Q4B & Q4C Neighbourhood A Larger homes with commercial areas more than a 45 min walk away min) Q4A. Your preference is: Q4B. Your current is more like: Q4C. Neighbourhood you d hope to find: 12.7% (155) Prefer A 11.0% (134) More like A 9.0% (137) More like A than current Neighbourhood B Smaller homes with commercial areas in walking distance ( % (509) Prefer B 43.3% (530) More like B 19.5% (239) More like B than current 42.4% (646) Equally prefer A and B 46.6% (710) similar to both A and B 70.7% (1,078) similar to current 45.7% (559) Equally prefer A and B 45.7% (559) similar to both A and B 71.8% (878) similar to current Of the 123 people in the GTA who said their is more like A 19 (15.4 percent) said that they would hope to find a more like B. In the GVRD, 25 of the 134 (18.7 percent) people who said their is more like A would hope to find a more like B than their current. Of the 692 people in the GTA who said their is more like B, 35 (5.1 percent) said they would hope to find a more

45 like A. Of the 530 people in the GVRD who said their is more like B, 32 (6.0 percent) said they would hope to find a more like A Trade-off #5: Lot Size and Commute Distance Figure 7: Trade-Off #5 -- Lot Size and Commute Distance About 40 percent of participants in both regions strongly prefer a with work, school, and other important destinations within 5 km, even if it means houses are closer together (Table 31 and Table 32). In the GTA, 44.6 percent say their current is more like Neighbourhood A, compared to 11.4 percent who say their current is more like B (Table 31). The remaining 44 percent feel their is similar to both A and B. Similarly, 42.2 percent in the GVRD say their current is more like A, and just 13.0 percent self-describe their current Neighbourhood as more like B (Table 32). Nearly 45 percent feel their is similar to both A and B. Approximately one-fifth of participants in both regions would hope to find a more walkable in terms of proximity to work and school compared to their current. 39

46 Table 31: GTA Trade-off #5 -- Q5A, Q5B & Q5C Neighbourhood A Houses closer together; work school, other important destinations within 5km destinations Q5A. Your preference is: Q5B. Your current is more like: Q5C. Neighbourhood you d hope to find: 40.3% (614) Prefer A 44.6% (680) More like A 22.6% (345) More like A than current Neighbourhood B Houses farther apart; must travel more than 25km to work, school, other important 17.1% (261) Prefer B 11.4% (174) More like B 12.5% (190) More like B than current 42.6% (650) Equally prefer A and B 44.0% (671) similar to both A and B 64.9% (990) similar to current Table 32: GVRD Trade-off #5 -- Q5A, Q5B & Q5C Neighbourhood A Houses closer together; work school, other important destinations within 5km destinations Q5A. Your preference is: Q5B. Your current is more like: Q5C. Neighbourhood you d hope to find: 38.7% (473) Prefer A 42.2% (516) More like A 21.0% (257) More like A than current Neighbourhood B Houses farther apart; must travel more than 25km to work, school, other important 15.9% (194) Prefer B 13.0% (159) More like B 11.3% (138) More like B than current 45.5% (556) Equally prefer A and B 44.8% (548) similar to both A and B 67.7% (828) similar to current Of the 174 people in the GTA who said their is more like B (must travel >25km to work, school, and houses are farther apart), 23 (13.2 percent) said that they would hope to find a more like A. In the GVRD, 10.7 percent (17 of 159) who said their is more like B would hope to find a more like A than their current. Of the 680 people in the GTA who said their is more like A, 67(9.9 percent) said they would hope to find a more like B. Of the 516 people in the GVRD who said their is more like A, 45 (8.7percent) said they would hope to find a more like B. 40

47 Trade-off #6: Street Design and Travel Options Figure 8: Trade-Off #6 -- Street Design and Travel Options In both regions 45.6 percent (GTA) to 42.1 percent (GVRD) of participants strongly prefer a with through streets with lots of foot/pedestrian traffic and where you can walk/cycle/take transit for some trips (Table 33 and Table 34). In the GTA, 51.9 percent say their current is more like Neighbourhood B, compared to 10.8 percent who say their current is more like A (Table 34). Similarly, 51.3 percent in the GVRD say their current is more like "B", and just 12.7 percent self-describe their current as more like A ( Table 34 and Table 35). Approximately one fifth of participants in both regions would hope to find a more walkable in terms of through street and transportation options as compared to their current. 41

48 Table 33: GTA Trade-off #6 -- Q6A, Q6B & Q6C Neighbourhood A Cul-de-sacs; few people from other s walking on them; must drive for all trips for some trips Q6A. Your preference is: Q6B. Your current is more like: Q6C. Neighbourhood you d hope to find: 16.3% (249) Prefer A 10.8% (165) More like A 10.2% (156) More like A than current Neighbourhood B Through streets with lots of foot/pedestrian traffic; can walk/cycle/take transit 45.6% (695) Prefer B 51.9% (792) More like B 23.2% (354) More like B than current 38.1% (581) Equally prefer A and B 37.2% (568) similar to both A and B 66.6% (1,015) similar to current Table 34: GVRD Trade-off #6 Q6A, Q6B & Q6C Neighbourhood A Cul-de-sacs; few people from other s walking on them; must drive for all trips for some trips Q6A. Your preference is: Q6B. Your current is more like: Q6C. Neighbourhood you d hope to find: 17.2% (210) Prefer A 12.7% (155) More like A 10.5% (129) More like A than current Neighbourhood B Through streets with lots of foot/pedestrian traffic; can walk/cycle/take transit 42.1% (515) Prefer B 51.3% (627) More like B 20.4% (249) More like B than current 40.7% (498) Equally prefer A and B 36.1% (441) similar to both A and B 69.1% (845) similar to current In the GTA, 10.9 percent (18 of 165) of people who said that their current is more like A (quiet cul-de-sacs, must drive for all trips) would hope to find a more walkable like B (Table 33). In the GVRD, 12.3 percent (19 of 155) who said their is more like A would hope to find a more like B than their current (Table 34). Of the 792 people in the GTA who said their is more like B, 41 (5.2 percent) said they would hope to find a more like A. Of the 627 people in the GVRD who said their is more like B, 50 (8.0 percent) said they would hope to find a more like A. 42

49 Trade-off #7: Public Recreation Opportunities and Lot Size Figure 9: Trade-off #7 -- Public Recreation Opportunities and Lot Size In both regions over 40 percent (GTA percent, GVRD percent) of participants strongly prefer Neighbourhood A (where it is a short walk to public recreation and greenspace, and there is little space for recreational activities on own property) (Table 35 and Table 36). A similar percentage of participants indicate they equally prefer s A and B (Table 35 and Table 36). In the GTA, 41.2 percent say their current is more like Neighbourhood A, compared to 10.2 percent who say their current is more like A (Table 31). Similarly, 43.5 percent in the GVRD say their current is more like A, and just 9.6 percent self-describe their current Neighbourhood as more like B (Table 35 and Table 36). Approximately one-fifth of participants in both regions would hope to find a more walkable in terms of through street and transportation options as compared to their current. 43

50 Table 35: GTA Trade-off #7 -- Q7A, Q7B & Q7C Neighbourhood A Short walk to public recreation and greenspace; little space for recreational activities on own property short walk Q7A. Your preference is: Q7B. Your current is more like: Q7C. Neighbourhood you d hope to find: 41.4% (632) Prefer A 41.2% (629) More like A 20.1% (307) More like A than current Neighbourhood B Ample space on own property for recreational activities; little public recreation and greenspace within 15.4% (235) Prefer B 10.2% (156) More like B 11.5% (175) More like B than current 43.1% (658) Equally prefer A and B 48.5% (740) similar to both A and B 68.4% (1,043) similar to current Table 36: GVRD Trade-off #7 -- Q7A, Q7B & Q7C Neighbourhood A Short walk to public recreation and greenspace; little space for recreational activities on own property short walk Q7A. Your preference is: Q7B. Your current is more like: Q7C. Neighbourhood you d hope to find: 44.2% (540) Prefer A 43.5% (532) More like A 20.7% (253) More like A than current Neighbourhood B Ample space on own property for recreational activities; little public recreation and greenspace within 12.2% (149) Prefer B 9.6% (117) More like B 8.7% (107) More like B than current 43.7% (534) Equally prefer A and B 46.9% (574) similar to both A and B 70.6% (863) similar to current Of the 156 people in the GTA who said their is more like B (lots of space on own property with minimal public recreation within a short walk), 18 (11.5 percent) said that they would hope to find a more like A (Table 35). In the GVRD, 15.4 percent (18 of 117) who said their is more like B would hope to find a more like A than their current (Table 36). Of the 629 people in the GTA who said their is more like A, 46 (7.3 percent) said they would hope to find a more like B. Of the 532 people in the GVRD who said their is more like A, 37 (7.0 percent) said they would hope to find a more like B. 44

51 Trade-off #8: Access to and Size of Food Outlets Figure 10: Trade-off #8 -- Access to and Size of Food Outlets In both regions 47.5 percent to 49.1 percent of participants strongly prefer Neighbourhood A, where one can easily walk to a wide range of small to medium size grocery stores, butchers, bakers, etc., (Table 37 and Table 38). Approximately 39 percent of participants indicate they equally prefer s A and B (Table 37 and Table 38). In the GTA and GVRD, 32.8 percent say their current is more like Neighbourhood A, compared to 19 percent in the GTA (17.3 percent GVRD) who say their current is more like B (Table 37 and Table 38). But even higher percentages of people say their current is equally like A and B (48.3 percent in GTA and 47.3 percent in GVRD). 45

52 Table 37: GTA Trade-off #8 Q8A, Q8B & Q8C Neighbourhood A Can easily walk to a wide range of small to medium size grocery stores, butchers, bakers, etc. 10 min drive Q8A. Your preference is: Q8B. Your current is more like: Q8C. Neighbourhood you d hope to find: 47.5% (725) Prefer A 32.8% (500) More like A 23.7% (361) More like A than current Neighbourhood B Few food stores within walking distance; several large supermarkets within 14.0% (213) Prefer B 19.0% (289) More like B 9.6% (146) More like B than current 38.5% (587) Equally prefer A and B 48.3% (736) similar to both A and B 66.8% (1,018) similar to current Table 38: GVRD Trade-off #8 -- Q8A, Q8B & Q8C Neighbourhood A Can easily walk to a wide range of small to medium size grocery stores, butchers, bakers, etc. 10 min drive Q8A. Your preference is: Q8B. Your current is more like: Q8C. Neighbourhood you d hope to find: 49.1% (601) Prefer A 32.8% (433) More like A 25.1% (307) More like A than current Neighbourhood B Few food stores within walking distance; several large supermarkets within 12.0% (147) Prefer B 17.3% (211) More like B 7.8% (95) More like B than current 38.8% (475) Equally prefer A and B 47.3% (579) similar to both A and B 67.1% (821) similar to current In the GTA, 18.0 percent (52 of 289) of people who said that their current is more like B (few food stores in walking distance) would hope to find a more walkable like A (Table 37). In the GVRD, 25.6 percent (54 of 211) who said their is more like B would hope to find a more like A than their current (Table 38). Of the 500 people in the GTA who said their is more like A, 15 (3.0 percent) said they would hope to find a more like B. Of the 433 people in the GVRD who said their is more like A, 14 (3.2 percent) said they would hope to find a more like B. 46

53 4.4.9 Comparing Neighbourhood Trade-off Responses by Participant Subregion (City & Suburbs) To explore any potential differences in preference and self-described current between participants who live in cities compared to those who live in suburban areas, trade-off responses were summarized for participants who live the City of Toronto (n=1,113), GTA suburbs (n=392), City of Vancouver (n=512), and the GVRD suburbs (n=711). Neighbourhood Preference For each trade-off question (Your preference is...), Table 39 shows the percentage of participants who strongly prefer 27 either a) a walking-oriented or b) an automobile-oriented. There are notable differences between city and suburban participants in the GTA and GVRD for preference responses as shown in the table below and as described in text after the table. Table 39: Participant responses by preference by subregion Neighbourhood Trade-off Trade-off #1: Lot size, proximity of commercial services, travel options, commute distance, transit options Trade-off #2: Walkability and proximity of commercial services Trade-off# 3: Level of activity and mix of housing Trade-off #4: Home size and travel options Trade-off #5: Lot size and commute distance Trade-off #6: Street design and travel options Trade-off #7: Public recreation opportunities and lot size Trade-off #8: Access to and size of food outlets City of Toronto (n=1,133) GTA suburbs (n=392) City of Vancouver (n=512) GVRD suburbs (n=711) a/b [a = Percent who strongly prefer more walkableoriented (0-2 or 8-10 on Likert scale) b = Percent who strongly prefer a more auto-oriented (0-2 or 8-10 on Likert scale)] 73.4/ / / / / / / / / / / / / / / / / / /7.2 29/ / / / / / / / / / / / /15.3 GTA 27 Strongly preferred are responses which are either 0-2 or 8-10 on the 0-10 Likert scale used in the survey question. 47

54 Strong preference for a pedestrian/transit-oriented is evident among City of Toronto participants. In Trade-off #1, which refers to several aspects of walkability, 73.4 percent of participants indicated they strongly prefer a pedestrian/transit-oriented compared to just 5.4 percent who strongly prefer an automobile-oriented. In the GTA suburbs, fewer participants indicated that they strongly prefer a pedestrian/transit-oriented. In Trade-off #1, 46.4 percent prefer a pedestrian/transit-oriented compared to 20.7 percent who strongly prefer an automobile-oriented. Being close to commercial services is popular among both in-city and suburban respondents. Among the seven specific trade-off questions 28, the highest percentage of responses indicating strong preference for a pedestrian/transit-oriented in both the City of Toronto and the GTA suburbs is "Trade-off #2: Walkability and proximity of commercial services", where 60.5 percent and 30.9 percent respectively strongly prefer such a. More city respondents prefer s where they can walk, cycle, or take public transit for some of their trips. The greatest discrepancy between GTA suburb participants and City of Toronto participants was in "Trade-off #6: Street design and travel options". The percentage of people who strongly preferred a where they can walk, cycle, or take public transit for some of their trips, even if it means it is designed with through-streets with people from other s walking or driving on them, is 2.3 times higher for participants in City of Toronto (53.4%) compared to GTA suburb participants (23.0%). GVRD City of Vancouver survey respondents also show strong preferences for walkable communities. In Trade-off #1, 74.1 percent indicated they strongly prefer a pedestrian/transit-oriented compared to only 5.5% who strongly prefer an automobile-oriented. More suburban respondents prefer walkable s to suburban ones. In the GVRD suburbs, fewer participants indicated that they strongly prefer a pedestrian/transit-oriented compared to City of Vancouver participants, however preference for such a is still more "common" than the alternative (a highly automobile-oriented ). In Trade-off #1, 56.7 percent prefer a pedestrian/transit-oriented compared to 12.0 percent who strongly prefer an automobile-oriented. A preference for being close to commercial services is most popular with in-city respondents, where suburban participants prefer nearby access to grocery stores and restaurants. Among the seven specific trade-off 28 Excludes Trade-off #1, which refers to several different aspects of walkability 48

55 questions 29, the strongest preference for a pedestrian/transit-oriented in the City of Vancouver is "Trade-off #2: Walkability and proximity of commercial services" (64.1%). Among GVRD suburb participants, the strongest preference was "Trade-off #8: Access to and size of food outlets" (40.2%). Preferences towards walkable s are stronger among incity respondents. Across all eight trade-offs, the percentage of people who strongly prefer a pedestrian/transit-oriented (0-2 or 8-10 on Likert scale) is an average of 22.1% higher among participants who live in the City of Vancouver. More city respondents prefer s where they can walk, cycle, or take public transit for some of their trips. The greatest discrepancy between City of Vancouver and GVRD suburb participants was in "Trade-off #6: Street design and travel options". The percentage of people who strongly preferred a where they can walk, cycle, or take public transit for some of their trips, even if it means it is designed with through-streets with people from other s walking or driving on them, is 1.9 times higher for participants in City of Vancouver (58.0%) compared to GVRD suburb participants (30.7%). Self-described Current Neighbourhood For each trade-off question, Table 40 shows two percentages in each cell indicating participants whose current is highly 30 a) walking-oriented or b) automobile-oriented. City and suburb participants self-describe their current very differently in both the GTA and GVRD. Key differences between city and suburb participant responses are shown in the table below and described in text after the table. 29 Excludes Trade-off #1, which refers to several different aspects of walkability 30 Very much like are responses which are either 0-2 or 8-10 on the 0-10 Likert scale used in the survey question. 49

56 Table 40: Participant responses by current (self-described) by sub-region Neighbourhood Trade-off Trade-off #1: Lot size, proximity of commercial services, travel options, commute distance, transit options Trade-off #2: Walkability and proximity of commercial services Trade-off# 3: Level of activity and mix of housing Trade-off #4: Home size and travel options Trade-off #5: Lot size and commute distance Trade-off #6: Street design and travel options Trade-off #7: Public recreation opportunities and lot size Trade-off #8 Access to and size of food outlets GTA City of Toronto (n=1,133) GTA suburbs (n=392) City of Vancouver (n=512) GVRD suburbs (n=711) a/b [a = % whose current is highly walking oriented (0-2 or 8-10 on Likert scale) b = % whose current is highly auto-oriented (0-2 or 8-10 on Likert scale)] 62.3/ / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /24.5 Twice as many in-city participants indicated that they live in a highly pedestrian/transit-oriented than suburban participants. In Trade-off #1, 62.3 percent of City of Toronto participants said their current is highly pedestrian/transit-oriented, while only 32.4 percent responded so in the GTA suburbs. By contrast, 8.0 percent of City of Toronto participants said their current is very automobile-oriented, compared to 24.0 percent of GTA suburb participants who responded this way. Among the seven specific trade-off questions 31, the highest percentage of responses indicating a highly pedestrian/transit-oriented current in both the City of Toronto and the GTA suburbs is "Trade-off #6: Street design and travel options" where 60.2 percent and 28.1 percent respectively live in such a. "Trade-off #8: Access to and size of food outlets" had the lowest percentage of responses for one s current being highly walkable for both City of Toronto (40.5 percent) and GTA suburb participants (10.5 percent). This trade-off also had the greatest percentage of participants indicating they live in a highly auto-oriented 31 Excludes Trade-off #1, which refers to several different aspects of walkability 50

57 13.2 percent in the City of Toronto and 35.7 in the GTA suburbs. Across all eight trade-offs, the percentage of people whose self-described their current as very pedestrian/transit-oriented (0-2 or 8-10 on Likert scale) is an average of 30.0% higher for participants who live in the City of Toronto. By contrast, the percentage of people who self-describe their current as very auto-oriented is an average of 17.3% higher among GTA suburb participants compared to City of Toronto participants. The greatest discrepancy between GTA suburb participants and City of Toronto participants when describing their current as very pedestrian/transit friendly was in "Trade-off #2: Walkability and proximity to commercial services", where the percentage of people who said their was very much like one that has houses and commercial areas within a 10 minute walk was 34.9% higher for City of Toronto participants (58.9%) compared to GTA suburb participants (24.0%). GVRD In Trade-off #1, about 10 percent more participants in both the City of Vancouver and the GVRD suburbs describe their current as highly transit/pedestrian-oriented compared to their GTA counterparts 72.5 percent of City of Vancouver participants said their current is highly pedestrian/transit-oriented, while 43.6 percent did so in the GVRD suburbs. Just 6.6 percent of City of Vancouver participants said their current is very automobile-oriented, compared to 19.1 percent of GVRD suburb participants who responded this way. Among the seven specific trade-off questions 32, the highest percentage of responses indicating a highly pedestrian/transit-oriented current in both the City of Vancouver and the GVRD suburbs is "Trade-off #6: Street design and travel options" where 70.7 percent and 37.3 percent respectively live in such a. Trade-off #8: Access to and size of food outlets had the lowest percentage of responses for current being highly walkable for City of Vancouver and GVRD suburb participants percent of City of Vancouver participants and 21.7 percent of GVRD suburb participants said their current was very much like one where they can easily walk to a wide range of small to medium sized grocery stores, fruit and vegetable stands, butchers, bakers, and specialty food stores. Among all trade-offs, this was the lowest response. When considering responses indicating a highly autooriented environment, "Trade-off #2: Walkability and proximity of commercial services had the highest percentage among City of 32 Excludes Trade-off #1, which refers to several different aspects of walkability 51

58 Vancouver participants (10.5 percent), while among GVRD suburb participants it was Trade-off #3: Level of activity and mix of housing (25.9 percent). Across all eight trade-offs, the percentage of people whose self-described their current as very pedestrian/transit-oriented (0-2 or 8-10 on Likert scale) is an average of 29.7% higher for participants who live in the City of Vancouver. By contrast, the percentage of people who self-describe their current as very auto-oriented is an average of 13.9 % higher among GVRD suburb participants compared to City of Vancouver participants. The largest difference among GVRD participants indicating they live in a very pedestrian/transit-oriented was for Trade-off #6: Street design and travel options, where the percentage of people who said Where I can walk, cycle, or take public transit for some of my trips, even if it has through streets and people from other s walking or driving on them was 33.4% higher for City of Vancouver participants (70.7%) compared to GVRD suburb participants (37.3%) Latent demand using objectively measured data This section makes use of objective, postal code-level built environment measures developed for the City of Toronto to further explore the number of participants not living in the type of they would prefer. This mismatch in preference and current represents an unmet demand for the preferred type, or a latent demand for it. Built environment measures were creating using 1km pedestrianaccessible road-based buffers originating from each postal code centroid, and then calculating built environment and transportation variables for these buffers. City of Toronto participants where categorized into a walkability quartile using a walk index variable based on the postal code they are located in. The walkability index is a measure of utilitarian walkability, and is a composite the following variables: residential density, retail floor-to-area ratio, land use mix, and intersection density. Please refer to Appendix D for further details regarding the derivation of the walkability index. Using an objective measure of walkability is different than using the selfdescribed responses provided by the participant. An individual can have a different perception of their s walkability based on several personal factors (e.g. age, lifestyle, other types of s they are familiar with). Objectively measured built environment data provides an alternative lens to explore how preference and where people currently live may differ from one another. The range for the postal-code level, city-wide walkability index values was quartiled and used to categorize the City of Toronto participants 52

59 (n=1,129) 33. The city-wide range was used rather than the range of the subset of postal codes containing participants in order to set the values in a city-wide context. Table 41 shows the count of survey participants in each objective walkability quartile. The medium-low walkability quartile has the largest number of participants (63.3%), while the high walkability quartile has the fewest (2.0%). Table 41: Walk Index Quartile Frequencies for City of Toronto Participants Using City-wide Range Objective City-wide (all postal codes) Walk Quartile Walk Index Ranges Survey Participant Counts Quartile 1: Low walkability thru (17.4%) Quartile 2: Medium-low thru (63.3%) walkability Quartile 3: Medium-high 3.78 thru (17.2%) walkability Quartile 4: High walkability 9.23 thru (2.0%) Total 1,129 (100%) Participants were further grouped into low walk (Quartiles 1 & 2) and high walk categories (Quartiles 3 & 4). Question C in each trade-off asked people, along a zero to 10 Likert scale if... the [they d] hope to find would be 34 : o 0= More like A than [their] current, o 5= Like [their] current, o 10= More like B than [their] current. Responses were grouped into strongly prefer A (0-2 on the 0-10 scale) and strongly prefer B (8-10). For each trade-off A and B were categorized as more pedestrian/transit or more auto oriented. Table 42 shows the count of City of Toronto survey participants for each trade-off question C, who strongly prefer the more walkable over their current one, and who prefer the more auto oriented over their current. 33 Four City of Toronto participants are located in postal codes where <75% of their 1km network buffer area is located within the City of Toronto (based on a GTA walkable road network). The participants in these postal codes are excluded from the analysis. 34 Each comparison question uses the same questions and 0-10 Likert scale. However, in the survey itself, the order (left/right, right/left) of the more walkable and automobile dependency scenario was changed for each question. It is due to this that the more auto-oriented end of the Likert scale is either 0-2 or 8-10, and similarly for the more walkable oriented. 53

60 Table 42: City of Toronto survey participants preferences compared to current Note: value in parentheses indicates percent of all City of Toronto participants, n=1,133) Neighbourhood trade-off Strongly prefer pedestrian/transitoriented environment more than current (0-2 or 8-10 on Likert scale) Strongly prefer auto-oriented environment more than current (0-2 or 8-10 on Trade-off #2: Walkability and proximity of commercial services Likert scale) 371 (32.7%) 63 (5.6%) Trade-off# 3: Level of activity and mix of housing Trade-off #4: Home size and travel options Trade-off #5: Lot size and commute distance Trade-off #6: Street design and travel options Trade-off #7: Public recreation opportunities and lot size 255 (22.5%) 114 (10.1%) 254 (22.4%) 71 (6.3%) 290 (25.6%) 99 (8.7%) 300 (26.5%) 86 (7.6%) 247 (21.8%) 112 (9.9%) Trade-off #8 287 (25.3%) 95 (8.4%) Access to and size of food outlets Cross-tabulations were generated between a participant s objective current grouping (low walk: Quartiles 1 & 2; high walk: Quartiles 3 & 4) and the pedestrian/auto oriented groupings of their desire for change (Table 43). These cross-tabulations show those people who are not in the type that they prefer, and represent a latent demand of unmet preference. The results are summarized in Table 43 below. 54

61 Table 43: Latent demand for more pedestrian/transit-oriented or autooriented s using City of Toronto walkability index Note: Values in parentheses indicate percent of participants in low walk (n_total=912, Quartiles 1 & 2, n=197 and n=715 respectively) or high walk (n_total=217, Quartiles 3 & 4, n=194 and n=23 respectively) s. Neighbourhood trade-off Trade-off #2: Walkability and proximity of commercial services Trade-off# 3: Level of activity and mix of housing Trade-off #4: Home size and travel options Trade-off #5: Lot size and commute distance Trade-off #6: Street design and travel options Trade-off #7: Public recreation opportunities and lot size Trade-off #8 Access to and size of food outlets Latent demand for pedestrian/transitoriented environment 35 Latent demand for auto-oriented environment (31.8%) 7 (3.2%) 193 (21.2%) 12 (5.5%) 187 (20.5%) 13 (6.0%) 223 (24.5%) 14 (6.5%) 231 (25.3%) 13 (6.0%) 190 (20.8%) 23 (10.6%) 216 (23.7%) 8 (3.7%) Among participants who currently live in a less walkable environment as defined by the objective walk index (quartiles 1 & 2), demand for a more walkable environment ranges from 20.5% and 31.8% across the seven individual trade-offs. Desire for a close proximity to commercial services (trade-off #2) had the highest proportion participants desiring change from their current, less walkable. Better street connectivity and more travel options (trade-off #6) had the second highest percentage of participants desiring change from their current, less walkable (25.3%). When considering participants who currently live in a more walkable (quartiles 3 & 4), desire for a less walkable is much less, ranging from 3.2% to 10.6% across the seven trade-offs in Table 43. More private space for recreation (trade-off #7) and larger lot size (trade-off #5) are the top two auto-oriented aspects of s that people living in more walkable s would like to see more of (10.6% and 6.5% respectively). 35 Cross-tabulation of objective current quartiles 1 & 2 (n=912) with question c 36 Cross-tabulation objective current quartiles 3 & 4 (n=217) with question c 55

62 Conclusions from Neighbourhood Trade-offs Overall, residential satisfaction is quite high. Across all trade-off questions in both regions, the percentage of people who would move to a that is similar to their current ranged from 62 to 72 percent. Across trade-off questions #2 through #8, the percentage of people who prefer a very walkable (0-2 or 8-10 on Likert scale) ranged from percent in both regions. The percentage of people who prefer a with both characteristics (3-7 on Likert scale) ranged from percent. Between 10.2 and 22.2 percent prefer an auto-oriented (0-2 or 8-10 on Likert scale). In both regions, there is strong demand for nearby access to commercial services and food outlets. Preference for a very walkable (0-2 or 8-10 on Likert scale) was strongest for trade-off #2 walkability and proximity to commercial services -- in the GTA (52.9 percent). The second highest preference for a walkable was for trade-off #8 access to and size of food outlets (47.5 percent). In the GVRD, preference for a very walkable was highest for trade-off #8 access to and size of food outlets (49.1 percent), and second highest for trade-off #2 walkability and proximity to commercial services (48.9 percent). Respondents desire to move to a more walkable compared to their current ranged from percent across all trade-offs; the highest percentage of people that would like to move to a more walkable was found in trade-off #2 walkability and proximity of commercial services with 30.0 percent in GTA and 27.7 percent in GVRD wanting to move to a closer to commercial services. The strongest preference for an auto-oriented was in Trade-off #3 level of activity and mix of housing -- where there are single family houses on larger lots, even if it means there is not an area with services or activities nearby (22.2 percent and 22.0 percent in GTA and GVRD respectively). The survey results show strong evidence of latent demand for more walkable environments in both regions=, but more so in the GVRD. Looking at just those people who described their current as like the more auto-oriented (0-2 or 8-10 on Likert scale), trade-off #8 access to and size of food outlets -- had the greatest percentage of people desiring to move to a more walkable compared to their current : 18 percent in GTA and 25.6 percent in GVRD. Trade-off #4 home size and travel options -- had the second largest discrepancy in the GTA, where 15.4 percent of people living in more auto-oriented s wanted to move to a more centrally 56

63 located, walkable. In the case of the GVRD, the second largest discrepancy was found for trade-off #2 walkability and proximity to commercial services, where 23 percent of people currently living in more auto-oriented s desired to change to a more walkable that is closer to commercial services. When considering latent demand for less walkable s (participants who describe their current as very walkable but desire to move to an auto-oriented ), trade-off #5 lot size and commute distance had the greatest percentage of responses in the GTA (9.9 percent) and GVRD (8.7 percent). Although participants in the city and suburbs both prefer a pedestrian/transit-oriented, the magnitude of such a preference was substantially greater among city participants in both the GTA and GVRD. Among city and suburb participants in the GTA, the trade-off with the greatest percentage of responses 37 for a pedestrian/transit-oriented environment was "Trade-off #2: Walkability and proximity of commercial services". In the GVRD, city participants also had the highest percentage strongly preferring a pedestrian/transitoriented for Trade-off #2, while among GVRD suburb participants, the highest percentage was Trade-off #8: Access to and size of food outlets. More city participants indicate that their current is very walkable than suburb participants an average of about 30% higher in the GTA and GVRD. In the both regions, Trade-off #6: Street design and travel options" had the highest percentage of responses for a pedestrian/transit-oriented type for city and suburb participants. Trade-off #8: Access to and size of food outlets had the greatest percentage of responses indicating they live in a highly autooriented in the GTA city and suburbs. Among City of Vancouver participants, the highest percentage for a very auto-oriented environment was "Trade-off #2: Walkability and proximity of commercial services, while among GVRD suburbs it was Trade-off #3: Level of activity and mix of housing. Finally, latent demand for more walkable s was also found among City of Toronto participants using an objective walkability index. Among participants living in the low and medium-low quartiles of objective walkability, demand for more walkable aspects of the built environment was present for between 20.5 percent to 31.8 percent of participants across the seven individual trade-offs. Desire to be in walking distance from commercial services had the largest percentage of participants desiring change from their current (31.8 percent), followed by better street connectivity and travel options (25.3 percent). 37 Excludes Trade-off #1, which refers to several different aspects of walkability 57

64 5.0 ANALYTICAL METHODS AND RESULTS 5.1 Methods & Outcomes of Principal Component Analysis Principal component analysis (PCA) is a commonly applied technique to reduce a set of correlated variables into artificial variables called principal components, which explain a high percentage of the variation among the observed variables 38 To use PCA it is suggested that correlations among at least some variables in the analysis should be greater than 0.3. The input trade-off variables used in the region-specific PCA are all highly correlated and exceed this recommended threshold (see Appendix C for correlation matrices). PCA is used to extract a factor that accounts for a large amount of the variation among the individual trade-off responses. This single factor per participant can then be used in subsequent analysis, instead of considering each of the eight trade-off responses separately. The following sections of this report provide analysis results by grouping participants into low, medium-low, medium-high, and high walkability quartiles based on their combined responses to the individual trade-off questions. Principal Components Analysis (PCA) was used to extract a principal component for each of the following two sets of the individual trade-off responses for: Question A: Your preference 39 is: 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B. Question B: Please indicate whether your current 40 is more like A or B : 0= More like A, 3= Somewhat like A, 5= Equally like A & B, 7= Somewhat like B, 10= More like B Table 44 (Table 45) shows the extracted components for the GTA (GVRD) current trade-offs (Question B). Again, one principal 38 Tuffery, S. (2011). Data mining and statistics for decision making. John Wiley and Sons: Wiley, West Sussex, UK. 39 For the preference principal component, responses for trade-offs #2 through #8 were used 40 For the current (self-described) principal component, responses for trade-offs #1 through #8 were used 58

65 component was extracted for each region, explaining 55.9 (GTA) and 56.2 (GVRD) percent of the variance among eight input variables. Table 44: GTA Current Neighbourhood Factor Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Component Total Percent of Variance Cumulative Percent Total Percent of Variance Cumulative Percent Extraction Method: Principal Component Analysis. a Region that participant is located in = GTA Table 45: GVRD Current Neighbourhood Factor Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Component Total Percent of Variance Cumulative Percent Total Percent of Variance Cumulative Percent Extraction Method: Principal Component Analysis. a Region that participant is located in = GVRD Table 46 (Table 47) shows the extracted components for the GTA (GVRD) preference trade-offs (Question A). Only components with eigenvalues greater than one are of interest, as components with values less than one explain less variation than the original input variable. In this case, one principal component was extracted in each region, which explains 58.0 (GTA) and 57.0 (GVRD) percent of the variance among the seven input variables. 59

66 Table 46: GTA Neighbourhood Preference Factor Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % Extraction Method: Principal Component Analysis. a Region that participant is located in = GTA Table 47: GVRD Neighbourhood Preference Factor Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % Extraction Method: Principal Component Analysis. a Region that participant is located in = GVRD Table 48 (Table 49) shows the factor loadings of each trade-off variable on the current (preferred) factor. The factor loadings are the correlations between the variable and the component, ranging from -1 to +1. PCA with a Varimax 41 rotation was used to generate principal components, or factors for preferred responses and current responses. The correlations between the input variables and the extracted component for each region are all highly correlated, with factor loadings ranging from to in the GTA and to in the GVRD. 41 Varimax is an orthogonal rotation that forces factors to be uncorrelated with one another (Tuffery, S. (2011). Data mining and statistics for decision making. John Wiley and Sons: Wiley, West Sussex, UK.) 60

67 Table 48: Factor Extraction Component Matrix for Current Neighbourhood (Question B) Neighbourhood Trade-off Loadings on current factor (component 1) GTA GVRD Trade-off #1 -- Lot size, proximity of commercial services, travel options, commute distance, transit options Trade-off #2 -- Walkability and proximity of commercial services Trade-off# 3 -- Level of activity and mix of housing Trade-off #4 -- Home size and travel options Trade-off #5 -- Lot size and commute distance Trade-off #6 -- Street design and travel options Trade-off #7 -- Public recreation opportunities and lot size Trade-off #8 -- Access to and size of food outlets Table 49: Factor Extraction Component Matrix for Neighbourhood Preference (Question A) Neighbourhood Trade-off Loadings on preference factor (component 1) GTA GVRD Trade-off #2 -- Walkability and proximity of commercial services Trade-off# 3 -- Level of activity and mix of housing Trade-off #4 -- Home size and travel options Trade-off #5 -- Lot size and commute distance Trade-off #6 -- Street design and travel options Trade-off #7 -- Public recreation opportunities and lot size Trade-off #8 -- Access to and size of food outlets For each participant, the individual trade-off loadings were used to create an individual factor score for each participant. A least squares regression approach was used to normalize the values to a mean of zero 42. Positive factor score values indicate a respondent s preference for, or that their current is more walkable (pedestrian/transit-oriented). Negative values represent a more autooriented and preferences for such s. The range of factor scores, for both the preferred and current s were then quartiled independently for each region and each participant was assigned to one of four quartiles: 1= Low walkability 2= Medium-low walkability 3= Medium-high walkability 42 See DiStefano et al. (2009). Understanding and Using Factor Scores Considerations for the Applied Researcher. Practical Assessment, Research & Evaluation, 14(20),

68 4= High walkability One thing to note is the range of factor scores was quartiled, so there are not necessarily an equal numbers of participants in each quartile. Please see the table below for frequency counts and quartile ranges. The majority of participants in both regions self-describe their current as either being in the highest or second highest walkability quartile 75.8 percent for GTA participants and 71.3 percent of GVRD participants (Table 50). In contrast for the low walkability quartile there are 74 (4.9 percent) participants in GTA and 86 (7 percent) in GVRD. While these numbers are lower in comparison to the counts for higher walkability quartiles, they are still sufficient for analysis purposes. Table 50: Participant Counts by Current (Self-described) Neighbourhood Walkability Quartiles Based on Region Specific Walkability Quartiles 43 GTA GVRD Walkability quartile (n=1,525) (n=1,223) Quartile 1: Low walkability 74 (4.9%) 86 (7.0%) Quartile 2: Medium-low walkability Quartile 3: Medium-high walkability Quartile 4: High walkability 296 (19.4%) 265 (21.7%) 573 (37.6%) 430 (35.2%) 582 (38.2%) 442 (36.1%) In order to explore distributions at the sub-regional level, frequencies for current, self-described walkability quartiles, as used above, are summarized by city and suburbs in Table 51. In the City of Toronto, 47.4 percent of survey participants describe their current as highly walkable, while only 11.4 percent do so in the GTA suburbs. Similarly, 58.2 percent of City of Vancouver participants describe their as highly walkable, compared to 20.3 percent of GVRD suburb participants (Table 51). 43 Quartile ranges GTA: ( thru =1) ( thru =2) ( thru =3) ( thru =4) Quartile ranges GVRD: ( thru =1) ( thru =2) ( thru =3) ( thru =4) 62

69 Table 51: Participant Counts by Current (Self-described) Neighbourhood Walkability Quartiles City of GTA City of GVRD Toronto Walkability quartile suburbs Vancouver suburbs (n=1,133) (n=392) (n=512) (n=711) Quartile 1: Low walkability 20 (1.8%) 54 (13.8%) 3 (0.6%) 83 (11.7%) Quartile 2: Medium-low walkability Quartile 3: Medium-high walkability 154 (13.6%) 142 (36.2%) 60 (11.7%) 205 (28.8%) 422 (37.3%) 151 (38.5%) 151 (29.5%) 279 (39.2%) Quartile 4: High walkability 537 (47.4%) 45 (11.4%) 298 (58.2%) 144 (20.3%) Neighbourhood preference quartile frequencies are shown in Table 52 for the GTA and GVRD. Similar to the current quartile frequencies, about three-quarters of participants in both regions are located in the top two quartiles of high walkability. Approximately 7 percent of participants are in the low walkability (first quartile) in each region. Table 52: Participant Counts by Preferred Neighbourhood Walkability Quartiles Based on Region Specific Walkability Quartiles Walkability quartile GTA (n=1,525) GVRD (n=1,223) Quartile 1: Low walkability 116 (7.6%) 91 (7.4%) Quartile 2: Medium-low walkability Quartile 3: Medium-high walkability Quartile 4: High walkability 319 (20.9%) 244 (20.0%) 501 (32.9%) 422 (34.5%) 589 (38.6%) 466 (38.1%) When preference quartile frequencies are generated for city and suburb participants in both regions, there is a greater preference for a highly walkable in the city sub-regions (Table 53). In the City of Toronto, 46.7 percent prefer a highly walkable, compared to 15.3 percent in the GTA suburbs. In the City of Vancouver, 53.9 percent prefer such a, compared to 26.7 percent of GVRD suburb participants. In the GTA, 34 percent more participants fall into the low walkability and medium-low walkability quartiles compared to City of Toronto participants. Similarly, preference for such a in the GVRD is 24.7 percent higher than among City of Vancouver participants. 63

70 Table 53: Participant Counts by Preferred Neighbourhood Walkability Quartiles Based on Region Specific Walkability Quartiles City of GTA City of GVRD Toronto Walkability quartile suburbs Vancouver suburbs (n=1,133) (n=392) (n=512) (n=711) Quartile 1: Low walkability 41 (3.6%) 75 (19.1%) 12 (2.3%) 79 (11.1%) Quartile 2: Medium-low walkability Quartile 3: Medium-high walkability 183 (16.2%) 136 (34.7%) 55 (10.7%) 189 (26.6%) 380 (33.5%) 121 (30.9%) 169 (33.0%) 253 (35.6%) Quartile 4: High walkability 529 (46.7%) 60 (15.3%) 276 (53.9%) 190 (26.7%) 5.2 Relationship between Current Neighbourhood and Physical Activity/Travel Outcomes Using the quartiles for current (described above), differences in the mean values for various activity variables are analyzed. Table 54 (Table 55) provides the GTA (GRTA) descriptive results by quartile, with additional ANOVA analysis to indicate if the differences across the quartiles of current, walkability are significantly different from the high walkability quartile (#4). Activity variables include frequency and time spent walking for utilitarian or recreational purposes, bicycle travel frequency, public transit travel frequency, vehicle travel frequency, and weekly vehicle kilometres travelled (VKT). BMI was also compared across current quartiles. 64

71 Table 54: Mean Walk Trips, VKT & BMI by Current Neighbourhood Walkability (self-described) Quartile (GTA) Note: standard deviation in parentheses BMI Walkability quartile (current ) 1 Low walkability 2 Mediumlow walkability 3 Mediumhigh walkability 4 High walkability Freq. Walking for utilitarian purposes (days/wk) Time spent Walking for utilitarian purposes (daily avg minutes) Freq. Walking for recreational purposes (days/wk) Time spent Walking for recreational purposes (daily avg minutes) Freq. Walking for any purpose (days/wk) Freq. Bicycling for any purpose (days/wk) Freq. Travel on public transit (days/wk) Freq. Vehicle travel (days/wk) Time spent - Vehicle travel (days/wk) Weekly Vehicle Kilometre Travelled (n=1525) (n=1020) (n=1525) (n=1090) (n=1525) (n=1525) (n=1525) (n=1525) (n=1169) (n=1042) (n=1380) 1.3 (2.2)* 26.1 (14.3) 1.8 (2.4)* 29.4 (23.4) 2.7 (2.6)* 31.3 (27.4) 4 (2.6) 32.1 (24.2) *significantly different (p<0.05) than the reference group, the high walkability quartile, # (2.5) 39.4 (25.3) 3 (2.9)* 1 (2) 0.6 (1.8)* 5.8 (1.9)* 51.4 (41.2) 2.9 (2.6) 35.1 (25.6)* 3.9 (2.8)* 1.4 (2.3) 1.1 (2.1)* 5.2 (2.4)* 52.1 (43.7) (235.3)* 316 (248.2)* 2.8 (2.5) 36 (26.4)* 4.3 (2.7)* 1.2 (2.2) 1.8 (2.4)* 4.3 (2.7)* 47.1 (38) (261.9)* 2.9 (2.6) 41.7 (32.3) 5.3 (2.4) 1.2 (2.2) 2.5 (2.5) 2.8 (2.7) 47.7 (38.2) (181.6) 27.3 (5.5) 26.9 (5.2) 26.5 (5.4) 26 (5.6) 65

72 Table 55: Mean Walk Trips, VKT & BMI by Current Neighbourhood Walkability (self-described) Quartile (GVRD) Notes: standard deviation in parentheses Walkability quartile (current ) 1 Low walkability 2 Mediumlow walkability 3 Mediumhigh walkability 4 High walkability Freq. Walking for utilitarian purposes (days/wk) Time spent Walking for utilitarian purposes (daily avg minutes) Freq. Walking for recreational purposes (days/wk) Time spent Walking for recreational purposes (daily avg minutes) Freq. Walking for any purpose (days/wk) Freq. Bicycling for any purpose (days/wk) Freq. Travel on public transit (days/wk) Freq. Vehicle travel (days/wk) Time spent - Vehicle travel (days/wk) Weekly Vehicle Kilometre Travelled (n=1223) (n=767) (n=1223) (n=941) (n=1223) (n=1223) (n=1223) (n=1223) (n=1002) (n=787) (n=1124) 1.2 (2.1)* 42.2 (27) 3.2 (2.6) 51.5 (34.9)* 3.7 (2.7)* 0.7 (1.5) 0.8 (1.8)* 5.8 (1.6)* 51.3 (38.9)* 1.6 (2.4)* (2.6) 37.2 (23.6) 3.9 (2.8)* 1.2 (2.2) 0.8 (1.8)* 5.1 (2.4)* 48.6 (29.1) (38.5)* 2.4 (2.6)* 30.4 (24.3) 4.1 (2.6) 33.3 (24.1) *significantly different (p<0.05) than the reference group, the high walkability quartile, # (2.5) 38 (27.9) 4.4 (2.6)* 1.1 (2.2) 1.6 (2.3)* 4.4 (2.6)* 45.5 (33.5)* 349 (436.8)* (215.9)* (220.7)* 3.3 (2.5) 41.3 (28.5) 5.5 (2.2) 1.2 (2.1) 1.8 (2.3) 3.1 (2.7) 38 (26) (178.8) BMI 26.1 (5.5) 26.4 (4.8) 26.3 (5.5) 25.5 (5.4) 66

73 Both GTA and GVRD participants who self-describe their current as being very walkable (Quartile 4) travel significantly more on foot for utilitarian purposes compared to participants who live in less walkable s (GTA: F3,1521 = , p< ; GVRD: F3,1219 = 76.7, p<0.001). GTA participants in Quartile 4 travel on foot an average of 4 days per week, compared to 1.3 days per week for participants living in the lowest quartile of walkability (Table 54 and Figure 11). Similarly, GVRD participants who live in Quartile 4 also walk significantly more for utilitarian purposes (4.1 days per week) compared to those in the other three quartiles, who walk 1.2 to 2.4 days per week (Table 55 and Figure 12). When walking frequency for relaxation and recreation is considered, there is not a significant difference between walkability quartiles for the GTA or GVRD, where average weekly walk trips ranging from 2.2 to 2.9 (F3,1521 = 1.7, p=0.158), and 3 to 3.3 (F3,1219 = 1.07, p=0.361), respectively. When walk trips for any purpose (utilitarian or recreational) are considered, GTA participants in the highest quartile walk an average of 5.3 days per week, while participants in the lowest quartile and second lowest quartile walk 3 days and 3.9 days per week respectively. GVRD participants show similar walk trip frequencies - the highest quartile has an average value of 5.5 days per week, while the lowest quartile has a higher than the GTA at 3.7 days per week. The differences are significant between quartiles in both regions (GTA: F3,1521 = 31.8, p<0.001, GVRD: F3,1219 = 29.5, p<0.001). For GTA participants, time spent walking for utilitarian purposes ranged from 26.1 (Quartile 1) to 32.1 minutes per day (Quartile 4), however the difference between quartiles was not significant (F3,1016 =0.772, p=0.510). In the GVRD, in contrast to GTA and unexpectedly, the time spent walking for utilitarian purposes was greatest in the lowest walkability quartile (42.2 minutes per day), but the differences were still not significant(f3,763 = 2.03, p=0.108). It is noted that of the 767 people who walked for utilitarian purposes, there are only 25 in Quartile 1. This is lower than desirable number to have in analysis set, and may be contributing to the unexpected results. The other quartiles have a larger share of the participants (112 in Quartile 2, 259 in Quartile 3 and 371 in Quartile 4. Weekly vehicle kilometres traveled (VKT) was significantly different between walkability quartiles (GTA: F3,1038 = 25.7, p<0.001, GVRD: F3,783 = 21.5, p<0.001)with participants in the lowest quartile in both regions 44 F ij: F=test statistic based on F-distribution; i=degrees of freedom between groups; j=degrees of freedom within groups 45 p=significance value, p<0.5 means there is a significant difference in mean values between groups (walkability quartiles) 67

74 driving just over twice the distance as their counterparts in the highest walkability quartile. Figure 11 and Figure 12 provides a bar graph showing frequency of walking (utilitarian, recreation, combined) and vehicle travel. Figure 11: GTA Walk Frequency and Automobile Travel Frequency by Participant s Current Neighbourhood Factor Score Figure 12: GVRD Walk Frequency and Automobile Travel Frequency by Participant s Current Neighbourhood Factor Score Although mean BMI among GTA participants increased for each quartile removed from the highest walkability quartile, the differences were not significant (F3,1376 = 2.14, p=0.094). BMI was also not significantly different among walkability quartiles for GVRD participants (F3,783 = 1.85 p=0.137) (Figure 13). 68

75 Figure 13: Mean BMI by Participant s Current Neighbourhood Type (n_gta=1,380 n_gvrd=1,124) The ANOVA analyses shows that, in both regions, there is a significant difference in physical activity and travel behaviour based on the type of a participant describes themselves as living in. Participants who describe their s as highly walkable walk significantly more for utilitarian purposes, spend more time walking for recreational purposes, take public transit more frequently, drive less often and drive fewer kilometres. Walking frequency for recreational purposes is not significantly different across walkability quartiles in either region, nor is the time spent walking for utilitarian purposes Comparing City & Suburb Current Neighbourhood with Physical Activity/Health Outcomes In order to expand upon the above region-level review, the following tables compare physical activity, travel, and health outcomes across selfdescribed walkability quartile by city and suburb regions in the GTA and GVRD. In Table 56, the F-test summary results are provided, by sub-region, for each of travel behaviour outcome questions. The quartile level mean values for each of the outcomes shown in are provided in Table 57 through Table 66. Also shown are which quartiles, in particular, are significantly different from the reference quartiles (#4, high walkability). As is shown in Table 56, across each of the four sub-regions there are statistically significant quartile differences (to at least the p<0.05 level) for the following outcomes: mean number of days traveled in a car, in a typical week (7 days), or other private motor vehicle (with fewer days traveled in the higher walk quartiles) 69

76 mean amount of vehicle kilometres traveled in a typical week (7 days) (with fewer kilometres traveled in the higher walk quartiles) Table 56: F-test Summary Results for Mean Walk Trips, Vehicle km Travelled, and BMI by Current Neighbourhood Walkability (self-described) Quartile by Sub-Region Note: green highlights indicate findings of significant differences between the mean quartile values. Question E1_1- In a typical week (7 days), how many days do you travel in a car or other private motor vehicle? E16_1 - How many days in a typical week (7 days) do you walk for at least 10 minutes at a time to travel to and from work/school, to do errands, or to go from place to place? Do not include walking done solely for relaxation, recreation and/or exercise. E17_1 - On average how much time do you usually spend on one of those days walking from place to place? E26_1 - How many days in a typical week (7 days) did you walk for at least 10 minutes at a time solely for relaxation, recreation and/or exercise? E27_1 - On average how much time did you usually spend on one of those days walking for solely relaxation, recreation and/or exercise? E6_1 - In a typical week (7 days), how many days do you travel in a bus, train (such as commuter/light rail, streetcar, subway) or other public transit vehicle? How many days in a typical week (7 days) do you walk for at least 10 minutes at a time for utilitarian and/or recreational purposes How many days in a typical week (7 days) do you bicycle for any purpose (E11_1 and E21_1 combined) Body mass index F32_weekly - Weekly distance driven (km) City of Toronto f 3,1129= 27.3, p=0 f 3,1129 =41, p=0 f 3,840 =0.7, p=0.562 f 3,1129 =0.9, p=0.462 f 3,810 =3.6, p=0.013 f 3,1129 =7.5, p=0 f 3,1129 =18.4, p=0 f 3,1129 =1.8, p=0.147 f 3,1014 =0.4, p=0.738 f 3,743 =7.4, p=0 GTA Suburbs f 3,388 =6.1, p=0 f 3,388 =1.8, p=0.148 f 3,172 =0.2, p=0.871 f 3,388 =1.1, p=0.341 f 3,272 =0.8, p=0.493 f 3,388 =1.3, p=0.269 f 3,388 =2, p=0.116 f 3,388 =0.4, p=0.782 f 3,358 =0.7, p=0.575 f 3,291 =2.7, p=0.044 City of Vancouver f 3,508 =7.9, p=0 f 3,508 =25.1, p=0 f 3,389 =1.2, p=0.304 f 3,508 =3.1, p=0.025 f 3,388 =3.4, p=0.019 f 3,508 =0.5, p=0.66 f 3,508 =19.3, p=0 f 3,508 =0.2, p=0.886 f 3,480 =0.3, p=0.827 f 3,329 =3.2, p=0.024 GVRD Suburbs f 3,707 =15.4, p=0 f 3,707 =21.1, p=0 f 3,370 =1.6, p=0.19 f 3,707 =0.1, p=0.942 f 3,545 =5, p=0.002 f 3,707 =6.7, p=0 f 3,707 =7.2, p=0 f 3,707 =1.9, p=0.132 f 3,636 =0.6, p=0.627 f 3,450 =6.3, p=0 The following three outcomes showed statistically significant quartile differences (to at least the p<0.05 level) in each of the sub-regions, except for the GTA suburbs, for the following outcomes: mean number of days in a typical week (7 days) walking was done for at least 10 minutes at a time to travel to and from work/school, to do errands, or to go from place to place, not including walking done solely 70

77 for relaxation, recreation and/or exercise (with more days walked in higher walk quartiles) mean amount of time usually spent per day walking for solely relaxation, recreation and/or exercise (with more time spent in higher walk quartiles) mean number of days in a typical week (7 days) walking was done for at least 10 minutes at a time for utilitarian and/or recreational purposes (with more days walked in higher walk quartiles) No statistical significance across quartiles was detected for the remaining questions, except for the City of Vancouver and the question regarding the number of days in a typical week (7 days) walked for at least 10 minutes at a time solely for relaxation, recreation and/or exercise. Please see Table 56 for additional details. Table 57 through Table 66 provide quartile level mean values for each of the outcomes shown in Table 56. Also shown are the specific quartiles which are significantly different from the reference quartile (#4, high walkability). Table 57: Mean Number of Days Traveled in a Car, in a Typical Week (7 Days), or Other Private Motor Vehicle (Q: E1_1) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver n=1133 n=392 n=512 n=711 GVRD suburbs 1 Low walkability 5 (2.7) ** 6.1 (1.4) 54** 4.3 (3.8) (1.5) 83* 2 Medium-low walkability 3 Medium-high walkability 4 High walkability 2.6 (2.7) (2.5) (2.6) (2.7) 144 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, # (2.7) 154* 6.1 (1.7) 142** 4.3 (2.8) 60** 5.3 (2.2) 205* 3.8 (2.8) 422* 5.6 (2) (2.8) 151** 4.8 (2.4) 279** 46 Format of cells: mean (standard deviation) count of participants (n) 71

78 Table 58: Mean Number of days in a typical week (7 days) walked for at least 10 minutes at a time to travel to and from work/school, to do errands, or to go from place to place (utilitarian) (Q: E16_1) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs n=1133 n=392 n=512 n=711 1 Low walkability 0.5 (1.4) * 1.6 (2.4) (0.6) 3*** 1.2 (2.2) 83* 2 Medium-low walkability 3 Medium-high walkability 4 High walkability 4.2 (2.5) (2.5) (2.5) (2.6) 144 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, # (2.5) 154* 1.4 (2.3) (2.6) 60* 1.5 (2.3) 205* 3 (2.6) 422* 1.9 (2.5) (2.7) 151* 2.1 (2.5) 279* Table 59: - Mean amount of time (minutes) usually spent on one day, of the days which included walking from place to place (utilitarian) (Q; E17_1) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs n=844 n=176 n=393 n=374 1 Low walkability 26.7 (10.4) (14.9) (N.A.) (27.5) 24 2 Medium-low walkability 28 (17.7) (30.3) (20.3) (31.3) 86 3 Medium-high walkability 4 High walkability 32.1 (24.6) (16.4) (23.3) (25.8) 108 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, # (26.8) (30.1) (23) (25.2) Format of cells: mean (standard deviation) count of participants (n) 48 Format of cell: mean (standard deviation) count of participants (n) 72

79 Table 60: Mean number of days in a typical week (7 days) walked for at least 10 minutes at a time solely for relaxation, recreation and/or exercise (Q: E26_1) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs n=1133 n=392 n=512 n=711 1 Low walkability 2.2 (2.5) (2.5) (1.5) (2.6) 83 2 Medium-low walkability 3 (2.6) (2.6) (2.3) 60** 3.2 (2.7) Medium-high walkability 2.8 (2.6) (2.3) (2.6) (2.5) High walkability 2.9 (2.6) (2.6) (2.6) (2.4) 144 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, #4. Table 61: Mean amount of time (minutes) usually spent per day walking for solely relaxation, recreation and/or exercise (Q: E27_1) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs n=814 n=276 n=392 n=549 1 Low walkability 46.7 (31.2) (22.7) (42.4) (35) 63** 2 Medium-low walkability 32.5 (21.5) 111** 37.9 (29.3) (28.1) (22.3) Medium-high walkability 36.9 (28.5) (20) (28.1) 113** 40.1 (27.6) High walkability 41.8 (33) (22.9) (30.3) (23.7) 117 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, #4. 49 Format of cell: mean (standard deviation) count of participants (n) 50 Format of cell: mean (standard deviation) count of participants (n) 73

80 Table 62: Mean number of day in a typical week (7 days) traveled in a bus, train (such as commuter/light rail, streetcar, subway) or other public transit vehicle (Q: E6_1_ Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs n=1133 n=392 n=512 n=711 1 Low walkability 0.8 (2.2) ** 0.5 (1.6) (2.9) (1.7) 83 2 Medium-low walkability 3 Medium-high walkability 2.2 (2.5) (1.8) (2.6) (2.1) High walkability 2.6 (2.5) (2.3) 45 2 (2.4) (2.1) 144 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, # (2.4) 154** 0.5 (1.4) (2.4) (1.5) 205* Table 63: Mean number of days in a typical week (7 days) walking was done for at least 10 minutes at a time for utilitarian and/or recreational purposes (walk for any purpose, combination of Q: E16_1 and E26_1) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs Low walkability Medium-low walkability Medium-high walkability High walkability n=1133 n=392 n=512 n= (2.6) * 3.1 (3) 54 2 (1) 3*** 3.8 (2.8) 83** 4.2 (2.8) 154* 3.5 (2.8) (2.8) 60* 4 (2.8) 205** 4.5 (2.7) 422* 3.9 (2.7) (2.7) 151* 4.4 (2.6) 279** 5.3 (2.3) (2.8) (2.1) (2.4) 144 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, #4. 51 Format of cell: mean (standard deviation) count of participants (n) 52 Format of cell: mean (standard deviation) count of participants (n) 74

81 Table 64: Mean number of days in a typical week (7 days) bicycled for at least 10 minutes at a time for utilitarian and/or recreational purposes (bicycle for any purpose) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs Low walkability Medium-low walkability Medium-high walkability High walkability n=1133 n=392 n=512 n= (0.7) (2.3) 54 1 (1.7) (1.5) (2.4) (2.1) (2.5) (2.1) (2.2) (2.2) (2.5) (2) (2.3) (1.9) (2.3) (1.6) 144 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, #4. Table 65: Mean amount of vehicle kilometres traveled in a typical week (7 days) (Q: F32_weekly) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs Low walkability Medium-low walkability Medium-high walkability High walkability n=747 n=295 n=333 n= (305.4) *** (211.6) (136) (441.3) 60** (186.9) 101** (276.9) 108*** (224.4) (206.1) 133** (227.3) 266** (316.6) (189.3) 95** (232.8) (174.4) (240.8) (137.7) (239.5) 95 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, #4. 53 Format of cell: mean (standard deviation) count of participants (n) 54 Format of cell: mean (standard deviation) count of participants (n) 75

82 Table 66: Mean body mass index (BMI) Walkability quartile (current, self-reported) City of Toronto GTA suburbs City of Vancouver GVRD suburbs n=1018 n=362 n=484 n=640 1 Low walkability 27.2 (6.3) (5.3) (1.9) (5.6) 76 2 Medium-low walkability 26.3 (4.7) (5.5) (4.6) (4.8) Medium-high walkability 26 (5.2) (5.6) (6.1) (4.9) High walkability (5.6) (5.9) (4.9) (6.1) 131 *significantly different (p<0.001) than the reference group, the high walkability quartile, #4. **significantly different (p<0.05) than the reference group, the high walkability quartile, #4. ***significantly different (p<0.1) than the reference group, the high walkability quartile, # Alignment between Neighbourhood Preference and Current Neighbourhood (Choice) One of the main purposes of the residential preference survey is to determine whether a discrepancy exists in the alignment between preference and choice. In other words, do people prefer to live in a that is different (e.g. more or less walkable) from than their current? Quartiles 1 and 2 of the current and preferred factor scores were grouped into a single low walkability category. Similarly quartiles 3 and 4 were grouped into a single high walkability category. Using these combined quartile groups, the following cohorts were created which cross preference with current type: Cohort 1: Prefer high walkability, live in low walkability Cohort 2: Prefer high walkability, live in high walkability (Aligned/satisfied high walkability) Cohort 3: Prefer low walkability, live low walkability (Aligned/ satisfied low walk ability) Cohort 4: Prefer low walkability, live high walkability Cohorts 1 and 3 are people whose preferences do not align with the type of they currently live in. They are considered to be unsatisfied with their current. Participants in cohorts 2 and 4 are considered satisfied with their current, since their preference aligns with the type of they live in. 55 Format of cell: mean (standard deviation) count of participants (n) 56 Difference between city/suburb BMI greatest in 3 rd and 4 th quartiles of walkability 76

83 A scatterplot can be created based on the cohort each participant is in. Figure 14 and Figure 15 show the scatter of satisfied and unsatisfied participants. For graphing purposes participants with a factor score that is +/-0.25 of the numeric split between the second and third quartiles (the range midpoint) are excluded from the scatterplot, hence the empty area bracketing the axis without points. Removing these participants from the graph highlights the break point between the second and third quartiles order and isolates the participant s with more extreme preferences and current type. Figure 14: GTA--Alignment of Preference and Current Neighbourhood 77

84 Figure 15: GVRD--Alignment of Preference and Current Neighbourhood The upper right quadrant of the graphs contains the most participants (71.5 percent of GTA participants and 71.5 percent of GVRD participants). These participants are satisfied with their more walkable (preference aligns with the current type). Participants in the lower left quadrant are also satisfied with the more auto oriented they live in (12.9 percent in the GTA and 16.0 percent in the GVRD). Participants in the other two quadrants do not have alignment between their preferences and the type of they currently live in. In the GTA a similar percentage of participants are found in each of these quadrants (7.9 percent prefer high walk, but live in low walk, and 7.6 percent prefer low walk, but live in high walk). In the GVRD, 6.2 percent prefer high walk, but live in low walk, and 6.3 percent prefer low walk, but live in high walk. 78

85 The tables below provide the participant counts in each of the cohorts shown on the graph above. Table 67: GTA Cross of Low/High Preferred/Current Neighbourhood Walkability GTA Current 57 Preferred 58 Low walk current 59 High walk current Total High walk preferred (7.9%) 902 (71.5%) 1002 Low walk preferred (12.9%) 96 (7.6%) 259 Total Table 68: GVRD Cross of Low/High Preferred/Current Neighbourhood Walkability GVRD Current 64 Current 65 Preferred 66 Low walk current 67 High walk current 68 High walk preferred (6.2%) 635 (71.5%) 690 Low walk preferred (16.0%) 56 (6.3%) Figure 16 maps all GTA participants by preference/current cohort. The red symbols represent mis-matched participants who would prefer a highly walkable, but currently live in an auto-oriented environment. The orange symbols represent mis-matched participants who prefer a more automobile dependent, but who currently live in a pedestrian/transit-oriented environment. The triangular symbols represent matched participants who prefer and live in a high walk environment (dark green), or prefer and live in a low walk environment 57 Values removed that are within 0.25 of split btw 2 nd and 3 rd quartiles 58 Values removed that are within 0.25 of split btw 2 nd and 3 rd quartiles 59 1st and 2nd quartiles of current walkability, 60 3rd and 4th quartiles of current walkability 61 3rd and 4th quartiles of current walkability 62 3rd and 4th quartiles of preferred walkability 63 3rd and 4th quartiles of preferred walkability 64 Values removed that are within 0.25 of split btw 2 nd and 3 rd quartiles 65 Values removed that are within 0.25 of split btw 2 nd and 3 rd quartiles 66 Values removed that are within 0.25 of split btw 2 nd and 3 rd quartiles 67 1st and 2nd quartiles of current walkability, 68 1st and 2nd quartiles of current walkability, 69 3rd and 4th quartiles of preferred walkability 70 3rd and 4th quartiles of preferred walkability 79

86 (light green). Figure 17 shows the same information for GVRD participants. Figure 16: GTA Participant Home Locations by Neighbourhood Preference/Current Neighbourhood Cohort 80

87 Figure 17: GVRD Participant Home Locations by Neighbourhood Preference/Current Neighbourhood Cohort The cross-tabulation between household income and preference/current alignment cohort is shown below in Table 69 for the GTA and Table 70 for the GVRD. In both regions, quadrant 3 (low walk preference, and current low walk) have the highest proportion of participants in the high income category (34.7 percent and 22.9 percent respectively). 81

88 Table 69: Household income frequencies by preference/current cohort - GTA Low income (0-40K) Middle income (40K-100K) High income (>100K) Total Quadrant 1 (upper left): Unmatched: preference=high walk; current=low walk Quadrant 2 (upper right): Matched: Preference=high walk, current=high walk Quadrant 3 (lower left): Matched: Preference=low walk, current=low walk Quadrant 4 (lower right): Unmatched: Preference=low walk, current=high walk 30 (23.4%) 65 (50.8%) 33 (25.8%) 128 (100%) 272 (28.3%) 502 (52.2%) 188 (19.5%) 962 (100%) 32 (13.2%) 126 (52.1%) 84 (34.7%) 242 (100%) 45 (23.3%) 110 (57.0%) 38 (19.7%) 193 (100%) Table 70: Average household income by preference/current cohort - GVRD GVRD Quadrant 1 (upper left): Unmatched: preference=high walk; current=low walk Quadrant 2 (upper right): Matched: Preference=high walk, current=high walk Quadrant 3 (lower left): Matched: Preference=low walk, current=low walk Quadrant 4 (lower right): Unmatched: Preference=low walk, current=high walk Low income (0-40K) Middle income (40K-100K) High income (>100K) Total 33 (24.8%) 76 (57.1%) 24 (18.0%) 133 (100%) 249 (33.0%) 380 (50.3%) 126 (16.7%) 755 (100%) 45 (20.6%) 123 (56.4%) 50 (22.9%) 218 (100%) 31 (26.5%) 72 (61.5%) 14 (12.0%) 117 (100%) 82

89 5.4 Preference/current & physical activity/travel outcomes This section explores the impact of the built environment on several health outcomes using the satisfaction cohort groupings based on preference crossed with current. This allows for the examination of how the different cohorts of preference/current associate with physical activity and other travel behaviour variables. For example, how does physical activity vary between someone who strongly prefers a that is auto-dependent, but lives in a that is very pedestrian/transit-oriented, compared to someone who shares the same preference (an auto-dependent ), but actually lives in a matching their preference? If preference was the only factor, it would be expected that both participants would exhibit similar behaviours. It is also possible to see how physical activity varies between participants who live in the same, but have contrasting preferences. For example, of those people living in high walk environments, do those who actually prefer to do so have different behaviours than those who would rather be in an auto-oriented environment? The tables presented below include the same set of outcome variables as were previously presented in Table 54 and Table 55. The previous tables looked at significant differences across quartiles of current walkability. The tables below bring in preference and use the quadrants of satisfaction presented in the previous section to explore significant differences in the mean values of outcomes across the cohorts or quadrants shown in the graphs above. The following tables use a single or double asterisk to indicate whether a value is significantly different from the value in its reference quadrant. Comparisons are made in two ways: quadrants with the same preference are compared across the two current types, and quadrants with the same current type are compared across the two different preferred types 83

90 Table 71: GTA ANOVA analyses between preference/selection cohorts Note: standard deviations are in parentheses Walkability quadrant) Freq. Walking for utilitarian purposes (days/wk) Time spent Walking for utilitarian purposes (daily avg minutes) Freq. Walking for recreational purposes (days/wk) Time spent Walking for recreational purposes (daily avg minutes) Freq. Walking for any purpose (days/wk) Freq. Bicycling for any purpose (days/wk) Freq. Travel on public transit (days/wk) Freq. Vehicle travel (days/wk) Time spent - Vehicle travel (minutes/typical day per typical wk) Weekly VKT 71 BMI 1 Quadrant 1 (upper left): Unmatched: preference = high walk; current = low walk 2 Quadrant 2 (upper right): Matched: Preference = high walk, current = high walk 3 Quadrant 3 (lower left): Matched: Preference = low walk, current = low walk 4 Quadrant 4 (lower right): Unmatched: Preference = low walk, current = high walk (n=1525) (n=1020) (n=1525) (n=1090) (n=1525) (n=1525) (n=1525) (n=1525) (n=1169) (n=1042) (n=1380) 2.1 (2.4)* 27.1 (24.8) 3.1 (2.6) 37.3 (29.9) 4.2 (2.7)*, ** 1.6 (2.5) 1.3 (2.2) * 4.8 (2.7)*,** 55.1 (47) (212.7) * 26.6 (5.5) 3.7 (2.6)** 31.8 (25.1) 2.9 (2.5) 39.8 (31) 5 (2.5)) ** 1.3 (2.3) 2.3 (2.5)** 3.3 (2.8)** 47.5 (39.2) (231.3)** 26.1 (5.4) 1.5 (2.4) 30.4 (19.9) 2.6 (2.5) 35 (22.6) 3.4 (2.9) 1.1 (2.1) 0.9 (2) 5.7 (2.1)* 50.5 (41.3) 347 (256.8)* 27.1 (5) 2.1 (2.5) 31.4 (29.3) 2.7 (2.6) 34.3 (20.9) 3.9 (2.8) 1 (2) 1.1 (2) 4.8 (2.5) 46.7 (33.1) (195.3) 27 (5.8) *significantly different (p<0.05) than the reference group, (for quadrant 1 the reference is quadrant 2, for quadrant 3 the reference is quadrant 4). Comparison groups share the same preference and are different on the current. **significantly different (p<0.05) than the reference group, (for quadrant 1 the reference is quadrant 3, for quadrant 2 the reference is quadrant 4). Comparison groups share the current and are different on the preference. 71 Based on self-reported yearly distance driven divided by

91 For the set of participants in the GTA (Table 71) it was found that: Of those that share the same preference: Participants in quadrant 1 and 2 both prefer high walk but they live in low and high walk respectively. Despite sharing the same preference, the person living in the more walkable area on average walks significantly more days per week than the person in the lower walk area (Utilitarian: 3.7 versus 2.1 days per week. All purposes: 5.0 versus 4.2 days per week). Despite sharing the same preference for high walk (quadrants 1 and 2) the person living in the less walkable area on average makes a vehicle trip significantly more days per week than the person in the higher walk area (4.8 versus 3.3 days per week, quadrant 1 and 2 respectively). They also travel significantly more distance by a vehicle than a person with the same preference but living in high walk (274.6 kilometres per week versus kilometres, quadrant 1 versus 2) Not surprisingly, people in low walk use transit significantly fewer days than those in high walk, even though they share a preference for high walk (2.3 versus 1.3 days per week, quadrant 2 and 1 respectively). Unlike walking using transit requires the routes, stops, stations and vehicles to be provided, making it more dependent on urban form Among participants with a preference for auto-oriented s (quadrants 3 and 4), vehicle travel frequency and weekly VKT is significantly higher for those who actually live in that type of, compared to those who live in a walkable environment (5.7 versus 4.8 days per week and km versus km) Of those that share the same built environment: People living in low walk areas with a preference for high walk s, on average, make fewer vehicle trips than their counterparts who also live in low walk areas but prefer this type of (4.8 versus 5.7 days per week, quadrant 1 and quadrant 3). They also walk significantly more for any purpose (4.2 versus 3.4 days per week) For participants living in pedestrian/transit-oriented s (quadrants 2 and 4), those who actually prefer to do so walk significant more for utilitarian purposes (3.7 versus 2.1 days per week) and any purpose (5.0 versus 3.9 days per week). They also use public transit more frequently (2.3 versus 1.1 days per week) and travel in an automobile less frequently (3.3 versus 4.8 days per week) and drive shorter distances (190.5 km versus km) 85

92 Table 72: GVRD ANOVA analyses between preference/selection cohorts Note: Cells contain mean values with standard deviations in parentheses Walkability quadrant Freq. Walking for utilitarian purposes (days/wk) Time spent Walking for utilitarian purposes (daily avg minutes) Freq. Walking for recreational purposes (days/wk) Time spent Walking for recreational purposes (daily avg minutes) Freq. Walking for any purpose (days/wk) Freq. Bicycling for any purpose (days/wk) Freq. Travel on public transit (days/wk) Freq. Vehicle travel (days/wk) Time spent - Vehicle travel (minutes/ty pical day per typical wk) Weekly VKT 72 BMI 1 Quadrant 1 (upper left): Unmatched: preference = high walk; current = low walk 2 Quadrant 2 (upper right): Matched: Preference = high walk, current = high walk 3 Quadrant 3 (lower left): Matched: Preference = low walk, current = low walk 4 Quadrant 4 (lower right): Unmatched: Preference = low walk, current = high walk (n=1223) (n=767) (n=1223) (n=941) (n=1223) (n=1223) (n=1223) (n=1223) (n=1002) (n=787) (n=1124) 1.8 (2.5)* 31.4 (19.7) 3 (2.6) 39.6 (23.4) 4 (2.8)*,** 0.9 (1.9) 1.1 (2) * 4.7 (2.4) *,** 46 (37.3) (258.6) * 3.6 (2.7)** 32.3 (24.2) 3.3 (2.5) 40.3 (29.1) 5.2 (2.4) ** 1.2 (2.1) 1.8 (2.4)** 3.6 (2.7) ** 40.4 (28.8) (198.9)** 1.3 (2.2) 37.5 (34) 3 (2.6) 41.7 (30) 3.8 (2.7) 1.2 (2.2) 0.6 (1.6) 5.7 (2)* 51.2 (39.2) (311.5)** 1.4 (2.1) 30.1 (23.8) 2.4 (2.4) 35.1 (19.8) 3.3 (2.6) 1.1 (2.1) 0.8 (1.8) 5.1 (2.3) 50.4 (37) (210.6) *significantly different (p<0.05) than the reference group, (for quadrant 1 the reference is quadrant 2, for quadrant 3 the reference is quadrant 4). Comparison groups share the same preference and are different on the current. **significantly different (p<0.05) than the reference group, (for quadrant 1 the reference is quadrant 3, for quadrant 2 the reference is quadrant 4). Comparison groups share the current and are different on the preference (5) 25.8 (5.6)) ** 26.4 (4.9) 26.1 (4.6) 72 Based on self-reported yearly distance driven divided by

93 For the set of participants in the GVRD (Table 72) it was found that: Of those that share the same preference: When comparing those who both prefer a high walk environment, the person who actually lives in a more walkable area (quadrant 2) on average walks significantly more days per week than the person in the lower walk area (quadrant 1) (Utilitarian: 3.6 versus 1.8 days per week. All purposes: 5.2 versus 4.0 days per week). A person living in and preferring high walk (quadrant 2), on average, makes vehicles trips on significantly fewer days per week (3.6) than those sharing the same preference but living in low walk (4.7, quadrant 1), as well as compared to people sharing the same current type of but preferring low walk (5.1, quadrant 4). People in low walk areas with a preference for high walk, on average, travel significantly more distance by a vehicle than a person with the same preference but living in high walk (289.7 km per week versus km, quadrant 1 and quadrant 2) Of those that share the same built environment: For participants living in low walk s (quadrants 1 and 3), those who would prefer a pedestrian/transit-oriented environment walk significantly more for all purposes (4.0 versus 3.8 days per week) and make significantly fewer vehicle trips (4.7 versus 5.8 days per week) Among those living in high walk areas (quadrants 2 and 4), those that actually prefer to do so walk significantly more for utilitarian purposes (3.6 versus 1.4 days per week) and all purposes (5.2 versus 3.3 days per week), take public transit more frequently (1.8 versus 0.8 days per week), and have a lower BMI (25.8 versus 26.1). On average, they also drive less often (3.6 versus 5.1 days per week and travel less distance in a vehicle (169.9 km versus km). In both regions there is not a significant difference between the quadrants for time spent walking for utilitarian or recreational purposes, frequency of recreational walking frequency of bicycling for any purpose, or time spent in vehicle traveling. 87

94 5.5 City of Toronto -- physical activity/travel outcomes & objective walkability data This section makes use of the objective, postal code-level built environment measures assigned to City of Toronto participants as described in Section The objective walkability quartiles are used in the ANOVA analysis below for City of Toronto participants to explore the differences in various outcomes across the four walkability quartiles. The mean values for each outcome across the quartiles are compared to the low-walk values. The following outcomes are significantly higher, when compared to low walkability quartile values, for participants living in the medium low, medium high, and high quartiles: 73 number of days/week walked for utilitarian purposes (F3,1125 = 44.6, p<0.001) number of days/week walked for any purpose (F3,1125 = 21.0, p<0.001) number of days/week traveled on public transit(f3,1125 = 10.9, p<0.001) The following outcomes are significantly lower, when compared to low walkability quartile values, for participants living in the medium low, medium high, and high quartiles: 74 number of days/week traveled by motor vehicle travel (F3,1125 = 38.7, p<0.001) vehicle kilometres of travel (VKT) per week (F3,741 = 15.9, p<0.001) 73 The high walkabilty quartile (#4) has a low number of participants (n=23). Despite this smaller than desirable number, the results are provided. 74 The high walkabilty quartile (#4) has a low number of participants (n=23). Despite this smaller than desirable number, the results are provided. 88

95 Table 73: ANOVA based on objective current (City of Toronto participants only) Notes: Cells contain mean values with standard deviations in parentheses. Reference case is walkability quartile #1 (low walkability). Quartile #4 was not used, unlike in the previous similar tables, due to the low participant count in this quartile. Walkability quartile (current ) Freq. Walking for utilitarian purposes (days/wk) Time spent Walking for utilitarian purposes (daily avg minutes) Freq. Walking for recreational purposes (days/wk) Time spent Walking for recreational purposes (daily avg minutes) Freq. Walking for any purpose (days/wk) Freq. Bicycling for any purpose (days/wk) Freq. Travel on public transit (days/wk) Freq. Vehicle travel (days/wk) Time spent - Vehicle travel (days/wk) (n=1,129) (n=841) (n=1,129) (n=811) (n=1,129) (n=1,129) (n=1,129) (n=1,129) (n=792) (n=745) (n=1,017) Quartile 1: Low walkability 2.0 (2.4) 30.9 (28.0) 2.8 (2.7) 33.1 (19.7) 3.8 (2.8) 1.2 (2.2) 1.4 (2.2) 4.6 (2.6) 52.7 (50.3) (249.2) 26.8 (5.0) Quartile 2: Medium-low walkability 3.4 (2.6)** 30.4 (21.2) 2.8 (2.5) 40.0 (31.1) 4.8 (2.6)** 1.3 (2.3) 2.4 (2.5)** 3.5 (2.8)** 46.7 (34.1) (189.5)** 25.9 (5.3) Quartile 3: Medium-high walkability 4.8 (2.4)** 34.0 (27.7) 2.9 (2.7) 39.7 (33.6) 5.7 (2.1)** 1.3 (2.3) 2.4 (2.4)** 1.9 (2.4)** 46.0 (42.4) (166.1)** 25.7 (5.6) Quartile 4: High walkability 5.4 (1.7)** 44.6 (50.6) 4.0 (2.7) 45.5 (34.2) 6.3 (1.1)** 1.2 (2.4) 3.5 (2.3)** 1.1 (2.1)** 62.1 (81.0) 45.0 (89.8)** 25.7 (5.9) *significantly different (p<0.05) than the reference group (quartile 1) **significantly different (p<0.1) than the reference group, (quartile 1) Note: quartile 4 results are highlighted in yellow to indicate the number of participants in this group is very low (n=23), and that is a smaller than desired set for statistical analysis. Despite this the results are provided, but should be reviewed in light of them being based on a small number of participants. Weekly VKT BMI 89

96 Table 74 provides mean age and income values by quartiles and indicates they are not significantly different across the quartiles of walkability, when compared to quartile 1 (low walkability). Table 74: Mean Age & Income across quartiles of objective current (City of Toronto participants only) Note: Cells contain mean values with standard deviations in parentheses. Walkability quartile (current ) Age 75 Income 76 Quartile 1: Low walkability 51.9 (12.7) 4.6 (1.8) Quartile 2: Medium-low walkability 49.8 (13.8) 4.7 (2.0) Quartile 3: Medium-high walkability 48.6 (13.9) 4.5 (2.0) Quartile 4: High walkability 47.4 (14.1) 4.5 (1.9) *significantly different (p<0.05) than the reference group (quartile 1) Note: quartile 4 results are highlighted in yellow to indicate the number of participants in this group is very low (n=23), and that is a smaller than desired set for statistical analysis. Despite this the results are provided but should be reviewed in light of the small number of participants. 75 (F 3,1125 = 2.3, p=0.078) 76 (F 3,1101 = 0.7, p=0.561). Categorized values: 1=Less than $10,000, 2=$10,000 to less than $20,000, 3=$20,000 to less than $40,000, 4=$40,000 to less than $60,000, 5=$60,000 to less than $80,000, 6=$80,000 to less than $100,000, 7=$100,000 to less than $120,000, 8=$120,000 or more 90

97 6.0 SUMMARY OF FINDINGS Strong preference for pedestrian/transit-oriented s is evident in the GTA and GVRD Overall, residential satisfaction is quite high based on trade-off questions which compare specific participant-assessed features. The percentage of people who would move to a that is similar to their current ranged from 62 to 72 percent for GTA and GVRD participants. Across trade-off questions #2 through #8, the percentage of people who prefer a very walkable ranged from 38.7 to 52.9 percent in both regions. The percentage of people who prefer a with both characteristics ranged from 34.7 to 47.5 percent. Between 10.2 and 22.2 percent prefer an auto-oriented. In the GTA, preference for a very walkable was strongest for trade-off #2 walkability and proximity to commercial services (52.9 percent). The second highest preference for a walkable was for trade-off #8 access to and size of food outlets (47.5 percent). In the GVRD, preference for a very walkable was highest for trade-off #8 access to and size of food outlets (49.1 percent), and second highest for trade-off #2 walkability and proximity to commercial services (48.9 percent). In both regions, the strongest preference for an auto-oriented was in Trade-off #3 level of activity and mix of housing -- where there are single family houses on larger lots, even if it means there is not an area with services or activities nearby (22.2 percent and 22.0 percent in GTA and GVRD respectively). Respondents desire to move to a more walkable compared to their current self-described ranged from percent across all trade-offs; the highest percentage of people that would like to move to a more walkable was found in trade-off #2 walkability and proximity of commercial services with 30.0 percent in GTA and 27.7 percent in GVRD wanting to move to a closer to commercial services. Neighbourhood preference and self-described vary considerably between city and suburban participants Whether a participants lives in the city or suburbs has a notable effect on preferences in both the GTA and GVRD. Although participants in the city and suburbs both prefer a pedestrian/transitoriented, the magnitude of such a preference was substantially greater among city participants in both regions an average of 26.2% higher for City of Toronto participants and 22.1% for City of Vancouver participants, compared to their suburban counterparts. 91

98 More city participants indicate that their current is very walkable than suburb participants an average of about 30% higher in the GTA and GVRD. In the both regions, Trade-off #6: Street design and travel options" had the highest percentage of responses for a pedestrian/transit-oriented type for city and suburb participants. Trade-off #8: Access to and size of food outlets had the greatest percentage of responses indicating they live in a highly autooriented in the GTA city and suburbs. Among City of Vancouver participants, the highest percentage for a very auto-oriented environment was "Trade-off #2: Walkability and proximity of commercial services, while among GVRD suburbs it was Trade-off #3: Level of activity and mix of housing. Survey results seem to indicate that latent demand for more walkable environments exists in both study regions When considering the subset of participants who self-describe their current as very auto-oriented: Trade-off #8 access to and size of food outlets -- had the greatest percentage of people desiring to move to a more walkable compared to their current : 18 percent in GTA and 25.6 percent in GVRD. Trade-off question #4 home size and travel options -- had the second largest discrepancy in the GTA, where 15.4 percent of people living in more auto-oriented s wanted to move to a more centrally located, walkable. In the GVRD, the second largest discrepancy was found for trade-off #2 walkability and proximity to commercial services, where 23 percent of people currently living in more auto-oriented s desired to change to a more walkable that is closer to commercial services. Demand also exists for more pedestrian-friendly environments when walkability is measured objectively Latent demand for more walkable s was also found among City of Toronto participants using an objective walkability index. Among participants living in the low and medium-low quartiles of objective walkability, demand for more walkable aspects of the built environment was present for between 20.5 percent to 31.8 percent of participants across the seven individual trade-offs. Desire to be in walking distance from commercial services had the largest percentage of participants desiring change from their current (31.8 percent), followed by better street connectivity and travel options (25.3 percent). Current affects physical activity and travel behavior ANOVA analyses shows that, in both regions, there is a significant difference in physical activity and travel behaviour based on the type of a participant describes they live in. 92

99 Participants who describe their s as highly walkable walk significantly more for utilitarian purposes, spend more time walking for recreational purposes, take public transit more frequently, drive less often and drive fewer kilometres. Walking frequency for recreational purposes is not significantly different across walkability quartiles in either region, nor is the time spent walking for utilitarian purposes. Neighbourhood satisfaction (self-reported ) is similar in both study regions When comparing participant reported composite assessments (across all trade-offs) of the self-reported current and preferred type: Over 12 percent of participants indicate a misalignment between their preference and the type they live in. o In the GTA 7.9 percent and in the GVRD 6.2 percent of participants report living in a low walkable (more automobile oriented), but would prefer living in a more walkable one. o In the GTA 7.6 percent and in the GVRD 6.3 percent of participants report living in a high walkable, but would prefer living in a more auto oriented one. Over 84 percent of participants show an alignment of the preference and the type they live in. o 72 percent of GTA and GVRD participants report living in and preferring a more walkable. o While it is a smaller set of participants, 12.9 percent in the GTA and 16.0 percent in the GVRD report living in and preferring a more automobile oriented. While a large majority of participants report satisfaction with where they live, 7.9 percent of participants in the GTA and 6.2 percent in the GVRD, indicate they would like to live in a more walkable. Facilitating their ability to move to such a could have positive public health and environmental impacts on a variety of physical activity and travel behaviour activities. Behaviour varies across preference/current cohorts Despite preferring same type of, people who live in a more walkable are more active. Among those who share a high walk preference, people living in the: more walkable areas, on average, walk significantly more days per week than the person in the lower walk area. more walkable areas, on average, take public transit significant more days per week than the person in the lower walk area less walkable areas, on average, make a vehicle trip significantly more days per week than the person in the higher walk area. 93

100 less walkable areas, on average, travel significantly more distance by a vehicle than a person with the same preference but living in high walk area. Despite living in the same type of, people who prefer a more walkable are more active than those who prefer an auto-oriented environment. Among those who live in an auto-oriented environment, people preferring: more walkable areas, on average, walk significantly more days per week than the person in the lower walk area. less walkable areas, on average, make a vehicle trip significantly more days per week than the person in the higher walk area. Behaviour varies across objectively measured walkability City of Toronto participants have significant variation in behaviour was across objectively measured quartiles of utilitarian-focused walkability. Participants living in the medium-low, medium-high, and high quartiles have significantly higher values, when compared to low walkability quartile values, for the following outcomes: number of days/week walked for utilitarian purposes number of days/week walked for any purpose number of days/week traveled on public transit In addition the following outcomes are significantly lower, when compared to low walkability quartile values, for participants living in the medium low, medium high, and high quartiles: 77 number of days/week traveled by motor vehicle travel vehicle kilometres of travel (VKT) per week The results provided here describe GTA and GVRD survey participants self-reported satisfaction with their s, highlight attributes of high importance and describe how physical activity and transport behaviour various by levels of self-reported, and in the case of the City of Toronto objectively measured levels of walkability. Overall the results provided by the CLASP residential preference survey provide important insights into the attitudes of the GTA and GVRD survey participants regarding different types of residential community environments, as well as their travel and physical activity behaviours. These results can be used in the policy and planning processes which affect design and housing options. 77 The high walkabilty quartile (#4) has a low number of participants (n=23). Despite this smaller than desirable number, the results are provided. 94

101 APPENDIX A ONLINE SURVEYING Note: the text below was supplied by Michael Howell, Senior Research Manager, Ipsos Reid Public Affairs. Tel: , michael.howell@ipsos.com Rationale for online vs. telephone quantitative surveying Over the years Ipsos Reid has built one of the largest pre-recruited panels in Canada, with over 240,000 pre-recruited panelists nationwide, over 90,000 panelists in Ontario and over 28,000 in the GTA. This enables us the option to conduct an array of different studies online, as opposed to through traditional telephone interviewing, from broad representative studies to very specified targeted recruits. Depending on the research objectives of an individual project, an online methodology may be an appropriate and successful way to approach the project. Both online and telephone methodologies can be used to achieve a representative sample of residents. The main difference between the two methods is cost. The cost to conduct a survey online using panel sample is significantly lower because you are not paying for interviewers to make the calls. In cases where you want to interview a low-incidence segment of the population, telephone can be especially costly because only a small percentage of participants initially contacted will qualify. In addition to significant cost-savings, online surveying offers many benefits: The first is that there is an easier ability to screen potential participants for your project s particular criteria (e.g. by age, gender, income, family composition, region within the City, employment status, etc.) based on the profiles that our online panelists complete ahead of time. As with telephone methodology, quotas are employed to ensure the mix of respondents we obtain reflects or represents the desired audience makeup, but more efficiently instead of initiating a call, pre-screening and then ending calls that are dead leads, the online invitation only goes to panelists that meet the desired criteria. In the case of City residents specifically, education, household income, dwelling type, and employment status distribution figures are also available that we can use to set quotas as necessary. In addition, the Ipsos online panel has many other characteristics of its panelists predetermined allowing for targeted studies to be executed in a relatively short timeframe. For standard representative studies these include: Gender Age Region Household size 95

102 For non-representative survey samples (such as pre-defined target audiences) the Ipsos panel provides substantial sampling options for a number of audiences, including but not limited to: Homeowners Rate payers (such as municipal taxes, waste collection fees, etc.) Internet use and time spent online Ailments (such as asthma suffers, allergies, etc) Small business owners and other occupations Family status (such as parents, kids living at home, etc) Use of services (such as financial products, telecommunications, etc) Media consumption habits (such as newspaper readership, etc) Many other demographic and target audience groups Since with online research we often begin with targeted sample, studies can often be executed in a much shorter timeframe than a comparable telephone survey. Both require standard upfront programming, but once in-field since an online survey is directed to people with profiles which match our sampling criteria and we find that by doing so we often can complete surveys much faster. Online surveys also allow respondents to complete the survey at their own leisure and if necessary stop a given survey and return at a later point in time to continue where they left off. Online methodology also offers the benefit of visual presentation to the respondent. For City of Toronto projects, this could be especially useful in testing creative/advertising or potential concepts (almost impossible to do in telephone methodology) while still offering more statistical reliability than in-person focus groups. If you envision the possibility of creative testing over the course of your project or program, it would be extremely useful to have benchmarked attitudes using an online method in prior research so that you are consistent (apples to apples). In regards to technical capacity, our online capabilities employ the latest technologies and techniques available, including Flash, video (MPG, AVI, etc), audio (MP3, WAV, etc.), and complex visual exercises (i.e. sorting exercises) to offer the flexibility our studies may require. From a technical standpoint, the main difference between the two methods is that typically a telephone methodology is based on random probability sampling, meaning in theory, all residents have an equal chance of being contacted for the survey because they are phoned randomly, whereas in the online method we invite respondents from our panel to participate. These individuals have previously opted to join the panel to participate in surveys (of all kinds) and thus are not randomly selected. In some circumstances or for certain research objectives, a telephone survey may be more appropriate. Lastly, the online method offers a distinct benefit over telephone when the project objectives include targeting the 18 to 34 age group. Typically telephone surveys employ RDD (random digit dialing) to contact individuals, however, reaching a large sample of 18 to 34 year olds 96

103 usually requires us to supplement RDD sample with lists that target households with individuals in this age range. Experience has taught us that this group is very difficult to reach in this day and age via telephone and thus it is often too costly for clients to use only RDD to reach the number of these individuals required for the quotas. In regards to telephone surveys, our data collection toolbox includes state-of-the-art telephone call centers, consistently high interview rates per hour, and thoroughly trained Interviewers. With more than 1,100 state-of-the-art computer-assisted telephone interviewing (CATI) stations and approximately 1,600 rigorously trained and monitored interviewers across the country, Ipsos Reid boasts unparalleled operational capacity. 97

104 APPENDIX B CLASP RESIDENTIAL PREFERENCE SURVEY (MS Word format, which served as the basis for creating a web-based version) CLASP NEIGHBOURHOOD PERCEPTION, PREFERENCE AND ACTIVITY SURVEY [SURVEY INTRODUCTION] Thank you for agreeing to participate in our study. We need your help to make this study a success. Your candid answers to the items in the survey are important. The survey will take approximately 28 minutes to complete. Please remember: Write down what YOU think, There are NO right or wrong answers, All information you provide will be kept strictly CONFIDENTIAL [SCREENER QUESTIONS] S1. [INSERT STANDARD IIS AGE QUESTION]. [TERINATE IF UNDER 25 YEARS OLD] S2. [INSERT STANDARD IIS GENDER QUESTION]. 98

105 [SECTION A: YOUR CURRENT RESIDENCE] A1. Please share with us some general information about your current home. Firstly, what type of housing do you live in? Detached house Semi-detached house Row/townhouses Duplex/triplex/quadplex Apartment/condo (1 to 4 stories) Apartment/condo (5 or more stories) Other, specify ( ) [IF ANY OF CODES 3-7 SELECTED SKIP TO QUESTION A3. IF CODE 1-2 SELECTED CONTINUE TO QUESTION A2] A3. Please indicate whether you own or rent your current home. Own Rent Other (please specify ) A4. How long have you lived at your current address? [YEARS TEXT BOX IS MANDATORY, BUT MONTHS TEXT BOX IS OPTIONAL] [NUMERIC TEXT BOX, RANGE 0-99] years and [NUMERIC TEXT BOX, RANGE 0-11] months. [DISPLAY A5a-c ON THE SAME SCREEN] A5a. Thinking of parking at the closest store to your residence. Which of the following best describes availability of parking at your closest store? (Select one). Limited (for example you often need to drive around to find a spot) Ample (for example you can always park immediately) A5b. And is parking (Select one) On street Off street Both on street and off street A5c. And thinking of the cost of parking at this store closest to where you live. Is there a cost per hour, or is it free to park? 99

106 Free Pay per hour. Cost =$[INSERT NUMERIC TEXT BOX 0-49] per hour Don t know A6. How many minutes does it typically take you to drive from your home to each of the following [NOT APPLICABLE ONLY AVAILABLE AS AN OPTION FOR ITEMS 1-2. COLUMNS ARE MUTUALLY EXCLUSIVE] Minutes Not applicable [NUMERIC TEXT / Don t Know BOX, RANGE 0-199] Your work location Your school location Nearest regional shopping centre Nearest park, recreational amenity, parkette, or green space Nearest store, shop, or service Nearest public bus stop Nearest public train (such as commuter/light rail, streetcar, subway) station/stop 100

107 A7. From the stop/station nearest your home, how long a trip on public bus /or train (such as commuter/light rail, streetcar, subway) is it to each of the following: [NOT APPLICABLE ONLY AVAILABLE AS AN OPTION FOR ITEMS 1-2. COLUMNS ARE MUTUALLY EXCLUSIVE] Work School Nearest regional shopping centre Nearest park, recreational amenity, parkette, or green space Nearest store, shop, or service Minutes [NUMERIC TEXT BOX, RANGE 0-199] Not applicable / Don t Know A8. Please indicate all the types of housing that exist in your (within a 10 minute walk from where you live). (Select all that apply) Detached house Semi-detached house Row/townhouses Duplex/triplex/quadplex Apartment/condo (1 to 4 stories) Apartment/condo (5 or more stories) Other, specify ( ) A10. Are cul-de-sacs or dead-end streets common in your (within a 10 minute walk from your home)? Yes No A9. Do you live on a cul-de-sac or a dead-end street? Yes No A11. Please rate your overall satisfaction with your current using the scale provided below. 101

108 HORIZONTAL SCALE LABEL TAILS ARE 0= Dislike very much, 10= Like very much ] [SECTION B: REASONS FOR MOVING TO YOUR CURRENT NEIGHBOURHOOD] B1. Please rate how important each of the following reasons was in your decision to move to your current. For each reason, please select a number between 1 and 4, where 1= not at all important and 4 = very important. [COLUMNS. HORIZONTAL SCALE 1-4. LABEL TAILS ARE 1= Not at all important, 4= Very Important ] [ROWS RANDOMIZE] Affordability/Value The amount of interior space in your home The size of your yard The noise from traffic Closeness to public open space (e.g. public parks, green space) Closeness to job or school Closeness to a bus stop Closeness to a train (such as commuter/light rail, streetcar, subway) station or stop Convenient access to work and other destinations on public transit Closeness to a wide range of small to medium sized grocery stores, fruit and vegetable stands, and/or specialty food stores. Closeness to restaurants Closeness to shops and services (such as a post office, bank, pharmacy, and/or dry cleaner) Ease of walking Ease of bicycling [HALF WAY DOWN ITEM LIST REPEAT SCALE WITH LABEL TAILS] Quality of schools Closeness to public recreation space for swimming, walking, jogging, running trails, social interaction, sports and playgrounds Highway/freeway access from your home Closeness to cultural/ entertainment venues (theatre, art gallery, museum, music, cinemas, clubs, etc.) Closeness to elementary school or child care or early learning centre Closeness to friends and family Closeness to particular cultural/ethnic community 102

109 [SECTION C: NEIGHBOURHOOD PREFERENCES] [INSERT TEXT] First, we d like you to imagine moving to a new. Please read the descriptions below and then answer the four questions that follow. For anything we do not refer to in the description below, such as school quality, public safety, or housing costs, please assume that it is exactly the same as where you live now. To begin, please carefully read the descriptions of the s below. [TRADEOFF1 TABLE] Neighbourhood A Within 1 kilometre or ½ mile of my home (a 10 minute walk) there is a mix of single family detached houses on smaller lots, town homes, semi-detached houses/duplexes, and mid-rise apartments and condominiums. Destinations such as shopping, a restaurant, a public library and a school are within a few blocks of my home. Local destinations are close enough that I can either walk or drive there. Parking there is limited. My one-way commute to work or school is 5 kilometres / 3 miles or less (a 10 minute drive; a 15 minute bicycle or transit trip). Bus and/or train (such as commuter/light rail, streetcar, subway) stops are close enough that I can either walk or drive there. Neighbourhood B Within 1 kilometre or ½ mile of my home (a 10 minute walk) there are only single-family houses on large lots. Destinations such as shopping, a restaurant, a public library and a school are within a few kilometres of my home. Destinations are far enough it is necessary to drive to there. Parking there is abundant. My one-way commute to work or school is 20 kilometres / 12 miles or more (a 30 minute drive; a 60 minute bicycle ride; a 50 minute transit trip). Bus and/or train (such as commuter/light rail, streetcar, subway) stops are far enough it is necessary to drive to there. [NEXT SCREEN] [FOR QUESTIONS 1a-e ALWAYS MAINTAIN TRADEOFF1 TABLE AT THE TOP OF THE SCREEN SO THAT RESPONDENTS CAN REFER TO IT] 1a. Assuming that there are no differences between the s apart from the ones we mentioned, which do you think you d rather live in? Neighbourhood A Neighbourhood B 1b. How do you think you d feel about living in Neighbourhood A? [HORIZONTAL SCALE LABEL TAILS ARE 0= Dislike very much, 10= Like very much ] 1c. How do you think you d feel about living in Neighbourhood B? 103

110 [HORIZONTAL SCALE LABEL TAILS ARE 0= Dislike very much, 10= Like very much ] 1d. Your current is (Select one) [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 1e. If you were to move, the you d hope to find would be. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ][INSERT PARAGRAPH OF TEXT] Now we d like you to imagine moving to a different. The next set of questions asks you about the kind of you d hope to find. Please look at the following images and read their descriptions, then select the appropriate number on the scale to indicate your answer. Keep in mind that anything that we do not refer to in a question such as school quality, public safety or house cost is exactly the same as where you live now. [AFTER PARAGRAPH SHOWN, CLICK TO MOVE TO NEXT SCREEN] 104

111 [TRADEOFF2] [SHOW QUESTIONS 2a-c ON THE SAME SCREEN] 2a. Your preference is: [HORIZONTAL SCALE LABEL TAILS ARE 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B ] 2b. Please indicate whether your current is more like A or B. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 2c. Regarding the ability to walk to nearby shops and services, the you d hope to find would be: [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ] 105

112 [SHOW QUESTIONS 3a-c ON THE SAME SCREEN] 3a. Your preference is: [HORIZONTAL SCALE LABEL TAILS ARE 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B ] 3b. Please indicate whether your current is more like A or B. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 3c. Regarding the level of activity and mix of housing, the you d hope to find would be: [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ] [TRADEOFF4 IS ASKED AFTER TRADEOFF8] 106

113 [SHOW QUESTIONS 5a-c ON THE SAME SCREEN] 5a. Your preference is: [HORIZONTAL SCALE LABEL TAILS ARE 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B ] 5b. Please indicate whether your current is more like A or B. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 5c. Regarding lot size and commute distance, the you d hope to find would be: [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ] 107

114 [SHOW QUESTIONS 6a-c ON THE SAME SCREEN] 6a. Your preference is: [HORIZONTAL SCALE LABEL TAILS ARE 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B ] 6b. Please indicate whether your current is more like A or B. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 6c. Regarding street types and travel options, the you d hope to find would be: [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ] 108

115 [SHOW QUESTIONS 7a-c ON THE SAME SCREEN] 7a. Your preference is: [HORIZONTAL SCALE LABEL TAILS ARE 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B ] 7b. Please indicate whether your current is more like A or B. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 7c. Regarding public recreation opportunities and lot size, the you d hope to find would be: [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ] 109

116 [SHOW QUESTIONS 8a-c ON THE SAME SCREEN] 8a. Your preference is: [HORIZONTAL SCALE LABEL TAILS ARE 0= Strongly prefer A, 3= Somewhat prefer A, 5= Neutral, 7= Somewhat prefer B, 10= Strongly prefer B ] 8b. Please indicate whether your current is more like A or B. [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A, 5= Equally like A & B, 10= More like B ] 8c. Regarding access to and size of food outlets, the you d hope to find would be: [HORIZONTAL SCALE LABEL TAILS ARE 0= More like A than your current, 5= Like your current, 10= More like B than your current ] 110

RESIDENTIAL PREFERENCES AND PUBLIC HEALTH IN METRO VANCOUVER. Promoting Health and Well Being by Meeting the Demand for Walkable Urban Environments

RESIDENTIAL PREFERENCES AND PUBLIC HEALTH IN METRO VANCOUVER. Promoting Health and Well Being by Meeting the Demand for Walkable Urban Environments RESIDENTIAL PREFERENCES AND PUBLIC HEALTH IN METRO VANCOUVER Promoting Health and Well Being by Meeting the Demand for Walkable Urban Environments A UBC Health & Community Design Lab Report September 2014

More information

Central London Neighbourhood Profile

Central London Neighbourhood Profile Central London Neighbourhood Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics

More information

Reference: Toronto Public Health. The Walkable City: Neighbourhood Design and Preferences, Travel Choices and Health. April 2012

Reference: Toronto Public Health. The Walkable City: Neighbourhood Design and Preferences, Travel Choices and Health. April 2012 Reference: Toronto Public Health. The Walkable City: Neighbourhood Design and Preferences, Travel Choices and Health. April 2012 Authors: Kim Perrotta, Monica Campbell, Shawn Chirrey, Larry Frank and Jim

More information

Southcrest Neighbourhood Profile

Southcrest Neighbourhood Profile Southcrest Neighbourhood Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics

More information

Hamilton Road Neighbourhood Profile

Hamilton Road Neighbourhood Profile Hamilton Road Neighbourhood Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics

More information

Westminster Neighbourhood Profile

Westminster Neighbourhood Profile Westminster Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics & Age

More information

Stoney Creek Neighbourhood Profile

Stoney Creek Neighbourhood Profile Stoney Creek Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics & Age

More information

East London Neighbourhood Profile

East London Neighbourhood Profile East London Neighbourhood Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics

More information

Jackson Neighbourhood Profile

Jackson Neighbourhood Profile Jackson Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics & Age Distribution

More information

Huron Heights Neighbourhood Profile

Huron Heights Neighbourhood Profile Huron Heights Neighbourhood Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics

More information

Summary Report: Built Environment, Health and Obesity

Summary Report: Built Environment, Health and Obesity Research and education Built Environment Edmonton Project Summary Report: Built Environment, Health and Obesity Introduction In 2007 the Canadian Institutes of Health Research and the Heart and Stroke

More information

Built Environment and Older Adults: Supporting Smooth Transitions Across the Life- Span. Dr. Lawrence Frank, Professor and Bombardier UBC

Built Environment and Older Adults: Supporting Smooth Transitions Across the Life- Span. Dr. Lawrence Frank, Professor and Bombardier UBC Built Environment and Older Adults: Supporting Smooth Transitions Across the Life- Span Dr. Lawrence Frank, Professor and Bombardier Chair @ UBC The Hidden Health Costs of Transportation - Frank et al

More information

2011 Origin-Destination Survey Bicycle Profile

2011 Origin-Destination Survey Bicycle Profile TRANS Committee 2011 Origin-Destination Survey National Capital Region December 2012 TRANS Committee Members: City of Ottawa, including OC Transpo Ville de Gatineau Société de transport de l Outaouais

More information

Fox Hollow Neighbourhood Profile

Fox Hollow Neighbourhood Profile Fox Hollow Profile For further information contact: John-Paul Sousa Planning Research Analyst Direct: (519) 661-2500 ext. 5989 I email: jpsousa@london.ca Page 1 Page 2 Population Characteristics & Age

More information

TRANSPORTATION TOMORROW SURVEY

TRANSPORTATION TOMORROW SURVEY Clause No. 15 in Report No. 7 of was adopted, without amendment, by the Council of The Regional Municipality of York at its meeting held on April 17, 2014. 15 2011 TRANSPORTATION TOMORROW SURVEY recommends

More information

Five Ways the 2016 Census Affects Marketers

Five Ways the 2016 Census Affects Marketers Five Ways the 2016 Census Affects Marketers February 15, 2018 Dr. Doug Norris Senior Vice President and Chief Demographer Rupen Seoni Senior Vice President and Practice Leader Today s presenters Dr. Doug

More information

Travel Patterns and Characteristics

Travel Patterns and Characteristics DRAFT 2006 Transportation Fact Book SECTION 4 Travel Patterns and Characteristics 43 2006 Transportation Fact Book DRAFT 44 DRAFT 2006 Transportation Fact Book Why do we conduct travel surveys? The main

More information

2011 Transportation Tomorrow Survey. Data Presentation

2011 Transportation Tomorrow Survey. Data Presentation 2011 Transportation Tomorrow Survey Data Presentation Participating Agencies Conduct of the Survey Supporting Agencies of TTS Agency 1986 1991 1996 2001 2006 2011 Mininstry of Transportation, Ontario Y

More information

Examining the Scope, Facilitators, and Barriers to Active Transportation Patterns in Kingston, Ontario: A Seasonal Analysis

Examining the Scope, Facilitators, and Barriers to Active Transportation Patterns in Kingston, Ontario: A Seasonal Analysis Examining the Scope, Facilitators, and Barriers to Active Transportation Patterns in Kingston, Ontario: A Seasonal Analysis Daphne Mayer, MPH, Kingston, Frontenac and Lennox & Addington Public Health Patricia

More information

1999 On-Board Sacramento Regional Transit District Survey

1999 On-Board Sacramento Regional Transit District Survey SACOG-00-009 1999 On-Board Sacramento Regional Transit District Survey June 2000 Sacramento Area Council of Governments 1999 On-Board Sacramento Regional Transit District Survey June 2000 Table of Contents

More information

Catalyst for Change:

Catalyst for Change: Catalyst for Change: Toronto Examples Linking Health and Transportation Presented at Walk 21 Conference Vancouver 2011 Monica Campbell, Director Healthy Public Policy Toronto Public Health 1 About Toronto

More information

University Of Maryland

University Of Maryland 2000 Census Census Data 200 Census Change 2000 to 200 SUBJECT Number Percent SUBJECT Number Percent Number Percent TOTAL POPULATION 437 TOTAL POPULATION 246-9 -43.7 White 283 64.8 White 65 67. -8-4.7 Black

More information

Customer Satisfaction Tracking Report 2016 Quarter 1

Customer Satisfaction Tracking Report 2016 Quarter 1 Customer Satisfaction Tracking Report 2016 Quarter 1 May 2016 Prepared by: NRG Research Group Project no. 317-15-1445 Suite 1380-1100 Melville Street Vancouver, BC V6E 4A6 Table of Contents Background

More information

Community & Transportation Preferences Survey

Community & Transportation Preferences Survey Community & Transportation Preferences Survey Webinar: August 5, 2015 Hugh Morris, AICP, LEED Realtor.org Jennifer Dill, Ph.D. trec.pdx.edu 1 Introduction National Association of Realtors Over 1,000,000

More information

Acknowledgements. Ms. Linda Banister Ms. Tracy With Mr. Hassan Shaheen Mr. Scott Johnston

Acknowledgements. Ms. Linda Banister Ms. Tracy With Mr. Hassan Shaheen Mr. Scott Johnston Acknowledgements The 2005 Household Travel Survey was funded by the City of Edmonton and Alberta Infrastructure and Transportation (AIT). The survey was led by a steering committee comprised of: Dr. Alan

More information

DON MILLS-EGLINTON Mobility Hub Profile

DON MILLS-EGLINTON Mobility Hub Profile Mobility Hub Profile Dundas Don Mills-Eglinton West-Bloor Anchor Hub Gateway Hub N MOBILITY HUBS: Places of connectivity between regional and rapid transit services, where different modes of transportation

More information

Briefing Paper #1. An Overview of Regional Demand and Mode Share

Briefing Paper #1. An Overview of Regional Demand and Mode Share 2011 Metro Vancouver Regional Trip Diary Survey Briefing Paper #1 An Overview of Regional Demand and Mode Share Introduction The 2011 Metro Vancouver Regional Trip Diary Survey is the latest survey conducted

More information

Healthy Toronto by Design: The role of public health in shaping a healthy city

Healthy Toronto by Design: The role of public health in shaping a healthy city Healthy Toronto by Design: The role of public health in shaping a healthy city Monica Campbell, Ronald Macfarlane and Carol Mee Healthy Public Policy, Toronto Public Health Presented at the 141 st American

More information

Non-motorized Transportation Planning Resource Book Mayor s Task Force on Walking and Bicycling City of Lansing, Michigan Spring 2007 pg.

Non-motorized Transportation Planning Resource Book Mayor s Task Force on Walking and Bicycling City of Lansing, Michigan Spring 2007 pg. Non-motorized Transportation Planning Resource Book pg. 105 of 158 Non-motorized Transportation Planning Resource Book pg. 106 of 158 Non-motorized Transportation Planning Resource Book pg. 107 of 158

More information

Sandra Nutter, MPH James Sallis, PhD Gregory J Norman, PhD Sherry Ryan, PhD Kevin Patrick, MD, MS

Sandra Nutter, MPH James Sallis, PhD Gregory J Norman, PhD Sherry Ryan, PhD Kevin Patrick, MD, MS Objectively Measured Environmental Correlates of Adolescent Physical Activity Sandra Nutter, MPH James Sallis, PhD Gregory J Norman, PhD Sherry Ryan, PhD Kevin Patrick, MD, MS San Diego State University

More information

Market Factors and Demand Analysis. World Bank

Market Factors and Demand Analysis. World Bank Market Factors and Demand Analysis Bank Workshop and Training on Urban Transport Planning and Reform. Baku, April 14-16, 2009 Market Factors The market for Public Transport is affected by a variety of

More information

Healthy Toronto by Design

Healthy Toronto by Design Healthy Toronto by Design 50 th International Making Cities Livable Conference June 23-27, 2013 Dr. David McKeown Medical Officer of Health Toronto City of Toronto: 2.7 million population 50% immigrants

More information

2020 K Street NW, Suite 410 Washington, DC (202)

2020 K Street NW, Suite 410 Washington, DC (202) 2020 K Street NW, Suite 410 Washington, DC 20006 (202) 463-7300 Interview dates: October 24 25, 2013 Interviews: 1,008 adults CONDUCTED BY IPSOS PUBLIC AFFAIRS These are findings of an Ipsos online poll

More information

Guidelines for Providing Access to Public Transportation Stations APPENDIX C TRANSIT STATION ACCESS PLANNING TOOL INSTRUCTIONS

Guidelines for Providing Access to Public Transportation Stations APPENDIX C TRANSIT STATION ACCESS PLANNING TOOL INSTRUCTIONS APPENDIX C TRANSIT STATION ACCESS PLANNING TOOL INSTRUCTIONS Transit Station Access Planning Tool Instructions Page C-1 Revised Final Report September 2011 TRANSIT STATION ACCESS PLANNING TOOL INSTRUCTIONS

More information

U.S. Bicycling Participation Study

U.S. Bicycling Participation Study U.S. Bicycling Participation Study Report of findings from the 2016 survey Conducted by Corona Insights Commissioned by PeopleForBikes Released July 2017 Table of Contents Background and Objectives 3 Research

More information

In 2018 a total of 56,127 students received an ATAR, 934 fewer than in The gender balance was similar to 2017.

In 2018 a total of 56,127 students received an ATAR, 934 fewer than in The gender balance was similar to 2017. ATAR 2018 Preliminary report on the Scaling of the 2018 NSW Higher School Certificate This preliminary report has been prepared to provide some information on the calculation of the Australian Tertiary

More information

Chapter 14 PARLIER RELATIONSHIP TO CITY PLANS AND POLICIES. Recommendations to Improve Pedestrian Safety in the City of Parlier (2014)

Chapter 14 PARLIER RELATIONSHIP TO CITY PLANS AND POLICIES. Recommendations to Improve Pedestrian Safety in the City of Parlier (2014) Chapter 14 PARLIER This chapter describes the current status and future plans for biking and walking in the City of Parlier. RELATIONSHIP TO CITY PLANS AND POLICIES The Parlier General Plan is the primary

More information

NASHUA REGIONAL PLANNING COMMISSION REGIONAL BICYCLE AND PEDESTRIAN PLAN

NASHUA REGIONAL PLANNING COMMISSION REGIONAL BICYCLE AND PEDESTRIAN PLAN NASHUA REGIONAL PLANNING COMMISSION REGIONAL BICYCLE AND PEDESTRIAN PLAN June, 2005 Prepared by the Nashua Regional Planning Commission 2005 NRPC Regional Bicycle and Pedestrian Plan- JUNE 2005 ACKNOWLEDGEMENTS

More information

Capital Bikeshare 2011 Member Survey Executive Summary

Capital Bikeshare 2011 Member Survey Executive Summary Capital Bikeshare 2011 Member Survey Executive Summary Prepared by: LDA Consulting Washington, DC 20015 (202) 548-0205 June 14, 2012 EXECUTIVE SUMMARY Overview This report presents the results of the 2012

More information

VI. Market Factors and Deamnd Analysis

VI. Market Factors and Deamnd Analysis VI. Market Factors and Deamnd Analysis Introduction to Public Transport Planning and Reform VI-1 Market Factors The market for Public Transport is affected by a variety of factors No two cities or even

More information

Kevin Manaugh Department of Geography McGill School of Environment

Kevin Manaugh Department of Geography McGill School of Environment Kevin Manaugh Department of Geography McGill School of Environment Outline Why do people use active modes? Physical (Built environment) Factors Psychological Factors Empirical Work Neighbourhood Walkability

More information

How Policy Drives Mode Choice in Children s Transportation to School

How Policy Drives Mode Choice in Children s Transportation to School How Policy Drives Mode Choice in Children s Transportation to School Physical Activity through Active Transportation Ruth L. Steiner 2011 Technical Conference and Exhibit Lake Buena Vista, FL April 3-6,

More information

2010 Pedestrian and Bicyclist Special Districts Study Update

2010 Pedestrian and Bicyclist Special Districts Study Update 2010 Pedestrian and Bicyclist Special Districts Study Update Pedestrian and Bicyclist Special Districts Program Overview H-GAC s Special Districts Program aims to provide strategic investments in pedestrian

More information

Bike Planner Overview

Bike Planner Overview Bike Planner Overview A Web-based Sketch Planning Tool for Los Angeles County presented by William E. Walter, GISP April 12, 2017 GIS-T Transportation leadership you can trust. Bike Planner Overview Guiding

More information

DUNDAS WEST-BLOOR Mobility Hub Profile

DUNDAS WEST-BLOOR Mobility Hub Profile Mobility Hub Profile Dundas West-Bloor Anchor Hub Gateway Hub N MOBILITY HUBS: Places of connectivity between regional and rapid transit services, where different modes of transportation come together

More information

Travel Behaviour Study of Commuters: Results from the 2010 Dalhousie University Sustainability Survey

Travel Behaviour Study of Commuters: Results from the 2010 Dalhousie University Sustainability Survey Travel Behaviour Study of Commuters: Results from the 2010 Dalhousie University Sustainability Survey Technical Report 2011-602 Prepared by: M.A. Habib, K.D. Leckovic & D. Richardson Prepared for: Office

More information

PASSENGER SURVEY RESULTS

PASSENGER SURVEY RESULTS ROGUE VALLEY TRANSPORTATION DISTRICT PASSENGER SURVEY RESULTS Date: December 12, 2018 Project #: 21289 To: Paige West, RVTD From: Susan Wright, PE; Molly McCormick; (Kittelson & Associates, Inc.) Subject:

More information

June 2015 REGIONAL TRANSPORTATION SNAPSHOT

June 2015 REGIONAL TRANSPORTATION SNAPSHOT June 2015 REGIONAL TRANSPORTATION SNAPSHOT THE REGION Who are we? The Greater Toronto and Hamilton Area (GTHA), consisting of Durham Region, Halton Region, the City of Hamilton, Peel Region, the City of

More information

2014 peterborough city and county. active. transportation. & health. indicators primer

2014 peterborough city and county. active. transportation. & health. indicators primer 2014 city and county active transportation & health indicators primer executive summary Walking, cycling and transit are good for our personal health, our local economies, and the environment. Understanding

More information

Health Impact Analysis for Integrated Regional Land Use and Transportation Plan

Health Impact Analysis for Integrated Regional Land Use and Transportation Plan Health Impact Analysis for Integrated Regional Land Use and Transportation Plan Hsi-Hwa Hu, Guoxiong Huang, Frank Wen, Simon Choi (Southern California Association of Governments) Margaret Shih (Los Angeles

More information

Travel and Rider Characteristics for Metrobus

Travel and Rider Characteristics for Metrobus Travel and Rider Characteristics for Metrobus 040829040.15 Travel and Rider Characteristics for Metrobus: 2012-2015 Overview The Miami Dade County Metropolitan Planning Organization (MPO) conducted a series

More information

Carbonless Footprints: Health and Environmental benefits of Active Transportation

Carbonless Footprints: Health and Environmental benefits of Active Transportation Carbonless Footprints: Health and Environmental benefits of Active Transportation Dr. Lawrence Frank, Professor and Bombardier Chair in Sustainable Transportation - University of British Columbia Health

More information

Modal Shift in the Boulder Valley 1990 to 2009

Modal Shift in the Boulder Valley 1990 to 2009 Modal Shift in the Boulder Valley 1990 to 2009 May 2010 Prepared for the City of Boulder by National Research Center, Inc. 3005 30th Street Boulder, CO 80301 (303) 444-7863 www.n-r-c.com Table of Contents

More information

NEWMARKET CENTRE Mobility Hub Profile

NEWMARKET CENTRE Mobility Hub Profile Mobility Hub Profile Dundas Newmarket West-Bloor Centre Anchor Hub Gateway Hub N MOBILITY HUBS: Places of connectivity between regional and rapid transit services, where different modes of transportation

More information

OC Healthy Communities Forum. The proportion of the population that live within a half mile of a major transit access point.

OC Healthy Communities Forum. The proportion of the population that live within a half mile of a major transit access point. OC Healthy Communities Forum Transit Access The proportion of the population that live within a half mile of a major transit access point. Use of public transit can result in decreased greenhouse gas emissions

More information

Exceeding expectations: The growth of walking in Vancouver and creating a more walkable city in the future through EcoDensity

Exceeding expectations: The growth of walking in Vancouver and creating a more walkable city in the future through EcoDensity Exceeding expectations: The growth of walking in Vancouver and creating a more walkable city in the future through EcoDensity Melina Scholefield, P. Eng. Manager, Sustainability Group, City of Vancouver

More information

Life Transitions and Travel Behaviour Study. Job changes and home moves disrupt established commuting patterns

Life Transitions and Travel Behaviour Study. Job changes and home moves disrupt established commuting patterns Life Transitions and Travel Behaviour Study Evidence Summary 2 Drivers of change to commuting mode Job changes and home moves disrupt established commuting patterns This leaflet summarises new analysis

More information

cyclingincities opinion survey ABOUT THE STUDY WHO DID WE ASK? WHAT DID WE DO?

cyclingincities opinion survey ABOUT THE STUDY WHO DID WE ASK? WHAT DID WE DO? cyclingincities opinion survey ABOUT THE STUDY Using a bicycle for transportation is good for the environment, and it also offers personal health benefits. Cycling is also feasible, since more than 80%

More information

Community Social Profile Wellesley, Wilmot and Woolwich

Community Social Profile Wellesley, Wilmot and Woolwich Community Trends for 2013 in Cambridge, North Dumfries, Wellesley, Wilmot and Woolwich Community Social Profile - Wellesley, Wilmot and Woolwich Published December 2014 Community Social Profile Wellesley,

More information

METROPOLITAN TRANSPORTATION PLAN OUTREACH: INTERACTIVE MAP SUMMARY REPORT- 10/03/14

METROPOLITAN TRANSPORTATION PLAN OUTREACH: INTERACTIVE MAP SUMMARY REPORT- 10/03/14 METROPOLITAN TRANSPORTATION PLAN OUTREACH: INTERACTIVE MAP SUMMARY REPORT- 10/03/14 INTRODUCTION This document summarizes the results of the online interactive mapping exercise implemented by MIG for the

More information

Transport attitudes, residential preferences, and urban form effects on cycling and car use.

Transport attitudes, residential preferences, and urban form effects on cycling and car use. Downloaded from orbit.dtu.dk on: Mar 10, 2019 Transport attitudes, residential preferences, and urban form effects on cycling and car use. Nielsen, Thomas Alexander Sick; Olafsson, Anton Stahl; Carstensen,

More information

University of Michigan & Urban Land Institute Real Estate Forum. Mary Beth Graebert Michigan State University

University of Michigan & Urban Land Institute Real Estate Forum. Mary Beth Graebert Michigan State University University of Michigan & Urban Land Institute Real Estate Forum Mary Beth Graebert Michigan State University November 20, 2013 Michigan State University Land Policy Institute Strong focus on research and

More information

nipigon.net Township of Nipigon 2018 Community Profile

nipigon.net Township of Nipigon 2018 Community Profile nipigon.net Township of Nipigon V 1.0 February 2018 2018 Nipigon nipigon.net nipigon.net Township of Nipigon nipigon.net Township of Nipigon nipigon.net Township of Nipigon nipigon.net Township of Nipigon

More information

2016 Capital Bikeshare Member Survey Report

2016 Capital Bikeshare Member Survey Report 2016 Capital Bikeshare Member Survey Report Prepared by: LDA Consulting Washington, DC 20015 (202) 548-0205 February 24, 2017 EXECUTIVE SUMMARY Overview This report presents the results of the November

More information

Executive Summary. TUCSON TRANSIT ON BOARD ORIGIN AND DESTINATION SURVEY Conducted October City of Tucson Department of Transportation

Executive Summary. TUCSON TRANSIT ON BOARD ORIGIN AND DESTINATION SURVEY Conducted October City of Tucson Department of Transportation Executive Summary TUCSON TRANSIT ON BOARD ORIGIN AND DESTINATION SURVEY Conducted October 2004 Prepared for: City of Tucson Department of Transportation May 2005 TUCSON TRANSIT ON BOARD ORIGIN AND DESTINATION

More information

National Community and Transportation Preferences Survey. September 2017

National Community and Transportation Preferences Survey. September 2017 National Community and Transportation Preferences Survey September Executive Summary - Overview The Community and Transportation Preferences Survey echoes many of the major findings from the previous surveys.

More information

Active Travel and Exposure to Air Pollution: Implications for Transportation and Land Use Planning

Active Travel and Exposure to Air Pollution: Implications for Transportation and Land Use Planning Active Travel and Exposure to Air Pollution: Implications for Transportation and Land Use Planning Steve Hankey School of Public and International Affairs, Virginia Tech, 140 Otey Street, Blacksburg, VA

More information

CONCEPTUAL MODELS: THE RELATIONSHIP BETWEEN BUILT ENVIRONMENT AND HEALTH

CONCEPTUAL MODELS: THE RELATIONSHIP BETWEEN BUILT ENVIRONMENT AND HEALTH CONCEPTUAL MODELS: THE RELATIONSHIP BETWEEN BUILT ENVIRONMENT AND HEALTH TABLE OF CONTENTS Acknowledgements 3 Description of Process 4 Overview Model: From Built Environment to Public Health 8 Aggregate

More information

DEVELOPMENT OF A SET OF TRIP GENERATION MODELS FOR TRAVEL DEMAND ESTIMATION IN THE COLOMBO METROPOLITAN REGION

DEVELOPMENT OF A SET OF TRIP GENERATION MODELS FOR TRAVEL DEMAND ESTIMATION IN THE COLOMBO METROPOLITAN REGION DEVELOPMENT OF A SET OF TRIP GENERATION MODELS FOR TRAVEL DEMAND ESTIMATION IN THE COLOMBO METROPOLITAN REGION Ravindra Wijesundera and Amal S. Kumarage Dept. of Civil Engineering, University of Moratuwa

More information

The Case for New Trends in Travel

The Case for New Trends in Travel The Case for New Trends in Travel The Future of Cities and Travel Steven E. Polzin, PhD. Center for urban Transportation Research University of South Florida October 19, 2008 Successful Strategies from

More information

The unmet demand for walkability: Disparities between preferences and actual choices for residential environments in Toronto and Vancouver

The unmet demand for walkability: Disparities between preferences and actual choices for residential environments in Toronto and Vancouver QUANTITATIVE RESEARCH The unmet demand for walkability: Disparities between preferences and actual choices for residential environments in Toronto and Vancouver Lawrence D. Frank, PhD, 1 Suzanne E. Kershaw,

More information

Creating walkable, bikeable and transit-supportive communities in Halton

Creating walkable, bikeable and transit-supportive communities in Halton Creating walkable, bikeable and transit-supportive communities in Halton By presenting current research and best practices, the information in this paper is meant to support and broaden discussion on how

More information

WALK Friendly Communities: Creating Vibrant, Inclusive Places for People

WALK Friendly Communities: Creating Vibrant, Inclusive Places for People WALK Friendly Communities: Creating Vibrant, Inclusive Places for People Walkers are the indicator species for vibrant communities ~ Dr. Rodney Tolley, Director, Walk21 Imagine yourself walking safely

More information

DON MILLS-SHEPPARD Mobility Hub Profile

DON MILLS-SHEPPARD Mobility Hub Profile DON MILLS-SHEPPARD Mobility Hub Profile Dundas Don Mills-Sheppard West-Bloor Anchor Hub Gateway Hub N MOBILITY HUBS: Places of connectivity between regional and rapid transit services, where different

More information

BUILDING THE CASE FOR TRAVEL OPTIONS IN WASHING TON COUNTY. Image: Steve Morgan. Image: Steve Morgan

BUILDING THE CASE FOR TRAVEL OPTIONS IN WASHING TON COUNTY. Image: Steve Morgan. Image: Steve Morgan BUILDING THE CASE FOR TRAVEL OPTIONS IN WASHING TON COUNTY Image: Steve Morgan Image: Steve Morgan Image: TriMet Image: TriMet WHAT ARE TRAVEL OPTIONS PROGRAMS? Travel options programs encourage residents,

More information

Peel Health Initiatives Health and Urban Form

Peel Health Initiatives Health and Urban Form Region of Peel Public Health Peel Health Initiatives Health and Urban Form alpha Conference June 9, 2008 Gayle Bursey Director, Chronic Disease and Injury Prevention Declaration No part of the information

More information

Access BART: TOD and Improved Connections. October 29, 2008

Access BART: TOD and Improved Connections. October 29, 2008 Access BART: TOD and Improved Connections October 29, 2008 1 Access BART Study Goals Evaluate at the system-level land use and access scenarios to optimize ridership Identify station clusters that provide

More information

Understanding the Pattern of Work Travel in India using the Census Data

Understanding the Pattern of Work Travel in India using the Census Data Understanding the Pattern of Work Travel in India using the Census Data Presented at Urban Mobility India Hyderabad (India), November 5 th 2017 Nishant Singh Research Scholar Department of Civil Engineering

More information

Introduction. Mode Choice and Urban Form. The Transportation Planner s Approach. The problem

Introduction. Mode Choice and Urban Form. The Transportation Planner s Approach. The problem Introduction The table below shows transit s share in the urban US (all trip purposes) and the 10 urban areas where it is most popular (2008 data): Mode Choice and Urban Form Philip A. Viton April 4, 2014

More information

Hunter and Angler Expenditures, Characteristics, and Economic Effects, North Dakota,

Hunter and Angler Expenditures, Characteristics, and Economic Effects, North Dakota, Agribusiness and Applied Economics Report No. 507-S January 2003 Hunter and Angler Expenditures, Characteristics, and Economic Effects, North Dakota, 2001-2002 Dean A. Bangsund and F. Larry Leistritz*

More information

Regional Bicycle Barriers Study

Regional Bicycle Barriers Study Regional Bicycle Barriers Study Executive Summary Background and Purpose The 2040 Transportation Policy Plan (TPP) sets policies for planning and investment direction in the transportation system in the

More information

Community & Transportation Preferences Survey U.S. Metro Areas, 2015 July 23, 2015

Community & Transportation Preferences Survey U.S. Metro Areas, 2015 July 23, 2015 Community & Transportation Preferences Survey U.S. Metro Areas, 2015 July 23, 2015 Realtor.org trec.pdx.edu 1 Highlights: Generation gaps in everyday travel Only 71% of Millennials like driving (the lowest

More information

Coolest Cities Results Summary

Coolest Cities Results Summary Coolest Cities Results Summary About Coolest Cities Canada s six largest urban areas provide homes and jobs for almost 15 million people, nearly half of our population. Transporting these citizens to and

More information

TR NEWS. Public Health and Transportation. Innovation, Intervention, and Improvements NUMBER 299 SEPTEMBER OCTOBER 2015

TR NEWS. Public Health and Transportation. Innovation, Intervention, and Improvements NUMBER 299 SEPTEMBER OCTOBER 2015 TR NEWS NUMBER 299 SEPTEMBER OCTOBER 2015 Public Health and Transportation Innovation, Intervention, and Improvements Public Health and Transportation Measuring the Health Benefits of Walking and Bicycling

More information

Transportation and Health Tool

Transportation and Health Tool Working together to evolve the Transportation and Health Tool APHA Webinar March 22, 2016 Ann Steedly, PE Overview THT Development Context Development of Indicators Strategies, Interventions & Policies

More information

FULL PROFILE Census, 2018 Estimates with 2023 Projections Calculated using Weighted Block Centroid from Block Groups Realm Realty Lat/Lon: 3

FULL PROFILE Census, 2018 Estimates with 2023 Projections Calculated using Weighted Block Centroid from Block Groups Realm Realty Lat/Lon: 3 FULL PROFILE 2000-2010 Census, 2018 Estimates with 2023 Projections Calculated using Weighted Block Centroid from Block Groups Realm Realty Lat/Lon: 30.0027/-90.1613 RF1 Lakeside Shopping Center Metairie,

More information

Motorized Transportation Trips, Employer Sponsored Transit Program and Physical Activity

Motorized Transportation Trips, Employer Sponsored Transit Program and Physical Activity Motorized Transportation Trips, Employer Sponsored Transit Program and Physical Activity Ugo Lachapelle Msc. Lawrence D. Frank, PhD Active Living Research Washington, DC April 12, 2008 Outline Background:

More information

Evaluation of San Diego's First CicloSDias Open Streets Event

Evaluation of San Diego's First CicloSDias Open Streets Event Evaluation of San Diego's First CicloSDias Open Streets Event Funded by a grant from The California Endowment San Diego State University School of Public Affair University of California San Diego Department

More information

2017 North Texas Regional Bicycle Opinion Survey

2017 North Texas Regional Bicycle Opinion Survey 2017 North Texas Regional Bicycle Opinion Survey Sustainable Development Program Kevin Kokes, AICP Public Meetings April, 2018 North Central Texas Council of Governments MPO for the Dallas-Fort Worth Region

More information

Understanding Transit Demand. E. Beimborn, University of Wisconsin-Milwaukee

Understanding Transit Demand. E. Beimborn, University of Wisconsin-Milwaukee Understanding Transit Demand E. Beimborn, University of Wisconsin-Milwaukee 1 Purpose To provide a basic understanding of transit ridership and some common misunderstandings. To explain concepts of choice

More information

The North Shore Transportation Improvement Strategy and Western Richmond Terrace 1 : The Forgotten Corridor

The North Shore Transportation Improvement Strategy and Western Richmond Terrace 1 : The Forgotten Corridor Elm Park Civic Association Island Voice Do Me A Faber The North Shore Transportation Improvement Strategy and Western Richmond Terrace 1 : The Forgotten Corridor Introduction Richmond Terrace is the northernmost

More information

Appendix 9 SCUBA diving in the sea

Appendix 9 SCUBA diving in the sea Appendix 9 SCUBA diving in the sea Firth of Clyde Forum SMRTS2015 Final Report 195 March 2016 Appendix 9 SCUBA diving in the sea Table A9.1: Summary of sample confidence levels Responses Spatial data Questionnaire

More information

Rolling Out Measures of Non-Motorized Accessibility: What Can We Now Say? Kevin J. Krizek University of Colorado

Rolling Out Measures of Non-Motorized Accessibility: What Can We Now Say? Kevin J. Krizek University of Colorado Rolling Out Measures of Non-Motorized Accessibility: What Can We Now Say? Kevin J. Krizek University of Colorado www.kevinjkrizek.org Acknowledgements Mike Iacono Ahmed El-Geneidy Chen-Fu Liao Outline

More information

SACRAMENTO AREA TRAVEL SURVEY: BEFORE BIKE SHARE

SACRAMENTO AREA TRAVEL SURVEY: BEFORE BIKE SHARE SACRAMENTO AREA TRAVEL SURVEY: BEFORE BIKE SHARE August 2017 A Research Report from the National Center for Sustainable Transportation Susan Handy, University of California, Davis Drew Heckathorn, University

More information

MANITOBA'S ABORIGINAL COMMUNITY: A 2001 TO 2026 POPULATION & DEMOGRAPHIC PROFILE

MANITOBA'S ABORIGINAL COMMUNITY: A 2001 TO 2026 POPULATION & DEMOGRAPHIC PROFILE MANITOBA'S ABORIGINAL COMMUNITY: A 2001 TO 2026 POPULATION & DEMOGRAPHIC PROFILE MBS 2005-4 JULY 2005 TABLE OF CONTENTS I. Executive Summary 3 II. Introduction.. 9 PAGE III. IV. Projected Aboriginal Identity

More information

WOMEN IN THE NWT - SUMMARY

WOMEN IN THE NWT - SUMMARY In 16, 44,469 people lived in the Northwest Territories (NWT) with females accounting for just under half (49%) of the population. The NWT population consists of almost equal numbers of Indigenous (First

More information

Urban planners have invested a lot of energy in the idea of transit-oriented

Urban planners have invested a lot of energy in the idea of transit-oriented DOES TRANSIT-ORIENTED DEVELOPMENT NEED THE TRANSIT? D A N I E L G. C H AT M A N Urban planners have invested a lot of energy in the idea of transit-oriented developments (TODs). Developing dense housing

More information

Frequently asked questions about how the Transport Walkability Index was calculated are answered below.

Frequently asked questions about how the Transport Walkability Index was calculated are answered below. Transport Walkability Index The Transport Walkability Index is a relative indicator of how well the built environment in different areas supports walking for transport. The index is frequently used in

More information

BUILT FOR WALKING: SAFE ENVIRONMENTS FOR ACTIVE SCHOOL TRANSPORTATION

BUILT FOR WALKING: SAFE ENVIRONMENTS FOR ACTIVE SCHOOL TRANSPORTATION TS4.1 BUILT FOR WALKING: SAFE ENVIRONMENTS FOR ACTIVE SCHOOL TRANSPORTATION June 24, City-School Boards Advisory Committee Linda Rothman, BScOT, PhD, Post-Doctoral Fellow, York University, School of Kinesiology

More information

Bike Share Social Equity and Inclusion Target Neighborhoods

Bike Share Social Equity and Inclusion Target Neighborhoods Bike Share Social Equity and Inclusion Target Neighborhoods Target Neighborhoods West End/Visitation Park/Academy/Hamilton Heights Wellsgoodfellow/Kingsway West The Ville/Greater Ville Kingsway East/Fountain

More information