The Potential Impacts of Urban and Transit Planning Scenarios for 2031 on Car Use and Active Transportation in a Metropolitan Area.

Land use and transportation scenarios can help evaluate the potential impacts of urban compact or transit-oriented development (TOD). Future scenarios have been based on hypothetical developments or strategic planning but both have rarely been compared. We developed scenarios for an entire metropolitan area (Montreal, Canada) based on current strategic planning documents and contrasted their potential impacts on car use and active transportation with those of hypothetical scenarios. We collected and analyzed available urban planning documents and obtained key stakeholders' appreciation of transportation projects on their likelihood of implementation. We allocated 2006-2031 population growth according to recent trends (Business As Usual, BAU) or alternative scenarios (current planning; all in TOD areas; all in central zone). A large-scale and representative Origin-Destination Household Travel Survey was used to measure travel behavior. To estimate distances travelled by mode, in 2031, we used a mode choice model and a simpler method based on the 2008 modal share across population strata. Compared to the BAU, the scenario that allocated all the new population in already dense areas and that also included numerous public transit projects (unlikely to be implemented in 2031), was associated with greatest impacts. Nonetheless such major changes had relatively minor impacts, inducing at most a 15% reduction in distances travel by car and a 28% increase in distances walked, compared to a BAU. Strategies that directly target the reduction of car use, not considered in the scenarios assessed, may be necessary to induce substantial changes in a metropolitan area.

Evaluating the impact of implementing public bicycle share programs on cycling: the International Bikeshare Impacts on Cycling and Collisions Study (IBICCS).

BACKGROUND: Despite rapid expansion of public bicycle share programs (PBSP), there are limited evaluations of the population-level impacts of these programs on cycling, leaving uncertainty as to whether these programs lead to net health gains at a population level or attract those that already cycle and are sufficiently physically active. Our objective was to determine whether the implementation of PBSPs increased population-level cycling in cities across the US and Canada. METHODS: We conducted repeat cross-sectional surveys with 23,901 residents in cities with newly implemented PBSPs (Chicago, New York), existing PBSPs (Boston, Montreal, Toronto) and no PBSPs (Detroit, Philadelphia, Vancouver) at three time points (Fall 2012, 2013, 2014). We used a triple difference in differences analysis to assess whether there were increases in cycling over time amongst those living in closer proximity (< 500 m) to bicycle share docking stations in cities with newly implemented and existing PBSPs, relative to those in cities with no PBSPs. RESULTS: Living in closer proximity to bicycle share predicted increases in cycling over time for those living in cities with newly implemented PBSPs at 2-year follow-up. No change was seen over time for those living in closer proximity to bicycle share in cities with existing PBSPs relative to those in cities with no PBSP. CONCLUSION: These findings indicate that PBSPs are associated with increases in population-level cycling for those who live near to a docking station in the second year of program implementation.

The approaches to measuring the potential spatial access to urban health services revisited: distance types and aggregation-error issues.

BACKGROUND: The potential spatial access to urban health services is an important issue in health geography, spatial epidemiology and public health. Computing geographical accessibility measures for residential areas (e.g. census tracts) depends on a type of distance, a method of aggregation, and a measure of accessibility. The aim of this paper is to compare discrepancies in results for the geographical accessibility of health services computed using six distance types (Euclidean and Manhattan distances; shortest network time on foot, by bicycle, by public transit, and by car), four aggregation methods, and fourteen accessibility measures. METHODS: To explore variations in results according to the six types of distance and the aggregation methods, correlation analyses are performed. To measure how the assessment of potential spatial access varies according to three parameters (type of distance, aggregation method, and accessibility measure), sensitivity analysis (SA) and uncertainty analysis (UA) are conducted. RESULTS: First, independently of the type of distance used except for shortest network time by public transit, the results are globally similar (correlation >0.90). However, important local variations in correlation between Cartesian and the four shortest network time distances are observed, notably in suburban areas where Cartesian distances are less precise. Second, the choice of the aggregation method is also important: compared with the most accurate aggregation method, accessibility measures computed from census tract centroids, though not inaccurate, yield important measurement errors for 10% of census tracts. Third, the SA results show that the evaluation of potential geographic access may vary a great deal depending on the accessibility measure and, to a lesser degree, the type of distance and aggregation method. Fourth, the UA results clearly indicate areas of strong uncertainty in suburban areas, whereas central neighbourhoods show lower levels of uncertainty. CONCLUSION: In order to accurately assess potential geographic access to health services in urban areas, it is particularly important to choose a precise type of distance and aggregation method. Then, depending on the research objectives, the choices of the type of network distance (according to the mode of transportation) and of a number of accessibility measures should be carefully considered and adequately justified.

Evaluating the impact of environmental interventions across 2 countries: the International Bikeshare Impacts on Cycling and Collisions Study (IBICCS) Study protocol.

BACKGROUND: Few international studies examine public bicycle share programs (PBSP) health impacts. We describe the protocol for the International Bikeshare Impacts on Cycling and Collisions Study (IBICCS). METHODS: A quasi-experimental non-equivalent groups design was used. Intervention cities (Montreal, Toronto, Boston, New York and Vancouver) were matched to control cities (Chicago, Detroit, and Philadelphia) on total population, population density, cycling rates, and average yearly temperature. The study used three repeated, cross-sectional surveys in intervention and control cities in Fall 2012 (baseline), 2013 (year 1), and 2014 (year 2). A non-probabilistic online panel survey with a sampling frame of individuals residing in and around areas where PBSP are/would be implemented was used. A total of 12,000 respondents will be sampled. In each of the 8 cities 1000 respondents will be sampled with an additional 4000 respondents sampled based on the total population of the city. Survey questions include measures of self-rated health, and self-reported height and weight, knowledge and experience using PBSP, physical activity, bicycle helmet use and history of collisions and injuries while cycling, socio-demographic questions, and home/workplace locations. Respondents could complete questionnaires in English, French, and Spanish. Two weights will be applied to the data: inverse probability of selection and post-stratification on age and sex.A triple difference analysis will be used. This approach includes in the models, time, exposure, and treatment group, and interaction terms between these variables to estimate changes across time, between exposure groups and between cities. DISCUSSION: There are scientific and practical challenges in evaluating PBSP. Methodological challenges included: appropriate sample recruitment, exchangeability of treatment and control groups, controlling unmeasured confounding, and specifying exposure. Practical challenges arise in the evaluation of environmental interventions such as a PBSP: one of the companies involved filed for bankruptcy, a Hurricane devastated New York City, and one PBSP was not implemented. Overall, this protocol provides methodological and practical guidance for researchers wanting to study PBSP impacts on health.

Grassroots projects aimed at the built environment: Association with neighbourhood deprivation, land-use mix and injury risk to road users.

OBJECTIVES: 1) To describe grassroots projects aimed at the built environment and associated with active transportation on the Island of Montreal; and 2) to examine associations between the number of projects and indicators of neighbourhood material and social deprivation and the built environment. METHOD: We identified funding agencies and community groups conducting projects on built environments throughout the Island of Montreal. Through website consultation and a snowballing procedure, we inventoried projects that aimed at transforming built environments and that were carried out by community organizations between January 1, 2006, and November 1, 2010. We coded and validated information about project activities and created an interactive map using Geoclip software. Correlational analyses quantified associations between number of projects, neighbourhood characteristics and deprivation. RESULTS: A total of 134 community organizations were identified, and 183 grassroots projects were inventoried. A large number of projects were aimed at increasing awareness of/improving active or public transportation (n=95), improving road safety (n=84) and enhancing neighbourhood beautification and greening (n=69). The correlation between the presence of projects and the extent of neighbourhood material deprivation was small (Kendall's t=0.26, p<0.001), but in areas with greater social deprivation there were more projects (Kendall's t=0.38, p<0.001). Larger numbers of projects were also associated with the presence of more extensive land-use mix (Kendall's t=0.23, p<0.001) and a greater proportion of road intersections with injured pedestrians, cyclists and motor vehicle users (Kendall's t=0.43, p<0.001). CONCLUSION: There is significant community mobilization around built environments and active transportation. Investigations of the implementation processes and impacts are warranted.