Transportation

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Walking and bicycling for daily transportation are important ways to get regular physical activity, but such active travel has decreased dramatically over the past few decades. Investing transportation funds in sidewalks, traffic-calming devices, greenways, trails and public transit make it easier for people to walk and bike within their own neighborhoods and to other places they need to go. Designing communities that support active travel also creates recreational opportunities, promotes health and can even lower health care costs. Research that shows how infrastructure improvements promote active travel can help policy-makers, planners and other professionals create healthier communities for residents of all ages.

Download our Transportation-related Resources Sheet for the best evidence available about a variety of transportation-based strategies for promoting physical activity.

You can also view and download our The Role of Transportation in Promoting Physical Activity infographic.

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Effects of Bicycle Boulevards: Findings from a Longitudinal Panel Study

Date: 
03/12/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Research demonstrating the links between the physical environment and walking and bicycling has been reviewed extensively (Owen et al. 2004, Saelens et al. 2003, Ogilvie et al. 2006, Transportation Research Board and Institute of Medicine 2005). Much of the research has focused on adult behavior and few studies explore bicycle-specific infrastructure. Moreover, Pucher, Dill and Handy (2010) found that only a handful of studies were longitudinal, including a control sample. A review of research on environmental correlates of children’s active transportation (Pont et al, 2009) included 38 peer-reviewed articles, though none with longitudinal data.

The role of specific types of bicycle infrastructure in cyclist’s route choice decisions was examined by Broach, Dill, and Gliebe. Using GPS data from adult cyclists, they found a preference for separated paths, followed by bicycle boulevards. Bicycle boulevards are a form of traffic calming on residential streets that give bicycles priority over motor vehicles. This is done through the installation of a combination of traffic calming techniques, such as traffic diverters (which force cars to turn, but bikes and pedestrians can travel through), speed humps, and chicanes and bulb outs (which narrow the street). The boulevards are signed as bicycle routes. When a bicycle boulevard crosses a busy street, traffic signals are sometimes installed to assist cyclists in crossing safely. Stop signs along the street are reversed, so that cross traffic is stopped, rather than the through traffic on the boulevard. Motor vehicle traffic on the streets is much lower than nearby parallel streets, since through traffic is discouraged, and traffic speeds are about the same as bicycles because of the treatments.

Traffic is a major barrier to both adults and children cycling and walking more. In a random phone survey of Portland adults, “too much traffic” was the primary environmental barrier cited by respondents who wanted to bicycle more (Dill and Voros 2007). Of the adults who were not cyclists, but wanted to cycle more, 60% cited traffic as a barrier, while 33% cited the lack of bike lanes/trails, the next highest response; 65% of the adults who only cycled for recreation cited traffic as a barrier. In a national survey, 40% of parents cited traffic danger as a barrier for their children walking and cycling to school, second to long distances (55%) and significantly higher than crime danger (18%) (Dellinger and Staunton 2002).

Objectives
The overall aim of this research was to evaluate the effects of new, innovative infrastructure on physical activity (PA) of families with children. More specifically, the research: 1) Evaluated the effects of new bicycle boulevards (a form of traffic calming) on PA; 2) Examined PA for both recreation and transportation; and 3) Considered other correlates of PA, including socio-demographics, social factors, attitudes, and other physical environment factors, using an ecological model.

Methods
The Family Activity Study is a longitudinal panel study of the effects of bicycle boulevards on bicycling and walking behavior. The study started with 333 families with children living in 19 study sites (nine treatment and ten control) in the City of Portland, OR. This included 495 adults, 325 children ages 5-10, and 176 children ages 11-17. About 80% of the sample completed all phases of the study. Surveys were conducted at three points in time: Pre, Post, and Interim. The Pre and Post surveys are approximately two years apart, with bicycle boulevard construction occurring in between. The Interim surveys were fielded about one year after the Pre surveys, during the phased construction of the projects. The surveys (adults and children) includes personal and household socio-demographics, subjective perceptions of their neighborhood environment, travel attitudes, social norms, self-efficacy towards travel behavior, and self-reported biking and walking behavior. GPS (the GlobalSat DG-100) and accelerometer (the ActiGraph GT3X) data were collected from adults and children for five days during the Pre and Post periods. Data collection was completed July 2013. GPS data are processed to detect mode of transportation (drive, bike, walk, transit, other) and link to the transportation network.

Results
Post data collection was completed one month ago, and data are still being processed and cleaned. During the Pre data collection phase, adults in the control neighborhoods walked an average of 86 minutes and biked an average of 29 minutes over 5-days; adults in the treatment areas walked an average of 97 minutes and biked an average of 37 minutes. These differences were not statistically significant. This conference presentation will focus on an evaluation of Pre vs. Post behavior which will be completed by January 31, 2014.

Conclusions
The presentation will draw conclusions related to the three research objectives, focusing on the intervention's effect on PA, controlling for other factors.

Implications for Practice and Policy
If bicycle boulevards are positively associated with increased PA and active transportation among youth and adults, this may encourage more cities to implement this relatively low-cost infrastructure improvement.

References

  1. Dellinger, A. M. & C. E. Staunton (2002) Barriers to Children Walking and Biking to School -- United States, 1999. MMWR Weekly, 51, 701-704.
  2. Dill, J. & K. Voros (2007) Factors Affecting Bicycling Demand: Initial Survey Findings from the Portland, Oregon, Region. Transportation Research Record: Journal of the Transportation Research Board, 2031, pp 9-17.
  3. John Pucher, Jennifer Dill, and Susan Handy, "Infrastructure, Programs and Policies to Increase Cycling: An International Review," Preventive Medicine, Vol. 50(S1): S106-125, January 2010.
  4. Joseph Broach, Jennifer Dill, and John Gliebe, “Where Do Cyclists' Ride? A Route Choice Model Developed with Revealed Preference GPS Data,” Transportation Research-Part A. 46: 1730–1740, 2012.
  5. Ogilvie, D., R. Mitchell, N. Mutrie, M. Petticrew & S. Platt (2006) Evaluating Health Effects of Transport Interventions: Methodologic Case Study. American Journal of Preventive Medicine, 31, 118-126.
  6. Owen, N., N. Humpel, E. Leslie, A. Bauman & J. F. Sallis (2004) Understanding environmental influences on walking; Review and research agenda. Am J Prev Med, 27, 67-76.
  7. Pont, K., J. Ziviani, D. Wadley, S. Bennett, and R. Abbott (2009). "Environmental Correlates of Children's Active Transportation: A Systematic Literature Review." Health Place 15: 827-40.
  8. Saelens, B. E., J. F. Sallis & L. D. Frank (2003) Environmental Correlates of Walking and Cycling: Findings from the Transportation, Urban Design, and Planning Literatures. Annals of Behavioral Medicine, 25, 80-91.
  9. Transportation Research Board & Institute of Medicine. 2005. Does the built environment influcence physical activity? Examining the Evidence. Washington, DC: National Academy of Sciences.

 

Support / Funding Source
The Family Activity Study was funded by the Active Living Research program of the Robert Wood Johnson Foundation and the Oregon Transportation Research and Education Consortium (OTREC).

Authors: 
Jennifer Dill, PhD, Joseph Broach, MA, & Nathan McNeil, MURP
Location by State: 

Evidence Review: Reporting Guidelines to Enhance Evidence-Based Practice

Date: 
03/12/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Over the past decade, public and private U.S. funders have invested in research and evaluation to understand the most effective, feasible, and sustainable strategies to combat childhood obesity. This evidence is used to aid practitioners and decision-makers at the organizational or agency, community, state, or national levels in selecting strategies to best fit their health, economic, environmental, and social circumstances. Current comprehensive review systems (such as the Community Guide and the Cochrane Review) provide guidance to practitioners and decision-makers interested in implementing change; yet, keeping up with the vast amount of research and evaluation data generated in the field is an ongoing challenge. In turn, decision-makers often rely on insufficient evidence as well as reviews focused more on assessing the internal validity of study results without complementary evaluation of the external validity (e.g., reach, implementation fidelity, and sustainability) associated with intervention impacts.

Objectives
The aims of the review were to: 1) develop and apply replicable methods – modeled after respected formal systematic evidence review systems (e.g., Community Guide) – to assess the scientific and grey literature addressing policy and environmental strategies for reducing obesity levels, improving healthy eating, and/or increasing physical activity among youth aged 3-18 years of age; 2) summarize these findings using easy-to-read evidence maps that identify effects/associations related to obesity/overweight, physical activity, and nutrition/diet outcomes; and 3) classify intervention strategies, based on their effectiveness and population impact using  ratings ranging from “effective” (recommended for use) to “promising” and  “emerging” (recommended for further testing).

More comprehensive reviews stemming from improved reporting and review standards may provide a better platform for practitioners, decision-makers, evaluators, and researchers to understand the effectiveness and impact of interventions to prevent childhood obesity.

Methods
Investigators created a protocol to systematically identify, abstract, review, and rate evidence from a variety of sources (e.g., intervention evaluations, associational studies). The ratings were designed to reflect effectiveness (study design, intervention duration, effects or associations) and population impact (effectiveness plus potential population reach –participation or exposure and representativeness) of multicomponent and complex interventions, with a particular emphasis on impacts for racial/ethnic and lower-income populations of greatest need for these interventions. Over 2,000 documents, published between January 2000 and May 2009 in the scientific and grey literature, were identified (2008-2009) and systematically analyzed (2009-2012). Studies focused on policy or environmental strategies to reduce obesity/overweight, increase physical activity, and/or improve nutrition/diet among youth (3-18 years). Related articles (i.e., those corresponding to an intervention or associational study) were grouped together into a “study grouping.” Study groupings were categorized into one or more of 24 independent strategies to increase healthy eating or active living. Investigators used the RE-AIM framework (i.e., Reach, Effectiveness, Adoption, Implementation, and Maintenance) both to assess internal and external validity, and to derive standard, objective ratings of intervention effectiveness and impact for each study grouping.  The assigned ratings were then entered into an Access database to generate reports for a range of indicators (e.g., outcomes assessed, intervention components, funding sources) within and across strategies.

Results
From 396 study groupings (600 independent articles) included in this analysis, 142 (36%) were intervention evaluations and 254 (64%) were associational studies. Reported outcomes varied, including physical activity (45%), obesity/overweight (25%), nutrition (18%), sedentary behavior (2%), and other shorter-term proxies, such as trail use or fruit and vegetable purchases (10%). Evidence for intervention effectiveness was reported in 56% of the evaluation, and 77% of the associational, study groupings. Among intervention evaluations, 49% had sufficient data for population impact ratings, and only 28% qualified for a rating of “high population impact.” Moreover, only 15% of intervention evaluations had sufficient data to provide high-risk population impact ratings, and only 9% qualified for a rating of “high” for high-risk population impact.

Conclusions
This study employed ways to build on assessments of internal validity to rate effectiveness and to evaluate external validity to rate population impact, thereby helping to characterize and synthesize practice-based evidence. Among studies eligible to receive ratings, investigators noted significant variation in methods, measures, and reporting. Other studies failed to report on key elements required for assessing the internal or external validity of intervention effects and impacts, including those elements specified by the RE-AIM framework.

Implications for Practice and Policy
This work helps to accelerate the pipeline of evidence, moving from evaluability assessments to syntheses of effectiveness and impact to rigorous expert review systems. To increase real-time evidence review and dissemination efforts, researchers and evaluators have to agree on standardized indicators and reporting mechanisms in all peer-reviewed publications. This analysis identifies several indicators that can be incorporated consistently to improve review and reporting standards, thus enhancing the ability of evaluators to assess internal and external validity.  In response, these efforts can more systematically enhance the knowledge base and improve recommendations for practitioners and decision-makers interested in childhood obesity prevention in both the general population and in high-risk populations.

Support / Funding Source
Support for this study was provided by a series of grants from the Robert Wood Johnson Foundation (#63675, 65518, 67413).

Authors: 
Allison Kemner, MPH, Melissa Swank, MPH, & Laura Brennan, PhD, MPH
Location by State: 

Measuring Perceived Environments through Ecological Momentary Assessment: Correspondence with Objective GIS Indicators

Date: 
03/12/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Perceived neighborhood traffic and greenness are important variables that have been examined in prior research correlating the built environment with health-related behaviors such as walking and exercise. In general, vehicular traffic presents hazards to pedestrians that limit participation in physical activity and has been associated with poorer health in adults and children. Neighborhood greenness improves perceived aesthetics and access to natural shade encouraging individuals to engage in physical activity and subsequently better overall health in the population. Studies typically use retrospective survey methods to measure subjective perceptions of the neighborhood environment (e.g., Neighborhood Environment Walkability Survey [NEWS]). However, this approach may be prone to recall biases, condense perceptions of multiple micro settings into one overall neighborhood rating, and take into account parts of the neighborhood that are never or not regularly encountered. Ecological momentary assessment (EMA) provides an alternate way to measure the perceived environment by collecting real-time assessments of one’s immediate setting on mobile devices. However, an important first step to using EMA measures of the perceived environment is to examine the extent to which they correspond to objective measures of the built environment such as Geographic Information System (GIS) indicators

Objectives
The primary purpose of this study was to assess the convergent construct validity of EMA self-report of perceived traffic and greenness. To address this objective, the study analyzed EMA items measuring adults’ perceptions of nearby traffic, greenery, and shade. These items were compared respectively to objective measures of traffic (all vehicular collisions) and greenness (Normalized Difference Vegetation Index) near each participant’s place of residence.

Methods
The study sampled adults from the first two waves of data from an ongoing study investigating the effects of environmental and interpersonal factors on health behavior decision-making. The participants carried mobile devices (HTC Shadow) with a custom EMA application that prompted for surveys eight times a day for a period of four days per wave. Each wave was separated by six months. Participants were asked a random subset of questions from a larger survey in order to limit time spent taking the short assessment. One item rated the perceived level of traffic (“How much TRAFFIC is on the closest street to where you are right now?”) and two items rated the perceived level of greenery (“How many TREES AND PLANTS are there in the area where you are right now?” and “How much SHADE FROM THE SUN is there in the area where you are standing right now?). Using ArcGIS, a 3000 meter street network buffer was created around each subject’s place of residence to measure NDVI in 20XX and all collisions after the year 2006. Three multilevel regressions examined the validity of EMA-reported perceived traffic against GIS-derived vehicular collisions, EMA-reported perceived greenness variable against GIS-derived NDVI, and EMA-reported perceived shade variable against GIS-derived NDVI. Time (wave) was treated as a covariate in each equation.

Results
The final sample consisted of 43 individuals with a total of 165 observations after exclusions. Eighty-one percent of subjects were female and 35% of subjects reported being Hispanic, with ages ranging from 29 to 59. After adjusting for wave, the positive association between EMA-reported perceived greenness and NDVI was statistically significant, B=11.59, p=0.008. EMA-reported perceived traffic was positively associated with vehicular collisions after adjusting for wave, B=0.02, p=0.016. The positive association between EMA-reported perceived shade and NDVI was marginally significant after adjusting for wave, B=4.13, p=0.087.

Conclusions
Results from this study provide initial evidence of the construct validity of EMA-reported perceptions of neighborhood traffic and greenness. EMA-reported perceived greenness (i.e., trees or plants) corresponded with an objective measure of greenness (NDVI). Likewise, the EMA-reported variable for perceived traffic was validated against an object measure of traffic (i.e., vehicular collisions). The findings are consistent with prior research in children validating the EMA-reported variables against parent-reported retrospective traffic and aesthetics on the NEWS. However, there was only partial validation of the EMA-reported variable for shade against objective greenness. One explanation for this could be vagueness of the question. While shade from the sun often refers to trees and other natural shrubbery, there are many situations where shade could come from tents, tall buildings (such as during sunset or sunrise), or other manmade structures (e.g. parking garages). These findings offer support for the construct validity of EMA items measuring perceived greenness and traffic and suggest that the EMA-reported item measuring shade may not be necessary when attempting to measure greenness, although future studies could validate the shade measure against a real-time UV monitor.

Implications for Practice and Policy
By showing construct validity, these findings allow future practice and policy research to utilize EMA measures for perceived greenness and traffic, thereby eliminating major hurdles such as recall bias.  New studies will be able to show more conclusive findings on greenness and traffic by correlating perceived micro settings with health behaviors.

Support / Funding Source
American Cancer Society (118283-MRSGT-10-012-01-CPPB), the National Heart Lung and Blood Institute (R21HL108018 ), and the National Cancer Institute (R01CA123243).

Authors: 
Eldin Dzubur, MS, Yue Liao, MPH, Mary Ann Pentz, PhD, & Genevieve Dunton, PhD, MPH
Location by State: 
Study Type: 

Contribution of Streetscape Audits to Explanation of Physical Activity in Four Age Groups: Validity of the Microscale Audit of Pedestrian Streetscapes (MAPS)

Date: 
03/12/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Many built environment factors have been related to physical activity and walking behavior (Bauman et al., 2012), microscale features that affect people’s experience of the environment have been less studied. The Microscale Audit of Pedestrian Streetscapes (MAPS) tool was designed to measure features such as street design, transit stops, sidewalk qualities, street crossing amenities, social features and aesthetics.

Objectives
To examine associations of a wide range of microscale environmental attributes, using a reliable instrument and systematic scoring system (Millstein et al., 2013), with multiple physical activity measures, in four age groups.  The present study fills additional gaps by studying three regions of the US, presenting findings with and without adjustments for macro-level neighborhood walkability, and assessing individual microscale attributes and cumulative scores.  Microscale characteristics were expected to be significantly associated primarily with walking for transportation, and the cumulative scores were expected to be stronger correlates of walking for transport than any individual characteristic.

Methods
Objective microscale environmental data were collected as part of three studies examining the relation of neighborhood design to physical activity, nutrition behaviors, and weight status in children, adolescents, adults, and older adults.  These studies were conducted in urban and suburban neighborhoods in Seattle/King County, WA, San Diego, CA, and the Baltimore, MD-Washington, DC regions.  Neighborhoods were selected to vary on macro-environment features and median income, so present analyses represented a wide range of neighborhood built environment and sociodemographic characteristics.  Participants (n=3677) represented four age groups (children, adolescents, adults and older adults).  MAPS audits were conducted along a 0.25 mile route from participant homes toward the nearest non-residential destination (i.e., shops or services, a park, or a school).  A comprehensive scoring system (Millstein et al., 2013) was used to construct subscales and overall summary scores for each section of MAPS: route, intersections, segments, and cul-de-sacs.  Walking/biking for transportation and leisure/neighborhood physical activity were measured with age-appropriate surveys (ActiveWhere, GPAQ, CHAMPS).  Objective physical activity was measured with accelerometers.  Mixed linear regression analyses were performed to assess the effect of MAPS scores on multiple physical activity outcomes for each age group, adjusting for all covariates as fixed effects and participant clustering in census block groups as a random effect.  All models were run with and without adjusting for macro-level GIS-defined walkability (high/low).

Results
There were many significant associations across all age groups after adjusting for macro-level walkability (51.2%, 22.1% and 15.7% of MAPS scores were significantly associated with walking/biking for transport, leisure/neighborhood physical activity, and objectively-measured MVPA, respectively).  Destinations and land use, streetscape, segment, and intersection variables were mainly related to transport walking/biking. Aesthetic variables were related to leisure/neighborhood physical activity.  The overall summary score was related to total MVPA in children and older adults.  Cul-de-sacs were related to neighborhood physical activity in children and adolescents.  In general, the strongest associations were seen with the MAPS summary scores.

Conclusions
The value of using observational measures of streetscapes was demonstrated by many findings that MAPS variables significantly explained physical activity among four age groups, adjusting for macro-level walkability.  The pattern of findings suggests that many modifiable built environment attributes are related to physical activity.  Environment-physical activity associations were specific to domain, consistent with hypotheses and previous research. The present study provides substantial evidence that microscale features independently explain physical activity, especially active transportation, adjusting for walkability. The importance of these findings is that microscale features like sidewalk quality, street crossing aids, and aesthetic variables are feasible and affordable to change.  Given that the strongest associations were with MAPS summary scores, physical activity behavior is more likely to be influenced by the cumulative impact of numerous environmental attributes than by a few critical variables.

Implications for Practice and Policy
Present findings provide strong evidence that microscale environment attributes are related to physical activity patterns across age groups, and these associations are independent of macro-level walkability.  The pattern of findings is consistent with an interpretation that the cumulative effect of numerous attributes is the likely mechanism of effect.  Using instruments like MAPS can help identify built environment changes that can be achieved at a reasonable cost and in a feasible time frame with a likelihood of improving physical activity.

References

  1. Bauman, A.E., Reis, R.S., Sallis, J.F., Wells, J.C., Loos, R.J.F., & Martin, B.W. on behalf of the Lancet Physical Activity Series Working Group. (2012). Correlates of physical activity: Why are some people physically active and others not? The Lancet, 380, 258-271.
  2. Millstein, R.A., Cain, K.L., Sallis, J.F., Conway, T.L., Geremia, C., Frank, L.D., Chapman, J., Van Dyck, D., Dipzinski, L., Kerr, J., Glanz, K., Saelens, B.E. (2013). Development, scoring, and reliability of the Microscale Audit of Pedestrian Streetscapes (MAPS). BMC Public Health, 13, 403.

 

Support / Funding Source
NIH grants RO1 ES014240, RO1 HL083454, and RO1 HL077141.

Authors: 
Rachel Millstein, MHS, MS, Kelli Cain, MA, James Sallis, PhD, Terry Conway, PhD, Kavita Gavand, MS, Lawrence Frank, PhD, Brian Saelens, PhD, James Chapman, MS, Marc Adams, PhD, Karen Glanz, PhD, & Abby King, PhD
Location by State: 

Spatial Profiling: A Latent Profile Analysis of Obesogenic Activity Spaces and Adult BMI

Date: 
03/12/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
In spite of progress on the issue, obesity remains among the most challenging health issues of our time.  Features of the built environment can contribute to obesity by increasing the real or opportunity costs of healthy food choices and physical activity.  The term “obesogenic environment” describes geographic areas that promote obesity across multiple domains—too much fast food, not enough fresh food, and not enough support for physical activity (1).  However, the effect of obesogenic environments on the actual weight status of those exposed to them has not been conclusively established.   Most research has focused on either single objective built environment indicators, subjective ratings of walkability, and/or conventional residential buffers to characterize neighborhood-level risk. In this study, we used multiple objective GIS measures to generate latent profiles of neighborhood risk, with neighborhood defined activity spaces rather than residences.

Objectives
Using a sample of 460 adults in Southern California, we sought to discover a typology of obesogenic risk in the built environment, and determine whether these categories of places predicted physical activity and weight status.

Methods
We used Wave 1 data from 460 adult respondents in two control groups from Healthy PLACES, a natural experiment which has the overarching goal of examining the effects of “smart growth” community design principles on obesity outcomes.  Study participants had at least one school-aged child who also participated in the study.  We used 7 measures of the built environment derived from a GIS: vegetation index, residential/commercial land use mix, fast food restaurants, parks, street connectivity, and traffic accidents involving pedestrians or cyclists.  To define neighborhood of likely exposure, we created stadium-shaped 1-mile buffers around the line connecting adults’ homes and the school at which their child is enrolled.  Since most adults spend a large amount of their time outside the immediate vicinity of home, but within a few miles of it (2), we took these buffers as a proxy for the local geography to which the study participants are likely to be exposed on a regular basis.  We also used self-reported data on age, gender, and educational attainment; anthropometric measures; and physical activity collected using an accelerometer over a 7-day study period.

Analysis proceeded in two phases.  Our first analytic step was to enter the set of 7 continuous area measures into a latent profile analysis.  A latent variable modeling approach can be used to identify unobserved subgroups among a set of continuous characteristics, in this case, characteristics of the built environment that have been linked to obesity.

In the second stage of analysis, we entered the categories of neighborhood identified in the first step as independent variables in a regression model.  Our outcomes in separate models were moderate-to-vigorous physical activity (MVPA) measured by accelerometer, body mass index (BMI), and waist circumference.  Final models were adjusted for age, gender, and educational level, an indicator of socioeconomic status.

Results
Latent profile analysis identified four distinct unobserved environmental profiles.  We expected neighborhoods classified as Profile 2 to be the most obesogenic, with low greenness, high proportion commercial land use, and the highest rate of pedestrian and bike accidents.  Neighborhoods fitting in Profile 3 seemed the least obesogenic, with high greenness, low proportion commercial, low pedestrian and bike accidents, and moderate street connectivity.  Bivariate analysis confirmed that participants in Profile 2 had the highest weight status and lowest MVPA; and those exposed to Profile 3 had the healthiest weight status and highest MVPA.  These differences were significant.

Membership in a Profile 3 neighborhood was significantly associated with lower BMI and nearly 20 minutes per day of additional MVPA, compared to membership in a Profile 2 context.  However, the results did not remain significant after adjusting for gender, age, and education.

Conclusions
Our primary aims were to find latent profiles of built environment obesity risk factors, and test whether these profiles were associated with increased risk for obesity.  Using LPA, we identified four distinct profiles of neighborhood obesogenic risk.  Furthermore, these context types were marginally predictive of obesity and physical activity among the adults who experienced them.  Our results suggest that latent profile analysis can uncover latent clusters of risk factors for obesity in the built environment.  Our results also suggest that the experience of built environment as a factor in obesity is complex and multidimensional.  Further research should focus on the interrelationships between many environmental exposure factors, and the possibility that they interact with one another.

Implications for Practice and Policy
As we work to change the obesity risk environment, we should consider that environments are multifactorial.  Strategic small changes in more than one dimension of the built environment may be able to shift the overall obesogenic profile of an area.  Also, we should be mindful of the fact that people do not spend all of their time at home; they experience a range of places and may self-select environments based on their own priorities.

References

  1. Saelens BE, Sallis JF, Frank LD, Couch SC, Zhou C, Colburn T, et al. Obesogenic neighborhood environments, child and parent obesity: the Neighborhood Impact on Kids study. Am J Prev Med 2012;42(5):e57-64.
  2. Jones M, Pebley AR. Redefining Neighborhoods Using Common Destinations: Social Characteristics of Activity Spaces and Home Census Tracts Compared. In press, Demography 2013.

 

Support / Funding Source
This research was supported by the National Cancer Institute (Grant T32CA009492-280).

Authors: 
Malia Jones, MPH, PhD, Jimi Huh, PhD, Donna Spruijt-Metz, MFA, PhD, Genevieve Dunton, MPH, PhD, & Mary Ann Pentz, PhD
Location by State: 
Study Type: 

Accountable Care Organizations, Physicians, and Private-Public Partnerships for Active Design

Date: 
03/12/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
How can the Affordable Care Act benefit the neighborhood built environment? Accountable care organizations (ACO’s), a relatively new model of healthcare delivery, may be a critical component to the multidisciplinary partnerships necessary to build healthy communities. The model, which rewards doctors and hospitals for health maintenance rather than health care provision, is a logical outgrowth of health reform measures designed to improve patient outcomes and reduce costs. In the wake of the new law, as health care systems reinvent themselves to maintain viability and profitability, ACOs will continue to proliferate across the nation, presenting a timely opportunity for organizations looking to move active living research into built realities.

As defined by a task force of the American Academy of Family Physicians, an ACO is “a primary care-based collaboration of health care professionals and health care facilities that accept joint responsibility and accountability for the quality and cost of care provided to a defined patient population.” They are a relatively new phenomenon; currently ACOs now number more than 400, but cover four million Medicare enrollees and millions more people with private insurance.

Because ACO profits will be tied to keeping their patient population healthy, and recruiting health-minded patients to select their ACO, these healthcare organizations are expected to play increasingly active roles in promoting community health by aligning with public health, local government community development departments and community-based organizations(CBO. Armed with new growing empirical evidence on the relationship between the built environment and preventative health behavior, ACO’s can potentially help fund and direct neighborhood health programs such as tree planting initiatives, retrofitting parks with walking paths, or sponsoring farmers’ markets. ACO’s can also influence community and regional health by providing grant match dollars needed for transportation projects to improve transit access, close sidewalk gaps and advance complete streets. Supporting this type of neighborhood, community and regional development can further improve health, supports the work of physicians in encouraging consumers to increase physical activity, and reduces the need for costly medical care.

Description
This research collaboration which includes professionals and researchers at Sutter Eden Medical Center, Kaiser Permanente, and Design 4 Active Sacramento (D4AS), a community-based organization and advisory council in Sacramento, California, discusses the nature and growth of ACO’s in the wake of the Affordable Care Act, and its potential for active living initiatives. Using our current work in Sacramento as a case study, we outline how we have already established partnerships between public health, local government, and community based organizations to fund and implement interventions in the built environment.

Lessons Learned
D4AS has already begun the process of implementing active design guidelines and programs such as improved access to transit, complete streets initiatives, sidewalk gaps closures, and a Safe Routes to School initiative. We discuss how they have leveraged these guidelines and programs into existing infrastructure and new development projects by strategically reaching out to other agencies and organizations and focusing on the monetary benefits of active design, from attaching “price tags” to and quantifying benefits of these programs for outside investment, to finding and structuring federal grant match programs.

Conclusions and Implications
By examining both the challenges and potential in healthcare provider partnerships and quantifying costs and benefits of active design implementation, we aim to lead a practical discussion on beginning to translate the vast research on active living into realized projects in a new era of healthcare healthcare delivery.

Next Steps
We outline our current and future efforts in integrating healthcare providers, with a specific focus on ACO’s, in the wake of the Affordable Care Act.

References

  1. Lowery, A. (2013, April 24). A Health Provider Strives to Keep Hospital Beds Empty. New York Times, p. A1.
  2. Bovbjerg, R. R., Ormond, B. A., & Waidmann, T. A. (2011). What Directions for Public Health under the Affordable Care Act? Urban Institute Health Policy Center.
  3. Rittenhouse DR, Shortell SM, Fischer ES. Primary care and accountable care – two essential elements of delivery-system reform. N Engl J Med 2009; 361(24): 2301-2303.
  4. Shortell, S. M. (2013). Bridging the Divide Between Health and Health. JAMA, 309(11), 1121-1122.

 

Support / Funding Source
The Design 4 Active Sacramento team was one of 20 teams nationwide chosen this year by the US Centers for Disease Control to participate in the National Leadership Academy for the Public’s Health.

Authors: 
Sara Carr, MArch, MLA, Edie Zusman, MD, FACS, FAANS, MBA, & Judy Robinson
Location by State: 
Population: 

Examining Local Land Use Policies that May Affect Active Living among School Students

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Policy makers and researchers have been examining ways to solve the youth obesity epidemic. One area of interest has focused on the adoption of local policies related to the built environment to promote physical activity.  The Task Force on Community Preventative Services recommends using community and street-scale design and land use policies to promote physical activity.1 Through its zoning and land development laws, a local government can regulate the location of park and recreation facilities, open space, trails, and other facilities that promote physical activity; regulate land use patterns (e.g. mixed use districts); and specify structural requirements such as sidewalks or bike lanes.

Objectives
This presentation will examine the extent to which youth reside in communities with local land development policies that address infrastructure-related features or improvements that would facilitate active living.

Methods
Data were compiled in 2011 from zoning ordinances and related policies obtained from 378 local governments (county, municipal, town/township) surrounding 154 secondary school catchments where a national sample of secondary school students were enrolled as part of the Bridging the Gap Community Obesity Measures Project (BTG-COMP).  Hard and electronic copies of the zoning codes and related policies for each jurisdiction were obtained and were independently reviewed and evaluated by trained policy analysts using the BTG-COMP Built Environment Local Zoning/Policy Audit Tool that seeks to assess the extent to which policies addressed active living. The Tool specifically captures the extent to which policies address any marker that would promote walking and biking (e.g., sidewalks), crosswalks, bike lanes, bike parking, trails/paths, mixed use, bike/pedestrian or street connectivity, active recreation (e.g. playgrounds, athletic fields, recreation facilities, etc.), passive recreation (e.g. open space, parks, etc.), and Complete Streets/Context Sensitive Design (CSD) policies.  The Tool also captures the strength and if applicable the type of use (permitted, conditional, accessory) related to each marker.

Each marker was weighted by the proportion of the youth (0-17) population in a given catchment area that resided in each jurisdiction sampled as a proxy for neighborhood school enrollment zones. Youth population estimates were derived from the American Community Survey 2007-2011 5-year file by multiplying each jurisdiction’s youth population density by the area in square miles that the jurisdiction overlapped its catchment. The proportion of the catchment youth population in a given jurisdiction was the resulting weight value. These measures were then aggregated to the catchment level. Thus, the weighted policy markers reflect the estimated proportion of the catchment’s youth population living in an area that addressed the active living markers of interest (e.g., bike lanes) as well as the strength and type of use variables. The catchment-level variables ranged from 0-1, with 0 meaning that no youth in the catchment were exposed to a given a policy provision and a score of 1 indicating that all of the youth in the catchment were exposed to a given policy. Data for this presentation were based on summary statistics examining the extent to which each of the active living policy markers were addressed and whether they were required and/or permitted uses.

Results
Most youth lived in catchments with zoning and land use policies that addressed passive recreation (89%), walking or biking infrastructure improvements (88%), active recreation (87%), mixed use (75%), or trails/paths/greenways (70%) (see Figure 1).  However, youth were least likely to reside in catchments with zoning and land use policies that addressed bike lanes (30%) or an officially adopted Complete Streets or CSD policy (12%). Required provisions or permitted use-type provisions also varied as youth were more likely to reside in catchments with policies containing provisions that required or allowed walking/biking-related infrastructure improvements (78%), passive recreation (85%), or active recreation (83%), and were less likely to require or allow policies related to crosswalks (18%), bike lanes (8%), or Complete Streets or CSD (7%).

Conclusions
Although many local governments include active-living oriented provisions in their land use policies, data from this study suggests that some provisions are more prevalent than others.  Policies were more likely to address items related to walking and biking, mixed use, and active and passive recreation than they were to address bike lanes or to contain Complete Streets or CSD provisions.

Implications for Practice and Policy
Local governments should review their existing land use policies and modify them to address infrastructure improvements or regulate land use patterns that could be to facilitate active living. Local governments should specifically require structural improvements, such as sidewalks or open space, to ensure active living opportunities.

References

Heath GW, Brownson RC, Kruger J, et al. The effectiveness of urban design and land use and transportation policies and practices to increase physical activity: a systematic review. J Phys Act Health. 2006;3(Suppl 1):S55-S76.

Support / Funding Source
Robert Wood Johnson Foundation Bridging the Gap Research Program.

Authors: 
Emily Thrun, MUPP, Jamie Chriqui, PhD, MHS, Christopher Quinn, MS, Sandy Slater, PhD, Dianne Barker, MHS, & Frank Chaloupka, PhD
Location by State: 
Study Type: 

The Impact of a Signalized Crosswalk on Crossing Behaviors in a Low-Income Minority Neighborhood

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Communities with predominantly low-income and minority populations are effected by the highest levels of sedentary behavior and obesity (Day, 2006). These underserved communities often have limited access to parks and active transportation resultant of high-speed, high-volume streets and an outdated built environment. While studies suggest that sidewalks, crosswalks, and traffic calming measures can increase pedestrian safety (Pucher & Dijkstra, 2003) few studies have evaluated pedestrian crossing behaviors as a result of infrastructure changes. In 2012-2013, the completion of a signalized crosswalk and landscaped median linking low-income housing with a public park provided a natural experiment to examine the effect of an infrastructure project upon active living behaviors.

Objectives
The purpose of this study was to examine the effect of changes to the built environment to determine whether street crossing infrastructure modifications change pedestrian crossing behaviors or traffic patterns in a low-income and predominately racial/ethnic minority community.

Methods
Data collection occurred at one Intervention site (Providence Road) and one Control site (College Avenue) in Columbia, MO. We selected the Control site by examining relevant characteristics of the neighborhood (e.g., size, income level), and the corresponding street (e.g., number of lanes, typical traffic volumes/speeds, pedestrian crossing facilities). Street crossing behaviors were collected using direct observation and assessed the mode of transportation, legality of the crossing (e.g., at intersections/crosswalks or not), as well as race/ethnicity, gender, and age within 5-6 zones at both sites. Magnetic traffic detectors were also embedded in both the Intervention and Control streets during the data collection to capture traffic volume and speed. Data collection ran concurrently at both sites for seven days (Monday-Sunday) over the same two-week period in June 2012 (pre-intervention) and June 2013 (post-intervention), crossing behaviors were recorded for three hours each day (7:30am, 12:30pm, and 3:30pm) while traffic data were collected continuously for 168 hours during the first week.

Descriptive statistics were calculated for all variables. Independent samples t-tests assessed overall changes in pedestrian crossings and traffic volume at each site from 2012 to 2013. Changes in legal/illegal crossings and traffic speed (above the speed limit/below the speed limit) at each site from 2012 to 2013 were analyzed using Pearson’s Chi Square.

Results
Total pedestrian crossings at the Intervention site (Providence Road) increased from 1,464 in 2012 to 1,658 in 2013 (p<0.001). Between 2012 and 2013, the number of legal crossings at the Intervention site increased from 553 (38%) to 795 (48%) (p<0.001). In both years, the majority of observations were pedestrians (1,099 [75%], 2012; 1,316 [79%], 2013) followed by bicyclists (332 [23%], 2012; 310 [19%], 2013). Amongst children and teens, legal crossings rose from 45(25%) to 94(61%) and from 90(23%) to 169(41%), respectively between 2012 and 2013 (both: p<0.001). In addition, total traffic volume at the Intervention site fell slightly from 148,857 vehicles in 2012 to 148,508 in 2013 (p=0.01). Motor vehicles that were traveling above the speed limit of 35 mph decreased from 67,922(46%) in 2012 to 51,339(35%) in 2013 (p<0.001).

There was no change in the number of total pedestrian crossings at the Control site (College Avenue) from 2012 (4,385) to 2013 (4,485) (p=0.90). Legal crossings increased at the Control site, but only by 2% (2,341 [53%] in 2012 to 2,507 [55%] in 2013) (p=0.01).  Similar to the Intervention site, pedestrians were most commonly observed (3712 [85%], 2012; 3890 [87%], 2013), followed by bicyclists (640[15%], 2012; 549[12%], 2013). Amongst children, the small number of legal crossings did not significantly change (10 [77%], 2012; 18 [95%], 2013) (p=0.135) but for teens changed from 497(39%) to 162(55%) (p<0.001), respectively between 2012 and 2013. As with the Intervention site, total traffic volume at the Control site fell from 132,428 in 2012 to 124,635 in 2013 (p<0.001). However, motor vehicles that were traveling above the speed limit of 35 mph increased from 64,310 (49%) in 2012 to 73,552 (59%) in 2013 (p<0.001).

Conclusions
The replacement of an unsafe pedestrian bridge with an at-grade, signalized pedestrian crosswalk and landscaped median significantly impacted both pedestrian crossing behaviors and vehicular traffic behaviors. Specifically, the installation of the pedestrian crosswalk yielded reduced proportions of illegal crossings (especially among children), and reduced the percentage of vehicles speeding on the highway through the neighborhood at the Intervention site while the percentage of vehicles speeding at the Control site increased. This study suggests that street crossing infrastructure changes do change behavior, which will help inform future street crossing interventions and may be used to guide policies promoting physical activity in similar communities where high-speed arterials are barriers to parks and active living.

Implications for Practice and Policy
By demonstrating increased pedestrian safety and traffic calming, this study adds support to the feasibility of advocacy efforts to reverse transportation practices that favor automobiles at the expense of pedestrian accessibility. These successful outcomes could be used to support advocacy efforts seeking to modify the built environment to increase physical activity in underserved neighborhoods.

References

  1. Day, K. (2006). Active living and social justice: Planning for physical activity in low-income, Black, and Latino communities. Journal of the American Planning Association, 72(1), 88-99.
  2. Pucher, J., & Dijkstra, L. (2003). Promoting safe walking and cycling to improve public health; Lessons from the Netherlands and Germany. American journal of public health, 93(9), 1509-1516.

 

Support / Funding Source
University of Missouri Research Board Grant.

Authors: 
Courtney Schultz, BS, Sonja Wilhelm Stanis, PhD, Ian Thomas, PhD, & Stephen Sayers, PhD
Location by State: 

Correlates of Walking for Transportation and Public Transportation Use among St. Louis Adults

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Walking for transportation, which can include walking that takes place at the beginning or end of a trip taken by public transportation, can provide individuals with the opportunity to meet recommended levels of physical activity. Previous studies have demonstrated that individuals who walk to and from public transportation stops engage in more daily physical activity than those who do not.[1-5] More evidence is needed, however, to better understand the relationship between walking for transportation and public transportation use and more specifically, the mechanisms through which this relationship occurs.[5] A growing body of evidence has also suggested that perceptions of built environment characteristics can influence walking for transportation.[6-8] Despite this evidence, little is known about how these perceived environmental factors influence public transportation use.

Objectives
The aims of this study were to: (1) further assess the relationship between individual factors, public transportation use, and walking for transportation, specifically in a low-income community of color; and (2) examine the association among individual and perceived environmental factors and public transportation use.

Methods
This cross-sectional study was conducted in 2012. We used questionnaire data from 772 adults living in St. Louis, Missouri. We used the International Physical Activity Questionnaire long form to assess walking for transportation and public transportation use. The abbreviated Neighborhood Environment Walkability Scale was used to examine perceptions of the environment. Two different models were tested using multinomial logistic regression with walking for transportation and public transportation use as the outcome variables. Model 1 examined the association between individual factors and public transportation use with walking for transportation. Model 2 examined the association between individual and perceived environmental factors with public transportation use.

Results
Most participants were women and adults less than 50 years old. The majority of the sample was employed outside of the home and 27% had an annual income less than $10,000.

Multinomial logistic regression analyses revealed that the odds of walking for transportation for 1-149 minutes/previous week and =150 minutes/previous week (OR=2.11, CI=1.31-3.40 and OR=2.08, CI=1.27-3.42, respectively) were higher for individuals who reported using public transportation 1-4 days in the previous week in comparison to individuals who did not use public transportation. Similarly, the use of public transportation for five or more days in the previous week was positively related to walking for transportation. Compared to individuals who did not use public transportation, individuals who used public transportation for five or more days in the previous week were 3.47 times more likely to walk for transportation for 1-149 minutes/previous week and 8.61 times more likely to walk for transportation for more than 150 minutes/previous week (CI=1.47-8.19 and CI=3.87-19.20, respectively).

Model 2 revealed that the odds of using public transportation more than once a week (1-4 days/previous week) was greater among individuals between 50-59 years old (OR=1.98, CI=1.06-3.70) in comparison to individuals between 18-29 years old. However, adults over 60 years old were less likely to use public transportation five or more days in the previous week (OR=.34, CI=.14-.86) compared to individuals between 18-29 years old. Employed individuals were less likely than unemployed individuals to use public transportation more than once a week (1-4 days/previous week: OR=.56, CI=.35-.92).

Participants who reported high traffic speed and high crime in their neighborhood were less likely to use public transportation. More specifically, individuals who reported that traffic exceeded the posted speed limits in their neighborhood were less likely to use public transportation for 1-4 days in the previous week (OR=.54, CI=.36-.81) compared to those who did not report high traffic speed in their neighborhood. Similarly, individuals who perceived high crime in their neighborhood had lower odds of using public transportation for more than five days in the previous week (OR=.50, CI=.28-.87) compared to those who did not report high crime.

Conclusions
Using a diverse sample of adults where many participants were unemployed and used public transportation as their primary mode of transport, we found that individuals that use public transportation more frequently are more likely to meet physical activity recommendations by walking for transportation. Our study results are consistent with earlier research demonstrating that regular public transportation use is associated with increased physical activity and that walking for transportation appears to occur in combination with public transportation.[1-5] Of the perceived environmental factors assessed, our study results indicated that high traffic speed and high neighborhood crime were negatively associated with public transportation use. To our knowledge, no studies to date have investigated the relationship between perceived built environment attributes and public transportation use.

Implications for Practice and Policy
Programs, policies, and infrastructure changes to improve the perception and actual safety from traffic and crime may be an important investment to increase public transportation use in similar urban communities, and thereby increase levels of walking.

References

  1. Besser LM, Dannenberg AL, 2005. Walking to public transit: steps to help meet physical activity recommendations. Am J Prev Med 29: 273-280.
  2. Frank LD, Greenwald MJ, Winkelman S, Chapman J, Kavage S, 2010. Carbonless footprints: promoting health and climate stabilization through active transportation. Prev Med 50: S99-105.
  3. Freeland AL, Banerjee SN, Dannenberg AL, Wendel AM, 2013. Walking associated with public transit: moving toward increased physical activity in the United States. Am J Public Health 103: 536-542.
  4. Lachapelle U, Frank L, Saelens BE, Sallis JF, Conway TL, 2011. Commuting by public transit and physical activity: where you live, where you work, and how you get there. J Phys Act Health 8: S72-82.
  5. Wener RE, Evans GW, 2007. A morning stroll: levels of physical activity in car and mass transit commuting. Environ Behav 39: 62-74.
  6. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW, 2012. Correlates of physical activity: why are some people physically active and others not? Lancet 380: 258-271.
  7. Duncan MJ, Spence JC, Mummery WK, 2005. Perceived environment and physical activity: a meta-analysis of selected environmental characteristics. Int J Behav Nutr Phys Act 2: 11.
  8. Van Dyck D, Cerin E, Conway TL, De Bourdeaudhuij I, Owen N, Kerr J, Cadon G, Frank LD, Saelens BE, Sallis JF, 2012. Perceived neighborhood environmental attributes associated with adults’ transport-related walking and cycling: Findings from the USA, Australia, and Belgium. Int J Behav Nutr Phys Act 9: 70.

 

Support / Funding Source
This study was supported by the International Center for Advanced Renewable Energy and Sustainability at Washington University in St. Louis, Missouri (1660-94758A) and the John Hopkins Global Center on Childhood Obesity (2001656847).

Authors: 
Marissa Zwald, MPH, Aaron Hipp, PhD, Marui Corseuil, MPH, & Elizabeth Dodson, PhD, MPH
Location by State: 
Study Type: 

Multimodality and Active Living: Connectivity of the Bus Rapid Transit with Pedestrian and Bicycle Facilities

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Multimodal connectivity refers to the movement of people that involves two or more modes of transport in a single journey. Several studies highlight the importance of multimodal travel approach to meet con¬temporary mobility challenges, such as the need to achieve socioeconomic equity or to reduce environmental impacts associated with urban transportation (Fábio and Fernando 2012). A Bus Rapid Transit (BRT) system can achieve significantly greater CO2 reductions and encourage active lifestyles if it is planned and implemented with a multimodal approach, integrating walking, bicycling, and car (Vincent and Jerram 2006; Litman 2012). Thus, the focus of this research is to analyze the current transportation infrastructure around stations of a BRT, the Metro Orange Line of San Fernando Valley in Los Angeles and to examine if it is designed to promote multimodality. We observe whether the infrastructure connects pedestrians, cyclists, taxis and car users to each station in a way that encourages multimodal transportation.

Objectives
The aim of this research is to investigate whether, and how, the Orange Line in San Fernando Valley has infrastructure to support a multimodal use of the system. A detailed analysis of pedestrian, bicycle, and auto links to the Orange Line was performed in April and May 2013. Based on the results, some recommendations are presented for enhancing the multimodal connectivity of the BRT for a maximum travel experience.

Methods
The study is based on a structured field observation of the Orange Line’s eighteen stations to determine whether they were, or could be, integrated with other means of transportation. Eighteen field evaluation cards were prepared for all the stations. A card includes evaluation criteria for various modes supposedly to be connected to the Orange Line. For integration with the pedestrian mode, the existence of a crosswalk near the station and the quality of the sidewalks within a 350ft radius of the terminal were considered. To analyze the condition of a sidewalk, its width (a good sidewalk being deemed to have a minimum of 4ft width) and the quality of its surface were examined. Terminal accessibility for people with disabilities was also monitored. For bicycles, the presence of bicycle lanes or paths leading to the stops or the vicinity of the terminal was evaluated, as well as availability of bicycle parking. For privately owned cars, the number of parking slots and the presence of park and ride facilities were examined. Once the field data was gathered and compiled, a statistical and spatial analysis was made using statistical software and Geographical Information Systems (GIS) to create a multimodal connectivity index for each station. The index then will be correlated to the socio-demographic and economic background of the area where the station rests.

Results
The calculated Multimodality Index (MI) is adequately differentiated to provide analytical insight. The three stations with the lowest MI were De Soto, Woodman, Valley College and Lauren Canyon. Two of these stations, De Soto and Valley College, are located by the Valley’s two major community colleges. Improved multimodal connectivity to the BRT might increase student use of the Orange Line. One sub-index of the MI, the sidewalk rating, averaged 3.64 (out of 5). The stations with the highest rated sidewalks are Warner Center and Sepulveda, with ratings above 4.5. The stations with the lowest sidewalk ratings are De Soto, Valley College, and Woodman, with ratings below 2.8. Other sub-indices such as the availability of bicycling facilities, parking lots, kiss-n-ride opportunities and facilities for disabilities indicates that some stations need significant improvements to encourage a multimodal travel experience for  BRT users.

Conclusions
The current transportation infrastructure of the Metro Orange Line does not fully promote multimodal connectivity. Increasing multimodal access to each Metro station promotes active transportation in the San Fernando Valley. Pedestrians and cyclists are the primary target because they use healthy, non-motorized modes to access the Orange Line. With regard to private cars, improved connectivity with BRT provides apparent environmental benefits, and can provide some social, and public health advantages.

Implications for Practice and Policy
The proposed research has empirical, conceptual and methodological contributions such as measuring the extent of multimodality of Bus Rapid Transit systems. The application of the analysis method introduced in this study is not limited to the Orange Line but it can be extended to the analysis of any BRT system. Besides, the results of this study would serve as indicator as to whether there is a lack of multimodality for different stations of the Bus Rapid Transit, so the empirical findings of this research will also have important implications for local transit planning.

References

  1. Fábio D., and R. Fernando. 2012. Intermodal Connectivity to BRT: A Comparative Analysis of Bogotá and Curitiba. Journal of Public Transportation, Vol. 15, No. 2, pp. 1-18.
  2. Vincent, W., and L. Jerram. 2006. The Potential for Bus Rapid Transit to Reduce Transportation-related CO2 Emissions. Journal of Public Transportation, BRT Special Edition: pp. 219–237.
  3. Litman, T. 2012. Introduction to Multi-Modal Transportation Planning: Principles and Practices, Victoria Transport Policy Institute

 

Support / Funding Source
This study is supported by a Research Grant from the College of Social and Behavioral Sciences (CSBS), California State University Northridge (CSUN).

 

Authors: 
Mintesnot Woldeamanuel, PhD & Craig Olwert, PhD
Location by State: 

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