Category Archives: risk factor

Learning from Bologna’s off-street bicycle network: tolerance, safety, thanks |

At, I have the following post: Learning from Bologna’s Off-street Bicycle Network: Tolerance, Safety, Thanks, complete with a vivid three minute video from the user perspective of the cyclist.

“The characteristics of a city’s off-street cycling network vary widely by culture. Expectations are adjusted accordingly. The most progressive cycling communities in the U.S. have set  high standards for what they consider to be suitable bicycle facilities…”

Minneapolis bike crash report

Bicyclist-Motorist Crash RateMinneapolis recently released a new report examining bicycle crashes. It is based off of 10+ years of DPS crash data which is pretty limited to begin with. I am pretty sure there is not much new in this report that we did not uncover back in 2006 or 2007 with our analysis of the same data; but, that was not commissioned in-house by Public Works and it was not done by Public Works. So, it is more important for them to be able to listen to themselves.

The Atlantic Cities article covers some popular press elements of the descriptive stats. They claim to see, again, an attribution of or mention of safety in numbers, directionality, and causality. But, as has been pointed out by others, there little to suggest we have anything here other than more people riding and crash rates staying level.

What really is needed is to figure out how to use the count data to uncover more reliable and geographic measures of exposure.

Health tradeoffs (some of them) hitting popular press

The Atlantic Cities has a diddy exposing some of the pollution ill-effects of cycling. But, the larger question is still left open. Even considering the air pollution burden from cycling–and perhaps even the safety risks owing to crashes–is it healthy? We need to look at the larger context. The prevailing evidence, I would argue, suggests that cycling is healthy–overall–because of the physical activity benefits.

Health benefits of switching to transport and bikes

Some of the most robust research, internationally, of the health benefits derived from switching car use to other modes is coming out of the Centre for Research in Environmental Epidemiology (CREAL) in Barcelona. They have looked at the impacts of Barcelona’s bike-sharing system in the past. Their latest work is more generally about the benefits of public transport and bike. Yes, they are working with future scenarios. Yes, there are lots of assumptions embedded. But the framework and the identification of key outcomes and specific measures is good to see.

Cover imageReplacing car trips by increasing bike and public transport in the
greater Barcelona metropolitan area: A health impact assessment study
Environment International
Volume 49, 15 November 2012, Pages 100–109
Rojas et al.


Estimate the health risks and benefits of mode shifts from car to cycling and public transport in the metropolitan area of Barcelona,Spain.
We conducted a health impact assessment (HIA), creating 8 different scenarios on the replacement of short and long car trips, by public transport or/and bike. The primary outcome measure was all-cause
mortality and change in life expectancy related to two different assessments: A) the exposure of travellers to physical activity, air pollution to particulate matter < 2.5 μm (PM2.5), and road traffic fatality; and B) the exposure of general population to PM2.5, modelling by Barcelona Air-Dispersion Model. The secondary outcome was a change in emissions of carbon dioxide.
The annual health impact of a shift of 40% of the car trips, starting and ending in Barcelona City, to cycling (n = 141,690) would be for the travellers who shift modes 1.15 additional deaths from air pollution, 0.17 additional deaths from road traffic fatality and 67.46 deaths avoided from physical activity resulting in a total of 66.12 deaths avoided. Fewer deaths would be avoided annually if half of the replaced trips were shifted to public transport (43.76 deaths). The annual health impact in the Barcelona City general population (n = 1,630,494) of the 40% reduction in car trips would be 10.03 deaths avoided due to the reduction of 0.64% in exposure to PM2.5. The deaths (including travellers and general population) avoided in Barcelona City therefore would be 76.15 annually. Further health benefits would
be obtained with a shift of 40% of the car trips from the Greater Barcelona Metropolitan which either start or end in Barcelona City to public transport (40.15 deaths avoided) or public transport and
cycling (98.50 deaths avoided).The carbon dioxide reduction for shifting from car to other modes of transport (bike and public transport) in Barcelona metropolitan area was estimated to be 203,251
t/CO2 emissions per year.

Interventions to reduce car use and increase cycling and the use of public transport in metropolitan areas, like Barcelona, can produce health benefits for travellers and for the general population of the
city. Also these interventions help to reduce green house gas emissions.

  • We assess the health impacts of replacing car trips by bicycle or public transport.
  • Replacement of the car trips reduces mortality in travellers who shift the mode.
  • Replacement of the car trips also reduces mortality in residents of urban areas.
  • Replacement of car trips can reduce the emissions of CO2.

Mineta report on promoting bicycle safety

The research reports keep coming in. Here is another one with lots of secondary data and sources, prepared in a manner that crosses between advocacy and research, and is pretty accessible. The focus in the title suggests safety but it is a bit broader in its coverage. Warning: it is a big long. 

Just released: The Mineta Transportation Institute recently published a report that leverages literature review and case studies in the San Francisco Bay area and Portland OR to recommend ways to improve safety for bicycle commuters. Promoting Bicycle Commuter Safety includes chapters on risks, application of social psychology to bike safety, dimensions of effective practices, and more. The report also includes illustrative tables and photos. Principal investigator was Asbjorn Osland, PhD, with several chapter contributors. The 157-page report is available for free PDF download from  

Robustly testing the effect of bicycle network quality

Most are familiar with the “go to” studies pointing to correlations between the quantity of bicycle facilities and use[1]. These are certainly a good starting point; but there are always more layers to the onion.
In particular,
-what do we know about the overall “quality” of the facilities?
-what is the role of network characteristics?
-what are different ways to operationalize characteristics of the network?
-how do these aspects relate to different ways of measuring key dependent variables?
Jessica Schoner from the University of Minnesota just received an honorable mention from APA’s Transportation Planning Division for her paper Shifting Gears: A cross-regional analysis of bicycle facility networks and ridership. This is a remarkably impressive piece of work for a class term paper at the master’s level—not even a thesis or dissertation! Said one reviewer: “Of all the years doing this contest this is by far the best on bicycling I’ve seen.”
The following attributes and reflections are of particular interest:
-She digs deep into elements of general network qualities and examines size, connectivity, directness, and fragmentation,
-She hones in on using percent of bicycle commuters that are women as one of the dependent variables. This is interesting not only because it helps shed light on the gender balance of bicycle commuters but also because women are often considered an indicator species for building bike-friendly cities[2].
-The findings suggest that connectivity, and to some extent fragmentation, are important factors associated with both bicycle ridership and the percentage of female bicycle commuters, even when controlling for household size and structure, vehicle ownership, and city size.
-While we all cry that there is not reliable data when it comes to cycling, there is a lot you can do with secondary data. She did a lot of work to uncover such for 74 communities.
It is comforting to see yet another example of really robust cycling research.

[1] Often referred to, aggregate multi-city cycling studies: Nelson, A. C. and D. P. Allen (1997). “If You Build Them, Commuters Will Use Them.” Transportation Research Record 1578: 79-83, Dill, J. and T. Carr (2003). “Bicycle Commuting and Facilities in Major U.S. Cities: If You Build Them, Commuters Will Use Them.” Transportation Research Record 1828: 116-123, Forsyth, A. and K. J. Krizek (2010). “Walking and bicycling: what works for planners? .” Built Environment 36(4): 429-446, Buehler, R. and J. Pucher (2011). “Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes.” Transportation July.
[2] Women as indicator species: Baker, L. (2009). “How to get more bicyclists on the road.” Scientific American.

Bicycle helmet and safety research

The whole issue of cycling, safety, and helmet use is pretty vast–too vast to go into all the various dimensions here and now. But, a pretty thorough report on bicycle helmet research  recently came across my desk. It covers a lot of ground, albeit with a Queensland Australia focus, and is pretty detailed in the later chapters. It was commissioned by the Queensland Department of Transport and Main Roads to review the national and international
literature regarding the health outcomes of cycling and bicycle helmets and examine crash and hospital data. It is the closest one-stop shopping for helmet research that is of high quality I have come across.

Advancing “total health:” shining light on somewhat competing issues of physical activity & air pollution exposure

What if a community had all the successful ingredients leading to higher rates of cycling and walking (e.g., population density, intersection density, diverse mix of land uses, bike paths galore, etc)? Would planners then being doing their job? How would this relate to the total health for residents?
A small but growing number of studies are looking at two criteria of health simultaneously: exercise and air pollution. The results suggest these things might not always move together in the same direction—a “wake up” call for planners who have typically been obsessed with increasing physical activity. This study helps bring to light that the health benefits from increased physical activity in highly walkable neighborhoods may be offset by adverse effects of air pollution exposure. In the words of one of the co-authors, “city planning efforts have been planning to optimize one risk factor [lack of physical activity], when there are multiple risk factors to be taken into account.” <just fyi, another health consideration is bicycle/traffic safety, but that issue might be less controversial>
Should we worry about this? Of course. Is it a growing issue that has the potential to further divide planning initiatives? Hopefully not. Two possibilities:
·         Will cleaner cars, cleaner businesses, and cleaner everything else coming on-line possibly lessen the need to be concerned about pollution.
·         Is the fact that the study is based in Los Angeles—a basin that has perennially been out of compliance with EPA standards and probably has a disproportionate share of polluting car use (both in terms of sheer use and % of fleet that is old)—reason to suggest the issues there are not as bad as other places?
It is hard to say. I don’t think the solution is pollution filter face masks. This work merely suggests an area worth of further investigation to ensure we are not shooting ourselves in the foot.
Background: Physical inactivity and exposure to air pollution are important risk factors for death and disease globally. The built environment may influence exposures to these risk factors in different ways and thus differentially affect the health of urban populations.
Objective: We investigated the built environment’s association with air pollution and physical inactivity, and estimated attributable health risks.
Methods: We used a regional travel survey to estimate within-urban variability in physical inactivity and home-based air pollution exposure [particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), nitrogen oxides (NOx), and ozone (O3)] for 30,007 individuals in southern California. We then estimated the resulting risk for ischemic heart disease (IHD) using literature-derived dose–response values. Using a cross-sectional approach, we compared estimated IHD mortality risks among neighborhoods based on “walkability” scores.
Results: The proportion of physically active individuals was higher in high- versus low-walkability neighborhoods (24.9% vs. 12.5%); however, only a small proportion of the population was physically active, and between-neighborhood variability in estimated IHD mortality attributable to physical inactivity was modest (7 fewer IHD deaths/100,000/year in high- vs. low-walkability neighborhoods). Between-neighborhood differences in estimated IHD mortality from air pollution were comparable in magnitude (9 more IHD deaths/100,000/year for PM2.5 and 3 fewer IHD deaths for O3 in high- vs. low-walkability neighborhoods), suggesting that population health benefits from increased physical activity in high-walkability neighborhoods may be offset by adverse effects of air pollution exposure.
Policy implications: Currently, planning efforts mainly focus on increasing physical activity through neighborhood design. Our results suggest that differences in population health impacts among neighborhoods are similar in magnitude for air pollution and physical activity. Thus, physical activity and exposure to air pollution are critical aspects of planning for cleaner, health-promoting cities.