Review of Popular Cycling Studies
Methods, Conclusions, and Problems of Popular Cycling Studies
The opprobrium of statistical knowledge, data collection, and interpretation is a profound trend in the recent history of American anti-intellectualism, but it is too often presented as a characteristic of extreme ideological groups on the left and right. While true that climate science and evolution deniers take the cake for challenging science, its methods, and data collected by large institutions, there are plenty of progressives, in my own communities of interest, whose first response to studies, surveys, and data-based knowledge is absolute skepticism, rather than trying to work through the data and research and find anything of value. This is summed up in the classic rejoinder that “you can make statistics say anything.” The giant sucking sound of many well-educated people’s positions on anti-vaccination, and the attention given to how GMO foods can make you sick (they don’t--they’re bad for other reasons) come to mind as some issues where progressive and educated folk have made some terrible choices based on conspiracy theory and fear, not on research and data.
My bailiwick is cycling advocacy, where a certain strain of anti-intellectualism, as I perceive it, has taken hold. I just can’t tell if it is my own, that of my peers, or all of us. My particular peeve is the great inattention given to the relative benefits of riding a bicycle versus the gross attention given to the dangers, especially in one of the most awesome cycling cities in the country, Gainesville, Florida. My question is, why can’t I and my colleagues see eye to eye on this, when in every way we advocate for the same public policies? Why do we encourage the media and each other to focus on helmets, crashing, and cars (all negative incentives to ride), when we know that perceived fear is a powerful phenomenon that accounts for the vast majority of people not riding a bike more?
I believe our inability to communicate is based on that anti-intellectual thing. I just can’t tell if it’s on my part and theirs. Perhaps I just don’t read the statistics right because I am so enamored of getting people to ride bikes. Bike riding has defined, guided, and literally saved my life and health. Whenever things aren’t going well, my brother’s first response is usually, “Are you riding?” It is personal to want to share something so vital to you with others you just know would benefit. So, I admit, I see no way to avoid letting emotion cloud my reading of the data. And yet, I believe, with admittedly infrequent humility, to be an intellectual, to have the capacity to do just that--be objective--at some level. I also know these other advocates with whom I disagree about safety, to the person, to be some of the finest intellects in our community. So what gives?
I thought, perhaps, that laying out some of the methodologies of historical and contemporary studies of cycling behaviors, crashes, safety, usage, and the like would help. I believe, that is, that reason in the end will prevail. Who knows, it may even cause someone to examine the same data I have and find that I am wrong, that cycling in Gainesville really is as dangerous as cyclists themselves, many of them committed advocates, make it out to be. I hope that’s not true. I may profess a certain objectivity, but my heart falls on the side of being right on this one.
As a disclaimer, and probably of surprise to some with whom I disagree, I began studying a lot of these sources, especially John Forrester’s work, to support an older belief of mine that cycling was dangerous because of automobiles crashing into us (almost exclusively, at a rate of 90% of our serious injuries). In fact, you can Google the 90% statistic pretty easily. Years ago before the internet that number would trace to the League of American Wheelmen, who assembled data from their experienced recreational cyclist membership, hardly an unbiased source, and also the most likely group to not be at fault when encountering a car. The 90% number was popular throughout the late 1990s when I traveled across the Northeast and Southeast racing bikes. It had traction. More recently, it has found its way to the internet/Google and appears to be sourced from a study of a mere 127 hours of riding done by cyclists with cameras on their heads who were, without doubt, behaving nicely, thinking intensely about safety, and probably more experienced than cyclists who don’t wear helmets, or cameras, or commute regularly, for cycling studies. These are the kind of data that had led me to believe so negatively about cycling safety in general for “regular folks.” When I discovered I was wrong, and was basing my perception of fear on bad research, I was even more encouraged to do cycling advocacy. It is certainly much easier to advocate for something in your town when you believe it to be safe.
As I studied more, and as more sources became available on the internet in the mid-2000s, I began to realize that a lot of what we believe about cycling is based on misinformation, anecdote, personal horror stories, retail industry hype, the anti-bike politicians, media hyperbole, and a more than passing combatitiveness with the car-only community. Let me pick a controversial topic as an example. Traditional helmets (the new MIPS may offer an exception but are unproven), most of the scientific community now knows, don’t really do much for the common concussive blows in day-to-day wrecks, and most people just don’t want to wear them. Cycling clubs in the D. C. area even convinced the federal government to take down industry-promotional claims that grossly exaggerate helmet safety and may even lead to unsafe behavior. As someone who has promoted, organized volunteers for, and taught multiple safety and riding courses, including participation in helmet giveaways to kids, this was a tough nut to swallow. I’ve sold and given away thousands of helmets, with the admonition to “never ride your bike without one.” Was I scaring people away from cycling? The answer, according to global data for three different countries with compulsory helmet laws, was yes. I never told anyone to stop wearing one, but I have been called ignorant, stupid, even “anti-cyclist” for pointing out and discussing the research and data.
Other research followed. In Fear and Loathing on a Bike in Gainesville, I explain that cycling here is really not as unsafe as the media, my cycling club, and fellow bike advocates make it out to be. I argued that we were all misusing statistics in an irresponsible way, allowing the media and our friends and family to augment, not challenge, their fear of riding. We should be telling people to “get out and ride” because more cyclists means better safety. I mean, what else should we tell them, not to ride? Many of the studies below appear in that article. And yes, I hope you will click on it and read it if you haven’t already (shameless plug).
I continue to advocate for safe, rideable streets, and better infrastructure funding, and I’m proud to have helped oppose an onerous bike licensing/registration attempt aimed, I still believe, at our lower income citizens and our cycling community in general. I continue to have friendly conversations with my co-workers, people on the street, and non-cycling politicians and fellow public advocates about getting people on bikes. But to do all those things we need to agree on some fundamental methods, sources, and data. While personal stories, testimonials, and public outcries are important parts of the democratic process, public policy on infrastructure, policing, enforcement, health, and safety must at some large level be determined by good research. Otherwise, we yield the floor to the anti-bike crowd and to fear-based behavior. And that, to be frank, is what we already have. And unlike cycling with or without a helmet in Gainesville, that is something to truly be afraid of.
Studies, Methods, Conclusions, and Problems
Please feel free to comment on Friends of the Gainesville Cycling Club Facebook Page where I have posted this article. I will gladly correct all errors of fact, or include any analysis or criticism I deem of merit. Please include your sources. The studies are listed in no particular order, and if you see one I missed, I may add it. I include critical sources that challenge the data, if they were easy to find (Googling “Criticism of SURVEYNAME” or “Problems with SURVEYNAME” for example, or looking on the LAB and other sites for criticism). I may look up some more criticism later, or include any that you contribute. This is a living document, very easy to change, so no problem. I am not a professional statistician, so I appreciate any scholarly input.
1. Bicycle Transportation: A Handbook for Cycling Traffic Engineers, 1983, by John Forrester
Methods: Forrester is the godfather of vehicular cycling. His massive in-street and live action studies used observers and cameras and traffic data to produce reams of data on bike-car interactions at every conceivable type of infrastructure and from all angles of approach and takeover.
How to Use It: The heavy statistics and charts in the original edition are not for the faint of heart, but Forrester’s is the original argument that we should not base policy or traffic building or our cycling attitudes on fear. It’s worth a read. The newest edition has updates on different types of infrastructure.
Conclusions: Forrester concluded that acting like traffic and on regular streets without separate or segregated facilities, was the safest and most effective way to be on a bicycle. More radically, he concluded that bike lanes and separate but equal infrastructure caused more wrecks and only confirmed the false perception of fear that cyclists had on roadways. American cycling treated bikes like toys, and cyclists like children. Cyclists, to some degree, shared the blame for this, as they began advocating for more and more “toy” bike lanes and separate facilities. The easier, cheaper, and more reliable solution was just to teach people how to “drive” their bikes and to overcome their fears. Forrester’s stridency is the foundation for an ongoing rift in the advocacy community, especially with the League of American Bicyclists now sending mixed signals about its commitment to vehicular cycling (see below).
Problems: Forresters’ anti-segregated facility posture was developed long before the U. S. and Europe had longitudinal experience with such facilities. Because they are difficult to build and because streets for the automobile are ubiquitous, segregated facilities should not be pursued at the expense of vehicular cycling. That said, segregated facilities have a growing place in our culture and traffic, even in the very concept of vehicular cycling that Forrester supports.
2. Modes Less Traveled: Bicycling and Walking in the United States, 2008-2012 by the U. S. Census Bureau (American Community Survey Questionnaire).
Methods: This study has the largest of all statistical samples for any related exclusively to cycling and walking. It basically asked people how they get to work in the form of a census questionnaire, along with identifying social and demographic data such as income, sex, ethnic or “racial” identity, education, and age. The study was an attempt to improve on prior studies that “hid” bike-ped data inside other surveys about transportation or general census data.
How to Use It: Beyond just reading the report, you can use the League of American Bicyclist’s instructions for using American Fact Finder, the official analytical engine of the U. S. Census Bureau. You can siphon off your own reports from this if you are committed.
Conclusions: Ridership has doubled in the decade before the study, but remains below 1% for many “categories” of populations and for many cities. The most surprising conclusions to me were that the least (less than high school) and most educated (more than a Master’s) share a higher cycling rate. Those with between high school and Master’s education commute less. “Hispanics” and “Whites” ride more than “Black or African-American” or “Asian” identified people, but the largest “racial” group of cycling commuters was “Some other Race or Two or More Races.” At any rate, all these numbers are under 1% for the “ethnic/racial” groups. Another unsurprising statistic, when people of any type have a car, they ride and walk very little.
Problems: The most glaring issue is that the survey only uses seriously regular cycling commuters, not people that “some” or “mostly” cycle commute, and it doesn’t count trips where a majority of the mileage is by other means than a bike. Therefore, multi-modalism is under-represented. Neighborhood maps for towns and cities in the census put ridership rates up over 20% for central and East Gainesville, but the “census data” show only 6% for Gainesville proper. You really need to use some research skills to find particular data that gives a good picture of who rides and where in your community. The American Fact Finder helps. Also, riding “to work” may be a small portion of the riding that people do, especially if they are homemakers or unemployed or use it for (public!) health. Recreational driving is still driving, so recreational cycling should still be considered cycling.
3. Where We Ride:Analysis of Bicycling in American Cities, 2012, by the League of American Bicyclists.
Methods: The LAB uses the analytical engine for the census described above. It includes a hearty section on cycling cities and weather (precipitation, cold, etc . . . ) which the census report does not.
How to Use: Read the darn thing. It’s a highly refined and digestible report.
Conclusions: Probably the best conclusion that comes from this, and that yields very different numbers in our favor for cycling in the nation’s cities, is that more people are riding than we had imagined, even by the account of the census report from the census data. In the LAB’s own words: “It’s important to note that the bicycling data in the ACS records only “journeys to work,” or commuting. The ACS only counts the “primary” mode. It does not count commuters as bicyclists if they rode only part of the week, or rode their bicycle to transit and the transit portion was longer, etc. In short, the ACS mostly captures the regular, everyday bicycle commuters.” Another plus, is they also report by in some tables by absolute numbers, not percentages, which reminds us that the big and seemingly “anti-bike” towns like L.A. and Chicago actually have the most cycling commuters in them. Growth over time since 1990 is shown as well, with Detroit, of all places, showing the largest increase in cycling among large cities. Probably not surprising since there are a lot of poor people there since the 1990s, and poor people without cars ride bikes a lot.
Problems: This is an analytical report without much analysis. It’s mostly a friendly graphic representation of some very cool compiling done on the census machine. The League has done the analysis in other places, but it leans on digestible graphics and charts a little too much. There’s no a lot of question answering as to why and how these numbers came to be.
4. Every Bicyclist Counts, by the League of American Bicyclists.
Methodology: When I first read it, I believed this was the most in-depth study of cycling fatalities in one year, plain and simple. Individual stories, reports, and postings of more than one-third of the fatalities for a one year period around 2012, from the death of the cyclist, right up to the 77 convictions on criminal charges. I know of no more devoted study of cycling carnage. While statistics are compiled, you can actually read about the cyclists and the people that killed them, an effective combination of narrative and hard data. But there are problems, big ones.
How to Use It: Read the explanation on the LAB page, then open the reader or download the longer document with data and individual stories. The LAB famously makes data digestible to viewers. It’s what they do.
Conclusions: This study challenges how the National Highway Traffic Safety’s Fatality Analysis Report System classifies and reports cycling deaths by arriving at different conclusions based on reported evidence of individual fatalities. For example, in a whopping 40% of fatalities a “rear-end collision” was the cause (whoever was at fault, but mostly the driver).
Problems: No raw data or method of calculation is provided. This may be available upon request. The LAB is a friendly organization and a non-profit. Other big problem, the American Bicycle Education Association takes apart the report pretty handily in a polemical but methodical essay. There may be some political motivations behind some of the conclusions in the study, and the way crashes were recorded, specifically LAB’s commitment to segregated bike infrastructure and declining allegiance to Forrester’s Vehicular Cycling practices. Notably, none of the data are from crash reports, not one, and the LAB plays fast and loose with some crash description terminology. For more on the early conflict between the vehicular cyclists and the segregated path schools, see John Forrester’s scathing memorandum from way back in the day. Personally, I used to be a hardcore vehicular cyclist, but I believe where possible we must and should build segregated paths. The data says they work, when built properly, which they aren’t always.
5. Florida Crash Statistics and Injury Reports, By Time and County.
Methodology: First responders and local governments use statewide crash data protocols to report all data. This is the most comprehensive reporting we have for all Counties, by County, in the State of Florida. The reports compiled by FIRES are used in legal proceedings and for insurance claims, for safety estimates, engineering, and traffic forecasting, and they include the geo-site of the crash. Data include five year histories of type of accident, mode of transportation, alcohol-related, victim age, safety equipment use (seatbelts, helmets), type of injury, and more.
How to Use: These are raw data. You’ll need to do some math and basic statistical analysis. To show change over time, some of the data would need to be compiled. I would use them alongside your local census data to make some conclusions and comparisons. The Florida Department of Transportation “Crash Facts” 2011 were the most recent ones I used for my 2013 article mentioned above. You can get the most updated from the Florida Integrated Report Exchange System by registering with the private company that provides that public data (a process which I oppose on principle). More “processed” data with graphs can be found at the “Public” site on their homepage above, where you can get highly processed (and therefore not very useful) data for Alachua County. The best way to use this is just to go through the FIRES portal and glance at all the pages for a year. There’s only about 25.
Conclusions: None. The data require analysis. There are other analytical reports in FIRES, but mostly on cars and commercial vehicles.
Problems: Personal experience suggests there may be some under-reporting or misreporting of bicycle incidents, as in this study of Boston reporting suggests, or as any time spent on any cycling club social media page will likely yield a lot of stories to that effect. Personally, I believe this is a problem for all vehicular accidents, but as cyclists we are more vulnerable because police tend to be less familiar with our status as vehicles. They are catching on, but they need our help. A great article on underreporting (that favors my upbeat view of cycling safety) is here in the NY Times.
6. 2012 National Survey of Bicycle and Pedestrian Attitudes and Behavior by the National Highway Safety Transportation Agency.
Methodology: From the NHSTA document on methodology . . . “The survey utilized an overlapping dual frame (landline and cell) sample design and included an oversample of 16-39 year olds. A total of 7,509 interviews were conducted with persons 16 years of age or older living in the United States. Interviewing began on July 12, 2012, and ended on November 18, 2012. The samples were combined and weighted to produce national estimates of the target population.”
How to Use: Read the report and examine some of the pie graphs.
Conclusions: People who already ride feel fairly safe when so doing, and they are surprisingly resilient when it comes to weather. Another conclusion is that summer, pretty much everywhere, is cycling season. This was not just a “commuter” survey, but also included recreational riders, so that makes sense.
Problems: This would be a more useful study if it had been subsumed underneath the American Communities Survey umbrella, by just adding it’s survey mechanism to that of the ACS. Separating out the attitudes study from the other data on actual commuting/cycling seems counterproductive. Also, the attitudes and behavior we should really be most interested in is that of people who are not already actively cycling. This just focuses on people who already do.
That’s all folks. So long, and Keep the Rubber Side Down,
James Thompson