You're being a dick. You asked, "do you think we could generate good statistics? what questions, limits, rules, processes, behaviors, cautions, have i not thought of? "

But you don't want questions or limitations. You want yes-men.

Have fun.

And don't try to play the death-card on me. I've watched cyclists, on the ground, in front of me.

What about using Strava or Training peaks aggregate data of miles ridden (or hours ridden) and compare that to the number of deaths in a given time period (which should be publicly available). I don't know if those sites would provide thisbinformation but it would at least be a start, and most folks on Strava / Training peaks are serious athletes. The idea is as such:

In California in 2016, x number of cyclists were killed compared to y number of miles ridden for that same time period.

This would likely overestimate the risk, as not everyone is on Strava or training peaks, but it would at least be a start. I'm interested in this risk, because I'm hesitant to ride outside (wife, two young kids and a mountain of medical school debt).

---

doctorironman.blogspot.com |

Loosing battle.
"forum content is at the discretion of forum administrators".

It has been made clear, that dissent contributions are not appreciated..

This is from 1993. Cycling fatality rates have declined since then.

If I ride for 10 hrs a week, 52 weeks per year, for 50 years, my total hours are 26,000. According to the list below the odds of being killed are 1 in 3.85M hrs, so I have 0.7% chance of being killed on my bike in my lifetime. That's if I'm average.

I think my odds are better than average. I try to be visible and avoid riding into the sun whenever possible. And I live in a place where the drivers seem to be courteous and aware. I'm mostly on rural roads with no shoulder, but traffic is light. I also have a lot of riding experience, which surely helps.

Fatalities per million hours
Sky diving
128.71
General aviation
15.58
On-road motorcycling
8.80
Scuba diving
1.98
Living (all causes of death)
1.53
Swimming
1.07
Snowmobiling
0.88
Passenger cars
0.47
Water skiing
0.28
Bicycling
0.26
Flying (scheduled domestic airlines)
0.15
Hunting
0.08
Cosmic radiation from transcontinental flights
0.035
Home living (active)
0.027
Traveling in a school bus
0.022
Passenger car post-collision fire
0.017
Home living (including sleeping)
0.014
Residential fire
0.003
Data from Failure Analysis Associates, Inc (now Exponent Inc), Design News, 10 April 1993.

I wonder if there is a proxy that can be used to determine if the risk has increased or not.

For car seatbelts it was fractured femurs. The increased use of seatbelts led to a decrease in incidence of femoral fractures.

I think you need:

• Population size - that ride outside, not total triathletes
• Time / Distance ridden
• Total Deaths minus obvious non cycling related causes
• I think you need to identify if there is an increase in car / bike interactions in general

I'm not entirely sure that this needs to be limited to deaths in the same way that hospital mortality is not the only indication of quality. Hospital acquired infections are a proxy for quality and tracking them overtime is an indicator of quality. Cyling incidents are not just limited to deaths and IF there were an increase in deaths, you'd expect (reasonably) to see a corresponding increase in other cycling incidents as its a reasonable assumption to think that drivers are not sat in their car saying if they can't kill them they won't hit them at all.


I would think its a reasonable starting point to look at both accidents / interactions that result in a police report irrespective of death and compare the total of those over time against deaths in the same number of reports.

Where do I get statistics for chance of being killed while not riding like a dumbass? Those are the only stats I care about.

i think the biggest problem here is probably going to be the denominator. (andrew's already pointed out that the numerator could be expanded, too - mortality's the most salient for riders, and the most unambiguous to measure, but there are plenty of people who survive accidents that are nonetheless life-changing, career-ending, etc.).

so:
-we're measuring deaths per X. person-miles? person-hours? cyclists? outdoor cyclists? total population?
-i think rates would be preferable to absolute numbers here, since the popularity of cycling (and driving) has definitely gone up and down, and all else equal, more riders and more cars on the road would mean more accidents overall, if not relatively.
-if you wanted to calculate and odds ratio or relative risk, you'd probably want to get an 'exposed' group (cyclists) and a control group (non-cyclists), follow them for, say, a year, and then it's simple arithmetic to work out risk of death in both groups. unfortunately this doesn't get us very far, since we can assume that the risk of being hit by a car while cycling is zero for non-cyclists.

-so on that front i think number of deaths per km (or hour) ridden would be 'best'.

-in terms of controls, i think there would be a lot of things to account for:
-seasonality comes to mind - probably far more accidents overall in summer. on the other hand, with so few people riding mid-winter, the 'effect size' of a single fatality would be larger.
-gas prices (more cars driving more miles when gas is cheap)
-time of day
-maybe proximity to weekends/holidays would put more drunks on the road?
-geography? many experienced cyclists will tell you that 'the drivers are good' in this area but 'bad' in that one. is there anything to that?
-maybe timing w/r/t advertising campaigns, police safety blitzes, etc
-helmet laws by region

that's about all i've got at the moment. the damn thing with stats is that it's easy to gather a huge pile of data that actually tell you nothing, or at least don't tell you what you think they're telling you.

-mike

---

____________________________________
https://lshtm.academia.edu/MikeCallaghan

http://howtobeswiss.blogspot.ch/

when I responded I was thinking about the hours v's distance

Intuitively I would think hours on a bike is better than distance given the range of speeds in cyclists is so great, though with a big enough sample size there is a regression to the average. With cars, distance makes sense as I suspect the spread is slightly lower in terms of speed - I do not know why I think this

On the other variables in your post - I am willing to bet that one of the best sources for data would be ambulance services rather than the police

I worked with London Ambulance for a number of years. Call patterns lead to the constant movement of ambulances over a 24 hour period on standby. Mornings - inward commute, Afternoons - exodus. Weekends away from CBD's.

Patters with respect to accident locations, time of day, severity are all pretty predictable in the same way that ambulance calls first peak is 4-6am as people wake up realising they've had a stroke / other, steady call rates as they go to work, drop off till they go outside for a break mid-morning and get run over, decrease again till lunch, increase, then decrease post lunch until about 2.30-3pm onwards when they continue to steadily rise as people leave work and get injured.

I suspect that the other thing that can be done in terms of looking at the under-reporting of non-fatal incidents would be to undertake a survey of, lets say, the ST population comprising; hours / distance ridden per year, incidents involving medical care, incidents requiring band aids but no clinical input and of these two what percentage were not reported v's reported.

Anyway - as a back of a fag packet means of determining risk it might give some ideas.

I would speculate that much like well established patterns for hospital admissions, hospital mortality, unreported near-misses, ambulance patterns that there are probably some underlying patterns worth being aware of and I would guess that they might be; riding in commute time, lunch time, when schools break out and dawn and dusk, in addition to simply riding in high traffic areas

I agree. I assume bicycle fatality statistics include the drunk guys riding the wrong way in the middle of the night while wearing all black. As well as those blasting through red lights in NYC without looking. I want to know my risk--riding on good roads, in control, wearing reflective gear and lights as necessary, and obeying traffic rules that affect my safety.

Maybe the answer is in the OP, concentrate the data collection on dedicated cyclists in cycle and triathlon clubs. I'm sure that the clubs will remember deaths in the last few years and could give a good guess at the average mileage of their members. Combine the two and you get a pretty good idea of risk for cycle training rides. As stated above, general cycle fatality numbers will contain an awful lot of noise such as deaths due to drunk cycling or night riding without lights. This would also allow you to regionalise the data to see the differences between urban and country areas.

  I would argue that life altering injuries are just as important in telling the story of "risk" as measuring for death.

You would need countless variables to get to a true and meaningful picture. Probably the most important is the time/miles on different types of roads. It would seem obvious that your risk of death or major injury is greater on a busy roadway with minimal or no shoulder vs a bike path with very minimal traffic.

I have always done my outside ride from my house starting with riding on Hwy 49, which lots drive 70 plus and the shoulder is not super wide. But, I have decided
that this is not smart with the odds, so this morning I have putting the bike rack on, and driving to start where there are much few cars. And doing on a Sunday morning.
So yep, where, when and how you ride impacts the odds also.

---

Dave Campbell | Facebook | @DaveECampbell | h2ofun@h2ofun.net

Boom Nutrition code 19F4Y3 $5 off 24 pack box | Bionic Runner | PowerCranks | Velotron | Spruzzamist

Lions don't lose sleep worrying about the sheep

Jason80134 wrote:

You would need countless variables to get to a true and meaningful picture. Probably the most important is the time/miles on different types of roads. It would seem obvious that your risk of death or major injury is greater on a busy roadway with minimal or no shoulder vs a bike path with very minimal traffic.

I think you could collect the following data at a high level:

1. Total deaths of cyclists registered in clubs or triathletes in tri clubs
2. Make a guess for total hours ridden in a year. I would expect that USAT and USA cycling have some general stats on the average number of hours their members ride. This is very course but we're talking averages here. I realize some of this will be indoors, but you have to start somewhere. What does the average "serious" cyclist ride per year? 100 hours? 200 hours? I doubt it is 300 hours (almost 1 hour per day).
3. Perhaps get stats on overall bike fatalities nationally urban vs rural. Just apply those overall percentages to the "serious cyclists" we are trying to create stats for.
4. Get overall national ambulance calls to an accident that involves a cyclist and compare it with overall deaths of cyclists (this includes the drunk guy riding in black at 2 am from the bar against traffic, but it's OK, let's use him too). Let's say that ratio is 4:1, then apply the same to derive ambulance calls involving serious cyclists.
5. From the overall ambulance calls, you should be able to get a breakdown of how many urban vs how many rural to get the triathlete breakdown. Having said that, perhaps since we cover more distance, we hit "rural" more often than the average person on a bike.

As a starting point if Slowman can aggregate deaths of serious cyclists from bike and tri clubs, we can then have a basis to overlay some of the general stats on us and perhaps infer how all that applies to our levels of risk.




Maybe an interesting starting point is two ST member polls


Poll 1: How many years have you been riding? (answers 1, 2, 4 , 5-10, 10+)
Poll 2: How many times have you been in an accident where an ambulance was called or should have been called (answers 1, 2, 3, 4, 5+).


If we can get 1000 people answering each poll (and I realize that the same people will not answer both), we can get an idea of experience level distributions of some hard core cyclists, and how often they are involved in a serious crash with a car. Maybe that alone is more useful data for "us".

I think I agree with this idea- the data is most likely to come from collecting data directly from the groups you wish to analyze. Cyclists, triathletes, etc I wouldn't think would be too hard to collect data from. The former tend to congregate in groups, and the second seem to not be strangers to collecting loads of data anyway. I guess you could collect as much as you want and then see which parts are useful, such as age, time of day riding, relative traffic load, etc. I imagine that on a first go, you won't get what you need there without a large and focused study.

But getting data on say, incidents or deaths per hour ridden, should be relatively easy, assuming that self report of those hours and report of incidents is accurate enough.

I would think finding as many cycling groups as possible- teams, clubs and such, sending questionnaires for distribution, and the same to bike shops all over the place, would be a great start. You could target each shop on the Road Show stops and send questionnaires there as well.

Might include:
Hours ridden per week on average, divided by traffic volume, traffic aggression, time of day, day of week, lighting (sunlight and use of lights)
Number of "close calls"
Number of incidents while riding- could split into "by motor vehicle, pedestrian, animal, road conditions, user error"

Information on deaths will be interesting- Since the actual number of deaths during cycling is small and the number of cyclists or cycling hours is big, I'm not sure how much specific data from that cyclists history would really sway the data, but since it's not going to be self report in that instance anyway, you could ask in your questionnaire if the responder knows of anyone that has been killed while riding, and then ask for estimates of hours ridden per year, for how many years. That data is going to be flimsy, but I'm not sure if there's an easy way to collect it. You'd always have duplicates that you'd have to weed out by maybe location of incident, first initial/last name, but that isn't going to be a huge number I'd imagine. Also would like circumstance if known surrounding event.

I think what we really want to know is incidents and/or deaths per hour. Dividing by circumstance is going to be hard. In deaths in air travel, the rate is going to vary based on if you fly in a small plane heading to Martha's Vineyard at night (Kennedy?), weather, experience of the pilot probably... but I'm certain those are grouped into the overall risk. Just as swimming in the ocean at dusk in South Africa probably increases likelihood of getting eaten.

Collect and see what falls out?

Ultimately events/hour is going to be helpful, assuming we are targeting recreational and up.

"Where do I get statistics for chance of being killed while not riding like a dumbass? Those are the only stats I care about."

i agree with you. the one thing i do worry about is the drunk or the phone user. this i can't inoculate myself against. there are a lot of distractions in cars now. navigation systems and other screen touch systems that require i make numerous and rather complicated transactions in the car, while driving.

i'd like to see how often this kind of thing nails us.

---

Dan Empfield
aka Slowman

"-we're measuring deaths per X. person-miles? person-hours? cyclists? outdoor cyclists? total population?"

deaths per relatively serious triathletes per time increment. i think the operative guidelines should be:

- a cohort that resembles us, otherwise the data won't pertain to us.
- a cohort that is of a size we can measure accurately.
- incidences we can measure. that we can count.

for example, swim deaths in triathlon don't give us a good measure of the risk, because dale basescu died last month while swimming in a masters workout. if i'm dead i'm dead and i don't feel any better about it because i didn't have a race number written on my shoulder. so, those 3 above, if we keep it simple, keep it to that, i think it's possible.

other bad stuff that can happen, broken leg, whatever, i don't think we should try to count those. deaths only. from deaths i suspect we could refer back to generalized data, such as, for x number of deaths there are y number of broken legs.

---

Dan Empfield
aka Slowman

If you could get to "for x number of deaths involving a car and a person on a bike, there were Y number of ambulance trips to get a cyclists hit by car" that might be a useful extra piece. it would allow US serious cyclists to infer the risk of an incident.

To some degree, aside for my loved ones i don't care if I die in car+bike incident. If I die pretty well instantly, I'm dead and gone. Limited pain, no change in quality of life (since the life is over at that moment and financially everyone is taken care of). It's just painful for those who I leave behind, but speaking completely objectively, I'm done over here and left quickly. But if I am in an incident that dramatically changes my quality of life and that of my loved one, this is a risk I also care about.

I think the best way to get a number of data set opportunities is to collect what can be collected by those on this forum that choose to participate.

From x date to x date, name, city, state and notes (hit by drunk or hit by distracted driver etc. if know) and during training/event ride or casual rider and finally - outcome (death, serious injury, walk away).

A spreadsheet on a page that we can go back to and update as we remember or get research collection (over say the next 30 days) for information during the past year.

Then see what can be inferred by what has been accumulated.

Edit: there is a "bike law group" I follow on Linkedin that could also provide a lot of information on incidents over the past year.

---

Dan Kennison

facebook: @triPremierBike
http://www.PremierBike.com
http://www.PositionOneSports.com

"for x number of deaths involving a car and a person on a bike, there were Y number of ambulance trips to get a cyclists hit by car"

again, i don't see the relevance. what if we find out that for x number of cycling deaths involving a car, three-quarters of x are people who are commuting to work, or are hit while riding on the wrong side of the road, or for running stop lights?

you know the people on this forum. the minute data is released, any data, regardless of how well constructed, regardless of anything, we'll get 40 posts on why the data is meaningless. therefore, i think any successful data should have a goal of relevance. for it to work, again:

1. the data should be relevant to us, to what we do;
2. the numerator - number of instances - needs to be a number we can count with confidence;
3. denominator, same thing, a number we can count with confidence.

if asking ambulance companies to provide us their data will do that, i'm all for it. but don't know ambulance companies. i do know 800 tri club presidents. i do know 1100 local bike shop owners and 700 run store owners. i do know 700 tri coaches. i do know all of you. and, you all know each other, or, you all are within 2 degrees of separation from every triathlete in north america.

triathletes are a pretty good cohort, in terms of relevance to us.

---

Dan Empfield
aka Slowman

When I watched the new report the other night, when they said car accidents have gone way up, after years of going down, and they had no idea why.
Cyclists, 13% up. Pedestrians 10% up.

Seems so easy the answer, you stated most but missed the more "drugs" being used. We have had pedestrians killed with the driver using Ambian as the excuse, so a drug,
anything which impacts the body or mind, is much larger than most think about.

I sure am NOT looking forward to my outside bike ride coming up in a little.

---

Dave Campbell | Facebook | @DaveECampbell | h2ofun@h2ofun.net

Boom Nutrition code 19F4Y3 $5 off 24 pack box | Bionic Runner | PowerCranks | Velotron | Spruzzamist

Lions don't lose sleep worrying about the sheep

OK fair Dan. What if we can manage to get incidents involving ambulances for us from the clubs and coaches. Dying is the extreme case. We are all afraid of dying, but the real thing to fear is a dramatic transformation of quality of life from an accident and living through that hell. If we can come up with the risk that compasses death and injury (rather than death alone), it would be awesome.

"Dying is the extreme case. We are all afraid of dying, but the real thing to fear is a dramatic transformation of quality of life from an accident and living through that hell."

i think what might be relevant from GENERAL statistics is, for every cycling death, there are x number of cycling limb breaks; y number of paralyses; z number of just accidents for which an ambulance is dispatched. fine. but we have to start with a manageable enterprise and unless you are willing to volunteer to find out how many times a triathlete has broken his finger or gotten a road rash i don't know who you think its going to find that data or how you think it could be found.

the problem with a simple survey is that people self-select what they want to answer. if put up a poll and ask how many people got their fingers stuck in a coke bottle when kids, i'll have an over-representation of people reporting yes, because people to whom that did not happen will not find the question interesting enough to answer.

also, from a simple survey of a discrete number of clubs i'm afraid we won't have enough size for statistical relevance. i'm not statistician, but if we ask x number of clubs about their club experience, how many people have died while cycling, and we have clubs responding that total 10,000 triathlete club members, if the incidence is 1 in 30,000 then i don't know that 10,000 respondents is a large enough cohort from which to draw relevance.

---

Dan Empfield
aka Slowman

Close to zero for triathletes. Using 2014 statistics:

• About 700 bicyclist fatalities per year in the nation. So if all of them were triathletes, and there are 500,000 registered with USAT, each of us has about 1,000:1 odds of dying in a given year. Do the math using realistic numbers.
• About 20% of bicycle deaths involved the bicyclist being legally drunk. So cancel that out of the stats, reducing them further
• About 20% of bicycle deaths were around dusk.
• About 70% occurred in urban areas. How much triathlon training occurs in urban areas?
• Maybe 40% of the fatalities occurred in California, Texas, or Florida. Why there? More triathletes? Or more immigrants riding to/from work during rush hours?
• About 1 in 6 riders killed were wearing a helmet. Nearly all triathletes wear helmets while riding.

I've been riding in NJ for 30 years or so, and I can recall only one triathlete fatality (and it was likely her fault) a couple of decades ago. (I swam with Chrissie, and she died about a mile from my house). Perhaps others in NJ can remind me of other fatalities among the triathlete community.


To try to be "constructive", here's one reference for how NYC derives its findings:




To describe bicyclist fatalities in New York City for the period 1996–2005, several data sources were analyzed. All known bicyclist deaths were included. The primary data source was the NYC DOT Fatality Database. This database is routinely cross-referenced and reconciled with the NYPD Accident and Investigation Squad (AIS) Database. For this study, recon- ciled deaths from 1996-2005 were then cross-referenced with death certificates maintained by DOHMH to confirm the cause of death and to identify any additional bicyclist fatalities. All fatalities with an underlying cause of death indicating the person to be a bicyclist were included, based on International Classification of Disease (ICD) codes (for a listing of these codes, please see the Technical Appendix).
Through a match with NYC death certificates, an additional 46 possible bicyclist deaths were identified. Records at the Office of the Chief Medical Examiner (OCME) for each of these possible additional deaths were reviewed by a team of three DOHMH investigators. Thirteen of the 46 possible deaths were deemed to be bicyclist fatalities occurring in NYC and were added to the NYC DOT Fatality and NYPD AIS databases (for additional details, please see the Technical Appendix).

---

----------------------------------
"Go yell at an M&M"

Generating statistics on this would be possible. Generating some meaningful numbers? That I am a lot less sure about.

The biggest issue that I see is that the risk of road cycling is wildly not uniform.

For some riders/situations, the risk of road riding is very very very low.
However, for other riders/situations, the risk of road riding is remarkably high.

I think we all want to know a number that meaningfully represents our own risk. And there are many things that highly affect our own risk. For example, if I live and ride in pretty deserted part of Idaho, I would imagine that my bike risk is very very different from a rider who starts his ride in downtown chicago.
Etc.

---

Advanced Aero TopTube Storage for Road, Gravel, & Tri...ZeroSlip & Direct-mount, made in the USA.
DarkSpeedWorks.com.....Reviews.....Insta.....Facebook
--