Safety vests and helmets make cyclists look ‘less human’ to other road users
Bike riders wear helmets and high-vis vests to reduce their vulnerability on the road. Problem is a new study finds this dehumanises cyclists, putting them more at risk of aggression from drivers.
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Well, it shows that either all places in the data set have universal helmet use (they don't) or that helmet use is not the dominating factor. Further, informing policy, is suggests that it would be better to mandate helmet use for the more dangerous modes such as walking and driving, and focus enforcement there
How do you conclude that walking and driving are more dangerous in terms of head injuries?
The article linked at the beginning of this thread lays out a good overview of the available research. This includes causes of head injury hospital visits, over half of which were from driving.
So if activity X has a 1 in 50 chance of injury, and activity Y has a 1 in 500 chance, which would you say is more dangerous?
I think I see what you are getting at... We need to look at the rate of injury per use. In traveling, we may want to look at travel times. From the article I mentioned:
Risk of head injury per million hours travelled
undefined
Cyclist - 0.41
Pedestrian - 0.80
Motor vehicle occupant - 0.46
Motorcyclist - 7.66
Which would you say is more dangerous? Those are probably the ones that should have mandatory helmets laws, no?
Do you know what “per million hours traveled” means and how it was calculated? Is it per person, cumulative across the population, something else…?
Using my example above, let’s say cycling had a 1:50 chance of injury and driving a 1:500. You’d naturally say cycling is more dangerous. Let’s also imagine on a given day in your city there are 1000 people cycling and 20000 driving (pulling numbers out of my butt, but probably not unreasonable).
With the above, the hospital ER would see 20 bike injuries and 40 car injuries per day. I.e. twice as many injuries from cars, even though the chance of being injured is an order of magnitude smaller.
That’s mostly the point I was trying to make. And why the details matter.
Also another thought on the article: to draw a fair conclusion (apples-to-apples comparison) you actually need to know the bike numbers without helmet. It could be, take the helmets off the cyclists and their injury rate skyrockets towards the motorcyclists.
It would certainly be reasonable to expect the head injury rate to go up without helmets on cyclists heads.
Yes, it's calculated across the population, it's an epidemiological study. That is, for every million hours the population as a whole spent driving, there where 0.46 head injuries (as an average). For every million hours the population as a whole spent cycling, there were 0.41 head injuries. This was before the helmet law went in to place. This means that, on a time sent basis, you where slightly more likely to receive a head injury in an automobile than on a bike. Your math would be correct, but the probabilities you listed are not those the study found.
Meanwhile, this study found that whole helmet use in Victoria and NSW increased from roughly 30% to roughly 75%, the proportion of head injuries only dropped by 13%. On the other hand, ridership declined after the helmet laws.
Raising more questions, during the same time period, the proportion of head injuries amongst pedestrians also declined by about the same amount, indicating that helmets may have partial or no responsibility for the decline.
Again, the available data suggests that without helmets, the rate of head injury stays in line with cars and walking, and with helmets, the rate stays in line with cars and walking.
I genuinely appreciate the replies and detail.
I must confess I hadn't read the articles you cited. I know the issue is complicated, so my goal was to make a very simple and transparent model to try and understand what's reasonable. The numbers you quote imply that an assumption in that model is wrong, or something really critical is missing that flips the result. It's hard to see what or understand why. In terms of head injuries, in a given day, riding is more safe than driving maybe ...? Or more people ride than drive ...? Probably not. So I'm left more confused by these numbers.
So then I went back to your references. The source of your numbers (from what I can tell) is here, which you gave above. This is an anti-helmet website, not a study. Noting that anyone can write a blog and claim numbers, I looked for the references to support their claims. There are none. So it's hard to tell if these are real studies (probably), but from when, where, cherry-picked, and so on (these details matter). Not linking to the source is a huge red flag for me and undermines any trust in what's argued.
I'm guessing the Australian study you reference above is the same as the one they mention (thank you for linking directly to it). This is a nearly 30 year old paper from UNE, looking at the numbers one year after helmet laws were introduced in Vic and NSW. Without going into detail about some of the questions I'm left with (e.g. what is the variance in the year-to-year numbers they're comparing the 1-year changes against? - if that variance is larger than the 1-year change then the change is statistically meaningless - and so on), I figured, regardless, this is a poor source to draw such significant conclusions from (old, 1 year of noisy data, limited geography etc). Surely there are more recent studies that track the longer trends with more complete data?
Looking at the papers that cited that paper, I find this, which is a 2018 meta analysis of 21 studies (including the older AU one) from Norwegian researchers. This should be a better source, given it covers a much wider timespan (collectively), populations, geography, methodologies etc. They also spent a lot of time on the uncertainties, biases, etc to aid in the interpretation of their results.
There's a lot of good information in the abstract, but here's what I think is the headline result:
"The summary effect of mandatory bicycle helmet legislation for all cyclists on head injuries is a statistically significant reduction by 20% (95% confidence interval [−27; −13]). Larger effects were found for serious head injury (−55%; 95% confidence interval; [−78; −8])."
There's lots more of interest to this discussion at the link. But I haven't gone through the paper beyond the abstract. I'm happy to take the abstract as written (since I have a job and other things to do today).
So what to make of all this? My experience is that there are two types of people. A small but very passionate minority of riders that are really, really against helmets. And the rest of the population who don't really care that much. They ride and wear their helmet - sometimes forget it and hope they don't get caught - but otherwise don't think about it.
The biggest issue I feel we should be directing our energy towards is improving the cycling infrastructure by separating bikes from cars. Cars are the biggest danger to riders. Until we do a better job at that, and without the benefit of a metal cage around us like cars provide, simple steps to protect our heads - the helmet - make a lot of sense, to me at least.
EDIT: some minor wording clarity.
That meta study is actually quite interesting as a source for specific data. For instance, this paper found that the swedish helmet law had low effect on head injuries because it causes low risk cyclists to stop cycling.
This paper demonstrates that a safety-in-numbers effect exists for cycling, suggesting that we have policy which encourages more cycling.
What most of the sources cited demonstrate, and which I haven't contested because its pretty self evident, is that out of people admitted to the emergency department of a hospital, those who where wearing helmets had less head injury.
That meta study, and most of the cited studies, does not account for the injury rate for time spent by cyclists, or the total number of cyclists on the road. As seen in studies linked elsewhere in this thread, helmet laws do have an impact on those metrics also, and can be detrimental to the safety in numbers effect.