How do you reconcile demographic helmet safety findings with individual helmet safety? [closed]

Question

There is some evidence that the rate of bicycle helmet use in various developed countries has a positive correlation with the rate of received head injuries & deaths in the cycling population. Put simply, countries with higher rates of helmet use may have higher rates of head injuries and deaths.

While no specific experiment has conclusively shown either efficacy or increased danger from helmet use Australia and New Zealand have conducted an excellent whole population study of the effects by making it mandatory by law that all cyclists wear a helmet.

https://www.thelibrarybook.net/pdf-head-injuries-and-helmet-laws-in-australia-and-new-zealand.html

Given this very large sample size data, how do we reconcile the difference between the statistical finding that demographically helmet laws do not increase safety, with the individual case that helmets do in fact protect individuals?

Answer 1

There are a number reasons for this, one of the main problems is a logical fallacy called an "ecological fallacy," where population averages do not necessarily apply to the individual. For example, an average head injury rate across a population could go up after a helmet law but that doesn't necessarily mean a helmet is not a good idea for an individual. There could be a number of confounding factors that result in this population level of effect, for example lower ridership due to enforced helmet laws could result in fewer cyclist on the road and therefore cyclists in general being less visible, which in turn results in drivers not watching for cyclists leading to more accidents and head injuries. In this situation it is still in individual cyclist's best interest to wear helmet.

People seem to confusion whether a policy has a beneficial effect at a population level as evidence whether or not there is a benefit at the individual level. These are very different concepts which can have very different results.

These types of questions (epidemiology) can be quite difficult to study because we must rely on observational studies. Here we rely on "nature" to assign the treatment of interest, which can result in problems such as lurking variables and confounded factors. Gold standards such as controlled experiment are not possible, as it is not possible to select subjects to crash their bikes in ways prescribed by the experimenter - for some reason these studies never seem to make it past the ethics committee. As such, we need to be careful giving too much credence to any one we need to look at the weight of evidence (e.g., meta-studies).

Some of the best evidence for individual benefits comes from case-control studies.

Finally, if you interested in some of the physics of why a helmet can help in a fall see: Would a military helmet make a safe alternative to a bicycle helmet?

Answer 2

1) Logical Fallacy

Never forget that "Correlation does not imply Causation." It is an easy mistake to make, but it is nevertheless a mistake. For example, maybe both things are caused by something else. Or maybe it is the second thing causing the first instead of vice versa. It is often a challenge in the sciences (especially when dealing with humans, eg: sociology, psychology) to weed out any other possible causes of the effect being studied, because what if you just haven't thought of everything yet? Instead we settle for... if it's so hard to figure out what other separate causes could be, then maybe nature can't separate them out either very often so you might as well consider them one and the same. "Every time it rains outside, the living room carpet gets wet, therefore the roof must be leaking." Fallacy: Actually, the sound of the rain was making your little brother have to pee uncontrollably while watching tv, so dealing with the roof won't help.

2) Aggregate vs. the Individual

I wore a helmet for a long, long time and I heartily recommend it. But now I realize I was specially trained to avoid hitting my head (and it's been tested over and over again, believe me), so the statistics would be very different for me as an individual than for the population as a whole.

Answer 3

I'm from New Zealand, and have been wearing a helmet since 1987. Because of 30+ years, I'm simply unwilling to ride without one. Even a quick test ride up and down the driveway makes me feel unhappy without one. Curiously I get a similar feeling trying to rollerblade without wrist-guards strapped on, but I've never worn a helmet for that.

I suspect the follow-on effects of mandated helmet usage are numerous.

1. Fewer cyclists, because there's a higher barrier to entry, being some combination of cost, inconvenience, embarrassment. Our average commuting by bike rate is between 6 and 10% depending on how commute is defined.

   This has become a challenge for bike rental schemes too, like Nextbike or corporates to have a "shared" bicycle.

2. Because there are fewer cyclists, motorists are more likely to tune them out and not see them. I've come close to being doored and cut-off so many times because drivers don't think to look first.

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On the other hand there's the oft-quoted "helmets make cars pass closer" study http://www.helmets.org/walkerstudy.htm which claimed that cyclists were given less space if they wore a helmet, and more space if they had a wig (looked female)

This study has been repeated and the initial conclusion is NOT supported. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3783373/

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If we try and break your statement down into atomic components, then I get:

• Helmets decrease the overall damage+injury received by the wearer when compared to the same accident without a helmet

Is this point being debated?

• Wearing a helmet increases/decreases the incidence (quantity) and/or the energy dissipation of accidents (separate to the amount of injury done to the rider)

To paraphrase, you're claiming helmets attract accidents, or helmets make accidents more severe?