The article is careful to point out that these are not the most common reasons men/women wind up in the hospital. They are the reasons that have a very gendered split as to who experiences them. So even if men stopped riding motorcycles, there would not necessarily be a noticeable decrease in male hospitalization rates.
>I’m having to choose my words carefully, because I need to stress one thing: these are not the most common reasons for men and women to be admitted to hospital. They are the most typically male and typically female.
The OP didn’t say all of the reasons for male related injuries were needless, but if you look at the list, it’s dominated by activities that are inherently voluntary and risky.
aren't you being a little naive by calling dangerous activities men have to take to survive "inherently voluntary"? go to a 3° world country or works as an immigrant somewhere rich to check your options. transportation included. it's easy to say one shouldn't use a cheap motorcycle and go for the one way sardine packed 2 hours bus ride across the city to reach work, everyday
Only 3 out of 18 reasons on that list are work-related, 2 maybe can be work related (lawnmowing and powered tools/household machinery?). I think cycling accidents (5 positions on the list) are in part normal cycling (like when riding to work) without rider's fault, and in a larger part taking unnecessary risks while riding, or riding for sport. And I'd guess motorcycle accidents (4 on the list) are mostly taking risks and riding too fast. 3 reasons are "assault". And that leaves only 1 reason from the list, sports equipment.
So out of 18 reasons on the list, only a small part is "activities men have to take to survive", but many of the others aren't "inherently voluntary and risky" or cannot be blamed on the hospitalized person. The list is too short to be really interesting, when half of that list is the same thing with small variations (cycling/motorcycling), and the same for women (mostly pregnancy).
This data reflects the UK, not a 3rd world country and my comments are restricted to this dataset.
Included in that same dataset are assaults and sports related injuries, which are additional risky activities.
You might argue assaults aren’t voluntary. My personal experience suggests most assaults are the result of voluntary activity rather than involuntary activity, YMMV.
I’m not being naive. I have lived in a 3rd world country where it wasn’t uncommon to see a family of 5 on a motorcycle.
I would note that you will tend to see, proportionately speaking, more women on motorcycles in those countries for the reasons you suggested.
>> So while men are taking risks, women take one for the team
I know you're joking but three of the top four are basically 'work related'. Men taking one for the team doing all the dangerous jobs.
And maybe if the men stop riding motorcycles the women will stop getting plastic surgery which is also shockingly high as a reason to end up in hospital.
This is probably the wrong chart for the comparison. The entire top section involves fewer total people than 3 separate 100% women related items on the bottom.
The follow-up article sorted by absolute numbers is a bit better suited, and predictably a bit more bland. Births is nearly in the top 10 though.
I'm a little bit confused about what that is. If you are admitted to hospital for pregnancy and its not delivery (thats a different category that is far larger in absolute numbers) then something has gone wrong.
And herein lies the joys of medical coding :). Likely more than 235k normal pregnancy checkups happening in hospitals over 3 years in the UK, these "Z34" codes will likely get coded as admissions if someone is admitted for concerns around the pregnancy and the net result is everything with the pregnancy ended up fine. Maybe some other oddball scenarios I'm not thinking of too, but if you just go in for a planned pregnancy checkup and it comes out fine it (shouldn't) be coded as an admission just because it was done in a hospital location. Unless the NHS just has really odd coding practices, which is possible, but the other chart isn't drowning in 10s and 10s of millions of vaccinations of each type either.
For similar reasons you may find a ton of other things which aren't normally an admission in the data, but at numbers less than one might expect because that alone isn't usually reason to admit.
Also worth noting that it is only looking at percentages. If you rendered the size of the blue and red bars based on total admissions, all you'd see is a bunch of red until you zoomed in very closely.
The pregnancy numbers are a policy and not related to accidents. It would be similar to say that children at age 3, 5 and 12 months are much more likely to end up in the hospital than other age groups, since those are the ages when they get vaccinations.
As with all statistics, there is some apple to oranges comparisons and some contexts that get lost.
Men, stop riding motorcycles Women, stop having kids
That last one might have some detrimental effects long term though.
So while men are taking risks, women take one for the team