As you can see, Bleak House is the dying-est novels for named characters.
Obviously, if you really go by what was going on in the novel in general, A Tale of Two Cities, which has a huge part of its action take place in the middle of The Terror, really was set in the most murderous time.
Looking at this body count, I’d say Bleak House is the one that comes closest to accurate Victorian UK mortality. It was brutal, y’all.
Going back to the mortality database from the U.S. in 2014, I needed to figure out what the relevant ICD-10 codes were.
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That’s a total of 384 deaths, and it looks like the primary cause is being attacked by some non-dog mammal. I would assume the second cause is primarily people being thrown from or falling off horses. Alas, most of the vehicular accident codes do not distinguish between hitting a person and hitting an animal.
It may not be fair to throw Finland in there, but if the excuse is hard-drinking and being northerly, Finland has that in excess, and they are beating all those other countries in life expectancy. So that’s not the difference.
Note that all the ex-Soviet states except Russia and Ukraine also had the post-USSR fall from 1989-1994… but started their mortality improvement in 1994, as opposed to a decade later.
Poland started doing well the moment communism went away. Isn’t that interesting?
But I want to note that Ukraine and Russia are lagging the comparable countries hugely. To be sure, Russia is huge, and includes Siberia, which is not the most congenial of locations. But Ukraine doesn’t have the excuse of Siberia.
Both places, in short, suck when it comes to mortality.
The rates are per 100,000 people for the year, but the point is who has the highest, and we see that the answer is:
For 2019: age 85+
For 2020: age 20-24
I threw in the age 15-19 group as ringers, by the way. When we get to all the age groups, they’re not even #4 in the ranking.
Just in that little table, you can see that the rates went up for the youngsters and dropped for the seniors. Think about why that might be.
As noted in my polling question, I’m not adjusting for the number of miles driven, and I’m not going to dig for that data now. But would you like to make some assumptions about the driving habits of these different groups? Especially during the pandemic?
These are awful trends. There’s nothing to caveat. Yes, Ukraine’s life expectancy is a little bit higher, but these numbers are awful, and yes, there was a cratering of male life expectancy after the collapse of the Soviet Union.
I will note that there was a general slide from the early 1960s until the early 1980s… a run-up for some reason (falsifying data?), and then absolute cratering. That’s just hideous.
Dropping about 5 years over a 5-year period is a horrible decrease.
There has been a recovery since 2004, but that life expectancy is still very low compared to other European countries, even other Eastern European countries, as we’ll see below.
With this tile grid map, we can see that the two-year mortality experience has been horrible, even on an age-adjusted basis. I will be using age-adjusted death rates [using the standard 2000-reference-age-adjustment] for all the comparisons. The methodology is at the end of the post.
I warn against taking any meaning from North Carolina, as it has a data-reporting problem. Hawaii, however, really does have a low increase in mortality, and I believe it is credible that the mortality increase of the northeast is also low. I am not sure how credibly to take the increase in mortality of Wyoming, given its relatively small population.
However, we can see some patterns. In general, one has a “hot spot”, and then the increase falls off as you retreat from that peak. The large pattern is the high increase along the southern border — Arizona, New Mexico, Texas, Mississippi — and then the next layer above is less bad, and so forth. There is the Wyoming peak, falls off around there. There is the midwest cluster – Illinois, Michigan, Indiana, Ohio. And then New York/New Jersey.
As well we know, the excess mortality is driven primarily by COVID, which I will get to in the next major section, but let me share some ranking tables.
I highlighted a few of the cause-of-death trends. In particular, COVID (which, obviously, is biased more towards the old), and external causes of death: homicide, suicide, and accidents (which includes drug overdoses and motor vehicle accidents).
There are basically too many things going on in this graph, so there aren’t a lot of good choices for either me or the SOA. What I did was to pick four of the data series to highlight with data labels, as noted above (and I also slapped one data label on dementia for the oldest age group, just because). I am in the middle of a series going through how that external causes of death changed in 2020 — in particular, accidents and homicides went up, and really affected mortality for adults under age 45, plus male teens.
Yeah, check out heart disease and cancer (bottom of the graph). Ain’t old age great?
The kinds of messages that are welcomed are “innovative” in terms of telling you that you don’t have to do the thing you really don’t want to do (put more money into the pensions, promise less, cut back on many things, tax more, etc.)
I don’t recommend simply doubling the numbers from the ranking table and comparing them to the 2020 table, especially for the COVID numbers. I know that won’t work, because of the overall 2021 mortality trend we saw:
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However, I have been making estimates and projections, and I see some really worrying numbers for the ages 15-44 grouping, especially for external causes of death: suicide, homicide, and accidents. The worrying trend is that these may extend past the time COVID mortality wanes. It looks worse for 2021 than for 2020.
I will be doing posts looking at these three large categories, starting with suicide, in upcoming posts, by more detailed demographics than just age. Some of these trends have geographic components to consider as well.
Actuarial News is a website Stu created for me to use as a place to collect all the articles, websites, data sources, etc. that I like to use for my research and writing. I tend to develop ideas over long periods, and I prefer my selections over trying to use regular search.
As noted in the video, I used to use the old Actuarial Outpost (RIP) as a repository for my articles on public pensions and finance, but now I use Actuarial.News.
By the way, for any readers seeking actuarial discussion as once was provided by the old Outpost, check out goActuary. I have a thread on spreadsheet screwups and one on non-pandemic mortality, for instance.
I present the rates in percentages, as opposed to the more traditional number (which is per 100,000 people per year), because I do not want people to get this confused with the raw counts of people who died. Yes, that does mean there are a lot of small numbers. For children, I even had to extend some out to 4 decimal places to get a significant figure.
In adulthood, natural causes of death tend to increase in rate with increasing age. More below.
External causes (accidents, homicides, and suicide) will have the similar rates over broad ages but drop dramatically in ranking with increasing age — as the natural causes become more likely to occur.
COVID has a similar pattern in mortality as heart disease — indeed, the heart disease death rate is approximately twice that of the COVID death rate for the entire age range from 15 to 85+ on the table.
The numbers below each cause are the total number of finalized deaths in CDC Wonder as of 11 January 2022 for the completed calendar year 2020.
COVID deaths for under age 15 weren’t in the top 10 causes for those age groups, which is why they aren’t seen in the table. But you may be interested in those numbers: at #12 for ages 5-14, with 49 deaths at #12 for ages 1-4, with 19 deaths at #13 for infant mortality (<1 year), at 35 deaths
In general, other than the new cause of COVID, most of the causes of death were in the same rank order as in 2019, with a few switches for causes that tend to be close in numbers.
