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Nike_Zoldyck t1_j4ufar8 wrote

Isn't it better to do a histogram or use the actual count for Y-axis, since population will keep varying and declining for various reasons. Would it be different from deaths per 100k metric?

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hcrx OP t1_j4ufni7 wrote

I'm not sure I'm following. The chart already depicts deaths per 100k people, so that variability in population does not affect the reading of the data.

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RoyalSpeedSter t1_j4uhc7i wrote

I think he asks whether it'll be better to just give the number of deaths outright instead of based on 100k that would flactuate with time

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Nike_Zoldyck t1_j4uib1v wrote

What I was trying to get at is that, at first glance it seems like a consistent normalized way to depict the comparison. Let's say you have a list of OD deaths(d) and a list of populations(p) over the years. You're using d/p for each year, right? but while d seems like an independent variable, the p also accounts for a corrected value due to natural deaths, gun violence, disease, other substance abuse etc., So if you had 2 subsequent years with the same number of people dying of Opioid overdose, but the population changed drastically with larger deaths or more births, the d/p changes. These 2 need not be balanced all the years and especially during the pandemic. Just using regular counts won't be affected by variability of population. if one year the (d,p) is (50,300) and next it is (45,200), has it increased or decreased per 10 people? Even though deaths decreased by 5, the deaths per 10 people are 1.6 and then 2.25, which means it increased a lot. So which way are you doing it and why not just show actual counts of it on the y scale instead? why would that give any wrong info?

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The_Athletic_Nerd t1_j4vih8h wrote

So the reason you don’t “just show counts” is precisely because of fluctuations in the denominator (the population). Deaths per 100,000 standardizes by the population so let’s make a fake and sort of exaggerated example. I’d say one year there are 50,000 deaths among a population of 100,000 the deaths per 100k estimate is of course 50,000 deaths per 100,000. Now let’s imagine the population double somehow by the next year and this time 100,000 people died. The deaths per 100,000 estimate comes out to…50,000 deaths per 100,000. So this tells us that the rate of overdose deaths did not change between the two years despite the populations changing dramatically. This is why counts themselves are not an informative statistic unless it’s amongst a stable population. Counts would be more useful if it was say the number of ED visits for overdose for a hospital and that hospital was trying to measure the volume of patients they see in a given period of time. Even then they would likely be just as if not more interested in the percentage of all ed visits were for overdoses.

You seem to be confused about deaths due to other causes somehow impacting the denominator, I think? The population is of course whoever was alive in that year so I don’t see how more births or more deaths is relevant because for deaths they obviously won’t be included in the population for the following year and births don’t really change dramatically enough to have great enough of an impact on the denominator but either way babies can still die from an overdose, it’s tragically sad but it does happen, so they should be included in the denominator.

This is a perfectly appropriate graph and I made several very similar to this as part of my thesis research on the opioid crisis.

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