Unpacking a Complex Biological Infographic
How Do We Die?
Hey, what could be more biologically interesting than knowing what sorts of things are killing us!
And the infographic has a ton of great information!
Just a quick scan tells you that. In the article, they explain some of the information, give a few more pieces of data and tell you that Cancer and Coronary heart diseases have increased over the time period and Neonatal conditions have decreased.
But they don’t unpack the infographic for you. They just summarize some of the highlights and expect you to do the rest yourself.
If you’ve got a few moments, I’d like to help you get even more from it.
First, we need to understand the actual layout. It’s really just a variation on the simple graphs you saw in high school math. This variation is often called a Bubble plot or a Bubble scatter plot since there are lots of various sized and coloured circles (the bubbles) scattered around in various positions. And they kinda look like they’re floating, just like the soap bubbles that you blow.
If you look on the very left side, there are numbers attached to light grey lines and are increasing from 0 to 250 in 50 unit increments as you read from bottom to top. In math, you would probably have seen a label to the left of them (and probably written with the text reading in a vertical line from bottom to top) telling you those numbers are the Global Disability-Adjusted Life Years (DALYs) in 2016 and the units are in millions of deaths.
They do give you that information but they put it on the top of an arrow at the top of the graph.
They also tell you that a DALY is the equivalent of a healthy year that was lost due to one of the conditions (illness, disability or premature death) they present as bubbles on the graph.
Why did they do that? They could have just used the standard format and a bit of text under the graph to define DALY.
They did it because they want to emphasize that this graph isn’t a simple box format that has a bottom left zero corner where both the vertical and horizontal lines (In math we call these axes) meet. The vertical axis does start at zero, but the horizontal axis starts at about minus 1.2 or so. The vertical axis arrow line they inserted is at the zero start point for the horizontal-axis.
The labeled Fewer and More arrows they give us at the bottom of the horizontal axis are also a nice touch for quick reading and remind us where the zero point for both axes is.
The horizontal axis is labeled; Change in the Number of Deaths per Year. The numbers, from -1.2 to 3 on the horizontal axis are the increase or decrease in deaths per year, in millions, worldwide.
For illustration purposes, let’s look at one of the bubbles. For no particular reason, I’m going to choose the Stroke bubble.
When we look at the Stroke bubble, we notice several things.
We see that it is larger than some and smaller than others and that it is a specific colour.
If you look on the right hand side, you can see a bit more information about bubbles. The size of the bubble tells us the death rate in 2016 per 100,000 people and the colour indicates that the disease is not a contagious or communicable one.
So for Stroke, the bubble size falls between 50 and 100 deaths per 100,000 people in 2016. I’m thinking it might have been nice if they had also put the actual size number inside the bubble, but then it would start to look even more complicated.
Let’s do some math here. I guesstimate the size of the Stroke bubble at about 75 deaths per 100,000 people. That means 750 deaths/million. That gives 750,000 deaths/billion. Since there are about 7.7 billion people on the planet that gives us 5.8 million deaths a year globally from stroke.
Wow, that’s not a small number anymore! We’re looking at really big numbers here! Not just a few people.
A quick scan of the chart tells us that most of the bubbles we see are either communicable or non-communicable diseases (light green vs dark blue).
We also see that deaths per year are decreasing for most of the communicable diseases shown (they are on the minus or Fewer side of the vertical-axis arrow) and are increasing for non-communicable diseases.
When we look at the actual causes we can infer even more information. Cancer, Stroke, Heart disease, Alzheimers and others are diseases associated with an aging population.
The population is changing and becoming older as we increase our ability to fight disease. We are living longer and these diseases are what we are most likely to die from.
There is an especially big decrease in deaths due to Neonatal conditions.
Nice! It’s great to see that more babies are surviving and more moms lives are being saved at a much higher rate than they were at the turn of the century.
But there’s even more subtle information.
In the article, they remind us that many of the non-communicable diseases can leave us with life-long chronic conditions and disabilities that prevent people from living comfortably and working effectively long before they die.
For the light blue bubbles which are injuries, there are road injuries and unintentional injuries and a third bubble which is not labeled. That’s a bit frustrating. It’s as large as the other injury bubbles but you can’t tell what it is. I’m going to take a wild guess and say that it’s intentional injuries (suicides) since that category seems to be missing, but that’s just my wild guess.
In any case, deaths due to injuries do not seem to be changing very much. They are either right on the vertical axis which is at the zero point on the horizontal axis, or close to it.
One more thing and then I’ll leave you to discover more on your own.
As you look along the vertical y-axis arrow, you see that in the bottom third of the chart, there are 12 bubbles sized less than 20 deaths per 100,000 that are not labeled.
Why include them? They apparently refer to minor diseases which are also following the major trends we observed between the communicable and non-communicable diseases or are not changing much in either direction.
I’ll say it again; Why include them? You’ll have to comment and ask the authors what all those unlabeled elements are. Personally, if you’re not going to label a data point, and you’re not going to tell me about it or give me a reference that can tell me what it is, it shouldn’t be there in the first place. It’s just some attractive filler.
So I hope that helped you to better understand this infographic and get a bit more information than you would have had you just gazed at it yourself for a few minutes.
And do read the article! There’s another good infographic and more story than I talked about here.
Until next time,
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