This visualisation is part of a YouTube video for my channel. If you want to learn more about the largest causes of death and support my work you can find the full video at: [https://youtu.be/N5hRvBhbqxA?si=UMs-C0xa2cgB-lv3](https://youtu.be/N5hRvBhbqxA?si=UMs-C0xa2cgB-lv3)
It also includes data visualisations for:
* Largest risk factors globally (e.g smoking, poor diet) * Quantifying loss of life quality per disease (Quality-Adjusted Life Years – QALYs)
If you want to explore the data yourself, you might enjoy this data visualization tool made by the Institute For Health Metrics and Evaluation: [https://vizhub.healthdata.org/gbd-compare/](https://vizhub.healthdata.org/gbd-compare/)
Eat right and avoid tobacco products and the graph would change a lot.
I really thought something like car accidents (transport injuries?) would be up there.
What counts as chronic respiratory diseases? Like I would think lung cancer from smoking but cancers are separate. I would still assume smoking related diseases maybe not cancers specfically.
It’d be interesting to see how covid changed the numbers.
“memeable data”, cringe
Were the figures in the lower half placed by hand? They seem uneven. And why is there a cluster of 5 in the Transport Injuries and Self-hard & interpersonal violence lines? Following the logic of the rest of the chart, there should be 2 figures on both of those lines.
Edit: similarly in the top section you’ve rounded 17.6 to 18, but 74.7 to 74. I get that you can’t follow rounding rules perfectly while making it add up to 100%, but isn’t it slightly more accurate to make it 75 and 17? Did you pick 74 and 18 for aesthetics rather than accuracy?
Isn’t Covid supposed to be on this list?
And you can thank antivaxxers for a large chunk of the people in red.
And this is pre pandemic, it is very interesting how chronic respiratory diseases had a high relevance even in that date
3D is unnecessary and arguably makes it harder to understand.
![[OC] Global Causes of Death](https://www.europesays.com/wp-content/uploads/2024/08/1p15gik3kujd1-1920x1024.png)
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Data source: [https://www.healthdata.org/research-analysis/library/global-burden-disease-2021-findings-gbd-2021-study](https://www.healthdata.org/research-analysis/library/global-burden-disease-2021-findings-gbd-2021-study)
Tool used: Blender
This visualisation is part of a YouTube video for my channel. If you want to learn more about the largest causes of death and support my work you can find the full video at: [https://youtu.be/N5hRvBhbqxA?si=UMs-C0xa2cgB-lv3](https://youtu.be/N5hRvBhbqxA?si=UMs-C0xa2cgB-lv3)
It also includes data visualisations for:
* Largest risk factors globally (e.g smoking, poor diet)
* Quantifying loss of life quality per disease (Quality-Adjusted Life Years – QALYs)
If you want to explore the data yourself, you might enjoy this data visualization tool made by the Institute For Health Metrics and Evaluation: [https://vizhub.healthdata.org/gbd-compare/](https://vizhub.healthdata.org/gbd-compare/)
Eat right and avoid tobacco products and the graph would change a lot.
I really thought something like car accidents (transport injuries?) would be up there.
What counts as chronic respiratory diseases? Like I would think lung cancer from smoking but cancers are separate. I would still assume smoking related diseases maybe not cancers specfically.
It’d be interesting to see how covid changed the numbers.
“memeable data”, cringe
Were the figures in the lower half placed by hand? They seem uneven. And why is there a cluster of 5 in the Transport Injuries and Self-hard & interpersonal violence lines? Following the logic of the rest of the chart, there should be 2 figures on both of those lines.
Edit: similarly in the top section you’ve rounded 17.6 to 18, but 74.7 to 74. I get that you can’t follow rounding rules perfectly while making it add up to 100%, but isn’t it slightly more accurate to make it 75 and 17? Did you pick 74 and 18 for aesthetics rather than accuracy?
Isn’t Covid supposed to be on this list?
And you can thank antivaxxers for a large chunk of the people in red.
And this is pre pandemic, it is very interesting how chronic respiratory diseases had a high relevance even in that date
3D is unnecessary and arguably makes it harder to understand.