Der Tag der Geburt eines Kindes ist der gefährlichste Tag im Leben.
Nach der Geburt nimmt das Sterberisiko eines Kindes im ersten Lebensjahr rapide ab. Die Risiken nehmen in den nächsten Jahren weiter ab, steigen aber im Jugendalter plötzlich wieder an. Schließlich steigt im Erwachsenenalter die Wahrscheinlichkeit zu sterben exponentiell an.
Wenn man das Sterberisiko gegen das Alter aufträgt, sieht es aus wie eine J-förmige Kurve oder ein Haken. Sie können dies in der Tabelle sehen.
Im historischen Zeitrahmen hat sich die gesamte Kurve jedoch nach unten verschoben – die jährlichen Sterberaten sind in allen Altersgruppen gesunken.
Dies erkennen Sie an den unterschiedlich farbigen Linien im Diagramm, die Geburtskohorten seit dem Jahr 1800 darstellen.
Datenquelle: Datenbank zur menschlichen Sterblichkeit (2023)
Verwendete Werkzeuge: OWID Grapher und Figma
Von ourworldindata
13 Kommentare
**Data source:** [Human Mortality Database](https://www.mortality.org/) (2023)
**Tools used:** OWID Grapher and Figma
Modern medical technology has done so little to help 90+ year olds. They are barely living longer.
This is a lovely graph! Really well presented, and full of interesting stories that make you want to dive in deeper.
Indoor plumbing and vaccines are the doing the heavy lifting here.
What’s the large jump around 20? Is that when US kids stop going to the doctor because they have to pay themselves, or is it lifestyle risks (cars, drugs, guns, alcohol), or?
e: It’s been pointed out that this is from Sweden, but the question still applies. 🙂
I’m sad the graphs don’t all end at 100% (given old enough data).
You can see those blue lines shoot up in teen years. Risky behavior, no doubt.
I notice this is coming from Our World In Data, which I no longer consider a reliable source of information. I don’t think they’re *lying* or *fabricating* data; I think they’re just very selective about what they publish. Why is there only a graph for Sweden? Is there not data to generate a graph like this for other nations?
I think using the rainbow color scale make this data less beautiful difficult as the colors that are closest are also the ones that will be the most similar data. If you want to keep the same color scheme, maybe do some being dotted or dashed lines?
Which countries are these data from?
Can you explain what the death rate means if you look at 50-year-olds and the rate is generally one percent or less across all cohorts.
Putting this on a log scale has absolutely no value and just hides how big the effect was.
You can clearly see the world wars on the graph, creating a big gap for 20yos in those years, even tho Sweden didn’t participate so actively as other countries. I wonder how that looks for the us, UK or Russia