Sugar, all of it

Lisa Charlotte Muth

What a great substance: sugar. Also evil. It tastes amazing and gives us a lot of energy, it’s nutrient as a sponge (meaning: not at all), makes us fat and makes our tooth decay. But it’s not all the same. There are different kinds of sugar (glucose, fructose…basically everything that ends on “-ose”): Lactose & galactose can be found in dairy products, maltose in grains, fructose in fruits, and sucrose is the sugar that’s made out of sugar beet or sugar cane and is used in chocolate and candy.

Like salt and fat (and lots of other things), sugar is important for functioning bodies. But like salt and fat, sugar is so common in our Western diet that the problem is not eating too little of it, but too much. Our bodies can make glucose (the “human body’s key source of energy”, according to Wikipedia) out of lots of non-sugary food, including vegetables, wheat, rice, nuts and seeds.

You might be surprised by the amount of sugar in an infant formula – turns out, breast milk contains a similar amount of lactose, which is important for a baby’s health.

Chart Choices

Last week, I wrote about the importance of reducing data to increase readability. This week, I want to make a point for adding data. Yes, we could have made a simple bar chart showing the amount of total sugar in each of these foods, without splitting them up in different kinds of sugar. Yes, it would still be an interesting chart. But it would remove so much available data that it would hurt a bit.

Don’t get me wrong: All charts simplify the world to add insight, and in my opinion, that’s a huge part of what makes charts so appealing. But in our case, we do have the data to show the parts our bars split up into. So why not use it? Why not add nuance? In our case, it doesn’t reduce readability by a lot. It even adds more insight. But most important: It adds a bit of the world’s complexity back to our chart.

Complexity in a chart is a bit like sugar in a diet: The right dose differentiates a poison and a remedy. Hm, does that make sense? It’s close to not making sense at all. Anyway, see you next week!

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Lisa Charlotte Muth

(she/her, @lisacmuth, @lisacmuth@vis.social) is Datawrapper’s head of communications. She writes about best practices in data visualization and thinks of new ways to excite you about charts and maps. Lisa lives in Berlin.

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