This study looks at “Activity Inequality,” a cool metric which, like income inequality, identifies a disparity across the population; in this case it tracks who’s getting exercise and who’s not. (The study is based on daily steps.)

This metric seems key to urbanist politics & analysis, and the study comes with findings that tease out the importance of the urbanist agenda. For example:

Screen Shot 2017-09-01 at 9.38.37 PM“Aspects of the built environment, such as walkability, may mitigate activity inequality. Higher walkability scores are associated with lower activity inequality based on data from 69 United States cities.”

But ultimately, the study is confusing because while it ranks countries based on which countries have the best and worst distribution of activity (the lower the score the less inequality), it’s not clear how that overlaps with high or low averages of personal activity in general.

Screen Shot 2017-09-02 at 6.28.00 AM

So, for example, Hong Kong is ranked No. 1 for activity distribution, but it doesn’t say if people living in Hong Kong are actually getting in more steps on average across the board compared to other places..like the U.S, which is ranked No. 42 for activity distribution.

Screen Shot 2017-09-02 at 6.30.18 AM

Meanwhile, when the study unpacks¬† “Activity Inequality,” it seems to focus on gender…which is important (and women appear to be getting less exercise in than men)…but it was frustrating not to see an income and race overlay.

Here’s the abstract:

Understanding the basic principles that govern physical activity is needed to curb the global pandemic of physical inactivity and the 5.3 million deaths per year associated with inactivity. Our knowledge, however, remains limited owing to the lack of large-scale measurements of physical activity patterns across free-living populations worldwide. Here, we leverage the wide usage of smartphones with built-in accelerometry to measure physical activity at planetary scale. We study a dataset consisting of 68 million days of physical activity for 717,527 people, giving us a window into activity in 111 countries across the globe. We find inequality in how activity is distributed within countries and that this inequality is a better predictor of obesity prevalence in the population than average activity volume. Reduced activity in females contributes to a large portion of the observed activity inequality. Aspects of the built environment, such as the walkability of a city, were associated with less gender gap in activity and activity inequality. In more walkable cities, activity is greater throughout the day and throughout the week, across age, gender, and body mass index (BMI) groups, with the greatest increases in activity for females. Our findings have implications for global public health policy and urban planning and highlight the role of activity inequality and the built environment for improving physical activity and health.

I want to have a better handle on this study (here’s the full report and the background data).

But with obscure explanations like this: “Activity inequality, which we define as the Gini coefficient of the population activity distribution,” I can’t say I know what the main point is.

It  does seem like this a significant bit of urbanist research. Hopefully someone who gets this stuff (and who reads this blog) will take a look at the findings and report back.

*The study doesn’t report on Seattle’s Activity Inequality data (though it was evidently factored in alongside the data from several other U.S. cities.) And there is a chart of Walkability scores for U.S. cities, and Seattle ranks No. 9; Walkability measures how friendly the built environment is for pedestrians.

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*Jakarta is apparently an abysmal walking city, according to this NYT article, which is where I came across this study in the first place.

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