I agree with most of your comment, but hiking for hours is pretty substantially different from the amount of walking you do in walkable areas. Particularly because, by definition they have shade and places you can stop for cool drinks etc. Thr notion that walkable areas aren't always good is a pretty silly conclusion to draw from the tragedy you cited.

"Inequality" is a bizarre concept to apply here -- and it seems it's used to signal social justice virtue: it's unfair that people in more successful economies have time for exercise and recreation, and/or that their cultural norms includes the concept of "healthy lifestyle".

Inequality is not just being used colloquially here.

https://en.m.wikipedia.org/wiki/Gini_coefficient

"difference" would be a better adjective. It would describe it without adding word which can carry unwanted inference.

Catchy headline for left leaning types.

You really ought to read the paper.

1. They do control for demographics.

2. They do account for temperature, by comparing geographically close cities with different activity inequality levels.

3. They do account for "cost". They repeatedly compare cities and countries with roughly the same income distributions.

Also, as far as I can tell, the paper draws _exactly_ the opposite conclusions as what you state. In no way do they claim that rich people exercise more, nor do they claim that demographics have a strong correlation with exercise.

From what I read, they come to two conclusions:

-There is a correlation between activity inequality and obesity.

-There is a negative correlation between activity inequality and walkability.

Agreed, there are red flags. All their data comes from this smartphone app (717,527 users):

  Download Argus now! Join MILLIONS and download the 
  world’s ONLY free all-in-one health & fitness app that 
  uses JUST your phone (no costly devices needed) and 
  conquer your goals! We have a super-easy calorie 
  counter with barcode scanner and massive food database.

As a scientist I would have rejected this Nature paper based on highly biased data collection.

I wonder WHO (in the sense of only a subset of a given population) would download and install that "all-in-one" tool.

I would guess:

1) people somehow interested in their fitness

2) people having some dietary issues (more probably believing to be more fat than what they should be and looking for a shortcut to get slimmer)

Customer of type #1 will likely do lots of steps, while customer of type #2 is more likely to do much less.

It is very possible that in whole coutries there is a preponderance of type #1 and in other ones of type #2.