Tuesday 19 July 2016

How does bedtime change with age?

I saw something earlier today that made me wonder how people's bedtime changes as they get older.  A quick google search pointed me to this study, which is probably the best/easiest to find data set that I'm likely to find just sitting online waiting.  There are a few obvious flaws:


  1. It relies on users of the Jawbone UP for the data sample.  I have never heard of this device, and I'm guessing a lot of people are in the same boat.
  2. Of those that do know of the Jawbone UP, they're probably younger than the average person, just because young people tend to use new tech at a higher rate.
  3. There's likely class/income/etc. biases, as not everyone has the money to spend on a $50 fitness doodle.
  4. There isn't actually any age data in the data set.
That last one isn't really that big of a show stopper.  

First step, scan through the source code to find the file that actually contains the data being used for the interactive map.  It's called counties.prod_.js, and nicely lists the county and state, bedtime in 12-hour format (minus 7, likely to ensure that there isn't a problem at the midnight boundary), as well as some other data I parsed out and saved in case I want to revisit something later.

Second step, trawl through the Census data for a county-by-county population breakdown, with age information.  That's here (although the full country data is actually 112MB, not the 11MB the page claims).  Then it's just a matter of pulling out the population data for 2015 (the closest match to the sleep data), setting the age for entire age groups at the midpoint, and calculating the weighted average age for each county (using the population in the age group as the weight).

So what's the result?
Other than me not truncating the best fit line.

The answer seems to be "Yes.  Bedtime is slightly earlier for older counties."  There's a bit of a plateau in the 16-20 range, but there's a reasonable decrease, even with the scatter.

Of course, using the full population isn't really the best, since the users of the Jawbone UP are likely adults, and not kids.  Redoing this analysis with just people older than 20 (due to the way the census data is binned into 5-year groups):


Basically the same, just shifted to an older age.


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