Showing cause and effect with Fitbit metrics

[Thaddeus23]

Greetings all,

I've had my Fitbit Inspire HR since July of this year, and I wanted to share with you how I benefit from its data. I'm 55 YO, a daily cyclist, 188cm and about 102kg. After a high blood pressure reading earlier in the year, I purchased a BP monitor as well. After about two months' logging on a Google spreadsheet, I saw patterns that have compelled me to change my habits. I found applying conditional formatting to the columns to highlight good and bad figures was more effective than charts.

After some time, I rearranged the columns to demonstrate cause and effect. In my case, I noticed good outcomes began with exercise, so I moved that column left. The following day or days, my sleep improves, so I moved that column to be next. My resting heart rate and blood pressure improve together after that. (Conversely, I noticed weeks ago how even moderate alcohol consumption raised my RHR, which then damaged my sleep and blood pressure.)

I've drawn the relationship between these columns in black outlines on the attached image. The first consequence of studying this data has been to (mostly) cut out booze. The second will be to make more strenuous exercise a daily habit. I now regard my overweight as the result of years of mindless (moderate) drinking and insufficiently strenuous exercise, and am using the data to steer myself back to better health.

[WavyDavey]

Hi @Thaddeus23

This is one of the coolest presentations of Fitbit data I've seen yet. Thanks for posting it. I'm sure others will want to copy your ideas.

[skms]

Thanks this is exactly the kind of analysis that i am doing too - very encouraging to find someone else! I am also colour-coding the variables to try to spot patterns. 

Are you doing the colour-coding manually, or have you set it up to do it automatically? I'm doing mine manually which is time consuming, so would be interested to know if you've found a faster way. 

Which element of the sleep score do you think that exercise is improving? Longer sleep, Deep sleep etc? Maybe its worth investing in the Premium to get the breakdown?

So far I haven't found any obvious patterns, and so at some point will do some statistical analysis to look for correlations that may pick up things that aren't obvious to the eye, and can also subject any apparent links to more rigorous analysis. For instance, if your theory is correct, how come you didn't have a high sleep score on 3rd October? To get stronger evidence it would be good to crunch more data. 

Keep up the good work!

[Thaddeus23]

Hi skms, all the colour is handled automatically by Google Sheets' Conditional Formatting. To streamline things, I'm only logging the general Sleep Score, which I'm satisfied is a faithful indicator of all the components. As for October 3, I drove over five hours back from holiday that day through a time zone, and any deviation from routine will upset things.

[skms]

OK thanks. I've set up the conditional formatting too now. 

Yes, I can see that would have affected things!