Quantified Self for Preventative Care

Quantified Self for Preventative Care - Boston QS

So as mentioned my name is Daniel Rinehart and I wanted to talk tonight about how I’ve been trying to use Quantified Self for preventative care. And by that I mean trying to track information through Quantified Self to kind of hope I live as long and healthy as I possibly can.

My route into Quantified Self was not coming in with wanting to make a specific change in my life, or want to try and track a specific experiment about a change in behavior. Instead I was really interested more in about collecting data about myself and that interest really started with the introduction of a project called the Zeo.

I first read about this back in the summer of 2009, and having always being fascinated with sleep and dreaming really was interested to see what kind of data I could get out of the Zeo. So that really started my interest in collecting data about myself, again not necessarily with a specific goal in mind.

I also started attending some of the local quantified Self meetups here in Boston, which is where I learned about another application. It was a study being done called to track your happiness, where you sign up and then at random intervals you get prompted to indicate what your current mood is, what your activity is, and just some other kinds of classification information.

And so this is another study that I’ve been participating in and kind of seeing what data it’s generating for me.

I also wanted to see how I was using time on my computer and on my phone. And there’s a company out there called Rescue Time what does what they call productivity tracking. You can go in and install an agent on your computer on your phone and assign very distracting to very productive classifications to a bunch of activities, and then it will generate reports for you to kind of say how productive you were that week.

And most recently based on another Quantified Self meetup I learned about a company called Inside Tracker, which is a company that’s helping you analyze your various biomarkers in your body. And so, they take a slight more approach based upon your results of you blood test, that they will make certain recommendations for you. And that’s kind of where my interest in how I’m using my quantified Self data has changed.

So right now I’m looking at a history of data that I’ve collected since about 2009 across sleep, and the happiness studies and productivity and then more recently getting my biomarkers tested at regular intervals. And so when I take a step back I think that’s a lot of data, what can it actually tell me that might be able to improve my long-term health.

And a few things that it has told me is one of which is looking at my sleep pattern I was able to discover what my sleep cycle is. And for me this occasionally plays an important role such that if I can’t get my full night’s sleep I know that I’m better off budgeting for a 90 minute interval of sleep such that I’m less likely to wake up groggy and given that I bike to work every day, I definitely don’t want to be groggy out there on the Boston roads.

Another thing that the happiness study kind of helped me observe was looking at the different types of activities that I was engaged with, the ones that involved these different characteristics was also the activities that I had the most focus and my mood was the best when I was participating in them.

And it turns out that these same types of activities are also very good for your long-term cognitive health, and so as a result I’ve tried to consciously plan additional activities in my life that really speak to one of these three goals.

The other thing that this data has allowed me to do is to establish various baselines, such that as I age or as I engage in different activities I can see if particular characteristics of how I’m living my life change. So for instance I’m fairly fortunate that I fall asleep fairly fast, don’t wake up and get a fairly good night’s sleep.

So I can now on a regular interval go back and say okay, over the last three months has my sleep habits drastically changed and kind of take a step back and say okay is that due to aging or due to some other factors that might be indicative of something that’s going on in my life and I might want to take preventative action for.

The other thing that the Inside Tracker information has kind of also let me see is that there are some experiments or kind of what ifs scenarios that I want to start exploring based upon the results of that information.

So I conducted two/three month experiments starting in November of last year. the first one was to spend three months working solely at standing desks both at work and at home. The next experiment that I took after sitting full-time was to make changes in my diet, and particularly change what I had for breakfast and what I had for lunch. And also to start taking supplements, and the recommendations of making those changes or some of the ideas in the Inside Tracker service recommended to me based upon the result of those biomarkers.

And so, one of the shocking things was that in particular when I switched to standing up throughout the day I definitely thought that additional activity would have an impact n my sleep cycle or potentially change how much time I wanted to spend in front of computers, because all that time in front of computers was standing up. Infact in both cases using the Zeo and Rescue Time I didn’t notice any change during that two experiments.

What did kind of shock me though was based upon the information from Inside Tracker, some fairly drastic changes to my overall total cholesterol. I started with a historical value that I got from an annual physical with my physician, and took the first reading that I got from Inside Tracker, then got retested after the three months of standing up, and then retested after three months of the diet change and was very surprised to see this dramatic shift in particular that the three month of change and the additional activity by standing up didn’t seem to have any impact on my total of cholesterol. But clearly, the following three months of a diet change did. And so right now I’m on the course of extending that diet change for another three month to see whether these values are stable.

The other changes I mentioned was kind of looking at looking at the Inside Tracker recommendation and taking a vitamin D supplement, again had the value from the start after the three months of standing and also after three months of adding a supplement to my diet. Now the decline in my value during my three months of standing might be due to the fact that that took place during the winter months. And so I suspect that decline may just be the fact that I wasn’t outside as much, and so here again I’d be kind of interested to see what happens after the next three months of this change in diet.

And so these are just a couple of the experiments I’ve done to kind of use this vast set of data that I’ve collected to try and make changes to my health that potentially get me in what Inside Tracker calls more towards the optimized zone, and really kind of potentially detect these types of issues before they become medically significant or actually manifest as an ailment or some other condition that would require more extensive changes or potentially medicine than you know just kind of changing my behavior.

So I’m really just kind of experimenting with how to fit all of these different pieces of data that I’m tracking together into a long-term picture. But so far these first couple of experiments and behavior and diet change I’ve been kind of involved then to look and see what additional types of tracking I can do or additional types of changes I might be able to make that set me up for long-term health and happiness. And so that’s all that I have to say.