The Background

It has been a while now that I’ve been bothered by one simple fact: running is simply not for everyone. Weigh-In Wednesday posts are runner-centric for a variety of reasons, including ease of tracking and, quite simply, it is the activity I personally have been doing. It has bothered me from the start though, that I haven’t been able to figure out a way to properly credit all types of activity. From Pat’s boxing to Susan’s cardio boot camp, and Brian’s p90X and Insanity workouts, to name a few. More importantly, I also have trouble giving proper credit to people just starting out on their fitness journeys, who have gotten off the couch and started going for bike rides, or long walks, or even yard and house work. The people with whom I want to celebrate the most are the ones who are systematically marginalized because they aren’t running or doing elliptical workouts.

Perhaps I’m coming off little dramatic, but I think my point is clear. All exercise, from walking to swimming an beyond, is valid, and I want to shine the spotlight on people who are getting active.

I sat down last night to revisit a concept that I’ve played with and researched quite a bit a while ago but didn’t pursue. There are vast tables of data available with values assigned to every single possible activity imaginable and this is known as Metabolic Equivalency of Task. These MET values are an estimate of the amount of energy expended from a given activity. For instance, running at a pace of 6 miles per hour has a higher MET score than running at a pace of 4 miles per hour. More importantly for our use, these values represent a way to standardize exercise between different activities such as walking and running.

text{1 MET} equiv 1 dfractext{kcal}{text{kg}*{h}} equiv 4.184 dfractext{kJ}{text{kg}*{h}}

To give a sample table of what I am describing:

Physical Activity MET
Watching Television 1.0
Walking 1.7 mph 2.3
Walking 2.5 mph 2.9
Jogging 7.0

Each activity, and I have literally thousands of values at my disposal, can then be weighted fairly according to its actual energy expenditure.

Introducing Anti-Fat Points!

With an enormous amount of MET values at hand (literally, they have a category for making a phone call to a government official . . .), I sat down to come up with a scoring system that fairly weights each exercise that is submitted to 2FNs. The product is Anti-Fat Points, or AFP. Each Wednesday I will now be posting AFP scores for each person. Anti-Fat Points are awarded based on duration, distance (if applicable), and the published MET value for that exercise.

How the Scoring Works

I think it is easiest to explain via an example. Say you have two people, Ellie and Jon. Jon decides to go for a run in the pouring rain, while Ellie decides to use the expensive gym membership they pay for each month instead. Ellie spends 60 minutes on the elliptical, while Jon runs in the rain for 30 minutes. Ellie covers 4 miles, while Jon covers 3.5 miles. An average pace for each exercise is computed, and the MET table is called up to find the appropriate MET value.

  • Ellie: Elliptical, 60 minutes, 4 miles : 4 mph : 8.3 METS
  • Jon: Running, 30 minutes, 3.5 miles : 7 mph : 11.5 METS

To calculate the score, we then take: [MET SCORE] * DURATION / 100 = AFP, resulting in:

  • Ellie: 4.98 AFP
  • Jon: 3.45 AFP

To graph various commonly submitted activities to demonstrate a time versus activity score:

Caveat

So, with any system, there are always little details that I wanted to talk about. First, not all workouts are pace dependent, as in there isn’t a distance metric to be kept. In this case, it is tough to gauge appropriate METS, so my plan is to allow the user to input their perceived effort level. You will be able to decide if it was an Easy, Average, or Intense workout, and from that I will attempt to determine a proper MET value.

Another caveat that is simply unavoidable is the fact that MET values are computed from an average across a population, meaning no two people are exactly alike. My true MET level for running a ten-minute mile compared to Ellie’s true MET level are undoubtably slightly different, however that is beyond the scope of my abilities, thus I ask for a little bit of slack. If some workouts are clearly weighted poorly, I’ll be doing some adjustments!

Automation

The last thing I wanted to talk about was how it would actually happen. My plan is to build this feature directly into the tracking system, so that you do not have to do any computations yourself. I plan to fully automate the calculations and present the AFP score for each workout as you submit it. Then, each Wednesday, I will query the database for the users’ AFP score for the week and be able to post a new graph!

Conclusion

This system should allow for an objective way to graph everyone and all of their activities that they do, giving value to harder, more intense workouts, but not discounting people for doing all different types of exercise. I am pretty excited to get to work setting this up, but I REALLY want feedback on this and to discuss any concerns people may have. My goal is to have it ready to go this coming Wednesday!