How Big Data and Fitness Apps Change Our Perceptions of Health

i-heartWhen the Supreme Court is deciding on the law, they are of course making their decision based on constitutionality, but that document is deliberately and wonderfully ambiguous. This open-ended nature can lead to interesting interpretations. One branch of jurisprudence where we see this is in interpretations of the 8th Amendment, which speaks against “cruel and unusual punishments,” a truly revolutionary piece ensuring that the state didn’t have total control over the human body. The question is, what constitutes our concept of “unusual?” Our standards have changed over the years, and one thing the courts have taken into account are the general standards of other countries. In this way, we look to others to judge our own nature.

Judging ourselves by how we compare to others isn’t just for Supreme Court judges. We all do it, especially when it comes to health and fitness. Because there is no 100% objective fitness standard, we usually do the eyeball test: does she look fitter than me? Is he more ripped than I am? Will he beat me in the hot dog eating contest? (Note: this isn’t a widely accepted fitness standard).

However, we can now do more than just look people over and hope that we stack up. The rise of Big Data, especially when it comes to mobile and wearable tech in the form of fitness apps, can help us collate what the national standards are and see where we’re going. This is more than just idle curiosity. This is a way to judge our health on a national level in a way that was never before possible.

Fitness Apps and Where Your State Stacks Up

The Healthy Habit Index is a project from MapMyFitness, a company with a series of apps designed to help people track their overall wellness. This project took data from all 50 states and Washington, D.C., and used it to figure out which states were the healthiest and which were the least-healthy. Granted, this was a limited sample size – only the people who use their products – but that is over 30 million people as of 2014. They use an open-source system that is compatible with over 400 fitness apps for both iOS and Android, so just about any mobile tech or wearable tech can feed into their database.

Their survey took into account three major fitness fields:

  • Healthy diet – This involves staying within calorie goals, as well as sugar, sodium, and fiber intake. This is interesting because there isn’t one set standard overall; instead, it uses your own goals as a baseline. These goals are best established with a professional. MyFitnessPal is one of the most popular apps for this, but others include Lose It, Restaurant Counter, and Daily Burn.
  • Exercise – This was measured by length, frequency, and the type of exercise done in each state. This might be ambiguous because different people are capable of doing different types of exercise, and one person’s gentle morning walk can count as much as another person’s CrossFit session. So the data here might not be ideal, but it still gives a rough look. Some of the best fitness apps include MapMyFitness, FitStar, and Fitocracy.
  • Sleeping habits – This one is too often overlooked in our desire to get as much done as possible. Sleep is just as important as the other two, though, and it is a smart thing to include as a gauge of overall health. This measured bedtime and rise time to get an overall sleep average. Some of the top sleep apps include SleepBot, SleepCycle, and Sleeptime, which track your sleeping, but also work to help you get to sleep.

Results and the Power of Big Data

The results? Colorado, Arizona, and California made up the Top 3. Nice work, Bay Area! That’s sort of expected, though. There were some surprises in the top 10, however, with Minnesota, Texas, and Wisconsin rounding out the list. Being a native Midwesterner, that somewhat surprised me, but it also showed why big data is interesting. It used to be really easy to dismiss fitness as a fad, a West Coast thing, but now we don’t have to do that, partly because the enormous surplus of data allows us to get a better sense of what is healthy.

Again, we don’t just have to look at the tautest bodies on the beach (though feel free). We can get a better overall picture, including sleep and diet. You can have hard-charging Type A’s who spend three hours in the gym every day, but never sleep, and have a lot of upcoming problems. You can have someone whose main exercise is a daily walk, but who eats moderately and takes care of themselves, and though you wouldn’t know it by looking at them, they may be far more healthy than most.

This is what our mobile tech and the information revolution can do for us. We don’t have to just look at one standard – the one elevated by the media. We can get a much clearer idea of what it means to be healthy by taking real data from millions of willing people who use that data to see how they are doing and what they need to get better – and what they don’t need. We have all the information in the world at our fingertips, in our smartphones, tablets, and other mobile devices, and at the end of the day, that is way more important for our health than the glistening sweat we see on commercials.

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