In the next few years, obesity will become one of the world’s biggest health issues with diabetes cases doubling each year, all over the world. It’s not just the American culture anymore, if you might think so. South-America, Asia and all over Europe we see a massive negative shift in food culture. Making obesity the number one slow-sniper on a global base.
This blog post contains (a part) of the transcript of the presentation I did during the Quantified Self Meetup in Amsterdam, last night. I’ve posted the slides here as well.
Looking back in history, we are on a logical point in the evolution of the machine that is our body. Over the past 100 years, we’ve over-innovated our food culture to match a need that is thought to be necessary.
While the first automobiles took the streets at the end of the 1800’s, it wasn’t until the second decade of the 20th century that a speedometer became a default tool for every automobile. The reason why they were needed was obvious: the technology had improved drastically, making driving a car an activity that no longer was to be done using common sense. People needed some extra tools to control the machine. And since Otto Schulze made the speedometer easy to implement on low costs, it soon became a essential part of driving an automobile and, later on, motorcycles and mopeds.
We are at exactly that point in time when looking at our eating habits. We’ve been shifting our food culture to a point where getting a grip on your eating pattern or habits can no longer be done using common sense by everyone. Yet we decide to control the greatest machine we ever own based on feeling over facts. On the other hand, in the last 5 years, we’ve slowly transformed in the real life cyborgs. Not in a Robocop or The Borg kind of way, but more like these guys:
I like to refer to Foodzy as a company that works with little big data. Bite size data, actually! Foodzy is your personal food journal, and with the apps for iPhone and Android and our website, you are able to keep track of everything you eat and drink. We turn this into a live activity stream and real time dashboards to show you how your day looked, and where you could do better.
So let me share some quick stats on the current state of Foodzy. We were recently named as one of Amsterdam’s hottest startups in Wired’s yearly overview, which is cool, because we like Wired! As some of you might now, Foodzy uses it’s own points systems for keeping track of your intake: bits. One bit is 20 calories, so this way it’s easier to keep track of the daily score. Our users gobbled up an impressive 6.6 million bits or 133 million calories in little over a year.
Of course, intake is just one part of the equation, so that’s why we’ve recently launched a Fitbit integration on top of our already existing Withings body scale connection. Now we can show you how many calories you’ve eaten, how many you’ve burned and how this all influences your weight stats.
I’m really proud of the fact that we recently reached a pretty cool milestone. A few days back we celebrated our millionth check-in on the platform.
All of those lines of data gives us a chance to analyze big chunks of it. For instance, in any given timeframe, if our users had 100.000 liters to drink, 35.000 liters of that was water. And about 14.000 liters was alcohol. Cheers!
This stuff really gets interesting if you zoom in a little bit. If you start looking at it from a personal level, you’ll bump into some pretty fascinating stuff. In preparation to my presentation I started looking at a snapshot of an average week of my data. I noticed something peculiar: while my amount of individual products went down on friday, there’s a jump upwards when it comes to calories consumed. Before I even started to investigate, it hit me: hitting the pub after work on friday usually leads to skipping dinner, but those beers pack some calories!
This got me thinking: exactly how does all the food I eat relate to each other, what does my foodprint actually look like. And this is why I love to call it little big data:
This is a networked graph of the food I had in the past year and which food I had it with on the same day as well. So, the nodes represent food, their size the amount of times I had it and the edges linking nodes represent the amount of times I had them together.
In the end, knowing all this, I had to come full circle. I needed to know just one thing: how big was the chance that I would fall for the traditional dutch pub-combo “beers and bitterballs?”. It turned out that based on my foodprint that chance would be 30%!
That’s not that good. 😉
I guess for me the most obvious next step would be to enable people to set alerts for themselves: give me a warning each time I check in a certain product: “Enjoy a beer or two, but skip the bitterballs, dude”. And since getting healthy can be a group process as well, peer pressure could be generated by alerting your mates that you just checked in a second candybar!
Where do possibilities stop? This is all stil based on data of our own service, but what if we start stacking up other services? I’m a runner myself, mostly in the morning, so it would be fascinating to cross-reference my running data with my caloric activity and weight stats to see how my activities stack up there. Or what about that late night snack? That glass of milk before bed or those crisps you had while watching the match, how do they influence my sleeping pattern?
In the near future we’re looking at the option to integrate Foursquare and it’s restaurant menus, making it possible to check in your meal directly from the menu. However, even more exciting, we could give you tips and hints based on the location your checking in. Imagine Foodzy cross-referencing your Foursquare check-in with your last time you were there, the nutritional value of the meal you had, the average of your consumption for the next day (or the rest of the day) based on your history and your weight stats and eventually advising the best possible choice on the menu.
But even a more proactive approach would be a possible. Connecting your doctor or dietician to your profile, you could create a personalized menu with daily nutritional goals. With each check-in you would be updated on your scores in each area of the menu and Foodzy could create a complete week menu based on your own recipes. Automatically varying with it based on your consumption through the day or week. Based on your personal needs and habits the platform could even help you discover new recipes and food groups.
At Foodzy we don’t believe that getting healthy is about extreme exercise or crash dieting. We don’t even think it’s about avoiding fast food or never eating another cupcake or donut again. We do believe that the first step to a healthy lifestyle is getting insight in what your lifestyle currently embodies.
When it comes to your body, it’s time to start making changes based on insights, not just intuition.
