Lessons From Food Tracking

Project Infobox
Self researcher(s)	Sara Cambridge
Related tools	the Eatery
Related topics	Food tracking
Builds on project(s)
Has inspired	Projects (0)

Show and Tell Talk Infobox
Featured image
Date	2013/03/22
Event name	Bay Area Meetup
Slides

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Lessons From Food Tracking is a Show & Tell talk by Sara Cambridge that has been imported from the Quantified Self Show & Tell library.The talk was given on 2013/03/22 and is about Food tracking.

Description

A description of this project as introduced by Quantified Self follows:

Sara Cambridge is in her last semester of graduate School of Information. Sarah started tracking food to determine how much raw food she was eating and encourage herself to eat more. She used the Eatery, a crowd sourcing helpfulness rating app to help with her tracking. In this talk, she discusses the lessons she learned from food tracking.

Video and transcript

https://vimeo.com/62746426

A transcript of this talk is below:

Sara Cambridge Lessons From Food Tracking

Hey everybody my name is Sara Cambridge and I am in my last semester at graduate school, I’m at the School of information and I’m taking data visualization classes this semester, and it’s really fun, and I have been designing for many years. So the first week of class he said start tracking something you know about your physical existence and I was like oh that is so painful to tell QS’ers to start tracking data. So I started tracking food and I knew I wanted to track food. I’ve been eating a lot of raw food, and trying to eat more. I mostly eat role in the morning until afternoon. I am not at all concerned with volume or calories, or carbs, so that’s why I chose to use the Eatery, which I’m sure a lot of you are familiar with. It’s a crowd sourcing helpfulness rating app, and I’ve got some screens here. So my goal was to be eating raw until 3 PM or what for whatever reason. But I don’t know if you guys have ever seen it all used it, but the whole thing and this is the interface that you see if ever you are posting and rating your own food, and he is somebody else’s, but this is just little scale down there, and this is what I would see that 10 people have rated my salad as 94 points of health. And this is the extent of their feedback that they give you. So it’s pretty minimum, it’s kind of you know it’s lightweight, but it’s fun and it’s social. So I did this for six weeks and I have 42 days of data, and I was kind of surprised in what was good about using the Eatery is that they have a lot of interesting data that they have collected over the last year. So I was kind of able to compare my findings to them, and bits of interesting insights. The drawback is like I said it’s a little bit lightweight. I have to say I have never used Excel before and this is the first time I have crunched my own data; it’s very exciting. So this is my data that I collected, I just dished the date, the day and the rating and this is the raw data that I got from them, and I needed the raw data and asked them for the raw data, because I had missed a few dates. So when I was going through it I realise that the school that I had been given in the app was different from the school that they were giving me. And I asked them about it, and they said that they have a formula that they put these schools through to jack it up a bit, because people rate the food, and somebody is going to rate that one dish much lower for someone else than they ate it. So in the effort not to demoralize people, they have a little formula, and I have put it in here for you computer scientists if so, you wish to know what it is. So I was like, okay, so never mind, I don’t need to know that kind of stuff. So I had never made a pivot table and I totally love pivot tables now, and fortunately I work with a lot of really smart people who could show me how to do this stuff. So a pivot table, and I was able to sort by you know the helpfulness and the days of the week, and what was the average score, and you know, look at the patterns and that was very cool and fun for me. I made about 20 of these, and then I had to start making sense out of it. So this is the final whole piece that I will show you, and it is actually five separate little vignettes that you will see. So the first one is just kind of like some of the stats. I had 257 food that I submitted, and I weighed 150 pounds at the start. My average helpfulness rating was 70%; I ate better than 78% of the average user, and only 17% better than the average San Franciscan, so that is the fun thing about having their data that I could look at. And an average of 10 people rated every item. So the first thing you are going to see is the top 10 food that I ate more frequently, and I have got them listed pretty much by the time of day I ate them. So the most frequent thing 41/42 days is I’d juiced my own food in the morning and that was pretty awesome. My salad and my dried fruit and nuts, smoothies, dark chocolate and the only thing under 50 is cookies, which I ate a lot at the times. And then there’s a bit of different visualization at the bottom of the frequency of the food that I ate in proportion how I ate them. Okay, so when did I eat healthiest, I ate the least healthiest on Fridays, which made sense because Friday is the most worst day for most people, obviously we are tired and stuff. But on Sunday, I get ate pretty well and most people their worst on the weekends, but I was home studying all day long. So I had nothing to do but make my fresh food and eat them while I was working. This was the most interesting thing for me, how healthy I ate at the time of day. Before 3 PM I had a 92% rating and after 3 PM it was 62%. So my thing was before 3 PM I would eat raw and then I could eat whatever I want. So this is a little bit of the worst food that I ate, peanut butter, cups, milkshakes, chocolate truffles because this was directly Valentine’s Day and other stuff like that. This was also pretty interesting, I found that the low rated food when I ate one on a day and at least two thirds of the time I ate two. So the whole idea of finding that I cannot eat one peanut butter cup or one French fry, so if I’m going to eat them, you know or not eat them. So okay, my final numbers and my main goal was to eat raw until 3 PM and I did that two thirds of the time, and My weight loss two pounds, which doesn’t really matter because it’s kind of in the range of what my weight fluctuates anyway, but nevertheless it was better than being on the other side of that.

So the other thing is kind of when I finished crunching this and one of the things that I learned in crunching data is that the more you look at it you find out about it. Also crunching it you learn a lot about it you wouldn’t otherwise know, and by looking at any Fitbit you know sheet, and since my goal was to eat raw, I actually at my first two meals of the day, which were raw 89% of the time, so that was very impressive to me. And the other thing from the Eatery what I thought was interesting that when any people have any kind of Association with what their diet is, vegetarian, vegan, plant base they are going to eat on average at 15% healthier than people who say they eat everything. So I eat raw until 3 PM, so thanks.

About the presenter

Sara Cambridge gave this talk.