Tag Archives: weight loss
Julie Price has been tracking her weight consistently for the last four years. Like many of us, she found that her weight goes up and down depending on various life events. In this talk, presented at the Bay Area QS meetup group, Julie discussed what she’s learned about her weight and what correlates with weight gain and weight loss. Specifically, she focuses on the role of family gatherings, exercise and running races, and how different food and dieting methods either helped of hindered her progress.
We’re excited to have Julie joining us at our 2015 QS Global Conference and Exposition on June 18-20th. Early bird tickets are now available, and we hope you can join us for a great three days of learning, sharing, and experiencing the latest in QS techniques and tools. Register now.
It’s link-apolooza time! Enjoy these great news pieces, blog posts, personal data stories, and visualizations.
Robert Wood Johnson Foundation Launches Initiative to Assess How Data Can Be Used to Improve Health by RWJF Staff. Some exciting news coming out of RWJF this week about their new program to explore how individuals and communities are using health data and information. Don’t forget to read the accompanying blog post to learn more.
“For These Times”: Dickens on Big Data by Irina Raicu. Who knew the philosophical debate on a life governed by measurable facts had such a pedigree!
How and Why We Are Working with the FDA: Background and a Brief Summary of the Recent Meeting with the FDA about the Nightscout Project by Scott Leibrand. We’re big fans of the Nightscout project here at QS Labs. It’s great to seem them moving forward with a productive dialogue with the FDA.
Sir Tim Berners-Lee Speaks Out on Data Ownership by Alex Hern.
The data we create about ourselves should be owned by each of us, not by the large companies that harvest it, Tim Berners-Lee, the inventor of the world wide web, said today.
Sensors and Sensibility by Andrew Leonard. One day we might look back at our fears of insurers nefariously using our data to adjust premiums. Until then, that fear is alive and real. Thorough reporting here from the new Backchannel.
One Quantified Self App To Rule Them All by Chris Roth. As Chris explored the growing QS space and worked on his own open-source logging app he noticed a few things. Read on to see his take on where the space should be evolving.
Quantified Health and Software Apps by Sara K. Moir. What started as a Tweetstorm about her experience with MyFitnessPal expanded into a great exploration about what it means to be a user (and designer) of health behavior tracking tools.
How Text Messages Change from Dating to Marriage by Alice Zhao. Only a data scientist would celebrate a six-year anniversary with a thoughtful and thorough analysis of their communication. Alice did a great job here showing what’s changed over the years as her and her husband have moved from courtship to marriage.
Losing 58.3 Lbs For Science by Zachary Townsend. Zachary just finished up his participation in the One Diet Does Not Fit All: Weight Loss study. Over the last year he’s lost nearly 60lbs and learned a lot about himself and his diet.
Using JSL to import BodyMedia Fit Activity monitor data into JMP by Shannon Conners. We featured Shannon’s amazing visualization work in our September 20th edition of What We’re Reading. She returns here with a thorough how-to on how to explore BodyMedia and MyFitnessPal data in JMP. Even as a non-JMP user I was delighted to find out about the MyFitnessPal Data Downloader Chrome Extension she used to download her meal data.
My Up Skyline for the Week by Abe Gong. Abe is a data scientist at Jawbone was taking a look at his own activity data and decided to use the then new Jawbone API to download his data and make some interesting visualizations.
Your Life on Earth by the BBC. Not a typical QS visualization, but unique and interesting to see what’s happened in and around the world over the course of your life.
I’ve been exploring upgrading my data visualization skills by learning D3. If you’re in the same boat or want know someone who is then you can point them towards this great intro from the engineers at Square.
From the Forum
Today’s Number is 35: The age of the spreadsheet!
Rosane Oliveiria is a researcher and scholar that focuses on integrative medicine, genomics, and nutrition. She’s also an identical twin. In 2012 she was struck by the different patterns of weight fluctuations that she and her sister, Renata, had been experiencing. Using historical data and medical records she was able to go back in time and track their paired histories, dietary changes, and blood markers. Rosane and Renata started adding to there data-rich story by exploring genetic testing, additional biomarkers, and are looking to incorporate activity and microbiome data in the future. Watch her presentation, from the 2013 Quantified Self Global Conference, to learn more about this interesting quantified double self story.
Maria Benet began tracking her activity a few years ago as a way to lose weight and take control of her health. What started with a simple pedometer and a few custom Access databases has morphed into a multi-year tracking project that includes news apps and tools. Her progress and data has even spurred her on to new experiences and athletic endeavors. Watch her talk, filmed at the Bay Area QS meetup group, and read the transcript below.
(Editors Note: We’re excited to have Maria attending the 2014 Quantified Self Europe Conference where we hope to hear an updated version of this wonderful talk.)
What did I do?
Hi, my name is Maria Benet and I am happy to tell you that only about two-thirds of me is here to talk about my tracking project. I mean that literarily, because in the 10 years since I’ve been self-tracking I lost over 50 pounds while getting fitter.
In my early 50s, I was overweight, out of shape, with bad knees, and when not cranky, depressed. I was already on meds for high blood pressure and was looking at the prospect of more prescriptions down the road.
So, what did I do to change my situation? I set about tracking my activity levels, my weight and my food intake with the help of apps, wearable devices – plus — in databases and Excel spreadsheets that I designed. Until late 2011, I tracked inconsistently, but once I discovered mobile apps and wearable devices — I became more systematic and consistent about tracking weight, food intake, and fitness data.
How did I do it?
When I first started — losing 50 pounds seemed daunting, but going for a walk at least 5 days a week seemed less formidable. To track walks I was going to take in the hilly neighborhood where I live, I created a simple Access database.
I bought a pedometer, hiking shoes, and off I went. After walking, I recorded the duration, the number of steps, and calculated the distances I covered. I also charted my routes by naming the streets, and made notes about the weather and my mood during the walk.
Recording the data turned out to be a form of reward in itself. At the start of this tracking project, I enjoyed seeing the database grow a little more than I enjoyed the actual walks themselves.
Over time, the walks got longer, steeper, and eventually included actual hikes. I also took up the practice of Yoga regularly, and then added Pilates to my exercise repertoire.
Along the way, I also started to lose weight. Though I didn’t weigh myself every day, I began to pay attention to the kinds of foods I ate and tried to wean myself off processed foods in general.
They say you get fit in the gym, but lose weight in the kitchen. In September 2011, when I discovered LoseIt, it became my virtual kitchen: LoseIt helped me see what foods I ate regularly, which of these spiked my weight, even if my calorie intake stayed the same. I noticed these relationships anecdotally, rather than by finding statistical correlations between them.
Tracking in LoseIt helped me realize that as much as I love bread and beer, they are not my friends. Two years ago, an allergist confirmed my wheat sensitivity through blood tests and an elimination diet.
I added Endomondo to my tool box a few months later, since I liked having the maps and stats it offered, in addition to the other data it showed. By December I also added a Fitbit, as with it I could track more accurately how many steps I took and approximate better the number of calories I burned. The Fitbit was like going back to the pedometer, but to one on steroids.
With the Fitibit, I focus mostly on the Very Active Minutes it claims to measure. Increasing that number over time became a game. In 2012, I was averaging about 57 minutes a day, which put me in the 98th percentile. Increasing to 69 minutes only brought me to the 99th percentile, as the Fitbit population also has increased over time.
The Fitbit turned out to be a catalytic tool, because it spurred me on to push the perceived limits of my fitness abilities and possibilities further. It ended up putting wheels under my dreams.
In the spring of 2012,I took up cycling to increase my active minutes and challenge a mental habit of opting out of things because of a fear of failure or thinking of them as not age appropriate. Biking, in turn, added to my collection of gadgets and apps for tracking the metrics involved.
By 2012 then, in addition to LoseIt and Fitbit, I was tracking workouts with a Garmin GPS watch with a HR monitor and my bike rides with a Garmin Edge computer, uploading the data to the Garmin site, to Endomondo and Strava, as each had strengths the other lacked, from my perspective.
To complicate data gathering, back in January 2012, I started a basic Excel spreadsheet that tracks highlights from each of these apps in an application-independent reference for me. In Excel I track the type of activity, duration, distance, if applicable, average and maximum heart rate, Strava suffer points, (a measure of exertion), the hours I slept and how that sleep seemed to me, and additional notes about the day I might think relevant.
The plethora of my gadgets and apps might earn me an entry into the next edition of The Diagnostic and Statistical Manual of Mental Disorders. But exploring these tools was, and still is, my way of looking for a comprehensive and personalized way to track the quantities in my habits and activities that make for a qualitative difference in my life … which brings me to what I learned so far:
What did I learn?
I learned that small quantitative changes in particular daily habits add up to a big difference in quality of life in general.
The incremental additions in my tracking methods and number of gadgets I added produced a lot of data, which I haven’t analyzed closely, because I was already getting a lot of return from them in the form of new experiences in my life.
The most memorable of these experiences is my having completed the metric century ride on the Tour de Fuzz in Sonoma last September. In the space of a little over a year I went from covering barely 8 miles in an hour on my first rides to completing 63 miles in 5 and ½ hours and feeling ready to ride a lot more.
It has been said that motivation is what gets us up and going, but it’s habit that keeps us going. So it is with my tracking: though the motivation was to lose weight, the habit of tracking and keeping an eye on the numbers are what allowed me to go from daily small changes to a much bigger transformation from the overweight, depressed, and achy person I was 10 years ago to who I am now: someone interested in health and fitness and setting goals I can meet.
I learned that for me the act of tracking is the project itself. Although the data I generate can be charted and described in numerical relationships the number that brings me the information that makes a difference in my life, is a simple 1 – or tracking one day at a time.
I love to see the numbers my Garmin and Fitbit generate, but in the end, the quantified self for me is not so much about the measured life as it is about keeping those numbers coming through a well-lived and, more importantly, well-enjoyed life as I go from my fitter fifties into what I hope will be my sounder sixties.
Duane Hewitt gives an update on his 23&Me data and what he’s started doing since he received his results.
Dmitri Gomon describes how he tracked his way to losing 9kg over four months.
Jim gave a brief overview of how and why he’s tracking his Starbucks intake.
It seems that food tracking can have an enormous impact on weight loss and weight control, but counting calories can be difficult. David Sweet was looking to lose weight and wanted to use a system that kept him engaged for a long period of time. He devised a unique system to track his food – the Fist-Sized Volume. Watch this interesting talk, filmed at the New York QS Meetup, to learn how he did it and what he learned (stick around for the great Q&A).
We’ve covered weight tracking here many times. It’s a very popular topic, and one of the easiest ways to get started with self-tracking. In this insightful talk from Matthew Ames we learn how weight tracking, in conjunction with diet and activity tracking, positively impact his weight loss and improved his fitness. (filmed at the Boston QS Meetup).
John Schrom is a data scientist, graduate student, and avid self-tracker. After taking a look at his historical weight data he decided to dig a bit deeper into the story. Luckily, in addition to collecting his weight (via a Withings scale), he’s also been using Foursquare to collect his geolocation history. With these two data sources in hand he asked himself, “What kind of places do I visit when I’m gaining or losing weight?” Watch this great talk talk recored at the Bay Area QS Meetup to learn how he used association rule mining to explore his data, and what he found. When you’re done with the video make sure to go and read his excellent write-up here.
“I was starting to feel a little bit out of control.”
Robert Carlsen used to be an amateur bike racer. When he moved to New York and stopped racing he found that his weight was slowly creeping up. He was still leading an active lifestyle, but he soon realized that most of daily food choices were the result of guess work. In this video, filmed at the New York City QS Meetup, Robert explains how he used different apps and tools to track his caloric inputs and outputs in order to move towards his goal weight.
Some people may be wondering how I find all the amazing people conducting neat self-tracking experiments and creating jaw-dropping personal data visualizations. Well, for the most part I just listen. I’m constantly paying attention to what’s being said on twitter about #QuantifiedSelf. When that doesn’t work I just use the power of Google to find people who are blogging about self-tracking, self-experimentation, or personal data. It’s great to look through the search results and see how many people are sharing their personal stories and insights. While doing some searching this morning I stumbled across a project that immediately brought a smile to my face. Hopefully you’re excited by this as much as I am.
Chris Volinsky is a statistician at AT&T Research and he’s no stranger to handling large data problems. Back in 2008 he was part of the team that won the $1 Million Netflix prize. He also has quite the impressive list of research papers that illustrate the many different uses of cellphone location data. But what is really interesting about Chris is his newest project: My Year of Data
Back in November of 2011 Chris started off a blog entry that with this:
My name is Chris. I am 40 years old. I am 5’9 1/2″ and weigh 174 pounds. I walked 9,048 steps and have consumed 1,406 calories today (so far).
Realizing that he’ld been gaining weight and wasn’t at his optimal health he decided to take a data-centric approach to improving his health. He is a statistician after all. So far, he’s found some interesting things. Take for instance his weight and dietary tracking.
As he explains in this post, Chris typically has a hard time tracking his diet consistently. This can be pretty frustrating when you hear about how important it is to eat this or not eat that to help with weight reduction. Rather than get frustrated Chris turned to the data to see what he could learn. When he stopped looking at the data he was entering and started looking at the missing data an interesting trend lept out. He found that fluctuations in his weight appeared to be correlated with whether or not he was logging food. Take for instance the plot below. It appears that there is a pretty clear association with periods of weight loss and periods of actively logging his food (pink zones). The opposite also appears to be true – no food logging = weight gain.
So this is where a typical NFATW post would stop. We have an interesting finding and a neat data visualization. But, Chris is doing something much more interesting than just talking about his weight data. He is on a long-term self-tracking and self-discovery journey and he is trying to enlist other interested parties to help him. Chris is going the extra step and posting all of his self-tracking data online for anyone to analyze, visualize, or just get inspired.
You can access all of his amazing data via a public dropbox folder that he’s set up. He even has a nice README file explaining the datasets and formats. So far he’s sharing the following:
- Fitbit: sleep and activity data
- FitLinxx: weight training data from gym activities
- Livestrong: dietary tracking data
- Runkeeper: running and other exercise activity data
- RescueTime: productivity tracking (computer/internet use)
All the data is open and available for you to play with. This should be a really interesting project to keep “track” of in the future (pun definitely intended). To help inspire some action on your part I took some time today and looked at Chris’s most recent available data to see what I could find out. I downloaded his Fitbit data and decided to look for any interesting patterns. Turns out that when taking a look at his daily patterns of activity there seems to be something going on on Thursdays that reduces his step count and activity time . Also, Saturday is by far the best day with an average of 9,862.56 steps and a 5.3 hours spent being active (data available here).
Make sure to reach out to Chris over at his blog and take a took at his data to see what interesting thing you can figure out!
Every few weeks be on the lookout for new posts profiling interesting individuals and their data. If you have an interesting story or link to share leave a comment or contact the author here.