One year later, we're revisiting some of the aggregated data we've generated via the Lose It! app. See the 2014 write up here. Consider this a 7-year test of whether or not the Lose It app functions as a weight loss instrument for someone who exercises regularly.
I'll ruin any suspense early: it does.
What we'll be doing differently here is ignoring the type of exercise done (which, Lose It the app doesn't really care about anyway; converting all work into calories expended). If we were doing hypertrophy work, we'd expect some weight gain. If we were doing more endurance work, we'd expect muscle loss, and therefore, weight loss. Maybe. But we're also not going to have any composition data to compare in this set up. Bodyfat up or down? We'll not know.
Optimally, we want to compare Bodyweight/Bodyfat to total food intake, with a macros breakdown, and an additional layer comparing total work volume done; and that, by work type - perhaps broken down by energy system.
Lose It! assumes that the user wants to lose bodyweight, and simply assumes that the less you eat, the less you'll weigh. Which is true; if you eat nothing, soon you'll weigh as much as worm shite since you'll be dead. Lose It does compute work calories by subtracting them from your daily total ingested. So if you work more, you get to eat more that day without going over your daily "limit." So we can examine those three factors while using the app - Bodyweight, Calories ingested, and Calories expended through exercise.
We've got 7 years of tracking, with a two-year hiatus hole in the middle where I didn't do any logging. Let's just look at the graphed data overlays and see what they suggest. First, we compare Bodyweight to Calories ingested:
...and see no real correllation. Late in the graph, we see that where the purple calories are up, weight goes down. Not what one might expect at all, right?
There's those two peaks on the right, where calories dipped and bodyweight dipped correspondingly by about 8-9 pounds, but generally, there's 3 years worth of plateau-ed intake with inexplicable BW change.
Compare the same Bodyweight chart, but now to an overlay of Calories expended during exercise.
Before the hiatus, we see low BW when calorie expenditure via exercise is high, and a general BW climb when exercise calories are lower. After the hiatus, exercise climbs and BW drops - still what the general consensus would presume. Especially since we aren't comparing intake as well.
So, let's add that. The three factors compared:
Which is messy. Cut to the chase. Here's where Lose It shines. The app takes the Calories In for the day minus Calories Out and ka-smushes them, into total Calories over or under your daily limit (which is the red line below, each data dot is a monthly average either above or below the limit line).
Very nearly a direct relationship between calories over showing as bodyweight gain, and calories under showing as bodyweight loss. Even with exercise type, and any macros breakdown, removed from the equation, the Eat-to-Work-to-Bodyweight math works within the limits of the app.
If you'll notice, there's also a month of lag-time along the rise and fall of the graph - maybe I have to undereat for a couple of months before my body decides it's going to be losing weight. The same happens when gaining. A visual reminder to me: whether cutting or building, have patience in the programming.
Sometimes there's truth in the data, sometimes it's interpretation. I pulled up my data from the lose it app; what I have is a full year of dedicated logs, then a year off with no data, then the last 6 months of renewed religious logging.
Now, lose it considers calories the fundamental unit for nutritional measurement. Here, we'll disprove that notion - basing our nutritional breakdown on the gram with our macronutrient bias. But remember that lose it loves calories, so that skews the way the following data is presented.
For instance, I'm interested in a macro comparison, but below the three macros are measured as a percentage of total caloric intake, rather than in total grams/day. I'd rather see it as total grams ingested, but it's a free app and you get what you pay for.
Each dot is a monthly average.
The first thing we see is that singular surprise of a first month journaling my macros, way back in 2011 when I thought that I was a carnivore, but was really a carbivore. That first pink dot at left representing protein is just above 20% - while 27% of my intake was carb-based. I reversed that pretty quickly (and dramatically, by the third month - note that the scatter pattern is more widely distributed than the lined-average), but by mid 2012, I'd gone back to my old carb-heavy consumption.
By comparison, during the second data set beginning in late 2013 after the hiatus during early 2012 thru mid 2013, I rebooted with carbs down in the 20% range, and protein intake averaging in the 35%'s.
Okay, set that knowledge aside for a minute. This next graph shows that there's no direct relationship between my bodyweight (blue line) and total calories (green bars). During the first data set, calories hold pretty steady, but bodyweight dips and then climbs. During the second data set, bodyweight drops steadily while caloric intake increases. This is the opposite of the common consensus that to lose weight you eat less, and to gain weight you eat more.
In the next graph, we add Exercise calories as another data layer. Hopefully, you can easily see the relationship one might have anticipated between food and weight demonstrated more directly in the relationship between calories expended and bodyweight: in 2011, weight was lowest just when exercise was highest, and as exercise dropped off, weight increased. In the second data set, weight declined as exercise increased.
Whoopdeedoo. Everyone knows that you'll lose weight if you exercise. However, when the general population hears the word exercise, the definition cardio is subbed in. What the graphic doesn't convey is the nature of the exercise. During the second data set, the exercise is primarily heavy 531 and Hypertrophy work. Muscular density and growth. During that second data set in early 2014, see how caloric intake is approximately 700 calories higher than at any other time, while exercise levels are generally lower (allowing for the March 2014 spike) - one would expect bodyweight to have increased during this time. But it falls by 7 pounds. Body measurements during this time clearly show that the weight lost was core fat, with extremity and muscle mass actually increasing.
Want to lose fat? Cardio isn't the sole cure you thought it was. Lift yourself thin! My new book. Just won't sell, it's too counterintuitive.
Let's go back to our original macros graph and layer that in. What we see, besides a muddied mess, is a coincidental relationship between protein intake and bodyweight - where BW is lowest in 2011, we also see the highest level of protein intake for the first data set, and the widest gap between protein intake and carb intake. As carb intake climbs and protein intake declines, BW also climbs. And (conjecture here) with lower exercise levels and total caloric intake at constant levels, the BW gained is fat weight rather than muscle.
If there's one takeaway today, it's that what you eat is more telling than how much you eat.
You can eat like a pig and work like a horse and still lose bodyweight (read: bodyfat). If. If protein is high, carbohydrates are low, you have bodyfat to lose that can provide the caloric deficit that the exercise creates.
One truth for me at least: I weigh less when I eat protein and lift heavy. Suck on that vegan yoga masters everywhere.
What else seems bubble to the surface here? One, that protein intake is more key than carb intake. It's easy to vilify carbos and try to avoid them, but I see that my bodyweight drops when protein intake is highest. A subtle shift in focus, but if I'm full of protein, I won't be hungry for carbs. So, less focus on the negative (avoid carbs!) and more focus on the positive (devour brontosaurs!).
Two. The data suggests that I can maintain high output levels on a high protein/lower carb mix. Just because I feel sluggish when I'm overreached doesn't mean that I should throw more carbs into my diet. I should just eat more protein.
There are a few questions raised from this:
Early success in 2014 only possible because there was lots of stored fat to burn gained during the 2013 blackout?
At what bodyfat % level does the BW loss stop its downward trend?
Intermittent Fasting isn't graphed here - how much influence does nutrient timing have in all this?
Time for more experimentation. Time will tell.
Before the hiatus, we see low BW when calorie expenditure via exercise is high, and a general BW climb when exercise calories are lower. After the hiatus, exercise climbs and BW drops - still what the general consensus would presume. Especially since we aren't comparing intake as well.
