Over the past few weeks, I’ve been more actively reviewing some of the data I’ve collected since 2FNs got started. Last night, I sat down and decided it might be worth a little bit of work to review my weight-loss trend compared to my food-log activity. To describe my question, I wanted to see if the frequency of the entries in my food log could predict or, at the very least, suggest a good or bad weigh-in week based on how many days of the week leading up to Wednesday I recorded my food intake.

Hypothesis: If I keep track of my food intake more frequently during the week, then I will lose more weight come Wednesday morning.

To do this, I looked back into my food logs on my smartphone app and recorded either the presence of an entry for a given day or the absence of an entry for a given day. This has a small caveat, which I may revisit later, in that not all of my entries were for an entire day, some including only breakfast and lunch. If the day had only a breakfast logged, I decided to throw that day out of the count.

The results were pretty interesting. My correlation values seemed lower than I had anticipated, only getting to about 0.48, which clearly suggests that there are other factors going on. But when I graphed the data and assigned one of three categories to each week—either a positive expected outcome, a neutral expected outcome, or a negative unexpected outcome—the results looked a bit more in tune with what I had a firm suspicion of.

Green Dots: Positive Expected Outcome
Yellow Dots: Neutral Expected Outcome
Red Dots: Negative, Unexpected Outcome

Above is a graph with the data. The two series are my weight loss over the past 34 weeks, while the bar graph is the frequency of logging in the seven days prior to the weigh-in. There are seventeen weeks that I felt were positive expected outcomes, where I lost an appropriate amount of weight based on the frequency of food logging. There were ten weeks that met my expectations of a neutral expected outcome. Neutral expected outcomes are results that I felt made sense based on my lack of logging and lack of weight loss. That accounts for 27 out of 34 weeks, or 79.4 percent of the data followed what I expected to see. There were six weeks that I felt bucked the expected trend in that I lost weight when there was no food log present or that I gained weight when I had food-log counts.

I know my approach is a little bit subjective and possibly is biased to demonstrate what I expected to see, but I don’t think it is too far off base. In short, I simply wanted to know if there was any visible trend or relationship between logging my intake and the amount of weight I can expect to lose.

To sum up, I think food logs really do help quite a lot; if you don’t believe the data, I urge you to try it out yourself. Maybe it is just a mental trick, but if it works for you, does it matter? On a side note: I may revisit this topic again with more stringent criteria for classification, and mainly to add in workout information to the mix.