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Diet tracking does not have to be perfect to promote weight loss

Many scientists and nutritionists have argued that the tedious process of tracking everything one eats and drinks in a day is a vital component of successful weight loss. However, according to a new study published in the journal Obesity, perfect diet tracking is not necessary to achieve significant weight loss.

To assess what the optimal thresholds were for diet tracking to predict three percent, five percent, and ten percent weight loss after six months, the experts enrolled 153 weight loss program participants, who had to self-report their food intake using a commercial digital program. 

“We partnered with WeightWatchers, who was planning on releasing a new Personal Points program, and they wanted to get empirical data via our clinical trial,” said study senior author Sherry Pagoto, a professor of Health Sciences at the University of Connecticut (UConn).

This program is based on a personalized approach of assigning points – including a list of “zero-point foods” – in order to eliminate the need for calculating calories for everything. By using a data science method called “receiver operating characteristics (ROC) curve analysis,” the researchers estimated how many days people needed to track their food consumption to reach clinically significant weight loss.

What the researchers learned 

“It turns out, you don’t need to track 100 percent each day to be successful,” said lead author Ran Xu, an applied statistician at UConn. “Specifically in this trial, we find that people only need to track around 30 percent of the days to lose more than three percent weight and 40 percent of the days to lose more than five percent weight, or almost 70 percent of days to lose more than 10 percent weight. The key point here is that you don’t need to track every day to lose a clinically significant amount of weight.”

Since the goal for a six-month weight loss program is typically between five and ten percent – a range where health benefits have been observed in clinical trials – these findings are highly promising. 

“A lot of times people feel like they need to lose 50 pounds to get healthier, but actually we start to see changes in things like blood pressure, lipids, cardiovascular disease risk, and diabetes risk when people lose about five-to-ten percent of their weight,” Pagoto explained. “That can be accomplished if participants lose about one to two pounds a week, which is considered a healthy pace of weight loss.”

Different tracking patterns yield positive results

The scientists found three distinct trajectories of diet tracking over the six months of the program. In the first one, “high trackers” or “super users” tracked food on most days of the week, and managed to lose around 10 percent of their weight. 

However, many participants belonged to a second category, which started to track regularly, but then their tracking gradually declined, with only one day per week tracked after four months. Nevertheless, these participants still managed to lose about five percent of their weight. Finally, the “low trackers” started tracking only three days a week, and dropped to zero by three months, reaching about two percent of weight loss after six months.

Further research is needed

Clarifying such patterns could help inform future weight loss programs that could be tailored to improve user tracking based on which group they belong to. However, future research is needed to better understand why these patterns arise and develop efficient interventions to improve outcomes.

“For me, what’s exciting about these digital programs is that we have a digital footprint of participant behavior. We can drill down to the nitty-gritty of what people do during these programs. The data can inform precision medicine approaches, where we can take this data science perspective, identify patterns of behavior, and design a targeted approach,” Xu explained.

“Before, it felt like we were flying in the dark or just going by anecdotes or self-reported measures, but it’s different now that we have so much user data. We need data science to make sense of all these data. This is where team science is so important because clinical and data scientists think about the problem from very different perspectives, but together, we can produce insights that neither of us could do on our own. This must be the future of this work,” Pagoto concluded.

By Andrei Ionescu, Staff Writer

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