MSGID: 1:317/3 6482ab0f   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    Diet tracking: How much is enough to lose weight?    
    'You don't need to have perfect tracking every day to lose a clinically   
   significant amount of weight'    
      
     Date:   
         June 8, 2023   
     Source:   
         University of Connecticut   
     Summary:   
         Keeping track of everything you eat and drink in a day is a tedious   
         task that is tough to keep up with over time. Unfortunately,   
         dutiful tracking is a vital component for successful weight loss,   
         however, a new study finds that perfect tracking is not needed to   
         achieve significant weight loss.   
      
      
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   FULL STORY   
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   Keeping track of everything you eat and drink in a day is a tedious task   
   that is tough to keep up with over time. Unfortunately, dutiful tracking   
   is a vital component for successful weight loss, however, a new study in   
   Obesity finds that perfect tracking is not needed to achieve significant   
   weight loss.   
      
   Researchers from UConn, the University of Florida, and the University   
   of Pennsylvania tracked 153 weight loss program participants for six   
   months where users self-reported their food intake using a commercial   
   digital weight loss program. The researchers wanted to see what the   
   optimal thresholds were for diet tracking to predict 3%, 5%, and 10%   
   weight loss after six months.   
      
   "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," says co-author and Department of Allied Health Sciences   
   Professor Sherry Pagoto.   
      
   Pagoto explains that the new program takes a personalized approach to   
   assigning points including a list of zero-point foods to eliminate the   
   need for calculating calories for everything, "Dietary tracking is a   
   cornerstone of all weight loss interventions, and it tends to be the   
   biggest predictor of outcomes. This program lowers the burden of that   
   task by allowing zero-point foods, which do not need to be tracked."   
   Researchers and developers are seeking ways to make the tracking process   
   less burdensome, because as Pagoto says, for a lot of programs, users may   
   feel like they need to count calories for the rest of their lives: "That's   
   just not sustainable. Do users need to track everything every single day   
   or not necessarily?"  With six months of data, Assistant Professor in   
   the Department of Allied Health Sciences Ran Xu was interested to see   
   if there was a way to predict outcomes based on how much diet tracking   
   participants did. Ran Xu and Allied Health Sciences Ph.D. student Richard   
   Bannor analyzed the data to see if there were patterns associated with   
   weight loss success from a data science perspective.   
      
   Using a method called receiver operating characteristics (ROC) curve   
   analysis they found how many days people need to track their food to   
   reach clinically significant weight loss.   
      
   "It turns out, you don't need to track 100% each day to be successful,"   
   says Xu. "Specifically in this trial, we find that people only need   
   to track around 30% of the days to lose more than 3% weight and 40%   
   of the days to lose more than 5% weight, or almost 70% of days to lose   
   more than 10% weight. The key point here is that you don't need to track   
   every day to lose a clinically significant amount of weight."  This is   
   promising since Pagoto points out that the goal for a six-month weight   
   loss program is typically 5% to 10%, a range where health benefits have   
   been seen in clinical trials.   
      
   "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 5-to-10% of their weight," says Pagoto. "That can   
   be accomplished if participants lose about one to two pounds a week,   
   which is considered a healthy pace of weight loss."  Xu then looked at   
   trajectories of diet tracking over the six months of the program.   
      
   The researchers found three distinct trajectories. One they call high   
   trackers, or super users, who tracked food on most days of the week   
   throughout six months, and on average lost around 10% of their weight.   
      
   However, many participants belonged to a second group that started   
   tracking regularly, before their tracking gradually declined over time   
   to, by the four- month mark, only about one day per week. They still   
   lost about 5% of their weight.   
      
   A third group, called the low trackers, started tracking only three days a   
   week, and dropped to zero by three months, where they stayed for the rest   
   of the intervention. On average this group lost only 2% of their weight.   
      
   "One thing that is interesting about this data is, oftentimes in the   
   literature, researchers just look at whether there is a correlation   
   between tracking and overall weight loss outcomes. Ran took a data   
   science approach to the data and found there is more to the story,"   
   Pagoto says. "Now we're seeing different patterns of tracking. This will   
   help us identify when to provide extra assistance and who will need it   
   the most."  The patterns could help inform future programs which could   
   be tailored to help improve user tracking based on which group they fall   
   into. Future studies will dig deeper into these patterns to understand   
   why they arise and hopefully develop interventions to improve outcomes.   
      
   "For me, what's exciting about these digital programs is that we have   
   a digital footprint of participant behavior," says Xu. "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."  Digitally delivered health programs give researchers   
   multitudes of data they never had before which can yield new insights,   
   but this science requires a multidisciplinary approach.   
      
   "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," says Pagoto.   
      
   Xu agrees: "From a data science perspective, machine learning is exciting   
   but if we just have machine learning, we only know what people do, but we   
   don't know why or what to do with this information. That's where we need   
   clinical scientists like Sherry to make sense of these results. That's   
   why team science is so important."  No longer flying in the dark,   
   these multi-disciplinary teams of researchers now have the tools needed   
   to start tailoring programs even further to help people achieve their   
   desired outcomes. For now, users of these apps can be assured that they   
   can still get significant results, even if they miss some entries.   
      
       * RELATED_TOPICS   
             o Health_&_Medicine   
                   # Diet_and_Weight_Loss # Obesity # Fitness #   
                   Diseases_and_Conditions   
             o Plants_&_Animals   
                   # Food # Extinction # Biology # New_Species   
       * RELATED_TERMS   
             o Hyperthyroidism o Weight_Watchers o Dieting o   
             Anti-obesity_drug o Weight_training o Weight_machine o   
             Birth_weight o Telomere   
      
   ==========================================================================   
   Story Source: Materials provided by University_of_Connecticut. Original   
   written by Elaina Hancock. Note: Content may be edited for style and   
   length.   
      
      
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   Journal Reference:   
      1. Ran Xu, Richard Bannor, Michelle I. Cardel, Gary D. Foster, Sherry   
         Pagoto. How much food tracking during a digital   
         weight‐management program is enough to produce clinically   
         significant weight loss? Obesity, 2023; DOI: 10.1002/oby.23795   
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   Link to news story:   
   https://www.sciencedaily.com/releases/2023/06/230608120944.htm   
      
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