Colorful foods improve athletes’ vision
Visual range is a critical asset for top athletes in almost any sport
Peer-Reviewed PublicationNutrition is an important part of any top athlete’s training program. And now, a new study by researchers from the University of Georgia proposes that supplementing the diet of athletes with colorful fruits and vegetables could improve their visual range.
The paper, which was published in Exercise and Sport Sciences Reviews, examines how a group of plant compounds that build up in the retina, known as macular pigments, work to improve eye health and functional vision.
Previous studies done by UGA researchers Billy R. Hammond and Lisa Renzi-Hammond have shown that eating foods like dark leafy greens or yellow and orange vegetables, which contain high levels of the plant compounds lutein and zeaxanthin, improves eye and brain health.
“A lot of the research into macular lutein and zeaxanthin has focused on health benefits, but from a functional perspective, higher concentrations of these plant pigments improve many aspects of visual and cognitive ability. In this paper, we discuss their ability to improve vision in the far distance or visual range,” said lead author Jack Harth, a doctoral candidate in UGA’s College of Public Health.
Visual range, or how well a person can see a target clearly over distance, is a critical asset for top athletes in almost any sport.
The reason why objects get harder to see and appear fuzzier the farther they are from our eyes is thanks in part to the effects of blue light.
“From a center fielder's perspective, if that ball's coming up in the air, it will be seen against a background of bright blue sky, or against a gray background if it's a cloudy day. Either way, the target is obscured by atmospheric interference coming into that path of the light,” said Harth.
Many athletes already take measures to reduce the impact of blue light through eye black or blue blocker sunglasses, but eating more foods rich in lutein and zeaxanthin can improve the eye’s natural ability to handle blue light exposure, said Harth.
When a person absorbs lutein and zeaxanthin, the compounds collect as yellow pigments in the retina and act as a filter to prevent blue light from entering the eye.
Previous work had been done testing the visual range ability of pilots in the 1980s, and Hammond and Renzi-Hammond have done more recent studies on how macular pigment density, or how much yellow pigment is built up in the retina, is linked to a number of measures of eye health and functional vision tests.
“In a long series of studies, we have shown that increasing amounts of lutein and zeaxanthin in the retina and brain decrease glare disability and discomfort and improve chromatic contrast and visual-motor reaction time, and supplementing these compounds facilitates executive functions like problem-solving and memory. All of these tasks are particularly important for athletes,” said corresponding author Billy R. Hammond, a professor of psychology in the Behavior and Brain Sciences Program at UGA’s Franklin College of Arts and Sciences.
This paper, Harth said, brings the research on these links between macular pigment and functional vision up to date and asks what the evidence suggests about optimizing athletic performance.
“We're at a point where we can say we've seen visual range differences in pilots that match the differences found in modeling, and now, we've also seen it in laboratory tests, and a future goal would be to actually bring people outside and to measure their ability to see contrast over distance through real blue haze and in outdoor environments,” said Harth.
But before you start chowing down on kale in the hopes of improving your game, he cautions that everybody is different. That could mean the way our bodies absorb and use lutein and zeaxanthin varies, and it could take a while before you notice any improvements, if at all.
Still, the evidence of the overall health benefits of consuming more lutein and zeaxanthin are reason enough to add more color to your diet, say the authors.
“We have data from modeling and empirical studies showing that higher macular pigment in your retina will improve your ability to see over distance. The application for athletes is clear,” said Harth.
JOURNAL
Exercise and Sport Sciences Reviews
ARTICLE TITLE
A Dietary Strategy for Optimizing the Visual Range of Athletes
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'
Peer-Reviewed PublicationKeeping 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.
JOURNAL
Obesity
METHOD OF RESEARCH
Data/statistical analysis
SUBJECT OF RESEARCH
People
ARTICLE TITLE
How much food tracking during a digital weight-management program is enough to produce clinically significant weight loss?
