Research Review: Food photos, exercise, and appetite
Our visual response to food is governed by a complex interplay of neurology. The more responsive your brain is, the more likely you are to overeat. However, exercise might help by moderating our drive to eat in response to pictures of food.
Exercise, appetite, and weight management
Exercise is a great way to improve your health and counteract some of the effects of overeating. But exercise alone won’t help you lose much weight.
Move more to weigh less may sound like great advice, but things are a bit more complicated than that. Many factors besides exercise can influence weight loss. One of those factors is your appetite or your desire for food.
Ap-pe-tite (noun): An instinctive physical desire, especially one for food or drink.
Of course, feeling hungrier and acting on that feeling are two different things. So the question becomes: To what degree do people who exercise compensate for their increased energy expenditure?
One way of compensating is to cut down on spontaneous non-exercise related activity following exercise. This compensatory mechanism was a matter of speculation in Exercise Less, Lose More Weight? What’s the Minimum Effective Dose?.
Another way of compensating might be by eating more. Studies have shown that there’s a huge amount of individual variability in what and how much people eat when they exercise (1). For some people, exercise helps to control appetite while for others, it seems to do the opposite.
So in this review, we’ll consider the role of appetite, or our drive to eat. What factors influence that drive – and can our appetite be overridden?
Why it’s tough to determine the effect of exercise on appetite
Research on the effect of exercise on appetite and energy intake is inconsistent at best. And really, it’s no wonder, since there are so many variables to account for: type of exercise, intensity, duration, age, gender, weight, what food was eaten the day before, the hour before, what type of food – you get the idea.
Not only that, but measures of appetite and exercise intensity are usually subjective. “Man, I am starving,” or “I worked out so hard I could puke.”
Okay… maybe the researchers can get a little more specific than that, but the problem remains: subjective measures don’t always tell us a lot.
The brain’s response to food
That’s why scientists have been looking for a more objective measure. Recently, rather than relying on subjects’ reports of how hungry they feel, several studies have measured brain wave activity in response to pictures of food.
Researchers have used this information to create a measurement called “food motivation” or a person’s attentional response to food (2). They hope that gathering objective data on a person’s food motivation could provide a way to predict their energy intake.
Confirmation for this idea comes from another recent study that discovered people’s conscious feelings of hunger didn’t predict the number of snacks they ate. A better predictor was what was happening in their brains’ reward centres.
The higher the brain response in the reward centre, the more they ate. Not only that, but in people with reported low levels of self-control, this was a double whammy and was associated with a higher BMI (3).
EERRRPPPP…..Oh my! Excuse me!
Event-related potential (ERP). No, we don’t mean the chance of meeting the man or woman of your dreams at your friend’s wedding.
An ERP is a measurement of brain electrical activity that’s linked to an external stimulus such as a picture or tone.
ERPs respond in milliseconds and are fairly easy for researchers to measure with scalp electrodes. (Yay! No need for lobotomies!)
One particular type of ERP is called late positive potential (LPP). LPP is associated with tiny brain wave changes elicited by emotional stimuli.
Previous studies have shown that LPP amplitudes are higher when hungry people look at pictures of food than when they look at pictures of flowers (2).
Food motivation, exercise and BMI
Unfortunately, measuring the brain response to food images still doesn’t explain why some people overeat and others don’t.
But comparing brain activity in overweight versus normal weight people could provide some additional clues, because weight affects levels of the appetite-regulating hormones leptin and ghrelin.
However, complicating this picture is the fact that some people seem to be able to override their desire to eat, which was the focus of a study that looked at BMI, snacking, and self-control (3).
And then when we bring exercise back into the picture, this raises even more questions.
For example, do normal weight people have a different brain response to food cues after exercise then overweight people?
Finding answers to these questions is what this week’s research review is all about.
This week’s research review investigated how the brain responds to pictures of food after a moderate-to-vigorous exercise session.
The researchers wanted to see if the BMI of a person (in this case, the subjects were women) affected the brain response. They also wanted to find out how the bout of exercise affected the level of physical activity and the food intake of the subjects during the rest of the day.
Hanlon, B., Larson, M.J., Bailey, B.W., Lecheminant, J.D. Neural response to pictures of food after exercise in normal-weight and obese women. Med Sci Sports Exerc. 44(10):1864-1870, October 2012. doi: 10.1249/MSS.0b013e31825cade5
The study used a quasi-experimental crossover design. A quasi-experimental design differs from a “true” experiment because it is missing one of the following:
- a pre-post test design;
- a treatment group and a control group; or
- random assignment.
In this case, the missing ingredient was random assignment of the participants.
An advantage to this design is that it is a useful method for identifying trends. A disadvantage is that without randomization there may be other factors that explain differences found between the groups.
However, as long as the limitations are recognized, the method is a good way to obtain some baseline information. If researchers identify trends, they can explore these trends further using more rigorous experimental designs.
To minimize the limitations of this type of protocol, the researchers used a crossover matched subject design with the order of the experimental conditions (non-exercise, exercise) balanced.
It looked something like this:
Group 1→Treatment A→ Treatment B→ Posttest
Group 2→Treatment B→ Treatment A→ Posttest
Each participant completed both the exercise and non-exercise experimental condition separated by 7 days. Participants were followed for 24 hours during each condition and identical outcomes were assessed.
The participants in the study were 35 women who were classified as normal weight (n=18, BMI30 kg/m2).
None of the women were active. (For the purposes of this study, “active” was quantified as more than 20 minutes of activity 3 days a week.) Despite this lack of activity, they were able to walk on a treadmill for 45 minutes at a moderate-vigorous level.
The women selected were in their 30s and went through screening for a whole host of health conditions. Thus, whether normal weight or obese, they were considered to be “healthy” subjects by the researchers.
For each of the experimental conditions, testing was done on the same day of the week, at the same time, and after at least 7 hours of sleep. The participants were told not to exercise or use caffeine in the 24 hours prior to testing.
On the morning of testing and 2 hours prior to the protocol, they were given a small meal (~10% of daily total calories) described as an “energy shake.” The shake ensured that testing would be done in a fed state.
The contents of the shake were not listed but I am curious as to the ratio of carbohydrates versus protein. This ratio could affect their hunger levels post-exercise.
Non-exercise condition – The “control intervention” consisted of no supervised exercise. When the participants went to the lab, their body composition was assessed (height, weight, % body fat) and then they began wearing an accelerometer that measured all of their movement. After the measurements, they completed a computerized task (viewing pictures of food and flowers) while wearing electrodes strapped to their heads to measure brain waves (more on this in a minute).
Following this task, they were sent home wearing the accelerometer, told to record everything they ate and drank, and asked to resume normal activities. They would return to the lab in 24 hours.
Exercise condition – The exercise condition was identical to the non-exercise condition except that instead of having their body composition assessed, subjects walked on a treadmill at 3.8 mph at 0% grade for 45 minutes.
This is a pretty good clip for women who were not active, and probably a bit of a challenge for the ones who were obese. However, the intensity and duration of this exercise protocol wasn’t just pulled out of a hat. Instead, it was based on recommendations from the American College of Sports Medicine and research by the investigators that it was “doable” for this population.
After the exercise bout, subjects in this group were fitted with electrodes, looked at pictures of food and flowers, and were sent home wearing the accelerometer with the same instructions as those in the control condition.
The researchers didn’t take any subjective measures of hunger levels. In other words, they didn’t ask the subjects how hungry they felt. All measures consisted of objective data collection.
“Food motivation” experimental task - After completing the body composition analysis (control group) or 45 minutes on the treadmill (exercise group), both sets of participants completed a computerized task where they simply sat passively and looked at a series of pictures. The pictures were shown in three blocks of 80 (240 total). Each block consisted of 40 pictures of flowers and 40 photos of plated meals, which were shown in random order.
Why flowers? The researchers chose them because images of flowers were used in previous research, which makes it easier to compare data. Another reason was that the photos of flowers and plated meals were similar in composition, with equally inviting colours, contrast and so on.
Participant responses to the pictures - Research on human emotion suggests there are two common emotion-processing dimensions: affective valence (ranging from pleasant to unpleasant); and emotional arousal (ranging from calm to excited). So the participants were asked to rate the pictures on a scale from 1-9 with 1 being extremely unpleasant/not at all arousing to extremely pleasant/extremely arousing.
Electrophysiological data recording and reduction - Electrical activity was measured in different parts of the brain using an EEG (electroencephalogram). Researchers focused on an area of the brain that is linked to arousal and affective valence, shown through previous research to be the area that corresponds to food motivation. Before the experiment, the researchers conducted baseline testing in order to create standards by which to compare their actual experimental results.
Energy intake - After participants completed their tasks they were sent home with a food log and food scale and told to measure, weigh and record all of the food and drink they consumed until the next morning. The food logs were analyzed using a standard diet analysis program.
Physical activity - The participants wore an accelerometer beginning at testing until the following morning. This is the same type of device used in the study discussed in a previous research review. The researchers wanted to see if there were differences in the total physical activity level of the two groups and whether BMI or the exercise intervention affected their brain’s response to food stimuli.
The researchers wanted to find out if there is an interaction between exercise and BMI on brain measures of food motivation. They also wanted to find out if the exercise intervention affected total physical activity level and caloric intake over a 24-hour period.
What they found was that in this experiment, exercise decreased food motivation in both groups.
“Food motivation” experimental task – There were no statistically significant differences based on BMI groupings in ratings of valence or arousal when the women looked at the pictures of food and flowers after exercise or after the body composition testing (no exercise). In other words, both groups recorded similar responses.
Electrophysiological data recording and reduction – This is where the results get interesting. In both groups, after body composition testing (non exercise), there was a statistically significant difference in ratings when they looked at food versus flowers: both groups rated food pictures higher on the two scales.
However, after exercise, this difference in rating all but disappeared in both groups. In other words, flowers and food received pretty close to the same ratings regardless of BMI. What this means is that in this study, 45 minutes on the treadmill decreased the food motivation of both groups of women. That is, exercise had at least some sort of transitory effect that reduced their hunger/appetite.
Energy intake – Based on the food intake data the researchers collected, caloric intake was similar in both groups whether they exercised or not and regardless of BMI.
Physical activity – Total activity was higher in both groups on the exercise days (no surprise here). However, when the researchers separated the activity levels of the women for the rest of the 24 hour period (sedentary, light, moderate, vigorous), the amount of time the obese women spent doing activity that was classified as moderate to vigorous was statistically significantly lower than the normal weight women.
Remember the talk about compensation in last week’s review?
There is a lot of conflicting information on the effect of exercise on appetite, mainly because most studies rely on subjective measures.
Measuring brain activity is great method to gather more objective data, which can help researchers gain a better understanding of how exercise affects food motivation and subsequent food choice.
In this study, the BMI of the women didn’t affect how their brain responded to viewing pictures of food – but exercise did. This is interesting data, which provides a basis for additional studies.
However, more data needs to be collected before conclusions can be formed.
This study was limited by the design type (no randomization) and by the fact that it didn’t take other objective measures that may influence appetite and weight into account – such as the appetite regulation hormones leptin and ghrelin. (For more on this see “Leptin, Ghrelin, Weight Loss: It’s Complicated“)
The study was also very short (24 hours for each intervention). Measuring energy intake, total physical activity and brain activity for a longer time period would provide more information on how long the brain wave response persists.
Finally, as noted in the study on BMI and snacking, a person’s rated level of self-control also appears to play a part in the extent to which the desire to eat is satisfied.
In this study at least, exercise seemed to temporarily derail the urge to eat, even in people who were set up for snack attacks. If exercise does temporarily decrease your brain’s response to food cues, then jump on this knowledge and use it to set yourself up for success.
Maintaining good eating habits is tough for most folks, so think about strategies you can use to “retrain your brain” and get rid of those automatic behaviours that may lead you to overeat or make poor choices.
In teaching, this is called the “teachable moment” — a time when learning becomes easiest.
Keeping healthy foods on hand, maintaining a list of healthy choices for those times when you are so hungry you can’t think, keeping visual cues of appropriate portions taped to your fridge – those are behaviours that with repetition can become automatic habits, creating linkages in your grey matter.
So what can you do today to reduce the influence of your nemesis food cues?
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