More and more studies are showing that changes in brain structure are associated with aging. These changes include a reduction in cortical thickness, a decrease in gray and white matter volume, and an increase in white matter hyperintensities (areas associated with aging and neurodegenerative diseases). However, there is considerable individual variability in the prevalence and progression of these declines. A better understanding of the underlying mechanisms and behaviours that promote or slow down these changes could help to develop interventions to slow down the structural and functional decline of the brain. Some researchers have hypothesized that high levels of fitness and overall physical activity could explain some of the individual differences observed in brain health.
Indeed, numerous studies have observed associations between physical activity and brain volume, as well as the risk of cognitive dysfunction. For example, systematic reviews have shown that high levels of fitness and moderate-to-intense physical activity are often associated with greater grey matter volume in key brain regions, such as the hippocampus and prefrontal cortex. Several longitudinal studies have also demonstrated a relationship between increased physical activity and changes in brain volume, both in healthy individuals and those with mild cognitive impairment. Furthermore, intervention studies suggest that increased physical activity improves cognitive function in the elderly, particularly when combined with strength training.
Independently of fitness and activity levels, body composition, particularly adiposity levels (the amount of body fat), could also influence brain volume and cognitive function. Studies have established a link between high body mass index (BMI) and reduced gray matter volume in several brain regions. In addition, obesity, particularly central obesity (i.e., excess visceral fat mass), has been correlated with reduced cortical thickness and gray matter volume, as well as impaired cognitive function in the elderly. Furthermore, insulin sensitivity in the brain is strongly associated with visceral fat volume, and insulin (in)sensitivity is associated with cognitive ability. Thanks to machine learning tools, it is now possible to estimate brain age (BrainPAD) by comparing brain volumetric measurements with people's chronological age. In this way, it is possible to determine whether an individual's brain structure is younger (negative BrainPAD) or older (positive BrainPAD) than expected. However, little longitudinal research has been conducted into the predictors of BrainPAD or the likelihood of changes in BrainPAD in response to changes in behavior (e.g. diet, physical activity, etc.) and associated changes such as fitness level, adiposity and sleep.
In an attempt to provide some answers, an international team of researchers observed the impact of physical exercise on brain age. To this end, 485 physically inactive people aged 64 to 85, not taking glucocorticoid or anti-diabetic medication, and with no diagnosis of cognitive disorders, neurodegenerative or cardiovascular diseases, were randomly assigned to 2 groups: an exercise group (n = 225) or a non-exercise group (n = 260).
The intervention involved a combination of cardiovascular training and resistance training. The sessions lasted 90 minutes and took place twice a week for 6 months. After the warm-up, classes were divided in two, with one group starting cardiovascular exercises and the other strength training. After 30 minutes, the groups switched workouts.
Using MRI, neuroimaging of the brains of all participants was collected before and after the 6-month intervention period. The BrainAge model developed by Cole et al. (2018), commonly known as BrainAgeR, was used for these analyses. BrainPAD scores were calculated by subtracting chronological age from the BrainAge score provided by the algorithm. Positive values reflect brains older than the expected chronological age, while negative scores indicate brains younger than the chronological age of the individual.
Aerobic capacity (assessed via a submaximal treadmill or cyclo-ergometer test), physical activity (estimated via accelerometer), sleep and body composition (measured via DEXA) were assessed and their impact on BrainPAD studied.
The main results of this study show that a combination of cardiovascular exercise and muscle strengthening significantly increased participants' cardiovascular capacity and improved their body composition by reducing body fat percentage and visceral adiposity and increasing muscle mass. Whereas for the non-exercising group, a significant decrease in lean tissue and non-significant changes in body fat and visceral fat were observed. The intervention also had a significant effect on total sleep time, with slight increases in the exercise group and a non-significant decrease in the non-exercise group.
As would be expected over a period of around 6 months, there was a significant effect of time for BrainAge, with BrainAge increasing by 0.709 years on average. However, this 6-month intervention did not appear to have a significant impact on BrainPAD.
However, the researchers analyzed correlations between changes in BrainPAD and changes in fitness, adiposity, activity and sleep regardless of the intervention group (with or without exercise). These analyses revealed that changes in BrainPAD were significantly associated with changes in body fat percentage and visceral fat, but not with changes in fitness level, sleep, or physical activity level. For every 1 kg change in visceral fat mass, there was a corresponding change of 0.948 BrainPAD years.
This contrasts with data linking fitness to brain health, both in terms of the volume of various brain structures and cognitive performance. It is possible that the relatively modest changes in fitness levels observed in this study (+0.5 METs at 85% of age-predicted maximum heart rate) were too small to induce significant changes in brain structure (and therefore BrainPAD). A longer or more intense intervention could perhaps bring about significant changes.
Given the large number of brain regions/features contributing to the BrainAge score, subtle changes in small brain regions may not be sufficient to have a significant impact on the score.
There appears to be a link between brain health, described here as the difference between the estimated biological age of the brain and the chronological age of the individual, and changes in body composition, more specifically in the level of general and visceral adiposity. Reduced visceral fat mass is associated with positive changes in BrainPAD, slowing brain aging relative to chronological body age. Visceral fat is associated with reduced immunity, increased levels of inflammation and greater oxidative stress. In addition, it decreases insulin sensitivity throughout the system, which is associated with impaired brain structure and cognitive function.
But the lack of impact of physical activity on BrainPAD suggests that the physiological aging of the brain as a whole cannot be slowed/changed simply by increasing exercise levels by a moderate amount over a short period, and so the results on fitness levels are relatively small. Knowing that exercise plays an important role in reducing visceral fat mass, we'll have to wait for a longer study with a more sustained exercise format to really understand the impact of exercise on brain health.
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