The Association between Physical Activity (PA) and Cognitive Ability

The benefits

It is part of natural aging that our cognitive capabilities may diminish. Cognitive functioning is essential for quality of life, why preserving our mental abilities is in the interest of our well-being (Edwards & Loprinzi, 2017). Physical activity (PA) plays a crucial role in developing and protecting mental abilities.

Swagerman et al. (2015) suggest that in the base population, regular leisure time PA has a limited long-term effect on cognition, except related to the domain of cognitive attention. However, the results from different studies related to age and gender specific sample as well as studies focusing specific types and intensities of physical activities (PA) and cognitive capabilities have provided more promising insights into the association of PA and cognitive capacity, although we are still left with a somewhat puzzling picture. Interestingly, animal research has been less inconsistent than the findings for humans (Swagerman et al., 2015). There may be soul-related spiritual factors at work too concerning our mental capabilities. However, this article is not delving deeper into this philosophical realm but rather identifies relevant biological components, environmental and lifestyle factors on which we have an influence too (Edwards & Loprinzi, 2017).

Brain-derived factors

PA has several effects on the brain: It, for example, mediates the brain’s thickness and synaptic density as relevant for brain plasticity (Hakansson et al., 2017). The literature explains partially improved cerebrovascular function with higher fitness levels (Gill et al., 2015). Cox et al. (2016) report the brain’s neuroplasticity even in old age and hypothesize that PA from earlier years prevents the cognitive decline in later years by enabling structural changes to the brain (e.g., increased blood flow, nerve-growth, and reduced cell death in the hippocampus) as a response to PA. Similarly,(Lo, Woodman, Pachana, Byrne, and Sachdev (2014) found biological mechanisms such as increased insulin-like growth factors, neurotransmitters, and brain-derived neurotrophic factors that may be protective against Alzheimer’s disease and dementia. Importantly, both short and long-term PA has beneficial effects on brain function (Soichi, 2016).

Current PA is most effective

Brain-derived neurotrophic factor serum, which is indicated to be a direct product of physical exercise, seems to positively affect working memory performance; even a single half an hour exercise does have this effect, in contrast to cognitive training or mindfulness practice (Hakansson et al., 2017). However, from a more broad and long-term perspective, associations have been found linking total lifetime PA to better cognitive function in later life too, mainly as a result of reducing the age-related modification of the brain (Gill et al., 2015). Stopping PA can lessen the protection from exercise as O’Callaghan, O’Catlaghan, Williams, Bor, and Najman (2012) found, showing that it is never too late to start though to reap the benefits of better memory scores from PA. High sedentary behavior correlates with a lower cognitive function for older people, but PA can significantly attenuate that association (Edwards & Loprinzi, 2017). Regarding other lifestyle factors, moderate levels of alcohol consumption might be protective for cognitive function in middle-to-old-aged women, all in contrast to smoking; however, recovery from a smoking-related decline of cognitive function may be possible over a longer period (Lo et al., 2014).

Intensity matters

According to O’Callaghan et al. (2012), more lower-level intensity PA is associated with increase intelligence, but not with vigorous exercise or walking. On the other side, Gill et al. (2015) state that only vigorous intensity PA is associated with increased global cognitive performance, while lifetime recreational (including transportation) activity was also positively influencing cognitive functioning, although this was true only for men. For older people though, more time of lighter PA and not necessarily PA of greater intensity, was found to be neuroprotective and therefore related to higher cognitive executive functioning (Johnson et al., 2016). An earlier study did some somewhat contradict that insofar as higher levels of rather vigorous PA was associated with reduced likelihood of cognitive impairment and better performance in memory and executive function for older adults (Zhu et al., 2015).

Benefit of PA for children

For children, it is rather aerobic fitness than daily PA that is positively related to the cognitive domains of inhibitory control and spelling (Pindus et al., 2016). Gill et al.’s (2015) research even revealed a significant impact of PA in childhood on global cognitive performance, although there is also the possibility that those children with higher mental capabilities are more likely to be physically active (O’Callaghan et al., 2012). It may be that children with higher cognitive ability participate in more PA too. The positive influence of PA on cognitive function for younger people mainly points to cognitive executive function (strong effect), memory (medium effect), and processing speed (weak effect) (Cox et al., 2016). Lower-fit children demonstrated less cognitive control and had longer cognitive reaction times, what clearly shows the benefit of keeping levels of physical exercise high and sedentary lifestyles limited in school age (Westfall, Kao, Scudder, Pontifex, & Hillman, 2017).

APPENDIX — Evaluation of Research Methods for the Association between Cognitive Ability and Physical Exercise

Physical activity (PA) is a factor that can be manipulated for different situations, why an experimental approach is possible (Field, 2013) and the preferred methodology for the research problem of whether there is an association between cognitive capability (CC) and PA. Ideally, there was a series of within-subject crossover interventions as conducted in Hakansson et al. (2017), taking data for each PA condition form all study subjects, allowing for within-subject and between-group statistical analysis. As positive influences on the brain come from short-term and longitudinal PA (Soichi, 2016), a study design with a relatively short period of repeated within-subject data collection would be a good solution as found in O’Callaghan, O’Catlaghan, Williams, Bor, and Najman (2012). PA shall be measured objectively by using accelerometer measurement devices (Johnson et al., 2016). For overcoming limitations of accelerometers regarding not capturing upper body activities and movements such as swimming or cycling, PA questionnaires could also be used. As suggested by Swagerman et al. (2015), genetic information should be added to strengthen the study design. Regarding the dependent variable of CC, the study shall determine which CC domains to measure, e.g., working memory, academic achievement (Pindus et al., 2016), or executive functions (Falck, Wilcox, Best, Chandler, & Liu-Ambrose (2017).

It is important to test the sample for its representativeness of the target population, as, e.g., separately for sexes and groups of age, like for example the research from Swagerman et al. (2015)), or Cox et al. (2016) who by design included only healthy adults in their study. To account for real-world challenges such as the aging society in many countries (Johnson et al., 2016) and long-term CC benefit of PA for children (Gill et al., 2015), a representative sample of these groups of interest may be especially beneficial.

It would be inappropriate to design the study using exclusively self-reporting tools, such as questionnaires, even if tested for appropriateness as in Jihoon, Hyunsoo, and Sungho, 2016. Self-reporting may involve forgetting relevant information or introducing tendencies according to personal wishful thinking (Edwards & Loprinzi, 2017). Furthermore, it would be a mistake to infer valid measures for PA from data related to physical fitness (Svedenkrans, Kowalski, Norman, & Bohlin, 2016). Attention should be paid to the control for relevant confound variables, such as education (Hyodo et al., 2016), and socio-economic factors that are influences on CC (Lo, Woodman, Pachana, Byrne, & Sachdev, 2014).

As it is not proposed to use a correlational study method, the limitations of unclear causalities in such cross-sectional studies (Zhu et al., 2015; Westfall, Kao, Scudder, Pontifex, & Hillman, 2017) can be avoided. This seems to be important when considering the possibility that increased PA can result from higher CC instead of the other direction (O’Callaghan et al., 2012). A limitation would be if small sample sizes were used reducing the accuracy of the statistical outcomes (Falck et al., 2017). Depending on the final scope of the research, limitations evolve either related to the validity or generalizability.

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