Cognitive decline can impair the quality of life of older adults and reduce their independence . Especially older adults with chronic illnesses (OACI) are prone to have lower levels of cognitive functioning (CF) compared to healthy older adults . Regular physical activity (PA) has been argued as an important protective factor against age-related cognitive decline, with PA at a moderate-to-vigorous intensity mostly being advised [3–5]. However, OACI can experience issues with being sufficiently physically active due to mobility problems, pain and fatigue . Therefore, performing activities at a lighter intensity is more achievable for OACI. However, only few studies investigated the relationship between light physical activity (LPA) and CF [7–9]. Hence, the longitudinal association in OACI between change in respectively both LPA and moderate-to-vigorous physical activity (MVPA) on the one hand and the change in CF on the other hand are investigated.
The association between PA and CF has been confirmed in both cross-sectional and longitudinal cohort studies [10, 11]. However, evidence from studies regarding the effect of PA interventions on CF in older adults is incoherent . Some meta-analyses have found moderate cognitive improvements as a result of PA interventions in older adults [4, 13–15]. Yet, other meta-analyses demonstrated none to limited cognitive improvements, even when the intervention lead to increased fitness and PA behavior [16–18]. Besides the wide variety in interventions (different type of PA activities, duration and frequency of the sessions, and the duration of the program), one of the possible explanations for this discrepancy can be found in the many different ways how PA was assessed .
For example, PA can be assessed subjectively with self-report questionnaires or objectively with accelerometers, and can be categorized into different intensity levels; sedentary, low, moderate and vigorous. Examples of LPA activities are walking at a low speed or light household chores. Bicycling at a low speed, vacuuming or walking briskly are examples of moderate intensity PA. And running, carrying heavy loads or swimming laps are examples of vigorous intensity PA. The effects of PA on physical health outcomes can be different at different intensity levels. Until recently, most research investigating the physical health benefits of PA, relied mainly on self-reported PA and often did not make a distinction between PA intensities. However, people’s ability to recall PA of MVPA is much more accurate than that of LPA . Currently, guidelines prescribe at least 150 minutes of MVPA spread over preferably multiple days per week to achieve physical health benefits , such as lower risk for obesity, cardiovascular disease, some types of cancer, osteoporosis and pre- mature death, hereby overlooking the role of LPA . However, more recent evidence from studies assessing PA with accelerometers proved that LPA can have physical health benefits too [23–25]. These studies suggest that LPA is inversely associated with all-cause mortality risk and associated favourably with some cardio metabolic risk factors including waist circumference, triglyceride levels, insulin, and presence of metabolic syndrome.
Next to the physical health benefits of PA, the evidence for cognitive health benefits of PA grows. PA can promote cognitive brain health (i.e. ability to remember, learn, plan, concentrate and maintain a clear, active mind) and counteract many effects of cognitive aging . In line with research into the physical health benefits of PA, research into the cognitive health benefits of PA have also mainly focused on MVPA. When looking at effects of MVPA on CF, the executive functions (inhibition, shifting and updating) seem to benefit the most [13, 15]. Executive functions are higher-order cognitive processes that are necessary to control cognitive behavior. Nonetheless, studies so far neglected the relation of PA on a lower intensity level with CF, but it appears that LPA could also be beneficial for CF [26–28]. In recent studies LPA has been positively associated with shifting, word fluency, processing speed and a reduced rate of cognitive ability decline [7–9]. However, until now there is little information on whether LPA influences different constructs of CF than MVPA does.
Despite the promising benefits of PA as described above, older adults are the least physically active age group, especially when they suffer from chronic illnesses [29, 30]. Fatigue and pain are examples of PA-related barriers experienced by OACI that may result in these low levels of PA [6, 29]. Increasing PA in general, especially through MVPA, is often difficult, and is sometimes accompanied by risks of injury and deterioration as a result of physical complications. Furthermore, increasing LPA is probably easier and safer for older adults. Therefore, it would be justified to determine which intensities of PA are associated with CF. Taking into account the fact that LPA (light housework, slow walking) is the dominant type of PA in older adults, especially in those who suffer from chronic illnesses, and that few of these older adults participate in meaningful amounts of MVPA, it is crucial to know how change in both LPA and MVPA are related to change in CF.
In a previous study on the effects of a computer-tailored PA stimulating intervention for OACI, we found no intervention effects on CF both six and 12 months after baseline (Volders et al., under review). This was most likely caused by the very limited objectively measured intervention effects on PA in this population . However, the intervention group showed significantly more increase in some self-reported PA activities.
Despite the fact that our intervention had limited effects on PA behaviour and no effects on CF, it is relevant and scientifically valuable to investigate whether and how the change in PA, operationalized as MVPA as well as LPA, is related to a change in CF in OACI, independent of the intervention. Innovative and powerful for the current study is the objective measurement of PA by accelerometers, taking into account the limitations of self-reported PA. We hypothesize that participants who increased their PA (i.e. between baseline and six months follow-up, between six months follow-up and 12 months follow-up, and between baseline and 12 months follow-up), showed more progress on the CF tests than those who did not increase their PA. Furthermore, we hypothesize that associations between change in PA en change in CF are expected to be stronger when similar time periods are compared in comparison to different, non-parallel time periods, as potential associations can fade away over time. As different concepts of CF can respond differently to PA [13, 27], we analyse the associations between change in PA (LPA and MVPA) and CF for different concepts of CF. The selected concepts of CF are verbal memory, shifting, inhibition, and information processing because these concepts are known to deteriorate with age and can possibly improve with increased PA [10, 16, 32–35].