Sleep, Physical Activity, and Cognitive Health in Older Adults

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44 Sleep, Physical Activity, and Cognitive Health in Older Adults Teresa Liu-Ambrose, Ryan S. Falck Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada

I INTRODUCTION With one new case of dementia occurring every 4 seconds worldwide (World Health Organization & Alzheimer’s Disease International, 2012) and no pharmaceutical cure currently available, there is a need for effective nonpharmaceutical strategies for older adults, which can prevent or at least delay the onset and progression of cognitive decline (Middleton & Yaffe, 2009). As a result, lifestyle and behavioral strategies are becoming an increasingly popular line of scientific inquiry and public interest. One promising strategy for maintaining cognitive health in older adulthood is to improve sleep quality. Poor sleep is a risk factor for both cognitive decline and Alzheimer’s disease (AD) (Ehrenberg et al., 2018; Lim et al., 2013), and poor sleep is more prevalent among individuals with cognitive impairment as compared with their cognitively healthy peers (da Silva, 2015). Furthermore, epidemiological evidence indicates that poor sleep quality is associated with an increased risk of progression from mild cognitive impairment (MCI) to dementia (Tranah et al., 2011). Although good-quality sleep is important for healthy aging, sleep deteriorates in both quality and quantity as a function of normal aging (Scullin & Bliwise, 2015). For example, sleep complaints are common in older adults, with >50% of adults 65+ years reporting at least one chronic sleep complaint (Foley et al., 1995). Changes in the function of circadian rhythms are closely tied to the natural changes in sleep quality that occur with aging. Circadian rhythms are governed by the  24hour biological clock, which adjusts/tunes physiology and behavior to the solar light-dark cycle (Borb
ely, Achermann, Trachsel, & Tobler, 1989; Daan, Beersma, & Borb
ely, 1984; Golombek & Rosenstein, 2010; Moore, 2013). The process

Handbook of Sleep Research, Volume 30 ISSN: 1569-7339 https://doi.org/10.1016/B978-0-12-813743-7.00044-X

by which the biological clock is synchronized with the solar light-dark cycle (i.e., entrainment) is controlled by the suprachiasmatic nuclei (SCN) (Shirani & Louis, 2009). Under normal conditions, the SCN functions as “the master biological clock” of the central nervous system and interacts with the homeostatic recovery process that increases sleep need as a simple function of prior wakefulness with the function of the circadian clock. However, with age, the SCN becomes less sensitive to time cues (i.e., zeitgebers), and its output signal dampens (Landry & Liu-Ambrose, 2014). This SCN “aging” results in less robust circadian rhythms (e.g., melatonin, body temperature, and sleep-wake rhythms) (Duffy, Zeitzer, & Czeisler, 2007). The weakening of circadian regulation by the SCN impacts thermoregulation, neuroendocrine function, and melatonin production—each of which reduces sleep quality and can increase the risk for sleepwake disorders (Mishima, 2016). While age-related changes in both sleep quality and circadian function are perhaps an unavoidable consequence of aging, poor sleep and circadian physiology may be modifiable using lifestyle and behavioral strategies (Landry & Liu-Ambrose, 2014). One important strategy, which may benefit sleep quality, circadian physiology, and cognitive function, is increasing older adult physical activity (PA). PA has long been thought to help improve poor sleep (Kredlow, Capozzoli, Hearon, Calkins, & Otto, 2015), and epidemiological studies have consistently found that people who report greater PA also report sleeping better (Youngstedt, 2005). There is also a growing body of evidence suggesting that PA, particularly PA in the form of exercise training, is a zeitgeber that can help realign the circadian clock (Landry & Liu-Ambrose, 2014). Furthermore, strong empirical data indicate that regular PA of 150 minutes/week can reduce the risk of dementia by up to 28% (Hamer & Chida, 2009), and since

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over 95% of older adults are physically inactive (i.e., do not engage in 150 minutes/week of PA) (Troiano et al., 2008), increasing PA among older adults has become a public health priority (Nelson et al., 2007). In fact, it is estimated that up to 18% of all AD cases could be prevented by increasing older adult PA to recommended levels (Middleton & Yaffe, 2009). There is thus a dynamic relationship between sleep quality, circadian function, PA, and cognitive health. Sleep in aging, mild cognitive impairment, and AD are covered in detail elsewhere in this volume (see Chapters 43 and 45). Here, we review the current evidence on the relationship between sleep, PA, and cognitive health in older adults. The following topics will be discussed: (1) the effect of aging on older adult sleep quality and circadian physiology, (2) how sleep quality and circadian rhythms can impact cognitive health, (3) how PA can affect sleep quality and circadian alignment, (4) the effect of PA on cognitive health, and (5) the current evidence that PA influences cognitive function by improving sleep quality. We highlight some of the potential underlying mechanisms and potential modifying factors. We conclude with limitations and future directions for this rapidly expanding line of research that aims at augmenting circadian regulation of sleep-wake rhythms through environmental zeitgebers to promote sleep and, consequently, cognitive health in older adults.

II DEFINITIONS We provide an overview of the terms that will be used throughout this chapter: Sleep quality: The term “sleep quality” is widely used by researchers, clinicians, and the public; however, the expression has lacked a definitional consensus until recently. The National Sleep Foundation (Ohayon et al., 2017) has recently defined several measures of sleep quality including (1) sleep efficiency (i.e., ratio of time spent sleeping to time spent trying to sleep), (2) sleep latency (length of time in minutes it takes to transition from wake to sleep), (3) sleep duration (total time spent sleeping), (4) awakenings (the number of times a person wakes after imitating sleep), (5) wake after sleep onset (the time spent awake after sleep has been initiated and before final awakening), and (6) sleep architecture (the basic structural organization of normal sleep). There are two structural types of sleep, non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. NREM sleep is divided into stages 1, 2, 3, and 4 (or 3 stages in some more recent classification systems), representing a continuum of relative depth. Stages 3 and 4 are classified as slow-wave sleep, or

deep sleep, and are also used as a marker of sleep depth and sleep quality (Ohayon et al., 2017). Sleep quality can be measured objectively using polysomnography (the gold standard for measuring sleep quality) or using wrist-worn and hip-worn actigraphy; sleep quality can also be measured subjectively by questionnaire. Circadian rhythms: The Latin words circa diem mean “approximately 1 day.” To this end, circadian rhythms are 24 hour cyclic changes in physiology and behavior that are governed by various biological clocks in coordination with the solar light-dark cycle (Daan et al., 1984; Golombek & Rosenstein, 2010; Moore, 2013). Importantly, sleep quality is closely tied to the function of circadian rhythms. Key features of circadian rhythms include the synchronizing effect of light-dark cycles, persistence of the rhythmicity in constant darkness, and negative masking by light, leading to rhythmic behavior even in an animal that lacks the ability to maintain rhythms in constant conditions. This rhythmic behavior in the presence of a rhythmic environment highlights the difference between a rhythm, which is endogenously generated, and one that is set by the environment (Mishima, 2016). Rhythms that are observed in a rhythmic environment are referred to as diurnal (i.e., daily) rhythms, and thus, normal human circadian rhythms are diurnal. Entrainment: The process by which the biological clock is synchronized with the solar light-dark cycle is known as entrainment and is regulated by the activity of the SCN—located directly above the optic chiasm in the hypothalamus of the brain. Zeitgeber: The entrainment of the biological clock is accomplished through certain external stimuli, known as zeitgebers (from the German time givers). These time givers help to prevent inadvertent drifting or divergence of the biological clock from the 24 hour day. Zeitgebers can be used as a chronobiotic— that is, a therapeutic agent to help realign the biological clock with the solar light-dark cycle. We will discuss two chronobiotics in detail: light and PA. Physical activity: The term PA refers to any bodily movement produced by skeletal muscles that requires energy expenditure. PA in daily life can be categorized into occupational, leisure-time, transportation, and household activities (Caspersen, Powell, & Christenson, 1985). PA can be further classified by the intensity of activity according to the number of metabolic equivalents (METs) of energy expended during activity. Briefly, these categories are (1) sedentary behavior (1.0–1.5 METs), (2) light PA (1.6–2.9 METs), and (3) moderate-tovigorous PA (>3.0 METs) (Pate, O’Neill, & Lobelo, 2008).

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Exercise: A subset of PA is exercise training, which is planned, structured, and repetitive PA and has as a final or an intermediate objective of improving or maintaining physical fitness (Caspersen et al., 1985). Maximizing the benefits of exercise training requires the precise prescription of exercise frequency, intensity, time, and type (Oberg, 2007). Briefly, frequency refers to how often the exercise occurs (i.e., days/week), intensity refers to the level of exertion during the exercise (e.g., heart rate and the percentage of repetition maximum), time refers to the duration of exercise training (usually in minutes), and type refers to the modality of exercise training (Baechle & Earle, 2008). The three most common types of exercise training are aerobic training (AT), resistance training (RT), and multicomponent training (MT). AT is defined as exercise when it has the intent of improving cardiovascular fitness and includes walking, running, or dancing. RT refers to exercise with the intent of increasing muscular strength, power, or endurance using bands, weight machines, or free weights. MT is either (1) exercise, which incorporates both AT and RT, or (2) AT and/ or RT, which also includes other forms of exercise training such as balance and agility training.

III CIRCADIAN RHYTHMS AND SLEEP IN NORMAL AGING The principal entraining zeitgeber for the human biological clock is light (Roenneberg & Foster, 1997; Sharma & Chandrashekaran, 2005), exerting its influence on retinal ganglion cells containing melanopsin (Blanks, Hinton, Sadun, & Miller, 1989; La Morgia et al., 2016; Schmidt, Chen, & Hattar, 2011; Sekaran, Foster, Lucas, & Hankins, 2003). Retinal light exposure directly stimulates the activity of the SCN, which phase delays the biological clock such that the desire for sleep decreases and wakefulness increases (or is maintained); reduced retinal light exposure results in less activity of the SCN and increases the desire to sleep by phase advancing the biological clock (Shirani & Louis, 2009). Thus, under normal circumstances, the biological clock is entrained to the solar light-dark cycle through the regulation of the SCN—which helps humans maintain a regular sleep-wake cycle (Mistlberger, 2005). However, aging significantly alters the functioning of circadian rhythms. Aging is associated with the biological clock initiating sleep-promoting mechanisms earlier in the day (Czeisler et al., 1992; Duffy, Dijk, Klerman, & Czeisler, 1998) and a decreased amplitude in circadian signals, which increase sleep need (Dijk, Duffy, Riel, Shanahan, & Czeisler, 1999; van Someren, Mirmiran, & Swaab, 1993). This weakening of circadian regulation

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with aging likely plays a prominent role in the fragmentation of sleep-wake rhythms observed in older adults during (1) the wake maintenance zone, which occurs 2–3 hours before habitual bedtime, and (2) the sleep maintenance zone, which occurs 2–3 hours before habitual wake time (Landry & Liu-Ambrose, 2014). In addition, older adults have reduced sensitivity to light, due to age-related loss of retinal ganglion cells and axons (Harwerth, Wheat, & Rangaswamy, 2008), which leads to poorer functioning of the SCN and divergence of the biological clock from the solar light-dark cycle (Neikrug & Ancoli-Israel, 2010). Behavioral changes in older adulthood—such as spending less time outdoors— could also further decrease bright light exposure, which may be a contributing factor to the decreased amplitude of circadian rhythms (Landry & Liu-Ambrose, 2014). This age-associated weakening in circadian regulation may also be linked to declines in sleep quality in older adulthood. Sleep changes as a function of normal aging, both in terms of decreased quality and quantity (Crowley, 2011; Espiritu, 2008). More than half of adults over 65 years report at least one chronic sleep complaint—the most common complaints being the inability to stay asleep at night and excessive daytime sleepiness resulting in frequent daytime naps (Foley et al., 1995). These complaints, in particular the reports of excessive daytime sleepiness (a key indicator of accumulated sleep debt (Carskadon, 1986; Johns, 1991)), suggest that age-related changes in sleep are likely the result of something beyond reduced need for sleep. The evidence therefore suggests that (1) normal aging may disrupt the function of circadian rhythms and (2) these age-related changes in the functioning of circadian rhythms may explain the declines in both sleep quality and quantity as people age.

IV SLEEP QUALITY AND OLDER ADULT COGNITIVE HEALTH The effects of poor sleep on cognitive health and functions are apparent following both acute and chronic poor sleep (Lowe, Safati, & Hall, 2017). Neurocognitive impairments following acute sleep loss are experienced almost universally and include impairments in attentional processing, executive function, memory, and emotional regulation and sensory perception (Durmer & Dinges, 2005; Goel, Rao, Durmer, & Dinges, 2009; Jones & Harrison, 2001; Walker, 2008). Importantly, optimal cognitive functioning is integral for older adult quality of life since it is linked to physical function and independence (Best, Davis, & Liu-Ambrose, 2015; Vaughan & Giovanello, 2010), emotional regulation (Gyurak, Goodkind, Kramer, Miller, & Levenson, 2012; Ochsner & Gross, 2005), and even eating behavior

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(Hall, 2016). Moreover, attentional failures or lapses due to sleep loss are considered the primary causative factor underlying fatigue-specific automobile accidents (Philip et al., 2005; Schwarz et al., 2016) (see Chapter 40), with a level of psychomotor impairment seen following acute sleep loss similar to that observed during alcohol intoxication (Williamson & Feyer, 2000). Perhaps most importantly, the observed neurocognitive impairments, which are a consequence of poor sleep, can be attributed to suboptimal functioning of the prefrontal cortex (Lowe et al., 2017), which is the principle cortical area responsible for higher-level cognitive processes (Banks & Dinges, 2007; Killgore, 2010). While it is clear that poor sleep quality can have an immediate impact on cognitive function, the chronic effects of poor sleep can have even more sinister consequences. Indeed, poor sleep quality is recognized as an important predictor of AD (Mander, Winer, Jagust, & Walker, 2016). Older adults diagnosed with obstructive sleep apnea—a common chronic sleep disorder characterized by frequent episodes of upper airway collapse during sleep, which results in recurrent arousals from sleep (Punjabi, 2008)—convert to MCI and AD at a younger age (Osorio et al., 2015). However, successfully treating obstructive sleep apnea can delay the age of MCI onset (Osorio et al., 2015) and improve cognitive function among adults with AD (Ancoli-Israel et al., 2008). Poor sleep is also more prevalent among individuals with cognitive impairment as compared with their cognitively healthy peers (da Silva, 2015), and epidemiological evidence indicates that poor sleep quality is associated with an increased risk of progression from MCI to dementia (Tranah et al., 2011). Poor sleep quality can also contribute to AD pathophysiology, and disruptions in sleep quality and circadian alignment represent typical AD biomarkers. Circadian dysregulation is also one of the hallmarks of AD progression (Landry & Liu-Ambrose, 2014). In fact, sleep disruptions that occur in AD are often exaggerated in a way that implies a form of accelerated aging or hyperaging (Witting, Kwa, Eikelenboom, Mirmiran, & Swaab, 1990), such that fragmentation of sleep-wake rhythms in adults with AD is more akin to much older adults without AD. Moreover, the SCN of older adults with AD is significantly atrophied compared with their cognitively healthy peers, which likely contributes to the fragmentation of sleep-wake cycles in AD (Stopa et al., 1999; Swaab, Fliers, & Partiman, 1985; Zhou, Hofman, & Swaab, 1995). Increases in cortical amyloid beta (Aβ), a key indicator of AD pathophysiology, lead to increases in sleep fragmentation and disrupt diurnal rhythms in the APPswe/PS1δE9 mouse model of AD (Roh et al., 2012). Chronic sleep restriction and corresponding increases in wake time significantly escalate Aβ accumulation in transgenic Tg2576 mice (Kang et al., 2009).

Increased Aβ load is linked to disrupted NREM slow-wave sleep (i.e., stages 3 and 4) and impaired hippocampusrelated memory consolidation (Mander et al., 2015). A recent randomized controlled trial (RCT) of middleaged adults suggests that as little as one night of total sleep deprivation can also significantly increase Aβ in healthy middle-aged men (Ooms et al., 2014), and a positron emission tomography study showed that acute sleep deprivation over one night increased Aβ burden in brain regions implicated in AD (Shokri-Kojori et al., 2018). It therefore appears that a vicious cycle of accelerating AD progression may occur with poor sleep—wherein poor sleep quality causes an increase in AD progression and vice versa ( Ju, Lucey, & Holtzman, 2014). While poor sleep thus appears to contribute to cognitive decline and dementia progression, good-quality sleep appears to be neuroprotective. For example, NREM sleep promotes the clearance of Aβ that accumulates during wake time (Xie et al., 2013) and combats oxidative stress (which is linked to AD pathology) by enhancing cellular restitution processes ( Ju et al., 2014). Improving sleep quality may also be an especially potent therapy for populations with a high risk for dementia, such as populations with the APOE-ε4 allele, who exhibit significant sleep deficits (Lim et al., 2013). Given that sleep is a modifiable behavior, which can target multiple cognitive processes (Gais et al., 2007; Marshall, Helgadóttir, M€ olle, & Born, 2006; Ngo, Martinetz, Born, & M€ olle, 2013), promoting older adult sleep quality appears to be an important strategy for maintaining cognitive health in later life.

V THE RELATIONSHIP OF PHYSICAL ACTIVITY, SLEEP QUALITY, AND CIRCADIAN RHYTHMS IN OLDER ADULTS Epidemiological studies have consistently found people with greater PA report sleeping better compared with more sedentary individuals (Youngstedt, 2005). While the reason for why PA and sleep are related is still unclear, current evidence suggests three possible explanations (Buman & King, 2010; Kredlow et al., 2015). First, negative affective states (i.e., depressive symptoms and anxiety) contribute to poor sleep (Morin et al., 1999), and PA counters this via its antidepressant and anxiolytic effects (Dunn, Trivedi, & O’Neal, 2001; Stathopoulou, Powers, Berry, Smits, & Otto, 2006). Second, obesity is related to poorer sleep quality (Fogelholm et al., 2007), and PA has a direct impact on weight regulation, which may promote better sleep quality (Hill, Wyatt, & Peters, 2012). Third, regular PA improves or maintains physical function (DiPietro, 1996); poor physical function is associated with poorer sleep quality in older adults (Ensrud et al., 2009). However, much of the evidence to date is

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based on self-reported PA and self-reported sleep quality (Kredlow et al., 2015; Youngstedt, 2005), which can be quite different from objectively measured data (Falck, McDonald, Beets, Brazendale, & Liu-Ambrose, 2016; Landry, Best, & Liu-Ambrose, 2015). The relationship between PA and sleep quality may weaken with age (Falck, Best, Davis, & Liu-Ambrose, 2018). One potential reason for this functional weakening is that we simply need less sleep as we age (Feinberg & Van Cauter, 2000). In addition, there is some evidence that underlying changes in older adult neurobiology (e.g., neural atrophy, nocturnal hypoxia, neuroendocrine changes, and altered neuromodulation) may reduce the potential to impact sleep quality through strategies such as PA (Scullin & Bliwise, 2015). PA in the form of exercise also appears to have chronobiotic effects in humans (Baehr et al., 2003; Buxton, Lee, L’Hermite-Bal
eriaux, Turek, & Van Cauter, 2003; Neikrug & Ancoli-Israel, 2010). The chronobiotic properties of PA have been well established in various animal models, with wheel running being the most commonly used approach in rodents (Hastings, Duffield, Smith, Maywood, & Ebling, 1998; Mrosovsky, 1996). Briefly, the circadian rhythms of rodents can be entrained by regularly scheduled exercise (Edgar & Dement, 1991; Marchant & Mistlberger, 1996), and single episodes of running in novel running wheels can advance the circadian clock (Mrosovsky, 1996; Turek, 1989), while the presentation of a novel running wheel can accelerate reentrainment and induce single-phase advances as large as 12 hours (Gannon & Rea, 1995). However, human studies on the chronobiotic properties of PA are difficult, given the challenges associated with isolating the effects of exercise from other factors such as light, food, and social influences (Mistlberger & Skene, 2004, 2005). However, studies of blind people who lack sensitivity to light—but remain able to entrain to daily work/social schedules without the involvement of exogenous melatonin—suggest that nonphotic stimuli are capable of synchronizing circadian rhythms (Mistlberger & Skene, 2005). It has yet to be determined whether it is exercise, social influences, regularly scheduled mealtimes, or a combination of these (and possibly other potential zeitgebers), which provides the critical entrainment signal. While the effects of PA as a chronobiotic have yet to be fully established, PA does appear to have a specific phase-response curve (Mistlberger & Skene, 2005). Briefly, PA performed in the morning or early afternoon does not appear to have a consistent effect on phase shifts of the biological clock; however, engaging in PA in the late afternoon causes a modest phase advance of the biological clock, while late-night PA causes a modest phase delay of the biological clock (Baehr et al., 2003; Buxton et al., 2003). Importantly, the effects of PA as a zeitgeber have been found in both young adults and older adults

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(Baehr et al., 2003). The time-based response to how PA can impact the SCN is hypothesized to coincide with the timing of the opening of the “sleep gate”—the shift of the biological clock from generating a waking signal, which reduces sleep need, to generating a signal that facilitates sleep (Dijk & Edgar, 1999). However, the use of PA as a strategy to maintain circadian alignment may be challenging from a practical standpoint. The current evidence describing the effects of PA as a zeitgeber comes from controlled laboratory experiments, where the timing and intensity of PA in the form of exercise is tightly controlled. Conducting an intervention where participants would be asked to engage in regularly timed PA at a prescribed intensity would (1) be burdensome to participants and (2) require enormous resources to ensure participant adherence. More importantly, evidence suggests that regular PA of 150 minutes/week—regardless of timing—is associated with better sleep quality (Kredlow et al., 2015; Youngstedt, 2005). The current body of evidence therefore suggests that PA has chronobiotic effects, which may play a role in promoting good-quality sleep. However, it is still unclear whether PA can improve the sleep quality of older adults given that circadian regulation and the relationship between PA and sleep quality appear to weaken with age. Future research is needed to determine the optimal dose (i.e., intensity, volume, and type) and timing of PA to promote a chronobiotic effect and determine if these chronobiotic effects can provide meaningful improvements in older adult sleep quality. Furthermore, it is unclear what aspects of sleep quality can be affected by PA—particularly among older adults—and thus, future research must determine the aspects of sleep quality that can be impacted by changes in PA.

VI PHYSICAL ACTIVITY AND OLDER ADULT COGNITIVE HEALTH Many studies have been published on the benefits of PA as it pertains to cognitive health, particularly among older adults (Colcombe & Kramer, 2003; Erickson, Weinstein, & Lopez, 2012; Hamer & Chida, 2009; Hillman, Erickson, & Kramer, 2007; Northey, Cherbuin, Pumpa, Smee, & Rattray, 2018). However, most of the evidence on how PA can impact cognitive health comes from observational data, rather than experimental data (Hamer & Chida, 2009), and only relatively few studies have examined whether increasing PA can promote cognitive health. Instead, most of the literature on whether PA improves cognitive health comes from (1) animal models, wherein AT is simulated using either forced treadmill or voluntary wheel running (Cotman & Berchtold, 2002; Cotman, Berchtold, & Christie, 2007);

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(2) animal models, wherein RT is simulated by tying a weight to an animal’s tail and conditioning the animal to climb up a ladder (Cassilhas et al., 2012); or (3) human exercise training RCTs, wherein participants are randomly assigned to an exercise training group (i.e., AT, RT, and MT) or to a control group (e.g., wait-list control, balance and tone, or usual care) (Northey et al., 2018). The results of these studies collectively suggest that PA in the form of exercise training can have significant benefit on cognitive function, neuroplasticity, and cortical function (Nagamatsu et al., 2014). However, exercise is a specific subdomain of PA, and it is yet unclear whether increasing total PA (as opposed to exercise training) can improve cognitive health. While it is difficult to determine if increasing total PA of any type can lead to significant improvements in cognitive health, there is little doubt that regular PA is neuroprotective and associated with better cognitive performance (Colcombe & Kramer, 2003), greater cortical volume (Gow et al., 2012), better functional plasticity (Kramer & Erickson, 2007), and reduced dementia risk (Hamer & Chida, 2009). The evidence examining the benefits of exercise training on cognitive health came primarily from RCTs in both animals and humans (Cotman et al., 2007; Northey et al., 2018), such that there is consistent causal evidence that exercise improves cognitive health at the cellular and system level. Most of the evidence on the impact of exercise on cognitive function comes from both animal and human trials on AT (Cotman et al., 2007; Cotman & Berchtold, 2002); however, there have been recent efforts to examine the effects of RT on cognitive health (Cassilhas et al., 2007, 2012; Liu-Ambrose et al., 2010). At the present time, the evidence suggests AT and RT may impact cognitive health through divergent mechanisms (Cassilhas et al., 2012). Briefly, AT improves cognitive health through three distinct mechanisms: (1) hippocampal neurogenesis (i.e., the creation of new neurons), (2) cerebral angiogenesis (i.e., the creation of new blood vessels in the brain), and (3) downregulation of inflammatory markers (Cotman et al., 2007). Recent data also suggest that RT increases IGF-1 signaling (Gomes et al., 2014), while AT triggers the production of brain-derived neurotrophic factor (BDNF) (Van Praag, Kempermann, & Gage, 1999). Upregulation of IGF-1 and BDNF is integral (i.e., sufficient and necessary) to the mechanism of neurogenesis (Ding, Vaynman, Akhavan, Ying, & Gomez-Pinilla, 2006), and thus, it appears that AT and RT may stimulate neurogenesis through independent mechanisms. To date, it is unclear why AT may target one (or some) areas of cognitive function, while RT may benefit other areas of cognitive function. A recent hypothesis is that the benefits of AT on memory and executive function were an evolutionary adaptation, which increased future hunter-gatherer success (Raichlen & Alexander, 2017). While this appears plausible, exercise training in the form

of either AT, RT, or MT are each beneficial to multiple aspects of cognitive health, including memory and executive function (Northey et al., 2018). It is unknown whether the different exercise modalities act simultaneously, synergistically, or in silos to impact cognitive health. However, human trials indicate that both AT and RT can increase functional plasticity (Best, Chiu, Hsu, Nagamatsu, & Liu-Ambrose, 2015; Erickson & Kramer, 2009; Voss, Vivar, Kramer, & van Praag, 2013) and improve functional brain connectivity (Suo et al., 2016; Voss et al., 2010). Hence, AT and RT may promote different substrates within the same mechanism— leading to improvements in cognitive function, neuroplasticity, and functional connectivity irrespective of the type of exercise training performed. Finally, it is unclear which aspects of cognitive function are most responsive to exercise training, which types of exercise training are most potent, and whether there are sex differences in the effects of exercise training (Barha, Galea, Nagamatsu, Erickson, & Liu-Ambrose, 2017). Current evidence suggests that the benefits of exercise training are greatest for memory and executive function (Colcombe & Kramer, 2003; Northey et al., 2018)—a broad term used to define planning and problem-solving capability (Brennan, Welsh, & Fisher, 1997; Perry & Hodges, 1999). The effects of exercise training on executive function also appear to be dependent on training type, such that AT appears to have the largest effect (Barha, Galea, et al., 2017). In addition, the effects of exercise training on cognitive function appear to be more robust for older adult females than for males—for both animal and human studies (Barha, Davis, Falck, Nagamatsu, & Liu-Ambrose, 2017; Barha, Falck, Davis, Nagamatsu, & Liu-Ambrose, 2017). Answering these remaining questions about how best to prescribe exercise for cognitive health will help further refine exercise training guidelines for promoting cognitive health.

VII DOES SLEEP QUALITY MEDIATE THE IMPACT OF PHYSICAL ACTIVITY ON COGNITIVE HEALTH? Although there is ample evidence that both PA and sleep quality can impact older adult cognitive health, together with a growing body of evidence suggesting that PA is associated with better sleep quality, it is unclear whether PA and sleep quality impact cognitive health through divergent or convergent mechanisms. We recently found that higher PA and greater sleep efficiency were independently associated with better cognitive performance, but PA and sleep quality were not associated with each other (Falck, Best, et al., 2018). However, there is also recent evidence suggesting that sleep efficiency may mediate the relationship between PA and cognitive

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function (Wilckens, Erickson, & Wheeler, 2018); these results provide at least initial support for the restoration hypothesis, which suggests that energy expenditure (i.e., PA) stimulates a restoration process by which sleep allows the body and brain to recuperate (Buman & King, 2010). Given that there are well-defined mechanistic pathways by which each of these behaviors can impact cognitive health, it is thus plausible that there may be both convergent and divergent mechanisms by which PA and sleep quality impact cognitive health.

VIII LIMITATIONS AND FUTURE RESEARCH While it is thus clear that PA and sleep quality are each important nonpharmaceutical strategies for maintaining cognitive health in later life, there are several important limitations to the current literature. For clarity, we will discuss the current limitations and future directions for each of the following major topics we have covered separately: (1) the impact of sleep quality and circadian rhythms on cognitive health; (2) the impact of PA on cognitive health; and (3) the relationship of PA, sleep quality, and circadian rhythms.

A The Impact of Sleep Quality and Circadian Rhythms on Cognitive Health While it is clear that there is a bidirectional relationship between sleep quality and cognitive health, it is unclear if poor sleep quality is a causal factor in the progression of dementia or if the pathophysiology of dementia is responsible for declines in sleep quality. One of the primary reasons that the temporality and directionality of this relationship are yet unclear is that elucidating this relationship would require a prospective longitudinal study that observes the changes in sleep quality from early life to old age in association with cognitive health. Thus, a critical next step in understanding how sleep quality can impact cognitive decline is to investigate changes in sleep quality and cognitive function from midlife onward. It is also noteworthy that sleep itself is complicated and difficult to measure. For example, polysomnography is the gold standard for objectively measuring sleep quality and architecture, but it is costly and technically complex. Only recently, home polysomnography equipment has been developed, such that older adults can use the device under their normal sleep routine (in the past, observation occurred in laboratory). The reduction in cost and complexity of objective equipment for measuring sleep quality and quantity will thus be an important step toward elucidating how sleep quality can impact

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cognitive health. In addition, objective and subjective measures of sleep quality do not correlate well and may measure different aspects of sleep quality (Landry et al., 2015). Thus, it still remains an open question whether improving subjective sleep quality, objective sleep quality, and/or sleep architecture provides similar (or differential) benefit to cognitive health. Far less is known about how circadian rhythms can impact cognitive health. Although sleep quality is closely tied to circadian function, it is unclear whether it is poor sleep quality or circadian dysregulation that is linked to cognitive decline. The strongest evidence that circadian dysregulation is associated with cognitive impairment comes from autopsies of older adults with AD and those without AD (Stopa et al., 1999; Swaab et al., 1985; Zhou et al., 1995). However, it cannot be ascertained from SCN atrophy if it is part of the general pathology of AD or whether SCN atrophy and circadian dysregulation play a role in exacerbating AD pathology. Perhaps most importantly, there have been few attempts to use chronotherapy—a set of intervention strategies, which can improve sleep quality through strengthening the entrainment of the biological clock to the solar light-darkcycle (Landry & Liu-Ambrose, 2014). Potential strategies for improving circadian alignment include bright light therapy, PA, and sleep hygiene; however, chronotherapy interventions are only in their infancy (Falck et al., 2018).

B The Impact of Physical Activity and Cognitive Health While strong and consistent empirical evidence indicates that PA is associated with better cognitive health, the precise prescription of PA for cognitive health has been elusive. The current PA guidelines suggest that all older adults should obtain at least 150 minutes of moderate-to-vigorous PA per week to maintain overall health (including cognitive health) (Piercy et al., 2018). However, it is unclear whether this prescription needs to be modified for individuals with a higher risk for dementia. We recently determined that the relationship between PA and cognitive function in older adults with MCI was attenuated compared with their cognitively healthy peers (Falck et al., 2017). While older adults with MCI had lower PA than their cognitively healthy peers, it is possible that there may be a threshold effect, such that higher amounts of PA are required for older adults with cognitive impairment. Indeed, current evidence indicates that the effects of PA in the form of exercise training may be more potent for older adults with MCI (Zheng, Xia, Zhou, Tao, & Chen, 2016) than for those with healthy cognition (Young, Angevaren, Rusted, & Tabet, 2015). The precise characterization of optimally effective exercise training has yet to be fully elucidated. For

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example, it is unclear whether AT, RT, or MT is most beneficial for cognitive health. Maximizing the benefits of exercise training for cognitive health will require the precise prescription of volume (i.e., frequency  duration) and intensity that are based on the best-available evidence. It is also unclear if the effects of different modalities of exercise training are domain-specific or global. Although there has been some recent debate as to what aspects of cognitive function are impacted (or not) by exercise training (Diamond & Ling, 2016, 2018; Hillman, McAuley, Erickson, Liu-Ambrose, & Kramer, 2018), the overwhelming evidence to date suggests that exercise training can impact global cognition, processing speed, executive functions, and memory (Nagamatsu et al., 2014). Future research will need to determine whether specific types of exercise training impact specific domains of cognitive function or if all types of exercise training impact the same areas of cognitive function. Lastly, the role of sex as a potential moderator of the efficacy of exercise needs further inquiry. Recent meta-analyses indicate that the effects of exercise training on cognitive function (particularly for executive function and memory) may be larger for females than for males (Barha, Davis, et al., 2017; Barha, Falck, et al., 2017); however, it is not clear if the extent of improvement for females is substantially greater, such that different exercise guidelines should be established for each sex. Large RCTs will be needed to establish if the benefits of different types of exercise training on cognitive function reflect a clinically meaningful difference.

C The Relationship of Physical Activity, Sleep Quality and Circadian Rhythms While there is at least initial evidence that greater PA is linked with better sleep quality (Kredlow et al., 2015; Youngstedt, 2005), most of this evidence is based upon self-reported PA and self-reported sleep quality. Importantly, objective measures of PA and sleep quality often measure different things than subjective measures (Falck et al., 2016; Landry et al., 2015). Objectively measured PA provides a more precise estimate of PA duration, intensity, and frequency, while subjective PA measures can provide important information on the type and context of PA performed. Objective measures of sleep quality can provide more precise estimates of sleep duration, efficiency, and architecture, while subjective sleep quality can provide contextual information about how an individual feels about their sleep quality and which aspects of their sleep quality are most salient to their overall rating of their sleep quality. Hence, it is important to include both objective and subjective measures of PA and sleep quality in future investigations. The strongest evidence indicating that PA can improve sleep quality comes from RCTs of exercise training;

however, there have been remarkably few studies of older adults (Kredlow et al., 2015). Indeed, current evidence suggests the effects of exercise training on older adult sleep quality appear to impact subjective sleep quality more than objective sleep quality (King, Oman, Brassington, Bliwise, & Haskell, 1997); however, this is the only RCT to our knowledge that has examined how exercise training effects older adult sleep quality. Future work is thus needed to examine whether exercise training can improve objective components of older adult sleep. Furthermore, the precise prescription of exercise training for improving sleep quality is far from clear, and it is unclear whether different types and intensities of exercise training can elicit greater improvements in older adult sleep. Results from a recent meta-analysis indicate that the relationship between PA and sleep quality may be attenuated in older adults (Kredlow et al., 2015). One potential reason for this apparent functional weakening in the relationship between PA and sleep quality is that we simply need less sleep as we age (Feinberg & Van Cauter, 2000). It is also plausible that underlying changes in older adult neurobiology (e.g., neural atrophy, nocturnal hypoxia, neuroendocrine changes, and altered neuromodulation) may reduce the potential to impact sleep quality through strategies such as PA (Scullin & Bliwise, 2015). However, both of these hypotheses lack data from long-term observational studies, and it remains to be seen whether PA can modulate age-associated changes in sleep quality. Lastly, the use of PA as chronotherapy is still in its infancy (Falck, Davis, et al., 2018). The current evidence describing the effects of PA as a zeitgeber comes from controlled laboratory experiments, wherein the timing and intensity of PA in the form of exercise training is tightly controlled. Conducting an intervention where participants would be asked to engage in regularly timed PA at a prescribed intensity would be burdensome to the participants and require enormous resources to ensure participant adherence. Moreover, less than 5% of older adults meet current guidelines of 150 minutes/week of PA (Piercy et al., 2018), and since increasing PA appears to positively impact sleep quality, it is unclear whether precisely timed PA (beyond suggesting that older adults avoid PA in the evening or at night) is necessary to improve sleep quality.

IX CONCLUSION Maintaining the cognitive health of older adults will be one of the major public health challenges for decades to come, as the total number of older adults worldwide continues to increase with each year and a cure for dementia remains elusive (Ferri et al., 2006). As we have discussed throughout this chapter, increasing older adult PA and

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improving older adult sleep quality and circadian regulation appear to be viable strategies for maintaining older adult cognitive health. In addition, there is growing evidence that PA can positively impact older adult sleep quality and circadian alignment, and there is at least preliminary evidence that PA and sleep quality may improve cognitive health through multiple mechanisms—both convergent and divergent. A critical next step is to determine whether increasing PA can be used to protect older adult sleep quality as a primary prevention strategy for dementia. In addition, research is required to determine the most potent prescription of PA for maintaining older adult sleep health and cognitive health.

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