measuring the impact of exercise on cognitive aging

Neurobiology of Aging 33 (2012) 622.e29–622.e43

Review

Measuring the impact of exercise on cognitive aging:methodological issues

Delyana I. Millera, Vanessa Talera,c, Patrick S. R. Davidsona,b,c, Claude Messiera,*a School of Psychology, University of Ottawa, Ottawa, Ontario, Canada

b Heart and Stroke Foundation of Ontario Centre for Stroke Recovery, Ontario, Canadac Élisabeth Bruyère Research Institute, Bruyère Continuing Care, Ottawa, Ontario, Canada

Received 4 September 2010; received in revised form 21 February 2011; accepted 22 February 2011

Abstract

Physical exercise and fitness have been proposed as potential factors that promote healthy cognitive aging. Support for this hypothesishas come from cross sectional, longitudinal, and intervention studies. In the present review, we discuss several methodological problemsthat limit the conclusions of many studies. The lack of consensus on how to retrospectively measure exercise intensity is a major difficultyfor all studies that attempt to estimate lifelong impact of exercise on cognitive performance in older adults. Intervention studies have a muchbetter capacity to establish causality, but still suffer from difficulties arising from inadequate control groups and the choice and modalityof administration of cognitive measures. We argue that, while the association between exercise and preserved cognition during aging isclearly demonstrated, the specific hypothesis that physical exercise is a cause of healthy cognitive aging has yet to be validated. A numberof factors could mediate the exercise-cognition association, including depression, and social or cognitive stimulation. The complexinteractions among these 3 factors and the potential impact of exercise on cognition remain to be systematically studied. At this time, thebest prescription for lifestyle interventions for healthy cognitive aging would be sustained physical, social, and mental activities. Whatremains unknown is which type of activity might be most useful, and whether everyone benefits similarly from the same interventions.© 2012 Elsevier Inc. All rights reserved.

Keywords: Alzheimer’s disease; Cognition; Mild cognitive impairment; Physical exercise; Methods; Fitness; Metabolism; Social stimulation; Cognitivestimulation

www.elsevier.com/locate/neuaging

1. Introduction

Of the known possible ways to preserve physical andmental abilities, four stand out and have received somescientific support. The first is food restriction, whichconsists of eating a balanced but restricted diet thatcontains fewer calories than normally needed. This dietextends the life of organisms, from fruit flies to monkeys,and is associated with preserved physical health andcognition (Piper and Bartke, 2008). The second is cog-

* Corresponding author at: School of Psychology, University of Ottawa,200 Lees Avenue Room 260J, Ottawa, Ontario, K1N 6N5, Canada. Tel.:�1 613 562 5800 � 4562; fax: �1 613 562 5147.

E-mail address: [email protected] (C. Messier).

0197-4580/$ – see front matter © 2012 Elsevier Inc. All rights reserved.doi:10.1016/j.neurobiolaging.2011.02.020

nitive exercise, in the form of sustained mental chal-lenges and lifelong learning, which are associated pri-marily with preserved cognition but also with improvedhealth (Daffner, 2010). The third is often intertwinedwith cognitive exercise: sustained social engagement andinteractions (Depp et al., 2010). The fourth is physicalexercise, the focus of this review, which has also beenclaimed to help preserve physical and mental abilitiesthroughout aging. These four putative avenues to a longand healthy life are not equally appealing to peoplebecause following them involves some effort (physicaland/or mental) and appears to go against our naturalinclination to eat and to rest physically and mentally. Inthe case of physical exercise, it is ironic that, until a century
ago, most people engaged in strenuous daily physical activity
mailto:[email protected]

622.e30 D.I. Miller et al. / Neurobiology of Aging 33 (2012) 622.e29–622.e43

but lived a much shorter life. In Westernized societies today,machines do much of the work, while the average lifespan islonger than ever, but as a society we are returning to physicalactivity to improve and lengthen our lives.

A number of questions are raised by studies that haveasked whether these lifestyle activities, and exercise in par-ticular, have a positive impact on longevity and preservedphysical and mental abilities. The first is whether physicalexercise can really bring about cognitive benefits in humans.This is not a trivial question because, with the exception ofa few long lasting longitudinal studies that have includedobjective measures of physical exercise or fitness, we stillhave to rely on unreliable retrospective data about lifetimeexercise to answer this question. Moreover, if we do find anassociation between physical exercise and preserved cogni-tive abilities in aging, we must ask whether we are seeing atrue causal relationship, or whether it is merely that thosewho naturally and effortlessly engage in exercise are thesame people destined to lead long, healthy lives with pre-served cognition in old age. The third set of questionsrelates to the exercise itself: how much and which type ofexercise is optimal? Is this the same for everyone? Finally(and most importantly), can we mend our ways with theassurance that making lifestyle changes late in life willbring at least some of the same benefits as lifelong involve-ment in exercise? Interestingly, the same type of questionscan be raised when examining the impact of “cognitivetraining” on cognitive aging (Thom and Clare, 2011).

In the present review, we will examine whether availableresearch answers these questions, and if so, what answers itprovides. It is important to acknowledge at the outset thatthe four lifestyle factors (dietary restriction, cognitive exer-cise, social engagement and physical exercise) cannot becompletely isolated from each other. For example, peoplewho exercise in a social context (for example with friends)may also benefit from the social and cognitive stimulationthat comes from these interactions. Moreover, people whoeat less and maintain a lower weight may be more likely toengage in more vigorous exercise (Hagströmer et al., 2010).These interactions are difficult to disentangle even withsophisticated statistical models in human studies, and maybe more amenable to animal research. Finally, a number ofcommon aging-related pathological processes, such as hy-pertension and diabetes, also have an impact on cognition,likely due to the increase in cerebrovascular pathology theyappear to promote (Messier and Gagnon, 2009). The presentreview does not list all previous studies: readers are directedinstead to published reviews and meta-analyses (Angevarenet al., 2008; Colcombe and Kramer, 2003; Erickson andKramer, 2009; Etnier et al., 2006; Heyn et al., 2004; Hill-man et al., 2008; Kramer and Erickson, 2007; Kramer et al.,2006; Rockwood and Middleton, 2007) as well as a recentcomprehensive review of the effect of enrichment on cog-nition (Hertzog et al., 2009). These reviews generally con-
clude that exercise is associated with improved cognition
during aging. Animal and molecular studies also supportthis contention (Cotman et al., 2007).

In the present review, we examine human studies, andcomment on specific ones to illustrate methodological andconceptual limitations in the field. We suggest methodolog-ical strategies to improve the ability of future studies todetermine the impact of exercise on cognition during aging.We now turn to the major theme of this review and examinethe main challenges for studies that aim to determine ifphysical exercise has an impact on cognition.

2. Physical exercise and cognition

Normal aging is associated with a decrease in brain sizeand plasticity (Peters, 2006) that results in cognitivechanges, although the cognitive and brain changes are notalways proportional to each other. Moreover, some cogni-tive domains are more affected than others (Davidson andWinocur, 2010). Normal aging is also associated with adecrease in the intensity and frequency of physical activity(Lindwall et al., 2008). A number of possible reasons forthis decrease have been proposed (and most are obvious).First, the physical component of daily activities usuallydecreases with age; this is likely related to decreased socialengagement. Reduced interactions with family and friendsmay lead to reduced opportunities for daily exercise. Sec-ond, some older people believe that physical exercise assuch (i.e., “sports” activities) may not be appropriate fortheir age, and that exercise could be harmful to them (Irwinet al., 2004). Others are simply not convinced that exercisecould be beneficial to them in any way (Hassmén et al.,1992). Physical handicaps associated with aging are also apotential obstacle; however, many older adults have littleknowledge that exercise programs can be adapted to theirphysical capacities and limitations (Hassmén et al., 1992)and that benefits appear to occur with even small increasesin exercise that would be regarded as negligible for anotherage group (Buchner, 2009; Kruger et al., 2009). This ap-parent lack of enthusiasm for exercise among many olderadults is problematic because exercise is one of the fewsimple lifestyle changes that has been proposed to be pro-tective against cognitive decline, possibly even reversingsome of the age-associated changes in the brain.

In healthy older adults, exercise is associated with im-proved cardiovascular function (Colcombe et al., 2004a;Dustman et al., 1984; Kramer et al., 1999; Madden et al.,1989), reduced age-associated brain volume tissue loss(Colcombe et al., 2003; Erickson et al., 2009; Haskell et al.,1992), and increased brain volume (Colcombe et al., 2006).Moderately vigorous physical activity has also been asso-ciated with decreased mortality in middle aged men fol-lowed for over 20 years (Paffenbarger et al., 1993). In-creased functional status, as measured by the ability to
perform activities of daily living (ADL) and instrumental

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activities of daily living (IADL), is also associated withmoderately vigorous physical activity (Gu et al., 2009).

In general, the published longitudinal and cross sectionalstudies have consistently shown a small but positive rela-tionship between greater physical activity and lower risk ofcognitive decline in older people, whereas the results of theintervention studies (where cognition is measured first, ex-ercise is then introduced and cognition is again measuredafter a period of time) are mixed. Each type of study has itsstrengths and weaknesses. Cross sectional studies are themost feasible (and consequently, the most numerous be-cause of their relatively low cost). However, they cannotestablish causality and they usually rely on self-report forlifelong involvement in physical exercise, which is bound tobe inaccurate over the lifespan (Haskell et al., 1992). Lon-gitudinal studies cannot establish causation either, but theyinclude, in some instances, longitudinal objective measure-ments of fitness, which is a much better proxy for exerciseparticipation than self-report. However, fitness is a relativemeasure, because some fit people may exercise moderatelywhile others may exercise much more often but still remainless fit for other reasons (e.g., incipient heart disease). Lon-gitudinal studies can also be designed to study representa-tive samples of a population, increasing generalizeability.Intervention studies are the most useful to establish causal-ity because the intervention is controlled. However theytend to be of short duration because of their high cost. Theyare also highly susceptible to selection and dropout biases.They typically use only older participants and thus cannotanswer the question of whether lifelong exercise preservescognitive abilities. With these caveats in mind, we now turnto major limitations of the conclusions of studies that haveaimed to establish that physical exercise leads to better andpreserved cognition during aging.

3. Measurement of physical activity and fitness

Measurement of physical activity is difficult. Existingmethods generally fall into two categories: self-report (e.g.,questionnaires, diaries, logs) and objective measures (e.g.,motion sensors, accelerometers, pedometers, heart ratemonitoring, direct observation) (Warren et al., 2010). Theaccuracy of each method is directly related to its costs, withself-reports being the least expensive but also the leastaccurate (Shephard, 2003). The limitation of using self-reported exercise history rather than more objective mea-sures of physical fitness such as maximal heart rate (VO2

max), applies to cross sectional and longitudinal studies.Most studies use some type of interview or questionnaire toassess the physical fitness level of participants (Bixby et al.,2007; Clarkson-Smith and Hartley, 1989; Hatta et al., 2005;Hillman et al., 2004, 2006; Iwadate et al., 2005; Lindwall etal., 2008; Roth et al., 2003; Vance et al., 2005), but some
studies have also used VO2 max obtained during a maximal
exercise test on a treadmill (Colcombe et al., 2003; Dustmanet al., 1990).

Self-reported measures of physical fitness vary greatlyfrom study to study in their definition of what constitutesphysical activity. Some researchers have asked participantsto report only athletic activities. For example, a study of therelationship between self-reported exercise and change inexercise and cognition in 813 men and women enrolled inthe Swedish National Study of Aging and Care used twosurvey questions to measure older adults’ participation inexercise. The first question was “How often did you exer-cise with light intensity (e.g., walking on roads, in parks orin woods, short bicycle tours, light gymnastics, golf orsimilar) in the last 12 months?” and the second was “Howoften did you exercise strenuously (e.g., jogging, long andhigh-intensity walking, heavy garden work, long bicycle-tour, intense gymnastics, skating on lakes, skiing, ball-sports or similar activities)?” (Lindwall et al., 2008). Sim-ilarly, a study of the association between physical activityand visual attention in 140 older adults used a questionnairethat was specifically designed to measure participation inexercise and physical training (Roth et al., 2003). Yet, thequestionnaire did not include other activities such as gar-dening and house chores. Another large study initially gath-ered information on participants’ engagement in householdchores (Vance et al., 2005) but later dropped them from thecalculation of physical activity, although a “physical fitnessindex” in the same study included yard work and gardening.In contrast, other researchers have been very liberal in theirdefinitions of physical activity, including such activities ashousecleaning, gardening, and even walking up stairs(Bixby et al., 2007; Clarkson-Smith and Hartley, 1989;Hillman et al., 2004). This varying scope of what constitutes“exercise” makes comparison across studies difficult.

One eye-catching study used a “sweat index” to calculatethe physical fitness level of participants (Hillman et al.,2006) by asking people if they participated at least once aweek in a physical activity that was sufficiently intense forthem to start sweating. Participants who answered “yes”were then asked to indicate the approximate number oftimes per week this occurred. Although such an index isnovel and creative, it is unfortunately confounded with age,because exercise that does not raise a sweat at age 60 maydo so at age 70. Conversely, a high sweat index mayindicate a poor physical status at 60 but a rather good one at80 years of age. The usefulness of the measure is alsolimited by the physiological decrease in sweating with age(Foster et al., 1976).

Clear evidence for the limited usefulness of self-reportedmeasures of exercise comes from a study that found acorrelation between peak oxygen consumption (VO2 max)at baseline and memory performance (Barnes et al., 2003).However, there was no association between the participants’self-reported participation in physical activity and their per-
formance on memory tests (Barnes, 2001). In a recent study,


the correlations between the results of exercise question-naires administered on 2 occasions ranged from 0.5 formoderate exercise and 0.47 for light exercise to 0.33 forvigorous exercise (Geda et al., 2010). Taken together, theseresults indicate the need to perform objective assessments offitness to complement exercise questionnaires (Moy et al.,2008). Recently, two studies have attempted to verify ifcardiorespiratory fitness could be predicted using demo-graphic data and one simple self-reported physical activityscale (Jurca et al., 2005; Mailey et al., 2010). Both studiesshowed that sex, age, body mass index, and a self-reportedscale could together provide a good estimate of cardiore-spiratory fitness. However, the self-reported scale wasfound to contribute the least to the estimate of cardiorespi-ratory fitness (Mailey et al., 2010).

As we can see, the heterogeneous definition of physicalactivity in studies that examine its interaction with cognitionduring aging is difficult to untangle from the aging processitself, which leads to progressively less physical activity inmany older people (Center for Disease Control, 2008; Donget al., 2004; Hagströmer et al., 2010). Following the “use itor lose it” tendency, less physically fit people will tend toexercise less and thus become even less fit. Conversely,healthier or more physically fit older adults may continueexercising at a constant rate for a longer period. This rela-tionship makes it more difficult to determine a causal linkbetween exercise and cognition. The foundations for a con-sensus position to define what constitutes exercise and howbest to measure exercise objectively has recently been ad-dressed in the context of epidemiological studies (Warren etal., 2010); the reader is directed to that review for a moreextensive discussion of exercise and fitness measurements.

4. Type and intensity of physical activity

The type and intensity of physical activity appears tohave an important influence on the relationship betweenexercise and cognition. Within the intervention studies,there seems to be a general consensus among researchersthat aerobic exercise (i.e., geared toward enhancement ofcardiovascular function), such as running, biking, or fastwalking, is associated with better performance on cognitivemeasures, whereas anaerobic exercise such as stretching,toning, or yoga does not have the same effect. In someintervention studies, participants in the stretching, toning, oryoga groups were used as controls for an aerobic exercisegroup (Colcombe et al., 2004a, 2006; Dustman et al., 1984).Participants in the anaerobic group in these studies did showa small improvement in aerobic capacity. However, theirimprovements on neuropsychological tests (Dustman et al.,1984), increases in brain activation (Colcombe et al.,2004a), or increases in brain tissue density (Colcombe et al.,2006) were smaller than the changes observed in the aerobicgroup. In 1 study, the combined changes on cognitive tests
after the toning/stretching intervention were significant but
absent in the “no intervention” group (Dustman et al., 1984)suggesting a possibility of an effect of nonaerobic exercisethat is smaller than that observed with aerobic exercise.

Intervention studies vary widely in the duration of exer-cise interventions used by researchers; the length of exerciseinterventions ranges from 8 weeks (Bakken et al., 2001) to3 years (Rikli and Edwards, 1991). However, most inter-ventions have lasted between 4 and 6 months (Colcombe etal., 2004a, 2006; Dustman et al., 1984; Kramer et al., 1999;Lautenschlager et al., 2008; Madden et al., 1989; O’Dwyeret al., 2007).

Perhaps not surprisingly, the duration of the exerciseintervention seems to exert a strong influence on the ob-served effect size of the association with cognition. Twometa-analyses examining the relationship between exerciseand cognition found that studies that used long lastingtraining programs (6 or more months) have a greater effecton cognitive performance than do short term programs (1–3months) (Colcombe and Kramer, 2003). One alternativehypothesis is that people who are less fit and less healthymay stop participating earlier in the study (particularly in along intervention or in the highest intensity group), resultingin a different group composition at the end of the interven-tion (Ghisletta et al., 2006; Lindenberger et al., 2002).

The exercise protocols employed by most researchers inintervention studies consist of sessions that last between 30minutes and 1 hour and occur 3 days per week (Bakken etal., 2001; Blumenthal et al., 1991; Colcombe et al., 2004b;Dustman et al., 1984; Madden et al., 1989; O’Dwyer et al.,2007). However, some researchers have used a gradualincrease in exercise intensity and duration (Colcombe et al.,2004a) or 2 exercise sessions per week (Fabre et al., 1999).The duration of each exercise session appears to be impor-tant for improving cognitive function. Colcombe and Kram-er’s meta-analysis found that studies using sessions of mod-erate duration (31–45 minutes) had the largest effect sizesand studies using exercise sessions lasting less than 30minutes did not show an association with cognitive functionmeasures (Colcombe and Kramer, 2003).

Some more recent cross sectional studies also supportthis conclusion. A study of 813 participants aged 60 yearsand older found that moderate exercise rather than strenuousphysical activity had a stronger association with better cog-nition (Lindwall et al., 2008). Another cross sectional studyby the same research group, examining the relationshipbetween exercise and depression, found similar results:moderate exercise was associated with fewer depressivesymptoms in adults over the age of 60, while the partici-pants in the light and strenuous exercise groups had moresymptoms of depression (Lindwall et al., 2007). In these lasttwo studies, light intensity was defined as walking on roads,in parks, or in the woods, short bicycle tours, light gymnas-tics, golf, or similar exercise, while strenuous activity was
defined as jogging, long and high-intensity walking, heavy


garden work, long bicycle tours, intense gymnastics, skatingon lakes, skiing, ball sports, or similar activities.

Epidemiological studies also support an intensity effect.One such study followed 295 healthy men from the surviv-ing representative cohort of 2285 men born between 1900and 1920 and recruited from the Finland, Italy and Nether-lands Elderly Study (van Gelder et al., 2004). Follow-upwas carried out in 1990, 1995, and 2000. Exercise wasassessed with a self-administered questionnaire; time spentexercising and average intensity were computed based onresponses to the questionnaire. Only men who were healthyand cognitively intact in the 1990 follow-up were included(average age of 74 years in 1990). Complete informationwas gathered from 1149 men in 1990. The researchersfound no significant difference in cognition, as measured bythe Mini-Mental State Examination (MMSE), between theexercisers and nonexercisers in 1990. A decade later, how-ever, the older adults who had maintained or increased theirphysical activity during the 10-year follow-up periodshowed lower levels of cognitive decline compared with theolder adults who either did not participate in physical ac-tivity or who exercised at lower levels of intensity. In thisstudy, intensity was estimated by summing products of thenumber of minutes per week of a given activity multipliedby an estimated energy expanded for that activity (in kcal/kg-hour). The estimated intensity of physical exercise wasfound to moderate the relationship between exercise andcognitive decline: the older adults who exercised at thelowest intensity were more likely to develop dementia 10years later compared with those who exercised at higherintensity.

Another epidemiological study examined the relation-ship between walking and the risk of dementia later in lifein a sample of 2257 men from the Honolulu-Asia AgingStudy (Abbott et al., 2004). This project followed a largesample of Hawaiian men of Japanese descent, starting in1965 (Yano et al., 1984); the study of the impact of exerciseon cognition and dementia was initiated in 1991. In thisstudy, exercise in the form of walking was assessed atbaseline via a combination of self-report and a test thatevaluated the ability to do a number of simple movementsassociated with balance and walking (e.g., length of time towalk 10 feet). Men who walked faster and more regularly(as evaluated 6 years previously) were less likely to developdementia.

A Canadian epidemiological study also reported thatphysical activity reduced the risk of cognitive decline in arepresentative sample of elderly people (Laurin et al., 2001).This study followed 4615 men and women aged 65 andolder from the Canadian Study of Health and Aging over aperiod of 5 years. The results showed a significant positiveeffect of exercise (as self-reported at baseline) in reducingthe risk of developing Alzheimer’s dementia; notably, how-ever, this association was much stronger for women than for
men. This study revealed a dose-response effect, indicating
that higher reported levels of physical activity were associ-ated with lower risk of cognitive impairment and lowermortality after 5 years, with a 40% death occurrence in thegroup that did not exercise compared with a 13.5% rate forpeople that engaged in the most exercise activities. How-ever, another large epidemiological study found that bothmoderate exercise (such as playing 18 holes of golf once aweek, playing tennis twice a week, or walking 1.6 km/day)and strenuous exercise (such as jogging or skiing) wereassociated with better cognition (Yaffe et al., 2001).

Although a number of studies suggest that “moderate”exercise (albeit often based on self-report) is most stronglycorrelated with preserved cognition, the lack of consensuson how to measure intensity leads to a lack of clear guide-lines for the optimal duration/intensity, the bare minimumto yield cognitive improvement (or, at least, prevent cogni-tive decline over time), and how many people (and who)would benefit from which exercise protocol.

5. At what age is the strongest association betweenexercise and cognition found?

One factor usually put forward to explain the largerfacilitating effect of exercise on cognition in older adults isthat they, as a group, have more limited cognitive resourcesand are unable to perform more complex tasks as effectivelyor as quickly as younger adults, leaving ample room forimprovement. Of course, ceiling effects can easily occur inpeople younger than 70 years (Wang et al., 2009) becausedecreased cognition is more often found in people over 70(Ryan and Geckle, 2000; Salthouse, 2010). Putting thiscaveat aside, support for a greater effect of exercise oncognition in older adults comes from a meta-analysis show-ing that the effect size of exercise on cognitive functionvaried as a function of participants’ age (Colcombe andKramer, 2003). For the group aged 55–65 years, the effectsize was 0.29, for the group of 66–70 years old the effectsize was 0.69, and for the oldest group (aged 71–80 years),the effect size was 0.55.

Not all evidence, however, is in line with this idea.Another meta-analysis indicated that the largest associationbetween exercise and cognition was found in adults aged 40to 60 years; moreover, the youngest group (18–30 yearsold) showed a larger association than the oldest group(60–90 years old) (Etnier et al., 1997). The conflictingfindings of the two meta-analyses could be due to differentselection criteria, and/or the way in which the age groupswere coded. In the Colcombe and Kramer (2003) meta-analysis, 3 age groups were included: 55–65, 66–70, and71� years old. They did not include studies in which par-ticipants were younger than 55 years of age. Etnier et al.(1997), in contrast, assigned participants from ages 60 to 90into one broad group which spanned all three senior groupsin Colcombe and Kramer (2003). In addition to the conflict-
ing findings of the 2 meta-analyses discussed above, some


studies have not found any changes in cognition in olderadults (aged between 60 and 83) following either 16 weeksor 40 weeks of aerobic exercise intervention (Blumenthal etal., 1991; Madden et al., 1989). Clearly, the effect of age inmoderating the relationship between exercise and cognitivefunction has yet to be clearly established, and future re-search is needed to examine the magnitude and the directionof the effect, as well as the impact of factors such asintensity of exercise (as a function of age), and the interac-tion between exercise, health status (as a function of age),and cognition. Such knowledge is central if we are to beable to formulate exercise recommendations. In the nextsection, we discuss whether health status (including depres-sion) can be a mediating factor for the effect of exercise oncognition.

6. Do health status and depression play a role?

Two additional variables may be important: generalphysical health, and mental health (especially depression).For the former variable, people in good health at the start ofa study may tend to exercise more and exhibit better cog-nitive health. For the latter variable, physical activity hasbeen linked to improved mood in depressed patients, im-proved overall psychological well-being, and decreasedstress and anxiety levels (Hill et al., 1993; Lindwall et al.,2006; Taylor et al., 1985). Exercise can improve depressedpatients’ ability to deal with stress and their self-concept,confidence, self-image, and social skills (Taylor et al.,1985). Improved mood in depressed patients is, in turn, alsoassociated with improved cognition (Thomas and O’Brien,2008). Whether this association holds true for nondepressedolder adults and reflects a causative link between the im-proved cognition and the effect of exercise on depressionremains to be determined (Brown et al., 2009; Williams andLord, 1997). Because these two factors are often inter-twined, we review them together in the relatively few stud-ies that have examined them.

In the Canadian Study of Health and Aging discussedabove, two additional analyses were used to address thepossibility that the association between exercise and cogni-tion (or cognitive disorders) may result from the fact thatpeople in good health at the start of the study tended toexercise more and exhibit better cognitive health. The re-searchers in this study added variables related to healthstatus into their logistic models, and observed that riskestimates remained very similar to those initially reported(when controlling for age and education only). The datawere also reanalyzed excluding subjects who reported earlycognitive decline symptoms in the first 2 years of follow-up;conclusions remained unchanged in this analysis (Laurin etal., 2001). When the participants were followed up 5 yearslater, the protective effect of exercise (at least 3 times perweek, at least as intense as walking) was still present
(Middleton et al., 2008) although no analysis of the contri-
bution of health status was performed. This large epidemi-ological study suggests that the association between exer-cise and preserved cognition cannot be solely explained byan association between good health at the outset of the studyand sustained levels of exercise.

Similar results were obtained in a prospective epidemi-ological study of a representative sample of 9704 womenaged 65 and over from the Study of Osteoporotic Fracture(Yaffe et al., 2001). In this study, lower self-reportedweekly exercise in general, and self-reported weeklyamount of walking in particular, were associated with cog-nitive decline as measured by the Mini-Mental State Exam-ination (MMSE) (Gagnon et al., 1990) 6 to 8 years later.This association remained unchanged after statistical adjust-ment for baseline health and functional status includingdepression.

The Adult Changes in Thought longitudinal study ofaging and dementia followed 1740 men and women aged 65years and older for 6 years (Larson et al., 2006). Exercisewas estimated from self-reports and a brief physical func-tioning test (timed short walk, time to stand up from a chair5 times, balance test and grip strength). Those who exer-cised more at baseline had higher education and lowerdepression symptoms and there was a 32% risk reductionfor developing dementia among those participants who hadreported 6 years earlier that they exercised 3 or more timesper week. The risk reduction was greater for participantswho had low physical functioning at baseline. Survivalanalysis suggested that exercise reduces the dementia riskby delaying its onset in people who exercised regularly. Theincidence of dementia was 13.0 per 1000 person-years forpeople who exercised 3 or more times per week, comparedwith 19.7 per 1000 person-years for people who exercisedfewer than 3 times per week. When several confoundingfactors were simultaneously adjusted for statistically (in-cluding education and depression), exercise was still pro-tective (odds ratio of 0.68).

Because depression has been associated with both exer-cise and cognitive deficits (Yaffe et al., 1999), many exper-iments have tried to establish the benefits of exercise fordepressive symptoms (e.g., Hamer et al., 2009). One im-portant caveat is that to date most studies have not includeda large number of clinically depressed participants, mostlikely because they excluded themselves by refusing toparticipate or did not complete the physical activity inter-vention. This general bias may reduce the ability of second-ary statistical analyses to shed light on the issue, because thestudies include few depressed participants with a smallerrange of depressive symptoms. With this caveat in mind, wenow turn to a review of some of the findings.

Few cross sectional and intervention studies have in-cluded a measure of depression, either to exclude depressedparticipants from the study (Bixby et al., 2007) or as acovariate in the statistical analyses (Dustman et al., 1984).
We are aware of only one study that included both a mea-

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sure of depressive symptoms and a measure of social stim-ulation (Vance et al., 2005). Results were mixed: whileDustman et al. (1984) observed an improvement in cogni-ion but not in depression scores after a 4-month exercisentervention, Vance et al. (2005) found that sedentary life-tyle was associated with better cognition and worse depres-ion.

However, several epidemiological studies have includedeasures of depression, most often the Geriatric Depressioncale (Herrman et al., 1996). The results of the Swedishational Study on Aging and Care provide indirect support

or the depression-reduction hypothesis of exercise effectsn cognition. Older individuals who had previously beenhysically active and had decreased the frequency and in-ensity of exercise or stopped exercising in the previous 12onths showed the same cognitive decline as individualsho had never exercised (Lindwall et al., 2008). Moreover,

ndividuals who had stopped or decreased their physicalctivity in the preceding 12 months had similar depressioncores as the inactive group; the depression scores wereigher than in the continuously exercising group (Lindwallt al., 2006). Finally, a recent cross sectional study foundhat, in patients with coronary heart disease, VO2 max wasssociated with executive functions (as measured by therail-Making Test Part B, the Stroop test, and the Digitymbol Coding task) even after adjustment for health statusnd depression (Swardfager et al., 2010). However the as-ociation between exercise and verbal memory was notignificant after adjustment for health status, including dia-etes and depression.

However, a recent study with identical twin pairs foundhat the twin who exercised the most (in each pair) dis-layed as many symptoms of depression as the twin whoxercised less; moreover, longitudinal analysis of exercisearticipation showed no relation between increased exercisend decreased depressive symptoms, even though there wassignificant association between exercise and depression

cross all participants similar to the one observed in non-win studies (De Moor et al., 2008). These results suggesthat the longitudinal association between exercise and de-ressive symptoms in this twin study was due not to a causalelationship between exercise and depression, but rather tonderlying overlapping common genetic factors. That is,here might be a common genetic susceptibility for bothepressive symptoms and lack of habitual physical exercise.

In summary, some studies suggest that participation inxercise is associated with a decrease in depressive symp-oms, indicating that depression could mediate the effect ofxercise on cognition. However, the few studies that haveontrolled for depressive symptoms have not found thisnote, that this conclusion should be tempered by the lowumber of depressed participants and the restricted range ofepressive symptoms in most studies, both of which wouldeduce their ability to reject the null hypothesis). A twin
tudy indicated that the association between exercise and a
epression might not be causal, but rather might reveal aommon underlying genetic factor. Of course, such an un-erlying genetic factor might only be valid for spontaneousctivities of daily life and not extend to voluntary “sport”hysical activities or a prescribed exercise regimen (Wolffnd Strohle, 2010).

The existing literature has tried to disentangle the possi-le negative impact of depression and pre-existing healthroblems as mediator variables. In the same fashion, theontribution of the positive effects of other factors, such asocial and cognitive stimulation, is difficult to untanglerom the effects of exercise. The next section briefly reviewsome studies that illustrate the potential impact of theseactors, and some of the difficulties in assessing them.

. The potential contributions of social and cognitivetimulation

Some studies have attempted to control for other factorshat may moderate the relationship between exercise andognition. However, despite many researchers’ intuitionshat cognitive and social stimulation might be important,ost studies have not attempted to measure these factors.he only variable sometimes included that might give in-estigators a sense of participants’ engagement in cogni-ively stimulating activities is years of education, which is atest a limited proxy for involvement in cognitively stimu-ating activities (Baldivia et al., 2008; Hultsch et al., 1999).

The Chicago Health and Aging Project examinedhether the impact of physical exercise on cognitive declineas independent of cognitive stimulation in a sample of055 men and women aged 65 and older; participants com-rised 52% of the residents in 3 Chicago neighborhoodsged 65 years and older that were able to at least walk ahort distance (Sturman et al., 2005). The researchers gath-red information from participants concerning participationn physical activity and seven cognitively stimulating activ-ties including the following: watching TV (although thelassification of TV as cognitively stimulating is debatable),eading newspapers, reading books, going to museums, lis-ening to the radio, and playing games such as puzzles orrosswords. The results indicated that regular exercise isssociated with a small reduction in the risk of cognitiveecline; however, this effect was no longer significant afterontrolling for cognitive stimulation. This finding suggestshat cognitive activity may mediate the effect of exercise, orhat exercise and cognitive activities are covariates.

To our knowledge, only one small study has attempted toxamine the separate, and possibly combined, effects ofxercise and cognitive stimulation on cognition. It involved

memory-training programs in 32 older adults aged be-ween 60 and 76 years (Fabre et al., 1999). Participants wereandomly assigned to 1 of 4 groups: (1) aerobic training, (2)erobic plus memory training, (3) memory training only,
nd (4) a control group. Participants in the exercise groups


performed aerobic exercise (walking and running outdoors)for 1 hour, twice a week for a month. The aerobic intensitywas individualized according to the baseline physical fitnesslevel of each participant. The memory training sessionslasted 90 minutes, and occurred once a week for 8 weeks. Inthese sessions, participants learned mnemonic strategies.Overall, the improvement observed in the combined train-ing group (physical and memory) was greater than either inthe physical or the memory training groups on the two testbatteries assessing learning, recall, orientation, semanticfluency, visual reproduction, and memory. This study sug-gests that exercise training may have additive effects withother training programs that could increase cognition in theelderly. From a practical point of view, it may prove veryuseful to learn more about the types of combination pro-grams that include exercise and can help older adults im-prove their quality of life. More research is needed toidentify the optimal combinations of exercise interventions.

Only one epidemiological study, the MRC National Sur-vey of Health and Development, has attempted to controlfor socially stimulating activities in examining the relation-ship between exercise and cognitive status. This studyfound no association between exercise participation andcognitive status later in life (Richards et al., 2003). It in-cluded a representative sample of 3035 men and womenfrom the British 1946 birth cohort, and examined the rela-tionship between two types of activities at the age of 36(leisure activities and physical exercise) with verbal mem-ory at the age of 43 and 53. Greater physical activity wasassociated with lower risk of memory decline between theages of 43 and 53. Both leisure activities (all involvingsocial contacts) and physical activities were associated withverbal memory performance at the age of 43: after control-ling for leisure activities, physical activity no longer had anindependent effect on verbal memory at the age of 43.However, the association between physical activities andcognition was no longer explained by leisure activities at 53.No further analyses were performed because, in this study,the measure of leisure activities changed between the twofollow-ups. This study also included relatively young par-ticipants; the absence of effects of other variables may notbe surprising in this younger cohort because of possibleceiling effects in the cognitive measures.

An experiment by Hassmén et al. (1992) is the only one,to our knowledge, that attempted to control for social stim-ulation. In this study, the control group met as frequently asthe experimental group, but performed mental arithmetic,problem solving, and logical thinking tasks rather thanphysical exercise. The use of the social control group waswell-justified, but in our opinion the choice of activity thatwould represent “social stimulation” was questionable, be-cause the problem solving, math problems, and logicalthinking training may actually have prepared the “control”subjects for the cognitive tests that were administered at the
end of the intervention period (face recognition and three
computerized tests: simple reaction time, complex reactiontime, and digit span). The study found no cognitive differ-ences between subjects in the exercise and control groups,and attributed the lack of effect to the low intensity of theexercise intervention. It is also possible that the choice of“socially stimulating” activities in the control group mayhave obscured the impact of the exercise intervention. Onelongitudinal study that attempted to separate the effects ofsocial stimulation from those of physical exercise on verbalmemory performance found that, after including partici-pants’ leisure and social activities (going out, religiousaffiliation) in the analysis, the effect of physical activity wasno longer significant (Richards et al., 2003).

Indirect support for the social stimulation hypothesis alsocomes from a meta-analysis in which the researchers re-ported that the size of the group in which participantsperformed exercise influenced the effect size on cognitionmeasures (Etnier et al., 1997). The effect sizes in studies inwhich exercise groups consisted of more than 20 peoplewere significantly larger than those studies in which partic-ipants were exercising alone. That is, the positive effects ofexercise on cognition increased as the size (alone, 1–10,11–20, and more than 20 participants) of the exercise groupincreased. It is possible that the observed improvements incognition were largely (or partially) due to the social stim-ulation that the participants received in addition to theexercise intervention.

The exact mechanism by which social stimulation im-proves cognition is unknown. One proposed explanationfocuses on the motivational factors that may come into play.Most people see exercise as a desirable behavior; thus,many people who engage in regular physical activity arepraised by others for their exercise routine (Hughes, 1984).The social reinforcement that exercisers receive may in turnimpact their performance on cognitive measures by increas-ing their motivation, self-efficacy, and/or self-confidence, orby reducing anxiety (Bennett et al., 2006).

One of the main methodological limitations in the exist-ing interventional research is the lack of adequate controlsto take into account the social and cognitive stimulation thatparticipants in the intervention groups receive in addition tophysical exercise. Some of the studies reviewed here usedcontrol groups that did not receive any intervention, butwere contacted at the beginning and at the end of theinvestigation (Bakken et al., 2001; Dustman et al., 1984;Hawkins et al., 1992; Hill et al., 1993). Some studies useda control group that received an alternative to aerobic ex-ercise, which consisted of stretching and toning exercises(Colcombe et al., 2004a, 2006; Kramer et al., 1999). Otherstudies used two control groups, one that performednonaerobic exercise (yoga) and another wait list control(Blumenthal et al., 1991; Madden et al., 1989). Only onestudy used a cognitive stimulation group, a group that re-ceived a combination of cognitive and physical stimulation,
and a control group that underwent no intervention (Fabre et

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al., 1999). It is interesting that in this study, both the cog-nitive training and the aerobic training improved cognitionto the same extent, but the combination of cognitive andaerobic training did not lead to additional gains. Finally, onestudy used a control group that was contacted as frequentlyas the experimental group but engaged in cognitive tasksrather than exercise (Hassmén et al., 1992). In that latterstudy, the control group improved in some of the cognitivemeasures but the low number of participants (n � 8) in eachgroup is problematic. The interaction of cognitive activitiesand cognitive performance independently of physical fitnessis suggested by a recent study that examined the predictorsof cognitive performance in older women (Eskes et al.,2010). This study showed that, age and education explained22% of the variance of cognitive test results, fitness (VO2

max) explained 12% of the variance, while self-reportedcognitive activities explained an additional 22% of the vari-ance. However in this study, self-reported cognitive activi-ties did not correlate with physical fitness or cardiovascularmeasures, indicating independent factors.

One serious but rarely-acknowledged problem in thesestudies is that just by participating, at least some membersof the control group may be led to increase their physicalactivity (imitation of treatment). For example, Ruscheweyhet al. (2009) examined the impact of a 6-month interventioninvolving low- and medium-intensity aerobic exercise oncognition and brain volume. Yet, in postintervention inter-views, all participants, including controls, indicated thatthey had increased their daily physical activities at leastsomewhat.

Another common problem is especially evident in thestudies that have included some kind of an alternative to a“no contact” control group as an attempt to rule out thesocial stimulation component of the physical intervention.Some used a yoga control group to reduce the social stim-ulation confound by providing social contact but no aerobictraining (Blumenthal et al., 1991; Madden et al., 1989).However, the 3 studies that have included only a stretchingand toning control group and no other “no contact” controlgroup all reported an increase of aerobic capacity (VO2

max) in these stretching and toning participants. In 1 study,there was a 9% improvement in the VO2 max levels ofcontrol” participants as well as improvement on neuropsy-hological measures (Dustman et al., 1984). Two othertudies reported a 2.9% (Colcombe et al., 2004a) and a 5.3%mprovement in VO2 max (Colcombe et al., 2006) in theoning and stretching exercise control group. Althoughhese changes did not reach statistical significance, theyake it seem unlikely that any “control” group that per-

orms anaerobic exercise is controlling only for social stim-lation; any additional exercise likely leads to some im-rovement in fitness. A more appropriate social stimulationontrol might be a group that met to perform some kind ofocial activity (such as involvement in an interesting dis-
ussion) but did not perform any type of exercise. To our
nowledge, however, this has rarely been done (but see, forxample, Stine-Morrow et al., 2008). Interestingly, a recenttudy reporting a 4.5% improvement in VO2 max in an

aerobic walking group (and no change in VO2 max in astretching and toning group) did not find any significantcognitive function improvement in the exercise group al-though, a modest trend toward cognitive improvement wasobserved in the aerobic walking group (Voss et al., 2010).Together, these studies indicate that the amplitude of VO2

max may be important to observe cognitive changes follow-ing exercise training.

It is clear that any positive effect of physical activity oncognitive aging is still confounded with a number of otherfactors, including level of cognitive activities and socialinteractions. This is a serious limitation because prescrip-tions of more exercise may not benefit people who engagein fewer social and cognitive activities, and exercise maysimply be a marker variable for people with high involve-ment in cognitive and social activities. On the other hand,exercise is more beneficial to people with lower educationlevels (Yaffe et al., 2001), which is a proxy measure ofcognitive engagement. This finding suggests that the effectsof cognitive stimulation and exercise on cognitive aging arenot necessarily additive (Fabre et al., 1999; O’Dwyer et al.,2007). This confound has not been sufficiently examined inlongitudinal studies (using cognitive tests that avoid ceilingeffects; for more on this see below) to conclude that cog-nitive and social activities underlie the positive effects ofexercise on cognition. In the next, and final, section, weaddress some issues regarding the type of outcome mea-sures used, which include cognitive measures and, morerecently, brain volume measures.

8. Outcome measures: the type of cognitive task used

In general, the use of standardized tests that can beadjusted using normative data should be promoted (Geda etal., 2010) because it controls for effects of age and educa-tion, two major contributors of variability on cognitivemeasures. Early on, it was suggested that the positive effectof exercise was observed on “complex” rather than on“simple” cognitive tasks (Weingarten, 1973). An often-citedmeta-analysis of 18 intervention studies suggested that ex-ercise was more beneficial on tasks that require executivefunction control than tasks that do not. Exercise appeared tohave a generally positive effect on a number of cognitivefunctions such as processing speed, visuospatial function,and controlled processing, but the largest effect sizes wereon tests thought to depend more on executive functions(Colcombe and Kramer, 2003). Other studies have alsosupported this finding by showing that physical exercise ismore strongly related to performance during task conditionsthat require greater amounts of interference control (Hill-man et al., 2006). However, another meta-analysis found no
effect of exercise on executive function and working mem-

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ory in 11 intervention studies (Angevaren et al., 2008). Inthat meta-analysis, the tasks that were associated with largereffect sizes included cognitive speed, auditory and visualattention, and delayed memory. Only four studies wereincluded in both meta-analyses, however (Emery and Gatz,1990; Emery et al., 1998; Madden et al., 1989; Moul et al.,1995), which may explain the diverging conclusions.

Another advantage of using standardized testing is thatmethods and scoring procedures are the same. However,different studies have used a variety of cognitive tasks tomeasure cognitive improvement following exercise inter-vention. Some researchers have included in their cognitivebatteries simple and choice reaction time (RT) tasks inwhich the participants are instructed to respond to a stimu-lus as quickly as possible (Colcombe et al., 2004a; Dustmanet al., 1984; Hassmén et al., 1992; O’Dwyer et al., 2007).However, even when the tasks appear to be quite similaracross studies, we still find only equivocal support for thebenefits of exercise: Colcombe et al. (2004), Dustman et al.(1984), and Hawkins et al. (1992) found improvement ontheir RT tasks, while Hassmén et al. (1992) did not. Krameret al. (1999) also found an improvement in performance on

T tasks that they argued involved an executive functionomponent; Madden et al. (1989), in contrast, found noffect of exercise on performance in an RT task of episodicnd semantic memory.

Other studies have included measures of higher ordercognitive processes such as planning, response inhibition,and working memory, but here again the data are equivocal.Dustman et al. (1984) found an improvement on some tasks(Digit Symbol, Dots Estimation [a detection task], andStroop Color and Word Test) following 4 months of aerobicexercise. However, following an exercise intervention of9–12 months and an improvement of VO2 max of 23%, Hillt al. (1993) found no improvement on the Logical Memorymmediate Recall and the Digit Symbol subtests of the

echsler Memory Scale and Wechsler Adult Intelligenceest (Revised version [1981]). In addition, Blumenthal et al.

1991) found no difference between their experimental andontrol groups on Digit Span, Benton Revised Visual At-ention, Selective Reminding, Digit Symbol, Trail Making,nd “2 and 7” tests (Ruff et al., 1986) after an exercisentervention of 4 months. Blumenthal et al. attributed themall improvement on test performance to practice effects.

Practice effects are rarely explicitly discussed in thexercise literature, but must be considered when choosingasks and analyzing results given that some tests are morerone to practice effects (Awad et al., 2004; Wilson et al.,006). For example, in two studies, a small improvement inognitive measures performance was attributed to practiceffects, even though the exercise intervention led to signif-cant improvement in participants’ VO2 max: 11.02% in

Madden et al. (1989) and 10% to 15% in Blumenthal et al.(1991). Although practice effects appear not to be a function
of age, sex, or education (Wilson et al., 2006, 2009), it
would be important to determine if exercise or fitness statusare associated with differential practice effects. An addedcomplication is that some tests are more prone to practiceeffects than are others (Awad et al., 2004; Wilson et al.,2006). Moreover, in some tasks practice effects may beobserved in healthy adults but not patients with cognitiveimpairment (e.g., Cooper et al., 2004). One way around thisgeneral problem is to have participants initially perform thetasks that they will be tested on so that the improvementassociated with familiarity is partly taken into account, astrategy used in a recent study of the effect of aerobicexercise in mild cognitive impairment (MCI) (Baker et al.,2010). This presents its own problems, of course, if differentgroups do not start out at the same baseline level of perfor-mance or if cognitive impairment diminishes practice ef-fects in some participants but not others.

8.1. Brain volume measures

Ultimately, preserved cognition in aging depends on ahealthy brain, and one indicator of a healthy brain is pre-served brain volume. Conversely, loss of neurons and con-nectivity is associated with reduced gray and white mattervolumes. Studies that include brain volume measures arebecoming more common, but they are still subject to manyof the same confounds and caveats as purely behavioralstudies. Various studies have indicated a link between phys-ical activity and brain volume. Using an in vivo voxel-basedmorphometric technique, researchers measured differencesin brain tissue volume between active and inactive olderadults aged 55 years and older, and correlated volumes withfitness as measured by estimated VO2 max (Colcombe et al.,2003). Older adults with better fitness had greater graymatter volumes in the prefrontal, superior parietal, and mid-dle/inferior temporal cortices, and greater white matter vol-umes in the anterior tracts and in transverse tracts runningbetween the frontal and the posterior parietal lobes. In thestudy sample, the areas of the brain that were the mosthighly correlated with age also showed the greatest corre-lation between volume and physical fitness.

In a subsequent study, the same researchers found anincrease in brain volume in several regions of the brain ofolder adults (aged 60–79 years) who performed 6 months ofaerobic exercise compared with age-matched control partic-ipants (Colcombe et al., 2006). The regions that showed thegreatest increase in brain volume were also associated withage-related decline in brain structure and cognition, namelythe dorsal anterior cingulate cortex, the dorsolateral regionof the inferior frontal gyrus, and the dorsal aspect of leftsuperior temporal lobe, as well as the anterior third of thecorpus callosum. The study did not include any type ofneuropsychological assessment; it would be of interest infuture to correlate the observed changes in brain volumewith functional activity during cognitive tests known to
depend on the areas that showed the largest improvements.

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Another provocative study found a positive relationshipbetween VO2 max and hippocampal volume after adjustingor age, sex, and education (Erickson et al., 2009). Interest-ngly, a 3-month aerobic exercise regimen can lead to aolume increase of the dentate gyrus of the hippocampus inounger (21–45 years) participants (Pereira et al., 2007).articipation in exercise (albeit estimated from a question-aire; Bowles et al., 2004) was associated with a reductionf the rate of shrinkage of the medial temporal lobe in olderdults (with a mean age of 68 years) (Bugg and Head,011). Another study found that walking 72 city blocks aeek was associated with preserved cortical gray matterolume 9 years later (Erickson et al., 2010). Similar findingsave been observed in older adults at risk for Alzheimer’sisease and early stage Alzheimer’s patients (Clinical De-entia Rating: 0.5–1.0) (Burns et al., 2008a, 2008b; Honea

t al., 2009). In one of these studies, no effect of thepolipoprotein E (APOE)-epsilon 4 allele was found on thetness-brain volume association (Honea et al., 2009): Alz-eimer’s disease (AD) patients with higher cardiorespira-ory fitness had greater parietal and medial temporalolume, regardless of APOE genotype. Two large epidemi-logical studies examined if the association between exer-ise and reduced risk of dementia was modulated by APOEenotype. One study found this to be the case (Podewils etl., 2005) while the other did not (Larson et al., 2006). Thessociation between exercise and brain volume is poten-ially significant because greater hippocampal and brainolume is associated with preserved cognition despite highurdens of pathological lesions associated with Alzheimer’sisease (Erten-Lyons et al., 2009).

One important caveat in interpreting the results of thesetudies, however, is that other factors such as depression,iabetes, reduced high density lipoprotein (HDL) levels,nd hyposmia (reduced olfaction) are also associated witholume reduction of the gray and white matter (Bitter, 2010;ruehl et al., 2009; Colla et al., 2007; Convit et al., 2003;ard et al., 2010). Because these conditions are observed in

lder people, they may mediate some of the observed struc-ural changes described above. Also, morphometric data doot specify which brain compartment is contributing to theolume changes (it could be anything from extracellularuid content to glial cells and blood vessels); the contribu-

ion of neurons and their neuropil to the volume changesemain to be studied. Furthermore, although many moreunctional magnetic resonance imaging (fMRI) studieshould be expected in the near future, the field has yet toeach a consensus on whether greater activation in relationo a given level of cognitive performance should be consid-red to be “better” (reflecting a large region robustly at worko support a task) or “worse” (reflecting neural inefficiency;or a similar debate in the cognitive aging literature; see:uckner, 2004; Cabeza et al., 2002).

In summary, the few studies suggesting that exercise
odifies brain structure, task-induced metabolic activity, g
nd brain connectivity have attracted a lot of attention.owever, at present it is possible that mediating variables

e.g., depression, impaired glucose tolerance, hyposmia,DL cholesterol) associated with exercise and fitness could

xplain some or all of these observations.

. Summary and suggestions

Taken together, the studies reviewed here show that theres a high likelihood that social, cognitive, and physicalctivities interact in their ability to sustain cognitive perfor-ance during aging. Because of the relatively high preva-

ence of depression in aging and its well known impact onome cognitive processes (Butters et al., 2008) and theeduction of depressive symptomology by exercise (Bar-our and Blumenthal, 2005), depression should be assessedn all studies using scales such as the Geriatric Depressioncale (Yesavage et al., 1982; for a discussion of these

ssues, see Kørner et al., 2007).When exercise is evaluated, some age adjustment should

lso be included. This would require developing age-dapted standards that determine the average exercise levelt each age and describe its characteristics. Similarly, theeuropsychological tests that are used should be adjustedsing normative data (e.g., age, education), have validatedlternate forms and allow for practice or familiarity effectso be controlled (Geda et al., 2010). This would reduce biasesulting from the comparison of groups that may have theame mean on several characteristics despite having differ-nt distributions.

It would also be important to do basic research on theorrelation between real-life exercising and the participants’ersonal estimates to determine the amount of bias in self-eported exercise and the factors associated with inexactelf-reported estimates (Bowles et al., 2004). At this time, itppears unlikely we will gain any useful additional infor-ation from cross sectional studies using self-reported

uestionnaires to elucidate the beneficial impact of exercisen cognition during aging. The reader is referred to a pre-ious extensive discussion on this topic (Haskell et al.,992). Perhaps the use of electronic pedometers might pro-ide additional information by evaluating one type of phys-cal activity more objectively (Lautenschlager et al., 2008).owever, compliance for the wearing of the device shoulde evaluated. Finally, age-normed objective exercise testshould be devised because intensity of exercise will varyith age and people should be compared within their ageroup as they are, for example, in long-distance running.

Many cross sectional studies on aging relying on volun-eer participants include a selection bias with overrepresen-ation of people of higher socioeconomic status, higherducation, and superior cognition. For that reason, emphasishould be placed on obtaining a representative sample onhese variables so that the conclusions of the study can be
eneralized to the population. There is some indication that


time of day (circadian rhythms) influences cognitive perfor-mance, particularly in older adults, suggesting that testingall participants either at their peak or lowest performanceperiod would reduce variability in cognitive testing results(Hasher et al., 2000).

For intervention studies, postintervention questionnairesshould be used to detect participants in control conditionswho have increased their physical activity levels, possiblyas a result of volunteering in the study and being madeaware of the potential benefits of exercise (Ruscheweyh etal., 2009).

Finally, retrospective studies all suffer from a limitationin the attribution of causality: does exercise increase lon-gevity and protect cognitive abilities or do longevity, goodhealth, and intact cognitive processes foster more physicalactivity? Although lifelong intervention studies are imprac-tical, several short term intervention studies in which par-ticipants are randomly assigned to exercise conditions sug-gest that exercise does indeed lead to improved cognition.

On the one hand, it seems intuitively obvious that phys-ical exercise can only be good for us as we grow older.Indeed, we have considerable sympathy with this point ofview, and would be happy if this turned out to be true. Onthe other hand, we have endeavored to point out that theevidence for a causative effect of exercise on cognition isstill debatable, despite the many studies that have examinedthis hypothesis. Considering the still-unresolved question ofpossible interactions among physical exercise and socialand cognitive stimulation, perhaps the best advice is to gofor regular brisk walks with good friends while doing cross-word puzzles (and watching our step!).

Disclosure statement

The authors have no actual or potential conflicts of in-terest.

Acknowledgements

C.M. and P.D. are funded by grants from the NaturalSciences and Engineering Research Council of Canada.V.T. is supported by a Young Investigator Award from theAlzheimer Society of Canada and the Canadian Institutesfor Health Research. Delyana Miller was supported by afellowship from the Natural Sciences and EngineeringCouncil of Canada.

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