The Impact of Exercise on the Cognitive Functioning of Healthy Older

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14 M.E. Kelly et al./ Ageing Research Reviews 16 (2014) 12–31

exclude articles that did not meet inclusion criteria. Full texts

of remaining studies were then screened for eligibility by two

independent reviewers. Disagreements were resolved through

discussions with our expert authors (study selection flowchart,

Appendix B).

2.2. Selection criteria

We followed PRISMA (Preferred Reporting Items for System-

atic Reviews and Meta-Analyses) guidelines. Trials were included

thatinvestigated the effects of aerobic exercise, resistance training,

or Tai Chi interventions on the cognitive function of community

dwelling older adults (>50) with no known cognitive impairment.

The exercise categories were chosen based on a scope of the avail-

able literature that found that the majority of RCTs fell into one of

these three categories. Studies required at leastten participantsper

condition in order to be included in the review. We also excluded

studies if participants had been diagnosed with any cardiovascular

disease, or other significant medical, psychiatric, or neurological

problems (see excluded studies table, Appendix C). The risk of bias

in individual studies was assessed by two independent reviewers

(Appendix D)usingguidelinesoutlined in Section 8 of the Cochrane

Handbook.

The primary outcome of interest was cognitive function, dividedintothe domains of memory andexecutive function. Sub-categories

were created within each domain. Memory domain sub-categories

were: recognition, immediate recall, delayed recall, face-name

recall, and paired associates. Executive function domain sub-

categories were: working memory, verbal fluency, reasoning,

attention, and processing speed. Composite measures of cogni-

tive function were also included. Secondary outcomes of interest

were subjective cognitive performance and activities of daily living

(ADL).

2.3. Statistical analysis

Data extraction was conducted by two independent reviewers

and cross-checked by a member of the expert panel. Review Man-ager Version 5.2.6 software for Windows was used to conduct the

analysis. We calculated treatment effects based on pooled data

from individual trials that were deemed clinically homogenous.

The neuropsychological measures in included articles are listed in

Tables 1–6. For the purpose of meta-analysis, some cognitive tests

were not included as double representation of studies in their cog-

nitive category would compromise the validity of the outcomes.All

trials reported outcomes as continuous data. The summary statis-

tics required for each outcome were the number of participants in

the intervention and control groups at baseline and post-test, the

mean change from baseline and the standard deviation (SD) of the

mean change. If change from baseline scores were not provided,

they were calculated using baseline and post-test mean and SDs.

Change SDs were calculated assuming zero correlation betweenthe measures at baseline and follow-up. Although this method may

overestimate the SD of the change from baseline, it is a conserva-

tive approach which is preferable in a meta-analysis (Levy et al.,

2012).

As pooled trials used different rating scales or tests, the

summary measure of treatment effect was the standardised

mean difference (SMD – the absolute mean difference divided

by the standard deviation). Where trials used the same rat-

ing scale or test, the weighted mean difference was calculated.

Individual effect sizes were combined using the inverse vari-

ance random-effects method (Braun et al., 2009). This was

used to allow the incorporation of heterogeneity among stud-

ies. Statistical heterogeneity was assessed by the I 2 test, which

describes the percentage of variability among effect estimates

beyond that expected by chance. Overall estimates of the treat-

ment difference are presented in forest plots (Figs. 1–6). As

it was not possible to pool data from all included studies, a

summary of results from individual trials are outlined and pre-

sented in Tables 1–6.

3. Results

3.1. Included studies

Twenty-five randomised controlled trials wereeligiblefor inclu-

sion with 731 participants in aerobic exercise, 304 in resistance

training, and 106 in Tai Chi exercise experimental groups; and 332

in stretching/toning, 572 in ‘no exercise’ active controls, and 172

in ‘no intervention’ control groups. The most common interven-

tion was aerobic exercise. The stretching/toning control consisted

of stretching and toning or yoga exercises. The ‘no exercise’ active

control groups receivedeither health education, watchedmovies or

engaged in general conversation and socialising. The ‘no interven-

tion’ controls received either no contact, minimum social support,

or were placedon a waiting list. Study characteristics arepresented

in Tables 1–6.

3.2. Aerobic exercise versus stretching/toning

Available data from individual trials were pooled for meta-

analyses(Fig.1). Despite a trend towardsimprovedperformance for

experimental versus control groups on each of the included meas-

ures,there wereno significant differences betweenaerobicexercise

versus stretching/toning on immediate recall ( p= 0.62), delayed

recall ( p= 0.16), working memory ( p= 0.30), attention ( p= 0.15),

or processing speed ( p=0.28). Data were not available for the

remaining outcomes of interest including recognition, face-name

recall, paired associates, verbal fluency, reasoning, overall cognitive

performance, subjective cognitive measures, or ADLs. A summary

of results from individual studies (Table 1) showed significant

improvements for aerobic exercise compared to stretching/toning

groups in three of 17 memory outcome measures reported in fourtrials (Barnes et al., 2013; Erickson et al., 2011; Kramer, Hahn,

McAuley, et al., 2002; Oken et al., 2006), with significant pre- to

post-interventionimprovements for theinterventiongroup butnot

for the control group on one additional memory outcome measure

(Krameret al., 2002). Significant improvements for aerobic exercise

versus stretching were reported in two out of 40 separate meas-

ures of executive function in five trials (Albinet et al., 2010; Barnes

et al., 2013; Kramer et al., 2002; Oken et al., 2006; Smiley-Oyen

et al., 2008), with significant pre- to post-intervention improve-

ments reported for the experimental butnot for the control groups

on one additional measure of executive function (Kramer et al.,

2002). None of the included studies measured maintenance effects.

3.3. Aerobic exercise versus no exercise active control

Results from the meta-analysis (Fig. 2) revealed no signif-

icant differences between aerobic exercise and ‘no exercise’

active control groups on the measures of recognition ( p= 0.51),

immediate recall ( p=1.00), delayed recall ( p= 0.67), verbal flu-

ency ( p=0.58), reasoning ( p=0.28), working memory ( p= 0.75),

attention ( p= 0.56), processing speed ( p= 0.76), or cognitive func-

tion ( p=0.26). Data were not available for face-name recall,

paired associates, subjective cognitive function or ADLs. Across

individual trials (Table 2), significant improvements for aerobic

exercise versus active controls were reported in one out of 10

memory outcome measures (Lautenschlager et al., 2008; Legault

et al., 2011; Maki et al., 2012; Mortimer et al., 2012) and two

out of 38 measures of executive function (Barella et al., 2010;







Table 2 (Continued)

Ref. author (year) Intervention Methods Participants (at PT) Outcomes of in

Muscari (2010) Exercise in community

gym versus educational

materials control

RCT

EG: 3×1h per week for 12 months, 70%

of maxHRR

FU: PT

EG: 60

CG: 60Cognitive funct

Age: 65–74

M age EG: 68.8 ( 2.5)

M age CG: 69.6 ( 2.8)

Netz (2007) 1. Moderate exercise

2. Moderately-intense

exercise (EG)

3. Movie-watching

control group (CG)

RCT

1.60%of HRR

2. (EG): single 44min training session;

70% of HRR

FU: PT

EG1: 20

EG2: 20

CG: 18

Working memo

Cognitive

flexibility/atten

Response inhib

(AUT persev. w

betweenc , rule

Age: 50–64

M age: 6 7. 8 (7.4)

Williamson (2009) Moderate intensityphysical activity versus

health education control

Single-blind RCTThree phases:

1. 3× centre-based (40–60min/week) for

2 months

2. 2× centre based

sessions+ 3×home-based sessions/week

for 4 months

3. Home based interventions+ optional 1

or 2 centrebased interventions for6

months

FU: PT

EG: 45CG: 48

Working memoProc. speed (DS

Attentionc

Cognitive funct

Age: 70–89

M age EG: 76.8 (4.4)

M age CG: 78.1 (4.1)

EG= experimental group; CG= control group; FU= follow up; PT= post training;M age =meanage (SD); DSST = digit symbol substitution test; UFOV= Useful Field of View; HR

Card Sort Test; ADAS-Cog= Alzheimer’s Disease Assessment Scale; DSCT =Digit Symbol Coding Test; CDRS= Clinical Dementia Rating Scale; CCRT= Cambridge Contextual R

AUT = Alternative Uses Test; HRR= heart rate reserve.a Significantly greater improvement for training compared to control.b Significant training effects forexperimental group from BL to PT; no significant effectfor controls.c No significant intervention difference between experimental and control groups.







Table 5

Characteristics of studies – resistance training versus no exercise active control.

Ref. author (year) Intervention Methods Participants (at PT) Outcomes of interest

Brown (2009) Three conditions:

1. Resistance and

balance training

exercises (EG)

2. Flexibility relaxation

programme (AC)

3. No-exercise control

(CG)

RCT

EG and AC: 2×1 h

(5–15min warm-up;

40min training; 10 min

cool-down)/week for 6

months

FU: PT

EG: 66

AC: 26

CG: 34

Paired associates

(verbalc, visualc)

Reasoningb

Attention (Trails-Bc ,

Stroopc)

Verbal fluencyc

Proc speedc

Working memory

(DSFc

DSBc)

Fluid intelligence

(arithmeticb, PCb)

Age: 62–95

M age EG: 79.5 (5.9)

M age AC: 81.5(6.9)

M age CG: 78.1 (6.4)

Kimura (2010) Strength training

programme versus

health education

classes

Single-blind RCT

EG: 2×1.5h/week for

12 weeks; 60% of 1RM

FU: PT

EG: 65

CG: 54Executive functionc

Age: ≥65

M age EG: 73.6 (4.7 )

M age

CG: 75.2 (6.3)

Liu-Ambrose (2008) Home-based resistance

and balance training

(Otago Exercsie

Program; OEP) versus

control

Single-blind RCT

EG: 3×30 min/week,

0.9kg increments as

required, and walk

2/weekfor 6 months

FU: PT, 6 months

EG: 28

CG: 24

Attention (Stroopa ,

Trails Bc)

Working memorycAge: ≥70

M age EG: 81.4 (6.2)

M age CG: 83.1 (6.3)

Venturelli ( 2010) Upper-body p hysical

training versus control

RCT

EG: 3×45minfor 12

weeks;50% of

1RM-adjusted as

needed, 53–62% of max

HRR

FU: PT

EG: 12

CG: 11

Cognitive functiona

Activities of daily

livingaAge: ≥65

M age EG: 83.3 (6.7 )

M age CG: 84.1 (5.8)

EG= experimental group; CG= control group; FU= follow up; PT= post training;M age =meanage (SD); DSST = digit symbol substitution test; UFOV= Useful Field of View; HR

Card Sort Test; ADAS-Cog= Alzheimer’s Disease Assessment Scale; DSCT =Digit Symbol Coding Test; CDRS= Clinical Dementia Rating Scale; CCRT= Cambridge Contextual R

AUT = Alternative Uses Test; RM= repetition maximum; HRR= heart rate reserve.

a Significantly greater improvement for training compared to control.b Significant training effects forexperimental group from BL to PT; no significant effectfor controls.c No significant intervention difference between experimental and control groups.



Table 6

Characteristics of studies – Tai Chi versusno exercise.

Ref. author (year) Intervention Methods Participants (at PT) Outcomes of interes

Mortimer (2012) Four conditions:

1. Tai Chi (EG)2. Walking

3. Social interaction

4. No intervention(CG)

Comparison: Tai Chi

versus no intervention

1. (EG): 3×50min per

week for 40 weeks2. 3×50minper week

for 40 weeks

FU: PT

EG: 30

CG: 30

Recognitionb

Immediate recallb

Delayed recalla

Working memory

(DSFb, DSBb, R ey

Osterreichb, clock

drawingb )

Attention (Stroopb,

Trails Aa , Trails Ba)

Verbal fluency

(categoriesa , Boston

namingb)

Reasoningb

Cognitive functiona

Age: 60–79

M age EG: 67.3 (5.3)

M age CG: 68.2(6.5)

Nguyen andKruse, 2012 Tai Chi group versus no

intervention control

EG: 2×1h per week

for 6 months

FU: PT

EG: 39

CG: 34

Proc speed (Trails A

Attention (Trails Ba

Age: 60–79

M age EG: 69.2 (5.3)

M age CG: 68.7(4.9)

Taylor-Piliae (2010) Two phase study 1.(EG): 1×45min per

week for 12 weeks

2. 1× (10min

warm-up/25min

aerobic/20min

resistance and

flexibility)+ 3×home

based exercises

(≥30min

walking+25min

resistance and

flexibility)

FU: measured at 6

months at end of 1st

phase and at 12months at end of 2nd

phase

First phase

EG1: 37

EG2: 39

CG: 56

Verbal fluencyb

Working memory

(DSFb, DSBa)

First phase: three

conditions

1. Tai Chi (EG)

2. Western exercise

3. Healthy ageing

classes (CG)

Second phase

EG1: 26

EG2: 34

Secondphase: two

conditions

1. Tai Chi (EG)

2. Western exercise

Age: 60–84

M age EG1:70.6(5.9)

M age EG2:68.5(5.0)

M age CG: 68.2(6.2)

EG= experimental group; CG= control group; FU= follow up; PT= post training;M age =mean age (SD); MIA =Meta-Memory in Adulthood; CFQ= Cognitive Failures Questionn

function.a Significantly greater improvement for training compared to control.b No significant intervention effects for experimental compared to control.




Fig. 1. Aerobic exercise versus stretching/toning.

Lautenschlager et al., 2008; Legault et al., 2011; Maki et al., 2012;

Mortimer et al., 2012; Netz et al., 2007; Williamson et al., 2009).

Significant within-group differences were reported on two fur-

ther executive measures (Barella et al., 2010; Williamson et al.,

2009), and in three out of six measures of cognitive function

(Lautenschlager et al., 2008; Mortimer et al., 2012; Muscari et al.,

2010; Williamson et al., 2009). Two trials conducted follow-up

assessments and reported maintenance of effects at 12 months

post-intervention (Barella et al., 2010; Lautenschlager et al.,

2008).

3.4. Aerobic exercise versus no intervention

Meta-analyses on available data revealed no significant dif-

ferences between aerobic exercise and ‘no intervention’ control

groups on measures of immediate recall ( p= 0.30), delayed recall

( p=0.13), verbal fluency ( p= 0.14), reasoning ( p= 0.48), working

memory (0.70), and processing speed ( p= 0.17) (Fig. 3). Differences

between the groups on measures of attention approached signifi-

cance ( p= 0.09). Data were not available for the remaining primary

and secondary outcomes measures. In individual trials, aerobic



M.E. Kelly et al./ Ageing Research Reviews 16 (2014) 12–31 23

exercise groups significantly outperformed controls on three out

of eight memory measures (Klusmann et al., 2010; Mortimer et al.,

2012; Oken et al., 2006), with no differences on one measure of

cognitive function (Mortimer et al., 2012). For executive meas-

ures there were significant between group differences in five out

of 41 executive measures, and significant pre-post intervention

improvements for exercise but not control groups on a further

10 measures of executive function (Klusmann et al., 2010; Maillot

et al., 2012; Marmeleira et al., 2009; Mortimer et al., 2012; Oken

et al., 2006). None of the above studies measured maintenance of

intervention effects.

3.5. Resistance versus stretching/toning

Three trials provided data comparing resistance training to

a stretching/toning control (Brown et al., 2009; Cassilhas et al.,

2007; Liu-Ambrose et al., 2010). Meta-analyses revealed significant

improvements in performance for experimental versus control on

Fig. 2. Aerobic exercise versus ‘no exercise’ active control.




Fig. 2. (Continued).

measures of reasoning ( p<0.005) but not on measures of work-

ing memory ( p=0.47) or attention (0.37) (Fig. 4). Data were not

available for the remainingoutcomes of interest. Results from indi-

vidual studies (Table 4) revealed that resistance groups performed

significantly better than stretching/toning controls on one out of

three measures of memory and on four out of 18 measures of

executive function. One trial reported pre- to post-intervention

improvement for the resistance group but not stretching controls

on onemeasure of reasoning(Brown et al., 2009). None of the three

studies in this category reported follow-up data.

3.6. Resistance versus no exercise active control

It was only possible to pool data for two outcome measures

comparing resistance training and ‘no exercise’ controls, with

comparisons revealing no significant differences on measures of

working memory ( p=0.31) or attention ( p=0.62) (Fig. 5). Com-

parisons of results across three individual trials (Table 5) revealed

no significant differences between resistance training and control

groups on two measures of memory and nine out of eleven meas-

ures of executive function (Brown et al., 2009; Kimura et al., 2010;

Liu-Ambrose et al.,2008). Venturelli et al. (2010) reported thattheir

resistance group performed significantly better than controls on

measures of cognitive function and activities of daily living. None

of the four studies included follow-up assessments.

3.7. Tai Chi versus no exercise active control

Meta-analysis on pooled data from two individual trials

revealed significant differences between Tai Chi experimental




groups and ‘no exercise’ control groups on measures of attention

( p< 0.001) and processing speed ( p< 0.00001), with differences for

working memory approaching significance ( p= 0.07). There were

no significant differences between the groups on measures of ver-

bal fluency ( p=0.27) (Fig. 6). Across individual trials (Table 6),

participants in Tai Chi groups outperformed ‘no exercise’ controls

on one out of three measures of memory, five out of 15 measures

of executive function, and on one measure of cognitive function

(Mortimer et al., 2012; Nguyen and Kruse,2012; Taylor-Piliae et al.,

2010). One study conducted follow-up assessments and reported

maintenance of improvements in cognitive functioning for the Tai

Chi group after 12 months (Taylor-Piliae et al., 2010)

4. Discussion

We examined the effects of aerobic exercise, resistance training,

and Tai Chi on the cognitive performance of older adults with-

out known cognitive impairment. Meta-analysis results revealed

Fig. 3. Aerobic exercise versus no intervention.




Fig. 3. (Continued).

that resistance training significantly improved performance on

measures of reasoning compared to a stretching/toning control.

Compared to a no exercise control, Tai Chi significantly improved

performance on measures of attention and processing speed, and

the effect for working memory approached significance. There

were no significant differences between exercise and controls

on any of the remaining 26 comparisons. Across individual tri-

als, 15 of the 25 studies reported some significant improvements

for exercise versus controls on measures of executive func-

tion, memory, and on composite measures of cognitive function.

Despite this, the majority of comparisons yielded no significant

differences.

Fig. 4. Resistance training versus stretching/toning.




Fig. 5. Resistance training versus ‘no exercise’ active control.

Fig. 6. Tai Chi versus ‘noexercise’ active control.




4.1. Exercise-types

4.1.1. Aerobic exercise

Our lack of consistent significant findings for aerobic exercise

are surprising considering conclusions of Colcombe and Kramer

(2003) and Smith et al. (2010) who reported that aerobic exercise

was associated with improvements in neurocognitive functioning,

particularly executive functions (see also Guiney and Machado,

2013). We found some supportive evidence for executive ben-

efits as differences for aerobic exercise versus ‘no intervention’

approached significance on measures of attention; and across indi-

vidual trials, aerobic exercise more reliably improved performance

on executive function tasks. Despite this our results are consis-

tent with four reviews of aerobic RCTs that concluded that there

is a lack of consistent evidence to show that aerobic interventions

(Angevaren et al., 2008; Clifford et al., 2009; Snowden et al., 2011)

or aerobic fitness (Angevaren et al., 2008; Etnier et al., 2006) result

in improved performance on cognitive tasks for older adults with-

out known cognitive impairment. Factors that may contribute to a

lack of significant findings are discussed in more detail below.

4.1.2. Resistance training

Although some reviews report evidence to suggest that resis-

tance training has cognitive benefits among seniors (Liu-Ambroseand Donaldson, 2009), the results of this review, andothers (Chang

et al., 2012; Snowden et al., 2011; van Uffelen et al., 2008) fail to

show any consistent evidence for the benefit of resistance training

on the cognitive function of older adults. We did find significant

improvements on measures of reasoning for resistance training

compared to a stretching and toning control, but no differences for

working memory or attention. Chang et al. (2012) suggested that

similar to aerobic exercise, resistance training may have differen-

tial effects on cognitive function, perhaps affectingperformance on

specific executivetasks. Ourfindingssupport this view, andmay go

some way towards explaining inconsistent results because many

resistance studies fail to include measures of reasoning, or other

executive measures. Better comparability in measures of execu-

tive function across studies that examine the effects of resistancetraining on cognition would bring greater clarity.

4.1.3. TaiChi

Our results on the effect of Tai Chi on attention, processing

speed, and working memory are consistent with those of Chang

etal. (2010)who reported thatTai Chi might havetask-specificben-

efits for executive function tasks. A recent meta-analysis similarly

reported significant benefits of Tai Chi for older adults’ executive

functioning (Wayne et al., 2014). Interestingly, both Colcombe and

Kramer (2003) and Smith et al. (2010) reported that combining

aerobic exercise and resistance training was more effective than

aerobic exercise alone at improving performance onexecutive tasks

of attention and working memory. As Tai Chi combines aspects of

aerobic, resistance, and flexibility training, this provides furthersupport to the findings of Colcombe and Smith. More research is

required to determine the possible cognitive benefits of combined

exercise programmes such as Tai Chi however as not all studies

show consistent cognitive benefits (Hall et al., 2009). Our results

were based on only two studies and lacked comparison with an

active control.

4.2. Discrepancies between RCT evidence and other exercise

literature

Inconsistentresults from RCTs that examine the benefitof exer-

cise on the cognitive function of older adults stands in sharp

contrast to the consistent evidence from epidemiological, cross-

sectional, and neuroimagingresearch. Thereare however a number

of possible explanations for the apparent contradictory findings,

which also contribute to explanations for inconsistent results

across exercise trials.

4.2.1. Baseline physical performance

The first factor to consider is baseline levels of physical activ-

ity. Some RCTs recruit participants who are already engaging in

regular physical exercise. For example Oken et al. (2006) allowed

participants to already be engaged in 30min of aerobic exercise

per day at entry into their study, while Barella et al. (2010) permit-

ted participants who regularly exercised to maintain their normal

exercise schedules. In contrast, epidemiological and cross-sectional

studies derive evidence of the benefits of physical activity on cog-

nitive function through comparisons of different baseline activity

levels. These studies show that individuals engaged in higher lev-

els of exercise at baseline have better cognitive function, or are at a

reduced risk of experiencing cognitive decline relative to counter-

parts who led sedentary lives, were less fit, or inactive at baseline

(Barneset al., 2008; Brownet al., 2012;Hamer and Chida,2009; Sofi

et al., 2011). Considering this, it is unsurprising that intervention

trials investigating theeffect of exercise on cognitionin participants

who are already physically active may not observe similar results,

as the variance in improvement may be too small to predict cog-

nitive benefit. Indeed RCTs that examine the effects of exercise onless physically active or frail older adults tend to show more con-

sistent positive results (Guiney and Machado, 2013; Langlois et al.,

2013). Future trials would benefit from control of baseline levels of

physical activity.

4.2.2. Length of intervention and follow-up

A lack of long-term monitoring in intervention trials may be

further contributing to discrepancies in the exercise literature. If

exercise is to be beneficialin ameliorating theeffects of age-related

cognitive decline, then the rate of change over longer periods of

time will be more relevant than any short-term, post-intervention

gain in cognitive performance (Angevaren et al., 2008; Salthouse,

2006). Observational data from epidemiological studies that exam-

ine cohorts over long periods indicate that physical activity maytake years to impact brain health (Beason-Held et al., 2007; Rovio

et al., 2005). RCTs are typicallymuch shorter in duration andthere-

fore may not be long enough to capture intervention effects. Also

by virtue of recruitment of healthy older adults, participants may

already be functioning cognitively at ceiling level, thus improve-

ments in cognitive performance would be difficult to ascertain over

short RCT intervention and follow-up periods. In this review, trials

most commonly ranged from 12 weeks to 6 months in duration,

and only two trials provided follow-up data. Interestingly, longer

interventions such as one year (Liu-Ambrose et al., 2010; Muscari

et al., 2010); and trials that included assessments up to 18 months

post-intervention (Lautenschlager et al., 2008; Taylor-Piliae et al.,

2010) reported more consistent positive effects (see also Clifford

et al., 2009; Colcombe andKramer,2003; Krameret al., 1999; Smithet al., 2010). Importantly these studies reported that while exercise

either improved or maintained cognitive performance; cognitive

performance in control groups declined over time (Liu-Ambrose

et al., 2008, 2010; Muscari et al., 2010). Future intervention studies

would benefit from longer intervention and follow-up periods to

assess whether cognitive differences between trained participants

and controls increase as a function of age.

4.2.3. Efficiency of the intervention and adherence

When comparing groups receiving exercise interventions with

controls, the eventual intervention effect will depend on both the

efficiency of the intervention in the intervention group and adher-

ence to the intervention; and the behaviour of participants in

the control group. In relation to efficiency, insufficiently designed




exercise programmes may explain a lack of significant findings in

many exercise RCTs (e.g. Barnes et al., 2013; Brown et al., 2009;

Kimura et al., 2010; Legault et al., 2011; Oken et al., 2006), and

other divergent results. Although the optimum exercise ‘dose’ to

benefit cognition has yet to be established (Chang et al., 2012;

Colcombe and Kramer, 2003), RCT interventions commonly fail to

meet current public health exercise recommendations for older

adults of 150 min of moderate intensity aerobic activity per week

(Haskell et al., 2007); and two sessions per week of moderate

intensity strength training working multiple muscle groups, with

one or more sets of 10–15 repetitions, and a rest interval of

2–3min (Medicine,2009). Incontrast, in epidemiological andcross-

sectional studies, participants in ‘high activity’ groups reported

engaging in 4–7h of exercise per week (Schuit et al., 2001; Sumic

etal., 2007) atmoderateto high intensitylevels (Brownet al., 2012).

Research indicates that exercise intensity might be more impor-

tant than duration in benefitting cognitive function (Angevaren

et al., 2007; van Gelder et al., 2004). Despite this, trials more often

focus on duration rather than intensity in intervention designs (see

Tables 1–6). Designing interventions that meet all minimum rec-

ommendations for exercise for older adults would allow for more

rigorouscomparisons of results across trials, andmight reveal more

consistent positive results.

There is a lack of standardised reporting of the characteristicsof exercise interventions (i.e. frequency, intensity, time and type

(F.I.T.T.)) in the RCT exercise research literature. This makes it dif-

ficult to determine the efficiency of interventions, or indeed what

constitutes an effective exercise intervention. Guidelines on repor-

ting of F.I.T.T. components for RCT research would improve study

comparability.In addition,data areoften not available on theeffect

of the training intervention on pre-post fitness or physical meas-

ures. In our review, 16 out of 25 studies reported physical or fitness

outcomes but there was little consistency in measures used and

outcomes reported.Making these data available in exercise RCTs in

a standardised way could facilitate the interpretation of cognitive

outcomes in RCTs more directly in the context of epidemiological

research.

Variability in adherence to prescribed interventions mightalso be contributing to discrepant results. Even with adequately

designed exercise regimes, low adherence can result in low activ-

ity levels for exercise groups. For example, Brown et al. (2009)

reported that their intervention group attended between 3 and 51

of 52 classes, with68% of participants attending lessthan 25 classes.

Similarly, Oken et al. (2006) reported that of all participants com-

pleting their aerobic exercise intervention, the attendance rate at

the weekly class was 69%, and participants exercised an average

of only 54% of all required days. Results from exercise interven-

tions that do not actually engage participants in regular physical

activity will logically differ from epidemiological data where par-

ticipants report actual active engagement in physical activity over

long periods. Future RCTs should attempt to control for or exclude

participants who do not comply with the target intervention (e.g.Smiley-Oyen et al., 2008).

Confounds associated with relevant behaviours of participants

in control groups might helpto explain thedivergence between RCT

evidence and other exercise literature. As previously mentioned,

some exercise trials recruit participants that are already engaging

in, and continue to engage in regular physical activity during the

course of the RCT. In some instances when these participants are

randomised into control groups, their behaviour patterns might

be similar to those of intervention participants. These potential

confounds compromise the validity of comparisons with epidemi-

ological data, because both groups would ultimately be considered

as ‘high activity’ groups in a prospective study. Control groups in

RCTs need to be categorised as ‘low activity’groups relative to ‘high

activity’ intervention groups.

4.2.4. Physical fitness and cognitive health

Longitudinal (Sturman et al., 2005) and prospective studies

(Weuve et al., 2004) show an association between physical fit-

ness and improved cognitive performance (Kramer et al., 2002).

Based on the assumption that improvements in physical fitness

mediate benefits in cognitive function, a prediction that exercise

resulting in enhanced fitness would improve cognitive outcomes

is not unreasonable. Systematic reviews of RCTs however fail

to show consistent evidence for a relationship between physi-

cal fitness and cognitive performance (Angevaren et al., 2008;

Etnier et al., 2006). A possible explanation for this is that brief

programmes of exercise may not be of sufficient duration or

intensity to impact fitness to a level observed in longitudinal

studies. Longitudinal data indicate that high levels of fitness are

achieved after years rather than months of training (Kramer

et al., 2002). Short-term improvements in cognitive function in

RCTs may therefore be driven by mechanisms other than phys-

ical fitness (Angevaren et al., 2008; Etnier et al., 2006; Kramer

et al., 2002); which may help to explain why similar results are

not seen in epidemiological data. Further research is required to

determine what factors, other than fitness, might mediate the

relationship between physical activityand cognitive function. Indi-

viduals with the APOE4 gene have been identified as a possible

sub-group whose cognitive performance is differentially affectedby aerobic fitness (Etnier et al., 2007; Podewils et al., 2005),

but the identification of additional subgroups might be benefi-

cial.

4.3. Inconsistent results across RCTs

Additional factors contributing to inconsistent RCT results

include differences in participant inclusion criteria, study design,

exercise programmes, and cognitive outcome measures. Variations

in inclusion criteria are common where some trials recruit phys-

ically active participants (Oken et al., 2006) while others recruit

those who are frail (Langlois et al., 2013), or sedentary (Barnes

et al., 2013); some trials recruit only older adults (Legault et al.,

2011) while others include data from younger, middle-aged andolder adults (Hoffman et al., 2008; Munguia-Izquierdo and Legaz-

Arrese, 2008); andsome trials recruit participantswith no cognitive

impairment (Klusmann et al., 2010) while others include data

from individuals with cognitive complaints (Lautenschlager et al.,

2008). Standards of reporting, attempts to reduce bias, and over-

all study quality also differ greatly across studies (Snowden et al.,

2011). Exercise programmes are often incomparable, even within

the same exercise-type, with large variations in frequency, dura-

tion, and intensity of exercise programmes in RCTs. In terms of

recording outcomes, a lack of consensus around appropriate or

necessary measures of cognitive function remains an issue despite

repeated recommendations for standardisation (Angevaren et al.,

2008; Chang et al., 2012; Smith et al., 2010).

4.4. Limitations of the review

A meta-analysis of data from such a broad agerange (50+)might

be masking intervention effects that would be evident in older

adults had we used a narrower age band (Barella et al., 2010). In

addition, more robust effects of exercise on cognitive processes

have been reported for older adults (65+) compared to younger-

older adults (aged 50–64) (Kramer et al., 2002). In this review,

the inclusion of participants aged 50+ allowed for the examina-

tion of a greater number of relevant trials (e.g. Erickson et al., 2011;

Krameret al., 2002; Marmeleira et al., 2009), andalso increasedthe

likelihood that a meta-analysis could be conducted. We undertook

further analysis to determine the results when limiting analyses to

studies of persons aged>65, andaged >65–75.Where meta-analysis



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Documents

The Impact of Exercise on the Cognitive Functioning of Healthy Older