depression, cognitive reserve and memory performance in older adults

RESEARCH ARTICLE

Depression, cognitive reserve and memory performance in
older adults
Mike Murphy and Eleanor O’Leary

Department of Applied Psychology, University College Cork, IrelandCorrespondence to: Dr M. Murphy, E-mail: [email protected]

Copyr

Objectives: The purpose of this research study was to examine the relationship between education andleisure, as markers of cognitive reserve, depressive symptoms and memory performance in a sample ofcognitively normal Irish older adults.

Methods:A cross-sectional survey style design was employed to gather data. A sample of 121 older adultsin the Cork area was recruited through publicly advertising for volunteers. Only those volunteers whoobtained a score of greater than 23 on the MMSE, and were not taking antidepressant or anxiolyticmedications, were included. Data from 99 participants were included in the analysis.

Results: Controlling for age and gender, depressive symptoms were found to be associated with poorerimmediate recall performance, while greater than 12 years of education was positively associated withdelayed recall and savings. Leisure did not emerge as being associated with any of the dimensions ofmemory assessed.

Conclusions: Depressive symptoms emerged as associated with immediate recall, even though few of theparticipants met the cut-off for caseness. This may indicate a need for intervention in cases of subclinicaldepression with associated memory complaints. The association between education level and bothdelayed recall and savings provides support for the cognitive reserve hypothesis, and may suggest usefulnon-pharmacological approaches to memory deficits in later life. Copyright# 2009 John Wiley & Sons, Ltd.

Key words: memory; education; leisure; depressive symptoms; agedHistory: Received 6 May 2009; Accepted 28 July 2009; Published online 5 October 2009 in Wiley InterScience(www.interscience.wiley.com).DOI: 10.1002/gps.2404

Introduction

We are living in a rapidly ageing world. The UnitedNations Department of Economic and Social Affairs(2004) observed that the proportion of the world’spopulation aged over 65 was 5.25% in 1950, rising to6.9% in 2000. However they went on to predict thatthis age group would expand to contribute 15.9% ofthe population in 2050, rising to 24.4% in 2100. Inabsolute terms, they projected a 238.4% increase in thenumber of older adults worldwide between 2000 and2050. An inevitable consequence of this dramaticdemographic shift is that changes asociated with ageingwill become more prevalent. One such age-relatedchange is in the area of memory performance.

A good deal of research has indicated the existence ofa link between increasing age and poorer memory

ight # 2009 John Wiley & Sons, Ltd.

performance (Ritchie et al., 1993; Stewart et al., 2001;Le Carret et al., 2003). The association between ageingand deteriorating performance on cognitive tasks hasseveral possible causes. Park (2000) outlined fourpossible links—a reduction in general processingspeed, a diminution of cognitive energy to apply totasks at hand, a drop in the ability to inhibit irrelevantinformation and so focus only on relevant stimuli, andfinally an indirect effect of diminished sensoryfunction. An alternative viewpoint is that proferredby Kleemeier (1962), which has earned the title of the‘terminal drop hypothesis’. This view suggests thatcognitive performance remains relatively stable up to afew years before death, and undergoes a moreprecipitate decline in the final years of life.

Gender has also been found to be associated withmemory performance, with the bulk of research

Int J Geriatr Psychiatry 2010; 25: 665–671.

666 M. Murphy and E. O’Leary

suggesting that females outperform males in verbalmemory tasks (Welsh et al., 1994; Knight et al., 2006).Research on brain structure helps to explain thisphenomenon. Neuroscientific evidence derived fromMRI scanning shows that females have a higherproportion of grey matter in the left (languagedominant) hemisphere than do males; and that malesshow a higher level of atrophy in the left hemisphere, adifference which becomes more pronounced with age(Gur et al., 1991; Gur et al., 1999). It may also be thecase that hemispheric lateralisation is not so great infemales, allowing for a higher level of functioning inthe presence of left hemispheric atrophy.

Age and gender, while important demographicfactors, are not the only dimensions which can impacton memory performance. Three which are of particularinterest, in that they provide the potential to interveneand ameliorate age-related decline, are depression,education level and leisure activity.

Depression has regularly been found to be associatedwith poorer memory performance. Christensen et al.(1997), in a meta-analysis of 154 studies, reportedsignificant effect sizes for the relationship betweendiagnosis of depression and both short-term anddelayed memory. Biringer et al. (2005), in a sample of1930 cognitively normal Norwegian older adults,reported that both number of depressive symptomsand depressive caseness were associated with poorerperformance in tests of visual memory.

It is the case, however, that the approach tooperationalising depression influences the resultswhich emerge from research. Whilst depressive case-ness has often been found to be related to memoryperformance, the same is not true of number ofdepressive symptoms. For example Clark et al. (2004)assessed depressive symptoms, immediate recall anddelayed recall in a sample of 257 Australian femalesaged 56–67 years, and found no relationship betweendepression score and performance. Simensky andAbeles (2002) failed to identify an association betweendepressive symptoms and immediate recall in a sampleof 88 cognitively normal adults aged 60 to 85 years.

Explanations of the impact of depression oncognitive performance focus largely on effort andattention. Baldwin (2002) suggested that greaterdepression-related decrements in performance wouldbe found in more effortful tasks. Hartlage et al. (1993)proposed that attention to the task at hand would bereduced through decreased motivation, distractionarising from internally generated depressive thoughts,or focus on mood-congruent items rather than the taskitself. Whilst these explanations are consistent with theDSM-IV depressive symptom of decreased ability to

Copyright # 2009 John Wiley & Sons, Ltd.

concentrate, it may also be that depression-related psy-chomotor retardation is a factor (Henry and Crawford,2005).

Education has also been linked to cognitive perfor-mance, including memory, in older age. For example,in a sample of 113 cognitively normal participants aged55–85 years and controlling for age and gender,Ylikoski et al. (1998) reported that those with greaterthan a grade school level of education ouperformedthose with lower education in tests of both immediateand delayed recall. In a similar vein, Le Carret et al.(2003) assessed cognitive function in 1022 Frenchadults aged 65 and over, and controlling for age,leisure, depressive symptoms and gender, found thatparticipants with greater than 5 years of educationshowed superior immediate and delayed recallperformance. There is conflicting evidence however.Wiederholt et al. (1993) assessed memory performancein 1692 community dwelling participant aged 55–94years, and found that delayed recall scores were higherin those who had attended third-level education, butreported no association between education level andimmediate recall. Welsh et al. (1994) examinedcognitive function in 413 cognitively normal partici-pants aged 50–89 years, and found that those withgreater than 12 years of education performed better onone of three tests of immediate recall, but that nodifference emerged in two immediate recall trials or ina delayed recall task.

Thus, the research evidence seems to suggest anassociation between memory and education, but onewhich is far from clear. The concept of cognitivereserve is a possible explanation for this relationship.The cognitive reserve hypothesis proposes that factorssuch as education level may contribute to superiorcognitive performance in later years through providinga buffer against the effects of age-related neurodegen-eration (Stern, 2003). Richards and Deary (2005)observed that there are two possible mechanismswhereby cognitive reserve can serve such a function:hardware, with greater education leading to changes inbrain structure through neurogenesis and/or increaseddensity of dendritic connections; and software, involvingthe development of more efficient neural pathways.

The possible impact of leisure on cognitive perfor-mance can also be partly explained with reference tothe cognitive reserve hypothesis. Cognitively-basedleisure activities can be expected to have a similar effectto education level. Physical leisure activity, if it has aneffect, is likely to exert its influence through physicalfitness (Colcombe and Kramer, 2003). Research onleisure in this context has been less comprehensive thanthat relating to education and depression; nonetheless


Memory in older adults 667

there is evidence which indicates a possible associationwith memory. Christensen et al. (1996), in a sample of858 older participants resident in Canberra, examinedthe relationships between physical activity and a varietyof cognitive dimensions, including memory (acomposite measure of visual and verbal recall, andrecognition). Regression analyses found that leisurewas a significant predictor when health, education,gender and activities of daily living were controlled.Weuve et al. (2004) gathered data from 18 776 retiredAmerican female nurses, aged 70–81 years. Convertingself-reported activity in the previous year to metabolicequivalents, these authors found that physical activitywas associated with both immediate and delayed recall,controlling for age, education, smoking, drinking andmental health. Singh-Manoux et al. (2003) conducteda study which included 10 308 civil servants based inLondon, all aged between 35 and 55 years. Taking totalcognitive and physical leisure together, they foundleisure to be significantly associated with immediaterecall. Further analysis found that cognitive activities,and those with a greater social component, wereparticularly strongly related to cognitive performance.There is also conflicting evidence—Wilson et al.(2003) examined the association between variousdimensions of cognitive performance and lifetimecognitive activity in a sample of 141 Chicagoan olderadults, and found an association with semanticmemory, but not episodic memory.

In summary, there is evidence to indicate that eachof age, gender, education level, depressive symptomsand leisure activity impact performance in memorytasks. It is hypothesised that, controlling for age andgender, greater education level and leisure activity andlower depressive symptoms will emerge as predictors ofsuperior recall performance in this sample. It is hopedthat the pattern of results emerging will provideinformation as to the nature of the relationships.

Method

Participants

The sample employed consisted of 99 community-dwelling volunteers (65 female, 34 male) living in thearea of Cork city, Ireland. All participants were agedbetween 60 and 83 years (mean age 66.89, sd¼ 5.32,median 66), and were deemed cognitively normal onthe basis of Mini-Mental State Examination (MMSE)scores, employing a cut-off of 23. Participants inreceipt of antidepressant or anxiolytic medication, or


who reported suffering an infection at the time ofinterview, were excluded.

Participants were recruited through advertising inlocal media, local churches and notices in libraries,post offices and medical centres.

Design

A cross-sectional survey was employed, involving a singleface-to-face meeting between the first author and eachof the participants. Although this form of design cannot reveal causal relationships (Neuman, 2007), it wasdeemed appropriate to address the research question.

Materials

The materials employed included a demographicquestionnaire which garnered information on age,gender, education level, leisure activity and medicalhistory; the MMSE; elements of the Consortium toEstablish a Registry for Alzheimer’s Disease (CERAD)Neuropsychological Battery (Morris et al., 1989), andthe Geriatric Depression Scale (GDS—Yesavage et al., 1983).

The MMSE was employed to assess general cognitivefunction. Items measure orientation to time and place,registration, attention, recall, naming, repetition,comprehension, reading, writing and drawing. Possiblescores range from a low of 0 to a high of 30, higherscores indicating superior cognitive function. Tom-baugh and McIntyre (1992), reviewing the researchliterature, reported that using the standard cut-offpoint of 23 for cognitive impairment led to a sensitivityof 87% and a positive predictive value of 79%.

Participants reported the number of years of formaleducation they had received, and this was dichot-omised at 12 years. Leisure was measured according tothe number of hours participants spent employed inleisure activities daily. Defined as time spent engaged inactivities which involved physical or cognitive effort,this variable was dichotomised at 3 h daily.

The GDS-30 was used to measure depressivesymptoms. This instrument consists of 30 items,responses being either ‘yes’ or ‘no’. A score of 0–9indicates that depression is not present, 10–19 milddepression and 20–30 severe depression. Yesavage et al.(1983), in a sample of 147 older adults deemed non-depressed, mildly depressed or severely depressedaccording to Research Diagnostic Criteria, found thatthe GDS scores of these three groups differedsignificantly, thus demonstrating construct validity.Convergent validity with the Zung Self-Rating Depres-sion Scale (r¼ 0.83), Hamilton Rating Scale for



Depression (r¼ 0.84) and Beck Depression Inventory(r¼ 0.73 and 0.91 in separate studies) has also beendemonstrated. An average reliability of 0.8773 wasreported by Keiffer and Reese (2002) in a review of 133studies. In the present study, Cronbach alpha wasfound to be 0.76.

The elements of the CERAD NeuropsychologicalBattery employed were the immediate recall anddelayed recall tests. There are three immediate recalltrials, in each case a list of 10 words (the same wordspresented in a different order on each occasion)being presented visually to participants. Each word ispresented for two seconds, and read aloud by theparticipant. Once all 10 have been presented theparticipant has 90 seconds to recall the words verballyin any order. Participants can score between 0 and 10,with higher scores indicating superior performance.

The delayed recall test involves free recall by theparticipant of the 10 words from the immediate recalltask. This takes place between 5 and 8 min after thefinal immediate recall trial, during which time adistractor task has been performed. The distractor taskemployed was the constructional praxis test of theCERAD. The participant again has 90 seconds to recallthe words verbally. Possible scores range from 0 to 10,with higher scores indicating superior performance.

Finally, a measure of retrieval of items successfullyrecalled in the immediate recall tests, termed ‘savings’,was calculated according to the equation: (delayedrecall � maximum immediate recall) X 100.

Procedure

Participants were recruited through the use ofadvertisements in local media and posters in variouscentres frequented by the public.

One hundred and twenty-one people volunteered toparticipate. Only those volunteers who scored higherthan 23 on the MMSE, and were not in receipt ofantidepressants or anxiolytics, were included in thestudy. The demographic questionnaire included ques-tions relating, inter alia, to illness, infections and

Table 1 Memory task performance

Min Max

Immediate recall I 2 9Immediate recall II 4 10Immediate recall III 2 10Total immediate recall 11 28Delayed recall 0 10Savings (%) 0 100


pharmacotherapy. This was briefly examined oncecompleted, and any volunteers who met exclusioncriteria were thanked for their interest and informed,with an explanation, that it would not be possible toinclude them in the study. A total of 22 volunteers wereexcluded from the study.

Following the completion of the demographicquestionnaire, the GDS was presented, followed inturn with the MMSE and the recall trials.

Results

Participants were 99 adults aged from 60 to 83 years(M¼ 66.89, SD¼ 5.32; median¼ 66). Sixty-five werefemale, and 34 male. Forty-one participants had12 years or less of education, while 58 hadreceived more than 12 years. Forty-eight participantsreported enjoying less than 3 h of leisure daily, while51 participants had more than 3 h of leisure time daily.In relation to GDS scores, the range reported in thisstudy was between 0 and 15, with a mean of 4.91(SD¼ 3.73) and a median score of four. Scores on thememory tasks are summarised in Table 1.

The relationships between each independent vari-able and each of the cognitive measures were examinedusing non-parametric bivariate tests. In relation toImmediate Recall I, only depressive symptoms emergedas having a significant association, higher depressivescores related to poorer memory performance. Inrelation to Immediate Recall II, both depressivesymptoms and education level were significantlyassociated, higher depressive symptoms and lowereducation level being related to poorer memoryperformance. None of the IVs were found to beassociated with Immediate Recall III, though depress-ive symptoms (rho¼�0.155, p¼ 0.063) and edu-cation level (U¼ 987.5, p¼ 0.071) approached sig-nificance with greater depressive symptoms and lowereducation level associated with poorer performance.Both depressive symptoms and education level werefound to be related to total immediate recallperformance, with greater depressive symptoms and

Mean SD Median

5.17 1.51 57.05 1.49 77.87 1.36 8

20.09 3.78 206.39 2.01 7

78.53 19.37 83.33


Table 2 Significant bivariate relationships

DV IV Test Statistic p

Immediate recall I Depressive symptoms Rho¼�0.199 0.025Immediate recall II Depressive symptoms Rho¼�0.233 0.010

Education U¼945.5 0.039Total immediate recall Depressive symptoms Rho¼�0.239 0.009

Education U¼942.0 0.039Delayed recall Education U¼933.5 0.033


lower education level associated with poorer cognitiveperformance. In relation to delayed recall, onlyeducation level emerged as significantly related, lowereducation level associated with poorer performance.None of the IVs were found to be associated withsavings. These findings are summarised in Table 2.

Standard multiple regressions were performed toexamine the relationships between each of the recallvariables and each of the predictors. Age, gender,depressive symptoms, education level and leisureactivity were included in a single block.

In relation to the first and second trials ofimmediate recall, only depressive symptoms emergedas a significant unique contributor to the predictivemodels. Only age emerged as a significant uniquecontributor to the model of the third trial ofimmediate recall. Depressive symptoms emerged asthe only significant unique contributor to the modelof total immediate recall, while in the analysis ofdelayed recall performance and savings, only edu-cation level emerged as a significant unique con-tributor to the models. These results are summarisedin Table 3.

Table 3 Results of Simultaneous Multiple Regressions

Immediate recall I Imm

b B SE b

Depressive �0.185* �0.075 0.044 �0.183*SymptomsEducation 0.079 0.240 0.325 0.102Leisure 0.056 0.169 0.314 0.034Age �0.106 �0.030 0.029 �0.013Gender �0.034 �0.107 0.325 �0.042

Total immediate recall D

b B SE b

Depressive �0.191* �0.194 0.108 0.037SymptomsEducation 0.114 0.867 0.803 0.221*Leisure 0.052 0.393 0.777 �0.039Age �1.116 �0.080 0.072 �0.049Gender �0.062 �0.490 0.804 �0.072

*p< 0.05.


In summary, depressive symptoms were found to besignificantly associated, both bivariately and control-ling for the other four predictors, with both the firsttwo trials of immediate recall and the total immediaterecall score. In each case, higher depressive symptomswere associated with poorer performance. Educationlevel was found in bivariate analysis and controlling forthe other predictors to be associated with delayedrecall. In bivariate analysis only, education level wasfound to be associated with the second trial ofimmediate recall and the total immediate recallmeasure. In relation to the savings measure, educationlevel was found to be significantly related controllingfor the remaining four predictors. In each case, thosewith over 12 years of formal education performed better.

Discussion

The data indicate that both depressive symptoms andeducation level were associated with aspects of recallperformance in this sample. Further, the pattern ofresults suggested that depressive symptoms particularly

ediate recall II Immediate recall III

B SE b B SE

�0.073 0.043 �0.125 �0.046 0.039

0.308 0.321 0.116 0.319 0.2890.100 0.311 0.046 0.124 0.279

�0.004 0.029 �0.182* �0.046 0.026�0.131 0.322 �0.089 �0.252 0.289

elayed recall Savings

B SE b B SE

0.020 0.058 0.143 0.745 0.558

0.896 0.430 0.223* 8.715 4.132�0.155 0.416 �0.054 �2.095 3.999�0.019 0.038 0.031 0.113 0.369�0.301 0.431 �0.090 �3.638 4.137


Key points

� InthisstudyofcognitivelynormalIrish olderadults,depressive symptoms and education level emerge asimpacting memory. Specifically, depressive symp-toms appear to impact encoding while educationlevel impacts storage and/or retrieval. Both out-comes are explicable with reference to theory andboth point to interventions which may prove usefulin reducing memory complaints in later life.


impacted immediate recall performance while educationlevel was particularly associated with delayed recall andsavings.

The results in relation to depressive symptoms arecomprehensible in view of the theories in relation toattention and concentration outlined above (Hartlageet al., 1993). It is to be expected that increased time forprocessing and greater numbers of presentations wouldserve to ameliorate the impact of reduced attention and/or psychomotor speed, and the data supports this view.In particular, the fact that depressive symptoms werefound to impact the first two trials of immediate recall,but not the third trial, delayed recall or savings, suggestthat the impact of depressive symptoms is on encodingrather than storage or retrieval of items.

An interesting point in relation to depressive symp-toms (as opposed to depressive caseness) is that, contraryto some previous research (e.g. Clark et al., 2004), thenumber of such symptoms were found to reduceimmediate recall performance. This finding mayhave important implications—as very few participantsmet the cut-off point for mild depression and none didso for severe depression, it may be that use of diagnosticcriteria may not be adequate to identify a level ofdepression which leads to reduced recall performance.Therapeutic intervention for older adults with sub-clinical levels of depressive symptoms may prove to bebeneficial in those with memory complaints.

Education, conversely, emerged as being selectivelyassociated with delayed recall and savings—thus withstorage and/or retrieval rather than encoding. Thisfinding is in keeping with the results of Wiederholtet al. (1993), that having attended third level wasassociated with superior delayed recall but not immedi-ate recall. The fact that other studies (Le Carret et al.,2003) showed an effect of education on both immediateand delayed recall when education was dichotomisedaround a lower level than in the present study maysuggest that the effect of education on memory is notlinear, but reaches a maximum for immediate recall atan earlier point than is the case for delayed recall.

The results of this and previous studies may providepotential for intervention in cases of memory com-plaints. In light of research linking higher educationlevel to both superior memory performance in cogni-tively normal older adults and to decreased risk ofincident dementia (e.g. Karp et al., 2004), increasedaccess to lifelong learning may prove to be a valuablepublic health tool. Furthermore, while there is con-siderable evidence that education is protective againstboth normal and pathological cognitive decline, it hasnot yet been established whether interventions basedon the cognitive reserve hypothesis can prove useful in


treating pre-existing age-related cognitive decline(Harvard Mental Health Letter 2006). Research inthis area could prove very beneficial in adding apowerful non-pharmacological weapon to thearmoury of those treating cognitive dysfunction.

The other marker of cognitive reserve employed inthe present study, leisure activity, did not prove to beassociated with any of the memory measures. Adifficulty in relation to this variable is that there is asyet no agreed means of measurement. It is possible thata more specific measure of lifetime cognitive activityrather than contemporary leisure activity would provea more effective predictor of cognitive performance.

The study has some limitations. The operationalisa-tion of leisure activity was focussed on present levelsrather than lifetime activity, and did not distinguishbetween cognitive and physical leisure. The sample wasrecruited through advertising; those with poorercognitive performance and greater levels of depressionmay have been less likely to respond, and so there maybe difficulties in generalising the findings. In addition,generalisability is compromised by the relatively smallsample, and particularly by the small number of maleparticipants. Nonetheless, the results are in keepingwith those of much previous research.

In summary, the findings of the present study are thatdepressive symptoms are selectively associated with imme-diate recall, while education level is selectively associatedwith delayed recall and savings. Both findings suggestpossible interventions which may prove beneficial inthe treatment of memory decline in older age.

Conflicts of interest

None known.

Ethics

This research was carried out in accordance with theethical guidelines of the British Psychological Society.



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depression, cognitive reserve and memory performance in older adults

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