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Linking depressive symptoms and functionaldisability in late lifeJ. J. Gallo , G. W. Rebok , S. Tennsted , V. G. Wadley , A. Horgas & The AdvancedCognitive Training for Independent and Vital Elderly (Active) Study Investigatorsa University of Pennsylvania , Philadelphia, Pennsylvaniab Johns Hopkins University , Baltimore, Marylandc New England Research Institutes , Watertown, Massachusettsd University of Alabama at Birmingham , Birmingham, Alabamae University of Florida , Gainesville, Florida, USAPublished online: 12 Jul 2010.

To cite this article: J. J. Gallo , G. W. Rebok , S. Tennsted , V. G. Wadley , A. Horgas & The Advanced Cognitive Trainingfor Independent and Vital Elderly (Active) Study Investigators (2003) Linking depressive symptoms and functional disabilityin late life , Aging & Mental Health, 7:6, 469-480

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ORIGINAL ARTICLE

Linking depressive symptoms and functional disability in late life

J. J. GALLO1, G. W. REBOK2, S. TENNSTEDT3, V. G. WADLEY4, A. HORGAS5 & THEADVANCED COGNITIVE TRAINING FOR INDEPENDENT AND VITAL ELDERLY (ACTIVE)STUDY INVESTIGATORS

1University of Pennsylvania, Philadelphia, Pennsylvania; 2Johns Hopkins University, Baltimore, Maryland;3New England Research Institutes, Watertown, Massachusetts; 4University of Alabama at Birmingham,

Birmingham, Alabama & 5University of Florida, Gainesville, Florida, USA

AbstractWe hypothesized that the relationship of depressive symptoms to functional disability might be mediated by cognitiveprocesses such as memory and problem-solving. The study sample consisted of 147 community-dwelling older adults (meanage¼ 74.0 years, SD¼ 5.9). In regression models that included terms for age, gender, and years of education, depressivesymptoms were significantly inversely associated with two performance-based measures of functioning: everyday problemstest (�¼�0.15, p¼ 0.04) and observed tasks of daily living (�¼�0.14, p¼ 0.02). When memory and problem-solving abilitywere added to the model, the relationship of depressive symptoms with function was attenuated. A structural equation modelbased on our conceptual framework revealed that both memory and problem-solving abilities were important mediators inthe relationship of depressive symptoms and functional disability. The results suggest that intervention studies intended tolimit functional disability secondary to depression among older adults may need to consider the effect of depression oncognition.

Introduction

Disability in older adults is a major determinant

of costly outcomes such as nursing home place-

ment, hospitalization, and mortality. The World

Health Organization report, ‘The Global Burden of

Disease,’ predicts that depression will be second only

to cardiovascular disease as a worldwide cause of

disability in the year 2020 (Murray & Lopez, 1996).

Depressive symptoms and functional disability go

hand-in-hand, but the processes underlying the

relationship are poorly understood. Studies have

found an association between functional disability

and the development of depression (Alexopoulos

et al., 1996; Lyness et al., 1993) and between

depression and the development of functional dis-

ability (Bruce et al., 1994;Gallo et al., 1997; Kennedy,

Klerman & Thomas, 1990; Penninx et al., 1998), but

it is not clear what cognitive factors, such as the effect

of depression on memory performance, might med-

iate this relationship. Complicating matters, older

adults with depression may not present in a stereo-

typical fashion—depression is sometimes expressed

in somatic or psychomotor terms—and subsyndromal

depressive symptoms, that is, symptoms that do not

meet the standard criteria for major depression, are

often associated with significant functional limitation

in their own right (Broadhead et al., 1990; Bruce et al.,

1994; Gallo et al., 1997; Horwath et al., 1992; Jaffe,

Froom & Galambos, 1994; Johnson, Weissman &

Klerman, 1992; Judd et al., 1996; Olfson et al., 1996;

Penninx et al., 1998).

Despite recent work that ties functional disability

to depressive symptoms, the intermediate processes

in the relationship have not been empirically tested.

In the context of depressive symptoms in late life,

this is especially important because we do not have

consensus on how to identify subsyndromal depres-

sive disorder. The study of potentially important

mediators between depressive symptoms and func-

tional disability can pave the way to a better

understanding of how depression relates to func-

tional disability, and what might be done to prevent

impairment secondary to depression. The purpose of

this investigation was to examine the extent to which

the relationship of depressive symptoms to functional

Correspondence to: Joseph J. Gallo, University of Pennsylvania Health System, Department of Family Practice andCommunity Medicine, 2 Gates Building, 3400 Spruce Street, Philadelphia, Pennsylvania 19104-4283, USA. Tel: þ1 215615 0849. Fax: þ1 215 662 3591. E-mail: jjgallo@mail.med.upenn.edu

Received for publication 8th July 2002. Accepted 3rd March 2003.

Aging & Mental Health, November 2003; 7(6): 469–480

ISSN 1360–7863 print/ISSN 1364–6915 online/03/060469–12 � Taylor & Francis LtdDOI: 10.1080/13607860310001594736

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disability might be mediated by cognitive processes

such as memory or problem solving in a sample of

community-dwelling older adults.

Several findings have led to a conceptual model

that ties functioning along cognitive dimensions to

everyday functioning. Fluid abilities refer primarily

to reasoning, abstraction, and problem solving

(Cattell, 1971; Cornelius & Caspi, 1987; Horn,

1982). Fluid abilities assessed at baseline are highly

predictive of everyday functioning at follow-up

(Willis & Marsiske, 1991). How do memory, speed

of processing, and fluid abilities relate to each other

as mediators of depressive symptoms and function?

Marsiske and colleagues found that working memory

and speed of processing had only indirect effects on

functioning, while fluid and crystallized intellectual

abilities were the direct predictors of functioning

in everyday life (Marsiske & Willis, 1995; Marsiske

et al., 1995; Willis et al., 1992). In a seven-year

follow-up, Willis and colleagues reported that 52%

of the variance in a basic skills measure at follow-up

was accounted for by tests of fluid abilities at baseline

(Willis et al., 1992).

In this study, we are modifying the model to

investigate the impact of depressive symptoms on

everyday function by positing that cognitive pro-

cesses serve as mediators (Figure 1). A characteristic

is a mediator if it accounts for the variation between

a predictor and an outcome. While moderators

indicate when effects might be seen, mediators

specify how or why (Baron & Kenny, 1986). The

conceptual model in Figure 1 represents a set of

testable hypotheses about how the constructs repre-

senting depressive symptoms and functional limita-

tions may be related to one another through their

association with cognitive functioning. First, depres-

sive symptoms might affect basic cognitive processes

(such as memory). Second, depressive symptoms

might affect more complex cognitive processes (such

as problem-solving abilities). Third, depressive

symptoms might affect functioning by coloring self-

evaluation of competence or mastery (related to loss

of interest in activities previously performed or to

self-efficacy). We hypothesized that depressive symp-

toms might act on cognitive constructs to interfere

with functioning. In other words, the association of

depressive symptoms with functional disability might

be mediated through the association of depressive

symptoms with impaired cognitive abilities. This

investigation differs from other studies of the asso-

ciation of depression and disability in at least three

important ways: (1) the sample consisted of com-

munity-dwelling older adults; (2) performance-based

measures of everyday functioning were employed;

and (3) the conceptual model into which we have

introduced depression has been the basis for studies

of cognitive abilities.

Method

Study sample

The sample was derived from a pilot study carried out

prior to a large-scale intervention study, the Advanced

Cognitive Training for Independent and Vital Elderly

(ACTIVE) Trial (Ball et al., 2002). None of the

participants in the pilot study were recruited for the

subsequent intervention trial. The ACTIVE study is a

multisite, clinical trial of cognitive interventions to

improve functional outcomes among older adults

recruited from community settings. ACTIVE consists

of six field sites based at the University of Alabama at

Birmingham, Wayne State University, Pennsylvania

State University, the Hebrew Rehabilitation Center

for the Aged, Boston, Massachusetts, Indiana

University School of Medicine, Johns Hopkins

University, Baltimore, Maryland, and a Data

Coordinating Center at the New England Research

Institutes, Watertown, Massachusetts (Jobe et al.,

2001).

At each site, investigators recruited older adults

aged 65 years and older from a variety of community

settings such as health centers, community and senior

centers, senior housing, and churches, as well as driv-

er registration lists (Owsley et al., 2002). Assessments

were carried out at recruitment sites and were

standardized through a variety of training and quality

control procedures including certification of assessors

by the data-coordinating center after a weeklong

training session. The screening occurred in two

stages: (1) an initial phase of screening on the

MemoryProblem-solvingabilities

Depressivesymptoms

Function

FIG. 1. Conceptual model guiding analysis of the potential relationship of depressive symptoms, cognition, and function.

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telephone to identify subjects who were obviously

cognitively or functionally impaired or who had a spe-

cific serious health problem and would be excluded

from the intervention trial; and (2) in-person assess-

ment to further determine eligibility. Institutional

Review Boards approved the project at each study site.

Eligibility criteria

Persons with significant cognitive impairment as

indicated by a Mini-Mental State Examination score

of less than 23/30 (a threshold consistent with

moderate to severe cognitive impairment [Anthony

et al., 1982; Folstein, Folstein & McHugh, 1975;

Tombaugh & McIntyre, 1992]) were excluded.

We also excluded from participation persons who

reported impairment in one or more personal

activities of daily living, had serious vision or hearing

impairments, had limited life expectancy, did not

speak English, or who were otherwise unable to give

informed consent.

Measurement strategy

Depressive symptoms:

. Center for Epidemiologic Studies Depression Scale

(CES-D): The CES-D was developed by the

Center for Epidemiologic Studies at the National

Institute of Mental Health for use in studies of

depressive symptoms in community samples

(Comstock & Helsing, 1976; Eaton & Kessler,

1981; Radloff, 1977). The CES-D contains 20

items. Typically, a threshold of 17 and above is

taken as defining ‘caseness’ (Katon & Schulberg,

1992). The CES-D has been employed in many

studies of older adults (e.g., Gatz et al., 1993;

Newmann, Engel & Jensen, 1991). Factor analyses

of the CES-D have suggested that the scale

comprises four subscales: negative affect, low

positive affect, interpersonal difficulties, and so-

matic complaints (Davidson, Feldman & Craw-

ford, 1994; Herzog et al., 1990; Radloff, 1977).

Somatic complaints on the CES-D increase as

medically ill patients experience depressive symp-

toms, but do not necessarily increase ‘false-

positives’ (Foelker & Shewchuk, 1992). Screening

instruments that give undue weight to mood

disturbance would miss potentially important

forms of depression, especially among older adults.

For the CES-D, � coefficients for internal con-

sistency of 0.8 to 0.9 have been reported (Davidson

et al., 1994; Roberts, 1980; Shinar et al., 1986),

with good correlation to other depression instru-

ments and to clinical assessments (Parikh et al.,

1988; Shinar et al., 1986; Zich, Attkisson &

Greenfield, 1990). The � coefficient for this

sample was 0.8. A total score derived from the

four subscale scores was used in the analysis.

. Everyday function—everyday problems test (EPT):

The EPT measures the ability of older adults to

understand and solve problems involving everyday

printed materials dealing with seven domains of

daily living (food preparation, medication use,

telephone use, financial arrangements, shopping,

transportation, and housekeeping and laundry)

(Diehl, Willis & Schaie, 1995; Marsiske & Willis,

1995). In the EPT, older persons see 15 different

everyday printed materials (e.g., a tax form, a

medication label). The test uses materials bor-

rowed from everyday life, not abstract versions.

The participant is asked to solve problems about

each printed item (e.g., when shown a drug label,

participants might be asked the maximum number

of teaspoons they should take over a two-day

period). The EPT consists of 84 items in seven

subscales, each associated with a domain of

instrumental activities of daily living (IADLs).

The test has excellent internal consistency (Cron-

bach’s � ¼ 0.94), test-retest reliability (two-month

reliability ¼ 0.94), and correlation with perfor-

mance-based measures of IADLs carried out in the

respondent’s home (Willis, 1996). The total score

is derived by summing the number of correct

responses across all the items.

. Observed tasks of daily living (OTDL): The OTDL

provides an observer-based measure of functioning

in three cognitively demanding tasks of daily living;

namely, medication use, telephone use, and

managing finances (Diehl et al., 1995). In contrast

to the EPT, the OTDL assesses performance

through direct observations of behavior. In the

OTDL, participants are shown certain items like

medicine bottles or a utility bill. Questions are

printed on cards and the participant must use the

prop to find the answer. The test presents practical

problems for which a solution is not readily

apparent, requiring inferential thinking. The total

score is the sum of the individual items.

Memory:

. Hopkins verbal learning test (HVLT): The HVLT

evaluates new verbal learning and memory. On

each of three trials, in this study, participants

listened to an audio-taped list of 12 words (four

from each of three different semantic categories),

read at two-second intervals, and were asked to

recall as many of the words as possible (Brandt,

1991). Immediately after the third trial a yes/no

recognition trial (12 targets, 12 distractors—six

semantically related, six not semantically related)

was presented. Total words correctly recalled over

the three learning trials, the number of correct

recognitions, the number of related and unrelated

false-positive errors, and a discrimination index

were calculated. For the present investigation, we

employed total number of words correctly recalled

over all three trials.

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. Auditory verbal learning test (AVLT): The AVLT is

a reliable and valid measure of the ability to form

and retain verbal memories that is widely used in

the differential diagnosis of memory disorders in

adults (Rey, 1964). The number of words recalled

across five trials provides an index of the efficiency

of new learning while a delayed recall trial assesses

adequacy in the consolidation of new memories. In

the administration of the AVLT for this study, the

participants listened to an audio-taped list of 15

words, read at two-second intervals, and were

asked to write down as many as they can remember

in two minutes. After hearing the list five times, a

new list of 15 words was presented and the

participants were asked to write down as many

words as they could remember from the new list.

Then respondents were asked to write down as

many words as they could remember from the first

list without hearing it again. We used the total

number correct of words recalled over the five

learning trials as the score in this analysis.

. Rivermead behavioral memory test: The Rivermead

behavioral memory test is a standardized battery of

new learning and everyday memory tasks (Wilson,

Cockburn & Baddeley, 1985). In the ACTIVE

study, the subtest that assesses memory for stories

was selected. For this task, a brief story consisting

of four to five sentences was played on a tape

recorder. The participant was then asked to write

down as much of the story as possible in three

minutes. The number of idea units presented in

the story that were correctly recalled (out of 21)

was taken as the score for this task.

Problem-solving ability:

. Letter series: Letter series is a measure of inductive

reasoning that is an adaptation of the number

series and letter series tests of Thurstone (Thur-

stone & Thurstone, 1962) and the letter sets test of

Ekstrom (Ekstrom et al., 1976). The study partic-

ipant was asked to discover one or more rules or

patterns and must then mark the letter that should

come next in the series. Each series of letters

followed a different pattern description rule. On

the left side of the page, subjects saw a row of

letters like ‘a c b a d b e _’ and must determine,

from an answer row on the right (e.g., ‘a b c d e f g

h’) which letter would come next in the series.

Participants were given six minutes to complete the

task. The total number of series correctly complet-

ed was recorded and used in analysis.

. Letter sets: In letter sets, participants viewed a set of

letters and had to identify the set that did not use

the same pattern rule as the other sets in that group

(Blieszner, Willis & Baltes, 1981). Participants

were presented a page with 15 lines of letter sets,

each line containing five sets of letters, and were

asked to mark an ‘x’ through the letter set that did

not fit the rule. A total of seven minutes was given

to complete the task. The total number of letter

sets correctly identified was recorded and used in

analysis.

. Word series: Word series tests whether individuals

can determine the pattern of words in a list and then

select the word that would come next in the series.

Each series of words follows a different pattern

description rule. The word series are usually made

up of months of the year or days of the week.

Moving down a column, participants saw a list of

words (e.g., ‘January, February, February, March,

April, April, _____’), and had to determine, from a

separate column of choices (e.g., ‘January, Febru-

ary, February, March, April, April, May, June’)

what word would come next in the series. Partici-

pants were given six minutes to complete the task.

The total number of word series correctly complet-

ed was scored and used in analysis.

Analytic strategy

Data analysis proceeded in three phases: (1) descrip-

tive analyses including examination of distributions

of the variables under study and estimates of

bivariate associations with measures of depressive

symptoms and functioning; (2) stepped multiple

regression to assess mediation with the measures of

functional status as the dependent variable; and (3)

a priori structural equation models to evaluate the

conceptual model dealing with memory and prob-

lem-solving abilities. In addition, we examined

separate models with EPT or OTDL measures of

functioning as the dependent variable. We carried

out two-tailed tests of significance with the Type I

error rate set at 0.05. Analyses were restricted to

persons who had complete data on all the variables

under study (n¼ 147).

Mediat ion assessed with mult ip le regress ion

analyses. The primary analytic method was multiple

regression, in which the covariates were entered

as continuous variables without transformation.

Measures of association were adjusted for age,

gender, and years of education because these personal

characteristics are often associated with performance

on cognitive tests. Consistent with the outline of

Baron and Kenny (1986), multiple regression anal-

yses were carried out in three stages: (1) regression

of depressive symptoms on cognitive measures;

(2) regression of functional disability measures on

depressive symptoms and cognitive measures sepa-

rately; and, (3) regression of functional measures on

depressive symptoms with terms representing cogni-

tive measures in the model. We reasoned that if

any significant association of depressive symptoms

and functional disability were attenuated with terms

representing cognitive variables in the multiple reg-

ression model, this would be evidence for mediation.

Separate analyses examined the EPT and OTDL as

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the dependent variable representing functioning.

Doing so provided an opportunity to replicate our

test of the conceptual model with two separate

operationalizations of functioning as the dependent

variable. SPSS software version 10.0 was used to carry

out the regression analyses.

Mediation assessed with structural equation models. To

assess the relative importance of memory abilities

versus problem-solving abilities as potential media-

tors of the relationship of depressive symptoms and

functional disability, analyses employing a structural

equation model (SEM) were carried out. A structural

equation model permitted us to test whether

depressive symptoms appear to act on functional

disability primarily through the relationship of

depressive symptoms with memory or primarily

through the relationship of depressive symptoms

with problem solving ability (which is not possible

with standard regression analyses). The model used

is an extension of Muthen’s multiple indicators,

multiple causes (MIMIC) model (Muthen, 1989),

which we have employed in other work (Gallo,

Anthony & Muthen, 1994; Gallo, Cooper-Patrick &

Lesikar, 1998; Gallo, Rabins & Anthony, 1999).

This model can be thought of as confirmatory factor

analysis with background variables (Muthen &

Muthen, 1998). We treated the CES-D score as a

single continuous variable measuring depressive

symptoms, but we specified a measurement model

for the other variables under study for which we have

two or three continuous measures of the underlying

latent variable. Specifically, memory was represented

by the HVLT, AVLT, and the Rivermead behavioral

memory test, problem-solving ability by the letter

series, letter sets, and word series tests, and func-

tioning by the EPT and the OTDL. The mea-

surement model allowed us to account for

measurement error in our measures of association

(Hoyle, 1995; Maruyama, 1998).

We report standardized measures of association to

account for the differing scales of the instruments

employed. We examined differences in �2 for nestedmodels to assess improvement in fit offered by freeing

parameters of interest that relate depression to the

variables under study. In addition, we compared the

value of the Akaike Information Criterion (AIC) for

each model (Aikaike, 1987). The AIC accounts for

both model fit and parsimony (Schumacker &

Lomax, 1996). The structural models were estimated

with Muthen’s SEM program Mplus with maximum

likelihood estimation (Muthen & Muthen, 1998).

Results

Characteristics of the sample

Table 1 provides the characteristics for the sample of

147 persons for whom complete data were available

on all variables. There were no statistically significant

differences in the means or proportions between the

group with no missing data and the entire pilot

sample of 170 at the �¼ 0.05 level. Continuous

variables were normally distributed.

Depressive symptoms and functioning

The regression coefficients of depressive symptoms

as measured by the CES-D on the cognitive variables

are presented in Table 2. In all cases, depressive

symptoms were related to the cognitive variables

under study. We also present regression coefficients

estimated with terms for age, gender, and level of

educational attainment in the model. Memory tests

and problem-solving abilities were associated with

depressive symptoms, although the relationships

were attenuated with adjustment for age, gender,

and years of education.

Depressive symptoms and cognitive variables

Table 3 presents the regression coefficients for the

regression of EPT and OTDL scores on depression,

memory, and problem-solving ability. Bivariate esti-

mates of association are also presented adjusted for

age, gender, and years of education. The cognitive

variables were all highly significantly associated with

measures of everyday function, even after adjustment.

Evidence for mediation through memory andproblem-solving abilities

We next introduced terms for depressive symptoms,

memory, and problem-solving abilities sequentially

TABLE 1. Characteristics of 147 participants withcomplete data

Mean (SD)or number (%)

SociodemographicsAge (years) 74.0 (5.88)Educational level (grade) 12.0 (2.91)Gender (% women) 119 (81.0%)Self-reported ethnicity (% non-White) 83 (56.5%)

MemoryHopkins verbal learning test 22.3 (5.50)Auditory verbal learning test 44.2 (10.60)Rivermead behavioral memory test 5.6 (2.38)

Problem-solving abilityLetter series 4.8 (2.76)Letter sets 4.9 (2.98)Word series 6.5 (4.40)

Depressive symptomsCES-D 6.4 (6.08)

FunctionEveryday problems test 13.6 (6.38)Observed tasks of daily living 16.6 (5.16)

CES-D, Centers for Epidemiologic Studies Depression Scale.

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into models with EPT score as the dependent

variable (shown in the left-hand side of Table 4).

We replicated the analysis with OTDL score as the

dependent variable (shown in the right-hand side of

Table 4). In each case, the association of depressive

symptoms with everyday function diminished to the

null value with cognitive variables in the model,

regardless of the particular measure of function

employed, and even after adjusting for age, gender,

and level of educational attainment.

Structural equation model of mediation

The SEM was employed to operationalize the

conceptual model of the mediation of memory and

problem-solving abilities in the relationship of

depressive symptoms and function as illustrated in

Figure 2. Standardized parameter estimates and

measures of model fit were estimated for each

model that included paths from depressive symp-

toms to memory, problem-solving abilities, or

function. In all models, the coefficients representing

the paths from depressive symptoms to memory and

to problem-solving abilities were significantly differ-

ent from zero. However, the direct path from

depressive symptoms to everyday function did not

significantly improve the fit (��2¼ 0.34, df¼ 1). We

selected the model illustrated in Figure 2 as the best

model on the basis of fit and parsimony and will

discuss that model in more detail.

For the selected model, the standardized param-

eter estimate for the relationship of memory to

problem-solving ability of 0.54 indicates that a one

standard deviation increase in memory function

could be expected to be associated with a 0.54

standard deviation increase in problem-solving abil-

ity. Similarly, the standardized parameter estimate

for the relationship of problem-solving ability to

everyday function of 0.76 indicates that a one

standard deviation increase in problem-solving abil-

ity could be expected to be associated with a 0.76

standard deviation increase in everyday functioning.

The coefficients estimated for the paths from

depressive symptoms to memory and problem-

solving ability were both significantly different from

the null value of zero. Based on our estimate for the

path from depressive symptoms to memory, a one

standard deviation increase in depressive symptoms

can be expected to be associated with a decline by

a 0.25 standard deviation in memory function.

Similarly, based on our estimate for the path from

depressive symptoms to problem-solving abilities, a

one standard deviation increase in depressive symp-

toms can be expected to be associated with a 0.15

standard deviation decline in problem-solving ability.

We can calculate the total effect of a one standard

deviation increase in depressive symptoms through

memory to everyday functioning as leading to an

expected 0.10 of a standard deviation decline in

everyday function (�0.25� 0.54� 0.76). A one

standard deviation increase in depressive symptoms

TABLE 3. Regression of function as measured by everyday performance test (EPT) and observed tasks of daily living(OTDL) scores on potentially mediating variables

Everyday Performance Test Observed Tasks of Daily Living

Unadjusted Adjusted Unadjusted Adjusted

� p-value � p-value � p-value � p-value

Depressive symptomsCES-D �0.24 0.01 �0.15 0.04 �0.21 0 �0.14 0.02

MemoryHVLT 0.56 <0.001 0.42 <0.001 0.35 <0.001 0.25 <0.001AVLT 0.29 <0.001 0.23 <0.001 0.14 <0.001 0.09 0.01Rivermead 1.20 <0.001 0.83 <0.001 0.70 <0.001 0.43 0

Problem-solving abilityLetter series 1.08 <0.001 0.79 <0.001 0.61 <0.001 0.40 0Letter sets 1.30 <0.001 0.99 <0.001 0.64 <0.001 0.38 0Word series 0.98 <0.001 0.76 <0.001 0.55 <0.001 0.36 <0.001

Adjusted models include terms for age, gender, and years of education. Data from the participants in pilot testing for the AdvancedCognitive Training for Independent and Vital Elderly (ACTIVE) trial. AVLT, Auditory verbal learning test; CES-D, Center forEpidemiologic Studies Depression Scale; HVLT, Hopkins verbal learning test; Rivermead, Rivermead behavioral memory test.

TABLE 2. Regression of CES-D score on potentiallymediating variables

Unadjusted Adjusted

� p-value � p-value

MemoryHVLT �0.25 0.01 �0.24 0.01AVLT �0.09 0.03 �0.09 0.06Rivermead �0.5 0.01 �0.42 0.05

Problem-solving abilityLetter series �0.4 0.02 �0.32 0.08Letter sets �0.43 0.01 �0.33 0.06Word series �0.38 < 0.001 �0.34 0.01

Adjusted models include terms for age, gender, and years ofeducation. AVLT, Auditory verbal learning test; HVLT,Hopkins verbal learning test; Rivermead, Rivermead behavioralmemory test.

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would lead to a 0.12 of a standard deviation decline

in everyday function (�0.15� 76). In total, a one

standard deviation decrease in depressive symptoms

would be expected to be associated with a 0.22

standard deviation decline in everyday function (sum

of indirect effects, [�0.10] þ [�0.12]¼ �0.22), as

estimated by this model with the operationalization

of the variables we have employed for this study.

Discussion

In our investigation, we found evidence that the

association of depressive symptoms with everyday

functioning among older persons without significant

cognitive impairment was mediated through the

association of depressive symptoms with specific

cognitive abilities. We must interpret our findings

cautiously because the results are based on cross-

sectional data in a pilot study. The findings require

confirmation in larger samples and with a long-

itudinal design to clarify the directionality of the

relationships postulated in the conceptual model.

Nevertheless, we have been able to link depressive

symptoms and functional disability as assessed with

standardized performance-based measures through

the association of depression with memory and

problem-solving abilities.

CES-D

MemoryProblem-solvingability

Function

Rivermead

HVLT AVLT

Letter Series

Word Series

Letter Sets

EPT OTDL

-0.245 -0.152

0.54 0.76

FIG. 2. Structural equation model relating depression scores to performance measures of function through measures ofmemory and problem-solving abilities. Standardized parameter estimates are provided. AVLT, auditory verbal learning test;CES-D, Center for Epidemiologic Studies Depression Scale; EPT, everyday problems test; HVLT, Hopkins verbal learningtest; OTDL, observed tasks of daily living; Rivermead, Rivermead behavioral memory test.

TABLE 4. Regression of function as measured by everyday performance test (EPT) and observed tasks of daily living(OTDL) scores on depressive symptoms and potentially mediating variables related to memory and problem-solving ability

Everyday Performance Test Observed Tasks of Daily Living

Model 1 Model 2 Model 3 Model 4(adjusted)

Model 1 Model 2 Model 3 Model 4(adjusted)

Depressive symptomsCES-D �0.240 �0.105 �0.016 �0.009 �0.205 �0.125 �0.094 �0.073

(0.005) (0.161) (0.801) (0.873) (0.003) (0.061) (0.214) (0.237)

MemoryHVLT 0.267 0.136 0.098 0.271 0.201 0.166

(0.021) (0.162) (0.290) (0.008) (0.046) (0.089)AVLT 0.107 0.076 0.099 0.020 �0.036 �0.019

(0.089) (0.144) (0.046) (0.719) (0.506) (0.712)Rivermead 0.635 0.195 0.107 0.410 0.204 0.138

(0.004) (0.300) (0.548) (0.035) (0.293) (0.461)

Problem-solving abilityLetter series �0.201 �0.053 �0.108 0.019

(0.317) (0.780) (0.601) (0.924)Letter sets 0.610 0.523 0.164 0.087

(0.001) (0.002) (0.359) (0.614)Word series 0.576 0.377 0.363 0.538

(<0.001) (0.010) (0.019) (<0.001)

Adjusted models presented in the rightmost columns include terms for age, gender, and years of education. Data from the participants inpilot testing for the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial. AVLT, Auditory verbal learning test;CES-D, Center for Epidemiologic Studies Depression Scale; HVLT, Hopkins verbal learning test; Rivermead, Rivermead behavioralmemory test. p-values in parentheses.

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Study strengths and limitations

Before discussing the results in detail and placing

them within the context of other work, limitations

deserve comment. First, we employed data from a

small sample. On the other hand, the participants

were community dwelling, quite healthy, and

mostly independent. Because we excluded individ-

uals with ADL impairments from participation, our

conclusions regarding the relationship of depressive

symptoms to the variables under study are not

influenced by the presence of relatively severe self-

care impairments. Instead, the functional outcomes

examined in this study were cognitively demanding

everyday activities. Thus disability in the activities

studied represents the early ‘preclinical’ (Fried

et al., 1997) phase of the disablement process.

Second, the data are cross-sectional. For that

reason, we cannot be sure the extent to which

our measures of association of depressive symp-

toms to cognitive status or functioning occurred

because persons with poor cognitive status or

functioning are more likely to express depressive

symptoms. Third, persons with depression tend to

rate their health or abilities more poorly than

others without depression or compared to the same

individuals when they are not depressed (Miranda

& Persons, 1988; Miranda, Persons & Byers,

1990). However, in this study, we have been able

to minimize this effect because we employed

performance measures of functioning in contrast

to a reliance on self-reports. In addition, we have

two performance-based measures of functioning

which act as a form of replication of our regression

results. With two measures of functioning, the

extent to which any association with depression

reflects the measurement properties of a particular

functional assessment instrument can be assessed.

We have supplemented our regression-based anal-

ysis with structural equation modeling. Using this

technique permits us to explicitly model mea-

surement error in the instruments employed in

operationalizing the constructs, such as memory

performance, within the conceptual framework

that guided our analyses. We were also able to

provide separate estimates of the mediation of the

association of depressive symptoms with func-

tioning through memory and problem-solving abili-

ties. Finally, we realize that even standardized

measures are fallible and may tap constructs that

were not intended by the developers or implied

by the labels given them. Depressive symptoms as

assessed by the CES-D do not correspond to

diagnostic criteria for major depression (American

Psychiatric Association, 1994). However, we would

argue that depressive symptoms are appropriate as a

focus of our investigation of older adults for reasons

we have discussed elsewhere (Gallo, 1995; Gallo

et al., 1994; Gallo et al., 1998; Gallo & Lebowitz,

1999; Gallo et al., 1999).

Linking depression and disability

Investigators have recently focused on the role

of cognitive functions on activities required for

independent living. Activities such as shopping,

telephone use, managing finances, and appropriate

use of medications call for complex cognitive

processes. Research into the faculties needed for

everyday functioning is a new field with several

names: practical problem solving, everyday problem

solving, everyday cognition, pragmatic intelligence,

and practical intelligence (Marsiske & Willis, 1995).

The cognitive processes underlying everyday ability

decline at different rates with age and involve

different brain regions, so that a multidimensional

model appears to be most appropriate in considering

how cognitive functions relate to everyday func-

tioning. The central notion is that certain basic

cognitive processes underlie the ability to carry out

everyday, practical tasks (Willis & Marsiske, 1991):

memory, speed of processing, and problem-solving

and crystallized abilities. Depressive symptoms may

affect each one of these cognitive domains, although

the extent to which cognitive processes link

simultaneously to depressive symptoms and everyday

functioning has not been clarified by previous

research. In our study, depressive symptoms were

independently associated with memory and problem-

solving ability as well as with functional ability.

However, the association of depression and func-

tional ability was fully accounted for by the relation-

ship of the cognitive variables with depression and

function. In the following sections, we will discuss

each component of the conceptual model we have

employed.

Depressive symptoms and memory

In the past decade, growing attention has been paid

to the question of whether depression in late life

impairs memory functioning. Although it has been

repeatedly shown that subjective memory complaints

are far more common among depressed than among

non-depressed elderly adults (Feehan, Knight &

Partridge, 1991; Scogin, Storandt & Lott, 1985;

Zarit, Cole & Guider, 1981), researchers using more

objective tests have reported inconsistent relation-

ships between depression and memory performance.

Some investigators have failed to find differences in

memory performance between depressed and non-

depressed elders (Neville & Folstein, 1979;

Niederehe, 1986; Rohling & Scogin, 1993), whereas

other investigators have demonstrated depression-

related impairments on various memory tasks

(LaRue, 1989; Pearlson et al., 1989; Raskin, 1986).

However, small sample sizes and treatment of

depression as a dichotomous variable often limit

interpretability of the results (Lichtenberg et al.,

1995).

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The differences noted above may be due, in part,

to differences across studies with regard to which

aspects of memory have been assessed (Backman

& Forsell, 1994). Depression-related deficits in

memory may be more pronounced in tasks involving

little retrieval support (e.g., free recall), whereas

differences between depressed and non-depressed

persons are reduced in tasks requiring high retrieval

support (e.g., recognition). Similarly, depression-

related deficits in memory appear to be most likely to

occur when there are high demands on effortful,

elaborative activities at encoding (Brand, Jolles &

Gispen-de Wied, 1992; Cohen et al., 1982; Hayslip,

Kennelly & Maloy, 1990; Weingartner, 1986;

Weingartner et al., 1981). For example, depressed

persons do not use organizational strategies sponta-

neously, fail to benefit from mental imagery, and

do particularly poorly when long memory lists are

used as study materials. When requirements of self-

initiated cognitive operations are less pronounced,

differences in memory performance between

depressed and non-depressed elderly are negligible.

Impaired attentional processes and motivational

disturbance do not appear to fully explain the

memory function changes reported in depression

(Austin et al., 1992; Richards & Ruff, 1989).

Depressive symptoms and problem-solving andcrystallized abilities

Depression does not appear to affect crystallized

abilities such as vocabulary (Hayslip et al., 1990;

Lyness, Eaton & Schneider, 1994) but does

adversely affect problem-solving abilities such as

reasoning and problem solving. Inductive reasoning

can be assessed through the use of letter, number, or

word series in which the object is to select the next

item in the series. Frontal lobe functions may figure

prominently in performance of novel situations

requiring the use of problem-solving strategies (in

contrast to routine or automatic tasks [Mesulam,

1985; Shallice, 1988]). This ‘novel situation’ func-

tion appears to be impaired in depression (Casseus,

Wolfe & Zola, 1990; Pendleton-Jones, Henderson &

Welch, 1987; Raskin, Friedman & DiMascio, 1982;

Silberman, Weingartner & Post, 1983), indepen-

dently of any effect due to impaired response speed

(Austin et al., 1992). Based on examination of 24

in-patients aged 60 years and older, Beats and

colleagues concluded that depressed patients were

disproportionately affected by initial failure to solve

the problems given (Beats, Sahakian & Levy, 1996).

As in other studies among depressed persons,

visuospatial learning was also impaired (e.g.,

Hayslip et al., 1990), but improved on recovery.

With regard to depression and cognitive impair-

ment, older depressed patients were impaired on

effortful processes, while dementia patients were

impaired on both effortful and automatic tasks

(Roy-Byrne et al., 1986; Weingartner, 1986).

Furthermore, depressed subjects report more fatigue

after effortful tasks than do persons who are not

depressed (Hayslip et al., 1990). In short, reasoning,

problem-solving, and visuospatial skills appear to be

adversely affected by depression and might be an

important link between depression and functional

disability.

Conclusion

Although our conclusions are tempered by limita-

tions, we believe the findings deserve attention in

future studies of how depressive symptoms are

related to functional disability. Given the expected

growth in the number of older persons and the

prevalence of depressive symptoms, cognitive

impairment, and functional limitations among older

adults, understanding the relationship of depression

to functional disability becomes an urgent task.

In this study, the relationship of depressive symp-

toms to the ability to carry out everyday tasks

as measured by standardized performance-based

assessments appeared to be mediated by cognitive

functions such as memory and problem solving.

If the mediation of the association of depressive

symptoms with everyday function by cognitive

abilities were confirmed by further studies, the

finding would have important implications for

prevention of functional disability secondary to

depression because cognitive factors will need to be

considered in the design of interventions. Our

findings call attention to the need for assessing

specific cognitive abilities when evaluating the effect

of interventions focused on depression and the ability

of older adults to care for themselves.

Acknowledgements

This paper was presented at the Gerontological

Soc ie ty o f Amer ica Annua l Meet ing in

Philadelphia, Pennsylvania, November 1998. The

Advanced Cognitive Training for Independent and

Vital Elderly (ACTIVE) Trial was funded by the

National Institute on Aging and the National

Institute for Nursing Research at the National

Institutes of Health. Members of the ACTIVE

Steering Committee include: Karlene Ball,

University of Alabama at Birmingham; Dave Smith

and Frederick Unverzagt, University of Indiana;

George Rebok, Johns Hopkins University; John

Morris, Hebrew Rehabilitation Center for the

Aged, Boston, Massachusetts; Sherry Willis,

Pennsylvania State University; Michael Marsiske,

Wayne State University, now affiliated with the

University of Florida; and Sharon Tennstedt, Data

Coordinating Center at New England Research

Institutes. Project Officers at the time of the pilot

Linking depression and disability 477

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study were Jared Jobe, National Institute on Aging

(NIA) and Mary Leveck, National Institute of

Nursing Research (NINR).

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