y 29 (2007) 340–348

General Hospital Psychiatr

Major depression in older medical inpatients predicts poor physical andmental health status over 12 months☆

Jane McCusker, M.D., Dr.P.H.a,b,⁎, Martin Cole, M.D., F.R.C.P.(C)c,d, Antonio Ciampi, Ph.D.b,Eric Latimer, Ph.D.d,e, Sylvia Windholz, M.D., C.C.F.P.f, Eric Belzile, M.Sc.a

aDepartment of Clinical Epidemiology and Community Studies, St. Mary's Hospital, Montreal (Quebec), Canada H3T 1M5bDepartment of Epidemiology and Biostatistics, McGill University, Montreal (Quebec), Canada H3T 1M5

cDepartment of Psychiatry, St. Mary's Hospital, Montreal, Montreal (Quebec), Canada H3T 1M5dDepartment of Psychiatry, McGill University, Montreal (Quebec), Canada H3T 1M5eDouglas Hospital Research Centre, Montreal, Montreal (Quebec), Canada H3T 1M5

fDivision of Geriatric Medicine, Department of Family Medicine, Sir Mortimer B. Davis Jewish General Hospital, and McGill University, Montreal (Quebec),Canada H3T 1M5

Received 24 January 2007; accepted 22 March 2007

Abstract

Objective: The aim of this study was to determine the 12-month effects upon physical and mental health status of a diagnosis of major orminor depression among older medical inpatients.Methods: Patients 65 years and older, admitted to the medical wards of two university-affiliated hospitals, with at most mild cognitiveimpairment, were screened for major and minor depression (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria).All depressed patients and a random sample of nondepressed patients were invited to participate. The physical functioning and mental healthsubscales of the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) were measured at baseline and at 3, 6 and 12 months.Results: Two hundred ten patients completed the SF-36 at baseline and at one or more follow-ups. In multiple linear regression analysis forlongitudinal data, adjusting for baseline level of the SF-36 subscale outcome, severity of physical illness, premorbid disability, age, sex andother covariates, patients with major depression at baseline had lower SF-36 scores at follow-up, in comparison to patients with no depression[physical health, 9.22 (95% CI −15.52 to −2.93); mental health, 6.28 (95% CI −11.76 to −0.79)].Conclusion: A diagnosis of major depression in cognitively intact older medical inpatients is associated with sustained poor physical andmental health status over the following 12 months.© 2007 Elsevier Inc. All rights reserved.

Keywords: Aged; Depression; Health status; Longitudinal study

1. Introduction

Despite its frequent occurrence [1] and poor prognosis[2], major depression in older medical inpatients is usuallynot detected or treated [3,4]. In part, this failure to detect

☆ This study was funded by Canadian Institutes for Health Research,Grants MOP82494 and MCT-15476.

⁎ Corresponding author. Department of Clinical Epidemiology andCommunity Studies, St. Mary's Hospital, 3830 Lacombe, Montreal(Quebec), Canada H3T 1M5. Tel.: +1 514 345 3511x5060; fax: +1 514734 2652.

E-mail address: jane.mccusker@mcgill.ca (J. McCusker).

0163–8343/$ – see front matter © 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.genhosppsych.2007.03.007

and treat may reflect lack of clear knowledge aboutwhether a diagnosis of depression in this population affectspatients' long-term physical and mental health outcomes,independently of severity of physical illness and otherfactors. To date, most studies in hospitalized samples haveused an outcome measure of physical disability [e.g.,dependence in activities of daily living (ADL)] [5–7]. Useof a generic health status measure such as the MedicalOutcomes Study 36-Item Short Form Health Survey (SF-36) is a useful means of assessing the impact of a healthproblem on different dimensions of health status [8] andcomparing this impact with population norms [9].Although the SF-36 appears to perform well as a tool

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for monitoring the effect of outpatient treatment ofdepression on mental health outcomes [10], only onestudy to our knowledge has investigated the use of ageneric health status measure among depressed olderhospitalized patients [11]. This study was limited by ashort (1 month) follow-up period, and the outcomes werenot adjusted for comorbidity. Thus, the primary objectiveof this study was to determine the impact of major orminor depression on a generic health status measure, theSF-36, during the 12 months after admission, independentof baseline physical disability, comorbidity and otherconfounding variables. There is some evidence fromcommunity but not from inpatient samples that socialnetwork and support can buffer the negative effects of latelife depression [12,13]. Therefore, a secondary objectivewas to determine whether the patient's social network orsupport modified the effects of depression diagnosis on thehealth status outcomes. Because we have reportedseparately on the effects of depression diagnosis onsurvival [14], patients who died during follow-up havebeen excluded from this study.

2. Methods

2.1. Study design

The study was an observational, prospective study of acohort of older medical inpatients, with oversampling ofpatients with a diagnosis of major or minor depression.Recruitment methods have been described in detailpreviously [1]. The study was conducted at two uni-versity-affiliated acute care Montreal hospitals, usingrandom sampling from lists of consecutive, nonelectiveadmissions of patients 65 years and older to the medicalservices (we focused on these admissions because of ourinterest in outcomes of depression in acutely medically illpatients.) The following were excluded: patients admittedto palliative care (because of expected survival of less than6 weeks); those who did not speak or understand Englishor French or were otherwise unable to communicate; thosewho lived off the island of Montreal (due to difficulty offollow-up) and those admitted to the intensive care orcardiac monitoring units. Eligible patients were screenedusing the Short Portable Mental Status Questionnaire(SPMSQ) [15]; those with five or more errors (indicatingmoderate-severe cognitive impairment) [16] were excludedbecause the presence of such cognitive impairmentcomplicates diagnosis and measurement of depression.Major and minor depression were diagnosed using theDiagnostic Interview Schedule (DIS) using Diagnostic andStatistical Manual of Mental Disorders, Fourth Edition(DSM-IV) criteria [17]. All depressed patients and arandom sample of nondepressed patients were invited toparticipate in the longitudinal component of the study. Atone of the hospitals, patients with major depression wereinvited to participate in a concurrent randomized controlled

trial (RCT) that compared systematic detection and multi-disciplinary management with usual care [18]. Because theintervention did not affect any of the outcomes at 6 or 12months (including physical and mental health status),patients who participated in the RCT have been includedin this analysis.

The study protocol was approved by the research ethicscommittees of both hospitals. Patients with severe depres-sion (clinical criteria) were referred to a specialist in geriatricpsychiatry (M.C.) or a geriatrician (S.W.).

2.2. Data collection

Data were collected at the two hospitals using the sameresearch staff and methods. Research assistants were blindto the patients' initial depression diagnosis. Patients wereinterviewed at baseline (as soon as possible after enroll-ment) and at 3, 6 and 12 months after enrollment. Otherdata sources included (1) review of patient medical charts;(2) abstraction of administrative databases at the twohospitals and (3) provincial hospital discharge, physicianbilling and prescription databases (all patients are coveredby government health insurance for these services).

2.3. Measures

2.3.1. DepressionThe depressive disorders section of the DIS [17] was

administered at the baseline research interview and at eachfollow-up. Patients were classified as having current (atleast 2 weeks duration of symptoms) major, minor or nodepression with DSM-IV criteria using the “inclusive”approach (symptoms counted towards the diagnosisregardless of the symptoms' origins, whether physicalillness or depression) [19]. The interrater reliability of theDIS was assessed in a convenience sample of 28 patientsat intervals throughout the study period, using independentsimultaneous ratings by two or more raters, including thestudy psychiatrist (M.C.). Values of the kappa coefficientwere .78 (95% CI 0.52–1.00) for a diagnosis of majordepression vs. minor or no depression and .61 (95%CI 0.35–0.87) for a diagnosis of either major or minor vs.no depression.

2.3.2. Health statusThe SF-36 was administered at all study baseline and

follow-up interviews [8]. This widely used measure hasdemonstrated validity, internal consistency and retestreliability [20,21] and also performs well in depressedelderly [10]. Two summary measures, the Mental andPhysical Component Summary Scales, and eight specificsubscales can be computed. To avoid any “contamination”of physical health status by mental health status (and viceversa) [22], we used the physical and mental healthsubscales instead of the summary scales (which use itemsfrom both domains). Preliminary analyses of the eightSF-36 subscales at baseline found a correlation of 0.37between the physical function and mental health subscales.

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The other six subscales had higher correlations with one orboth of the physical or mental subscales (data not shown)and were not analyzed further. The correlations betweenthe physical function and mental health subscales at eachfollow-up were similar to the baseline correlation, and thecorrelations between the change scores at any twoconsecutive time points were even lower (0.15–0.24).Thus, these two subscales measure two largely indepen-dent aspects of health status in this sample.

2.3.3. History of depressionA history of depression at enrollment was defined as

either a positive response to a question as to whether thepatient had ever been told by a doctor that they weredepressed, or a diagnosis of depression in the hospital chartduring the 2 years before admission.

2.3.4. Antidepressant treatmentAntidepressant medication prescriptions were abstracted

from the prescription database for the period from 60 daysbefore admission to the patient's last follow-up interview.

2.3.5. Cognitive impairmentThe Mini-Mental State Examination (MMSE) was

administered at baseline and all follow-up interviews [23];scores range from 30 (no impairment) to 0 (maximumimpairment).

2.3.6. Premorbid disabilityPremorbid ADL disability (2 weeks before admission)

was measured by self-report, using 14 items on a 3-pointscale (completely independent, partially dependent andcompletely dependent) [24]. Patients with partial orcomplete dependence were considered disabled. Becausealmost all patients had some premorbid instrumentalADL disability, patients were classified into those withand without premorbid disability in basic (physical) ADL.

2.3.7. Medical illness at enrollmentFour measures of medical illness were used. First, the

Charlson Comorbidity Index was derived from chartreview of diagnoses during the two years before enroll-ment [25]. Second, clinical severity of the medical illnesswas assessed at enrollment based on a global clinicalimpression on a scale ranging from 1 (not ill) to 9(moribund) [26]. Third, the Acute Physiology Score (APS)derived from the Acute Physiology and Chronic HealthEvaluation II was coded from the computerized laboratorytest results and hospital chart data [27]. Fourth, the primarydischarge diagnosis was abstracted from hospital adminis-trative databases.

2.3.8. Social networks and supportSocial network and support questions administered at

baseline and each follow-up interview included theperceived adequacy of emotional and tangible support (inthe last month, could you have used more emotionalsupport — or help with daily tasks — than you received?),

presence of a confidant (person you feel close and intimatewith, share confidences with, can depend on); the numberof children seen at least once a month, and the number ofother relatives and friends seen at least once a month [28].Bereavement was measured by a question about the deathof someone close during the past year.

2.3.9. Sociodemographic and other variablesAge, sex, years of education, marital status and liv-

ing arrangement (alone or with others) were measuredat enrollment.

2.4. Statistical methods

The sample used for these analyses comprised enrolledpatients with a baseline research interview and at leastone follow-up interview at which both the SF-36subscales were completed (more than 90% of the samplecompleted at least two of the follow-ups). We comparedthe baseline characteristics of the sample with two groupsof excluded patients — those who died during the follow-up and those who were lost to follow-up for reasons otherthan death.

Data were analyzed using the linear mixed model [29];several correlation structures were examined and one wasselected (compound symmetry) since it minimizes valuesof both the Akaike Information Criterion and theBayesian Information Criterion. Two longitudinal out-comes were modeled separately: physical function andmental health as assessed by the SF-36 at 3, 6 and 12months. The main independent variables of interest weredepression (diagnosis and history) and social support, allmeasured at baseline. The potential confounders (alsomeasured at baseline) include those described in Table 1.In the initial univariate models for each independentvariable and confounder, the baseline score of theoutcome and the time variable were included ascovariates. Since the ratio of the sample size to thenumber of covariates was small (<8), we excluded fromthe final multivariate models those confounders withsmall absolute t values (<1). We tested interactionsbetween depression diagnosis and follow-up time, depres-sion diagnosis and history of depression and depressiondiagnosis and the social support variables. Antidepressantmedication prescriptions at baseline and at follow-up wereadded to the final multivariate models, and interactionsbetween medications and depression diagnosis weretested. Finally, a model with depression diagnosis astime-dependent covariate was fitted for both outcomes.Due to the relatively small number of tests we areinterested in (effects of depression and social network ondepression), we have not adjusted for multiple compar-isons. Overall, 66% had complete data at the threefollow-up times (3, 6 and 12 months); 25% had completedata at two follow-up times, and 9% had data at onefollow-up time only. Missing data were imputed using thelinear mixed model estimated on the available data. All

Table 1Baseline characteristics of study sample (n=210)

Variables n Mean (S.D.) %

SociodemographicAge 210 79.0 (7.3)Female 210 65.2Living at home alone 206 46.1Education (years) 2101–6 9.57–12 39.1>12 51.4

DepressionCurrent diagnosis 210Major depression 43.3Minor depression 16.2No depression 40.5History of depression 210 27.1Use of antidepressant: at baseline 210 22.4During follow-up 210 34.8

Physical healthPrimary discharge diagnosis 209Circulatory 30.6Respiratory 18.7Mental and nervous disorders 6.7Symptoms and signs 11.5Neoplasms 3.4Others 29.5Premorbid disability 207 63.8Acute Physiology Score (range, 0–11) 208 2.5 (2.3)Comorbidity (range, 0–8) 209 1.4 (1.5)Clinical severity (range, 1–7) 202 3.7 (1.0)Mini-Mental State Examination 204<24 27.4<19 4.4

Social networks/supportConfidant 210 77.6Bereavement 207 41.1Adequacy of tangible support a 210 3.4 (1.0)Adequacy of emotional support a 204 3.5 (1.0)No. of children seen every month 209 1.1 (1.4)No. of close friends/relatives seen every month b 208 2.5 (2.6)

a Could have used: a lot more (1), some more (2), a little more (3) and nomore (4) help.

b 5=5–10 and 10=≥10.

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the analyses were conducted with SAS software, Cary,NC, USA (version 9.1).

3. Results

A total of 1718 patients met study eligibility criteria,and 1686 (98.0%) of these consented to depressionscreening (Fig. 1). The prevalence of depression (majoror minor) was 27.9% (471/1686) at screening. Studyparticipation rates were 73.0% (344/471) among patientswith a depression diagnosis and 72.7% (186/256) in thesample of nondepressed patients invited to participate.Subsequently, 210 patients completed the baseline researchinterview and at least one follow-up, 145 patients died andthe remainder (n=175) failed to complete either the

baseline or any follow-up (including 20 patients whowere interviewed but did not complete the SF-36subscales). Most of this attrition took place betweenscreening and the baseline research interview, reflectingdifficulties in recontacting patients during their hospitalstay. There were, however, no significant differencesbetween the sample of 210 and the patients who wereexcluded for reasons other than death (n=175) in thescreening diagnosis of depression, history of depression,SPMSQ score, age, sex or the chart-based measures ofphysical illness. In contrast, those who died weresignificantly more acutely ill and had higher comorbidityat baseline (data not shown). The baseline characteristics ofthe sample of analysis (n=210) are shown in Table 1.

Fig. 2 shows the mean physical functioning SF-36subscale scores (and 95% confidence intervals) at baselineand follow-up by depression diagnosis. Patients in all threegroups had scores that remained significantly below theCanadian norms for these scales for comparable age groups[9]. However, a gradient in the scores was observed with thelowest scores among patients with major depression,followed by those with minor depression.

Fig. 3 shows the same results for the mental healthsubscale. Patients with major depression had scores thatremained substantially below the norms, patients with minordepression had scores approaching the norms, while thosewith no depression had scores similar to the norms.

Table 2 shows the univariate and multivariate regressionmodels (the covariates dropped from the multivariate modelsare those shown in the univariate but not the multivariatemodels shown in the table). The coefficient of a variablerepresents its population average effect on the SF-36 scoreover follow-up period (3–12 months). For example, formodel B (physical function) patients with major depressionhad a follow-up score that was on average 9.2 points lessthan patients without depression. In comparison withpatients with no depression diagnosis, those with majordepression had significantly lower scores on both subscalesat follow-up, even after adjustment for all covariates. Therewas no clinically or statistically significant effect of minordepression on either score. In multivariate analyses, othernotable predictors of worse physical health status scoresincluded less than 7 years of education, premorbid disabilityand presence of a confidant. Compared with the referencegroup of patients with “other” (miscellaneous) dischargediagnoses, a diagnosis of a respiratory, mental or nervousdisorder was associated with a better physical function scoreat follow-up. Premorbid basic ADL disability and a lowerCharlson comorbidity score predicted a worse mental healthscore at follow-up in multivariate analyses.

In secondary analyses, we added depression diagnosisto the final multivariate model as time-dependent variables.The results differed for physical and mental health scales(data not shown). For physical health, the effect of majordepression at baseline remained strong (−8.02, 96% CI−14.45 to −1.60), while diagnosis at follow-up was less

Fig. 1. Enrollment flow chart.

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strong (−3.71, 95% CI −7.77 to 0.35). In contrast, themeasures of major depression at follow-up had a strongeffect on mental health (−14.35, 95% CI −18.18 to−10.52) while the effect of the baseline diagnosis wasmuch weaker (−.53, 95% CI −7.56 to 2.50). Minordepression at follow-up did not predict physical or mentalhealth status.

Interactions between depression diagnosis and the socialnetwork/support variables were tested in the final multi-variate models shown in Table 2. There were significantinteractions only with the number of children seen everymonth (data not shown). Among patients with minordepression, both scores at follow-up improved with anincreased number of children visiting (P=.002 for physical

Fig. 2. Crude physical functioning scores over time (mean and 95% CI) by depression diagnosis.

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function, P=.009 for mental health). Among patients withmajor depression, the mental health score at follow-up (butnot the physical function score) was lower for those withmore children visiting (P=.007).

Finally, we added measures of antidepressant use atbaseline and at follow-up to the final models (data notshown). Antidepressant use at baseline had a small negativeeffect upon mental health (but not physical health) at follow-up [−4.89 (95% CI −10.47 to 0.69)], with minimal changesin estimates of other variables in the model. Antidepressantuse during the follow-up had no effect upon either mentalhealth or physical health outcomes. There were nosignificant interactions between antidepressant use anddepression diagnoses.

4. Interpretation

This observational 12-month prospective study found thatmajor depression in a sample of older medical inpatients isan important independent predictor of poorer physical andmental health status after discharge, even after adjustment forbaseline disability, the nature and severity of physical illness

and other patient characteristics. Neither minor depressionnor a history of depression predicted physical or mentalhealth status scores at follow-up, either in univariate ormultivariate analyses.

The results of this study contribute to the literature inseveral ways. This is the first study of older medicalinpatients with follow-up to 12 months to investigate theeffect of depression diagnoses on both physical and mentalaspects of health status measured with a widely usedgeneric health status instrument. The results indicate that,even in a medically ill population, a diagnosis of majordepression has a sustained, independent effect on bothphysical and mental health outcomes. However, there areimportant differences in the way major depression affectsthe two different outcomes. First, the mental health statusscale (measuring a construct similar to that of depression)was strongly related to the diagnosis of major depressionat the same point in time. This supports the use of thisshort (four-item) scale for the monitoring of treatment inmajor depression, as suggested previously [10]. Second,major depression at baseline predicted mental health statusat follow-up, indicating the persistent nature of majordepression in this population [30]. In contrast, the effect

Table 2Longitudinal multiple regression models a of baseline predictors of mental and physical subscales over 12 months

Predictor Physical function Mental health

A b B c (n=202) A b B c (n=205)

Estimate 95% CI Estimate 95% CI Estimate 95% CI Estimate 95% CI

Baseline score of outcome 0.65 ⁎⁎ 0.56–0.75 0.54 ⁎⁎ 0.43–0.65 0.49 ⁎⁎ 0.41–0.57 0.37 ⁎⁎ 0.28–0.47Follow-up time (months) −0.34 ⁎ −0.68 to 0.01 −0.35 ⁎ −0.68 to −0.02 −0.08 −0.43 to 0.28 −0.10 −0.45 to 0.26DepressionCurrent diagnosisMajor depression (vs. no) −5.51 −11.68 0.67 −9.22 ⁎⁎ −15.52 to −2.93 −8.29 ⁎⁎ −13.69 to −2.88 −6.28 ⁎ −11.76 to −0.79Minor depression (vs. no) −2.37 −10.33 to 5.61 −3.94 −11.56 to 3.68 −2.85 −9.35 to 3.65 −1.76 −8.16 to 4.63History of depression 2.50 −3.75 to 8.75 2.96 −3.32 to 9.23 −4.72 −9.80 to 0.36 −3.06 −8.15 to 2.04

DemographicAge −0.47 ⁎ −0.84 to −0.10 −0.26 −0.63 to 0.10 −0.20 −0.49 to 0.09 −0.17 −0.46 to 0.12Female (vs. male) −5.84 ⁎ −11.68 to −0.01 −4.20 −9.93 to 1.54 −4.02 −8.41 to 0.37 −1.93 −6.37 to 2.50<7 years education (vs. ≥7) −9.70 ⁎ −18.89 to −0.51 −11.56 ⁎ −20.32 to −2.80 −4.28 −11.58 to 3.01 −3.68 −10.73 to 3.37Living at home alone 3.84 −1.63 to 9.31 −0.27 −4.62 to 3.96

General healthPrimary discharge diagnosisCirculatory (vs. others) 1.67 −5.23 to 8.56 2.89 −3.60 to 9.37 1.78 −3.66 to 7.21Respiratory (vs. others) 8.01 −0.35 to 16.37 8.57 ⁎ 0.73–16.41 0.07 −6.36 to 6.50Mental and nervous disorders(vs. others)

10.46 −0.86 to 21.78 11.54 ⁎ 0.51–22.57 −1.74 −10.70 to 7.21

Symptoms and signs (vs. others) 6.88 −2.50 to 16.26 9.60 ⁎ 0.77–18.43 −2.23 −9.72 to 5.27Neoplasms (vs. others) −0.37 −15.85 to 15.10 1.09 −13.59 to 15.78 4.79 −7.40 to 16.99Comorbidity (continuous) −0.96 −2.72 to 0.81 −1.35 −3.06 to 0.35 1.72 ⁎ 0.36–3.07 1.52 ⁎ 0.18–2.86Clinical severity (continuous) −1.18 −3.97 to 1.61 0.78 −1.38 to 2.93APS (continuous) −1.12 −2.28 to 0.04 0.33 −0.57 to 1.22MMSE <24 −2.97 −9.14 to 3.21 0.01 −4.78 to 4.80Premorbid disability −13.07 ⁎⁎ −19.39 to −6.74 −10.58 ⁎⁎ −16.90 to −4.25 −6.90 ⁎⁎ −11.36 to −2.45 −5.43 ⁎ −10.02 to −0.84

Social networks/supportBereavement −2.73 −8.33 to 2.87 −1.92 −6.12 to 2.28Confidant (vs. none) −7.54 ⁎ −13.97 to −1.11 −6.34 ⁎ −12.66 to −0.02 2.08 −2.99 to 7.15Adequacy of tangible support −0.93 −3.61 to 1.75 −1.51 −4.13 to 1.11 1.55 −0.55 to 3.64 1.15 −0.93 to 3.22Adequacy of emotional support −1.20 −3.93 to 1.53 1.08 −1.09 to 3.26No. of friends visiting monthly(continuous)

−0.51 −1.64 to 0.62 −0.59 −1.68 to 0.49 0.35 −0.52 to 1.22

No. of children visiting monthly(continuous)

1.74 −0.23 to 3.71 2.23 ⁎ 0.30 to 4.15 −0.58 −2.04 to 0.89 −0.54 −1.97 to 0.88

a Mixed linear model with correlation structure (compound symmetry).b Model for each predictor variable, adjusted with time and baseline outcome score (sample sizes given in Table 1).c Final multivariate model.⁎ P<.05.⁎⁎ P<.01.

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of major depression at baseline on physical health statusat follow-up was stronger than that of a diagnosis made atfollow-up. In this population, patients with majordepression at hospital admission had the worst physicalhealth (compared to those with minor or no depression),and their health did not improve at follow-up (Fig. 1).Analysis of survival during follow-up in this same cohortfound that, after adjustment for physical health and othercovariates at hospital admission, patients with majordepression did not have worse survival [14]. Thus, themain independent health impact of a diagnosis of majordepression in older medical inpatients appears to be onmorbidity rather than mortality.

Visits from children appeared to reduce the negativeeffects of minor depression on both physical and mental

aspects of health status, as expected. In contrast, patientswith major depression who reported more visits fromchildren experienced worse physical health status atfollow-up; visits by children among these more severelydepressed patients may be a marker of greater need.

The study has four main limitations. First, the mostseverely physically ill patients, those with moderate orsevere cognitive impairment and patients who died duringfollow-up were excluded, so the study results are notgeneralizable to these groups of patients. Second, there wasrelatively high attrition (particularly between screening andthe baseline interview, due to difficulties in recontactingpatients during their hospital stay). However, the baselinecharacteristics of patients in the study sample (n=210) weresimilar to those of patients who failed to complete both the

Fig. 3. Crude mental health scores over time (mean and 95% CI) by depression diagnosis.

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baseline and at least one follow-up interview for reasonsother than death (n=175). Third, the relatively small sampleof patients with minor depression reduced the power of thestudy to detect effects of this diagnosis on the outcome.Fourth, our measures of antidepressant use were crude; dataon the duration and dosages of antidepressants and oncompliance are needed to evaluate whether use of thesemedications has an impact on health status.

We conclude that, among older medical inpatients,major depression has a sustained negative effect on bothphysical and mental dimensions of health status, indepen-dent of the negative effects of physical health, premorbiddisability and other covariates. These results underline theneed for effective interventions for major depression inolder medical inpatients. Major depression in older adultscan respond to antidepressant and psychological treat-ments [31] and to disease management programs inprimary care settings [32,33]. However, efforts to detectand treat major depression systematically in older medicalinpatients have had disappointing results, in part becauseof high rates of patient attrition and poor adherence [18].

Interventions that include patient and family education andthat link patients to community-based management maybe more effective.

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