Depressive symptoms in the very old living alone: prevalence, incidence and risk factors

Depressive symptoms in the very old living alone:prevalence, incidence and risk factors

Kenneth Wilson1*, Patricia Mottram2 and Andrew Sixsmith2

1Catherine’s Hospital, Birkenhead, Wirrall, UK2University of Liverpool, Liverpool, UK

SUMMARY

Background Living alone is one of many risk factors associated with depression. This project is nested within theENABLE-AGE project designed to explore the relationship between housing environment and health in the very old livingalone in their own homes.Aim Our aim is to describe the prevalence, incidence and associated risk factors of clinically significant depressivesymptoms in this population with particular emphasis on the role of the home environment.Method We conducted a one year follow up of 376 subjects aged between 80 and 90 years old. Data collected includedvariables concerned with housing, social circumstances, physical health and psychological well being.Results A prevalence rate of 21% and an annual incidence of 12.4% (Geriatric Depression Score of five or more) werefound. Risk factors associated with prevalence depression include not living close to friends and family (OR 2.540, CI;1.442, 4.466), poor satisfaction with living accommodation (OR; 0.840, CI; 0.735, 0.961) and poor satisfaction with finances(OR; 0.841, CI; 0.735, 0.961). Subsequent development of clinically significant depressive symptoms was associated withbase line increased scores in depression (OR; 1.68, CI; 1.206, 2.341).Conclusions These results are consistent with findings in the general population of similar age with the exception ofconsiderably higher prevalence and incidence rates. However, we were unable to demonstrate that housing related variableswere significant risk factors in terms of incidence cases.Clinical Implications Older people living alone are particularly vulnerable to depression and may benefit from targetedscreening and development of appropriate care pathways. Copyright # 2006 John Wiley & Sons, Ltd.

key words—depression; very old; community; living alone; housing; incidence; prevalence; risk factors

INTRODUCTION

Beekman et al. (1999) drew attention to the variationin prevalence rates of depression in older people. Anincrease in prevalence with age has been reported byNewman and Engle (1991), with prevalence rates ashigh as 16% being found in octogenarians (Zarit et al.,1999). Forsell et al. (1995) found lower rates of 7.9%(DSM-IV) and 9.1% (ICD-10) in nonagenarians. Riskfactors for depression include handicap, pain, lone-liness (Prince et al., 1998) and accommodation quality(Stewart et al., 2002). As 48% of those aged 75 andolder live alone (National Statistics, 2006), this group

may be of particular risk of experiencing clinicallysignificant depressive symptoms. Our aim is toidentify the prevalence, incidence and associated riskfactors of people aged between 80 and 90 years oldliving alone in their own homes.

METHODS

The project is nested in an international projectdesigned to examine the home environment inrelationship to autonomy, participation and well-beingin the very old (Iwarsson et al., 2004).

Sampling

The Wirral peninsula has a similar demographicprofile to the UK, with 3.8% of the population aged 80

INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY

Int J Geriatr Psychiatry 2007; 22: 361–366.

Published online 17 October 2006 in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/gps.1682

*Correspondence to: Prof. K. Wilson, St Catherine’s Hospital,Derby Road, Birkenhead, Wirral CH42 0LQ, UK.E-mail: [email protected]

Copyright # 2006 John Wiley & Sons, Ltd.Received 5 May 2006

Accepted 1 August 2006

and over. It has a mixed housing profile, characterisedby both deprivation and affluence. Inclusion criteriaincluded; living alone in own domicile (excludingnursing and residential homes and including shelteredaccommodation), being aged between 80 and 90 andbeing able to provide informed consent and participatein the assessments. Subjects were recruited throughlists generated by two Primary Care organisations.Letters were sent to 7,144 Wirral inhabitants agedbetween 80 and 90 and living in their own homes orsheltered accommodation, irrespective of whetherthey lived alone. Subjects were age and genderstratified, enabling recruitment of 200 subjects agedbetween 80 and 84 and 200 aged between 85 and90 years old with 25% of the sample being male.

Assessments/instruments

Each assessment consisted of a battery of interviewer-delivered instruments.Demographic data included; age, gender, marital

status, satisfaction with income, monthly income,subjective evaluation of income (high, average ormedium, as determined by the subject) and level ofeducation.In assessing mental health we used the 15-item

Geriatric Depression Rating Scale (GDS) (Sheikh andYesavage, 1986). An abbreviated version of the MiniMental State Examination (MMSEa) (Eccles et al.,1998) was used to rate cognitive impairment.Housing data included the type of area; urban, semi-

rural, rural, and type of dwelling; apartment, house,sheltered accommodation. The Housing Optionsfor Older People (HOOP) (Heywood et al., 1999)was used to rate satisfaction with current housingconditions. In addition, the Usability of HousingQuestionnaire was used to capture 16 items addressingissues regarding housing utility in terms of activities ofdaily living, socialisation and access. Each item is

graded on a continuum ranging between ‘not usable atall’ to ‘fully usable’ (Fange and Iwarsson, 1999).

Social contact and support were assessed by accessto a confidant, living close to and having frequentcontact with family and friends, having friendlyneighbours, being satisfied with the immediatecommunity area and having ready access to localinformal and statutory health and domestic support.Feelings of loneliness were rated 0–10.

Physical health was assessed using the PhysicalSymptom List (Tibblin et al., 1990). Activities of dailyliving were assessed using the Activities of Daily LivingStaircase (ADL Staircase) (Iwarsson and Isacsson,1997). It rates nine items of activity and data is rankedfor analysis (Iwarsson and Lanke, 2004).

Data analysis

The prevalence rate of clinically significant depressivesymptoms was calculated. All base line variableswere entered into a univariate analysis using STATA.The dichotomous variable GDS score ‘<5/�5’ wasused as the dependent variable. Simple logisticregression was conducted with each of the variables.The model was established and tested using postestimation techniques including sensitivity and speci-ficity and goodness of fit (Hosmer et al., 1988).Incidence was defined as the percentage of subjectsrating less than five at base line and achieving a scoreof five or more one year later. Base line variables wereincorporated into a logistic regression in order toidentify risk factors associated with incidence.

RESULTS

Postal contact generated 516 positive responses and276 negative responses. Of the negative responders;12 refused due to health reasons, 53 felt that the studywould be to intrusive, 129 were not living alone,

Table 1. Description of sample

Aged 80–84 Aged 85–89

245 (65.2%) 131 (34.8%)

Male Female Male Female

76 (20.2%) 169 (45%) 37 (9.8%) 94 (25.0%)

Widowed 66 (86.8%) 149 (88.2%) 33 (89.2%) 85 (90.4%)Never married 4 (5.3%) 13 (7.7%) 1 (2.7%) 1 (7.4%)Divorced 3 (3.9%) 1 (0.6%) 2 (5.4%) 3 (2.1%)Married partner living elsewhere 3 (3.9%) 2 (1.2%) 1 (2.7%) —Living alone but with a close relationship — 4 (2.4%) — —

Copyright # 2006 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2007; 22: 361–366.

DOI: 10.1002/gps

362 k. wilson ET AL.

11 were not interested, eight people were reported asdeceased and 63 gave no reason. Three hundred andseventy six subjects were included within the study(see Table 1).

Seventy eight (21%) of the sample had a GDS scoreof five or more at first assessment (Table 2).

The initial model for risk factors associated withclinically significant depressive symptoms at firstassessment included; not living close to friends andfamily [Odds Ration (OR): 2.540, 95% ConfidenceIntervals (CI); 1.442, 4.466], HOOP score (OR; 0.840,CI; 0.735, 0.961), poor satisfaction with finances (OR

0.841, CI 0.735, 0.961), and the ADL Staircase score(OR; 0.995, CI; 0.992, 0.997). Although significant,the ADL Staircase score was excluded through postestimation techniques to improve the model fit(Table 3).Of the original 376, 316 were followed up,

generating data on 303 subjects (80.6% of the originalsample). Of the 73 subjects for which there was nofollow-up data; 20 died, 13 generated insufficient data,two developed significant cognitive impairment andthe remainder were lost to follow-up through with-drawal of consent and loss of contact. Comparisonbetween the study sample and subjects that droppedout demonstrated that the latter had increased ADLdependency ( p< 0.01). No other differences in base-line variables were found.Of the 303 subjects included in the follow-up, 61

had a GDS score of five or more at first interview(prevalence cases). All these were excluded from theincidence analysis. Of the 61 prevalence cases, 22 hadscores of less than five and 39 had scores of five orgreater at second interview. Of the remaining enteredinto the incidence analysis (242), 30 subjects hadscores of five or more at second interview, generatingan annual incidence of 12.4%. All the variablesidentified at base line were entered into a logistic

Table 2. Prevalence of depression

Not depressed Depressed

GenderMale 95 (84%) 18 (16%)Female 203 (77%) 60 (23%)

EthnicityWhite 297 77Black African 1 0Indian 0 1Age 84.80

(SD 84.50, 85.10)84.91

(SD 84.31, 85.51)Total 298 (79%) 78 (21%)

Table 3. Logistic regression: prevalence related risk factors

Base line variable Odds ratio p-Value 95% Confidence intervals

Demographic/economicAge 1.004 0.927 0.905, 1.114Gender 1.380 0.332 0.720, 2.647Marital status 0.775 0.186 0.532, 1.130Income satisfaction 0.841 0.010* 0.735, 0.961Monthly income 1.000 0.674 0.999, 1.000Level of education 1.000 0.148 0.999, 1.000

HousingType of area 1.093 0.729 0.661, 1.806Type of dwelling 0.927 0.636 0.678, 1.267Usability of housing 0.977 0.574 0.900, 1.060HOOP 0.840 0.000* 0.735, 0.961Satisfaction with area 1.000 0.992 0.996, 1.004

Physical healthADL Staircase 0.995 0.000* 0.992, 0.997Symptom list score 1.001 0.672 0.994, 1.009

Mental healthMMSEa 1.408 0.088 0.950, 2.085

Social aspectsLiving far from family 2.540 0.001* 1.442, 4.466Helpful neighbours 1.009 0.414 0.986, 1.033Access to confidant 0.986 0.220 0.964, 1.008Social exclusion 0.990 0.371 0.969, 1.011Visitor access 0.932 0.323 0.912, 1.071Feeling lonely 1.008 0.488 0.985, 1.031Access to social and domestic care 0.773 0.387 0.432, 1.385

*significant at p< 0.05.


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depressive symptoms in the very old living alone 363

regression. The base-line GDS score (<5) was theonly significant risk factor for incidence clinicallysignificant depressive symptoms (OR; 1.68, CI; 1.206,2.341).

DISCUSSION

The base-line interviews generated a prevalence ofclinically significant depressive symptoms of 21%.Increased risk was associated with low financialsatisfaction, not living close to friends and family andlow housing satisfaction. An annual incidence of12.4% was found. Higher sub-clinical GDS scores (0–4) was associated with subsequent development ofclinically significant depressive symptoms.

STUDY LIMITATIONS

The study was not designed as an epidemiologicalstudy. This is reflected in the sampling techniquewhich does not attempt to provide a representativesample of the very old living alone. Consequently acautious interpretation must be placed in generalisingthe findings.In using an abbreviated form of the MMSE we were

unable to describe the cognitive profile of the sample.Through having to gain written consent and excludingsubjects unable to fully participate in interviews andthose in institutions, it is likely that the sample isskewed towards the cognitively unimpaired. This mayexplain why, contrary to other findings (Vinkers et al.,2004) base line cognitive impairment was not found tobe a risk factor for depression.The validity of the GDS as a case finding instrument

has been criticised (Arthur et al., 1999). Mostdiagnostic instruments demand a degree of stabilityof symptoms across time, in the absence of this it islikely that individuals will fluctuate between ‘case’and ‘non case’. This may be reflected in these data inthat 36% of prevalence cases scored less than five atsecond assessment. However, depressive symptomsare associated with significant morbidity in their ownright (Gallo et al., 1970) and the instrument hasrecognised validity in terms of screening fordepression in this age group (D’Arth et al., 1994;Osborn et al., 2002). A variety of cut-off scores havebeen used (Osborn et al., 2002). A cut-off of five andabove was used in this study as it has been validatedagainst other rating scales (Herrmann et al., 1996) andhas been used in studies of populations of similar ages,enabling comparison.

PREVALENCE AND INCIDENCE

Osborn and colleague’s (2002) large study of subjectsaged 75 and older used a cut-off of 5/5þ and founda prevalence of 13.1%. Stek et al. (2004) founda prevalence of 15.4%, using the same GDS cut-offin a Dutch population (aged 85 and over). Over half ofthis population lived alone. A prevalence of 26% hasbeen found by Bergdahl et al. (2005) in Swedishpeople aged 85 and over, living in residential care,nursing homes and in their own homes. In comparisonto our study sample Bergdahl’s sample is likely tohave much higher dependency levels and cognitiveimpairment. Stek and colleagues (2006) follow-upstudy is the only incidence study conducted on asimilar age group, using the same cut-off score on theGDS. They found an incidence of 6.8% which isrelatively low compared to the 12.4% found in thisstudy. The difference may reflect differing samplecharacteristics. The Wirral sample was confined tosubjects living alone, 88% were widowed and only11% identified as having a high income. In Stek’sstudy 58% were living alone, 55% of the sample waswidowed and 35% described as having high levels ofincome. Living alone, widowhood and poverty arerecognised risk factors for depression.

RISK FACTORS

We found prevalence depressive symptoms correlatedwith dissatisfaction with housing, poor satisfactionwith income and not living close to family and friends.The finding of dissatisfaction with housing isconsistent with the findings of Stewart et al. (2002).The association between depression and dissatisfac-tion with income in older community residents reflectsfindings of other studies (Wilson et al., 1999). Ourfinal model did not include ADL scores as have beenfound in other studies (Stek et al., 2004). Thisprobably reflects the nature of the Wirral sampleconsisting of subjects living alone (and likely to berelatively independent) and the exclusion of institu-tionalised subjects (and more dependent). Likewise,we did not find an association with loneliness in thissample. Subjects with clinically significant depressivesymptoms rated them selves more lonely compared towell subjects, however the variable did not reachsignificance. We did demonstrate the importance ofliving close to family and friends. This may reflect therelative importance of family contact for people livingalone, usually widowed or bereaved.

Stek et al. (2006) found that poor daily functioningand institutionalisation were risk factors for incidence


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depression. The lack of this finding in our study is notsurprising in view of the sample characteristics and thedisproportionate loss of the more dependent fromfollow-up (in terms of activities of daily living). Themain finding that base-line GDS score (less than 5)was associated with subsequent clinically significantdepressive symptoms has been described in similarstudies (Stek et al., 2006) and from a clinicalperspective has some important implications.

CLINICAL IMPLICATIONS

Our findings are consistent with other studiessuggesting that living alone is associated with higherlevels of depression (Livingston et al., 1990). Ourstudy also draws attention the importance of thehousing environment, social contacts and economicwelfare and depression in older people. It is evidentthat people with minor or few symptoms are likely toget worse. Relatively few older people with depressionare identified and receive treatment (Crawford et al.,1998). Effective interventions have been describedand primary care organisations are encouraged toundertake early intervention (NICE, 2004). Ourfindings indicate that the very old, living aloneconstitute an easily recognised, relatively small, high-risk group which may well benefit from a targetedscreening programme.

ACKNOWLEDGEMENTS

Sponsored by the European Commission (QLRT-2001-00334).

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KEY POINTS

� Older people living alone are at high risk ofsuffering from clinically significant depressivesymptoms.

� Living far from family and friends, dissatisfac-tion with income and housing are associatedwith depression.

� Mild depressive symptoms are a risk factor forsubsequent increased severity.


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depressive symptoms in the very old living alone 365

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Depressive symptoms in the very old living alone: prevalence, incidence and risk factors

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