British Journal of Psychiatry (1994), 165 (suppl. 26), 16-22

Lifetime Risk of DepressionHANS-ULRICH WITTCHEN, BARBEL KNAuPER and RONALD C. KESSLER

Over the past decade, major epidemiological studies have been conducted to determine theprevalence of depressive syndromes, primarily major depression or dysthymia. The highestprevalences occur in younger cohorts (18-29 years); considerably lower prevalences are foundin older individuals (45 years and above), with the lowest in those aged 65 and older. Severalstudies have confirmed an increase in the cumulative lifetime estimates of major depressionin successively younger birth cohorts during this century. At the same time, questions havebeen raised about the low prevalence of depression in the elderly, including the role ofconfounding factors (e.g. differential morbidity and response-biased memory). Standardiseddiagnostic assessment procedures may be insufficiently adapted for use in the elderly. It hasalso been recognised that a substantial number of elderly individuals suffer from clinicallyrelevant symptoms of depression but do not meet the criteria for major depression. Futureresearch will be required to elucidate fully the apparently changing rates of depression.

The ideal basis for evaluating depression across thelife-cycle would be a prospective, long-term,epidemiological study in which different successiveage-cohort samples of the general population arefollowed for many years, taking into account themany variables that might affect onset andrecurrence of depressive disorders during a lifetime.Potential precipitating factors include external(social, cultural, and environmental) changes, butalso many psychological, or internal, changes (self­perception, goals, aspirations, cognitive functions,experiences, and emotions). Furthermore, externaland internal factors are closely interrelated withbiological variations across the life-cycle, includingchanges in the central and autonomic nervoussystems, development of biological dysfunctions andillnesses, regeneration capacity, and physical fitness(Wittchen, 1988).

Because complex studies that take these variationsinto account are not feasible, conclusions about theprevalence of depressive disorders are based on apatchwork of less perfect studies, ranging fromanecdotal to retrospective or, less frequently,prospective, epidemiological studies. Several criticalmethodological issues make a review of the currentknowledge about depression across the life cycledifficult. These include interstudy differences withregard to sampling, age group composition,diagnostic criteria, diagnostic assessment procedures,and different historical time frames covered. All ofthese issues affect the reported lifetime prevalenceestimates. Studies also vary considerably with regardto the level of detail in which the depressivesymptomatology, subtypes of the depressivedisorder, and associated features are investigated.

16

With these concerns in mind, this paper focuseson the prevalence of depressive disorders, withspecific emphasis on the variability of findingsbetween studies, empirical support for age-cohorteffects, and deficits in our current knowledge aboutdepressive disorders across the life span.

Prevalence of depressive disorders

Since the landmark review of epidemiological studiesconducted by Boyd & Weissman (1982), a numberof major epidemiological studies have been carriedout in representative samples of the generalpopulation using various diagnostic criteria andinstruments (e.g. Diagnostic Interview Schedule(DIS), Composite International Diagnostic Interview(CIDI» (Blazer & Williams, 1980; Weissman et 01,1985;Henderson, 1986;Lewinsohn et 01,1986; Blandet 01, 1988; Parmelee et 01, 1989; Burke et 01, 1991;Robins & Reiger, 1991; Angst, 1992; Katona, 1992;Romanoski et 01, 1992;Turrina et 01, 1992; Wittchenet 01, 1992; Henderson et 01, 1993; Kessler et 01,19940).

Since 1980, 20 studies have been identified inwhich the Research Diagnostic Criteria (RDC),DSM-III or DSM-III-R (American PsychiatricAssociation, 1980, 1987), or the ICD-I0 (WorldHealth Organization, 1992) criteria were used toreport on the estimates of major depression,dysthymia and other affective disorders (Table 1).Although there was some variation, the point­prevalence of major depression was approximately3070 (i.e. 3070 of the adult population suffered frommajor depression at the time of the study interview).Similarly, the reported 6-month to l-year prevalence

LIFETIME RISK OF DEPRESSION 17

Table 1Point, six-month to one-year, and lifetime prevalence rates of depressive disorder reported in epidemiological surveys

conducted since 1980 (see text for references)

Disorder

Point

Median % (range)

Six-month to one-year Lifetime

Major depression/major depressive episodeDysthymiaRecurrent brief depressionBipolar disorder

3.1 (1.5-4.9)2.1 (1.2-3.9)

0.9 (0.1-2.3)

6.5 (2.6-9.8)3.3 (2.3-4.6)- (4.2-7.2)1.1 (1.0-1.7)

16.1 (4.4-18)3.6 (3.1-3.9)

11.11.3 (0.6-3.3)

of major depression varied somewhat (range2.6-9.8070), but was approximately 6070. Lifetimeprevalence estimates across all studies show the mostvariation, but the majority of recent studies citeprevalences of 15-18070. However, in the five-siteEpidemiologic Catchment Area (ECA) studyconducted in the US, the lowest prevalence estimatesfor all time-frames were reported (e.g. lifetimeprevalence of 3.0-5.9070: Robins & Regier, 1991).

The highest prevalence estimates have resultedfrom studies conducted in the late 1980s or early199Os. For instance, in the Zurich cohort, the lifetimeprevalence of major depression was estimated to beapproximately 16-20070 (Angst & Dobler-Mikola,1985), a prevalence of 15.7070 was reported in arepresentative sample of the Basel population(Wacker et al, 1992), and Kessler et al (1994a), inthe National Comorbidity Survey, reported a lifetimeprevalence of 17.1070 .

Compared with DSM-III major depression, theprevalence estimates reported for dysthymia aremuch lower. However, at one time or another, manyof these patients meet the criteria for majordepressive disorder. This phenomenon was describedby Keller & Shapiro (1982) as "double depression".Because of the immense overlap of major depressionand dysthymia, and because most of the investigatorswho conducted epidemiological studies did notdifferentiate between non-remitting major depressionand dysthymia, low prevalence estimates need to beconsidered with caution. The point-prevalences fordysthymia range from 1.2070 to 3.9070, which issimilar to the one-year or lifetime prevalenceestimates of approximately 3.3070 and 3.6070respectively (Table 1).

Several factors account for the variability of studyfindings. For instance, the studies did not all use thesame diagnostic procedures. In the ECA study,reported estimates of major depression excludedshort-term grief, bipolar 1 and 2 disorder, andschizophrenia. Other investigators did not use someor any of these exclusion criteria (Angst et al, 1990;

Wacker et al, 1992; Kessler et al, 1994a). Thus, thefindings of the latter relate to major depressiveepisodes and not to major depression.

The type of assessment instruments used is asecond source of variation. Kessler et al (1994a)suggested that the higher estimates for majordepressive episodes in their study might be partly dueto three factors. These are (a) use of a non­respondent survey, which allowed them to correctprevalence estimates for the lower interviewcompletion rate among people with a history ofdepression; (b) use of a life-review section that helpedto stimulate the respondents' active memory searchfor recall of lifetime disorders; and (c) the criticalrole of sequence effects in the assessment ofdepressive disorders. Because an instrument such asthe DIS assesses depressive symptomatology afterlengthy sections for somatisation disorder have beencompleted, lower prevalences of depression mightresult (e.g. Wacker et al, 1992). Alternatively, whendepression was evaluated earlier in the interviewprocess, higher prevalences of depression werereported (Kessler et al, 1994a).

However, most of the variance between studies canbe explained by the age composition of the samplesstudied, such that the highest prevalence estimatesof depressive episodes were reported in the studieswith the youngest samples, and vice versa.Additionally, the variable rates can be explained bythe year in which the study was conducted, such thathigher prevalences were reported in the most recentstudies. These findings suggest that different ratesof depressive disorders exist in the young versus theold, or that the prevalence of depressive disordersis changing with time.

Changing rates of depression

Traditionally, the risk of depression has been thoughtto increase with age. However, results of severalstudies, demonstrating considerably higher preva­lences in younger than in older people, suggest

WITTCHEN ET AL

0.06

1905-1914_____-v <1905

o 5 15 25 35 45 55 65 70

0.02

0.04

0.10cc~ 0.08oCJ)w~a::w>§:::J::E:::Jo

18

60

a: 50w0a:a:

4000-,en«-:EO

30~~-en~en 20~~

(Lw 10°

o 10 20 30 40 50 60 70 AGE OF ONSET (y)

CURRENT AGE (y)

Fig. 1 Cumulative rates of depression among relatives and controlsfor successive birth cohorts and the respective age at the time ofthe clinician-administered interview (SADS). Reprinted withpermission from Klerman & Weissman (1989), Journal of theAmerican Medical Association, 261, 2229-2235; copyright 1989,American Medical Association.

that for successive birth cohorts during this centurythe prevalence of depression has been increasing andthat the age of first onset has been decreasing (Fig.1). Additional evidence supporting changing rates ofdepression has been derived from observations madeduring the 1960s and 1970s, including an increase inhospital admissions for affective illnesses during thelatter half of this century versus the first half, ayounger age of onset of illness than that reportedbefore the Second World War, an increase in thenumber of childhood depressions seen by clinicians,and an increase in suicide attempts and deaths amongadolescents (Klerman & Weissman, 1989). Further­more, on the basis of clinical and epidemiologicalstudies, depression does not appear to increasefollowing menopause, and the prevalence of suicideamong elderly persons is low.

Temporal trends

Several studies using multivariate statisticaltechniques for analysing time-dependent data (e.g.life-table methods, survival analysis) have beenpublished that focus on the changing rate of majordepression across the life span (Cross-NationalCollaborative Group, 1992; Lewinsohn et al, 1993;Kessler et ai, 1994b). The term 'temporal trends' ismost often used to describe these findings (Crow,1986), but other terms have also been used, including'birth cohort trends' (Klerman et ai, 1985)and 'birthcohort changes' (Gershon et al, 1987).

Temporal trends are variations in prevalences overtime and can be age, period, or cohort trends

Fig. 2 Cumulative lifetime rates of major depressive disorder bybirth cohort and age of onset in subjects (n = 18 244) evaluated inthe Epidemiologic Catchment Area Study (ECA). Reprinted withpermission from Cross-National Collaborative Group (1992),Journal of the American Medical Asosciation, 268, 3098-3105;copyright 1992, American Medical Association.

(Klerman & Weissman, 1989). Age trends refer tochanges in age-specific rates of illness, usually usingthe age of first onset of the disorder. Period trendsare defined by rates of illnesses associated withspecific time periods, such as infectious epidemics.Lastly, cohort trends refer to changes in rates ofillness among individuals who are defined by someshared continued temporal experience (i.e, the yearof their birth).

The Cross-National Collaborative Group (1992)directly reanalysed the temporal trend hypothesis ofmaj or depression using data from nineepidemiological and three family studies conductedindependently in the 1980s in North America,western Europe, the Middle East, Asia, and thePacific Rim. These studies used similar diagnosticcriteria and assessment instruments (DSM - III,Schizophrenia and Affective Disorder Schedule(SADS), DIS), and a common data analysis plan.In the reanalysis, seven birth cohorts, divided intoten-year time intervals, were defined (i.e, earlier than1905, 1905-1914, and so on, up to 1955 or later).Age of onset of major depression was divided intosimilar ten-year time intervals from age 5 to 74 years.This study confirmed a significant trend forincreasing rates of major depression over time, inaddition to an earlier age of onset for youngercohorts (Fig. 2). However, there was intersitevariation with regard to the age-specific cohortprevalences of depression, ranging from 6070 in the1945-1954 age cohort in Puerto Rico, to 9070 in thesame age cohort of the ECA, to as high as 14070 inMunich, 18070 in Florence, and 21070 in Beirut. It isalso important to note that the consistently lowerprevalence estimates for the elderly also varied (2070

LIFETIME RISK OF DEPRESSION 19

Fig. 4 Cumulative lifetime hazard rate for the development ofmajor depressive episodes by birth cohort and age of onset inwomen evaluated in the National Comorbidity Survey. Reprintedwith permission from Kessler et al (1994b).

AGEATONSET(y)

45-54

35-4415-24 23-34

0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54

1935-1944~

0.30

0.250a:

0.20~J: 0.15w>5 0.10::J~ 0.05::J0

0.00

0.0700 0.06~u.0 0.05enw

0.04~a:w 0.03>~ 0.02....J::)~ 0.01::)o

AGE OF ONSET (y)

Fig. 3 Cumulative lifetime rates of major depressive disorder bybirth cohort and age of onset in Puerto Rican subjects (n = 1551)representing a lack of an age-cohort effect. Reprinted withpermission from Cross-National Collaborative Group (1992),Journal of the American Medical Association, 268, 3098-3105;copyright 1992, American Medical Association.

0.014

0.012w 0.010~a: o.ooe0a:~ 0.006:I: 0.004

0.002

0.0000-4

Male

5-9 10-14 15-19 20-24 25-29 30·34 35-39 40-44 45-49 50-54

in the ECA, 60/0 in Munich, and 50/0 in Puerto Rico).Interestingly, the weakest age-cohort effect wasfound among Hispanic samples (Puerto Rico, LosAngeles Hispanics) (Fig. 3).

In another analysis, data from three samples ofadults and a larger sample of adolescents aged 14-18(n = 1710) were used to study age-cohort effects(Lewinsohn et ai, 1993). A significant age-cohorteffect was found in all three adult samples as wellas the adolescent sample, with a trend for an earlierage of onset of illness. In an additional analysis ofthe possible role of confounding factors that mightartificially influence prevalence estimates, fourcritical variables were identified: current mood state,social desirability response bias, labelling, and timeinterval between episodes and diagnostic interview.Although these variables, except for labelling, weresignificantly associated with reports of past episodesof the disorder and with birth cohorts, they did notinfluence the age-cohort effect.

The National Comorbidity Survey (NCS) is thefirst survey in the US conducted in a representativesample of the general population (Kessler et ai,1994b). Younger age groups (15 years old) wereincluded in the evaluation, and specific innovationsof social survey research, in conjunction with theCIDI, were used to improve the probands' memorywith regard to past symptoms specifically relevantfor the assessment of lifetime psychopathology(Witt chen et ai, 1991). This study provides furtherevidence that there is a consistent trend for thelifetime risk of depression to be higher in successively

AGE(y)

Fig. 5 Lifetime hazard rates for developing major depressiveepisodes based on gender and age in subjects evaluated in theNational Comorbidity Survey. Reprinted with permission fromKessler et al (1994b).

younger cohorts (Fig. 4). The cohort difference seemsto be more pronounced in the youngest cohort forboth men and women, as found in the earlier studiessuch as the ECA (Robins & Regier, 1991).Respondents in the youngest cohort of the NCS studywere between 5 and 15 years of age at the time theECA study was carried out in 1981. Therefore thesubstantially increased risk of depression in thisyoungest cohort suggests a possible extension of thecohort effect found in the ECA.

Another important finding of the NCS is thatdifferences with regard to rates of depressionbetween men and women begin in early adolescenceand persist until late middle-age (Fig. 5). A similarobservation was made by Burke et al (1991) in theECA. However, in the NCS, the gender differencein cumulative onset risk appears five years earlierthan in the ECA (age 10 v. age 15). This might beimportant because of speculation in the literature thatthe gender difference in depression is triggered bypuberty (Nolen-Hoeksema, 1987), which is moreconsistent with the NCS results than the ECAfinding. No decrease in the hazard rate after age 30was observed in the NCS, which is consistent withobservations of stable rates of depressive episodes

20 WITTCHEN ET AL

across mid-life. In addition, men and women witha history of depression did not differ from each otherin either the probability of being chronicallydepressed or having an acute recurrence in the pastyear. Therefore, the higher prevalence of 12-monthdepression in women is a result of the increased riskof developing depression in women.

Explanations for the variation between youngand old subjectsIn almost all of these studies, the estimates of majordepressive episodes have increased with successivelyyounger birth cohorts. High estimates of childhoodand adolescent depression have been confirmed inat least two independent child psychiatry investi­gations (Garrison et 01, 1992; Lewinsohn et 01,1993). However, the low prevalence of depressionobserved among the elderly has been criticisedheavily as being possibly artefactual (Klerman et 01,1985; Klerman & Weissman, 1989; Knauper &Wittchen, 1994).Differential morbidity, institutiona­lisation, selective migration, and response-biasedmemory are some of the possible confoundingfactors that may contribute to the findings in theelderly, and most of these factors have had asignificant impact on prevalence estimates (Blazer,19890; Lewinsohn et 01, 1993). However, it is widelyheld that none of these factors, singly or incombination, is completely responsible for the largedifference between the prevalence of depression inthe young versus the old (Cross-NationalCollaborative Group, 1992; Lewinsohn et 01, 1993).

Further potentially confounding factors includethe possibility that current diagnostic procedures(structured diagnostic interview questions andprobes) have specific limitations in the assessmentof psychopathology in the elderly (Knauper, 1994;Knauper & Wittchen, 1994). Decreased memorycapacity in elderly patients may critically affect thediagnostic process. Content aspects, such as the roleof somatisation in depression, have also beensuggested as reasons for the lower prevalence ofdepression in the elderly (Blazer, 1989a,b, 1991).These studies may eventually lead to a revision orspecification of both diagnostic criteria and adequateassessment tools for the elderly.

Henderson et 01 (1993), using ICD-I0 clinicaldiagnostic criteria, reported that the overallprevalence for depressive episodes in the elderly was2.9070 in community residents, 6.4070 amonginstitutionalised residents, and 3.3070 among the totalpopulation aged 70and over. These data suggest bothfactors, the use of a clinical diagnostic instrumentas well as the inclusion of an institutional sample,do not affect the finding of a lower prevalence ofdepressive disorders in the elderly compared withyounger cohorts. Lower prevalences are reported

when the DSM- III - R criteria for depression, whichare stricter than ICD-I0, are used. DSM-III-Rcriteria gave prevalences of 0.4070,6.3070, and 1.0070among community residents, institutionalisedresidents, and the overall population, respectively(Henderson et 01, 1993).

In addition to the impact of diagnostic criteria,higher prevalences have been found when lessstandardised assessment procedures are used. Kayet 01 (1985), who used a modified version of theGeriatric Mental State Schedule (GMS: Copeland et01, 1976) combined with a psychiatric rating, foundhigher prevalence rates of major depressive episodescompared with those who used fully standardiseddiagnostic instruments (Blazer et 01, 1987;Hendersonet 01, 1993).

Thus the diagnostic procedures used in the elderlymay not be fully appropriate. Many investigatorsagree that few of the elderly fulfil the criteria formajor depression or dysthymia (Gaitz & Scott, 1972;Blazer, 1989a,b, 1991; Fuhrer et 01, 1992). However,many elderly individuals appear to have clinicallyrelevant syndromes of slightly or markedly differentphenomenology that escape the strict DSM- III - Rand ICD-I0 criteria. Blazer (1991) regarded this asan epidemiologic dilemma and suggested the use of'minor depression' as a diagnostic category in theelderly.

Conclusions

The most striking finding in recent years with regardto depression across the lifespan has been theincreasing rates of depressive disorder in successivelyyounger birth cohorts. Although the question hasbeen raised as to whether this effect might be, atleast in part, due to an artefact of the researchmethodology, many attempts have been made toexplain the finding as a 'true' increase of depressivedisorders during this century. For example, changingfamily structures, social forces and patterns ofurbanicity have been discussed as contributingfactors (Klerman et 01, 1985; Klerman & Weissman,1989). The fact that gender differences in depressionin recent cohorts appear to be decreasing as theoverall prevalence of depression increases has led tospeculation that the most important causes areassociated with the changing roles of men andwomen in society and, in particular, with changesin gender-related occupational patterns (Kessler &McRae, 1981, 1982).However, no empirical researchhas yet been carried out to provide a convincingevaluation of these hypotheses.

Further research is required not only to investigatethe determinants of cohort differences in depression,but also to study factors that influence the natural

LIFETIME RISK OF DEPRESSION 21

course of depressive disorders. We now know thatthe determinants of first onset of depression maydiffer from the determinants of recurrence andpersistence, but not enough systematic research hasbeen carried out to provide a good understandingof these differential effects. Several interestinghypotheses have been proposed. One is that earlyonset of depression may be a risk factor forrecurrence. Another is that the rise in prevalenceamong more recent cohorts may be associated witha lower risk of chronicity because of the fact thatthese new depressions might be situational ratherthan biological (Wittchen & von Zerssen, 1988;Lewinsohn et al, 1993; Kessler et al, 1994b).

Future research will also be required to determinewhether other types of depressive disorders, such asadjustment disorders or mixed anxiety/depressivesyndromes, may account for changes in theprevalence of major depressive episodes across thelifespan. This issue is particularly relevant in the lightof lower prevalence rates reported in the elderly, andthe possibility that many of these individuals havesubsyndromal illnesses and do not meet the criteriafor major depression.

Additionally, evaluation of the diagnostic processand its special characteristics in the elderly will berequired to assess depressive phenomena in old age.Whereas the self-report isnot the perfect way to assesssymptomatology in the elderly, it is still relied uponwithout accounting for different age-related cognitiveabilities, the influence of physical conditions ondepressive symptomatology, and differences ininformation-processing capacity that might playacritical role in reporting depression in this population.

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Hans-Ulrich Wittchen, PhD; Barbel Knauper, PhD, Max Planck Institute of Psychiatry, Munchen, Germany;Ronald C. Kessler, PhD, Institute for Social Research, University of Michigan, Ann Arbor, USA

Correspondence: Professor H.-V. Wittchen, Max Planck Institute of Psychiatry, Clinical Institute, Kraepelinstrasse 10,80804 Munchen, Germany