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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Depress Anxiety. Author manuscript; available in PMC 2011 July 19.
Published in final edited form as:
PMCID: PMC3139270

Age differences in the prevalence and comorbidity of DSM-IV major depressive episodes: Results from the WHO World Mental Health Survey Initiative

Ronald C. Kessler, Ph.D.,1,* Howard Birnbaum, Ph.D.,2 Victoria Shahly, Ph.D.,3 Evelyn Bromet, Ph.D.,4 Irving Hwang, M.A.,1 Katie A. McLaughlin, Ph.D.,1 Nancy Sampson, B.A.,1 Laura Helena Andrade, M.D., Ph.D.,5 Giovanni de Girolamo, M.D.,6 Koen Demyttenaere, M.D., Ph.D.,7 Josep Maria Haro, M.D., M.P.H., Ph.D.,8 Aimee N. Karam, Ph.D.,9 Stanislav Kostyuchenko, M.D.,10 Viviane Kovess, M.D., Ph.D.,11 Carmen Lara, M.D., Ph.D.,12 Daphna Levinson, Ph.D.,13 Herbert Matschinger, Ph.D.,14 Yoshibumi Nakane, M.D.,15 Mark Oakley Browne, FRANZCP Ph.D.,16 Johan Ormel, Ph.D.,17 Jose Posada-Villa, M.D.,18 Rajesh Sagar, M.D.,19 and Dan J. Stein, Ph.D.20



Although depression appears to decrease in late life, this could be due to misattribution of depressive symptoms to physical disorders that increase in late life.


We investigated this issue by studying age differences in comorbidity of DSM-IV major depressive episodes (MDE) with chronic physical conditions in the WHO World Mental Health (WMH) surveys, a series of community epidemiological surveys carried out in 10 developed countries (n = 51,771) and 8 developing countries (n = 37,265). MDE and other mental disorders were assessed with the Composite International Diagnostic Interview (CIDI). Organic exclusion rules were not used to avoid inappropriate exclusion of cases with physical comorbidity. Physical conditions were assessed with a standard chronic conditions checklist.


Twelve-month DSM-IV/CIDI MDE was significantly less prevalent among respondents ages 65+ than younger respondents in developed but not developing countries. Prevalence of comorbid mental disorders generally either decreased or remained stable with age, while comorbidity of MDE with mental disorders generally increased with age. Prevalence of physical conditions, in comparison, generally increased with age, while comorbidity of MDE with physical conditions generally decreased with age. Depression treatment was lowest among the elderly in developed and developing countries.


The weakening associations between MDE and physical conditions with increasing age argue against the suggestion that the low estimated prevalence of MDE among the elderly is due to increased confounding with physical disorders. Future study is needed to investigate processes that might lead to a decreasing impact of physical illness on depression among the elderly.

Keywords: Elderly, Depression, Disability, Comorbidity, Epidemiology


Community epidemiological surveys in developed countries consistently find that current prevalence of major depression decreases with age and is especially low among the elderly. [1-3] A number of methodological explanations have been proposed for this finding, suggesting that age-related differentials in mortality, selection out of the household population, willingness to participate in surveys, and willingness to admit psychiatric problems lead to downward bias in prevalence estimates among the elderly.[4,5] However, evidence for these methodological interpretations is weak,[6] leading some commentators to conclude that the prevalence of depression is genuinely low among the elderly.[2]

An important issue in studying late-life depression is that many physical disorders increase in old age, possibly resulting in depression being under-estimated because it is confused with the symptoms of physical disorders.[7] A complicating factor is that some somatic disorders that increase with age can induce depression,[8,9] while late-life depression can increase risk of some physical disorders.[10,11] In an effort to shed light on this issue, we analyzed data on age-related changes in the associations of physical disorders with DSM-IV major depressive episodes (MDE) in the World Health Organization (WHO) World Mental Health (WMH) surveys.[12] Parallel analyses were carried out for comorbid DSM-IV mental disorders. MDE was defined without either organic exclusions or diagnostic hierarchy rules to facilitate investigation of comorbidity. Our primary aims were to see if the presumed decline in MDE prevalence with age is associated with comorbidity. In studying comorbidity, we focused on associations rather than conditional prevalence, as data already exist on age-related changes in prevalence[13-15] but not on age-related changes in associations. An examination of these associations is of interest because we would expect them to increase with age if the assessment of MDE is confounded by physical disorders. As a preliminary to these analyses, we also examined MDE prevalence by age as well as age differences in the ratios of recent to lifetime prevalence, age-of-onset distributions, and persistence-severity of 12-month MDE.



Data are presented for 17 countries, 10 classified by the World Bank developed (Belgium, France, Germany, Israel, Italy, Japan, Netherlands, New Zealand, Spain, United States), and 8 developing (Brazil, Colombia, India, Lebanon, Mexico, South Africa, Ukraine, Shenzhen in the People's Republic of China).[16] 89,036 adults participated in the surveys (51,771 in developed and 37,265 in developing countries). (Table 1) All surveys involved nationally representative household samples except Colombia and Mexico, which featured representative samples of urban areas. Weights were used to adjust for differential probabilities of selection and to match sample socio-demographic distributions with population distributions. The weighted average response rate across surveys was 72.0%, ranging from 45.9% in France to 98.6 % in India. Other than in Israel, sub-sampling was used to reduce respondent burden by dividing the interview into two parts. All respondents completed Part 1, which assessed core mental disorders. Part II assessed additional disorders and correlates and was administered to all Part 1 respondents who met criteria for any Part I disorder plus a probability subsample of other Part I respondents. Part II responses were weighted by the inverse of their probability of selection to adjust for differential selection. Further details about WMH survey methodology are presented elsewhere.[17]

Table 1
World Mental Health (MH) Survey sample characteristics


Mental disorders

Mental disorders were assessed using the WHO Composite International Diagnostic Interview (CIDI) Version 3.0,[18] a fully-structured lay-administered interview that generates diagnoses for commonly occurring DSM-IV mental disorders. In addition to MDE, these disorders included other mood (dysthymic disorder, bipolar disorder), anxiety (generalized anxiety disorder, panic disorder, agoraphobia without panic disorder, specific phobia, social phobia, post-traumatic stress disorder, adult separation anxiety disorder), substance (alcohol and drug abuse with and without dependence), and intermittent explosive disorders. Blinded clinical reappraisal interviews using the Structured Clinical Interview for DSM-IV (SCID)[19] with a probability sub-sample of WMH survey respondents from four countries found generally good concordance between diagnoses based on the CIDI and those based on the SCID.[20] DSM-IV/CIDI disorders were defined without organic exclusions and without diagnostic hierarchy rules in order to facilitate analysis of comorbidity. Although no comparisons were made of differences in diagnoses with and without these exclusions, previous WMH analyses suggest that such differences are slight.[15]

MDE course was examined using retrospectively reported data on age-of-onset, number of lifetime episodes, and number of weeks in episode in the past 12 months. MDE clinical severity was assessed among 12-month cases using the Quick Inventory of Depressive Symptomatology Self-Report (QIDS).[21] Standard QIDS cut-points were used to define episodes as severe, moderate, mild, or not clinically significant. Role impairment among 12-month cases was assessed using the Sheehan Disability Scale (SDS),[22] which asks respondents to rate how much their 12-month depression interferes with their home management, work performance, social life, and personal relationships on a 0-10 visual analogue scale with response anchors of none (0), mild (1-3), moderate (4-6), severe (7-9), and very severe (10). Both the QIDS and the SDS assessed severity for the one month in the past year when symptoms were most severe. Respondents with 12-month MDE were also asked to estimate the number of days out of 365 in the past year they were totally unable to work or carry out their other usual daily activities because of their depression.

Comorbid physical disorders

Physical disorders were assessed with a standard chronic conditions checklist containing 14 conditions based on the list in the US National Health Interview Survey.[23,24]2 Such checklists are widely used in epidemiological studies and yield more accurate reports than open-ended questions.[25] Good concordance has been documented between condition reports based on such checklists and medical records.[26-28] The 14 physical conditions considered here include cardiovascular (heart attack, hypertension, other heart disease, stroke), musculoskeletal (arthritis/rheumatism, chronic back/neck problems), respiratory (seasonal allergies, asthma, other chronic lung disease such as chronic obstructive pulmonary disorder and tuberculosis), and pain (frequent/severe headaches, other chronic pain conditions) conditions along with cancer, diabetes, and ulcers. Although respondents reported the presence of each condition in their lifetime and during the past 12 months, we focus on disorders present in the past 12 months.

Depression treatment

Respondents were asked about treatment obtained at any time in the 12 months before interview for problems with emotions, nerves, or substance use. We examine treatment among respondents with 12-month DSM-IV/CIDI MDE separately in the specialty sector (psychiatrist or other mental health professional), general medical sector (MD or non-MD health professional excluding mental health professionals), human services sector (religious counselors, social workers seen in a human services setting), and the complementary-alternative medical (CAM) sector (e.g., self-help groups, faith healers, traditional healers).

Analysis methods

Age differences in prevalence, course, severity, and treatment of MDE were examined using cross-tabulations and mean comparisons. Multiple regression analysis with both linear and logistic link functions was used to study comorbidity of MDE with other physical and mental disorders. Regression equations were estimated separately in four age groups (18-34, 35-49, 50-64, 65+) in developed and developing countries. These equations included covariates for sex, income, employment status (employed/self-employed, student, homemaker, retired, disabled/unemployed), and marital status (married, previously married, never married). Wald χ2 tests (logistic regressions) and F-tests (linear regressions) were used to evaluate the significance of interactions. We also evaluated whether the conditional prevalence of comorbid disorders among people with MDE varies with age. Because the data are weighted and clustered, the Taylor series linearization method[29] implemented in the SUDAAN software package[30] was used to estimate standard errors. Statistical significance was evaluated using .05-level two-sided tests.



The estimated 12-month prevalence of MDE is 5.5% in developed countries and 5.9% in developing countries. (Table 2) These estimates vary significantly across the four age groups in developed (χ23 = 150.2, p < .001) but not developing (χ23 = 2.2, p = .52) countries. The significant association in developed countries is due to highest prevalence in the youngest age group (18-34; 7.0%) and lowest in the oldest age group (65+; 2.6%). This pattern is statistically significant in seven of the ten developed countries. The exceptions are Israel, Italy, and Spain, all with insignificant age-MDE associations (χ23 = 0.5-6.5, p = .09-.91). The association is also insignificant in four of the seven developing countries (Colombia, Lebanon, Mexico, South Africa; χ23 = 3.0-6.3, p = .10-.39). In one of the other three (Brazil), the pattern is similar to developed countries, with highest prevalence in the youngest age group and lowest in the oldest age group (10.9% vs. 3.9%, χ23 = 36.1, p < .001). An opposite pattern is found in one other developing country (Ukraine), with lowest prevalence among the young and highest among the old (6.0% vs. 13.0%, χ23 = 21.1, p < .001). The age trend is significant but not monotonic, in the remaining developing country (India) (χ23 = 33.0, p < .001).

Table 2
Twelve-month prevalence of DSM-IV/CIDI MDE by country and age

Age-of-onset, course, and severity of MDE

Retrospectively reported MDE age-of-onset (AOO) varies significantly with age in both developed (χ23=3717.2, p<.001) and developing (χ23=1596.3, p<.001) countries, with mean AOO increasing monotonically from youngest (19.1-19.3) to oldest (46.3-40.3) age groups. (Table 3) The difference between mean age-at-interview and mean AOO of MDE in each age group also increases consistently with age. This is important because it is what we would expect based on substantive processes and argues against a methodological interpretation of the age differences, as methodological confounding would be expected to cause the difference between age-at-interview and AOO to remain constant with age.[31] Mean number of lifetime episodes of MDE among respondents with a lifetime history also increases monotonically with age (χ23=21.3-36.1, p < .001). Country-specific analyses (not shown, but available on request) find similar age-related patterns of onset-course in each country.

Table 3
Dimensions of DSM-IV/CIDI MDE lifetime onset-course and 12-month persistence-severity by age among WMH respondents with MDE

The mean self-reported duration of MDE (in weeks) in the 12 months before interview among 12-month cases increases monotonically from youngest to oldest ages in both developed (25.3 vs. 31.7, F3,2969 = 4.8, p = .002) and developing (23.1 vs. 33.8, F3,2289 = 3.6, p = .013) countries. The relationship between age and severity of 12-month MDE, however, differs both by type of country and type of measure. Clinical severity, as assessed by the QIDS, varies inversely with age in developed countries (χ23=15.2, p=.002), with the percent classified clinically severe lower in the 65+ age group (19.6%) than younger age groups (29.6-39.7%). Clinical severity does not vary with age, in comparison, in developing countries (χ23=3.7, p=.296), although the proportion of 12-month cases rating their recent MDE as causing severe role impairment varies inversely with age in both developed (65.3% vs. 54.8%, χ23 = 12.4, p = .006) and developing (49.3% vs. 42.7%, χ23 = 11.4, p = .010) countries. Mean number of days out of role in the past year due to MDE among 12-month cases is lowest in the oldest age group in developed countries (25.5 vs. 46.4-52.5, F3,2969 = 12.4, p = .006), but highest in the oldest age group in developing countries (50.4 vs. 16.0-34.9, F3,2289 = 3.6, p = .013).

Comorbidity of 12-month MDE with other 12-month DSM-IV disorders

All 14 12-month DSM-IV disorders considered here are significantly and positively associated with 12-month MDE in the total sample in both developed and developing countries and in both linear and logistic regression models. (Detailed results are not reported, but are available on request.) There is a general tendency for odds-ratios (ORs) of MDE with classes of 12-month comorbid DSM-IV/CIDI disorders (i.e., mood, anxiety, and substance disorders) and with numbers of such disorders to increase with age. (Table 4) More disaggregated analyses (results not reported, but available on request) show that ORs of 12-month MDE with comorbid 12-month disorders vary significantly with age for six of the 14 comorbid disorders in developed countries, in four of which the OR is highest in the oldest age group (bipolar disorder, generalized anxiety disorder, PTSD, and panic disorder), and for five of the 14 comorbid disorders in developing countries, in two of which the OR is highest in the oldest age group (dysthymia and adult separation anxiety disorder).

Table 4
Twelve-month comorbidity (odds-ratios) of DSM-IV/CIDI MDE with other 12-month DSM-IV/CIDI disorders by age1

Despite the ORs generally increasing with age, the conditional prevalence of comorbid mental disorders among people with 12-month MDE generally either remains stable or decreases with age. These differences between logistic and linear regression results are due to a methodological fact: that ORs can be large even when the proportions of people with a comorbid disorder are small. It is consequently useful to examine patterns of comorbidity based not only on logistic regression equations but also on linear regression equations. This analysis (detailed results are not shown, but are available on request) showed that even though the ORs of MDE with comorbid mental disorders generally increase with age, age-related differences in prevalence of these disorders between respondents with vs. without MDE are much less consistent. Linear regression coefficients of MDE with comorbid mental disorders are predominantly lowest among the oldest respondents (nine of 14 disorders, four of them significant: dysthymia, specific phobia, alcohol abuse with dependence, drug abuse with dependence) in developed countries, but as likely to be highest (six of 14 disorders, two of them significant: bipolar disorder, adult separation anxiety disorder) as lowest (five others of the 14 disorders, two of them significant: specific phobia, drug abuse) among the oldest respondents in developing countries.

Comorbidity of 12-month MDE with 12-month chronic physical disorders

As with mental disorders, all 14 physical conditions are positively related to MDE in linear models in both developed (12 statistically significant) and developing (all 14 significant) countries. (Detailed results are not presented, but are available on request.) Eleven of the 14 are also positively related to MDE in logistic models in developed countries (eight significant) and 13 of the 14 in developing countries (12 significant). A similar pattern exists for both aggregated classes and numbers of comorbid physical conditions, where 18 of 22 associations are positive (17 statistically significant). (Table 5). However, unlike the situation with comorbid mental disorders, where ORs generally increase with age, ORs of MDE with physical conditions generally are unrelated to age. The differences that do exist usually reflect the OR being lowest rather than highest in the oldest age groups.

Table 5
Twelve-month comorbidity (odds-ratios) of DSM-IV/CIDI MDE with chronic physical disorders by age1

A similar pattern can be seen in the linear regression results in developed countries (results not shown, but available on request), where prevalence differences in comorbid physical conditions between people with vs. without MDE consistently (13 of 14 conditions) decrease with age (8 statistically significant). This pattern is less consistent in developing countries, where the prevalence difference is lower with increasing age for only five conditions and none of these is statistically significant. These decreasing associations with age occur despite the fact that conditional prevalence of physical conditions among people with MDE consistently increases with age in both developed and developing countries. This increase is statistically significant for 10 of 14 comorbid conditions (the exceptions being seasonal allergies, asthma, ulcers, and headaches, for none of which is there a meaningful age difference) in developed countries. In developing countries, this increase is statistically significant for 9 of 14 comorbid conditions (the exceptions being stroke, seasonal allergies, asthma, chronic pains and headaches).

Age-related differences in treatment of 12-month MDE

Approximately half (54.3%) of respondents with 12-month MDE in developed countries and one-quarter (25.2%) in developing countries reported receiving some type of treatment for emotional problems in the year before interview. (Table 6) The proportion who received treatment varies significantly with age in developed countries (χ23 = 34.9, p < .001) and is lowest in the oldest age group (44.0% vs. 48.4-61.7%). This pattern of under-treatment can be seen in the youngest age group as well as in the oldest, although the pattern in the oldest age group is more pronounced than in the youngest age group when we focus on the specialty sector.

Table 6
Past year treatment of emotional problems among respondent with 12-month DSM-IV/CIDI MDE by age


The above results must be interpreted in the context of several limitations: First, individuals with severe physical or neurocognitive impairment may have been less likely to participate, presumably reducing our estimates of the associations between MDE and physical conditions more among elderly than younger respondents. Second, physical conditions were assessed with a checklist, whereas mental disorders where assessed with a comprehensive diagnostic interview, possibly leading to greater attenuation of estimated associations involving physical than mental disorders. Third, the fact that the assessments were made with fully-structured interviews rather than clinical interviews might have artificially inflated comorbidity estimates between diagnoses of MDE and the other disorders due to overlap in core symptoms (e.g., lethargy, insomnia), although we tried to minimize this problem by not using organic exclusion rules in making diagnoses of mental disorders.

Notwithstanding these limitations, our results are consistent with previous studies in showing that recent MDE is less prevalent among older than younger respondents in developed countries.[2,32] The finding that MDE generally does not decrease with age in developing countries is also consistent with the small number of previous studies that have examined this pattern in developing countries;[33-36] although those studies generally found depression to increase with age whereas we found that association with age to be for the most part insignificant. We did not investigate reasons for the differing relationship between age and depression between developed and developing countries, but this should be the focus of future study. Our findings of higher mean MDE AOO and longer time lag between AOO and current age with increasing age are both substantively plausible and inconsistent with evidence of age-related recall bias in previous epidemiological surveys.[31] We attribute this difference between the WMH results and the results of previous survey to the use of an innovative AOO probing technique in the WMH surveys that has been shown experimentally to reduce recall bias.[37]

The finding that retrospectively reported number of lifetime episodes increases with age among respondents with a history of MDE is, like the findings for AOO in the preceding paragraph, substantively plausible and consistent with previous research.[38] The finding that age is positively related to duration of 12-month depressive symptoms among 12-month cases, in comparison, is inconsistent with previous research that found no association between age and 12-month duration of depressive episodes.[39,40] It should be noted, though, that these earlier studies were based on much smaller samples than the WMH series. Our results regarding longer episode duration among the oldest respondents are also consistent across types of countries. We also found consistently across countries that despite the longer duration of recent episodes, recent MDE was reported to cause less role impairment than among younger depressed people. At least two previous studies also found that symptom severity and severity of role impairment due to 12-month depression are both inversely related to age.[6,41] One plausible interpretation of the lower impact of depression on role impairment with increasing age is that role demands decrease with age. However, this interpretation does not explain the finding that symptom severity also decreases significantly with age in developing countries. Another possibility is that depression subtypes change with age and that the subtypes more typical of older people are less severe and impairing than those more typical of younger people.[42,43] Although no attempt was made here to examine depressive symptom profiles by age to investigate this interpretation, this would be a useful extension of the current results.

Our finding that 12-month prevalence of some mental disorders decreases with age while prevalence of most physical disorders increases with age is consistent with much previous research.[13,14] We are aware of little previous research, though, other than earlier WMH analyses[15,44] on age differences in the associations of depression with comorbid disorders. Our findings that these associations generally increase with age when they involve comorbid mental disorders but decrease with age when they involve comorbid physical disorders are consequently of special interest. The most plausible interpretation of the generally increasing are-related ORs with other mental disorders is that comorbid cases have a more persistent course than pure cases. Although it is beyond the scope of the current report to investigate the reasons for such an effect, it is noteworthy that this could also be implicated in the longer duration of depressive episodes among the elderly. The fact that the role impairment associated with depression is lowest among the elderly is all the more striking in light of the greater persistent and higher comorbidity of MDE with other mental disorders among the elderly.

The generally decreasing age-related ORs of MDE with physical disorders are more interpretable because the age patterns in prevalence are different for MDE (decreasing prevalence with age) and most physical disorders (increasing prevalence with age). In a situation of this sort, it is likely that the decreasing ORs are at least partially attributable to a decrease in the causal effects of physical disorders on MDE. Whether or not causal effects of MDE on comorbid physical disorders also decrease with age is difficult to say because the implications of such a decrease on the prevalence of physical disorders would be negligible in light of the much lower prevalence of MDE than chronic physical conditions among the elderly. In either case, though, the existence of these patterns argue against the suggestion that the low prevalence of MDE among the elderly in developed countries is due to increased confounding of depression symptoms with symptoms of chronic physical conditions.

Our results shed no light on why physical disorders might have decreasing effects on MDE among the elderly. One possibility proposed in the literature is that elderly people are more accepting than those of younger ages of the inevitability of physical illness, resulting in the otherwise adverse psychological effects of physical disorders being buffered.[6] A related suggestion is that elderly people are “immunized” from the negative psychological effects of adversity by prior life experience.[45] Although we are aware of no direct test of these hypotheses, elderly people have been shown to be more likely than younger people to cope with adversity by using strategies that accept and adapt rather than try to change their situations[46] and that disengage from stressful situations in ways that reduce adverse emotional effects.[47] Other research has shown similar age differences in coping with physical illness,[48] but has not investigated whether these differences lead to reductions in the causal effects of physical disorders on depression. Investigation of these buffering effects is an important next step that, while beyond the scope of the present study, might help delineate positive patterns of response to the increasing physical infirmity of advanced age. Another possibility is that elderly people might have reduced capacity to register or express mood states due to autonomic, neuroendocrine, or cognitive dysfunction that lead to reduced prevalence of mood disorders in old age.[49] It is unclear, though, how this or any of the other explanations proposed in the literature would account for the fact that age-related decline in depression prevalence is largely confided to developed countries. New theorizing is required to explain this specification.


We found that the widely documented decrease in the prevalence of MDE among the elderly is much more pronounced in developed than developing countries. We found that even though the prevalence of chronic physical conditions increased with age in both developed and developing countries, the association between depression and chronic conditions generally decreases with age. This result argues against the view that the apparent decrease in clinical depression among the elderly is due to increasing confounding of the symptoms of depression with the symptoms of chronic physical conditions. It is unclear why the age gradient in depression differs in developed versus developing countries, but this difference represents an important and previously neglected specification that provides an opportunity to investigate cross-national differences in age-related correlates. Such an investigation might shed light on the reasons for the decline in depression with age in developed countries. It is also unclear why the associations between depression and comorbid physical conditions decrease with age despite the prevalence of these conditions increasing with age and the persistence of depression increasing with age. An understanding of the causal processes involved in this uncoupling of depression from physical illness in old age could have important implications for interventions with patients who have comorbid mental-physical disorders.


Analysis of the data and preparation of this paper was supported by an unrestricted educational grant from Sanofi-Aventis. This report is carried out in conjunction with the World Health Organization World Mental Health (WMH) Survey Initiative. We thank the WMH staff for assistance with instrumentation, fieldwork, and data analysis. These activities were supported by the United States National Institute of Mental Health (R01MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, the Eli Lilly & Company Foundation, Ortho-McNeil Pharmaceutical, Inc., GlaxoSmithKline, Sanofi Aventis and Bristol-Myers Squibb. A complete list of WMH publications can be found at

The São Paulo Megacity Mental Health Survey is supported by the State of São Paulo Research Foundation (FAPESP) Thematic Project Grant 03/00204-3. The Colombian National Study of Mental Health (NSMH) is supported by the Ministry of Social Protection. The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123), the Piedmont Region (Italy), Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spain (FIS 00/0028), Ministerio de Ciencia y Tecnología, Spain (SAF 2000-158-CE), Departament de Salut, Generalitat de Catalunya, Spain, Instituto de Salud Carlos III (CIBER CB06/02/0046, RETICS RD06/0011 REM-TAP), and other local agencies and by an unrestricted educational grant from GlaxoSmithKline. The WMHI was funded by WHO (India)and helped by Dr R Chandrasekaran, JIPMER. The Israel National Health Survey is funded by the Ministry of Health with support from the Israel National Institute for Health Policy and Health Services Research and the National Insurance Institute of Israel. The World Mental Health Japan (WMHJ) Survey is supported by the Grant for Research on Psychiatric and Neurological Diseases and Mental Health (H13-SHOGAI-023, H14-TOKUBETSU-026, H16-KOKORO-013) from the Japan Ministry of Health, Labour and Welfare. The Lebanese National Mental Health Survey (LEBANON) is supported by the Lebanese Ministry of Public Health, the WHO (Lebanon), Fogarty International, Act for Lebanon, anonymous private donations to IDRAAC, Lebanon, and unrestricted grants from Janssen Cilag, Eli Lilly, GlaxoSmithKline, Roche, and Novartis. The Mexican National Comorbidity Survey (MNCS) is supported by The National Institute of Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science and Technology (CONACyT-G30544- H), with supplemental support from the PanAmerican Health Organization (PAHO). Te Rau Hinengaro: The New Zealand Mental Health Survey (NZMHS) is supported by the New Zealand Ministry of Health, Alcohol Advisory Council, and the Health Research Council. The South Africa Stress and Health Study (SASH) is supported by the US National Institute of Mental Health (R01-MH059575) and National Institute of Drug Abuse with supplemental funding from the South African Department of Health and the University of Michigan. The Ukraine Comorbid Mental Disorders during Periods of Social Disruption (CMDPSD) study is funded by the US National Institute of Mental Health (RO1-MH61905). The US National Comorbidity Survey Replication (NCS-R) is supported by the National Institute of Mental Health (NIMH; U01-MH60220) with supplemental support from the National Institute of Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; Grant 044708), and the John W. Alden Trust.


Conflict of Interest: The remaining authors report no conflict of interest.

Disclosure: Dr. Kessler has been a consultant for GlaxoSmithKline Inc., Kaiser Permanente, Pfizer Inc., Sanofi-Aventis, Shire Pharmaceuticals, and Wyeth-Ayerst; has served on advisory boards for Eli Lilly & Company and Wyeth-Ayerst; and has had research support for his epidemiological studies from Bristol-Myers Squibb, Eli Lilly & Company, GlaxoSmithKline, Johnson & Johnson Pharmaceuticals, Ortho-McNeil Pharmaceuticals Inc., Pfizer Inc., and Sanofi-Aventis.


1. Beekman AT, Copeland JR, Prince MJ. Review of community prevalence of depression in later life. Br J Psychiatry. 1999;174:307–311. [PubMed]
2. Blazer DG, 2nd, Hybels CF. Origins of depression in later life. Psychol Med. 2005;35:1241–1252. [PubMed]
3. Jorm AF. Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychol Med. 2000;30:11–22. [PubMed]
4. Schoevers RA, Geerlings MI, Deeg DJ, Holwerda TJ, Jonker C, Beekman AT. Depression and excess mortality: evidence for a dose response relation in community living elderly. Int J Geriatr Psychiatry. 2009;24:169–176. [PubMed]
5. Snowdon J. Depression in old age: questions concerning prevalence studies. Int J Geriatr Psychiatry. 1997;12:1043–1045. [PubMed]
6. Ernst C, Angst J. Depression in old age. Is there a real decrease in prevalence? A review. Eur Arch Psychiatry Clin Neurosci. 1995;245:272–287. [PubMed]
7. Drayer RA, Mulsant BH, Lenze EJ, Rollman BL, Dew MA, Kelleher K, Karp JF, Begley A, Schulberg HC, Reynolds CF., 3rd Somatic symptoms of depression in elderly patients with medical comorbidities. Int J Geriatr Psychiatry. 2005;20:973–982. [PubMed]
8. Bremmer MA, Beekman AT, Deeg DJ, Penninx BW, Dik MG, Hack CE, Hoogendijk WJ. Inflammatory markers in late-life depression: results from a population-based study. J Affect Disord. 2008;106:249–255. [PubMed]
9. Salaycik KJ, Kelly-Hayes M, Beiser A, Nguyen AH, Brady SM, Kase CS, Wolf PA. Depressive symptoms and risk of stroke: the Framingham Study. Stroke. 2007;38:16–21. [PubMed]
10. Bremmer MA, Deeg DJ, Beekman AT, Penninx BW, Lips P, Hoogendijk WJ. Major depression in late life is associated with both hypo- and hypercortisolemia. Biol Psychiatry. 2007;62:479–486. [PubMed]
11. Petronijevic M, Petronijevic N, Ivkovic M, Stefanovic D, Radonjic N, Glisic B, Ristic G, Damjanovic A, Paunovic V. Low bone mineral density and high bone metabolism turnover in premenopausal women with unipolar depression. Bone. 2008;42:582–590. [PubMed]
12. Kessler RC, Üstün TB, editors. The WHO World Mental Health Surveys: Global Perspectives on the Epidemiology of Mental Disorders. New York, NY: Cambridge University Press; 2008.
13. Blazer D, Hughes DC, George LK. The epidemiology of depression in an elderly community population. Gerontologist. 1987;27:281–287. [PubMed]
14. Kennedy GJ, Kelman HR, Thomas C. The emergence of depressive symptoms in late life: the importance of declining health and increasing disability. J Community Health. 1990;15:93–104. [PubMed]
15. Scott KM, Von Korff M, Alonso J, Angermeyer M, Bromet EJ, Bruffaerts R, de Girolamo G, de Graaf R, Fernandez A, Gureje O, et al. Age patterns in the prevalence of DSM-IV depressive/anxiety disorders with and without physical comorbidity. Psychol Med. 2008;38:1659–1669. [PMC free article] [PubMed]
16. World Bank. Data & Statistics, Country groups by income. 2009 [cited July 7, 2009]; Available from:,,contentMDK:20421402~pagePK:64133150~piPK:64133175~theSitePK:239419,00.html.
17. Heeringa SG, Wells EJ, Hubbard F, Mneimneh ZN, Chiu WT, Sampson NA, Berglund PA. Sample designs and sampling procedures. In: Kessler RC, Üstün TB, editors. The WHO World Mental Health Surveys: Global perspectives on the epidemiology of mental disorders. New York, NY: Cambridge University Press; 2008. pp. 14–32.
18. Kessler RC, Üstün TB. The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) Int J Methods Psychiatr Res. 2004;13:93–121. [PubMed]
19. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders, Research Version, Non-patient Edition (SCID-I/NP) New York, NY: Biometrics Research, New York State Psychiatric Institute; 2002.
20. Haro JM, Arbabzadeh-Bouchez S, Brugha TS, de Girolamo G, Guyer ME, Jin R, Lepine JP, Mazzi F, Reneses B, Vilagut G, et al. Concordance of the Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO World Mental Health surveys. Int J Methods Psychiatr Res. 2006;15:167–180. [PubMed]
21. Rush AJ, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, Markowitz JC, Ninan PT, Kornstein S, Manber R, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biological Psychiatry. 2003;54:573–583. [PubMed]
22. Leon AC, Olfson M, Portera L, Farber L, Sheehan DV. Assessing psychiatric impairment in primary care with the Sheehan Disability Scale. Int J Psychiatry Med. 1997;27:93–105. [PubMed]
23. Centers for Disease Control and Prevention. National Health Interview Survey. 2009 [cited July 20, 2009]; Available from:
24. Schoenborn CA, Adams PF, Schiller JS. Summary health statistics for the U.S. population: National Health Interview Survey, 2000. Vital Health Stat 10. 2003:1–83. [PubMed]
25. Knight M, Stewart-Brown S, Fletcher L. Estimating health needs: the impact of a checklist of conditions and quality of life measurement on health information derived from community surveys. J Public Health Med. 2001;23:179–186. [PubMed]
26. Baker M, Stabile M, Deri C. What do self-reported, objective, measures of health measure? J Human Resources. 2004;39:1067–1093.
27. Edwards WS, Winn DM, Kurlantzick V, Sheridan S, Berk ML, Retchin S, Collins JG. Evaluation of National Health Interview Survey diagnostic reporting. Vital Health Stat. 1994;2:1–116.
28. Revicki DA, Rentz AM, Dubois D, Kahrilas P, Stanghellini V, Talley NJ, Tack J. Gastroparesis Cardinal Symptom Index (GCSI): development and validation of a patient reported assessment of severity of gastroparesis symptoms. Qual Life Res. 2004;13:833–844. [PubMed]
29. Wolter KM. Introduction to Variance Estimation. New York, NY: Springer-Verlag; 1985.
30. Research Triangle Institute. SUDAAN: Professional Software for Survey Data Analysis. Version 8.0.1. Research Triangle Park, NC: Research Triangle Institute; 2002.
31. Simon GE, VonKorff M. Reevaluation of secular trends in depression rates. Am J Epidemiol. 1992;135:1411–1422. [PubMed]
32. Weissman MM, Bruce ML, Leaf PJ, Florio LP, Holzer C. Affective disorders. In: Robins LN, Regier DA, editors. Psychiatric Disorders in America: The Epidemiologic Catchment Area Study. New York: Free Press; 1991. pp. 53–80.
33. Carvalhais SM, Lima-Costa MF, Peixoto SV, Firmo JO, Castro-Costa E, Uchoa E. The influence of socio-economic conditions on the prevalence of depressive symptoms and its covariates in an elderly population with slight income differences: the Bambui Health and Aging Study (BHAS) Int J Soc Psychiatry. 2008;54:447–456. [PubMed]
34. Chiao C, Weng LJ, Botticello A. Do older adults become more depressed with age in Taiwan? The role of social position and birth cohort. J Epidemiol Community Health. 2009;63:625–632. [PubMed]
35. Jang SN, Cho SI, Chang J, Boo K, Shin HG, Lee H, Berkman LF. Employment Status and Depressive Symptoms in Koreans: Results From a Baseline Survey of the Korean Longitudinal Study of Aging. J Gerontol B Psychol Sci Soc Sci. 2009 [PubMed]
36. Kilzieh N, Rastam S, Maziak W, Ward KD. Comorbidity of depression with chronic diseases: a population-based study in Aleppo, Syria. Int J Psychiatry Med. 2008;38:169–184. [PMC free article] [PubMed]
37. Knauper B, Cannell CF, Schwarz N, Bruce ML, Kessler RC. Improving the accuracy of major depression age of onset reports in the US National Comorbidity Survey. Int J Methods Psychiatr Res. 1999;8:39–48.
38. Corruble E, Gorwood P, Falissard B. Association between age of onset and symptom profiles of late-life depression. Acta Psychiatr Scand. 2008;118:389–394. [PubMed]
39. Mitchell AJ, Subramaniam H. Prognosis of depression in old age compared to middle age: a systematic review of comparative studies. Am J Psychiatry. 2005;162:1588–1601. [PubMed]
40. Sargeant JK, Bruce ML, Florio LP, Weissman MM. Factors associated with 1-year outcome of major depression in the community. Arch Gen Psychiatry. 1990;47:519–526. [PubMed]
41. Koenig HG, Meador KG, Shelp F, Goli V, Cohen HJ, Blazer DG. Major depressive disorder in hospitalized medically ill patients: an examination of young and elderly male veterans. J Am Geriatr Soc. 1991;39:881–890. [PubMed]
42. Newmann JP, Klein MH, Jensen JE, Essex MJ. Depressive symptom experiences among older women: a comparison of alternative measurement approaches. Psychol Aging. 1996;11:112–126. [PubMed]
43. Sneed JR, Rindskopf D, Steffens DC, Krishnan KR, Roose SP. The vascular depression subtype: evidence of internal validity. Biol Psychiatry. 2008;64:491–497. [PMC free article] [PubMed]
44. Kessler RC, Birnbaum H, Bromet E, Hwang I, Sampson NA, Shahly V. Age differences in major depression: results from the National Comorbidity Survey Replication (NCS-R) Psychol Med. in press. [PMC free article] [PubMed]
45. Henderson AS, Montgomery IM, Williams CL. Psychological immunisation. A proposal for preventive psychiatry. Lancet. 1972;1:1111–1112. [PubMed]
46. Diehl M, Coyle N, Labouvie-Vief G. Age and sex differences in strategies of coping and defense across the life span. Psychol Aging. 1996;11:127–139. [PubMed]
47. Charles ST, Carstensen LL. Unpleasant situations elicit different emotional responses in younger and older adults. Psychol Aging. 2008;23:495–504. [PMC free article] [PubMed]
48. Felton BJ, Revenson TA. Age differences in coping with chronic illness. Psychol Aging. 1987;2:164–170. [PubMed]
49. McEwen BS. Physiology and neurobiology of stress and adaptation: central role of the brain. Physiol Rev. 2007;87:873–904. [PubMed]