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. Author manuscript; available in PMC: 2010 Mar 30.
Published in final edited form as: Lancet. 2007 Sep 8;370(9590):841–850. doi: 10.1016/S0140-6736(07)61414-7

Worldwide Use of Mental Health Services for Anxiety, Mood, and Substance Disorders: Results from 17 Countries in the WHO World Mental Health (WMH) Surveys

Philip S Wang 1,13, Sergio Aguilar-Gaxiola 2, Jordi Alonso 3, Matthias C Angermeyer 4, Guilherme Borges 5, Evelyn J Bromet 6, Ronny Bruffaerts 7, Giovanni de Girlolamo 8, Ron de Graaf 9, Oye Gureje 10, Josep Maria Haro 11, Elie G Karam 12, Ronald C Kessler 13, Viviane Kovess 14, Michael C Lane 13, Sing Lee 15, Daphna Levinson 16, Yutaka Ono 17, Maria Petukhova 13, José Posada-Villa 18, Soraya Seedat 19, J Elisabeth Wells 20
PMCID: PMC2847360  NIHMSID: NIHMS176783  PMID: 17826169

Abstract

Background

Mental disorders are leading causes of disability worldwide, including in low- and middle-income countries least able to bear such burdens. To begin understanding and improving their treatment, we describe mental health care in 17 countries of the WHO World Mental Health (WMH) Survey Initiative.

Methods

Face-to-face household surveys were conducted among 84,848 community adult respondents in low- or middle- (Colombia, Lebanon, Mexico, Nigeria, China, South Africa, Ukraine) and high-income countries (Belgium, France, Germany, Israel, Italy, Japan, Netherlands, New Zealand, United States). 12-month DSM-IV disorders, their severity, and mental health service use were assessed with the WMH Composite International Diagnostic Interview.

Findings

Respondents using any 12-month mental health services (57 [1.6%; Nigeria] to 1477 [17.9%; US]) was generally lower in less-developed than developed countries and tended to track with countries’ percentages of GDP spent on health care. Although disorder seriousness was related to service use, only 5 (11.0%; China) to 46 (62.1%; Belgium) of severe cases received any care in the prior year. General medical sectors were the largest sources of mental health services. Among respondents initiating treatments, 152 (70.2%; Germany) to 129 (94.5%; Italy) received any follow-up care and 1 (10.4%; Nigeria) to 113 (42.3%; France) received treatments meeting minimal standards for adequacy. Being male, married, less-educated, and in the extremes of age or income were associated with undertreatment.

Interpretation

Unmet needs for mental health treatment are pervasive and especially dire in less-developed countries. Alleviating these unmet needs will require expansion and optimal allocation of treatment resources.

Keywords: Mental disorders, mental health service use, WMH surveys

BACKGROUND

Neuropsychiatric conditions are the leading causes of disability worldwide, accounting for 37% of all healthy life years lost from disease; they are the most disabling conditions even in low- and middle-income countries, which may be least able to bear such burdens.1 Although efficacious and tolerable treatments are increasingly available, even economically-advantaged societies experience competing priorities and budgetary constraints.2 Knowing how to provide effective mental health care has become imperative worldwide.3 Unfortunately, most countries suffer from a lack of data to guide decisions, absent or competing visions for resources, and near constant pressures to cut insurance and entitlements.4

How can countries redesign their mental health care systems and optimally allocate resources? A first step is documenting the services currently being used as well as the extent and nature of unmet needs for treatment. A second step may be conducting cross-national comparisons of service use and unmet needs in countries with different mental health care systems. Such comparisons can help uncover optimal financing, national policies, and delivery systems for mental health care. Unfortunately, few cross-national studies are available.5,6

For these reasons, WHO established the World Mental Health (WMH) Survey Initiative in 1998.7 Coordinated surveys on mental disorders, their severity, impairments, and treatments have been implemented in 28 less-developed and developed countries. The current report describes the levels, types and adequacy of mental health service use in 17 countries where WMH surveys are complete. We also examine unmet needs for treatment among strata defined by the seriousness of mental disorders. Finally, we identify socio-demographic correlates of unmet needs for treatment to guide design and targeting of future resources, policies, and interventions.

METHODS

Respondent Samples

WMH surveys were carried out in the following regions (and countries): Africa (Nigeria; South Africa); the Americas (Colombia; Mexico; United States), Asia and the Pacific (Japan; New Zealand; Beijing and Shanghai in the Peoples Republic of China), Europe (Belgium; France; Germany; Italy; the Netherlands; Spain; Ukraine); and the Middle East (Israel; Lebanon). 7 Using World Bank criteria,8 countries were classified as low-income (Nigeria), lower middle-income (China, Columbia, South Africa, Ukraine), higher middle-income (Lebanon, Mexico), and high-income (all others). Conventional multi-stage clustered area probability designs were generally employed (exceptions being countries with population registries, which were used to avoid within-household probability-of-selection weights) to select mainly nationally representative samples and the remainder focusing on major metropolitan areas (see Table 1). Trained lay interviewers conducted surveys face-to-face and returned to households up to 15 times when respondents were not available as well as used standardized refusal conversion procedures to improve response rates. The total sample size of those aged 18 and older was 84,848, with individual country samples ranging from 2372 in the Netherlands to 12,790 in New Zealand. The weighted average response rate across all countries was 71.1%, with individual country rates ranging from 45.9% (France) to 87.7% (Colombia). Non-respondent surveys have been carried out in many WMH surveys to learn about people who declined participation.

Table 1.

Sample Characteristics

Country Percent of Health budget to GDP* Survey1 Sample Characteristics2 Field Dates Age Range Sample Size Response Rate
Part I Part II Part II and Age ≤ 444
Low
    Nigeria 3.4 NSMHW Stratified multistage clustered area probability sample of households in 21 of the 36 states in the country, representing 57% of the national population. The surveys were conducted in Yoruba, Igbo, Hausa and Efik languages. 2002-3 18+ 6752 2143 1203 79.3
Low-Middle
    PRC6 Beijing 5.5 B-WMH Stratified multistage clustered area probability sample of household residents in the Beijing metropolitan area. 2002-3 18+ 2633 914 307 74.8
    PRC6 Shanghai 5.5 S-WMH Stratified multistage clustered area probability sample of household residents in the Shanghai metropolitan area. 2002-3 18+ 2568 714 263 74.6
    Colombia 5.5 NSMH Stratified multistage clustered area probability sample of household residents in all urban areas of the country (approximately 73% of the total national population) 2003 18-65 4426 2381 1731 87.7
    South Africa 8.6 SASH Stratified multistage clustered area probability sample of household residents. NR 2003-4 18+ 4315 -- -- 87.1
    Ukraine 4.3 CMDPSD Stratified multistage clustered area probability sample of household residents. NR 2002 18+ 4725 1720 541 78.3
High-Middle
    Lebanon 12.2 LEBANON Stratified multistage clustered area probability sample of household residents. NR 2002-3 18+ 2857 1031 595 70.0
    Mexico 6.1 M-NCS Stratified multistage clustered area probability sample of household residents in all urban areas of the country (approximately 75% of the total national population). 2001-2 18-65 5782 2362 1736 76.6
High
    Belgium 8.9 ESEMeD Stratified multistage clustered probability sample of individuals residing in households from the national register of Belgium residents. NR 2001-2 18+ 2419 1043 486 50.6
    France 9.6 ESEMeD Stratified multistage clustered sample of working telephone numbers merged with a reverse directory (for listed numbers). Initial recruitment was by telephone, with supplemental in-person recruitment in households with listed numbers. NR 2001-2 18+ 2894 1436 727 45.9
    Germany 10.8 ESEMeD Stratified multistage clustered probability sample of individuals from community resident registries. NR 2002-3 18+ 3555 1323 621 57.8
    Italy 8.4 ESEMeD Stratified multistage clustered probability sample of individuals from municipality resident registries. NR 2001-2 18+ 4712 1779 853 71.3
    Israel 8.7 NHS Stratified multistage clustered area probability sample of household residents. NR 2002-4 21+ 4859 -- -- 72.6
    Japan 8.0 WMHJ2002-2003 Un-clustered two-stage probability sample of individuals residing in households in four metropolitan areas (Fukiage, Kushikino, Nagasaki, Oyayama) 2002-3 20+ 2436 887 282 56.4
    Netherlands 8.9 ESEMeD Stratified multistage clustered probability sample of individuals residing in households that are listed in municipal postal registries. NR 2002-3 18+ 2372 1094 516 56.4
    New Zealand5 8.3 NZMHS Stratified multistage clustered area probability sample of household residents. NR 2004-5 16+ 12992 7435 4242 73.3
    Spain 7.5 ESEMeD Stratified multistage clustered area probability sample of household residents. NR 2001-2 18+ 5473 2121 960 78.6
    United States 13.9 NCS-R Stratified multistage clustered area probability sample of household residents. NR 2002-3 18+ 9282 5692 3197 70.9
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*

World Health Organization. Project Atlas: Resources for Mental Health and Neurological Disorders. Available at: www.who.int/globalatlas/dataQuery/default.asp.

1

ESEMeD (The European Study Of The Epidemiology Of Mental Disorders); NSMH (The Colombian National Study of Mental Health); NHS (Israel National Health Survey); WMHJ2002-2003 (World Mental Health Japan Survey); LEBANON (Lebanese Evaluation of the Burden of Ailments and Needs of the Nation); M-NCS (The Mexico National Comorbidity Survey); NZMHS (New Zealand Mental Health Survey); NSMHW (The Nigerian Survey of Mental Health and Wellbeing); B-WMH (The Beijing World Mental Health survey); S-WMH (The Shanghai World Mental Health Survey); SASH (South Africa Health Survey); CMDPSD (Comorbid Mental Disorders during Periods of Social Disruption); NCS-R (The US National Comorbidity Survey Replication).

2

Most WMH surveys are based on stratified multistage clustered area probability household samples in which samples of areas equivalent to counties or municipalities in the US were selected in the first stage followed by one or more subsequent stages of geographic sampling (e.g., towns within counties, blocks within towns, households within blocks) to arrive at a sample of households, in each of which a listing of household members was created and one or two people were selected from this listing to be interviewed. No substitution was allowed when the originally sampled household resident could not be interviewed. These household samples were selected from Census area data in all countries other than France (where telephone directories were used to select households) and the Netherlands (where postal registries were used to select households). Several WMH surveys (Belgium, Germany, Italy) used municipal resident registries to select respondents without listing households. The Japanese sample is the only totally un-clustered sample, with households randomly selected in each of the four sample areas and one random respondent selected in each sample household. Nine of the 15 surveys are based on nationally representative (NR) household samples, while two others are based on nationally representative household samples in urbanized areas (Colombia, Mexico).

3The response rate is calculated as the ratio of the number of households in which an interview was completed to the number of households originally sampled, excluding from the denominator households known not to be eligible either because of being vacant at the time of initial contact or because the residents were unable to speak the designated languages of the survey.

4

All countries, with the exception of Nigeria, PRC Beijing, PRC Shanghai, and Ukraine (which were age restricted to ≤ 39) were age restricted to ≤ 44.

5

For purposes of cross-national analysis the New Zealand sample was restricted to ≤ 18 years of age for a total n of 12790.

6

People's Republic of China

All respondents completed Part I which contained core diagnostic assessments. All Part I respondents who met criteria for any disorder and a sub-sample of approximately 25% of others were administered Part II which assessed correlates, service use, and disorders of secondary interest. Data were weighted to adjust for this differential sampling of Part II respondents, differential probabilities of selection within households, and to match samples to population socio-demographic distributions.

To help ensure that valid estimates of the prevalences of mental disorders could be made across potentially different cultural settings, a standardized WHO protocol was employed to develop, pilot-test, review, translate, back-translate, and harmonize all WMH-CIDI interview schedules. Furthermore, standardized interviewer training procedures were followed and are described in more detail elsewhere.7 Informed consent was required before beginning interviews in all countries. Procedures for obtaining informed consent and protecting human subjects were approved and monitored by the Institutional Review Boards of organizations coordinating surveys in each country.

12-Month Mental Disorders

The WMH-CIDI, a fully structured diagnostic interview, was used to assess the presence of 12-month mental disorders using the definitions and criteria of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). The disorders considered in this analysis include anxiety (agoraphobia; generalized anxiety disorder; panic disorder; post-traumatic stress disorder; social phobia; specific phobia), mood (bipolar disorder including bipolar I and II; dysthymia; major depressive disorder), and substance disorders (alcohol and drug abuse and dependence). All diagnoses were made with CIDI organic exclusion rules. WHO-CIDI Field Trials and clinical calibration studies provide evidence that the WMH-CIDI assesses the disorders considered here with generally acceptable reliability and validity.9,10 Cross-national comparisons of the validity of WMH-CIDI diagnoses are currently underway.

Severity of Mental Disorders

Because the simple presence of a diagnosis may not indicate the level of need for services, we classified WMH-CIDI mental disorders as serious, moderate, or mild. Serious disorders were defined as: bipolar I disorder or substance dependence with a physiological dependence syndrome; making a suicide attempt in conjunction with any other disorder; reporting severe role impairment due to a mental disorder in at least two areas of functioning measured by disorder-specific Sheehan Disability Scales (SDS);11 or having overall functional impairment from any disorder consistent with a Global Assessment of Functioning (GAF)12 score of 50 or less. Disorders not classified as serious were classified as moderate if the respondent had: substance dependence without a physiological dependence syndrome; or at least moderate interference in any SDS domain. All other disorders were classified as mild. While the accuracy of this measure of disorder seriousness has not been firmly established, some evidence for its validity comes from statistically significant monotonic associations in all but two surveys between disorder severity and days in the prior year that respondents were totally unable to carry out normal daily activities because of disorders.7

12-Month Mental Health Service Use

Services received in the prior 12 months were assessed by asking respondents if they ever saw any of several types of professionals, either as an outpatient or inpatient, for problems with emotions, nerves, mental health, or use of alcohol or drugs. Included were mental health professionals (e.g., psychiatrist, psychologist), general medical professionals (e.g., general practitioner, occupational therapist), religious counselors (e.g., minister, sheikh), and traditional healers (e.g., herbalist, spiritualist). Examples of these types of providers were presented in a Respondent Booklet as a visual recall aid and varied somewhat across countries depending on local circumstances. Follow-up questions asked about age at first and most recent contacts as well as number and duration of visits in the past 12 months.

Reports of 12-month service use were classified into the following sectors: mental health specialty [MHS](psychiatrist, psychologist, other mental health professional in any setting, social worker or counselor in a mental health specialty setting, use of a mental health hotline); general medical [GM](primary care doctor, other general medical doctor, nurse, any other health professional not previously mentioned); human services [HS](religious or spiritual advisor, social worker or counselor in any setting other than a specialty mental health setting); and complementary and alternative medicine [CAM](any other type of healer such as chiropractors, participation in an internet support group, participation in a self-help group).

Continuity and Adequacy of Treatments

A definition of follow-up care—that could be applied in both low- as well as high-resource countries—consisted of receiving ≥2 visits to any service sector (1 visit for presumptive evaluation/diagnosis and ≥1 visit for treatment or monitoring). Because respondents who began treatments shortly before interview may not have had time to fulfill these requirements, anyone reporting being in ongoing treatment at interview was considered to have met this definition.

A second more rigorous definition identified those who potentially may have received minimally adequate treatment according to available evidence-based guidelines.13-15 This definition consisted of receiving either pharmacotherapy (≥1 month of a medication plus ≥4 visits to any type of medical doctor) or psychotherapy (≥8 visits with any professional). The decision to require ≥4 physician visits for pharmacotherapy was based on the fact that ≥4 visits for medication evaluation, initiation and monitoring are generally recommended during the acute and continuation phases of treatment.13-15 At least eight sessions were required for psychotherapy based on the fact that clinical trials demonstrating effectiveness have generally included ≥8 visits.13-15 Any respondent in ongoing treatment was considered to have met this definition.

Socio-demographic predictor variables

Socio-demographic variables included: cohort (defined by age at interview and categorized as <35, 35-49, 50-64, 65+); gender; completed years of education (four country-specific categories); marital status (married-cohabitating, separated-widowed-divorced, never married); and family income in relation to country medians (low, low average, high average, high).

Analysis Procedures

We first computed the proportions in treatment in any or specific sectors, and probabilities of service use meeting criteria for follow-up care or potentially minimally adequate care. We then examined how these basic patterns of service use differed across strata defined by the severity of disorders. Logistic regression analysis was used to study socio-demographic predictors of receiving any 12-month services. Standard errors were estimated using the Taylor series method as implemented in SUDAAN.16 Two-sided significance tests at the .05 level were made in logistic regression analyses using Wald χ2 tests based on coefficient variance–covariance matrices adjusted for design effects using the Taylor series method.

FINDINGS

12-Month Use of Mental Health Services

Respondents using any mental health services in the prior 12 months varied significantly (from 57 [1.6%] in Nigeria to 1477 [17.9%] in the US; X216=764.6, p<.0001), with generally fewer in low- or middle-income vs. high-income countries (Table 2). The proportions receiving services also tended to correspond with countries’ overall spending on health care (see proportions of health budgets to GDP in Table 1).17 The largest proportions used GM followed by MHS sectors (with the exceptions of Mexico, Columbia, and Israel, where this was reversed); smaller proportions used HS and CAM sectors. The right hand columns of Table 2 present proportions using specific sectors among respondents receiving any 12-month services. With the exception of the two Latin American countries and Israel, the sectors used most frequently by treated respondents were GM followed by MHS; again, smaller proportions used HS and CAM.

Table 2.

Twelve-month service use by sectors in the WMH surveys

Among Respondents*
 Among Respondents Using Services†
Country income level Any Treatment Mental Health Specialty General Medical Human Services CAM‡ Mental Health Specialty General Medical Human Services CAM‡
N
 %
 se
 N
 %
 se
 N
 %
 se
 N
 %
 se
 N
 %
 se
 N
 %
 se
 N
 %
 se
 N
 %
 se
 N
 %
 se
Low
    Nigeria 57 1.6 0.3 5 0.1 0.1 42 1.1 0.2 14 0.5 0.2 1 0.0 0.0 5 8.3 3.7 42 66.6 10.1 14 30.9 10.2 1 1.1 1.1
Low-Middle
    China 74 3.4 0.6 19 0.6 0.2 41 2.3 0.5 6 0.3 0.1 18 0.7 0.3 19 18.0 5.9 41 68.5 6.8 6 7.4 3.8 18 21.2 7.3
    Colombia 217 5.5 0.6 126 3.0 0.4 82 2.3 0.4 19 0.5 0.2 10 0.2 0.1 126 53.4 4.8 82 41.7 5.1 19 9.2 2.8 10 3.7 1.4
    South Africa 675 15.4 1.0 108 2.5 0.4 440 10.2 0.8 169 3.7 0.4 161 3.7 0.3 108 16.3 2.2 440 66.4 2.5 169 24.0 1.9 161 23.8 2.1
    Ukraine 212 7.2 0.8 39 1.2 0.3 135 4.0 0.7 47 1.7 0.4 29 1.0 0.3 39 17.2 3.8 135 55.4 7.1 47 24.1 5.1 29 14.4 4.0
High-Middle
    Lebanon 77 4.4 0.6 18 1.0 0.3 53 2.9 0.5 11 0.8 0.3 0 0.0 0.0 18 22.3 5.7 53 66.6 7.4 11 17.5 6.1 0 0.0 0.0
    Mexico 240 5.1 0.5 121 2.8 0.3 92 1.7 0.3 15 0.3 0.1 45 1.0 0.2 121 53.6 4.2 92 33.1 4.0 15 6.2 2.0 45 20.0 3.4
High
    Belgium 187 10.9 1.4 96 5.2 0.7 147 8.2 1.3 6 0.4 0.2 12 0.7 0.3 96 47.9 4.4 147 75.5 3.8 6 3.7 1.8 12 6.5 2.9
    France 272 11.3 1.0 111 4.4 0.5 214 8.8 0.9 10 0.4 0.2 9 0.5 0.3 111 39.4 3.6 214 78.4 3.3 10 3.4 1.2 9 4.3 2.1
    Germany 183 8.1 0.8 100 3.9 0.6 102 4.2 0.6 16 1.0 0.4 15 0.6 0.2 100 48.5 4.8 102 51.7 5.1 16 12.2 4.5 15 7.4 2.5
    Israel 421 8.8 0.4 215 4.4 0.3 169 3.6 0.3 71 1.6 0.2 42 0.8 0.1 215 50.5 2.6 169 40.4 2.6 71 18.0 2.0 42 9.6 1.5
    Italy 141 4.3 0.4 55 2.0 0.3 107 3.0 0.3 15 0.4 0.1 4 0.1 0.0 55 47.1 5.1 107 70.9 4.8 15 9.1 2.4 4 1.5 0.7
    Japan 92 5.6 0.9 43 2.4 0.5 47 2.8 0.5 8 0.8 0.5 13 0.6 0.2 43 42.5 5.5 47 50.2 8.2 8 15.0 6.7 13 11.1 4.7
    Netherlands 202 10.9 1.2 105 5.5 1.0 141 7.7 1.1 14 0.6 0.2 27 1.5 0.4 105 51.0 6.0 141 71.2 6.1 14 5.4 1.6 27 13.5 3.8
    New Zealand 1592 13.8 0.5 585 5.2 0.3 1122 9.2 0.4 203 1.6 0.2 265 2.6 0.3 585 37.6 1.8 1122 66.5 1.8 203 11.5 1.1 265 19.0 1.7
    Spain 375 6.8 0.5 200 3.6 0.4 249 4.4 0.4 11 0.1 0.1 20 0.2 0.1 200 52.2 3.6 249 64.9 3.4 11 2.1 0.8 20 3.5 1.0
    USA 1477 17.9 0.7 738 8.8 0.5 773 9.3 0.4 266 3.4 0.3 247 2.8 0.2 738 48.8 1.7 773 51.8 1.3 266 18.8 1.1 247 15.6 1.0
χ 2 16 764.6 (<.001) 679.6 (<.001) 732.2 (<.001) 262.9 (<.001) 388.0 (<.001) 232.4 (<.001) 207.3 (<.001) 201.8 (<.001) 223.1 (<.001)
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*

Percentages among respondents are based on entire part II samples.

†

Percentages are based on respondents using any 12-month services.

‡

CAM: Complementary and alternative medicine.

Service Use by Severity of Mental Disorders

Significant, generally monotonic relationships existed between disorder severity and probability of service use in every country except China (Table 3). In spite of these dose-response relationships, only 5 (11.0%; China) to 46 (62.1%; Belgium) of serious cases received any service in the prior year. Lower proportions of moderate and mild cases generally received services in the prior year. Numerically small but still meaningful numbers of those apparently without disorders used treatments (ranging from 29 [1.0%; Nigeria] to 479 [9.7%; US]). Cross-national differences were significant in all severity categories, with generally less service use in low- and middle-income vs. high-income countries.

Table 3.

Percentages using 12-month services by severity of mental disorders in the WMH surveys†

Test of Difference in Probability of Treatment By Severity
Country income level Country Severe Moderate Mild None
N
 %‡
 se
 N
 %‡
 se
 N
 %‡
 se
 N
 %‡
 se
 χ 23
 (p-value)
Low
Nigeria 8 21.3 11.9 6 13.8 7.4 14 10.0 3.0 29 1.0 0.3 27.7* (<.001)
Low-Middle
China 5 11.0 5.4 11 23.5 10.9 3 1.7 1.2 55 2.9 0.6 16.1* (.001)
Colombia 54 27.8 4.8 47 10.3 2.0 30 7.8 1.6 86 3.4 0.6 96.1* (<.001)
South Africa 45 26.2 3.6 66 26.6 3.9 67 23.1 3.2 497 13.4 0.9 41.0* (<.001)
Ukraine 49 25.7 3.2 68 21.2 3.6 19 7.6 2.6 76 4.4 0.8 81.2* (<.001)
High-Middle
Lebanon 22 20.1 5.2 19 11.6 3.1 7 4.0 1.6 29 3.0 0.7 34.9* (<.001)
Mexico 52 25.8 4.3 53 17.9 2.9 33 11.9 2.3 102 3.2 0.4 132.9* (<.001)
High
Belgium 46 62.1 9.2 30 38.4 8.3 13 12.7 4.6 98 6.8 1.1 227.1* (<.001)
France 56 48.0 6.4 70 29.4 4.0 43 22.4 3.4 103 7.0 1.1 82.6* (<.001)
Israel 81 53.9 4.0 54 32.6 3.7 19 14.4 3.2 267 6.0 0.4 368.1* (<.001)
Germany 30 40.6 8.9 39 23.9 4.7 27 20.5 5.2 87 5.9 0.9 54.5* (<.001)
Italy 29 51.6 6.5 38 25.9 4.2 21 17.8 4.5 53 2.2 0.4 192.7* (<.001)
Japan§ 10 24.2 5.0 16 24.2 5.0 9 12.8 4.4 57 4.5 0.9 44.5*§ (<.001)
Netherlands 57 49.2 6.6 36 31.3 7.2 15 16.1 6.0 94 7.7 1.3 66.8* (<.001)
New Zealand 458 56.6 2.2 421 39.8 1.9 184 22.2 1.9 529 7.3 0.5 644.8* (<.001)
Spain 79 58.7 4.9 93 37.4 5.0 35 17.3 4.3 168 3.9 0.5 446.1* (<.001)
USA 385 59.7 2.4 394 39.9 1.3 219 26.2 1.7 479 9.7 0.6 668.5* (<.001)
        χ 2 16 ∥ 186.9* (<.001) 145.6* (<.001) 104.1* (<.001) 330.0* (<.001)
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*

Significant at the .05 level, two-sided test.

†

Percents based on entire part II samples.

‡

Percents are based on respondents using any services within each level of severity.

§

Severe and moderate cases were combined into 1 category for Japan and the percent using services was displayed in both columns. The χ2 test was two degrees of freedom for this country.

∥

χ216 is from a model predicting any 12-month service use among respondents within each level of severity.

Mental Health Specialty Use by Severity of Disorders

Table 4 presents associations between disorder severity and use of the MHS sector among respondents receiving services. Statistical power was low in these analyses due to the small numbers of treated respondents. Nevertheless, significant relationships between severity and use of MHS sectors existed in only 6 of 17 countries. Even in those countries where such a relationship exists, meaningful proportions of mild and non-cases consume MHS services.

Table 4.

Percentages using mental health specialty sectors among respondents using any services in the WMH surveys†

Test of Difference in Probability of Treatment By Severity
Country income level Country Severe Moderate Mild None χ2 (p-value)
N
 %‡
 se
 N
 %‡
 se
 N
 %‡
 se
 N
 %‡
 se
 (1 or 3 df)∥
Low
Nigeria 1 -§ -§ 0 -§ -§ 3 9.5 4.5 1 9.5 4.5 1.4 (.235)
Low Middle
China 3 -§ -§ 2 -§ -§ 3 16.7 6.8 11 16.7 6.8 0.2 (.644)
Colombia 30 62.9 8.3 28 47.1 8.0 19 62.2 10.3 49 48.8 8.3 1.9 (.599)
South Africa 14 35.9 7.6 13 19.7 5.9 12 15.5 5.6 69 14.1 2.0 15.4* (.002)
Ukraine 15 34.8 6.8 9 16.2 8.2 3 -§ -§ 12 12.5 5.3 8.6* (.035)
High-Middle
Lebanon 7 35.6 9.2 5 35.6 9.2 1 14.0 7.3 5 14.0 7.3 3.1 (.077)
Mexico 26 60.3 8.0 30 59.1 6.8 15 51.0 11.2 50 50.4 7.0 1.1 (.778)
High
Belgium 25 58.6 9.8 17 48.6 10.9 6 -§ -§ 48 43.4 7.0 1.5 (.677)
France 27 49.7 8.6 26 33.8 8.3 13 34.1 7.0 45 40.1 6.9 2.4 (.502)
Germany 17 46.4 12.1 27 68.9 8.9 12 -§ -§ 44 47.4 6.2 9.8* (.020)
Israel 39 47.4 5.7 31 55.7 7.1 10 -§ -§ 135 50.0 3.3 1.1 (.765)
Italy 10 -§ -§ 11 33.8 10.6 7 -§ -§ 27 63.6 7.5 7.0 (.071)
Japan 7 -§ -§ 13 -§ -§ 5 34.2 6.0 18 34.2 6.0 12.0* (<.001)
Netherlands 34 66.9 7.3 22 45.2 15.5 7 -§ -§ 42 47.5 9.2 2.5 (.483)
New Zealand 232 57.4 2.9 140 34.7 3.4 49 26.3 4.3 164 32.0 2.9 63.1* (<.001)
Spain 52 65.4 7.3 55 61.3 5.5 19 41.2 10.4 74 45.8 6.5 5.6 (.131)
USA 250 66.0 2.4 182 45.0 3.3 91 41.5 3.1 215 43.8 2.6 59.6* (<.001)
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*

Significant at the .05 level, two-sided test.

†

Percents based on entire part II samples.

‡

Percents are those in any mental health treatment among respondents using any services within each level of severity.

§

Percents not reported if the number of respondents using any services in a level of severity < 30.

∥

One degree of freedom χ2 tests were performed for Nigeria, Lebanon, Japan and China, where combined Severe and Moderate was compared against combined Mild and None category.

Three degree of freedom tests were performed for all other countries.

Continuity and Adequacy of Treatments

Among respondents initiating treatments, those receiving any follow-up care varied significantly between 152 (70.2%; Germany) to 129 (94.5%; Italy)(Table 5). Although the proportions were generally smaller proportions in low- or middle- vs. high-income countries, there were notable exceptions to this pattern. Significant relationships between disorder severity and the probability of receiving follow-up care existed in only seven countries. As a result, receiving at least some follow-up care among treatment initiators was by no means universal among severe cases and it was quite common among apparent non-cases.

Table 5.

Percentages receiving follow-up treatment† among respondents using services in the WMH surveys

Test of Difference in Probability of Follow-up Treatment By Severity
Country income level Country Any Severity Severe Moderate Mild None χ2 (p-value)
N
 %‡
 se
 N
 %§
 se
 N
 %§
 se
 N
 %§
 se
 N
 %§
 se
 (1 or 3 df)
Low
Nigeria 47 76.3 8.7 6 -∥ -∥ 6 -∥ -∥ 13 74.6 9.2 22 74.6 9.2 0.4 (.512)
Low-Middle
China 56 77.6 6.0 4 -∥ -∥ 6 -∥ -∥ 3 80.8 6.8 43 80.8 6.8 1.0 (.328)
Colombia 158 72.0 4.3 49 92.6 3.5 31 73.1 7.9 20 61.7 11.3 58 63.6 7.9 12.3* (.006)
South Africa 601 89.1 1.7 42 93.9 3.9 63 95.7 3.0 58 87.4 3.7 438 88.0 2.2 3.0 (.394)
Ukraine 167 79.1 3.8 44 92.3 3.6 51 82.3 4.5 14 -∥ -∥ 58 71.8 7.0 12.5* (.006)
High-Middle
Lebanon 62 78.9 6.9 17 84.1 4.4 15 84.1 4.4 7 75.7 10.2 23 75.7 10.2 0.8 (.367)
Mexico 180 74.5 4.4 40 85.5 4.2 41 76.6 6.7 25 84.3 6.9 74 67.8 7.7 6.0 (.110)
High
Belgium 165 84.3 3.9 42 84.4 9.5 27 84.3 10.4 12 -∥ -∥ 84 83.1 5.1 3.1 (.376)
France 235 86.0 3.9 49 87.5 4.7 65 97.3 1.6 35 89.7 4.4 86 80.0 6.9 7.8 (.051)
Germany 152 70.2 5.1 28 89.2 8.5 37 97.1 0.7 23 -∥ -∥ 64 61.1 7.4 66.4* (<.001)
Israel 364 86.1 1.8 73 90.7 3.2 48 89.2 4.2 17 -∥ -∥ 226 83.6 2.4 3.3 (.344)
Italy 129 94.5 1.5 28 -∥ -∥ 34 93.1 3.7 19 -∥ -∥ 48 94.4 2.4 1.3 (.728)
Japan 83 89.8 2.6 9 -∥ -∥ 13 -∥ -∥ 9 91.2 3.3 52 91.2 3.3 0.9 (.332)
Netherlands 183 85.9 4.3 53 96.4 2.1 35 98.9 1.2 15 -∥ -∥ 80 78.5 7.2 10.0* (.007)
New Zealand 1394 85.7 1.3 421 92.5 1.4 368 88.7 1.8 151 83.5 3.2 454 81.0 2.8 15.1* (.002)
Spain 341 88.8 2.6 73 95.3 1.9 86 92.6 3.0 33 90.8 6.2 149 84.7 4.7 5.8 (.121)
USA 1313 86.8 1.4 362 93.2 1.7 354 88.4 2.0 187 83.0 2.9 410 83.3 2.6 17.2* (.001)
χ 2 16 # 67.1 (<.001) 25.4 (.062) 71.5 (<.001) 21.3 (.129) 47.9 (<.001)
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*

Significant at the .05 level, two-sided test.

†

Follow-up treatment was defined as receiving 2 or more visits to any service sector, or being in ongoing treatment at interview.

‡

Percents based on entire part II samples.

§

Percents are those receiving follow-up treatment among those in treatment within each level of severity.

∥

Percents not reported if the number of cases with any treatment in a level of severity < 30.

One degree of freedom Chi-Square tests were performed for Nigeria, Lebanon, Japan and China, where combined Severe and Moderate was compared against combined Mild and None category. Three degree of freedom tests were performed for all other countries.

#

χ213 is from a model predicting follow-up treatment among respondents in each level of severity that used any 12-month services.

Among respondents using services, those that received treatments that were potentially minimally adequate varied significantly between 1 (10.4%; Nigeria) and 113 (42.3%; France)(see Table 6). Proportions were generally smaller in lower-income countries, with the low rate in the US (18.1%; n=302) being a notable exception. There were significant relationships between severity and receiving potentially minimally adequate treatment in only five countries; as a result, substantial fractions of severe cases using services failed to receive minimally adequate treatment while many non-cases did.

Table 6.

Percentages receiving minimally adequate treatment† among respondents using services in the WMH surveys

Test of Difference in Probability of Minimally Adequate Treatment By Severity
Country income level Country Any Severity Severe Moderate Mild None χ2 (p-value)
N
 %‡
 se
 N
 %§
 se
 N
 %§
 se
 N
 %§
 se
 N
 %§
 se
 (1, 2, or 3 df)
Low
Nigeria 1 10.4 9.8 0 -∥ -∥ 0 -∥ -∥ 0 12.4 11.8 1 12.4 11.8
Low-Middle
China 19 24.1 7.0 0 -∥ -∥ 3 -∥ -∥ 2 20.1 5.9 14 20.1 5.9 0.8 (.364)
Colombia 33 14.7 3.4 11 23.1 8.5 7 21.7 10.5 3 6.3 4.6 12 10.1 3.5 4.7 (.195)
South Africa 0 -** -** 0 -** -** 0 -** -** 0 -** -** 0 -** -**
Ukraine 0 -** -** 0 -** -** 0 -** -** 0 -** -** 0 -** -**
High-Middle
Lebanon 18 24.5 7.1 5 24.0 6.2 3 24.0 6.2 3 24.8 10.7 7 24.8 10.7 0.0 (.949)
Mexico 42 15.2 2.7 8 11.3 4.5 13 28.6 6.3 6 19.8 5.8 15 11.3 4.0 10.5* (.014)
High
Belgium 78 33.6 5.2 23 42.5 8.5 12 35.5 12.6 5 -∥ -∥ 38 29.4 6.2 1.7 (.626)
France 113 42.3 5.4 29 57.9 8.5 28 36.5 6.6 15 41.5 9.7 41 40.2 8.3 3.4 (.335)
Germany 91 42.0 6.1 21 67.3 10.7 21 53.3 8.4 14 -∥ -∥ 35 35.4 8.8 6.1 (.108)
Israel 148 35.1 2.5 28 34.4 5.4 21 40.3 6.8 6 -∥ -∥ 93 34.3 3.1 0.7 (.867)
Italy 45 33.0 5.1 12 -∥ -∥ 11 35.7 9.4 6 -∥ -∥ 16 29.9 7.4 3.5 (.325)
Japan 35 31.8 6.8 6 -∥ -∥ 6 -∥ -∥ 5 27.9 7.0 18 27.9 7.0 4.4* (.037)
Netherlands 98 34.4 5.0 37 65.7 9.2 19 34.1 10.2 10 -∥ -∥ 32 21.9 5.2 23.2* (<.001)
New Zealand 0 -** -** 0 -** -** 0 -** -** 0 -** -** 0 -** -**
Spain 152 37.3 3.3 41 47.5 7.5 37 43.6 5.6 20 44.8 9.9 54 30.1 4.4 8.5* (.037)
USA 302 18.1 1.1 160 41.8 3.2 101 24.8 2.1 41 4.9 0.8 - - - 114.0* (<.001)
χ 2 12 # 117.0 (<.001) 41.0 (<.001) 31.2 (.002) 25.9 (.011) 96.7 (<.001)
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*

Significant at the .05 level, two-sided test.

†

Minimally adequate treatment was defined as receiving 8 or more visits to any service sector, or 4 or more visits and at least 1 month of medication, or being in ongoing treatment at interview.

‡

Percents based on entire part II samples.

§

Percents are those receiving minimally adequate treatment among those in treatment within each level of severity.

∥

Percents not reported if the number of cases with any treatment in a level of severity < 30.

The test was not performed for Nigeria because there was only one (unweighted) case with adequate treatment. One degree of freedom chi-square tests were performed for Lebanon, Japan and China, where combined Severe and Moderate was compared against combined Mild and None category. Two degree of freedom test was performed for the USA, where the Mild and None categories were collapsed. Three degree of freedom tests were performed for all other countries.

#

χ213 is from a model predicting minimally adequate treatment among respondents in each level of severity that used any 12-month services.

**

The questions on pharmacoepidemiology were not asked in Ukraine, South Africa, or New Zealand.

Predictors of Any 12-Month Service Use

Gender was significantly related to any 12-month service use in 10 countries, with women being more likely than men in all 10 (results available upon request). Age was a significant predictor of receiving mental health services in eight countries; in these, respondents in the middle years of life were generally more likely to receive services than either those younger or older. There were significant positive relationships between education and service use in three countries. Marital status was significantly related to using services in five countries, with those married being less likely than those unmarried in all five. Income was significantly related to service use in four countries, positively so in three and negatively in one.

INTERPRETATION

These results should be interpreted with the following five sets of limitations in mind. First, response rates in the WMH surveys varied widely and included some below standards usually considered acceptable. We did attempt to control for differential response through post-stratification adjustments. However it remains possible that survey response was related to the presence and severity of mental disorders or treatment in ways that were not corrected, potentially leading to biased cross-national comparisons. Item-missing data is another potential limitation, especially if it was related to psychopathology or treatment.

Second, readers should keep in mind that some clinically important disorders such as schizophrenia were not assessed in WMH surveys because earlier validation studies have shown they are over-estimated in lay-administered interviews like the CIDI.32 However these studies have also shown that even if disorders such as non-affective psychosis are not assessed, the vast majority of such cases would still meet criteria for comorbid anxiety, mood, or substance disorders and are therefore captured in our analyses. Another related limitation to keep in mind is that the exact disorders assessed also varied across surveys because some conditions were felt a priori to have low relevance in certain countries. Although we replicated analyses using only disorders assessed in all surveys and found little change in results (available on request), it remains possible that other findings are sensitive to differences in the disorders assessed.

A third potential limitation is that the reliability and validity of diagnoses made with the WMH CIDI may vary across countries. Although acceptable concordance has been observed between diagnoses made with the CIDI and those from blind clinical re-interviews, such studies have been conducted almost exclusively in developed Western countries. It remains possible that the accuracy of CIDI diagnoses could be worse in other countries. One distinct possibility is that there may be a lower relevance of CIDI symptom descriptions in non-Western cultures or greater reluctance to endorse emotional problems in countries with shorter traditions of free speech and anonymous public opinion surveying. In fact, much lower rates of CIDI alcohol disorders have been observed in the Ukraine than expected from administrative data.18 Furthermore, countries with the lowest disorder prevalences in this report also had the highest proportions of treated respondents that were apparently sub-threshold cases, suggesting greater under-estimation of disorders. Clinical reappraisal studies are currently underway in both developed and less-developed WMH countries and will shed light on the magnitude and seriousness of concerns over differential diagnostic validity.

Fourth, without corroborating data on service use we cannot study the accuracy of self-reported treatment use or how this validity may differ across specific sectors or clinical, sociodemographic, and cultural groups. Earlier studies suggest that self-reports of service use may overestimate administrative records, especially among respondents with more distressing disorders.19,20 WMH surveys did attempt to minimize such inaccuracies by using commitment probes (i.e., questions measuring a subject's commitment to the survey) and excluding respondents who failed to endorse that they would think carefully and answer honestly. Nevertheless, potentially biased recall of service use remains possible and may have led to underestimation of unmet need for treatment, especially among those with more serious disorders. Finally in spite of the unprecedented scope and size of the WHO WMH survey initiative, some analyses involved small numbers of respondents and may have rendered our conclusions less certain.

With these limitations in mind, these results reveal disturbingly high levels of unmet need for mental health treatment worldwide, even among cases with the most serious disorders. The situation appears to be most dire in less-developed nations, with only small fractions of severe cases receiving any form of care in the prior year; however even in more developed Western nations, roughly half of severe cases receive no services. Additionally, the study limitations described above that would lead to underestimation of unmet needs for treatment, especially in less-developed countries, compound these troubling findings.

Among the minority of cases receiving some services, even fewer are likely to have been effectively treated. Some received non-health care from CAM and human services sectors, despite growing questions over the efficacy and safety of such treatments.21 In many countries, nearly one quarter of those initiating treatments failed to receive any follow-up care. Consistent with prior studies, only a minority of treatments were observed to meet minimal standards for adequacy.13-15,22

High levels of unmet need worldwide are not surprising, given WHO Project ATLAS’ findings of much lower mental health expenditures than indicated by the magnitude of burdens from mental illnesses.1,23 Generally greater unmet needs in low- and middle-income countries may be due to these nations spending smaller proportions (often <1%) of already diminished health budgets on mental health care and relying heavily on out-of-pocket spending by citizenry ill-equipped to do so.23 Notable exceptions to the rule of greater unmet needs in developing vs. developed countries may be explained by levels of investment in health care. For example, South Africa's high rates of treatment may reflect its greater spending (8.6% of GDP) on health care than any low- or middle-income country studied, and even some high-income countries; on the other hand, Japan's and Italy's smaller rates of treatment may reflect less spending (8.0% and 8.4% of GDP, respectively) than other high- and even some low-/middle-income countries.17

Additional research is needed to understand how the limited mental health resources that nations do possess can be optimally allocated. An overly simplistic view of our results could be that a meaningful number of services are going to those without apparent needs. Such potential diversion of limited treatment resources to individuals without apparent needs would be concerning in light of the magnitude of unmet needs among cases with clearly defined and serious disorders.24 The weak or lack of relationship between use of specialty sectors and disorder severity could also be further evidence of poor prioritization of treatment for more severe cases. However, it is critical to first identify whether such services are being used appropriately for disorders not assessed in WMH surveys, subthreshold symptoms, secondary prevention of lifetime disorders, or even primary prevention.25 Uncovering other factors, beyond clinical severity, disability, or distress, that may motivate use of mental health services will also be important in the future.26

The general medical sector is for most countries the largest source of mental health services. This may reflect conscious attempts by policy makers to broaden access to services, rather than concentrating resources on the relatively fewer patients with access to specialty sectors.27 It may also reflect “gatekeeping” by primary care physicians employed in some countries to reserve specialty treatment for severe cases.28 Whatever the rationale, future research is need to ensure that mental health care received in general medical sectors is not of low intensity and adequacy, as has been observed in other studies.22

Our results concerning predictors of service use are generally consistent with prior research. The young relative to middle-aged may be more dependent on others and therefore reluctant to access services;29 on the other hand, the elderly may avoid seeking mental health care due to the greater perceived stigma of mental disorders and treatments among people in this age range.30 Higher rates of treatment among women than men may be explained by women's diminished perceptions of stigma as well as their greater abilities to translate nonspecific feelings of distress into conscious recognition of having a mental health problem.31

Effects of greater income were variable, increasing service use in some countries and decreasing it in others. In countries where positive associations exist, this may reflect the formidable influences of financial barriers on seeking treatment.32 On the other hand, negative associations may be explained by the fact that only the poor qualify for entitlements in some countries.32 More educated respondents may also have greater resources; alternatively, their higher treatment rates may reflect that some modalities (e.g., psychotherapies) place an emphasis on knowledge and cognitive processes The generally greater use of mental health services among those not married may indicate the power of relationship loss, strife, or social impairments as motivators for seeking treatment.30

These results have implications in several areas. First, alleviating the problem of widespread undertreatment will almost certainly require expansion of treatment resources and governmental as well as private means of financing mental health services. Second, there is also a pressing need to devise rational, transparent, and ethical allocation rules. In many countries it is unclear whether to focus resources on those with the greatest needs vs. larger numbers with milder disorders (e.g., to prevent negative sequelae), deliver services through primary vs. specialty sectors or inpatient vs. community settings, and whether to provide mental health services on parity with those for general medical disorders.33 Ideally these questions would be answered through formal analyses of the burdens from illnesses and the cost-effectiveness of treatments.34 Unfortunately rigorous data to compare disease burdens and weigh the costs and benefits of different regimens are largely lacking.27 In the absence of such rational schemata, decisions regarding resource allocation are often made on the basis of simple cost-minimization and even attitudinal factors such as stigma and desire to punish persons perceived as being personally responsible for their problems.35

Finally, when rational, transparent, and ethical priorities have been set, policy makers need specific designs they can implement to achieve their goals. Some techniques employed in managed care systems (e.g., gatekeeping, increased cost-sharing, utilization review, prior approval, etc.) could presumably be brought to bear on unnecessary use but not underuse—in fact, they may worsen unmet needs for treatment; furthermore, these elements from largely developed nations such as the U.S. may not be translatable to other countries and circumstances. The impacts of other policies, delivery system features, and means of financing that policy makers could implement, are essentially unknown. For these reasons, collection of detailed data on the mental health policies, delivery system features, and means of financing mental health care in different countries is a promising area for future research.23 When merged with WMH surveys on the use and adequacy of treatments, such combined data could shed light on the impacts of policies, delivery system, and financing features and help policy makers choose ones that achieve their desired goals.36

ACKNOWLEDGEMENTS

The surveys discussed in this article were 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 R01-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical, Inc., GlaxoSmithKline, and Bristol-Myers Squibb. A complete list of WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/. The Chinese World Mental Health Survey Initiative is supported by the Pfizer Foundation. The Colombian National Study of Mental Health (NSMH) is supported by the Ministry of Social Protection, with supplemental support from the Saldarriaga Concha Foundation. 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, and other local agencies and by an unrestricted educational grant from GlaxoSmithKline. 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), 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 Nigerian Survey of Mental Health and Wellbeing (NSMHW) is supported by the WHO (Geneva), the WHO (Nigeria), and the Federal Ministry of Health, Abuja, Nigeria. 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 044780), and the John W. Alden Trust.

Appendix

Appendix table 1A.

Sociodemographic predictors† of using services among respondents in the WMH surveys

Gender
 Age‡
Country income level Female
 Male
 χ2
 (p-value)
 ≤34
 35-49
 50-64
 ≤65
 χ2
 (p-value)
Low
    Nigeria 1.1 (0.4-3.0) 1.0 - 0.1 (.786) 1.0 - 0.8 (0.3-2.6) 1.6 (0.5-5.5) 0.5 (0.1-2.7) 3.7 (.298)
Low-Middle
    China 1.4 (0.7-3.0) 1.0 - 0.9 (.355) 1.0 - 8.0* (1.6-39.8) 12.5* (3.1-51.3) 26.7* (3.8-184.9) 15.6* (.001)
    Colombia 1.4* (1.0-2.0) 1.0 - 3.8 (.052) 1.0 - 1.0 (0.7-1.7) 1.0 (0.5-1.9) 1.1 (0.4-2.9) 0.2 (.977)
    South Africa 1.2 (1.0-1.6) 1.0 - 2.6 (.109) 1.0 - 1.3 (0.9-1.7) 1.4 (1.0-2.0) 1.0 (0.6-1.6) 5.4 (.146)
    Ukraine 2.4* (1.4-4.0) 1.0 - 12.2* (<.001) 1.0 - 0.9 (0.5-1.7) 0.8 (0.5-1.3) 1.4 (0.7-3.0) 3.0 (.397)
High-Middle
    Lebanon 2.3* (1.1-4.9) 1.0 - 5.3* (.022) 1.0 - 0.9 (0.4-2.1) 0.5 (0.2-1.1) 0.6 (0.2-1.7) 8.1* (.045)
    Mexico 1.7* (1.1-2.7) 1.0 - 5.4* (.020) 1.0 - 1.0 (0.6-1.7) 1.1 (0.6-2.1) 1.2 (0.6-2.5) 0.3 (.956)
High
    Belgium 1.3 (0.8-2.2) 1.0 - 1.5 (.226) 1.0 - 1.5 (0.8-3.0) 1.3 (0.5-2.9) 0.7 (0.3-1.8) 6.8 (.079)
    France 1.5 (0.8-2.8) 1.0 - 2.0 (.162) 1.0 - 1.4 (0.7-2.8) 1.9* (1.2-2.9) 0.5* (0.2-1.0) 22.8* (<.001)
    Germany 2.0* (1.1-3.6) 1.0 - 5.8* (.016) 1.0 - 2.9* (1.6-5.3) 2.1* (1.0-4.6) 1.7 (0.6-4.7) 17.8* (<.001)
    Israel 1.5* (1.2-1.9) 1.0 - 11.1* (.001) 1.0 - 1.6* (1.1-2.2) 1.1 (0.8-1.6) 0.8 (0.5-1.2) 18.5* (<.001)
    Italy 2.5* (1.3-4.9) 1.0 - 7.3* (.007) 1.0 - 1.0 (0.5-2.1) 1.2 (0.5-2.9) 0.6 (0.2-1.9) 2.0 (.577)
    Japan 1.5 (0.8-2.9) 1.0 - 1.6 (.205) 1.0 - 1.0 (0.4-2.7) 1.2 (0.5-2.9) 1.6 (0.4-5.8) 0.6 (.906)
    Netherlands 2.2* (1.1-4.7) 1.0 - 4.9* (.027) 1.0 - 2.2 (1.0-5.1) 1.8 (0.7-4.4) 1.9 (0.5-8.1) 4.0 (.259)
    New Zealand 1.6* (1.3-1.9) 1.0 - 25.3* (<.001) 1.0 - 1.5* (1.1-1.9) 1.2 (0.9-1.7) 0.7 (0.4-1.0) 42.2* (<.001)
    Spain 1.9* (1.2-3.1) 1.0 - 7.2* (.008) 1.0 - 3.1* (1.5-6.6) 4.2* (2.3-7.6) 3.2* (1.7-6.2) 23.1* (<.001)
    USA 1.7* (1.5-1.9) 1.0 - 69.1* (<.001) 1.0 - 1.3 (1.0-1.7) 1.3 (1.0-1.7) 0.7* (0.5-1.0) 29.4* (<.001)
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*

Significant at the .05 level, two-sided test.

†

From a logistic regression model of any 12-month service use containing all covariates shown in tables 1A-D as well as severity.

‡

Age starts at 21 in Israel; age categories for Colombia and Mexico are 18-29, 30-44, 45-54 and 55-65.

Appendix table 1B.

Sociodemographic predictors† of using services among respondents in the WMH surveys

Education‡
 Marriage
Low Low Average High Average High Married Sep/Wid/Div Never Married
Country income level OR
 CI
 OR
 CI
 OR
 CI
 OR
 CI
 χ23
 (p-value)
 OR
 CI
 OR
 CI
 OR
 CI
 χ22
 (p-value)
Low
    Nigeria 1.0 - 1.4 (0.4-4.5) 1.7 (0.4-7.3) 1.7 (0.2-12.9) 0.6 (.902) 1.0 - 0.4 (0.1-2.2) 0.6 (0.2-1.5) 1.9 (.384)
Low-Middle
    China 1.0 - 1.2 (0.3-4.3) 1.5 (0.4-6.3) 1.4 (0.3-5.8) 0.5 (.919) 1.0 - 0.6 (0.2-2.2) 1.9 (0.5-8.3) 2.1 (.352)
    Colombia 1.0 - 0.7 (0.4-1.3) 0.7 (0.4-1.6) 0.9 (0.4-1.8) 1.1 (.777) 1.0 - 2.4* (1.2-4.9) 1.1 (0.6-2.0) 6.5* (.038)
    South Africa 1.0 - 1.2 (0.8-1.7) 1.1 (0.7-1.6) 1.3 (0.8-2.0) 3.0 (.396) 1.0 - 1.0 (0.7-1.4) 0.8 (0.6-1.1) 2.2 (.335)
    Ukraine 1.0 - 1.3 (0.6-2.9) 1.6 (0.7-3.7) 2.4 (0.8-7.4) 3.9 (.273) 1.0 - 1.2 (0.7-2.2) 0.8 (0.4-1.6) 1.0 (.592)
High-Middle
    Lebanon 1.0 - 2.1 (0.8-5.8) 0.8 (0.2-2.8) 2.3 (1.0-5.7) 10.4* (.015) 1.0 - 1.3 (0.5-3.4) 0.4 (0.1-1.1) 4.6 (.100)
    Mexico 1.0 - 0.6 (0.3-1.2) 0.6 (0.3-1.1) 0.9 (0.5-1.9) 6.1 (.106) 1.0 - 1.0 (0.6-1.7) 1.3 (0.7-2.3) 0.9 (.644)
High
    Belgium 1.0 - 1.9 (0.6-6.3) 1.4 (0.5-3.5) 1.9 (0.8-4.5) 3.1 (.373) 1.0 - 0.9 (0.6-1.3) 0.8 (0.3-1.7) 0.9 (.623)
    France 1.0 - 1.3 (0.8-2.1) 1.0 (0.5-1.8) 1.4 (.507)
    Germany 1.0 - 1.0 (0.6-1.6) 1.3 (0.7-2.5) 1.3 (0.5-3.8) 1.3 (.721) 1.0 - 0.6 (0.4-1.1) 2.0 (0.9-4.1) 9.1* (.011)
    Israel 1.0 - 0.9 (0.6-1.2) 0.7 (0.5-1.0) 0.9 (0.6-1.2) 3.8 (.285) 1.0 - 1.4* (1.0-1.9) 1.4* (1.0-2.0) 7.9* (.019)
    Italy 1.0 - 0.6 (0.3-1.3) 1.1 (0.6-2.1) 2.4* (1.1-5.3) 15.4* (.002) 1.0 - 2.4 (0.9-6.4) 1.1 (0.5-2.4) 3.2 (.205)
    Japan 1.0 - 3.3 (1.0-10.4) 3.7 (1.0-13.7) 2.8 (0.9-9.1) 5.6 (.132) 1.0 - 1.6 (0.8-3.1) 1.6 (0.5-5.1) 2.3 (.317)
    Netherlands 1.0 - 1.3 (0.4-3.8) 2.1 (0.5-8.4) 2.7 (1.1-6.8) 6.4 (.092) 1.0 - 1.6 (0.7-3.7) 1.1 (0.6-1.8) 1.6 (.460)
    New Zealand 1.0 - 1.2 (0.9-1.6) 1.2 (0.9-1.5) 1.5 (1.1-1.9) 10.4* (.016) 1.0 - 1.5 (1.2-2.0) 1.1 (0.9-1.4) 10.9* (.004)
    Spain 1.0 - 0.6 (0.3-1.0) 1.1 (0.6-1.9) 1.0 (0.5-1.8) 6.3 (.098) 1.0 - 1.4 (1.0-2.0) 1.4 (0.7-2.8) 5.6 (.061)
    USA 1.0 - 1.0 (0.8-1.3) 1.2 (1.0-1.6) 1.3 (0.9-1.8) 4.8 (.190) 1.0 - 1.6* (1.3-2.0) 1.1 (0.9-1.3) 17.0* (<.001)
Open in a new tab
*

Significant at the .05 level, two-sided test.

†

From a logistic regression model of any 12-month service use containing all covariates shown in tables 1A-D as well as severity.

‡

Country-specific education categories are used.

Appendix table 1C.

Sociodemographic predictors† of using services among respondents in the WMH surveys

Income
Low Low Avg High Avg High
Country income level OR
 CI
 OR
 CI
 OR
 CI
 OR
 CI
 χ23
 (p-value)
Low
    Nigeria 1.0 - 0.9 (0.3-3.2) 0.6 (0.2-1.6) 0.4 (0.2-1.2) 7.5 (.058)
Low-Middle
    China 1.0 - 0.4* (0.2-0.8) 0.2* (0.1-0.5) 0.1* (0.0-0.6) 12.8* (.005)
    Colombia 1.0 - 1.0 (0.6-1.8) 1.0 (0.4-2.1) 2.0* (1.0-3.8) 11.2* (.010)
    South Africa 1.0 - 1.0 (0.7-1.4) 1.0 (0.7-1.5) 0.7 (0.5-1.0) 5.9 (.116)
    Ukraine 1.0 - 0.6 (0.3-1.3) 0.5 (0.3-1.0) 0.7 (0.3-1.6) 3.8 (.280)
High-Middle
    Lebanon 1.0 - 5.1* (1.7-15.2) 7.8* (2.9-21.2) 8.4* (2.3-30.5) 18.0* (<.001)
    Mexico 1.0 - 0.8 (0.5-1.4) 1.0 (0.6-1.7) 0.7 (0.4-1.4) 1.8 (.608)
High
    Belgium 1.0 - 1.2 (0.5-3.0) 0.9 (0.4-2.2) 1.3 (0.6-3.2) 1.2 (.751)
    France 1.0 - 1.7 (0.9-3.4) 1.9 (1.0-3.7) 1.3 (0.7-2.6) 5.5 (.140)
    Germany 1.0 - 1.6 (0.7-3.6) 1.6 (0.7-3.5) 1.5 (0.7-3.3) 1.8 (.614)
    Israel 1.0 - 1.0 (0.7-1.4) 1.1 (0.7-1.5) 2.0* (1.4-2.9) 25.7* (<.001)
    Italy 1.0 - 0.6 (0.3-1.3) 0.5 (0.3-1.1) 0.5* (0.3-1.0) 5.1 (.164)
    Japan 1.0 - 3.7 (1.2-11.1) 2.2 (0.8-6.1) 4.1* (1.1-15.2) 7.7 (.052)
    Netherlands 1.0 - 0.8 (0.4-1.6) 0.8 (0.4-1.7) 0.7 (0.3-2.0) 0.6 (.887)
    New Zealand 1.0 - 1.1 (0.9-1.3) 1.0 (0.8-1.3) 1.2 (0.9-1.6) 1.6 (.667)
    Spain 1.0 - 0.5 (0.3-1.1) 0.7 (0.4-1.2) 1.2 (0.5-2.8) 6.8 (.078)
    USA 1.0 - 1.0 (0.7-1.2) 1.0 (0.7-1.4) 1.1 (0.8-1.6) 3.0 (.389)
Open in a new tab
*

Significant at the .05 level, two-sided test.

†

From a logistic regression model of any 12-month service use containing all covariates shown in tables 1A-D as well as severity.

Appendix table 1D.

Sociodemographic predictors† of using services among respondents in the WMH surveys

Severity
Severe Moderate Mild None
Country income level OR
 CI
 OR
 CI
 OR
 CI
 OR
 CI
 χ23
 (p-value)
Low
    Nigeria 28.7 (4.7-176.0) 16.8 (4.1-68.9) 11.5 (3.6-37.5) 1.0 - 25.7* (<.001)
Low-Middle
    China 5.0* (1.2-21.5) 15.6* (3.6-68.4) 0.6 (0.1-2.8) 1.0 - 20.7* (<.001)
    Colombia 12.4* (7.5-20.4) 3.4* (1.8-6.4) 2.5* (1.4-4.2) 1.0 - 104.7* (<.001)
    South Africa 2.3* (1.6-3.3) 2.2* (1.5-3.2) 2.0* (1.4-2.9) 1.0 - 38.0* (<.001)
    Ukraine 9.9* (6.0-16.4) 5.7* (3.2-10.1) 2.2* (1.0-4.9) 1.0 - 90.7* (<.001)
High-Middle
    Lebanon 8.1* (2.7-23.9) 4.5* (1.8-11.3) 1.2 (0.3-4.4) 1.0 - 24.8* (<.001)
    Mexico 11.4* (6.6-19.8) 6.2* (3.9-9.8) 4.0* (2.3-6.9) 1.0 - 116.7* (<.001)
High
    Belgium 27.8* (12.6-61.6) 9.1* (3.9-21.3) 1.8 (0.7-4.7) 1.0 - 160.3* (<.001)
    France 12.9* (6.5-25.7) 5.1* (3.1-8.3) 3.8* (2.1-6.7) 1.0 - 76.2* (<.001)
    Germany 14.0* (6.3-31.3) 4.6* (2.2-9.8) 4.3* (1.9-9.9) 1.0 - 52.6* (<.001)
    Israel 18.7* (12.9-27.0) 7.1* (5.0-10.1) 2.6* (1.6-4.3) 1.0 - 327.8* (<.001)
    Italy 54.2* (28.0-105.0) 15.4* (8.6-27.6) 8.7* (4.0-19.3) 1.0 - 193.4* (<.001)
    Japan 17.3* (7.4-40.3) 5.0* (1.9-13.0) 2.9 (1.1-7.9) 1.0 - 59.1* (<.001)
    Netherlands 10.4* (5.8-18.5) 5.0* (2.4-10.4) 2.1* (0.6-7.2) 1.0 - 74.5* (<.001)
    New Zealand 16.7* (12.7-21.8) 7.9* (6.3-9.9) 3.4* (2.5-4.5) 1.0 - 532.6* (<.001)
    Spain 37.2* (23.4-59.1) 15.9* (9.8-25.8) 6.1* (3.1-12.0) 1.0 - 387.7* (<.001)
    USA 13.4* (10.6-16.9) 5.8* (4.8-7.1) 3.2* (2.6-3.9) 1.0 - 582.9* (<.001)
Open in a new tab
*

Significant at the .05 level, two-sided test.

†

From a logistic regression model of any 12-month service use containing all covariates shown in tables 1A-D as well as severity.

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