 |
 |
|
|
|
 Bipolar disorder is a severe and persistent mental illness that is associated with significant morbidity and mortality (1). According to the WHO, it is the sixth leading cause of disability-adjusted life years worldwide among persons aged 15 to 44 years (2). Tremendous direct and indirect societal costs are associated with BD (3), yet there are limited data on this illness from a population perspective in Canada. This report examines the prevalence and illness characteristics of BD in a large, representative sample of Canadians. Reported lifetime prevalence rates of BD vary greatly, owing to different definitions of BD as well as to the country in which the data were obtained (4–7). Much of the Canadian and North American epidemiologic data on BD prevalence were collected over 10 years ago (8–11). Further, Canadian data have been geographically limited to a specific region or city. The recent completion of the CCHS 1.2 by Statistics Canada provides an opportunity to examine more recent data on this illness from a representative sample of Canadians from 10 provinces (12). Men and women have similar prevalence rates of BD (5), yet there may be important differences in how the illness manifests. Data on suspected sex differences in age of illness onset, number of lifetime depressive episodes, and rates of comorbid psychiatric conditions are inconsistent (13–22), and much of the available data are derived from clinical samples, which raises concern about selection or ascertainment bias. The current study uses data from the CCHS 1.2 to investigate potential sex differences in illness course and comorbidity among individuals with BD. MethodologySurvey The CCHS 1.2 was a cross-sectional survey of the mental health of Canadians. Statistics Canada conducted this representative survey, collecting data between May and December 2002 from participants in all 10 provinces. Responses were obtained from individuals aged 15 years or over who were living in private occupied dwellings (approximately 98% of the population). Individuals living on Reserves, on Crown lands, or in one of the northern territories; residents of health care institutions; full-time members of the Armed Forces; and residents of remote regions were excluded. One person aged 15 years or over was randomly selected from the eligible sampled households. Before the first household contact, an introductory letter and a brochure were sent to each selected dwelling. Considerable effort was made to interview respondents in person; however, 14% of the interviews were completed by telephone. Interviews were conducted in English, French, Chinese, or Punjabi (as required). The national response rate was 77% (total of 36 984 respondents). The CCHS 1.2 interview was based on the WMH-CIDI, an instrument that establishes psychiatric diagnoses according to DSM-IV criteria. In addition, the CCHS 1.2 interview collected sociodemographic data and information on illness course. Well-trained lay interviewers used computer-assisted techniques to administer the CCHS 1.2 interview. Study Sample Of the 36 984 total respondents, the study sample included those aged 15 years and over who met the criteria for BD. The diagnosis was established by identifying the presence of any past or current episode of mania (see criteria below), which by definition indicates that an individual has BD. Dependent Variables Mania. The presence of a past or current manic episode was determined by specific criteria that were similar, but not identical, to DSM-IV criteria. To be defined as mania, an episode had to involve a period of several days or longer of elevated or irritable mood; include 3 or more additional DSM-IV–defined manic symptoms (that is, inflated self-esteem or grandiosity, decreased need for sleep, more talkative or pressured speech, racing thoughts or flight of ideas, distractibility, increased goal-directed activity, or excessive involvement in pleasurable activities that have a high potential for painful consequences); cause significant impairment; and not be the result of medications, drugs, alcohol, or physical causes such as thyroid disease or cancer. Only when a respondent met all these criteria simultaneously was the diagnosis of a manic episode given. The CCHS 1.2 interview did not explore criteria specific to DSM-IV–defined hypomania (for example, change that is observable by others), and it was decided not to diagnose hypomania in participants who met some, but not all, criteria for mania. For this study, we did not consider respondents with only some of the criteria for a manic episode to have BD. Although the DSM-IV criteria for a manic episode require a distinct period lasting at least 1 week (or any duration if hospitalization is necessary), the CCHS 1.2 interview defined a distinct period of several days or longer as sufficient. This was felt to be an acceptable duration, given the required presence of other criteria for mania. For this study, we considered respondents to have BD if they met criteria for a past or current manic episode according to the CCHS 1.2 interview. Illness History. Past depressions were defined according to DSM-IV criteria, with a minimum of 2 weeks’ duration of depressive symptoms and associated functional impairment. Age of illness onset was defined as the age at which respondents experienced their first manic episode or first depressive episode, whichever came first. Respondents’ ages when the first manic episode occurred and when the first depressive episode occurred were also recorded. In addition, the number of manic and depressive episodes experienced over the respondents’ lifetime was documented. Psychiatric Comorbidity. Alcohol and drug use in the previous 12 months were independently assessed and classified for each respondent as abstinent, use, heavy use, problematic use, or probable dependence. For the alcohol use variable, abstinent was defined as no drinking; use, as never or less than once monthly having 5 or more drinks per occasion; heavy use, as having 5 or more drinks per occasion once or more monthly with no problems (such as being drunk or hungover at work or school, increased chance of getting hurt in an activity because of drinking, or emotional or psychological problems because of alcohol use); problematic use, as one or more problems but no more than 2 DSM-IV criteria for dependence; and probable dependence, as 3 or more DSM-IV criteria for dependence. For the drug use variable, abstinent was defined as no drug use; use, as use of any drug less than 1 to 3 times monthly; heavy use, as use of any drug 1 to 3 or more times monthly, with no DSM-IV criteria for dependence; problematic use, as 1 to 2 DSM-IV criteria for dependence; and probable dependence, as 3 or more DSM-IV criteria for dependence. The specific drugs that were asked about included cannabis, cocaine or crack, speed or amphetamines, ecstasy (MDMA), hallucinogens, glue or solvents, heroin, and steroids. Respondents classified with problematic use or probable dependence with regard to alcohol, drugs, or both were considered to have a comorbid substance use problem. Comorbid anxiety disorder was defined by a lifetime history of panic disorder, agoraphobia, or social phobia. Other anxiety disorders were not assessed in the interview. Independent Variables Demographic variables such as age, sex, marital status, highest education level, and immigrant status were included as covariates. Income adequacy was also used in the data analysis. This is a somewhat refined measure of economic status that takes into account the number of people living in the household. Low income adequacy is defined as a total household income of less than $15 000 for 1 or 2 household residents, less than $20 000 for 3 or 4 residents, and less than $30 000 for 5 or more residents. Statistical Analyses The CCHS 1.2 used a stratified design with differences in sampling fractions across the strata. Some geographical areas were over- or underrepresented in the sample relative to their representation in the population; therefore, we used weights recommended by Statistics Canada when conducting analyses. The only exceptions were number of respondents and sample sizes, which remained unweighted. The bootstrap method (23) was used to address the potential bias resulting from design effects. First, we calculated descriptive statistics, including overall prevalence of BD and the prevalence across sex, geographic regions, and comorbid psychiatric disorders. Second, we examined factors associated with the presence of BD, using a logistic regression analysis. Finally, we evaluated differences between men and women with BD across various demographic variables and illness characteristics, using 2-tailed t tests for continuous variables and chi-square analyses for categorical or binary variables. We reported P values of less than 0.05 as significant. All statistical analyses were conducted using master file data. The research ethics board at Sunnybrook and Women’s College Health Sciences Centre approved this study. ResultsPrevalence Estimates Among all respondents (unweighted n = 36 984), 852 met the criteria for BD. The overall weighted lifetime prevalence rate of BD was 2.2% (95%CI, 1.94% to 2.37%). Table 1 displays the weighted lifetime prevalence rates of BD based on sociodemographic variables, psychiatric comorbidity, and province of residence. Although there were more female (n = 467) than male (n = 385) respondents with BD, there was no significant sex difference in lifetime prevalence of BD when weights were applied. A logistic regression model examining regional differences found a significantly higher prevalence rate of BD in British Columbia (P = 0.002) than in the other regions.
Correlates of BD Diagnosis Several sociodemographic and psychiatric comorbidity variables appeared to be associated with higher prevalence rates of BD. To examine the independent effects of each of these variables, we used a logistic regression model to identify correlates of the presence of BD. Table 2 shows the results of this model. Younger age, low income adequacy, lifetime anxiety disorder, and presence of a substance use disorder in the previous 12 months were each significantly associated with the presence of a BD diagnosis (P < 0.001 for each). The largest effect was found for the presence of an anxiety disorder (OR 7.94; 95%CI, 6.35 to 9.92). The OR for age appears small (0.99), but age in this analysis is a continuous variable. Therefore, this effect is interpreted as the change in odds for each age interval. Overall, younger age was found to significantly increase the likelihood of a BD diagnosis; however, this relation was curvilinear.
Sociodemographic Variables Among the respondents who met the criteria for BD (weighted), 50.6% were female, 42.4% were married, 2.5% were widowed, 18.0% were separated, and 37.2% were single. The mean age of the respondents with BD was 37.3 years, SD 13.7. Male respondents with BD had a mean age of 38.0 years, SD 11.2, and female respondents had a mean age of 36.6 years, SD 14.1, a nonsignificant difference. English was the preferred language for 75.3% of the respondents with BD, and 16.5% of the group were in the low income adequacy category. Sex Differences Table 3 presents data on illness course and psychiatric comorbidity for the entire group with BD, stratified by sex. The mean age of illness onset was 22.5 years, SD 12.0, with 53.4% (95%CI, 48.4% to 58.3%) of respondents developing the illness before age 21 years. The mean age of first depressive episode was significantly lower among women (21.2 years, SD 11.5), compared with men (26.0 years, SD 14.4; P = 0.04).
Only a minority of the respondents with BD (20.3%; 95%CI, 15.9 to 24.8) fully abstained from substance use (alcohol or drugs) during the previous 12 months. Men were found to be significantly more likely than women to meet the criteria for problematic use (P < 0.001) or probable dependence (P < 0.001). A lifetime history of anxiety disorder was present in 51.8% (95%CI, 47.1% to 56.5%) of the respondents with BD, with both panic disorder and agoraphobia each being more frequent among women, compared with men (P = 0.01 and P < 0.001, respectively). DiscussionAccording to data from the CCHS 1.2, the estimated lifetime prevalence rate of BD in Canada is 2.2%. This translates to well over 500 000 Canadians who would meet study criteria for mania at some point in their lives. The definition of mania used in the CCHS 1.2 interview was similar, but not identical, to DSM-IV criteria, in that a manic episode needed to last only several days or longer, as opposed to the DSM-IV requirement of at least 7 days (unless hospitalization was necessary). Thus patients who would likely meet DSM-IV criteria for mania (BD I), hypomania (BD II), or BD not otherwise specified were grouped together as respondents with BD. The interview did not allow for reliable separation of BD subtypes. The lifetime prevalence rate of BD found in this study is somewhat higher than rates in other large epidemiologic surveys that exclusively examined BD I (5,24), and it is lower than rates in surveys that included respondents who experienced subsyndromal hypomania or bipolar spectrum disorder (25,26). Given that these differences can likely be explained by inconsistent definitions of BD across surveys, there is no indication that BD is more or less prevalent in Canada than in other developed nations. This implies that the tremendous societal costs associated with BD identified in other countries are most likely equally at play in Canada (3,27). We also identified interprovincial differences in the lifetime prevalence rate of BD in this study. Prevalence rates in Ontario (1.9%; 95%CI, 1.61% to 2.16%) and in the Atlantic provinces (2.0%; 95%CI, 1.59% to 2.40%) were numerically lowest, whereas the rate in British Columbia was significantly higher (2.9%; 95%CI, 2.22% to 3.57%) (P = 0.002). This is a previously unreported finding that requires further study to explore the possible societal, environmental, or other unknown factors that could account for this difference. We did not consider respondents to have BD if they reported manic symptoms attributable to substance use or physical causes . This approach differs from that used in an internal Statistics Canada report on BD, based on CCHS 1.2 data, which did not exclude respondents with mania induced by substances or physical causes and reported a lifetime prevalence of 2.6% (28). Given that individuals with manic symptoms attributable to substance use or physical causes are not given a BD diagnosis according to DSM-IV criteria and are generally excluded from other prevalence estimates of BD (4,6,10), inclusion of these respondents would have the effect of inflating the estimated prevalence rate of BD. Further, including respondents with manic symptoms secondary to substance use or physical causes might significantly influence the examination of sex differences in BD, since that approach might lead to the inclusion of a proportionally greater number of men with substance-induced mood symptoms who do not in fact have BD. Finally, the Statistics Canada report focused on respondents aged 25 to 64 years, whereas this report examined all respondents aged 15 years or over. Our results thus differ considerably from the Statistics Canada report, and this difference further exemplifies the important effects of different diagnostic definitions and exclusion criteria when results across studies are compared. Nearly 52% of the respondents with BD in our study met the criteria for a comorbid anxiety disorder. High rates of comorbid anxiety have been found in other studies of BD (29,30), and the presence of the comorbidity is generally associated with increased morbidity and treatment resistance (31). These results further support the importance of screening all patients with BD for anxiety symptoms and diagnoses. In addition, the prevalence rate of BD was 9.5% among respondents with a lifetime history of an anxiety disorder, making an anxiety disorder the strongest independent predictor of a BD diagnosis (OR 7.94). The clinical implications of this finding suggest that all patients with an anxiety disorder may need to be screened for BD as well as being monitored on an ongoing basis for the emergence of any hypomanic or manic symptoms. Many patients with an anxiety disorder are treated with antidepressants that have the potential to unmask a bipolar diathesis, so particular attention should be paid early in the course of antidepressant treatment when the risk of mania induction is highest. Other independent correlates of a BD diagnosis in this sample were younger age, low income adequacy, and a substance use disorder in the past 12 months. These results mirror previous findings in other large surveys, adding to the list of variables associated with a bipolar diagnosis (10,32). Given that these data are cross-sectional, it is not possible to establish cause and effect relations. However, regardless of whether a relation such as that found between income adequacy and BD is causal, it is troubling that a significant proportion of individuals with BD live at or below the low-income cut-off line. Programs to address the needs of low-income persons with mental disorders are required, since these individuals have social challenges (such as housing and employment) that likely further exacerbate the experience of their illness. The association with substance abuse also leads to considerable challenges in terms of increased risk of chronic symptoms and nonresponse to treatment (33). Coordinated care for both substance abuse and BD is the ideal; however, few treatment centres are adequately equipped to comprehensively address this comorbidity. We identified several sex differences in the group with BD, including increased frequency of comorbid panic disorder and agoraphobia and decreased frequency of substance use disorder among women. The rate of no substance use was similar between men and women, but men had higher rates of problematic use or probable dependence: 46% of men reporting any substance use had problematic use or probable dependence, compared with only 22% of women. These findings suggest that there must be a high index of suspicion regarding substance use problems among all patients with BD and especially among men with any substance use. The mean age at onset of illness among respondents with BD in this sample was 22.5 years, SD 12.0, which is somewhat older than the mean age in other recent studies of subjects with BD recruited from clinical populations (17,34). Clinical samples may be biased toward more severely ill patients, who are more likely to have an earlier age of onset; however, a more definitive explanation would require direct comparison of age of onset among subjects with BD recruited through various methods. Respondents with BD reported a surprisingly high number of lifetime manic and depressive episodes. This may be attributable to the self-report nature of the interview, in that individuals do not experience their illness according to DSM-IV criteria and past episodes may not have all met strict diagnostic criteria. Further, many patients with BD experience chronic, fluctuating symptoms that would be difficult to accurately capture in an episode count (35,36). Our study results must be viewed in the context of several limitations. First, not all sampled households produced a survey participant (77% response rate). Individuals with a history of mental illness may have been either more or less likely to agree to participate in the survey; thus the identified lifetime prevalence rates in this and other epidemiologic surveys are only estimates. A second limitation is that data were not collected from individuals living on Reserves, in health care institutions, or in remote regions of the country, nor were data collected from full-time members of the Armed Forces. Again, the nonparticipation of such individuals may have influenced the estimates; however, it is unlikely that the relatively small number of individuals in these categories would have significantly changed the findings. Another limitation is that the diagnosis of BD was determined according to a CIDI-based structured interview that relied heavily on retrospective data. As well, interrater reliability in establishing the diagnosis of BD with the CCHS interview was not available. Although considerable effort was made to increase diagnostic accuracy (including extensive training of interviewers, conducting interviews at home, and using computer-assisted interviewing to elevate the quality of data collection), the accuracy could not be fully assured. Nonetheless, the use of lay interviewers is standard across other epidemiologic surveys and is the only feasible way to recruit such a large, nationally representative sample. The CIDI has shown validity in establishing the diagnosis of “classic” BD (37); however, the interview’s ability to accurately differentiate mania from bipolar spectrum disorder has not been well established (6,10). For this study, we therefore chose not to separate respondents with BD into subtypes and considered all subjects who met the study criteria for mania to have BD. In conclusion, the estimated lifetime prevalence rate of BD in Canada is 2.2%. The study results have implications for health care policy, as over 500 000 Canadians likely suffer from this condition, and identifying those at highest risk according to sociodemographic and other health factors is important. This information may assist in the development of more effective strategies to identify BD in the community. From a clinical perspective, knowledge of high rates of comorbid psychiatric conditions and sex differences in illness presentation may assist the planning for the care of these patients. Funding and SupportThis study was supported by the Ontario Ministry of Health and Long-Term Care. References1. Goodwin FK, Jamison KR. Manic-depressive illness. New York (NY): Oxford University Press; 1990. 2. Murray CL, Lopez AD, editors. The global burden of disease. A comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020. Cambridge (MA): Harvard University; 1996. 3. Das Gupta R, Guest JF. Annual cost of bipolar disorder to UK society. Br J Psychiatry 2002;180:227–33. 4. Weissman MM, Bland RC, Canino GJ, Faravelli C, Greenwald S, Hwu H-G, and others. Cross-national epidemiology of major depression and bipolar disorder. JAMA 1996;276:293–9. 5. Waraich P, Goldner EM, Somers JM, Hsu L. Prevalence and incidence studies of mood disorders: a systematic review of the literature. Can J Psychiatry 2004;49:124–38. 6. ten Have M, Vollebergh W, Bijl R, Nolen WA. Bipolar disorder in the general population in the Netherlands (prevalence, consequences and care utilisation): results from The Netherlands Mental Health Survey and Incidence Study (NEMESIS). J Affect Disord 2002;68:203–13. 7. Szadoczky E, Papp Z, Vitrai J, Rihmer Z, Furedi J. The prevalence of major depressive and bipolar disorders in Hungary. Results from a national epidemiologic survey. J Affect Disord 1998;50:153–62. 8. Bland RC, Orn H, Newman SC. Lifetime prevalence of psychiatric disorders in Edmonton. Acta Psychiatr Scand 1988;77(Suppl 338):24–32. 9. Parikh SV, Wasylenki D, Goering P, Wong J. Mood disorders: rural/urban differences in prevalence, health care utilization and disability in Ontario. J Affect Disord 1996;38:57–65. 10. Kessler RC, Rubinow DR, Holmes C, Abelson JM, Zhao S. The epidemiology of DSM-III-R bipolar I disorder in a general population survey. Psychol Med 1997;27:1079–89. 11. Weissman MM, Leaf PJ, Tischler GL, Blazer GD, Karno M, Livingston-Bruce M, and others. Affective disorders in five United States communities. Psychol Med 1988;18:141–53. 12. Statistics Canada. Canadian Community Health Survey: Mental Health and Well-Being, 2002. Available: http://www.statcan.ca/cgi-bin/imdb/p2SV.pl?Function=getSurvey&SDDS=5015&lang=en&db=IMDB&dbg=f&adm=8&dis=2. Accessed 2005 November 24. 13. Kessing LV. Gender differences in the phenomenology of bipolar disorder. Bipolar Disord 2004;6:421–5. 14. Frye MA, Altshuler LL, McElroy SL, Suppes T, Keck PE, Denicoff K, and others. Gender differences in prevalence, risk, and clinical correlates of alcoholism comorbidity in bipolar disorder. Am J Psychiatry 2003;160:883–9. 15. Robb JC, Young LT, Cooke RG, Joffe RT. Gender differences in patients with bipolar disorder influence outcome in the medical outcome survey (SF-20) subscale scores. J Affect Disord 1998;49:189–93. 16. Raymont V, Bettany D, Frangou S. The Maudsley bipolar disorder project. Clinical characteristics of bipolar disorder I in a catchment area treatment sample. Eur Psychiatry 2003;18:13–7. 17. Perlis RH, Miyahara S, Marangell LB, Wisniewski SR, Ostacher M, DelBello MP, and others. Long-term implications of early onset in bipolar disorder: data from the first 1000 participants in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Biol Psychiatry 2004;55:875–81. 18. Hendrick V, Altshuler LL, Gitlin MJ, Delrahim S, Hammen C. Gender and bipolar illness. J Clin Psychiatry 2000;61:393–6. 19. Cate Carter T, Mundo E, Parikh SV, Kennedy JL. Early age at onset as a risk factor for poor outcome of bipolar disorder. J Psychiatr Res 2003;37:297–303. 20. Leibenluft E. Women with bipolar illness: clinical and research issues. Am J Psychiatry 1996;153:163–73. 21. Roy-Byrne P, Post RM, Uhde TW, Porcu T, Davis D. The longitudinal course of recurrent affective illness: life chart data from research patients at the NIMH. Acta Psychiatr Scand Suppl 1985;317:5–34. 22. Winokur G, Coryell W, Akiskal HS, Endicott J, Keller M, Mueller T. Manic-depressive (bipolar) disorder: the course in light of a prospective ten-year follow-up of 131 patients. Acta Psychiatr Scand 1994;89:102–10. 23. Statistics Canada. Bootvar program for variance estimation. Version 2.2. Ottawa (ON): Statistics Canada; 2005. 24. Kessler R, McGonagle K, Zhao S, Nelson CB, Hughes M, Eshleman S, and others. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry 1994;51:8–19. 25. Angst J. The emerging epidemiology of hypomania and bipolar II disorder. J Affect Disord 1998;50:143–51. 26. Judd L, Akiskal H. The prevalence and disability of bipolar spectrum disorders in the US population: re-analysis of the ECA database taking into account subthreshold cases. J Affect Disord 2003;73:123–31. 27. Begley CE, Annegers JF, Swann AC, Lewis C, Coan S, Schnapp WB, and others. The lifetime cost of bipolar disorder in the US. Pharmacoeconomics 2001;19(5 Pt 1):483–95. 28. Wilkins K. Bipolar I disorder, social support and work. Health Rep 2004;15 Suppl:21–-30. 29. Boylan KR, Bieling PJ, Marriot M, Begin H, Young LT, MacQueen GM. Impact of comorbid anxiety disorder on outcome in a cohort of patients with bipolar disorder. J Clin Psychiatry 2004;65:1106–13. 30. McElroy SL, Altshuler LL, Suppes T, Keck PE, Frye MA, Denicoff KD, and others. Axis I psychiatric comorbidity and its relationship to historical illness variables in 288 patients with bipolar disorder. Am J Psychiatry 2001;158:420–6. 31. Simon NM, Otto MW, Wisniewski SR, Fossey M, Sagduyu K, Frank E, and others. Anxiety disorder comorbidity in bipolar disorder patients: data from the first 500 participants in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Am J Psychiatry 2004;161:2222–9. 32. Bland RC. Epidemiology of affective disorders: a review. Can J Psychiatry 1997;42:367–77. 33. Levin FR, Hennessy G. Bipolar disorder and substance abuse. Biol Psychiatry 2004;56:738–48. 34. Chengappa KNR, Kupfer DJ, Frank E, Houch PR, Grochocinski VJ, Cluss PA, and others. Relationship of birth cohort and early age at onset of illness in a bipolar disorder case registry. Am J Psychiatry 2003;160:1636–42. 35. Judd LL, Akiskal HS, Schettler PJ, Endicott J, Maser J, Solomon DA, and others. The long-term natural history of the weekly symptomatic status of bipolar I disorder. Arch Gen Psychiatry 2002;59:530–7. 36. Post RM, Leverich GS, Altshuler LL, Frye MA, Suppes TM, Keck PE, and others. An overview of recent findings of the Stanley Foundation Bipolar Network (part I). Bipolar Disord 2003;5:310–9. 37. Wittchen H-U. Reliability and validity studies of the WHO-Composite International Diagnostic Interview (CIDI): a critical review. J Psychiatr Res 1994;28:57–84. Author(s)Manuscript received March 2005, revised, and accepted May 2005. 1. Head, Mood Disorders Program, Sunnybrook and Women’s College Health Sciences Centre; Assistant Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario. 2. Research Scientist, Health Systems Research and Consulting Unit, Centre for Addiction and Mental Health; Assistant Professor, Departments of Psychiatry and of Public Health Science, University of Toronto, Toronto, Ontario. 3. Staff Psychiatrist, Sunnybrook and Women’s College Health Sciences Centre; Assistant Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario. 4. Research Analyst, Health Systems Research and Consulting Unit, Centre for Addiction and Mental Health, Toronto, Ontario. 5. Psychiatrist-in-Chief, Sunnybrook and Women’s College Health Sciences Centre; Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario Address for correspondence: Dr Ayal Schaffer, Sunnybrook and Women’s College HSC, 2075 Bayview Avenue, Room FG29, Toronto, ON M4N 3M5 e-mail: ayal.schaffer@sw.ca
1 | 2
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||