An animated depiction of major depression epidemiology

<p>Abstract</p> <p>Background</p> <p>Epidemiologic estimates are now available for a variety of parameters related to major depression epidemiology (incidence, prevalence, etc.). These estimates are potentially useful for policy and planning purposes, but it is first necessary that they be synthesized into a coherent picture of the epidemiology of the condition. Several attempts to do so have been made using mathematical modeling procedures. However, this information is not easy to communicate to users of epidemiological data (clinicians, administrators, policy makers).</p> <p>Methods</p> <p>In this study, up-to-date data on major depression epidemiology were integrated using a discrete event simulation model. The mathematical model was animated in Virtual Reality Modeling Language (VRML) to create a visual, rather than mathematical, depiction of the epidemiology.</p> <p>Results</p> <p>Consistent with existing literature, the model highlights potential advantages of population health strategies that emphasize access to effective long-term treatment. The paper contains a web-link to the animation.</p> <p>Conclusion</p> <p>Visual animation of epidemiological results may be an effective knowledge translation tool. In clinical practice, such animations could potentially assist with patient education and enhanced long-term compliance.</p

Accumulation of major depressive episodes over time in a prospective study indicates that retrospectively assessed lifetime prevalence estimates are too low

<p>Abstract</p> <p>Background</p> <p>Most epidemiologic studies concerned with Major Depressive Disorder have employed cross-sectional study designs. Assessment of lifetime prevalence in such studies depends on recall of past depressive episodes. Such studies may underestimate lifetime prevalence because of incomplete recall of past episodes (recall bias). An opportunity to evaluate this issue arises with a prospective Canadian study called the National Population Health Survey (NPHS).</p> <p>Methods</p> <p>The NPHS is a longitudinal study that has followed a community sample representative of household residents since 1994. Follow-up interviews have been completed every two years and have incorporated the Composite International Diagnostic Interview short form for major depression. Data are currently available for seven such interview cycles spanning the time frame 1994 to 2006. In this study, cumulative prevalence was calculated by determining the proportion of respondents who had one or more major depressive episodes during this follow-up interval.</p> <p>Results</p> <p>The annual prevalence of MDD ranged between 4% and 5% of the population during each assessment, consistent with existing literature. However, 19.7% of the population had at least one major depressive episode during follow-up. This included 24.2% of women and 14.2% of men. These estimates are nearly twice as high as the lifetime prevalence of major depressive episodes reported by cross-sectional studies during same time interval.</p> <p>Conclusion</p> <p>In this study, prospectively observed cumulative prevalence over a relatively brief interval of time exceeded lifetime prevalence estimates by a considerable extent. This supports the idea that lifetime prevalence estimates are vulnerable to recall bias and that existing estimates are too low for this reason.</p

Describing the longitudinal course of major depression using Markov models: Data integration across three national surveys

BACKGROUND: Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. METHODS: Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada) were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. RESULTS: The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study using the WHO Mental Health Composite International Diagnostic Interview (WMH-CIDI). Consistent with previous work, transition probabilities reflecting recovery were high in the initial weeks of the episodes, and declined by a fixed proportion with each passing week. CONCLUSION: Markov models provide a framework for integrating psychiatric epidemiological data. Previous studies have illustrated the utility of Markov models for decomposing prevalence into its various determinants: incidence, recovery and mortality. This study extends the Markov approach by distinguishing several recurrence categories

The effect of major depression on participation in preventive health care activities

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to determine whether major depressive episodes (MDE) contribute to a lower rate of participation in three prevention activities: blood pressure checks, mammograms and Pap tests.</p> <p>Methods</p> <p>The data source for this study was the Canadian National Population Health Survey (NPHS), a longitudinal study that started in 1994 and has subsequently re-interviewed its participants every two years. The NPHS included a short form version of the Composite International Diagnostic Interview (CIDI-SF) to assess past year MDE and also collected data on participation in preventive activities. Initially, we examined whether respondents with MDE in a particular year were less likely to participate in screening during that same year. In order to assess whether MDE negatively altered the pattern of participation, those successfully screened at the baseline interview in 1994 were identified and divided into cohorts depending on their MDE status. Proportional hazard models were used to quantify the effect of MDE on subsequent participation in screening.</p> <p>Results</p> <p>No effect of MDE on participation in the three preventive activities was identified either in the cross-sectional or longitudinal analysis. Adjustment for a set of relevant covariates did not alter this result.</p> <p>Conclusion</p> <p>Whereas MDE might be expected to reduce the frequency of participation in screening activities, no evidence for this was found in the current analysis. Since people with MDE may contact the health system more frequently, this may offset any tendency of the illness itself to reduce participation in screening.</p

Typology of adults diagnosed with mental disorders based on socio-demographics and clinical and service use characteristics

<p>Abstract</p> <p>Background</p> <p>Mental disorder is a leading cause of morbidity worldwide. Its cost and negative impact on productivity are substantial. Consequently, improving mental health-care system efficiency - especially service utilisation - is a priority. Few studies have explored the use of services by specific subgroups of persons with mental disorder; a better understanding of these individuals is key to improving service planning. This study develops a typology of individuals, diagnosed with mental disorder in a 12-month period, based on their individual characteristics and use of services within a Canadian urban catchment area of 258,000 persons served by a psychiatric hospital.</p> <p>Methods</p> <p>From among the 2,443 people who took part in the survey, 406 (17%) experienced at least one episode of mental disorder (as per the Composite International Diagnostic Interview (CIDI)) in the 12 months pre-interview. These individuals were selected for cluster analysis.</p> <p>Results</p> <p>Analysis yielded four user clusters: people who experienced mainly anxiety disorder; depressive disorder; alcohol and/or drug disorder; and multiple mental and dependence disorder. Two clusters were more closely associated with females and anxiety or depressive disorders. In the two other clusters, males were over-represented compared with the sample as a whole, namely, substance abuses with or without concomitant mental disorder. Clusters with the greatest number of mental disorders per subject used a greater number of mental health-care services. Conversely, clusters associated exclusively with dependence disorders used few services.</p> <p>Conclusion</p> <p>The study found considerable heterogeneity among socio-demographic characteristics, number of disorders, and number of health-care services used by individuals with mental or dependence disorders. Cluster analysis revealed important differences in service use with regard to gender and age. It reinforces the relevance of developing targeted programs for subgroups of individuals with mental and/or dependence disorders. Strategies aimed at changing low service users' attitude (youths and males) or instituting specialised programs for that particular clientele should be promoted. Finally, as concomitant disorders are frequent among individuals with mental disorder, psychological services and/or addiction programs must be prioritised as components of integrated services when planning treatment.</p

The emerging modern face of mood disorders: a didactic editorial with a detailed presentation of data and definitions

The present work represents a detailed description of our current understanding and knowledge of the epidemiology, etiopathogenesis and clinical manifestations of mood disorders, their comorbidity and overlap, and the effect of variables such as gender and age. This review article is largely based on the 'Mood disorders' chapter of the Wikibooks Textbook of Psychiatry http://en.wikibooks.org/wiki/Textbook_of_Psychiatry/Mood_Disorders