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

Unmet need for the treatment of depression in Atlantic Canada

Objective: Most people with depression do not receive treatment, even though effective interventions are available. Population-based data can assist health service planners to improve access to mental health services. This study aimed to examine the determinants of untreated depression in Canada's Atlantic provinces

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

Patterns of Recovery from Severe Mental Illness: A Pilot Study of Outcomes

We performed a pilot study examining the patterns of recovery from severe mental illness in a model integrated service delivery system using measures from the Milestones of Recovery Scale (MORS), a valid and reliable measure of recovery outcomes which ranges from 1 to 8 (8 levels). For purposes of presentation, we constructed an aggregate MORS (6 levels) where the levels are described as follows: (1) extreme risk; (2) unengaged, poorly self-coordinating; (3) engaged, poorly self-coordinating; (4) coping and rehabilitating; (5) early recovery, and (6) self reliant. We analyzed MORS data on individuals followed over time from The Village in Long Beach, California (658 observations). Using Markov Chains, we estimated origin-destination transition probabilities, simulating recovery outcomes for 100 months. Our models suggest that after 12 months only 8% of “extreme risk” clients remain such. Over 40% have moved to “engaged, poorly self-coordinating.” After 2 years, almost half of the initial “extreme Risk” clients are “coping/rehabilitating”, “early recovery” or “Self reliant.” Most gains occur within 2 years

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

Simulation studies of age-specific lifetime major depression prevalence

BACKGROUND: The lifetime prevalence (LTP) of Major Depressive Disorder (MDD) is the proportion of a population having met criteria for MDD during their life up to the time of assessment. Expectation holds that LTP should increase with age, but this has not usually been observed. Instead, LTP typically increases in the teenage years and twenties, stabilizes in adulthood and then begins to decline in middle age. Proposed explanations for this pattern include: a cohort effect (increasing incidence in more recent birth cohorts), recall failure and/or differential mortality. Declining age-specific incidence may also play a role. METHODS: We used a simulation model to explore patterns of incidence, recall and mortality in relation to the observed pattern of LTP. Lifetime prevalence estimates from the 2002 Canadian Community Health Survey, Mental Health and Wellbeing (CCHS 1.2) were used for model validation and calibration. RESULTS: Incidence rates predicting realistic values for LTP in the 15-24 year age group (where mortality is unlikely to substantially influence prevalence) lead to excessive LTP later in life, given reasonable assumptions about mortality and recall failure. This suggests that (in the absence of cohort effects) incidence rates decline with age. Differential mortality may make a contribution to the prevalence pattern, but only in older age categories. Cohort effects can explain the observed pattern, but only if recent birth cohorts have a much higher (approximately 10-fold greater) risk and if incidence has increased with successive birth cohorts over the past 60-70 years. CONCLUSIONS: The pattern of lifetime prevalence observed in cross-sectional epidemiologic studies seems most plausibly explained by incidence that declines with age and where some respondents fail to recall past episodes. A cohort effect is not a necessary interpretation of the observed pattern of age-specific lifetime prevalence

Physical activity interventions in schools for improving lifestyle in European countries

Background : In the last decades, children’s and adolescents’ obesity and overweight have increased in European Countries. Unhealthy eating habits and sedentary lifestyle have been recognized to determine such an epidemic. Schools represent an ideal setting to modify harmful behaviors, and physical activity could be regarded as a potential way to avoid the metabolic risks related to obesity. Methods : A systematic review of the literature was carried out to summarize the evidence of school-based interventions aimed to promote, enhance and implement physical activity in European schools. Only randomized controlled trials were included, carried out in Europe from January 2000 to April 2014, universally delivered and targeting pupils aged between 3 and 18 years old. Results : Forty-seven studies were retrieved based either on multicomponent interventions or solely physical activity programs. Most aimed to prevent obesity and cardiovascular risks among youths. While few studies showed a decrease in BMI, positive results were achieved on other outcomes, such as metabolic parameters and physical fitness. Conclusion : Physical activity in schools should be regarded as a simple, non-expensive and enjoyable way to reach all the children and adolescents with adequate doses of moderate to vigorous physical activity

Cross-sectional survey of users of internet depression communities

Background: Internet-based depression communities provide a forum for individuals to communicate and share information and ideas. There has been little research into the health status and other characteristics of users of these communities. Methods: Online cross-sectional survey of Internet depression communities to identify depressive morbidity among users of Internet depression communities in six European countries; to investigate whether users were in contact with health services and receiving treatment; and to identify user perceived effects of the communities. Results: Major depression was highly prevalent among respondents (varying by country from 40% to 64%). Forty-nine percent of users meeting criteria for major depression were not receiving treatment, and 35% had no consultation with health services in the previous year. Thirty-six percent of repeat community users who had consulted a health professional in the previous year felt that the Internet community had been an important factor in deciding to seek professional help. Conclusions: There are high levels of untreated and undiagnosed depression in users of Internet depression communities. This group represents a target for intervention. Internet communities can provide information and support for stigmatizing conditions that inhibit more traditional modes of information seeking