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Lay opinions and published papers alike suggest mood varies with the seasons, commonly framed as higher rates of depression mood in winter. Memory and confirmation bias may have influenced previous studies. We therefore systematically searched for and reviewed studies on the topic, but excluded study designs where explicit referrals to seasonality were included in questions, interviews or data collection.
Methods
Systematic literature search in Cochrane database, DARE, Medline, Embase, PsychINFO and CINAHL, reporting according to the PRISMA framework, and study quality assessment using the Newcastle-Ottawa scale. Two authors independently assessed each study for inclusion and quality assessment. Due to large heterogeneity, we used a descriptive review of the studies.
Results
Among the 41 included studies, there was great heterogeneity in regards to included symptoms and disorder definitions, operationalisation and measurement. We also observed important heterogeneity in how definitions of ‘seasons’ as well as study design, reporting and quality. This heterogeneity precluded meta-analysis and publication bias analysis. Thirteen of the studies suggested more depression in winter. The remaining studies suggested no seasonal pattern, seasonality outside winter, or inconclusive results.
Conclusions
The results of this review suggest that the research field of seasonal variations in mood disorders is fragmented, and important questions remain unanswered. There is some support for seasonal variation in clinical depression, but our results contest a general population shift towards lower mood and more sub-threshold symptoms at regular intervals throughout the year. We suggest future research on this issue should be aware of potential bias by design and take into account other biological and behavioural seasonal changes that may nullify or exacerbate any impact on mood.
The second Singapore Mental Health Study (SMHS) – a nationwide, cross-sectional, epidemiological survey - was initiated in 2016 with the intent of tracking the state of mental health of the general population in Singapore. The study employed the same methodology as the first survey initiated in 2010. The SMHS 2016 aimed to (i) establish the 12-month and lifetime prevalence and correlates of major depressive disorder (MDD), dysthymia, bipolar disorder, generalised anxiety disorder (GAD), obsessive compulsive disorder (OCD) and alcohol use disorder (AUD) (which included alcohol abuse and dependence) and (ii) compare the prevalence of these disorders with reference to data from the SMHS 2010.
Methods
Door-to-door household surveys were conducted with adult Singapore residents aged 18 years and above from 2016 to 2018 (n = 6126) which yielded a response rate of 69.0%. The subjects were randomly selected using a disproportionate stratified sampling method and assessed using World Health Organization Composite International Diagnostic Interview version 3.0 (WHO-CIDI 3.0). The diagnoses of lifetime and 12-month selected mental disorders including MDD, dysthymia, bipolar disorder, GAD, OCD, and AUD (alcohol abuse and alcohol dependence), were based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria.
Results
The lifetime prevalence of at least one mood, anxiety or alcohol use disorder was 13.9% in the adult population. MDD had the highest lifetime prevalence (6.3%) followed by alcohol abuse (4.1%). The 12-month prevalence of any DSM-IV mental disorders was 6.5%. OCD had the highest 12-month prevalence (2.9%) followed by MDD (2.3%). Lifetime and 12-month prevalence of mental disorders assessed in SMHS 2016 (13.8% and 6.4%) was significantly higher than that in SMHS 2010 (12.0% and 4.4%). A significant increase was observed in the prevalence of lifetime GAD (0.9% to 1.6%) and alcohol abuse (3.1% to 4.1%). The 12-month prevalence of GAD (0.8% vs. 0.4%) and OCD (2.9% vs. 1.1%) was significantly higher in SMHS 2016 as compared to SMHS 2010.
Conclusions
The high prevalence of OCD and the increase across the two surveys needs to be tackled at a population level both in terms of creating awareness of the disorder and the need for early treatment. Youth emerge as a vulnerable group who are more likely to be associated with mental disorders and thus targeted interventions in this group with a focus on youth friendly and accessible care centres may lead to earlier detection and treatment of mental disorders.
Major depressive disorders are highly prevalent in the world population, contribute substantially to the global disease burden and cause high health care expenditures. Information on the economic impact of depression, as provided by cost-of-illness (COI) studies, can support policymakers in the decision-making regarding resource allocation. Although the literature on COI studies of depression has already been reviewed, there is no quantitative estimation of depression excess costs across studies yet. Our aims were to systematically review COI studies of depression with comparison group worldwide and to assess the excess costs of depression in adolescents, adults, elderly, and depression as a comorbidity of a primary somatic disease quantitatively in a meta-analysis.
Methods
We followed the PRISMA reporting guidelines. PubMed, PsycINFO, NHS EED, and EconLit were searched without limitations until 27/04/2018. English or German full-text peer-reviewed articles that compared mean costs of depressed and non-depressed study participants from a bottom-up approach were included. We only included studies reporting costs for major depressive disorders. Data were pooled using a random-effects model and heterogeneity was assessed with I2 statistic. The primary outcome was ratio of means (RoM) of costs of depressed v. non-depressed study participants, interpretable as the percentage change in mean costs between the groups.
Results
We screened 12 760 articles by title/abstract, assessed 393 articles in full-text and included 48 articles. The included studies encompassed in total 55 898 depressed and 674 414 non-depressed study participants. Meta-analysis showed that depression was associated with higher direct costs in adolescents (RoM = 2.79 [1.69–4.59], p < 0.0001, I2 = 87%), in adults (RoM = 2.58 [2.01–3.31], p < 0.0001, I2 = 99%), in elderly (RoM = 1.73 [1.47–2.03], p < 0.0001, I2 = 73%) and in participants with comorbid depression (RoM = 1.39 [1.24–1.55], p < 0.0001, I2 = 42%). In addition, we conducted meta-analyses for inpatient, outpatient, medication and emergency costs and a cost category including all other direct cost categories. Meta-analysis of indirect costs showed that depression was associated with higher costs in adults (RoM = 2.28 [1.75–2.98], p < 0.0001, I2 = 74%).
Conclusions
This work is the first to provide a meta-analysis in a global systematic review of COI studies for depression. Depression was associated with higher costs in all age groups and as comorbidity. Pooled RoM was highest in adolescence and decreased with age. In the subgroup with depression as a comorbidity of a primary somatic disease, pooled RoM was lower as compared to the age subgroups. More evidence in COI studies for depression in adolescence and for indirect costs would be desirable.
For the past quarter of a century, Frank et al.’s (1991) consensus-based definitions of major depressive disorder (MDD) episode, remission, recovery, relapse and recurrence have been the paramount driving forces for consistency in MDD research as well as in clinical practice. This study aims to review the evidence for the empirical validation of Frank et al.’s proposed concept definitions and to discuss evidence-based modifications.
Methods.
A literature search of Web of Science and PubMed from 1/1/1991 to 08/30/2017 identified all publications which referenced Frank et al.’s request for definition validation. Publications with data relevant for validation were included and checked for referencing other studies providing such data.
Results.
A total of 56 studies involving 39 315 subjects were included, mainly presenting data to validate the severity and duration thresholds for defining remission and recovery. Most studies indicated that the severity threshold for defining remission should decrease. Additionally, specific duration thresholds to separate remission from recovery did not add any predictive value to the notion that increased remission duration alleviates the risk of reoccurrence of depressive symptoms. Only limited data were available to validate the severity and duration criteria for defining a depressive episode.
Conclusions.
Remission can best be defined as a less symptomatic state than previously assumed (Hamilton Rating Scale for Depression, 17-item version (HAMD-17) ⩽4 instead of ⩽7), without applying a duration criterion. Duration thresholds to separate remission from recovery are not meaningful. The minimal duration of depressive symptoms to define a depressive episode should be longer than 2 weeks, although further studies are required to recommend an exact duration threshold. These results are relevant for researchers and clinicians aiming to use evidence-based depression outcomes.