Seasonality in Major Depressive Disorder: Effect of Sex and Age

Major depressive disorder: hypothesis, mechanism, prevention and treatment

Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.

The Influence of the Great Recession on Adolescent Major Depressive Episodes and Treatment in the United States: An Interrupted Time Series Analysis

PURPOSE

In the United States, adolescent depression increased beginning in 2008-2010, coinciding with the Great Recession. We investigated whether this time of changing economic circumstances impacted adolescent depression and treatment.

METHODS

We analyzed data for adolescents aged 12-17 years from the 2004-2019 National Survey on Drug Use and Health (N = 256,572). Adolescents' past-year major depressive episodes (MDEs) were measured by self-reported symptoms. MDE treatment included seeing a health professional or receiving MDE medication. We tested how MDE and MDE treatment changed from pre-Great Recession (2004 to Fall 2007) to post-Great Recession (Winter 2007-2019) using interrupted time-series segmented regression models, accounting for seasonality and autocorrelation and testing for moderation by household poverty.

RESULTS

The Great Recession was not associated with an immediate increase in MDE prevalence (β:-0.77 [i.e., quarter-year change in prevalence], 95% confidence interval (CI): -2.23, 0.69). However, the increase in MDE prevalence accelerated following the Great Recession (β: 0.29, 95% CI: 0.13, 0.44). The Great Recession was not associated with immediate or long-term changes in adolescent MDE treatment (immediate β: -2.87, 95% CI: -7.79, 2.04; long-term β: 0.03, 95% CI: -0.46, 0.51). Effects were similar for households by poverty status.

DISCUSSION

The Great Recession was not associated with increased adolescent depression prevalence, although there was an acceleration in the trend of adolescent MDE following the recession. The prevalence of MDE treatment remained stable. Adolescent depression prevention efforts should be heightened as prevalence increases, including actively engaging caregivers as family supports to alleviate potential negative implications of economic distress for adolescent MDE.

Seasonal patterns of sickness absence due to diagnosed mental disorders: a nationwide 12-year register linkage study

AIMS

Although seasonality has been documented for mental disorders, it is unknown whether similar patterns can be observed in employee sickness absence from work due to a wide range of mental disorders with different severity level, and to what extent the rate of change in light exposure plays a role. To address these limitations, we used daily based sickness absence records to examine seasonal patterns in employee sickness absence due to mental disorders.

METHODS

We used nationwide diagnosis-specific psychiatric sickness absence claims data from 2006 to 2017 for adult individuals aged 16-67 (n = 636,543 sickness absence episodes) in Finland, a high-latitude country with a profound variation in daylength. The smoothed time-series of the ratio of observed and expected (O/E) daily counts of episodes were estimated, adjusted for variation in all-cause sickness absence rates during the year.

RESULTS

Unipolar depressive disorders peaked in October-November and dipped in July, with similar associations in all forms of depression. Also, anxiety and non-organic sleep disorders peaked in October-November. Anxiety disorders dipped in January-February and in July-August, while non-organic sleep disorders dipped in April-August. Manic episodes reached a peak from March to July and dipped in September-November and in January-February. Seasonality was not dependent on the severity of the depressive disorder.

CONCLUSIONS

These results suggest a seasonal variation in sickness absence due to common mental disorders and bipolar disorder, with high peaks in depressive, anxiety and sleep disorders towards the end of the year and a peak in manic episodes starting in spring. Rapid changes in light exposure may contribute to sickness absence due to bipolar disorder. The findings can help clinicians and workplaces prepare for seasonal variations in healthcare needs.

Changes in anxiety and depression symptoms during the Covid-19 lockdown in the Netherlands. The moderating role of pre-existing mental health, employment situation and alcohol consumption

PURPOSE

Evidence suggests an increase of depression and anxiety symptoms during the Covid-19 pandemic but most studies relied on cross-sectional designs and/or small samples, and they often overlooked subgroup effects in the impact of the lockdown. We investigated the effect of the pandemic on depression and anxiety symptoms, and whether it differed by employment situation and alcohol consumption.

METHODS

This longitudinal study used 23 waves of the Covid-Questionnaire (April 2020-July 2021), within the Lifelines cohort from the Netherlands (n = 76,254). Depression and anxiety symptoms were combined in a "mental health score". Linear fixed-effects models were fitted to analyse trends in mental health throughout the observation period. The moderating role of pre-existing mental health, employment situation, and alcohol consumption was tested.

RESULTS

Depression and anxiety symptoms fluctuated considerably during the observation period, with clear peaks in winter 2021, during the strictest lockdown period. Moreover, temporal patterns differed by employment situation and alcohol consumption patterns, suggesting that various subgroups reacted to the pandemic and the lockdown in different ways.

CONCLUSION

Lockdowns increased depression and anxiety symptoms in the Netherlands. The effect was particularly strong for unemployed individuals, those with risky alcohol consumption patterns and those with pre-existing mental health disorders.

Association of Redlining and Natural Environment with Depressive Symptoms in Women in the Sister Study

BACKGROUND

Improving mental health is recognized as an important factor for achieving global development goals. Despite strong evidence that neighborhood greenery promotes better mental health, there are environmental justice concerns over the distribution of neighborhood greenery. Underlying these concerns are present-day consequences of historical discriminatory financial investment practices, such as redlining which was established by the U.S. Federal Home Owners' Loan Corporation (HOLC) in the 1930s. The impacts of redlining on environmental and health disparities have been researched extensively. However, the influences of redlining on the associations between neighborhood environment and health outcomes have not been fully assessed.

OBJECTIVES

The aim of this study was to examine whether associations between residential tree cover and depressive symptoms vary across areas subject to HOLC practices.

METHODS

Depressive symptoms were defined by the 10-item Center for Epidemiologic Studies Depression Scale collected during the period 2008-2012 for 3,555 women in the Sister Study cohort residing in cities subject to HOLC practices across the United States. HOLC rating maps were obtained from the Mapping Inequality Project, University of Richmond, with neighborhoods graded as A (best for financial investment, green), B (still desirable, blue), C (declining, yellow), and D (hazardous, red-known as redlined). Tree cover within 500 m and 2,000 m from residences was estimated using 2011 U.S. Forest Service Percent Tree Canopy Cover. Mixed model using climate zone as the random effect was applied to evaluate the associations with adjustments for potential covariates. Analyses were stratified by HOLC grade.

RESULTS

Tree cover was significantly higher in neighborhoods with better HOLC grades. A 10% increase in tree cover was associated with reduced odds of depressive symptoms for the full study population, with adjusted odds ratios (AORs) of 0.93 [95% confidence interval (CI): 0.88, 0.99], and 0.91 (0.85, 0.97) for 500 -m and 2,000 -m buffer, respectively. Across HOLC grades, the strongest associations were observed in redlined neighborhoods, with respective AORs of 0.72 (95% CI: 0.52, 0.99) and 0.63 (95% CI: 0.45, 0.90) for 500 -m and 2,000 -m buffer.

DISCUSSION

Findings support a remediation strategy focused on neighborhood greenery that would address multiple public health priorities, including mental health and environmental justice. https://doi.org/10.1289/EHP12212.

Seasonality of brain function: role in psychiatric disorders

Seasonality patterns are reported in various psychiatric disorders. The current paper summarizes findings on brain adaptations associated with seasonal changes, factors that contribute to individual differences and their implications for psychiatric disorders. Changes in circadian rhythms are likely to prominently mediate these seasonal effects since light strongly entrains the internal clock modifying brain function. Inability of circadian rhythms to accommodate to seasonal changes might increase the risk for mood and behavior problems as well as worse clinical outcomes in psychiatric disorders. Understanding the mechanisms that account for inter-individual variations in seasonality is relevant to the development of individualized prevention and treatment for psychiatric disorders. Despite promising findings, seasonal effects are still understudied and only controlled as a covariate in most brain research. Rigorous neuroimaging studies with thoughtful experimental designs, powered sample sizes and high temporal resolution alongside deep characterization of the environment are needed to better understand the seasonal adaptions of the human brain as a function of age, sex, and geographic latitude and to investigate the mechanisms underlying the alterations in seasonal adaptation in psychiatric disorders.

Seasonal Effects on Hospitalizations Due to Mood and Psychotic Disorders: A Nationwide 31-Year Register Study

Purpose

To examine seasonal patterns of hospital admissions due to mood and psychotic disorders and to investigate whether the admission rates show variation according to the seasonal daylength (photoperiods).

Patients and Methods

A retrospective nationwide register-based cohort of all psychiatric admissions (N=978,079) during 1987–2017 in Finland was utilized. The smoothed time-series of adjusted ratio of observed and expected (O/E) daily counts were estimated to examine seasonal variation. The mean O/E with 95% confidence intervals (CI) was used to study the admission rates by photoperiods. The calendar days were classified into the 71-day photoperiods based on the daylength (long/summer, short/winter, equal/spring, equal/fall) and the pace of change in daylength (slowly/rapidly increasing/decreasing daylength).

Results

Manic episodes peaked in summer during the long (mean O/E=1.10, 95% CI=1.06–1.13) and slowly decreasing (1.09, 1.06–1.13) photoperiods and had a nadir in winter during the slowly increasing (0.93, 0.89–0.98) photoperiod. Admissions for unipolar depressive (UPD) episodes peaked in autumn and in spring at the end of the rapidly decreasing (1.03, 1.02–1.04) and increasing (1.03, 1.01–1.04) photoperiod, and dropped in summer during the long and slowly decreasing (0.95, 0.94–0.96) photoperiods. Bipolar depressive (BPD) and mixed episodes signaled excess admissions in autumn and in spring. Admissions for schizophrenia were higher than expected from summer to early-autumn, during the long and slowly decreasing photoperiods (1.02, 1.02–1.03), and lower than expected in other seasons, especially in mid-spring during the rapidly increasing photoperiod (0.98, 0.98–0.99).

Conclusion

The study indicates the seasonality and photoperiodicity of mental disorders, especially for manic episodes. The seasonal pattern is similar between schizophrenia and manic episodes, and between UPD, BPD, and mixed episodes.

Depressive Disorder Related Hospitalizations in Portugal Between 2008-2015: a Nationwide Observational Study

Depression is a prevalent disease, being one of the most relevant contributors of disability in the overall global burden of diseases. Hospitalization episodes are important quality indicators in psychiatric care. The primary aim of this study is to analyse depressive disorder related hospitalizations in Portuguese public hospitals and to detail clinical and sociodemographic differences among various subtypes of depression. Admissions with a primary diagnosis of depression in adult patients(> = 18 years) were selected from a national mainland hospitalization database. ICD-9-CM codes were used to select the diagnoses of interest: 296.2 × to 296.3x (Major depressive disorder), 300.4 (Dysthymic disorder) and 311 (Depressive disorder, not elsewhere classified). Birth date, sex, residence address, primary and secondary diagnoses, admission date, discharge date, length of stay (LoS), discharge status, and hospital estimated charges were obtained. A total of 28,569 hospitalizations (22,387 patients) with a primary diagnosis of depression were analysed. In the 8-year period of the study, 19.1% of all hospitalizations with a primary diagnosis of psychiatric disorder were linked to Depression. Major Depressive episodes were the most common (n = 15,384; 53.8%), followed by Depression unspecified episodes (n = 6,793; 23.8%), and Dysthymia (n = 6,392; 22.4%). Most episodes occurred in female patients (70.2%; n = 20,052), with a mean age of 50.6 years, and 37.0% (n = 10,564) of the episodes were associated to other psychiatric comorbidities. Depressive disorders are one of the leading causes of hospitalization in Portuguese psychiatric departments, being responsible for approximately 1 in 5 hospitalizations with a psychiatric diagnosis.

Significantly Increased Public Interest in Major Depressive Disorder During the COVID-19 Pandemic: Insights From a Google Trends Analysis

Background

As early as before the coronavirus disease 2019 (COVID-19) pandemic, nearly one billion people worldwide suffered from mental health problems. Of all the mental health conditions, major depressive disorder (MDD) is the leading cause of global health-related burden. During the COVID-19 pandemic, many uncertain factors affecting mental health accumulated, such as virus transmission, blockade and ban, public transport restrictions, closure of schools and enterprises, and reduction of social interaction, which led to an increase in the potential risk of MDD, further increasing the global health-related burden.

Methodology

To better clarify the public interest in major depressive disorder during the COVID-19 pandemic, a Google Trends analysis was employed with data from December 2019 to December 2021, taking the cumulative diagnosis rate and cumulative mortality rate of COVID-19 as the reference standard, The changes in public interest and behavior in online searching for major depressive disorder in the three countries most affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus (i.e. the United States, Brazil, and India) were evaluated.

Results

We observed that during the COVID-19 pandemic, public interest in major depressive disorder increased significantly on the Internet. At the same time, compared with the United States, this upward trend is more prominent in India and Brazil. The study found that the major depressive disorder search index of the United States reached the maximum at the end of September 2021, the major depressive disorder search index of Brazil reached the maximum at the beginning of July 2021, and the major depressive disorder search index of India reached the maximum at the beginning of June 2021. The above time nodes are the first turning point of decline after the continuous surge of COVID-19 confirmed cases in the United States, Brazil, and India, indicating that there is an important time correlation between the surge of COVID-19 cases and the public online search term major depressive disorder.

Conclusion

The Google Trends analysis shows that public interest in major depressive disorder is on the rise under the COVID-19 pandemic and that COVID-19 may be associated with MDD. These findings deserve further exploration, especially as a growing body of research reports suggests that the COVID-19 pandemic has led to a surge in the prevalence of MDD. The epidemic alerts the vast majority of countries to urgently strengthen mental health systems and provide patients with the necessary interventions based on the determinants of poor mental health.