Duration of anxiety disorder and its associated risk indicators: Results of a longitudinal study of the general population

Neuroticism/negative emotionality is associated with increased reactivity to uncertain threat in the bed nucleus of the stria terminalis, not the amygdala

Neuroticism/Negative Emotionality (N/NE)-the tendency to experience anxiety, fear, and other negative emotions-is a fundamental dimension of temperament with profound consequences for health, wealth, and wellbeing. Elevated N/NE is associated with a panoply of adverse outcomes, from reduced socioeconomic attainment to psychiatric illness. Animal research suggests that N/NE reflects heightened reactivity to uncertain threat in the bed nucleus of the stria terminalis (BST) and central nucleus of the amygdala (Ce), but the relevance of these discoveries to humans has remained unclear. Here we used a novel combination of psychometric, psychophysiological, and neuroimaging approaches to rigorously test this hypothesis in an ethnoracially diverse, sex-balanced sample of 220 emerging adults selectively recruited to encompass a broad spectrum of N/NE. Cross-validated robust-regression analyses demonstrated that N/NE is preferentially associated with heightened BST activation during the uncertain anticipation of a genuinely distressing threat (aversive multimodal stimulation), whereas N/NE was unrelated to BST activation during certain-threat anticipation, Ce activation during either type of threat anticipation, or BST/Ce reactivity to threat-related faces. It is often assumed that different threat paradigms are interchangeable assays of individual differences in brain function, yet this has rarely been tested. Our results revealed negligible associations between BST/Ce reactivity to the anticipation of threat and the presentation of threat-related faces, indicating that the two tasks are non-fungible. These observations provide a framework for conceptualizing emotional traits and disorders; for guiding the design and interpretation of biobank and other neuroimaging studies of psychiatric risk, disease, and treatment; and for informing mechanistic research.

Integrating EEG and Ensemble Learning for Accurate Grading and Quantification of Generalized Anxiety Disorder: A Novel Diagnostic Approach

Current assessments for generalized anxiety disorder (GAD) are often subjective and do not rely on a standardized measure to evaluate the GAD across its severity levels. The lack of objective and multi-level quantitative diagnostic criteria poses as a significant challenge for individualized treatment strategies. To address this need, this study aims to establish a GAD grading and quantification diagnostic model by integrating an electroencephalogram (EEG) and ensemble learning. In this context, a total of 39 normal subjects and 80 GAD patients were recruited and divided into four groups: normal control, mild GAD, moderate GAD, and severe GAD. Ten minutes resting state EEG data were collected for every subject. Functional connectivity features were extracted from each EEG segment with different time windows. Then, ensemble learning was employed for GAD classification studies and brain mechanism analysis. Hence, the results showed that the Catboost model with a 10 s time window achieved an impressive 98.1% accuracy for four-level classification. Particularly, it was found that those functional connections situated between the frontal and temporal lobes were significantly more abundant than in other regions, with the beta rhythm being the most prominent. The analysis framework and findings of this study provide substantial evidence for the applications of artificial intelligence in the clinical diagnosis of GAD.

Risk factors of chronic course of anxiety and depressive disorders: a 3-year longitudinal study in the general population

BACKGROUND

Risk factors of a chronic course of anxiety and depressive disorders were previously studied using a limited definition of recovery, i.e. remission of the index disorder. However, frequently, other mental disorders are present at follow-up. Thus, the course of anxiety and depressive disorders was represented too rosy and the identified determinants may not apply when using a broader, more realistic definition. Additionally, physical health risk factors have often been ignored.

METHODS

Data were used from two waves of the Netherlands Mental Health Survey and Incidence Study-2 including 509 respondents with 12-month anxiety disorder (panic disorder, social phobia, agoraphobia or generalized anxiety disorder) or/and major depressive disorder at baseline. Chronic course was defined as (1) presence of index disorder; and (2) presence of any anxiety, mood or substance use disorder (overall course) during the subsequent three years. Regression models were built with sociodemographic, clinical, and lifestyle/physical health indicators. Predictive accuracy was evaluated with area under the curve (AUC).

RESULTS

Chronic course of the index disorder was present among 24.8% of cases, whereas 38.7% had a chronic overall course. The accuracy of prediction of chronic course of the index disorder was suboptimal (AUC = 0.68) compared to prediction of overall course (AUC = 0.75). The main risk factors were baseline number of mental disorders, neuroticism, childhood abuse, parental psychopathology and alcohol use. Lifestyle and physical health indicators were marginally relevant.

CONCLUSION

Transdiagnostic risk factors are important in predicting overall course of anxiety and depressive disorders but cannot accurately predict chronic course of the index disorder.

Changes in anxiety and depression among public health workers during the COVID-19 pandemic response

OBJECTIVES

The COVID-19 pandemic has negatively impacted mental health indicators, leading to an increase in symptoms of anxiety and depression in both the general population of adults and children and many occupational groups. This study aims to examine changes in anxiety and depression among a cohort of public health workers in the U.S. during the first year of the COVID-19 pandemic and identify potential risk factors.

METHODS

Longitudinal data were collected from a sub-sample (N = 85) of public health workers in 23 U.S. states who completed two surveys in 2020 and 2021. Information on background characteristics, personal well-being, and work environment as well as validated scales to assess generalized anxiety disorder (GAD), depressive disorder, and burnout was collected. Data were analyzed using Stata Version 17, and significant differences were determined using Pearson's Chi2 and Fisher's Exact tests.

RESULTS

The proportion of those reporting GAD (46.3% to 23.2%) or depression (37.8% to 26.8%) improved from Survey 1 to Survey 2 overall; symptoms of anxiety saw the largest improvement. Persistent depression was associated with sustained burnout, changes in social support, and days worked per week.

CONCLUSION

Public health workers experienced elevated levels of anxiety and depression during the initial pandemic response, but a reduction in these symptoms was observed in the subsequent year after vaccines had become widely available. However, unmet needs remain for ongoing workplace mental health supports to address burnout, as well as for additional emotional supports outside of work for public health professionals.

The Netherlands Mental Health Survey and Incidence Study-3 (NEMESIS-3): Objectives, methods and baseline characteristics of the sample

OBJECTIVES

NEMESIS-3 (Netherlands Mental Health Survey and Incidence Study-3) is a psychiatric epidemiological cohort study of the Dutch general population that replicates and expands on two previous NEMESIS-studies conducted in 1996-1999 and 2007-2018 respectively. The main aims of NEMESIS-3 are to provide up-to-date information on the prevalence, incidence, course and consequences of mental disorders, their risk indicators, and to study the relevant time trends. This paper gives an overview of the objectives and methods of NEMESIS-3, especially of the recently completed first wave, and describes the sample characteristics.

METHODS

NEMESIS-3 is based on a multistage, stratified random sampling of individuals aged 18-75 years. Face-to-face interviews were laptop computer-assisted and held at the respondent's home. A slightly modified Composite International Diagnostic Interview (CIDI) version 3.0 was used to assess both Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) and DSM-5 mental disorders. Two follow-up waves are planned three and six years after baseline.

RESULTS

In the first wave, performed from November 2019 to March 2022, 6194 individuals were interviewed: 1576 respondents before and 4618 respondents during the COVID-19 pandemic. The average interview duration was 91 min and the response rate was 54.6%. The sample consisted of 50.4% women and had a mean age of 47.9 years. The sample was reasonable nationally representative, although some sociodemographic groups were somewhat underrepresented.

CONCLUSIONS

Despite the COVID-19 restrictions, we were able to build a large and comprehensive dataset of good quality, permitting us to investigate the latest trends in mental health status, various new topics related to mental health, and the extent to which the pandemic has had an effect on the population's mental health.

Recurrence of anxiety disorders and its predictors in the general population

BACKGROUND

Anxiety disorders frequently recur in clinical populations, but the risk of recurrence of anxiety disorders is largely unknown in the general population. In this study, recurrence of anxiety and its predictors were studied in a large cohort of the adult general population.

METHODS

Baseline, 3-year and 6-year follow-up data were derived from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2). Respondents (N = 468) who had been in remission for at least a year prior to baseline were included. Recurrence was assessed at 3 and 6 years after baseline, using the Composite International Diagnostic Interview version 3.0. Cumulative recurrence rates were estimated using the number of years since remission of the last anxiety disorder. Furthermore, Cox regression analyses were conducted to investigate predictors of recurrence, using a broad range of putative predictors.

RESULTS

The estimated cumulative recurrence rate was 2.1% at 1 year, 6.6% at 5 years, 10.6% at 10 years, and 16.2% at 20 years. Univariate regression analyses predicted a shorter time to recurrence for several variables, of which younger age at interview, parental psychopathology, neuroticism and a current depressive disorder remained significant in the, age and gender-adjusted, multivariable regression analysis.

CONCLUSIONS

Recurrence of anxiety disorders in the general population is common and the risk of recurrence extends over a lengthy period of time. In clinical practice, alertness to recurrence, monitoring of symptoms, and quick access to health care in case of recurrence are needed.

Alcohol use as a predictor of the course of major depressive disorder: a prospective population-based study

AIMS

There are indications that problematic alcohol use may negatively impact the course of major depressive disorder (MDD). However, most studies on alcohol use and adverse MDD outcomes are conducted amongst MDD populations with (severe) alcohol use disorder in psychiatric treatment settings. Therefore, it remains unclear whether these results can be generalised to the general population. In light of this, we examined the longitudinal relationship between alcohol use and MDD persistence after a 3-year follow-up amongst people with MDD from the general population.

METHODS

Data were derived from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2), a psychiatric epidemiological prospective study comprising four waves amongst the adult Dutch general population (n = 6.646). The study sample (n = 642) consisted of those with 12-month MDD who participated at the follow-up wave. The outcome was 12-month MDD persistence after the 3-year follow-up, which was assessed via the Composite International Diagnostic Interview version 3.0. Weekly alcohol consumption was operationalised as non-drinking (0 drinks), low-risk drinking (⩽7 drinks; reference), at-risk drinking (women 8-13 drinks, men 8-20 drinks) and high-risk drinking (women ⩾14, men ⩾21 drinks). We performed univariate and multiple logistic regression analyses, which were adjusted for various socio-demographic and health-related factors.

RESULTS

The majority (67.4%) of the MDD sample were female, while the mean age was 47.1 years. Amongst these, 23.8% were non-drinkers, 52.0% were low-risk drinkers and 14.3% and 9.4% were at-risk and high-risk drinkers, respectively. Around one-quarter of the sample (23.6%) met the criteria for a persistent MDD after 3-year follow-up. No statistically significant association was found between alcohol use and MDD persistence, either for the crude model or the adjusted models. In comparison to low-risk drinking, the full adjusted model showed no statistically significant associations between MDD persistence and non-drinking (odds ratio (OR) = 1.15, p = 0.620), at-risk drinking (OR = 1.25, p = 0.423), or high-risk drinking (OR = 0.74, p = 0.501).

CONCLUSIONS

Contrary to our expectations, our findings showed that alcohol use was not a predictor of MDD persistence after 3-year follow-up amongst people with MDD from the general population.

How chronic are depressive and anxiety disorders? 9-year general population study using narrow and broad course outcomes

BACKGROUND

Existing studies on disease course usually apply relatively short follow-up periods and narrow definitions of disease course resulting in too optimistic views on disease prognosis. This study explores the relevance of using a longer and broader (cross-disorder) perspective.

METHODS

Respondents with a 12-month disorder at baseline and available at 3-, 6- and 9-year follow-up were selected (major depressive disorder, MDD: n = 208; anxiety disorder: n = 220) from a general population study (N = 6646). DSM-IV disorders were assessed with the Composite International Diagnostic Interview. Disease course was described using a short and narrow perspective (i.e., 3-year follow-up, and considering presence of the index disorder only) and a long and broad perspective (9-year follow-up, and considering presence of any mood, anxiety or substance use disorder as outcome).

RESULTS

The recovery rates of both MDD and anxiety disorder reduced by half when the perspective switched from short and narrow (MDD: 74.0 %; anxiety disorder: 79.5 %) to long and broad (35.6 % and 40.0 % respectively). At 9-year follow-up, the rates of a persistent disorder (a disorder at each follow-up assessment) tripled when the perspective switched from narrow to broad (MDD: from 4.8 % to 13.9 %; anxiety disorder: from 4.5 % to 15.5 %).

LIMITATIONS

The findings are not generalizable to the most severe depressed and anxious patients.

CONCLUSIONS

Most people with MDD or anxiety disorder in the general population have a rather favourable prognosis when a narrow perspective is applied, but an unfavourable prognosis when a long-term and broad perspective is applied. Consequently, MDD and anxiety disorder should not merely be perceived as episodic disorders, and require longer-term disease monitoring and management.

Illness-Death Model as a Framework for Chronic Disease Burden Projection: Application to Mental Health Epidemiology

Introduction

Estimates of future disease burden supports public health decision-making. Multistate modeling of chronic diseases is still limited despite a long history of mathematical modeling of diseases. We introduce a discrete time approach to the illness-death model and a recursion formula, which can be utilized to project chronic disease burden. We further illustrate an example of the technique applied to anxiety disorders in Germany.

Materials and Equipment

The illness-death model is a multistate model that relates prevalence, incidence, mortality, and remission. A basic recursion formula that considers prevalence, incidence, mortality among the susceptible, and mortality among the diseased can be applied to irreversible chronic diseases such as diabetes. Among several mental disorders, remission plays a key role and thus an extended recursion formula taking remission into account is derived.

Methods

Using the Global Burden of Disease Study 2019 data and population projections from the Federal Statistical Office of Germany, a total number of individuals with anxiety disorders by sex in Germany from 2019 to 2030 was projected. Regression models were fitted to historical data for prevalence and incidence. Differential mortality risks were modeled based on empirical evidence. Remission was estimated from prevalence, incidence, and mortality, applying the extended recursion formula. Sex- and age-specific prevalence of 2019 was given as the initial value to estimate the total number of individuals with anxiety disorders for each year up to 2030. Projections were also made through simple extrapolation of prevalence for comparison.

Results

From 2019 to 2030, we estimated a decrease of 52,114 (-1.3%) individuals with anxiety disorders among women, and an increase of 166,870 (+8.5%) cases among men, through the illness-death model approach. With prevalence extrapolation, an increase of 381,770 (+9.7%) among women and an increase of 272,446 (+13.9%) among men were estimated.

Discussion

Application of the illness-death model with discrete time steps is possible for both irreversible chronic diseases and diseases with possible remissions, such as anxiety disorders. The technique provides a framework for disease burden prediction. The example provided here can form a basis for running simulations under varying transition probabilities.

Circadian rhythm disorder and anxiety as mental health complications in post-COVID-19

In 2020, the world gained dramatic experience of the development of the 2019 coronavirus disease pandemic (COVID-19) caused by severe acute respiratory syndrome 2 (SARS-CoV-2). Recent researches notice an increasing prevalence of anxiety and circadian rhythm disorders during COVID-19 pandemic. The aim of the study was describing clinical features of circadian rhythm disorders and the level of anxiety in persons who have had COVID-19. We have conducted a cohort retrospective study that included 278 patients who were divided into 2 study groups according to medical history: group 1 includes patients with a history of COVID-19; group 2 consists of patients who did not have clinically confirmed COVID-19 and are therefore considered not to have had this disease. To objectify circadian rhythm disorders, they were verified in accordance with the criteria of the International Classification of Sleep Disorders-3. The level of anxiety was assessed by the State-Trait Anxiety Inventory. The most common circadian rhythm disorders were sleep phase shifts. We found that COVID-19 in the anamnesis caused a greater predisposition of patients to the development of circadian rhythm disorders, in particular delayed sleep phase disorder. In addition, it was found that after COVID-19 patients have increased levels of both trait and state anxiety. In our study, it was the first time that relationships between post-COVID-19 anxiety and circadian rhythm disorders had been indicated. Circadian rhythm disorders are associated with increased trait and state anxiety, which may indicate additional ways to correct post-COVID mental disorders and their comorbidity with sleep disorders.