Journal of affective disorders最新文献

Background: There is ample evidence that socioeconomic status, objectively quantified by tangible resources, impacts mental health outcomes. However, the psychosocial mechanism linking objective socioeconomic status (OSS) with mental health is not clear. This study examined to what extent associations between OSS and the twelve-month prevalence of mental disorders, are mediated by the individual perception of social conditions-the subjective social status (SSS).

Methods: We employed data from the Iranian Mental Health Survey (IranMHS), collected through interviews with 7886 Iranian adults. We used the Composite International Diagnostic Interview (CIDI 2.1) to assess any mental disorder, any anxiety disorder, and any major depressive disorder (MDD). We measured OSS based on education, occupation, wealth, and a composite OSS index, while SSS was evaluated using the MacArthur scale. We investigated the indirect associations and stratified the analyses by gender.

Results: In this national sample, 4499 (57.0 %) were women, 4380 (55.5 %) were urban, and the mean (SE) age was 31.7 (0.2) years. SSS had a partial to full mediating effect. Specifically, there were significant indirect effects for the impact of wealth (mediation percentage: 78.9 %), education (73.3 %), OSS index (56.0 %), and occupation (33.3 %) on any mental disorder through SSS.

Limitations: The cross-sectional nature of the data presents constraints in establishing causal relationships.

Conclusions: Our findings highlight the role of SSS as the psychosocial mechanism linking OSS with mental disorders. A better understanding of the social factors that influence the association between OSS and SSS may enhance our insight into the mental health effects of socioeconomic status.

Background: Insomnia is a common symptom of major depressive disorder (MDD). Presence of insomnia symptoms in MDD (MDDIS) has been associated with worse depression severity and outcomes. This study assessed the economic and clinical burden of MDDIS in the United States.

Methods: Commercially and Medicaid-insured adults from Merative® MarketScan® Databases (01/2016-06/2021) with ≥1 MDD diagnosis (index date) were included in the MDDIS cohort if they had ≥1 insomnia diagnosis within 12 month afterwards or in the other MDD cohort if they had no insomnia diagnoses/treatments; patients without MDD diagnoses/treatments (random index date) were included in the non-MDD cohort. Cohorts were propensity score-matched. Healthcare resource utilization (HRU), costs, and treatment patterns 12 months post-index were compared between MDDIS and each control cohort using linear and Poisson regressions.

Results: In both commercially (N = 52,280; mean age: 44 years; 67 % female) and Medicaid-insured (N = 15,653; mean age: 41 years; 73 % female) populations, the MDDIS cohort had significantly higher HRU and cost than the other MDD and non-MDD cohorts. Mean total all-cause healthcare cost difference between the MDDIS and other MDD cohort was $5842 (commercial) and $5152 (Medicaid); between the MDDIS and non-MDD cohort, it was $14,266 (commercial) and $11,314 (Medicaid). MDDIS compared to other MDD was associated with higher use of antidepressants, particularly agents with sedative effect.

Limitations: Data were subject to incompleteness that might lead to measurement biases.

Conclusions: MDDIS compared to other MDD and non-MDD was associated with significantly higher economic and clinical burden, highlighting the need for effective treatments for this population.

Background: The PROACTIVE trial was a task-shared, stepped and collaborative care, psychosocial intervention based on psychoeducation and behavioural activation in 715 participants (60-94 years; mean (SD) 68·6 (6.9) years; 74·1 % female), that was highly effective at improving recovery from depression among older adults in Brazil. Here we investigate mediators of the intervention's effectiveness.

Methods: Causal mediation analysis using interventional indirect effects, simultaneously decomposed the total effect of PROACTIVE on recovery from depression (PHQ-9 < 10) into multiple indirect effects including: dose of intervention (numbers of sessions and activities completed); social support (Luben Social Network Scale); perceived loneliness (UCLA questionnaire); and additional sessions offered to participants who did not respond during the initial phase of the stepped care intervention.

Results: Of the intervention's total effect (difference in probability of recovery from depression between the intervention and control arms 0·216 [bias-corrected 95 % CI: 0·149, 0·291]): 13 % was mediated through reduced loneliness (0·028 [0·013, 0·046]); and 25 % through attending additional sessions for participants who did not initially respond to the intervention (0·055 [0·007, 0·102]).

Limitations: Due to limitations in our sample size our study may lack power to detect some nuances such as interactions between different mediators.

Conclusions: Our findings emphasise the importance of a home-based intervention to improve depression outcomes where participants are encouraged to self-select activities to mitigate against loneliness. Importantly, our findings suggest that the intervention's stepped-care component offering additional sessions to participants who did not experience an early response shows promise in ensuring a sustained recovery from depression.

This study examined moderators of the association between intimate relationship breakdown and suicidal ideation using data from a large representative cohort of Australian men. Across four waves (2013-2022), participants (n = 14,610) responded to measures of past 12-month relationship breakdown, past 2-week suicidal ideation, theorised but to-date untested moderators (age, social support, alcohol use, and masculine norms of self-reliance and emotional control), and demographic covariates. Binomial logistic regression models using generalised estimating equations modelled the association between relationship breakdown and suicidal ideation at both proximal (i.e., within-wave), and future (i.e., at the next wave) timepoints, with iterative adjustments for wave, demographics, other covariates, and prior-wave suicidal ideation. Interaction terms in sequential models examined moderation. In multi-wave cross-sectional analyses, after full adjustment, relationship breakdown was associated with 82 % greater odds of suicidal ideation (OR = 1.82, 95 % CI 1.56-2.12). Moderation analyses indicated that this association was specific to men without prior-wave suicidal ideation (OR = 2.18, 95 % CI 1.85-2.56), in comparison to men who had reported prior-wave suicidal ideation (OR = 1.19, 95 % CI 0.94-1.51). The association between relationship breakdown and proximal ideation did not differ by men's age, levels of social support, harmful alcohol use, or endorsement of self-reliance or emotional control. Finally, longitudinal models highlighted relationship breakdown was not associated with men's suicidal ideation at a subsequent wave, after adjustment for covariates and proximal suicidal ideation. Our findings suggest that suicidal ideation should be monitored in men known to have experienced relationship breakdown in the past year, especially those without a recent history of suicidal ideation.

Background: Psychological pain is a multidimensional structure that has long been recognized as an important risk factor for suicidal ideation and behavior. The roles of interactions among psychological pain subfactors at different stages of suicidality remain unclear.

Methods: A relatively large sample of outpatients with major depressive disorder (N = 501) was recruited to complete the Three-Dimensional Psychological Pain Scale (TDPPS). Exploratory graphical analysis (EGA) was conducted to explore the factor structure of TDPPS, thereby ensuring that the psychological pain subfactor was measured accurately. Network analysis included all TDPPS items, depression, passive suicidal ideation (PSI), active suicidal ideation (ASI), and history of suicidal action (SA) to identify key loops of suicidality.

Results: EGA disclosed a three-factor structure of TDPPS comprising cognitive, affective, and motivational factors. Network analysis revealed that items of motivational factors, but none of the items of cognitive and affective factors, were directly linked to PSI, ASI, and SA. Furthermore, three communities were identified by a "walktrap" algorithm. Depression and cognitive factor coalesced into a 'cognitive' community, affective factor constituted an 'affective' community, and motivational factor, PSI, ASI, and SA comprised a 'suicidal' community.

Limitations: This study used a cross-sectional design that cannot provide information on causal relationships among variables in the network.

Conclusions: Psychological pain avoidance may be a direct driver of suicidality, and therefore its assessment and intervention in clinical practice is necessary.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) and intermittent Theta Burst Stimulation (iTBS) are non-invasive treatments for major depressive disorder (MDD). While effective, variability in outcomes necessitates identifying predictors of therapeutic response. This study examined whether motor threshold (MT), percentage of motor threshold (%MT), and treatment intensity could predict clinical outcomes in MDD patients undergoing rTMS and iTBS.

Methods: Adult MDD patients treated with NeuroStar rTMS or iTBS at Mayo Clinic from February 2016 to April 2024 were included. MT, %MT, and treatment intensity were recorded. Clinical outcomes were assessed via Patient Health Questionnaire-9 (PHQ-9) score changes, response (PHQ-9 change ≥50 %), remission (PHQ-9 < 5), and a patient-reported outcome (PRO) on treatment helpfulness. Linear and logistic regression models were used to assess predictors of clinical outcomes.

Results: Among 149 patients analyzed (mean age 45.7, 67.8 % female), response rate was 43.0 % and remission rate was 16.8 %. MT and %MT did not significantly correlate with clinical outcomes. Treatment intensity and TMS type did not predict PHQ-9 score changes. Higher treatment intensity was associated with decreased odds of positive PRO responses. Linear regression showed that age and gender significantly predicted PHQ-9 score changes, with older patients and females showing greater improvement. MT was significantly lower in men and with iTBS compared to rTMS.

Conclusion: MT, %MT, and treatment intensity did not reliably predict outcomes. Higher intensity was linked to reduced patient-reported helpfulness, suggesting that patient comfort is crucial. iTBS's lower MT may benefit those needing less stimulation. Future research should identify better predictors to improve TMS outcomes.

Background: Comorbid depression and cardiometabolic diseases are prevalent and increase risk of mortality. However, trends in the prevalence and multimorbidity of cardiometabolic diseases in depression are unclear.

Methods: Data of adults aged ≥20 years with depression from the National Health and Nutrition Examination Survey 2005-2020 were analyzed. Joinpoint regression analysis was used to estimate trends in the prevalence of dyslipidemia, hypertension, diabetes, chronic kidney disease, non-alcoholic fatty liver disease, and cardiovascular disease as well as having ≥3 of these diseases. Differences in the prevalence of these diseases in depression vs no depression were assessed using Poisson regressions after applying propensity score weighting.

Results: A total of 3412 adults with depression were included. The prevalence of cardiometabolic diseases as well as having ≥3 diseases remained high and stable in the overall sample from 2005 to 2020 (P for trend >0.05). In 2017-2020, the prevalence ranged from 17.1 % (95 % CI, 12.7 %-21.5 %) for cardiovascular disease to 58.4 % (95 % CI, 50.4 %-66.3 %) for dyslipidemia; 40.7 % (95 % CI, 34.4 %-46.9 %) had ≥3 diseases. The prevalence of diabetes, cardiovascular disease, and having≥3 diseases was 23 %-85 % higher in adults with depression than those without.

Limitations: The utilization of self-reported data and/or one-time laboratory measurements may misclassify participants.

Conclusions: Prevalence of cardiometabolic diseases was high and multimorbidity was common in US adults with depression. Addressing the prevention, treatment, and management of cardiometabolic diseases in depression requires greater public health and clinical attention.

Background: Considerable research has mapped the human brain networks implicated in anxiety. Yet, less is known about the intrinsic features of the brain implicated in adolescent anxiety and their generalizability to affective and behavioral problems. To this end, we investigated the intrinsic functional connectomes associated with anxiety, their associations with behavioral phenotypes of clinical interest, and the cross-syndrome overlap between the anxiety network and other affective syndromes in an adolescent sample.

Methods: We used the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) dataset which comprises 203 clinical and healthy adolescents aged 14-17. Participants underwent a resting-state magnetic resonance imaging scan and completed the Child Behavior Checklist (CBCL) and Behavioral Inhibition/Activation System scale. Using network-based statistics, we identified functional networks associated with anxiety and other behavioral syndromes. The anxiety network strengths were then correlated with behavioral measures.

Results: A significant resting-state functional network associated with anxiety was identified, largely characterized by hyperconnectivity between the somatomotor and both the default mode network and subcortical regions. Network strengths derived from the anxiety network were significantly correlated to various behavioral syndromes, including internalizing and externalizing tendencies. Cross-syndrome overlapping edges were also observed in networks of internalizing disorders, more prominently post-traumatic stress syndromes.

Conclusions: Our results revealed the functional connectomes characteristic of anxiety in adolescents. This resting-state functional network was also predictive of and shared similar features with behavioral syndromes typically associated with anxiety-related disorders, providing evidence that the high comorbidity of anxiety with other clinical conditions may have a neurobiological basis.

Background: Lower functioning and higher symptom severity are observed when panic disorder (PD) co-occurs with generalized anxiety disorder (PD + GAD). No research on cortical gyrification patterns in the PD + GAD group has been conducted to date, which could show the alterations in brain connectivity in the extended fear network (EFN). This study aimed to investigate the characteristics of cortical gyrification in the PD + GAD group, compared to that in the PD without comorbid GAD (PD-GAD) group.

Methods: This study included 90 patients with PD, with propensity score matching between the PD + GAD (n = 30) and PD-GAD groups (n = 60), and 65 healthy controls (HC). For clinical evaluation, we assessed the anxiety symptomatology, suicidality, and harm avoidance. The local gyrification index (LGI) was obtained from T1-weighted brain MRI data using FreeSurfer.

Results: In the PD group compared to the HC, the hypergyrification involved the EFN. In the PD + GAD group compared to the PD-GAD group, hypergyrification was shown in the pathological worry-related brain regions. Within the PD + GAD group, significant positive correlations were observed between the superior frontal gyrus LGI values and suicidality scores, as well as between the superior parietal gyrus LGI values and harm avoidance levels.

Limitations: Given the variability in cortical gyrification patterns, longitudinal studies are needed to assess the occurrence of hypergyrification in specific brain regions.

Conclusions: This study is the first to demonstrate cortical gyrification patterns in the PD + GAD group compared to those in the PD-GAD group. Notably, the EFN and pathological worry-related brain regions have been implicated in the pathology of PD + GAD.

Background: Rumination is implicated in the onset and maintenance of major depressive disorder (MDD). Rumination-Focused Cognitive Behavioral Therapy (RF-CBT) effectively targets rumination and may change resting-state brain connectivity and change in activation during a rumination induction task (RIT) post-intervention predicts depressive symptoms two years later. We examined brain activation changes during an RIT in adolescents with remitted MDD following RF-CBT and evaluated RIT reliability (or stability) during treatment as usual (TAU).

Method: Fifty-five adolescents ages 14-17 completed an RIT at baseline, were randomized to 10-14 sessions of RF-CBT (n = 30) or treatment as usual (n = 25) and completed an RIT at post-treatment or equivalent time delay. The RIT includes recalling negative memories (Rumination Instruction), dwelling on their meaning/consequences (Rumination Prompt), and imagining unrelated scenes and objects (Distraction). We assessed activation change in the RF-CBT group using paired-samples t-tests. We assessed reliability (or stability) via intraclass correlation coefficients (ICCs) of five rumination-related ROIs for TAU and RF-CBT separately across task blocks.

Results: Following treatment, participants receiving RF-CBT demonstrated increased activation of left precuneus during Rumination Instruction and of left angular and superior temporal gyri during Rumination Prompt blocks (p < .01). From baseline to post-treatment, across most ROIs and task blocks, the RF-CBT group demonstrated poor stability (M = 0.21, range = -0.19-0.69), while the TAU group demonstrated fair-to-excellent stability (M = 0.52, range = 0.27-0.86).

Conclusion: RF-CBT changes activation of rumination-related circuitry during state-induced rumination, offering exciting avenues for future interventions. The RIT has fair-to-excellent stability among individuals not explicitly treated for rumination, and as expected, RIT stability is disrupted by RF-CBT.