Bipolar Diagnosis Research Articles

Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data.

Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.

Advancing clinical practice and discovery research through revised taxonomy: Case in point bipolar disorder diagnosis: Commentary on "The diagnosis of bipolar disorder in children and adolescents: Past, present and future".

Advancing clinical practice and discovery research through revised taxonomy: Case in point bipolar disorder diagnosis: Commentary on "The diagnosis of bipolar disorder in children and adolescents: Past, present and future".

Early exposure to cannabis and bipolar disorder incidence: Findings from a 22-year birth cohort study in Brazil.

Bipolar disorder is a chronic condition affecting millions of people worldwide. Currently, there is some evidence to suggest that cannabis use during adolescence may be an environmental risk factor for its onset, however inconsistencies have been observed across the literature. Considering this, we aimed to assess whether early lifetime cannabis is associated with subsequent bipolar disorder in young adults between 18 and 22 years of age. Using data from the 1993 Pelotas (Brazil) birth cohort (n = 5249), cannabis exposure was examined at age 18 by self-report, and bipolar disorder diagnosis was measured at age 22 using the Mini International Neuropsychiatric Interview (MINI). In order to control the analysis, we considered socioeconomic status index, sex, skin color, physical abuse by parents and lifetime cocaine use. A total of 3781 individuals were evaluated in 2015 aged 22 years, of whom 87 were diagnosed with the bipolar disorder onset after the age of 18. Lifetime cannabis use predicted bipolar disorder onset at 22 years old (OR 1.82, 95% CI [1.10, 2.93]), and the effect remained after adjusting for socioeconomic status, sex, skin color, and physical abuse by parents (OR 2.00, 95% CI [1.20, 3.25]). However, this association was attenuated to statistically non-significant after further adjustment for all available covariates, including lifetime cocaine use (OR 1.79, 95% CI [0.95, 3.19]). We also found similar results for early cocaine use, where the association with bipolar disorder onset did not maintain significance in the multivariate model (OR 1.35, 95% CI [0.62, 2.86]). Otherwise, when we considered cannabis or cocaine lifetime use as a unique feature, our findings showed that the adolescent exposure to cannabis or cocaine increased the odds by 1.95 times of developing bipolar disorder at 22 years age, even when controlling for all other study variables (OR 2.14, 95% CI [1.30, 3.47]). Finally, our models suggest that cocaine use may potentially exert a major influence on the effect of lifetime cannabis use on bipolar disorder onset, and that physical abuse by parents and sex may modify the effect of cannabis use for later bipolar disorder onset. Based on our findings, early cannabis exposure predicted bipolar disorder onset in young adults, but this association was confounded by cocaine use. Contrary to schizophrenia, cannabis as a sole exposure was not associated with bipolar disorder onset after adjusting for control variables.

Risk factors for oral infection and dry socket post-tooth extraction in medically complex patients in the absence of antibiotic prophylaxis: A case-control study.

Dry socket and infection are complications of tooth extractions. The objective was to determine risk factors for post-extraction complications in patients without antibiotic prophylaxis stratified by early- and late-complications and complication type (oral infection and dry socket). Retrospective, case (with complications)-control (without complications) study of patients (n=708) who had≥1 extraction performed at any Veterans Health Administration facility between 2015-2019 and were not prescribed an antibiotic 30 days pre-extraction. Early complication cases (n=109) were more likely to be female [odds ratio (OR)=2.06; 95% confidence interval (CI):1.05-4.01], younger (OR=0.29; 95% CI:0.09-0.94 patients ≥ 80 years old, reference:18-44 years), Native American/Alaska Native (OR=21.11; 95% CI:2.33-191.41) and have fewer teeth extracted (OR=0.53 3+ teeth extracted; 95% CI:0.31-0.88, reference:1 tooth extracted). Late complication cases (n=67) were more likely to have a bipolar diagnosis (OR=2.98; 95% CI:1.04-8.57), history of implant placement (OR=8.27; 95% CI:1.63-41.82), and history of past smoking (OR=2.23; 95% CI:1.28-3.88). Predictors for post-extraction complications among patients who did not receive antibiotic prophylaxis were similar to prior work in cohorts who received prophylaxis. Unique factors identified in a medically complex population included being younger, Native American/Alaska Native, having mental health conditions, history of a dental implant, and fewer teeth extracted.

Development and multi-site external validation of a generalizable risk prediction model for bipolar disorder

Bipolar disorder is a leading contributor to disability, premature mortality, and suicide. Early identification of risk for bipolar disorder using generalizable predictive models trained on diverse cohorts around the United States could improve targeted assessment of high risk individuals, reduce misdiagnosis, and improve the allocation of limited mental health resources. This observational case-control study intended to develop and validate generalizable predictive models of bipolar disorder as part of the multisite, multinational PsycheMERGE Network across diverse and large biobanks with linked electronic health records (EHRs) from three academic medical centers: in the Northeast (Massachusetts General Brigham), the Mid-Atlantic (Geisinger) and the Mid-South (Vanderbilt University Medical Center). Predictive models were developed and valid with multiple algorithms at each study site: random forests, gradient boosting machines, penalized regression, including stacked ensemble learning algorithms combining them. Predictors were limited to widely available EHR-based features agnostic to a common data model including demographics, diagnostic codes, and medications. The main study outcome was bipolar disorder diagnosis as defined by the International Cohort Collection for Bipolar Disorder, 2015. In total, the study included records for 3,529,569 patients including 12,533 cases (0.3%) of bipolar disorder. After internal and external validation, algorithms demonstrated optimal performance in their respective development sites. The stacked ensemble achieved the best combination of overall discrimination (AUC = 0.82–0.87) and calibration performance with positive predictive values above 5% in the highest risk quantiles at all three study sites. In conclusion, generalizable predictive models of risk for bipolar disorder can be feasibly developed across diverse sites to enable precision medicine. Comparison of a range of machine learning methods indicated that an ensemble approach provides the best performance overall but required local retraining. These models will be disseminated via the PsycheMERGE Network website.

The prevalence and associated characteristics of Bipolar Disorder diagnosis among admitted patients at three tertiary psychiatric hospitals in Zimbabwe: A cross sectional study.

Bipolar Affective Disorder (BD) is a serious condition that affects more than 1% of the world's population. If not treated can cause disability, yet its prevalence in Zimbabwe is not known. This study explores the burden of Bipolar Disorder and its associated factors in Zimbabwe. A cross sectional study with a sample of 272 participants was carried out at three tertiary hospitals in Zimbabwe. Data was collected using an interviewer administered questionnaire and the Mini International Neuropsychiatric Interview (M.I.N.I). The study shows the prevalence and factors associated with Bipolar Disorder at tertiary psychiatric hospitals. Data analysis was done using STATA S/E 13.0 for data management. The prevalence of BD in the sample was 39.3%. Factors associated with BD were, being formally employed (AOR = 3.69, 95%CI: 1.55-8.79), a history of defaulting medications (AOR = 1.90, 95%CI: 1.02-3.57) and a reported previous diagnosis of BD (AOR = 5.66, 95%CI: 2.72-11.8). The prevalence of BD among admitted participants in tertiary psychiatric hospitals in Zimbabwe is high. It is comparable to that from African studies done in clinical settings. There is need for in-service training for clinicians to be more vigilant in diagnosing BD.

Just Not Enough: Utilization of Outpatient Psychotherapy Provided by Clinical Psychologists for Patients With Psychosis and Bipolar Disorder in Switzerland.

Treatment guidelines state that evidence-based psychotherapy is effective for people with psychosis and bipolar disorder and should be offered during every phase of the treatment process. However, research has indicated a lack of outpatient psychotherapeutic services for this patient group, for example, in the United States or Germany. We extend this finding by presenting survey data from Switzerland. We surveyed 112 inpatients with a diagnosis of a schizophrenia spectrum disorder or bipolar disorder and assessed outpatient treatment over the 5 years prior to their index hospitalization by using retrospective self-reports. The survey focused on psychotherapy provided by clinical psychologists. Results indicate that only 23.2% of participants retrospectively reported having utilized any outpatient psychotherapy within the reporting period and only 8% of participants reported having received a number of outpatient sessions that reaches recommended levels of psychotherapy. Exploratory analyses did not detect a significant association between self-reported utilization of outpatient psychotherapy sessions and most demographic, psychiatric, and psychological attributes, but patients with a bipolar disorder diagnosis (vs schizophrenia spectrum diagnosis) reported having utilized outpatient treatment more often. These findings are preliminary. When replicated they highlight the need for increased access to outpatient psychotherapy and better alignment between guideline recommendations and outpatient supply.

Elevated Brain-Derived Neurotrophic Factor Levels During Depressive Mixed States.

Neurotrophin-like brain-derived neurotrophic factor (BDNF) and pro-inflammatory cytokines may modulate the pathophysiology of mood disorders. Although several studies show alterations in these biomarkers during the depressive, manic, and euthymic states of mood disorders, evidence is lacking for those in a mixed state. Therefore, this study aimed to investigate the relationship between the depressive mixed state (DMX) and peripheral neurobiological factors. We enrolled 136 patients with major depressive episodes. Depressive symptoms were assessed using the Quick Inventory of Depressive Symptomatology Self-Report Japanese version (QIDS-SR-J). The severity of DMX was assessed using the self-administered 12-item questionnaire (DMX-12). Categorical screening as DMX-positive (n=54) was determined by a cutoff score of 13 or more in the specific eight symptoms from the DMX-12; the remaining were DMX-negative (n=82). Serum BDNF, tumor necrosis factor-α, highsensitivity C-reactive protein, and interleukin-6 levels were measured. When comparing biomarkers between the DMX-positive and DMX-negative groups, higher serum BDNF concentration in the DMX-positive group than in the DMX-negative group was the only significant finding (p=0.009). A positive correlation existed between the total score of the eight specific symptoms of DMX-12 and the BDNF concentration (r=0.190, p=0.027). After adjustment for confounders, logistic regression analysis revealed that BDNF (odds ratio [OR]=1.07, 95% confidence interval [CI]=1.00-1.14, p=0.045), bipolar diagnosis (OR=3.43, 95% CI=1.36-8.66, p=0.009), and total QIDS-SR-J score (OR=1.29, 95% CI=1.15-1.43, p<0.001) were significantly associated with DMX positivity. BDNF was positively associated with DMX severity, suggesting that higher BDNF concentrations may be involved in the pathophysiology of DMX.

How People With a Bipolar Disorder Diagnosis Talk About Personal Recovery in Peer Online Support Forums: Corpus Framework Analysis Using the POETIC Framework.

Personal recovery is of particular value in bipolar disorder, where symptoms often persist despite treatment. We previously defined the POETIC (Purpose and Meaning, Optimism and Hope, Empowerment, Tensions, Identity, Connectedness) framework for personal recovery in bipolar disorder. So far, personal recovery has only been studied in researcher-constructed environments (eg, interviews and focus groups). Support forum posts can serve as a complementary naturalistic data resource to understand the lived experience of personal recovery. This study aimed to answer the question "What can online support forum posts reveal about the experience of personal recovery in bipolar disorder in relation to the POETIC framework?" By integrating natural language processing, corpus linguistics, and health research methods, this study analyzed public, bipolar disorder support forum posts relevant to the lived experience of personal recovery. By comparing 4462 personal recovery-relevant posts by 1982 users to 25,197 posts not relevant to personal recovery, we identified 130 significantly overused key lemmas. Key lemmas were coded according to the POETIC framework. Personal recovery-related discussions primarily focused on 3 domains: "Purpose and meaning" (particularly reproductive decisions and work), "Connectedness" (romantic relationships and social support), and "Empowerment" (self-management and personal responsibility). This study confirmed the validity of the POETIC framework to capture personal recovery experiences shared on the web and highlighted new aspects beyond previous studies using interviews and focus groups. This study is the first to analyze naturalistic data on personal recovery in bipolar disorder. By indicating the key areas that people focus on in personal recovery when posting freely and the language they use, this study provides helpful starting points for formal and informal carers to understand the concerns of people diagnosed with a bipolar disorder and to consider how to best offer support.

Cognitive Disengagement Syndrome Symptoms from Early Childhood to Adolescence in a Nationally Representative Spanish Sample

ABSTRACT Objective The identification of a common set of symptoms for assessing cognitive disengagement syndrome (CDS, formerly sluggish cognitive tempo) for early childhood (ages 5–8), middle childhood (ages 9–12), and adolescence (ages 13–16) is needed to advance research on the developmental psychopathology of CDS (i.e. a common symptom set with comparable internal and external validity for each age group). Method Parents of a nationally representative sample of 5,525 Spanish children and adolescents (ages 5 to 16, 56.1% boys) completed measures of CDS, attention-deficit/hyperactivity disorder-inattention (ADHD-IN), and other measures. Results First, the 15 CDS symptoms showed convergent and discriminant validity relative to the ADHD-IN symptoms within each age group. Second, CDS showed stronger first-order and unique associations than ADHD-IN with anxiety, depression, somatization, daytime sleep-related impairment, and nighttime sleep disturbance, whereas ADHD-IN showed stronger first-order and unique associations than CDS with ADHD-hyperactivity/impulsivity, oppositional defiant disorder, and academic impairment. Third, CDS showed stronger first-order and unique associations than ADHD-IN with a history of having an anxiety, depression, or bipolar disorder diagnosis, whereas ADHD-IN showed stronger first-order and unique associations with having an ADHD diagnosis. Conclusions The identification of a common set of CDS symptoms spanning early childhood to adolescence allows for the advancement of research on CDS, with a particular need now for longitudinal studies and examination of CDS with other functional outcomes and across other cultural contexts.

Bipolar Disorder and Antidepressant Associated Hypomania

The impact of antidepressant associated hypomania on monomanic depression and its relationship to bipolar disorder. This review attempts to investigate and review current research on bipolar disorder diagnosis, the neurobiological mechanisms of antidepressant-associated hypomania, risk factors, and how to manage the occurrence of this condition. Bipolar disorder is a widespread, debilitating, recurrent, variable-severity mental health condition in which the patient exhibits two different states and unpredictable mood switching. Mania, hypomania, mixed states, depression, and depression interspersed with moments of relative health are the stages of the disorder. Early identification of bipolar disorder can improve prognosis. Patients with monophasic episodes are uncommon, as the clinical manifestation of bipolar illness is unpredictable. Throughout their lives, individuals with bipolar disorder alternate between episodes of mania or hypomania and depression. Depressive episodes in bipolar disorder are referred to as bipolar depression, and the underlying core symptom is depressed mood, which are essentially identical to the diagnostic criteria and clinical symptoms of uniphasic depression, so there is a high risk of misdiagnosis during the initial visit. Patients often choose to seek specialist help during depressive episodes, and this can lead to a tendency to overlook whether a patient has bipolar disorder. Antidepressant monotherapy is contraindicated for hypomanic episodes. Antidepressants tend to induce hypomanic and manic episodes, a phenomenon known as antidepressant-associated hypomania (AAH). All antidepressant drugs may cause mania. One is drug induced mania; The other is considered a potential bipolar disorder. There is a high co-occurrence of psychiatric disorders, but only bipolar disorder, monophasic depression, and antidepressant-induced hypomanic episodes are discussed here.

Pilot effectiveness trial of Mood Lifters for individuals who self-report bipolar disorder

PurposeBipolar disorder is associated with poor mental and physical health outcomes, and therefore, it is crucial to research and develop effective interventions for this population (Grande et al., 2016). Unfortunately, research on the efficacy of current interventions shows only small improvements in symptoms and quality of life (Oud et al., 2016). Additionally, individuals with bipolar disorder face barriers to accessing care like social stigma, isolation and financial constraints (Blixen et al., 2016). This paper aims to introduce and examine the effectiveness of an accessible, peer-led group program, Mood Lifters (Votta and Deldin, 2022), in those who completed the program and also self-reported a diagnosis of bipolar disorder.Design/methodology/approachMood Lifters is a 15-week, peer-led group program that approaches mental wellness from a biopsychosocial framework using strategies from a variety of evidence-based treatment methods (e.g. cognitive-behavioral therapy, dialectical behavior therapy, interpersonal psychotherapy, etc.). Participants meet once a week for 1 hour to review various mental health topics, including behavioral changes and insight into mood patterns. Individuals who participated in nonacademic groups in a company setting and self-reported a bipolar diagnosis were surveyed at the beginning and end of their program to measure various aspects of psychological functioning.FindingsResults suggest that these individuals experienced significant improvements in depression, anxiety, social functioning and perceived stress, along with flourishing and positive and negative affect.Originality/valueThese findings are promising, given that bipolar disorder is historically difficult to treat (Grande et al., 2016). Based on this preliminary evidence, the authors have developed a Mood Lifters program specifically for individuals with bipolar disorder and are launching a randomized control clinical trial.

Characteristics of persistent depression in the long-term: Randomized controlled trial and two-year observational study

Major depressive disorder is a chronic condition that can recur and relapse. It would be clinically useful to know the patient background to predict the chronicity of depressive symptoms, and the change in diagnosis of bipolar disorder. This study included 197 patients enrolled in a six-week randomized controlled trial with a two-year follow-up. We conducted multiple logistic regression analyses to identify the clinical and sociodemographic characteristics associated with persistent depressive disorder (PDD), relapse, and changes in bipolar disorder diagnosis. The significantly correlated factors were residual symptoms, including insight, work and activity, and general somatic symptoms at week six. We could not identify any factors that contributed to relapse or change in the diagnosis of bipolar disorder. We found that the specific residual symptoms of acute treatment affected long-term treatment outcomes for depression. Attention should be paid to the residual symptoms of depression in the early stages of treatment, and measures should be considered to improve them. There are several limitations to this study, including the fact that PDD may exist among patients who discontinued treatment, treatment was not standardized during the study period, and adherence was confirmed verbally.

Preliminary results from the Australian Genetics of Bipolar Disorder Study: A nation-wide cohort.

The Australian Genetics of Bipolar Disorder Study is a nation-wide cohort of adults living with bipolar disorder. The study aims to detect the relationships between genetic risk, symptom severity, and the lifetime prevalence of bipolar disorder, treatment response and medication side effects, and patterns and costs of health care usage. A total of 6682 participants (68.3% female; aged 44.8 ± 13.6 years [range = 18-90]) were recruited in three waves: a nation-wide media campaign, a mail-out based on prescriptions for lithium carbonate and through the Australian Genetics of Depression Study. Participants completed a self-report questionnaire. A total of 4706 (70%) participants provided a saliva sample and were genotyped and 5506 (82%) consented to record linkage of their Pharmaceutical and Medicare Benefits Schedule data. Most participants were living with bipolar I disorder (n = 4068) while 1622 participants were living with bipolar II disorder and 992 with sub-threshold bipolar disorder. The mean age of bipolar disorder diagnosis was 32.7 ± 11.6 years but was younger in bipolar I (p = 2.0E-26) and females (p = 5.7E-23). Excluding depression with onset prior to bipolar disorder diagnosis, 64.5% of participants reported one or more co-occurring psychiatric disorders: most commonly generalised anxiety disorder (43.5%) and posttraumatic stress disorder (20.7%). Adverse drug reactions were common and resulted in discontinuation rates ranging from 33.4% for lithium to 63.0% for carbamazepine. Our findings highlight the high rate of comorbidities and adverse drug reactions among adults living with bipolar disorder in the general Australian population. Future genomic analyses focus on identifying genetic variants influencing pharmacotherapy treatment response and side effects.

Abstract P425: Peripartum Cardiomyopathy And Other Cardiac Events In Pregnant And Postpartum Patients With Mood Disorders

Background: Evidence suggests a link between depression and adverse cardiac events. We sought to understand whether mood disorders are associated with peripartum cardiomyopathy (PPCM) and other cardiac events in pregnancy and postpartum. Methods: Retrospective cohort study utilizing the National Inpatient Sample (HCUP) of pregnant and postpartum patients from 2017-2019. Subjects were separated into two groups based on ICD10 coding for presence or absence of mood disorder (depression, bipolar, anxiety, or other mood diagnosis). The primary outcome was diagnosis of PPCM. Secondary outcomes included a composite of acute cardiac events and maternal death. Groups were compared via t-tests, chi-squared analysis, and logistic regression that included all variables that differed between groups with p&lt;0.05. Results: Over 2.2 million subjects were analyzed and approximately 168,000 (7.4%) had an ICD10 diagnosis of mood disorder. Those with mood disorders were more likely to be non-Hispanic white, obese, tobacco user, publicly insured, have comorbidities, and deliver at a large, private, non-profit hospital (all p&lt;0.05). They delivered earlier in pregnancy and were also more likely to undergo cesarean (37.0±4.6 vs 37.8±3.7 weeks and 35.8% vs 31.8%, respectively, p&lt;0.001). The primary outcome of PPCM was more than twice as common in those with mood disorder (0.12% vs 0.05%, p&lt;0.001) as were other cardiac events, include the composite of adverse cardiac events (0.36% vs 0.14%, p&lt;0.001). Maternal death was the same in both groups (p=0.253). After controlling for confounders, PPCM remained independently associated with diagnosis of mood disorders (aOR 1.36, 95%CI 1.03-1.80) as did the composite of adverse cardiac events (aOR 1.57, 95%CI 1.37-1.81). Conclusion: Mood disorders in pregnancy and postpartum are associated with increased rates of PPCM and other cardiac events.

Graph Self-Supervised Learning With Application to Brain Networks Analysis.

The less training data and insufficient supervision limit the performance of the deep supervised models for brain disease diagnosis. It is significant to construct a learning framework that can capture more information in limited data and insufficient supervision. To address these issues, we focus on self-supervised learning and aim to generalize the self-supervised learning to the brain networks, which are non-Euclidean graph data. More specifically, we propose an ensemble masked graph self-supervised framework named BrainGSLs, which incorporates 1) a local topological-aware encoder that takes the partially visible nodes as input and learns these latent representations, 2) a node-edge bi-decoder that reconstructs the masked edges by the representations of both the masked and visible nodes, 3) a signal representation learning module for capturing temporal representations from BOLD signals and 4) a classifier used for the classification. We evaluate our model on three real medical clinical applications: diagnosis of Autism Spectrum Disorder (ASD), diagnosis of Bipolar Disorder (BD) and diagnosis of Major Depressive Disorder (MDD). The results suggest that the proposed self-supervised training has led to remarkable improvement and outperforms state-of-the-art methods. Moreover, our method is able to identify the biomarkers associated with the diseases, which is consistent with the previous studies. We also explore the correlation of these three diseases and find the strong association between ASD and BD. To the best of our knowledge, our work is the first attempt of applying the idea of self-supervised learning with masked autoencoder on the brain network analysis.

Identifying Cigarette Smoking Trajectories from Homelessness to Housing

AbstractThis study examines cigarette smoking trajectories from homelessness to housing and assesses demographic and clinical characteristics associated with multiple longitudinal smoking behavior patterns. Data were drawn from a longitudinal prospective cohort study of 421 adults experiencing homelessness who entered permanent supportive housing (PSH). Four quantitative surveys (baseline [while homeless], 3-, 6-, and 12 months post-housing) gathered participants’ smoking frequency used for Repeated Measure Latent Class Analysis (RMLCA), which identified subgroups that share longitudinal smoking behavior patterns. Baseline and time-varying demographic, mental health (e.g., schizophrenia), and substance use (e.g., cannabis use) measures were examined as correlates of class membership. RMLCA estimates supported a three-class model: (1) mixed-frequency decreasers (n = 71): who smoked at differing frequencies while demonstrating a significant decrease over time; (2) high-frequency maintainers (n = 194): participants who smoked daily/almost-daily and maintained this smoking rate across waves; and (3) low-frequency increasers (n = 56): participants who generally were non-smokers at baseline and significantly increased to monthly or weekly consumption longitudinally. Compared to Black and African American participants, Hispanic and Latino participants had greater odds of low-frequency increaser and mixed-frequency decreaser membership. Schizophrenia and bipolar disorder diagnoses increased odds of high-frequency maintainer membership compared to the two less-frequent-using subgroups. Cannabis use increased longitudinally and was associated with greater odds of high-frequency maintainer membership. This is the first study to find smoking changes from homelessness to housing. While encouraging that some residents reduce their smoking post-housing, many maintained high smoking rates. Cessation services that address mental health and co-occurring substance use within PSH are warranted.

Association of sociocultural stressors with bipolar disorder onset in Puerto Rican youth growing up as members of a minoritized ethnic group: results from the Boricua Youth Longitudinal Study

The development of bipolar disorder is currently explained by a complex interaction of genetic and environmental factors. Less is known regarding the influence of sociocultural factors. This study aims to evaluate the incidence and impact of sociocultural factors on bipolar disorder onset in two comparable samples of youth growing up in different social settings. We leveraged data from two urban population-based cohorts representative of Puerto Rican children growing up in either San Juan (Puerto Rico) or the South Bronx (NYC) and followed up for 17 years. Bipolar disorder diagnoses were based on retrospective self-reports on the World Health Organization Composite International Diagnostic Interview. We used a causal inference approach to estimate associations of sociocultural factors with bipolar disorder onset after adjusting for potential confounders. We found that South Bronx children, who grew up as a minoritized group, had twice the risk of bipolar disorder onset as young adults, with an incidence rate of 2.22 new cases per 1000 person-years compared to 1.08 new cases in San Juan (incidence rate difference, 1.13; 95% CI, 0.09-1.20). After adjusting for potential confounders, South Bronx children had the same lifetime hazard of bipolar disorder onset compared to San Juan children. However, our analysis demonstrated that caregivers' exposure to societal cultural stress partially explained the increased risk of bipolar disorder onset in the South Bronx, in addition to the potential contribution of genetics. Our results provide evidence that societal cultural stress can increase the risk of lifetime bipolar disorder onset in youth growing up as a minoritized group. Addressing stress in minoritized groups might reduce the risk of bipolar disorder onset. The Boricua Youth Study has been supported by the National Institutes of HealthMH56401, MH098374, DA033172, and AA020191. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article.

Bipolar disorder longitudinal study in Nigeria – Preliminary data on demographic and clinical findings of the study cohort

BackgroundBipolar disorder, severe mood disorder characterised by its ability to swing between two contrasting poles of low and elated mood with a return to relatively normal level of functioning, has a lifetime prevalence of up to 2.4%, a heterogenous clinical picture, significant burden of disease, and a high co-morbidity rate. With significant lack of data from the African continent on bipolar disorder, this study was started with an aim to provide insight into the sociodemographic, biological, clinical, and cultural picture of bipolar disorder in Nigeria. MethodsPhase I of the study required the development of a bipolar registry and collection of data in a retrospective manner from patient clinically diagnosed with bipolar disorder at the department of neuropsychiatry, University of Port Harcourt Teaching Hospital in Nigeria. Data collection on demography, illness onset, duration to bipolar diagnosis, mood polarity etc., were extracted manually from patient case files using a data form developed by the research team. ResultBipolar disorder has a mean age at onset of 27.43±10.56 years, with younger age at onset in males. There is a relatively high misdiagnosis rate of bipolar disorder with delay in making a bipolar diagnosis of 19.39 months. The data also show the presence of singular mood polarity in bipolar disorder. ConclusionPreliminary findings from the bipolar disorder longitudinal study in Nigeria has provided much needed data for bipolar disorder in Nigeria. It also makes evident the need for a prospective, multicentre study of the life course of bipolar disorder as intended in the second phase of the study.

Effects of the COVID-19 Pandemic on Anxiety Symptoms in Long-Term Care Residents: A Multilevel Growth Curve Analysis.

The coronavirus disease 2019 (COVID-19) pandemic has negatively impacted the mental health functioning of older adults residing in long-term care (LTC) settings. This study examines the impact of the lockdown on anxiety symptoms over time in LTC residents. Secondary data analysis was conducted on clinical data obtained with permission from a large behavioral health company that provides behavioral health services in long-term care (LTC) and assisted living (AL) facilities. Data were obtained from 1149 adults (mean age 72.37, 70% female) in LTC and AL facilities across the United States who were receiving psychological services 1 year prior, and 1 year after, the COVID-19 pandemic lockdown. Changes in anxiety (measured using a clinician rating scale) over time before and after the pandemic were assessed using latent growth curve modeling with psychiatric diagnosis, psychiatric medication, and demographic factors included as covariates. Anxiety severity decreased over time before and after the onset of the COVID-19 pandemic. Although pandemic-level factors such as facility closure and telehealth availability did not affect anxiety over time, individual treatment factors such as obsessive compulsive disorder diagnosis, initial anxiety severity, bipolar disorder diagnosis, and prescriptions for anxiolytic and antipsychotic medications affected the trajectory of anxiety during the pandemic. These results demonstrate that individual covariates such as diagnosis, symptom severity, and medication use impacted the trajectory of anxiety symptoms before and during the COVID-19 pandemic more strongly than pandemic-related circumstances (facility closure, telehealth availability). The impact of the COVID-19 pandemic may be better observed through treatment-relevant variables, rather than pure symptom severity. In preparation for future pandemics or other large-scale disasters potentially impacting service delivery, facilities should continue to prioritize continuity of care or a timely resumption of services attending to individual treatment factors.