Background

Recent evidence suggests increased risk for mortality in bulimia nervosa (BN). However, little is yet known about suicidal behavior in BN.

Aims

To examine frequency and correlates of suicidal ideation and attempts in adolescents and adults with BN in two population-based samples.

Method

A total of 10,123 adolescents and 2980 adults in two nationally representative surveys of mental disorder were queried regarding eating disorder symptoms and suicidal ideation and attempts.

Results

Less than 1 percent (0.9%) of adolescents and 1.0% of adults met the criteria for BN. Suicidal ideation was more common among adolescents with BN (53.0%) compared with those with binge eating disorder (BED) (34.4%), other psychopathology (21.3%) or no psychopathology (3.8%). Similar trends emerged for the association between BN and self-reported suicidal plans or attempts. Among adults, suicidality was more common in BN than in the no psychopathology group, but not significantly different from the anorexia nervosa (AN), BED, or other psychopathology subgroups.

Conclusion

There is a high risk of suicidal ideation and behavior among those with BN. These results underscore the importance of addressing suicide risk in adolescents and adults with eating disorder symptoms.

BACKGROUND: Environmental noise has been linked to negative health outcomes, like poor sleep, poor mental health, and cardiovascular disease, and likely accounts for more than 1 million disability-adjusted life years annually in Western Europe. Adolescence may be a particularly sensitive period for noise exposure due to an increased need for sleep, failure to meet sleep guidelines, and increased risk for first onset of some mental health disorders. However, the potential health effects of living in high-noise environments have not been studied in US adolescents, rarely in European adolescents, and mental health outcomes studied have not corresponded to diagnoses from the Diagnostic and Statistical Manual of Mental Disorders (DSM). METHODS: Using a US-based nationally representative survey of urban adolescents (N = 4,508), we estimated associations of day-night average sound levels exceeding the US Environmental Protection Agencys 55 decibel limit with sleep outcomes and lifetime mental health DSM diagnoses. We implemented doubly robust targeted minimum loss-based estimation coupled with propensity score matching to account for numerous potential adolescent, household, and environmental confounders. RESULTS: Living in a high- versus low-noise Census block group was associated with later bedtimes on weeknights (0.48 hours, 95% confidence interval [CI] = -0.15, 1.12) and weekend nights (0.65 hours, 95% CI = 0.37, 0.93), but not with total hours slept. Associations between living in a high- versus low-noise Census block group and mental disorders were mixed, with wide CIs, and not robust to sensitivity analyses. CONCLUSIONS: We find evidence for an association between residence in a high-noise area and later bedtimes among urban adolescents but no consistent evidence of such an association with mental health disorders.

Sleep and circadian rhythms disturbances (SCRD) in young people at high risk or with early onset of bipolar disorders (BD) are poorly understood. We systematically searched for studies of self, observer or objective estimates of SCRD in asymptomatic or symptomatic offspring of parents with BD (OSBD), individuals with presentations meeting recognised BD-at-risk criteria (BAR) and youth with recent onset of full-threshold BD (FT-BD). Of 76 studies eligible for systematic review, 35 (46%) were included in random effects meta-analyses. Pooled analyses of self-ratings related to circadian rhythms demonstrated greater preference for eveningness and more dysregulation of social rhythms in BAR and FT-BD groups; analyses of actigraphy provided some support for these findings. Meta-analysis of prospective studies showed that pre-existing SCRD were associated with a 40% increased risk of onset of BD, but heterogeneity in assessments was a significant concern. Overall, we identified longer total sleep time (Hedges g: 0.34; 95% confidence intervals:.1, .57), especially in OSBD and FT-BD and meta-regression analysis indicated the effect sizes was moderated by the proportion of any sample manifesting psychopathology or receiving psychotropic medications. This evolving field of research would benefit from greater attention to circadian rhythm as well as sleep quality measures.

Background

Heterogeneous mental health outcomes during the COVID-19 pandemic are documented in the general population. Such heterogeneity has not been systematically assessed in youth with autism spectrum disorder (ASD) and related neurodevelopmental disorders (NDD). To identify distinct patterns of the pandemic impact and their predictors in ASD/NDD youth, we focused on pandemic-related changes in symptoms and access to services.

Methods

Using a naturalistic observational design, we assessed parent responses on the Coronavirus Health and Impact Survey Initiative (CRISIS) Adapted For Autism and Related neurodevelopmental conditions (AFAR). Cross-sectional AFAR data were aggregated across 14 European and North American sites yielding a clinically well-characterized sample of N = 1275 individuals with ASD/NDD (age = 11.0 ± 3.6 years; n females = 277). To identify subgroups with differential outcomes, we applied hierarchical clustering across eleven variables measuring changes in symptoms and access to services. Then, random forest classification assessed the importance of socio-demographics, pre-pandemic service rates, clinical severity of ASD-associated symptoms, and COVID-19 pandemic experiences/environments in predicting the outcome subgroups.

Results

Clustering revealed four subgroups. One subgroup-broad symptom worsening only (20%)-included youth with worsening across a range of symptoms but with service disruptions similar to the average of the aggregate sample. The other three subgroups were, relatively, clinically stable but differed in service access: primarily modified services (23%), primarily lost services (6%), and average services/symptom changes (53%). Distinct combinations of a set of pre-pandemic services, pandemic environment (e.g., COVID-19 new cases, restrictions), experiences (e.g., COVID-19 Worries), and age predicted each outcome subgroup.

Limitations

Notable limitations of the study are its cross-sectional nature and focus on the first six months of the pandemic.

Conclusions

Concomitantly assessing variation in changes of symptoms and service access during the first phase of the pandemic revealed differential outcome profiles in ASD/NDD youth. Subgroups were characterized by distinct prediction patterns across a set of pre- and pandemic-related experiences/contexts. Results may inform recovery efforts and preparedness in future crises; they also underscore the critical value of international data-sharing and collaborations to address the needs of those most vulnerable in times of crisis.

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n=664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).