Capturing the clinical complexity in young people presenting to primary mental health services: a data-driven approach.

AIMS: The specific and multifaceted service needs of young people have driven the development of youth-specific integrated primary mental healthcare models, such as the internationally pioneering headspace services in Australia. Although these services were designed for early intervention, they often need to cater for young people with severe conditions and complex needs, creating challenges in service planning and resource allocation. There is, however, a lack of understanding and consensus on the definition of complexity in such clinical settings. METHODS: This retrospective study involved analysis of headspace's clinical minimum data set from young people accessing services in Australia between 1 July 2018 and 30 June 2019. Based on consultations with experts, complexity factors were mapped from a range of demographic information, symptom severity, diagnoses, illness stage, primary presenting issues and service engagement patterns. Consensus clustering was used to identify complexity subgroups based on identified factors. Multinomial logistic regression was then used to evaluate whether these complexity subgroups were associated with other risk factors. RESULTS: A total of 81,622 episodes of care from 76,021 young people across 113 services were analysed. Around 20% of young people clustered into a 'high complexity' group, presenting with a variety of complexity factors, including severe disorders, a trauma history and psychosocial impairments. Two moderate complexity groups were identified representing 'distress complexity' and 'psychosocial complexity' (about 20% each). Compared with the 'distress complexity' group, young people in the 'psychosocial complexity' group presented with a higher proportion of education, employment and housing issues in addition to psychological distress, and had lower levels of service engagement. The distribution of complexity profiles also varied across different headspace services. CONCLUSIONS: The proposed data-driven complexity model offers valuable insights for clinical planning and resource allocation. The identified groups highlight the importance of adopting a holistic and multidisciplinary approach to address the diverse factors contributing to clinical complexity. The large number of young people presenting with moderate-to-high complexity to headspace early intervention services emphasises the need for systemic change in youth mental healthcare to ensure the availability of appropriate and timely support for all young people.

Development and temporal validation of a clinical prediction model of transition to psychosis in individuals at ultra-high risk in the UHR 1000+ cohort.

The concept of ultra-high risk for psychosis (UHR) has been at the forefront of psychiatric research for several decades, with the ultimate goal of preventing the onset of psychotic disorder in high-risk individuals. Orygen (Melbourne, Australia) has led a range of observational and intervention studies in this clinical population. These datasets have now been integrated into the UHR 1000+ cohort, consisting of a sample of 1,245 UHR individuals with a follow-up period ranging from 1 to 16.7 years. This paper describes the cohort, presents a clinical prediction model of transition to psychosis in this cohort, and examines how predictive performance is affected by changes in UHR samples over time. We analyzed transition to psychosis using a Cox proportional hazards model. Clinical predictors for transition to psychosis were investigated in the entire cohort using multiple imputation and Rubin's rule. To assess performance drift over time, data from 1995-2016 were used for initial model fitting, and models were subsequently validated on data from 2017-2020. Over the follow-up period, 220 cases (17.7%) developed a psychotic disorder. Pooled hazard ratio (HR) estimates showed that the Comprehensive Assessment of At-Risk Mental States (CAARMS) Disorganized Speech subscale severity score (HR=1.12, 95% CI: 1.02-1.24, p=0.024), the CAARMS Unusual Thought Content subscale severity score (HR=1.13, 95% CI: 1.03-1.24, p=0.009), the Scale for the Assessment of Negative Symptoms (SANS) total score (HR=1.02, 95% CI: 1.00-1.03, p=0.022), the Social and Occupational Functioning Assessment Scale (SOFAS) score (HR=0.98, 95% CI: 0.97-1.00, p=0.036), and time between onset of symptoms and entry to UHR service (log transformed) (HR=1.10, 95% CI: 1.02-1.19, p=0.013) were predictive of transition to psychosis. UHR individuals who met the brief limited intermittent psychotic symptoms (BLIPS) criteria had a higher probability of transitioning to psychosis than those who met the attenuated psychotic symptoms (APS) criteria (HR=0.48, 95% CI: 0.32-0.73, p=0.001) and those who met the Trait risk criteria (a first-degree relative with a psychotic disorder or a schizotypal personality disorder plus a significant decrease in functioning during the previous year) (HR=0.43, 95% CI: 0.22-0.83, p=0.013). Models based on data from 1995-2016 displayed good calibration at initial model fitting, but showed a drift of 20.2-35.4% in calibration when validated on data from 2017-2020. Large-scale longitudinal data such as those from the UHR 1000+ cohort are required to develop accurate psychosis prediction models. It is critical to assess existing and future risk calculators for temporal drift, that may reduce their utility in clinical practice over time.

Ventilation heterogeneity is increased in adults exposed to coal mine fire-related PM2.5.

BACKGROUND AND OBJECTIVES: The Hazelwood Health Study was set up to study long-term health effects of a mine fire that blanketed residents of the Latrobe Valley with smoke for 45 days in 2014. The Respiratory Stream specifically assessed the impact of fine particulate matter <2.5 µm diameter (PM2.5) exposure from mine fire smoke on lung health. The multiple breath nitrogen washout (MBW) test assesses ventilation heterogeneity, which may detect sub-clinical airways dysfunction not identified using standard tests such as spirometry. This analysis assessed the association of PM2.5 exposure with measures of ventilation heterogeneity. METHODS: Exposed (Morwell) and unexposed (Sale) participants were recruited 3.5-4 years after the fire from those who had participated in an Adult Survey. MBW was performed to measure lung clearance index (LCI), functional residual capacity (FRC), acinar (Sacin) and conductive (Scond) ventilation heterogeneity. PM2.5 exposure was estimated with emission and chemical transport models. Multivariable linear regression models were fitted controlling for confounders. RESULTS: We recruited 519 participants. MBW tests were conducted on 504 participants with 479 acceptable test results (40% male; 313 exposed, 166 unexposed). Exposure to mine fire-related PM2.5 was associated with increasing Scond (ß = 1.57/kL, 95%CI: 0.20-2.95, p = 0.025), which was comparable to the estimated effect on Scond of 4.7 years of aging. No other MBW outcomes were statistically different. CONCLUSION: Increasing exposure to PM2.5 was associated with increased ventilation heterogeneity in the conductive region of the lungs 4 years after the event.

What impact did the COVID-19 pandemic have on psychosis and the delivery of early intervention psychosis services?

BACKGROUND: In Australia, the first nationwide COVID-19 lockdown occurred in March 2020 bringing challenges for early intervention psychosis (EIP) services. Limited evidence exists on the impacts of the pandemic on treatment outcomes among EIP clients. METHODS: This prospective cohort study analysed routine data from 15 headspace Early Psychosis centres in Australia. Participants were 12 to 25 years, meeting criteria for First Episode Psychosis (FEP) or Ultra High Risk of psychosis (UHR) comparing those who commenced treatment 'pre-COVID-19' (between 16th August 2018 and 15th August 2019), and 'during-COVID-19' (between 1st March 2020 and 15th September 2020). Clinical symptoms at treatment commencement were assessed using the Brief Psychiatric Rating Scale (BPRS) and the Kessler Psychological Distress Scale (K10). with outcomes after 6 months compared between cohorts using linear mixed-effects regression, controlling for confounders. RESULTS: Of 1246 young people analysed (653 FEP, 596 UHR), significant improvements were observed with treatment in both groups (5 to 13-point reduction in BPRS score per 6-months treatment). Treatment effectiveness reduced during-COVID-19 for psychosis symptoms, with the FEP BPRS treatment effect lower by 4.3 points (95%CI: 0.5, 8.1). UHR clients had lower BPRS negative symptoms during-COVID-19 (p = 0.020). Service contacts increased during-COVID-19, with increased telehealth services (p < 0.001). CONCLUSIONS: Early intervention remained effective for FEP and UHR, despite the pandemic and transition of EIP services to virtual service delivery. Reduced treatment efficacy in FEP psychosis symptoms may indicate potential limitations of telehealth. Further research to examine longer term clinical and functional outcomes due to the pandemic is required.

Cancer incidence after an open cut coal mine fire.

Using population-level cancer diagnosis data, we compared cancer incidence in locations affected by smoke from a six week-long open cut coal mine fire in regional Victoria, Australia, up to seven years following the event. There was no detectable effect on cancer incidence overall. While several subgroups exhibited changes, these were more likely due to statistical chance rather than real effects. These findings may be limited by low statistical power and short duration of follow up. To confirm the influence of open cut coal mine fires on cancer incidence, further research and an extended follow-up duration are necessary.

Changes in Rates of Special Considerations in Higher Education Applications Pre- and During the COVID-19 Pandemic in Victoria, Australia.

BACKGROUND AND AIMS: Since the onset of the COVID-19 pandemic, a significant rise in mental ill health has been observed globally in young people, particularly those in their final years of secondary school. Students' negative experiences coincide with a critical transitional period which can disrupt milestones in social and educational development. This study aimed to use innovative population-level data to map the impact of the pandemic on students entering higher education. METHODS: Pre-pandemic (2019/2020) and pandemic (2020/2021) tertiary education application data were obtained from the Victorian Tertiary Admissions Centre. Prevalence of applications for special consideration related to mental ill health were compared between cohorts across various geographical areas and applicant demographic subgroups. Relative risk regression models were used to understand the role of different risk factors. RESULTS: Rates of mental health-related special consideration applications increased by 38% among all applications (pre-pandemic: 7.8%, n = 56 916; pandemic: 10.8%, n = 58 260). Highest increases were observed among students in areas with both extended and close-quarter lockdown experiences, and areas impacted by 2019/2020 black summer bushfires. The increases were higher among Year 12 students and students with other special consideration needs (e.g., physical condition, learning disability). Slightly higher increases were observed in areas with higher socio-economic status, which may potentially be related to inequality in mental health service access. CONCLUSION: As consequences of mental health difficulties and academic disruption in youth can be long lasting, it is critical to establish a mental health support framework both in and outside of higher education to facilitate young people's recovery from the pandemic.

Inequitable access to mental healthcare for socially excluded adolescents.

BACKGROUND: Adolescence is a critical period for mental health and social exclusion, a key social determinant of mental health. Early intervention approaches are key to mitigating the impact of mental ill-health during adolescence, however social exclusion can create additional barriers to accessing care. AIM: We aimed to better understand help-seeking experiences of adolescents facing co-occurring social exclusion and mental ill-health, including sources of support, barriers and preferences for service provision. METHOD: Cross-sectional data were analysed, from the 2022 Mission Australia Youth Survey (N = 18,800). Adolescents aged 15 to 19 years were recruited from around Australia, through schools, community organisations and digital platforms. Indices of four domains of social exclusion (housing, finances, relational and education/employment) were created using existing Youth Survey variables, and supplemented with demographic characteristics, psychological distress and help-seeking behaviours (perceived need, mental health supports, barriers to access and preferences). Relationships between social exclusion domains, mental health concerns and help-seeking behaviours were explored using logistic regression models. RESULTS: A total of 9,743 young people reported having needed mental health support, yet only 58.1% reportedly sought support (n = 5,565). Social exclusion domains were associated with different help-seeking behaviours: housing challenges with higher help-seeking (OR = 1.28; 95% CI [1.15, 1.42]); relational difficulties and edu-employment issues with lower (OR = 0.75; 95% CI [0.68, 0.83] and OR = 0.82; 95% CI [0.75, 0.89]). Stigma, confidentiality concerns, cost and not knowing where to seek help were common barriers to help-seeking; those experiencing social exclusion more likely to report these. Participants reported a strong preference for face-to-face support. CONCLUSIONS: This study highlights the additional needs and challenges faced by adolescents dealing with both social exclusion and mental ill-health. With greater barriers to help-seeking, concerted efforts are needed to reduce stigma, improve mental health literacy and increase access to trusted information sources. Further initiatives should focus on structural factors that socially exclude young people and exacerbate inequitable access to mental healthcare.

Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods.

BACKGROUND: In randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual's risk of experiencing an outcome, then measuring treatment effect by subgroup. Given the limited availability of externally validated outcome risk prediction models, internal models (created using the same dataset in which heterogeneity of treatment analyses also will be performed) are commonly developed for subgroup identification. We aim to compare different methods for generating internally developed outcome risk prediction models for subject partitioning in HTE analysis. METHODS: Three approaches were selected for generating subgroups for the 2,441 participants from the United States enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial. An extant proportional hazards-based outcomes predictive risk model developed on the overall ASPREE cohort of 19,114 participants was identified and was used to partition United States' participants by risk of experiencing a composite outcome of death, dementia, or persistent physical disability. Next, two supervised non-parametric machine learning outcome classifiers, decision trees and random forests, were used to develop multivariable risk prediction models and partition participants into subgroups with varied risks of experiencing the composite outcome. Then, we assessed how the partitioning from the proportional hazard model compared to those generated by the machine learning models in an HTE analysis of the 5-year absolute risk reduction (ARR) and hazard ratio for aspirin vs. placebo in each subgroup. Cochran's Q test was used to detect if ARR varied significantly by subgroup. RESULTS: The proportional hazard model was used to generate 5 subgroups using the quintiles of the estimated risk scores; the decision tree model was used to generate 6 subgroups (6 automatically determined tree leaves); and the random forest model was used to generate 5 subgroups using the quintiles of the prediction probability as risk scores. Using the semi-parametric proportional hazards model, the ARR at 5 years was 15.1% (95% CI 4.0-26.3%) for participants with the highest 20% of predicted risk. Using the random forest model, the ARR at 5 years was 13.7% (95% CI 3.1-24.4%) for participants with the highest 20% of predicted risk. The highest outcome risk group in the decision tree model also exhibited a risk reduction, but the confidence interval was wider (5-year ARR = 17.0%, 95% CI= -5.4-39.4%). Cochran's Q test indicated ARR varied significantly only by subgroups created using the proportional hazards model. The hazard ratio for aspirin vs. placebo therapy did not significantly vary by subgroup in any of the models. The highest risk groups for the proportional hazards model and random forest model contained 230 participants each, while the highest risk group in the decision tree model contained 41 participants. CONCLUSIONS: The choice of technique for internally developed models for outcome risk subgroups influences HTE analyses. The rationale for the use of a particular subgroup determination model in HTE analyses needs to be explicitly defined based on desired levels of explainability (with features importance), uncertainty of prediction, chances of overfitting, and assumptions regarding the underlying data structure. Replication of these analyses using data from other mid-size clinical trials may help to establish guidance for selecting an outcomes risk prediction modelling technique for HTE analyses.

Vocational functioning in young people accessing services for first-episode psychosis and ultra-high risk of psychosis: A longitudinal naturalistic cohort study.

AIMS: Young people with first-episode psychosis (FEP) or at ultra-high risk (UHR) of psychosis often have lower vocational engagement than their peers. This study examines the effect of treatment in early intervention for psychosis services in Australia on engagement in education and employment. METHODS: This is a naturalistic sample of young people aged 12-25 with FEP (n = 1574) and UHR (n = 1515), accessing treatment in the headspace Early Psychosis (hEP) programme. Engagement in education and employment was assessed at baseline and every 90 days in treatment. Mixed effects logistic regression were used to analyse changes over time. RESULTS: On entering the hEP programme, approximately 49% of the young people with FEP and 28% of the young people at UHR status identified as Not in Education, Employment or Training (NEET). The odds of being NEET were reduced by 27% (95% confidence interval = [14, 39]) for every 6 months treatment for the FEP group, but no change in NEET status was observed in the UHR group. In both groups, absence from daily activities was significantly reduced during time in treatment. CONCLUSION: While there are methodological challenges analysing real-world non-control group cohort data, the findings indicate positive effects of the hEP programme on vocational and daily activity engagement for young people with FEP and at UHR status. A large proportion of the young people still identified as NEET after receiving treatment services, suggesting further refinement to ensure targeted and consistent vocational support throughout care.

Long-term effects of a coalmine fire on hospital and ambulance use: An interrupted time series study.

BACKGROUND: In 2014, the Hazelwood coalmine fire in regional Victoria, Australia shrouded nearby communities in smoke for six weeks. Prior investigations identified substantial adverse effects, including increases in the use of health services. In this study, we examined the effects on hospital and ambulance use in the eight years following the fire. METHODS: Using Victorian hospital (Jan 2009-Jun 2022) and ambulance (Jan 2013-Dec 2021) data, we conducted an interrupted time series of changes to the rate of hospital admissions, emergency presentations, and ambulance attendances. A categorical exposure model compared two locations, most-exposed Morwell and less-exposed Latrobe Valley, to the rest of regional Victoria. A continuous exposure model used spatial estimates of fire-related PM2.5. Analyses were stratified by sex, age group (<65/65+ years), and condition (cardiovascular, respiratory, mental health, injury). RESULTS: There were small but significant increases in overall hospital admissions and emergency presentations across all analyses, but little evidence of change in overall ambulance attendances. Effects varied considerably by condition, with the biggest relative increases observed among hospital admissions for mental health conditions and injuries. While cardiovascular-related hospital admissions and emergency presentations increased post-fire, ambulance attendances decreased. CONCLUSIONS: Our findings suggest the Hazelwood coalmine fire likely increased hospital usage. However, it is unclear whether this was due to the direct effects of smoke exposure on health, or the disruptive socioeconomic and behavioural impacts of an environmental disaster that affected how communities engaged with various health services.

Association between PM2.5 from a coal mine fire and FeNO concentration 7.5 years later.

BACKGROUND AND AIM: There are few long-term studies of respiratory health effects of landscape fires, despite increasing frequency and intensity due to climate change. We investigated the association between exposure to coal mine fire PM2.5 and fractional exhaled nitric oxide (FeNO) concentration 7.5 years later. METHODS: Adult residents of Morwell, who were exposed to the 2014 Hazelwood mine fire over 6 weeks, and unexposed residents of Sale, participated in the Hazelwood Health Study Respiratory Stream in 2021, including measurements of FeNO concentration, a marker of eosinophilic airway inflammation. Individual exposure to coal mine fire PM2.5 was modelled and mapped to time-location diaries. The effect of exposure to PM2.5 on log-transformed FeNO in exhaled breath was investigated using multivariate linear regression models in the entire sample and stratified by potentially vulnerable subgroups. RESULTS: A total of 326 adults (mean age: 57 years) had FeNO measured. The median FeNO level (interquartile range [IQR]) was 17.5 [15.0] ppb, and individual daily exposure to coal mine fire PM2.5 was 7.2 [13.8] µg/m3. We did not identify evidence of association between coal mine fire PM2.5 exposure and FeNO in the general adult sample, nor in various potentially vulnerable subgroups. The point estimates were consistently close to zero in the total sample and subgroups. CONCLUSION: Despite previous short-term impacts on FeNO and respiratory health outcomes in the medium term, we found no evidence that PM2.5 from the Hazelwood coal mine fire was associated with any long-term impact on eosinophilic airway inflammation measured by FeNO levels.

A Prototype Software Framework for Transferable Computational Health Economic Models and Its Early Application in Youth Mental Health.

We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework.

Increased vascular stiffness in children exposed in utero but not children exposed postnatally to emissions from a coal mine fire.

Background: Chronic, low-intensity air pollution exposure has been consistently associated with increased atherosclerosis in adults. However, there was limited research regarding the implications of acute, high-intensity air pollution exposure during childhood. We aimed to determine whether there were any associations between early-life exposure to such an episode and early-life vascular function changes. Methods: We conducted a prospective cohort study of children (<9 years old) who lived in the vicinity of the Hazelwood coal mine fire (n = 206). Vascular function was measured using noninvasive diagnostic methods including carotid intima-media thickness and pulse wave velocity (PWV). Exposure estimates were calculated from prognostic models and location diaries during the exposure period completed by each participant's parent. Linear mixed-effects models were used to determine whether there were any associations between exposure and changes in vascular outcomes at the 3- and 7-year follow-ups and over time. Results: At the 7-year follow-up, each 10 µg/m3 increase in daily PM2.5 in utero was associated with increased PWV (ß = 0.13 m/s; 95% confidence interval [CI] = 0.02, 0.24; P = 0.02). The association between in utero exposure to daily PM2.5 was not altered by adjustment for covariates, body mass index, and maternal fire stress. Each 1 µg/m3 increase in background PM2.5 was associated with increased PWV (ß = 0.68 m/s; 95% CI = 0.10, 1.26; P = 0.025), in children from the in utero exposure group. There was a trend toward smaller PWV (ß = -0.17 m/s; 95% CI = -0.366, 0.02) from the 3- to 7-year follow-up clinic suggesting that the deficits observed previously in children exposed postnatally did not persist. Conclusion: There was a moderate improvement in vascular stiffness of children exposed to PM2.5 from a local coal mine fire in infancy. There was a mild increase in vascular stiffness in children exposed to PM2.5 from a local coal mine fire while their mothers were pregnant.

Validating cognitive screening in young people with first-episode psychosis: The CogScreen protocol.

AIM: Cognitive impairments are a core feature of first-episode psychosis (FEP) and one of the strongest predictors of long-term psychosocial functioning. Cognition should be assessed and treated as part of routine clinical care for FEP. Cognitive screening offers the opportunity to rapidly identify and triage those in most need of cognitive support. However, there are currently no validated screening measures for young people with FEP. CogScreen is a hybrid effectiveness-implementation study which aims to evaluate the classification accuracy (relative to a neuropsychological assessment as a reference standard), test-retest reliability and acceptability of two cognitive screening tools in young people with FEP. METHODS: Participants will be 350 young people (aged 12-25) attending primary and specialist FEP treatment centres in three large metropolitan cities (Adelaide, Sydney, and Melbourne) in Australia. All participants will complete a cross-sectional assessment over two sessions including two cognitive screening tools (Screen for Cognitive Impairment in Psychiatry and Montreal Cognitive Assessment), a comprehensive neuropsychological assessment battery, psychiatric and neurodevelopmental assessments, and other supplementary clinical measures. To determine the test-retest reliability of the cognitive screening tools, a subset of 120 participants will repeat the screening measures two weeks later. RESULTS: The protocol, rationale, and hypotheses for CogScreen are presented. CONCLUSIONS: CogScreen will provide empirical evidence for the validity and reliability of two cognitive screening tools when compared to a comprehensive neuropsychological assessment. The screening measures may later be incorporated into clinical practice to assist with rapid identification and treatment of cognitive deficits commonly experienced by young people with FEP.

Does diet quality moderate the long-term effects of discrete but extreme PM2.5 exposure on respiratory symptoms? A study of the Hazelwood coalmine fire.

In 2014, a fire at an open cut coalmine in regional Victoria, Australia burned for 6 weeks. Residents of the nearby town of Morwell were exposed to smoke, which included high levels of fine particulate matter (PM2.5). We investigated whether the long-term effects of PM2.5 on respiratory health were moderated by diet quality. A cross-sectional analysis was conducted of data collected 8.5 years after the mine fire from 282 residents of Morwell and 166 residents from the nearby unexposed town of Sale. Primary outcomes were respiratory symptoms. Exposure was coalmine fire-related PM2.5 and diet quality was assessed as Australian Recommended Food Score (ARFS) derived using the Australian Eating Survey (AES). The moderating effect of diet quality on respiratory outcomes associated with PM2.5 was assessed using logistic regression models, adjusting for potential confounders. Diet quality was poor in this sample, with 60% in the lowest category of overall diet quality. Overall diet quality and fruit and vegetable quality significantly attenuated the association between PM2.5 and prevalence of chronic cough and phlegm. Sauce/condiment intake was associated with a greater effect of PM2.5 on COPD prevalence. No other moderating effects were significant. The moderating effects of overall diet quality and vegetable and fruit intake aligned with a priori hypotheses, suggesting potential protective benefits. While more evidence is needed to confirm these findings, improving diets, especially fruit and vegetable intake, may provide some protection against the effects of smoke exposure from fire events.

Impact of climate zones and seasons on indoor airborne microbial communities: Insights from a comprehensive analysis.

Bacteria and fungi are ubiquitous throughout built environments and are suspended in the air, potentially affecting human health. However, the impacts of climate zones on the diversity, structure, and stochastic assembly of indoor airborne microbes remain unknown. This study comprehensively analyzed indoor airborne microbes across five climate zones in China during the summer and winter using high-throughput sequencing. The diversity and structure of indoor airborne communities vary across climatic zones. A random forest model was used to identify biomarkers in different climate zones. The results showed no relationship between the biomarkers and their rankings in mean relative abundance. The Sloan neutral model fitting results indicated that the impact of climate zones on the stochastic process in the assembly of indoor airborne microbes was considerably more important than that of seasons. Additionally, the influence of seasons on the diversity, structure, and stochastic assembly process of indoor airborne microbes differed among different climate zones. The diversity, structure, and stochastic assembly processes of bacteria present distinctive outcomes in climate zones and seasons compared with those of fungi. Overall, these findings indicate that customized strategies are necessary to manage indoor airborne microbial communities in each climate zone, season, and for specific microbial species.

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research.

Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.

Lung function changes in children exposed to mine fire smoke in infancy.

BACKGROUND AND OBJECTIVE: Chronic, low-intensity air pollution exposure has been consistently associated with reduced lung function throughout childhood. However, there is limited research regarding the implications of acute, high-intensity air pollution exposure. We aimed to determine whether there were any associations between early life exposure to such an episode and lung growth trajectories. METHODS: We conducted a prospective cohort study of children who lived in the vicinity of the Hazelwood coalmine fire. Lung function was measured using respiratory oscillometry. Z-scores were calculated for resistance (R5 ) and reactance at 5 Hz (X5 ) and area under the reactance curve (AX). Two sets of analyses were conducted: (i) linear regression to assess the cross-sectional relationship between post-natal exposure to mine fire-related particulate matter with an aerodynamic diameter of less than 2.5 micrometres (PM2.5 ) and lung function at the 7-year follow-up and (ii) linear mixed-effects models to determine whether there was any association between exposure and changes in lung function between the 3- and 7-year follow-ups. RESULTS: There were no associations between mine fire-related PM2.5 and any of the lung function measures, 7-years later. There were moderate improvements in X5 (ß: -0.37 [-0.64, -0.10] p = 0.009) and AX (ß: -0.40 [-0.72, -0.08] p = 0.014), between the 3- and 7-year follow-ups that were associated with mean PM2.5 , in the unadjusted and covariance-adjusted models. Similar trends were observed with maximum PM2.5 . CONCLUSION: There was a moderate improvement in lung stiffness of children exposed to PM2.5 from a local coalmine fire in infancy, consistent with an early deficit in lung function at 3-years after the fire that had resolved by 7-years.

Long-term effects of extreme smoke exposure on COVID-19: A cohort study.

BACKGROUND: In 2014, the Hazelwood coalmine fire shrouded the regional Australian town of Morwell in smoke and ash for 6 weeks. One of the fire's by-products, PM2.5 , is associated with an increased risk of COVID-19 and severe disease. However, it is unclear whether the effect persisted for years after exposure. In this study, we surveyed a cohort established prior to the pandemic to determine whether PM2.5 from the coalmine fire increased long-term vulnerability to COVID-19 and severe disease. METHODS: From August to December 2022, 612 members of the Hazelwood Health Study's adult cohort, established in 2016/17, participated in a follow-up survey that included standardized items to capture COVID-19 cases, as well as questions about hospitalization and vaccinations. Associations were evaluated in crude and adjusted logistic regression models. RESULTS: A total of 268 (44%) participants self-reported or met symptom criteria for having had COVID-19 at least once. All models found a positive association, with odds of COVID-19 increasing by between 4% and 30% for a 10 µg/m3 increase in coalmine fire-related PM2.5 exposure. However, the association was significant in only 2 of the 18 models. There were insufficient hospitalizations to examine severity (n = 7; 1%). CONCLUSION: The findings are inconclusive on the effect of coalmine fire-related PM2.5 exposure on long-term vulnerability to COVID-19. Given the positive association that was robust to modelling variations as well as evidence for a causal mechanism, it would be prudent to treat PM2.5 from fire events as a long-term risk factor until more evidence accumulates.

Risk evaluation of venue types and human behaviors of COVID-19 outbreaks in public indoor environments: A systematic review and meta-analysis.

Despite increasing vaccination rates, the incidence of breakthrough infections with COVID-19 has increased due to the continued emergence of new variants of the SARS-CoV-2 coronavirus. Therefore, Non-pharmaceutical interventions remain the most effective measures for coping with the ever-changing pandemic. The lifting of compulsory interventions has made individuals primary responsibility for their own health, which highlights the importance of increasing awareness of the infection risk from the environment in which they live and their individual behaviors. We systematically searched PubMed, Web of Science, ScienceDirect, and Scopus on April 17, 2023, for all studies reporting COVID-19 outbreaks in public indoor venues. The study outcome was the attack rate. A total of 42 studies, which included cross-sectional studies, cohort studies, and case studies, reporting data on 1951 confirmed cases in 64 COVID-19 outbreaks satisfied the meta-analysis and were included in the review. A random-effect model was used in the meta-analysis, and subgroup analyses were conducted to investigate factors affecting attack rates. We found a strong level of evidence (p < 0.01) supporting a higher pooled attack rate in recreation-related venues (0.44, 95% CI: 0.30 to 0.60) than in work-related venues (0.21, 95% CI: 0.16 to 0.27). Compared to those outbreaks without that, outbreaks with high-intensity exercise, vocalization, contact behavior, or close body proximity had a higher attack rate of 0.51, 0.55, 0.33, and 0.39, respectively. Further studies suggest that different attack rates across different types of settings may be the result of heterogeneity in exposed people's behaviors. There were significant heterogeneities that may limit the interpretation of connections between influencing factors and outbreak outcomes. The identification of key behaviors that may contribute to transmission risk, and their correlation with venue type, has important implications for the development of future public health interventions and individual prevention strategies for respiratory infectious diseases such as COVID-19.