What is the prevalence, and what are the clinical correlates, of insulin resistance in young people presenting for mental health care? A cross-sectional study

Insulinemic potential of lifestyle is associated with depression and anxiety in adults: A large community-based study

BACKGROUND

We aimed to investigate the association between an empirical lifestyle index for hyperinsulinemia (ELIH), empirical lifestyle index for insulin resistance (ELIR), and depression and anxiety in an adult Iranian population.

METHODS

In this cross-sectional study, a total of 6450 participants, aged 35-65 years were recruited as part of the MASHAD cohort study. Dietary intakes were assessed using a validated food frequency questionnaire (FFQ). Depression and anxiety were screened using Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI). ELIH and ELIR were calculated using dietary intake, body mass index, and physical activity information. Multivariable ordinal logistic regression models were applied to determine the association between ELIH, ELIR, and depression and anxiety severity.

RESULTS

In a fully adjusted model, participants with the highest ELIH quartile had a higher odds of more severe depression and anxiety compared to those in the lowest category (OR = 1.44; 95 % CI = 1.22-1.71 and OR = 1.62; 95 % CI = 1.37-1.25, respectively). Participants with the highest ELIR had higher odds of more severe depression and anxiety compared to those in the lowest category (OR = 1.22; 95 % CI = 1.04-1.43 and OR = 1.21; 95 % CI = 1.03-1.42, respectively).

LIMITATIONS

The assessment of dietary intake and mental health by questionnaires may increases the rate of misclassification. Due to the study's cross-sectional nature, causal relationships cannot be established.

CONCLUSION

There was a significant positive association between the hyperinsulinemia and insulin resistance potential of lifestyle and severity of depression and anxiety among Iranian adults.

Cross-sectional and longitudinal associations between cardiometabolic measures and clinical stage in young people accessing early intervention mental health services

AIM

This retrospective cohort study aimed to identify the cardiometabolic characteristics, cross-sectionally and longitudinally, associated with clinical stage in youth accessing early intervention mental health services.

METHODS

Cardiometabolic data we collected in 511 young people (aged 12-25 years at entry) receiving mental health care at the early intervention services in Sydney, Australia.

RESULTS

The majority of young people (N = 448, 87.67%) were classified in stage 1a or 1b at entry. At entry to care, there was no cross-sectional relationship between clinical stage and age, gender, fasting insulin, fasting glucose, updated homeostatic model assessment for insulin resistance (HOMA2-IR) score, BMI or waist circumference. Of the 111 (21.7%) young people initially classified at stage 1a ('non-specific symptoms') and the 337 (65.9%) classified in stage 1b ('attenuated syndromes'), 40 individuals transitioned to stage 2+ (7.8%) ("full-threshold disorders") longitudinally. No cardiometabolic factors predicted clinical stage transitions. However, those with an increase in BMI over the course of care (n = 54) were 1.46 (OR; 95% CI: 1.02-2.17) times more likely to progress to stage 2+ at follow up.

CONCLUSIONS

Whilst no relationships were found between demographic or cardiometabolic variables and clinical stage at entry to care, an increased BMI over time was associated with clinical stage transition longitudinally. Further longitudinal research is needed to understand the demographic, clinical, illness progression or treatment factors associated with changes in cardiometabolic status.

Double-blind, randomised placebo-controlled clinical trial of metformin as an adjunct to a sleep-wake, activity and metabolically focused behavioural intervention to improve cardiometabolic outcomes and mood symptoms in youth with major mood syndromes: study protocol

INTRODUCTION

Metformin is a medication likely to improve measures of cardiometabolic disturbance in young people with mental illness. Evidence also suggests metformin may improve depressive symptoms. This 52-week double-blind randomised control trial (RCT) aims to investigate the efficacy of metformin pharmacotherapy as an adjunct to a healthy lifestyle behavioural intervention in improving cardiometabolic outcomes, and depressive, anxiety and psychotic symptoms in youth with clinically diagnosed major mood syndromes.

METHODS AND ANALYSIS

At least 266 young people aged 16-25 presenting for mental healthcare for major mood syndromes who are also at risk for poor cardiometabolic outcomes will be invited to participate in this study. All participants will engage in a 12-week sleep-wake, activity and metabolically focused behavioural intervention programme. As an adjunctive intervention, participants will receive either metformin (500-1000 mg) or placebo pharmacotherapy for 52 weeks.Participants will undergo a series of assessments including: (1) self-report and clinician-administered assessments; (2) blood tests; (3) anthropometric assessments (height, weight, waist circumference and blood pressure); and (4) actigraphy. Univariate and multivariate tests (generalised mixed-effects models) will be used to examine changes in primary and secondary outcomes (and associations with predetermined predictor variables).

ETHICS AND DISSEMINATION

This study has been approved by the Sydney Local Health District Research Ethics and Governance Office (X22-0017). The results of this double-blind RCT will be disseminated into the scientific and broader community through peer-reviewed journals, conference presentations, social media and university websites.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry (ANZCTR) Number: ACTRN12619001559101p, 12 November 2019.

Metabolic and clinical profiles of young people with mood or psychotic disorders who are prescribed metformin in an inpatient setting

OBJECTIVE

Youth with early-onset mood or psychotic disorders are occasionally prescribed metformin to manage cardiometabolic risk. This retrospective study explores the demographic, clinical and metabolic factors associated with metformin prescription youth with mood or psychotic disorders.

METHOD

Participants included 72 youth with mood or psychotic disorders from a young adult mental health inpatient unit, of which 18 (33%) were newly prescribed metformin, and 54 (66%) were not prescribed metformin. Demographic and clinical information were extracted from the patients' medical files along with body mass index (BMI), fasting serum bloods and calculated updated homeostatic model of insulin resistance assessment (HOMA2-IR) scores to compare profiles between groups.

RESULTS

Of those prescribed metformin, 83% were overweight or obese and 72% had elevated HOMA2-IR scores. Of those not receiving metformin treatment, 41% were overweight or obese and 22% had elevated HOMA2-IR scores. Youth prescribed metformin had significantly higher BMI, and elevated markers of insulin resistance, but did not differ to those not prescribed metformin on other demographic, clinical or metabolic factors.

CONCLUSIONS

While metformin is prescribed to some youth with mood or psychotic disorders displaying markers of cardiometabolic disturbance, there is a need to develop clearer treatment guidelines for metformin in these youth.

Identifying pathways to early-onset metabolic dysfunction, insulin resistance and inflammation in young adult inpatients with emerging affective and major mood disorders

AIM

Young people with common mood disorders face the prospect of shortened life expectancy largely due to premature cardiovascular disease. Metabolic dysfunction is a risk factor for premature cardiovascular disease. There is an ongoing debate whether metabolic dysfunction can be simply explained by weight gain secondary to psychotropic medications or whether shared genetic vulnerability, intrinsic immune-metabolic disturbances or other system perturbations (e.g. dysregulated sympathetic nervous system, circadian dysfunction) are more relevant determinants of premature cardiovascular disease. Thus, we aimed to investigate underlying drivers of metabolic dysfunction and premature cardiovascular disease in young people in the early phases of common mood disorders.

METHODS

We evaluated the relationships between insulin resistance (assessed by HOMA2-IR) and body mass index (BMI), sex, diagnosis, medication, inflammatory markers and hormonal factors in 327 inpatients with emerging affective and major mood disorders admitted to the Young Adult Mental Health Unit, St Vincent's Private Hospital, Sydney.

RESULTS

While HOMA2-IR scores were positively associated with BMI (r_s  = 0.465, p < .001), they were also higher in those prescribed mood stabilizers (p = .044) but were not associated with specific diagnoses, other medication types or the number of prescribed medications. Further, high-sensitivity C-reactive protein levels (but not thyroid-stimulating hormone and ferritin levels) were positively associated with HOMA2-IR (r_s  = 0. 272, p < .001) and BMI (r_s  = . 409, p < .001).

CONCLUSIONS

In addition to BMI, other non-specific markers of inflammation are associated with early metabolic dysfunction in young people with emerging affective and major mood disorders.

Young people's advisory groups in health research: scoping review and mapping of practices

BACKGROUND

Young people's advisory groups (YPAGs) for research are comprised of children or adolescents who work with researchers to shape different stages of the research process. Their involvement is expected to ensure studies better reflect the preferences and needs of targeted youth populations. However, despite their increasing use in health research, there is little systematic evidence on the methods and impacts associated with YPAGs.

METHOD

To address this gap, we conducted a scoping review of YPAGs in youth-focused health studies. We systematically searched MEDLINE for empirical studies in populations between 12 years and 18 years of age published in 2019. If a potential YPAG was identified, authors were contacted for additional information about the activities and level of involvement of the YPAG.

FINDINGS

Of all studies that collected primary data from persons aged 12-18 years, only 21 studies reported using youth advice during their research. This represents less than 1% of all published empirical child and adolescent studies. There was variation in the type of research activity undertaken by YPAGs and their level of involvement. Most studies involved YPAGs in co-production of research design and/or in dissemination activities. The majority of authors that responded were positive about the impact of YPAGs.

INTERPRETATION

Recommendations for consistent reporting of YPAG involvement in empirical studies include reporting on the match between YPAG and study populations, frequency/format of meetings, and the nature and level of involvement.

Association between insulin resistance and BMI with FEV1 in non-hypoxemic COPD out-patients

OBJECTIVES

This study was conducted to determine the impact of insulin resistance using Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) score and BMI in non-hypoxemic out-patients with COPD on FEV₁ using linear and polynomial regressions and to determine their correlation.

METHODS

COPD patients of both genders were included after informed consent. Fasting blood sugar and serum insulin were done to calculate HOMA-IR, which were segregated into two groups of ≥ 3 and < 3 labeled insulin resistance present and absent, these were compared with BMI. Patients were segregated into GOLD Grade 1-4 per GOLD Guidelines and compared with HOMA-IR and BMI. Curve and linear regressions, multivariate and univariate analysis of HOMA-IR with BMI, FVC, and FEV₁ were done.

RESULTS

A total of 273 subjects were inducted after informed consent. There was a linear correlation between HOMA-IR and BMI (r² 0.498, P < 0.001) and nonlinear correlation between HOMA-IR and FEV1 (r² 0. 617, P < 0.001) which showed little evidence of association above FEV1 > 60 predicted, but a clear negative association below that. Significant increase in HOMA-IR was seen from GOLD-2 to 3 and from GOLD-3 to 4 classes. The impact of HOMA-IR on FEV1 was 49.9% (P < 0.001) on FVC was 43.7%.

CONCLUSIONS

The results indicate that there is a high prevalence of IR in non-hypoxemic COPD. A nonlinear association is present between FEV1 and HOMA-IR which is most evident with FEV1 <60% predicted.

Youth Mental Health Tracker: protocol to establish a longitudinal cohort and research database for young people attending Australian mental health services

INTRODUCTION

Mental disorders are a leading cause of long-term disability worldwide. Much of the burden of mental ill-health is mediated by early onset, comorbidities with physical health conditions and chronicity of the illnesses. This study aims to track the early period of mental disorders among young people presenting to Australian mental health services to facilitate more streamlined transdiagnostic processes, highly personalised and measurement-based care, secondary prevention and enhanced long-term outcomes.

METHODS AND ANALYSIS

Recruitment to this large-scale, multisite, prospective, transdiagnostic, longitudinal clinical cohort study ('Youth Mental Health Tracker') will be offered to all young people between the ages of 12 and 30 years presenting to participating services with proficiency in English and no history of intellectual disability. Young people will be tracked over 3 years with standardised assessments at baseline and 3, 6, 12, 24 and 36 months. Assessments will include self-report and clinician-administered measures, covering five key domains including: (1) social and occupational function; (2) self-harm, suicidal thoughts and behaviour; (3) alcohol or other substance misuse; (4) physical health; and (5) illness type, clinical stage and trajectory. Data collection will be facilitated by the use of health information technology. The data will be used to: (1) determine prospectively the course of multidimensional functional outcomes, based on the differential impact of demographics, medication, psychological interventions and other key potentially modifiable moderator variables and (2) map pathophysiological mechanisms and clinical illness trajectories to determine transition rates of young people to more severe illness forms.

ETHICS AND DISSEMINATION

The study has been reviewed and approved by the Human Research Ethics Committee of the Sydney Local Health District (2019/ETH00469). All data will be non-identifiable, and research findings will be disseminated through peer-reviewed journals and scientific conference presentations.

Right care, first time: a highly personalised and measurement-based care model to manage youth mental health

Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change. Consequently, the effects of adolescent-onset mood and psychotic syndromes can have long term consequences. A key clinical challenge for youth mental health is to develop and test new systems that align with current evidence for comorbid presentations and underlying neurobiology, and are useful for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. Our highly personalised and measurement-based care model includes three core concepts: ▶ A multidimensional assessment and outcomes framework that includes: social and occupational function; self-harm, suicidal thoughts and behaviour; alcohol or other substance misuse; physical health; and illness trajectory. ▶ Clinical stage. ▶ Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on proposed pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). The model explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within this highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care as well as utilisation of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality, mental health care for young people. CHAPTER 1: MULTIDIMENSIONAL OUTCOMES IN YOUTH MENTAL HEALTH CARE: WHAT MATTERS AND WHY?: Mood and psychotic syndromes present one of the most serious public health challenges that we face in the 21st century. Factors including prevalence, age of onset, and chronicity contribute to substantial burden and secondary risks such as alcohol or other substance misuse. Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change; thus, effects can have long term consequences. We propose five key domains which make up a multidimensional outcomes framework that aims to address the specific needs of young people presenting to health services with emerging mental illness. These include social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Impairment and concurrent morbidity are well established in young people by the time they present for mental health care. Despite this, services and health professionals tend to focus on only one aspect of the presentation - illness type, stage and trajectory - and are often at odds with the preferences of young people and their families. There is a need to address the disconnect between mental health, physical health and social services and interventions, to ensure that youth mental health care focuses on the outcomes that matter to young people. CHAPTER 2: COMBINING CLINICAL STAGE AND PATHOPHYSIOLOGICAL MECHANISMS TO UNDERSTAND ILLNESS TRAJECTORIES IN YOUNG PEOPLE WITH EMERGING MOOD AND PSYCHOTIC SYNDROMES: Traditional diagnostic classification systems for mental disorders map poorly onto the early stages of illness experienced by young people, and purport categorical distinctions that are not readily supported by research into genetic, environmental and neurobiological risk factors. Consequently, a key clinical challenge in youth mental health is to develop and test new classification systems that align with current evidence on comorbid presentations, are consistent with current understanding of underlying neurobiology, and provide utility for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. This chapter outlines a transdiagnostic framework for classifying common adolescent-onset mood and psychotic syndromes, combining two independent but complementary dimensions: clinical staging, and three proposed pathophysiological mechanisms. Clinical staging reflects the progression of mental disorders and is in line with the concept used in general medicine, where more advanced stages are associated with a poorer prognosis and a need for more intensive interventions with a higher risk-to-benefit ratio. The three proposed pathophysiological mechanisms are neurodevelopmental abnormalities, hyperarousal and circadian dysfunction, which, over time, have illness trajectories (or pathways) to psychosis, anxious depression and bipolar spectrum disorders, respectively. The transdiagnostic framework has been evaluated in young people presenting to youth mental health clinics of the University of Sydney's Brain and Mind Centre, alongside a range of clinical and objective measures. Our research to date provides support for this framework, and we are now exploring its application to the development of more personalised models of care. CHAPTER 3: A COMPREHENSIVE ASSESSMENT FRAMEWORK FOR YOUTH MENTAL HEALTH: GUIDING HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE USING MULTIDIMENSIONAL AND OBJECTIVE MEASURES: There is an urgent need for improved care for young people with mental health problems, in particular those with subthreshold mental disorders that are not sufficiently severe to meet traditional diagnostic criteria. New comprehensive assessment frameworks are needed to capture the biopsychosocial profile of a young person to drive highly personalised and measurement-based mental health care. We present a range of multidimensional measures involving five key domains: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Objective measures include: neuropsychological function; sleep-wake behaviours and circadian rhythms; metabolic and immune markers; and brain structure and function. The recommended multidimensional measures facilitate the development of a comprehensive clinical picture. The objective measures help to further develop informative and novel insights into underlying pathophysiological mechanisms and illness trajectories to guide personalised care plans. A panel of specific multidimensional and objective measures are recommended as standard clinical practice, while others are recommended secondarily to provide deeper insights with the aim of revealing alternative clinical paths for targeted interventions and treatments matched to the clinical stage and proposed pathophysiological mechanisms of the young person. CHAPTER 4: PERSONALISING CARE OPTIONS IN YOUTH MENTAL HEALTH: USING MULTIDIMENSIONAL ASSESSMENT, CLINICAL STAGE, PATHOPHYSIOLOGICAL MECHANISMS, AND INDIVIDUAL ILLNESS TRAJECTORIES TO GUIDE TREATMENT SELECTION: New models of mental health care for young people require that interventions be matched to illness type, clinical stage, underlying pathophysiological mechanisms and individual illness trajectories. Narrow syndrome-focused classifications often direct clinical attention away from other key factors such as functional impairment, self-harm and suicidality, alcohol or other substance misuse, and poor physical health. By contrast, we outline a treatment selection guide for early intervention for adolescent-onset mood and psychotic syndromes (ie, active treatments and indicated and more specific secondary prevention strategies). This guide is based on experiences with the Brain and Mind Centre's highly personalised and measurement-based care model to manage youth mental health. The model incorporates three complementary core concepts: ▶A multidimensional assessment and outcomes framework including: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness trajectory. ▶Clinical stage. ▶Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on three underlying pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). These core concepts are not mutually exclusive and together may facilitate improved outcomes through a clinical stage-appropriate and transdiagnostic framework that helps guide decisions regarding the provision of appropriate and effective care options. Given its emphasis on adolescent-onset mood and psychotic syndromes, the Brain and Mind Centre's model of care also respects a fundamental developmental perspective - categorising childhood problems (eg, anxiety and neurodevelopmental difficulties) as risk factors and respecting the fact that young people are in a period of major biological and social transition. Based on these factors, a range of social, psychological and pharmacological interventions are recommended, with an emphasis on balancing the personal benefit-to-cost ratio. CHAPTER 5: A SERVICE DELIVERY MODEL TO SUPPORT HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE IN YOUTH MENTAL HEALTH: Over the past decade, we have seen a growing focus on creating mental health service delivery models that better meet the unique needs of young Australians. Recent policy directives from the Australian Government recommend the adoption of stepped-care services to improve the appropriateness of care, determined by severity of need. Here, we propose that a highly personalised approach enhances stepped-care models by incorporating clinical staging and a young person's current and multidimensional needs. It explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within a highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care and use of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality of, mental health care for young people.