Prevalence of adolescent mental disorders in Kenya, Indonesia, and Viet Nam measured by the National Adolescent Mental Health Surveys (NAMHS): a multi-national cross-sectional study.

BACKGROUND: Mental disorders are the leading global cause of health burden among adolescents. However, prevalence data for mental disorders among adolescents in low-income and middle-income countries are scarce with often limited generalisability. This study aimed to generate nationally representative prevalence estimates for mental disorders in adolescents in Kenya, Indonesia, and Viet Nam. METHODS: As part of the National Adolescent Mental Health Surveys (NAMHS), a multinational cross-sectional study, nationally representative household surveys were conducted in Kenya, Indonesia, and Viet Nam between March and December, 2021. Adolescents aged 10-17 years and their primary caregiver were interviewed from households selected randomly according to sampling frames specifically designed to elicit nationally representative results. Six mental disorders (social phobia, generalised anxiety disorder, major depressive disorder, post-traumatic stress disorder, conduct disorder, and attention-deficit hyperactivity disorder) were assessed with the Diagnostic Interview Schedule for Children, Version 5. Suicidal behaviours and self-harm in the past 12 months were also assessed. Prevalence in the past 12 months and past 4 weeks was calculated for each mental disorder and collectively for any mental disorder (ie, of the six mental disorders assessed). Prevalence of suicidal behaviours (ie, ideation, planning, and attempt) and self-harm in the past 12 months was calculated, along with adjusted odds ratios (aORs) to show the association with prevalence of any mental disorder in the past 12 months. Inverse probability weighting was applied to generate national estimates with corresponding 95% CIs. FINDINGS: Final samples consisted of 5155 households (ie, adolescent and primary caregiver pairs) from Kenya, 5664 households from Indonesia, and 5996 households from Viet Nam. In Kenya, 2416 (46·9%) adolescents were male and 2739 (53·1%) were female; in Indonesia, 2803 (49·5%) adolescents were male and 2861 (50·5%) were female; and in Viet Nam, 3151 (52·5%) were male and 2845 (47·4%) were female. Prevalence of any mental disorder in the past 12 months was 12·1% (95% CI 10·9-13·5) in Kenya, 5·5% (4·3-6·9) in Indonesia, and 3·3% (2·7-4·1) in Viet Nam. Prevalence in the past 4 weeks was 9·4% (8·3-10·6) in Kenya, 4·4% (3·4-5·6) in Indonesia, and 2·7% (2·2-3·3) in Viet Nam. The prevalence of suicidal behaviours in the past 12 months was low in all three countries, with suicide ideation ranging from 1·4% in Indonesia (1·0-2·0) and Viet Nam (1·0-1·9) to 4·6% (3·9-5·3) in Kenya, suicide planning ranging from 0·4% in Indonesia (0·3-0·8) and Viet Nam (0·2-0·6) to 2·4% (1·9-2·9) in Kenya, and suicide attempts ranging from 0·2% in Indonesia (0·1-0·4) and Viet Nam (0·1-0·3) to 1·0% (0·7-1·4) in Kenya. The prevalence of self-harm in the past 12 months was also low in all three countries, ranging from 0·9% (0·6-1·3) in Indonesia to 1·2% (0·9-1·7) in Kenya. However, the prevalence of suicidal behaviours and self-harm in the past 12 months was significantly higher among those with any mental disorder in the past 12 months than those without (eg, aORs for suicidal ideation ranged from 7·1 [3·1-15·9] in Indonesia to 14·7 [7·5-28·6] in Viet Nam). INTERPRETATION: NAMHS provides the first national adolescent mental disorders prevalence estimates for Kenya, Indonesia, and Viet Nam. These data can inform mental health and broader health policies in low-income and middle-income countries. FUNDING: The University of Queensland in America (TUQIA) through support from Pivotal Ventures, a Melinda French Gates company.

Correlates of mental disorder and harmful substance use in an indigenous Australian urban sample: an analysis of data from the Queensland Urban Indigenous Mental Health Survey.

PURPOSE: Limited data exists on the relationship between sociodemographic and cultural variables and the prevalence of specific mental and substance use disorders (MSDs) among Indigenous Australians, using diagnostic prevalence data. This paper utilises data from the Queensland Urban Indigenous Mental Health Survey (QUIMHS), a population-level diagnostic mental health survey, to identify socioeconomic and cultural correlates of psychological distress and specific MSDs in an urban Indigenous Australian sample. METHODS: Using a mixture of household sampling (door-knocking) and snowball sampling (promotion of the survey in the community), 406 participants aged 18 to 89 were recruited across key locations in Southeast Queensland. The study investigated various demographic, socioeconomic, and cultural factors as predictors of psychological distress (measured by the Kessler-5) and MSD diagnoses (utilising the Composite International Diagnostic Interview, CIDI 3.0) using a series of univariate logistic regressions. RESULTS: Individuals in unstable housing (homeless, sleeping rough) and those reporting financial distress were more likely to experience an MSD in the past 12 months and throughout their lifetime. Individuals reporting lower levels of connection and belonging, limited participation in cultural events, and lower empowerment were more likely to have a lifetime mental disorder. CONCLUSION: This data emphasises the importance of addressing systemic and social determinants of health when designing and delivering community mental health services and underscores the need for holistic approaches when working with Indigenous communities.

Association between Mental Disorders and Subsequent Medical Conditions.

BACKGROUND: Persons with mental disorders are at a higher risk than the general population for the subsequent development of certain medical conditions. METHODS: We used a population-based cohort from Danish national registries that included data on more than 5.9 million persons born in Denmark from 1900 through 2015 and followed them from 2000 through 2016, for a total of 83.9 million person-years. We assessed 10 broad types of mental disorders and 9 broad categories of medical conditions (which encompassed 31 specific conditions). We used Cox regression models to calculate overall hazard ratios and time-dependent hazard ratios for pairs of mental disorders and medical conditions, after adjustment for age, sex, calendar time, and previous mental disorders. Absolute risks were estimated with the use of competing-risks survival analyses. RESULTS: A total of 698,874 of 5,940,299 persons (11.8%) were identified as having a mental disorder. The median age of the total population was 32.1 years at entry into the cohort and 48.7 years at the time of the last follow-up. Persons with a mental disorder had a higher risk than those without such disorders with respect to 76 of 90 pairs of mental disorders and medical conditions. The median hazard ratio for an association between a mental disorder and a medical condition was 1.37. The lowest hazard ratio was 0.82 for organic mental disorders and the broad category of cancer (95% confidence interval [CI], 0.80 to 0.84), and the highest was 3.62 for eating disorders and urogenital conditions (95% CI, 3.11 to 4.22). Several specific pairs showed a reduced risk (e.g., schizophrenia and musculoskeletal conditions). Risks varied according to the time since the diagnosis of a mental disorder. The absolute risk of a medical condition within 15 years after a mental disorder was diagnosed varied from 0.6% for a urogenital condition among persons with a developmental disorder to 54.1% for a circulatory disorder among those with an organic mental disorder. CONCLUSIONS: Most mental disorders were associated with an increased risk of a subsequent medical condition; hazard ratios ranged from 0.82 to 3.62 and varied according to the time since the diagnosis of the mental disorder. (Funded by the Danish National Research Foundation and others; COMO-GMC ClinicalTrials.gov number, NCT03847753.).

Diagnostic accuracy of the Composite International Diagnostic Interview (CIDI 3.0) in an urban Indigenous Australian sample.

OBJECTIVE: The Composite International Diagnostic Interview 3.0 is a standardised diagnostic interview commonly used in population-based mental health surveys, but has not been used in community-residing Indigenous Australians. This paper seeks to determine whether the Composite International Diagnostic Interview 3.0 can produce valid diagnostic information when compared with a diagnostic interview in an urban Indigenous Australian sample. METHOD: This research was conducted over 10 weeks with adult Indigenous clients of two participating Aboriginal Medical Services in South-East Queensland. Using a cross-sectional, repeated-measures design, participants were administered the Composite International Diagnostic Interview 3.0 by an Indigenous interviewer and within 2 weeks attended a second appointment with an Indigenous clinical psychologist, who produced a diagnostic summary. The Composite International Diagnostic Interview 3.0 diagnoses were compared with the diagnostic summaries and clinical concordance between the two measures was calculated. RESULTS: The diagnostic accuracy of the Composite International Diagnostic Interview 3.0 differed by module. The Post-traumatic Stress Disorder and Major Depression modules had good utility in diagnosing post-traumatic stress disorder and major depressive episodes, respectively; however, the Mania module that provides diagnoses of bipolar disorder was found to be unsuitable for this population. Although there were no identified contraindications for the use of the Generalised Anxiety and Alcohol Use Disorder modules, further research on the diagnostic accuracy of these modules is warranted. CONCLUSIONS: The Composite International Diagnostic Interview 3.0 can accurately diagnose some common mental disorders in an Indigenous Australian population, but was found to be unsuitable for others. Given these findings, care should be taken when using the Composite International Diagnostic Interview 3.0 in epidemiological prevalence studies with Indigenous Australian populations.

Mental health systems modelling for evidence-informed service reform in Australia.

Australia's Fifth National Mental Health Plan required governments to report, not only on the progress of changes to mental health service delivery, but to also plan for services that should be provided. Future population demand for treatment and care is challenging to predict and one solution involves modelling the uncertain demands on the system. Modelling can help decision-makers understand likely future changes in mental health service demand and more intelligently choose appropriate responses. It can also support greater scrutiny, accountability and transparency of these processes. Australia has an emerging national capacity for systems modelling in mental health which can enhance the next phase of mental health reform. This paper introduces concepts useful for understanding mental health modelling and identifies where modelling approaches can support health service planners to make evidence-informed decisions regarding planning and investment for the Australian population.

The global gap in treatment coverage for major depressive disorder in 84 countries from 2000-2019: A systematic review and Bayesian meta-regression analysis.

BACKGROUND: The treatment coverage for major depressive disorder (MDD) is low in many parts of the world despite MDD being a major contributor to disability globally. Most existing reviews of MDD treatment coverage do not account for potential sources of study-level heterogeneity that contribute to variation in reported treatment rates. This study aims to provide a comprehensive review of the evidence and analytically quantify sources of heterogeneity to report updated estimates of MDD treatment coverage and gaps by location and treatment type between 2000 and 2019. METHODS AND FINDINGS: A systematic review of the literature was conducted to identify relevant studies that provided data on treatment rates for MDD between January 1, 2000, and November 26, 2021, from 2 online scholarly databases PubMed and Embase. Cohort and cross-sectional studies were included if treatment rates pertaining to the last 12 months or less were reported directly or if sufficient information was available to calculate this along with 95% uncertainty intervals (UIs). Studies were included if they made use of population-based surveys that were representative of communities, countries, or regions under study. Studies were included if they used established diagnostic criteria to diagnose cases of MDD. Sample and methodological characteristics were extracted from selected studies. Treatment rates were modeled using a Bayesian meta-regression approach and adjusted for select covariates that quantified heterogeneity in the data. These covariates included age, sex, treatment type, location, and choice of MDD assessment tool. A total of 149 studies were included for quantitative analysis. Treatment coverage for health service use ranged from 51% [95% UI 20%, 82%] in high-income locations to 20% [95% UI 1%, 53%] in low- and lower middle-income locations. Treatment coverage for mental health service use ranged from 33% [95% UI 8%, 66%] in high-income locations to 8% [95% UI <1%, 36%] in low- and lower middle-income countries. Minimally adequate treatment (MAT) rates ranged from 23% [95% UI 2%, 55%] in high-income countries to 3% [95% UI <1%, 25%]) in low- and lower middle-income countries. A primary methodological limitation was the lack of sufficient data from low- and lower middle-income countries, which precluded our ability to provide more detailed treatment rate estimates. CONCLUSIONS: In this study, we observed that the treatment coverage for MDD continues to be low in many parts of the world and in particular in low- and lower middle-income countries. There is a continued need for routine data collection that will help obtain more accurate estimates of treatment coverage globally.

The Productivity Commission inquiry into mental health.

The report of the Productivity Commission Inquiry into mental health was released in November 2020, estimating the economic cost of mental illness in Australia at over $200 billion a year. The report makes wide-ranging recommendations for improving the mental health of the population, reforming the mental health treatment system, and in the way mental health is managed in other sectors of society.

Quantifying the size of the informal care sector for Australian adults with mental illness: caring hours and replacement cost.

PURPOSE: To quantify and value the total informal support provided by family and friends to Australian adults with mental illness in 2018. METHODS: The number of mental health carers was drawn from the 2015 Survey of Disability, Ageing and Carers (SDAC), adjusted to the 2018 population. Annual caring hours by type of assistance were estimated using the SDAC, 2007 National Survey of Mental Health and Wellbeing and an online carer survey. Caring hours for each task were assigned an hourly replacement cost from the National Disability Insurance Scheme. Informal caring was valued as the sum of these costs minus expenditure on carer income support payments, estimating how much it would hypothetically cost governments to replace this care with formal support services. RESULTS: An estimated 354,000 (95% uncertainty interval (UI): 327,000-383,000) Australian mental health carers provided 186 million (95% UI: 159-215) hours of support in 2018. The estimated replacement cost was AU$8.4 billion (95% UI: 7.0-10.0), excluding AU$1.3 billion in income support. Univariate sensitivity analyses demonstrated that results were robust to variation in model inputs, with total caring hours the most influential parameter. Using an alternative estimate of mean caring hours, the replacement cost could be as high as AU$13.2 billion (95% UI: 11.2-15.4). CONCLUSION: Informal carers provide substantial support to people with mental illness, highlighting their important contribution to the mental health system and reinforcing the need for carer support services. Future valuation studies would benefit from refinement of available data collections, particularly on hours and types of care provided.

New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis.

BACKGROUND: Existing WHO estimates of the prevalence of mental disorders in emergency settings are more than a decade old and do not reflect modern methods to gather existing data and derive estimates. We sought to update WHO estimates for the prevalence of mental disorders in conflict-affected settings and calculate the burden per 1000 population. METHODS: In this systematic review and meta-analysis, we updated a previous systematic review by searching MEDLINE (PubMed), PsycINFO, and Embase for studies published between Jan 1, 2000, and Aug 9, 2017, on the prevalence of depression, anxiety disorder, post-traumatic stress disorder, bipolar disorder, and schizophrenia. We also searched the grey literature, such as government reports, conference proceedings, and dissertations, to source additional data, and we searched datasets from existing literature reviews of the global prevalence of depression and anxiety and reference lists from the studies that were identified. We applied the Guidelines for Accurate and Transparent Health Estimates Reporting and used Bayesian meta-regression techniques that adjust for predictors of mental disorders to calculate new point prevalence estimates with 95% uncertainty intervals (UIs) in settings that had experienced conflict less than 10 years previously. FINDINGS: We estimated that the prevalence of mental disorders (depression, anxiety, post-traumatic stress disorder, bipolar disorder, and schizophrenia) was 22·1% (95% UI 18·8-25·7) at any point in time in the conflict-affected populations assessed. The mean comorbidity-adjusted, age-standardised point prevalence was 13·0% (95% UI 10·3-16·2) for mild forms of depression, anxiety, and post-traumatic stress disorder and 4·0% (95% UI 2·9-5·5) for moderate forms. The mean comorbidity-adjusted, age-standardised point prevalence for severe disorders (schizophrenia, bipolar disorder, severe depression, severe anxiety, and severe post-traumatic stress disorder) was 5·1% (95% UI 4·0-6·5). As only two studies provided epidemiological data for psychosis in conflict-affected populations, existing Global Burden of Disease Study estimates for schizophrenia and bipolar disorder were applied in these estimates for conflict-affected populations. INTERPRETATION: The burden of mental disorders is high in conflict-affected populations. Given the large numbers of people in need and the humanitarian imperative to reduce suffering, there is an urgent need to implement scalable mental health interventions to address this burden. FUNDING: WHO; Queensland Department of Health, Australia; and Bill & Melinda Gates Foundation.

A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study.

BACKGROUND: Systematic reviews have consistently shown that individuals with mental disorders have an increased risk of premature mortality. Traditionally, this evidence has been based on relative risks or crude estimates of reduced life expectancy. The aim of this study was to compile a comprehensive analysis of mortality-related health metrics associated with mental disorders, including sex-specific and age-specific mortality rate ratios (MRRs) and life-years lost (LYLs), a measure that takes into account age of onset of the disorder. METHODS: In this population-based cohort study, we included all people younger than 95 years of age who lived in Denmark at some point between Jan 1, 1995, and Dec 31, 2015. Information on mental disorders was obtained from the Danish Psychiatric Central Research Register and the date and cause of death was obtained from the Danish Register of Causes of Death. We classified mental disorders into ten groups and causes of death into 11 groups, which were further categorised into natural causes (deaths from diseases and medical conditions) and external causes (suicide, homicide, and accidents). For each specific mental disorder, we estimated MRRs using Poisson regression models, adjusting for sex, age, and calendar time, and excess LYLs (ie, difference in LYLs between people with a mental disorder and the general population) for all-cause mortality and for each specific cause of death. FINDINGS: 7 369 926 people were included in our analysis. We found that mortality rates were higher for people with a diagnosis of a mental disorder than for the general Danish population (28·70 deaths [95% CI 28·57-28·82] vs 12·95 deaths [12·93-12·98] per 1000 person-years). Additionally, all types of disorders were associated with higher mortality rates, with MRRs ranging from 1·92 (95% CI 1·91-1·94) for mood disorders to 3·91 (3·87-3·94) for substance use disorders. All types of mental disorders were associated with shorter life expectancies, with excess LYLs ranging from 5·42 years (95% CI 5·36-5·48) for organic disorders in females to 14·84 years (14·70-14·99) for substance use disorders in males. When we examined specific causes of death, we found that males with any type of mental disorder lost fewer years due to neoplasm-related deaths compared with the general population, although their cancer mortality rates were higher. INTERPRETATION: Mental disorders are associated with premature mortality. We provide a comprehensive analysis of mortality by different types of disorders, presenting both MRRs and premature mortality based on LYLs, displayed by age, sex, and cause of death. By providing accurate estimates of premature mortality, we reveal previously underappreciated features related to competing risks and specific causes of death. FUNDING: Danish National Research Foundation.

A systematic review of service models and evidence relating to the clinically operated community-based residential mental health rehabilitation for adults with severe and persisting mental illness in Australia.

BACKGROUND: Clinically operated community-based residential rehabilitation units (Community Rehabilitation Units) are resource intensive services supporting a small proportion of the people with severe and persisting mental illness who experience difficulties living in the community. Most consumers who engage with these services will be diagnosed with schizophrenia or a related disorder. This review seeks to: generate a typology of service models, describe the characteristics of the consumers accessing these services, and synthesise available evidence about consumers' service experiences and outcomes. METHOD: A systematic review was undertaken to identify studies describing Community Rehabilitation Units in Australia, consumer characteristics, and evidence about consumer experiences and outcomes. Search strings were applied to multiple databases; additional records were identified through snowballing. Records presenting unique empirical research were subject to quality appraisal. RESULTS: The typology defined two service types, Community-Based Residential Care (C-BRC), which emerged in the context of de-institutionalisation, and the more recent Transitional Residential Rehabilitation (TRR) approach. Key differentiating features were the focus on transitional care and 'recovery' under TRR. Schizophrenia spectrum disorders were the most common primary diagnosis under both service types. TRR consumers were more likely to be male, referred from community settings, and less likely to be subject to involuntary treatment. Regarding outcomes, the limited quantitative evidence (4 records, 2 poor quality) indicated C-BRC was successful in supporting the majority of consumers transferred from long-term inpatient care to remain out of hospital. All qualitative research conducted in C-BRC settings was assessed to be of poor quality (3 records). No methodologically sound quantitative evidence on the outcomes of TRR was identified. Qualitative research undertaken in these settings was of mixed quality (9 records), and the four records exploring consumer perspectives identified them as valuing the service provided. CONCLUSIONS: While there is qualitative evidence to suggest consumers value the support provided by Community Rehabilitation Units, there is an absence of methodologically sound quantitative research about the consumer outcomes achieved by these services. Given the ongoing and increasing investment in these facilities within the Australian context, there is an urgent need for high-quality research examining their efficiency and effectiveness. TRIAL REGISTRATION: PROSPERO ( CRD42018097326 ).

Hours of Care and Caring Tasks Performed by Australian Carers of Adults with Mental Illness: Results from an Online Survey.

The aim of this study was to provide a detailed profile of the hours of care Australian mental health carers provide for different types of caring tasks. The UQ Carer Survey 2016 was administered online to 105 adults caring for someone aged 16 years or older whose main condition is mental illness. Mental health carers reported providing on average 37.2 h of care per week to their main care recipient. Carers spent most of their active caring time providing emotional support, and the least of their time assisting with activities of daily living. Carers highlighted that this care time fluctuates with the undulating nature of mental illness, and many noted additional hours devoted to being 'on call' in case of emergency. Carers provide large amounts of support on a long-term and often unpredictable basis. Government services need to match the undulating nature of the illness by providing more flexible support options for mental health carers.

The prevalence and burden of mental and substance use disorders in Australia: Findings from the Global Burden of Disease Study 2015.

OBJECTIVES: Timely and accurate assessments of disease burden are essential for developing effective national health policies. We used the Global Burden of Disease Study 2015 to examine burden due to mental and substance use disorders in Australia. METHODS: For each of the 20 mental and substance use disorders included in Global Burden of Disease Study 2015, systematic reviews of epidemiological data were conducted, and data modelled using a Bayesian meta-regression tool to produce prevalence estimates by age, sex, geography and year. Prevalence for each disorder was then combined with a disorder-specific disability weight to give years lived with disability, as a measure of non-fatal burden. Fatal burden was measured as years of life lost due to premature mortality which were calculated by combining the number of deaths due to a disorder with the life expectancy remaining at the time of death. Disability-adjusted life years were calculated by summing years lived with disability and years of life lost to give a measure of total burden. Uncertainty was calculated around all burden estimates. RESULTS: Mental and substance use disorders were the leading cause of non-fatal burden in Australia in 2015, explaining 24.3% of total years lived with disability, and were the second leading cause of total burden, accounting for 14.6% of total disability-adjusted life years. There was no significant change in the age-standardised disability-adjusted life year rates for mental and substance use disorders from 1990 to 2015. CONCLUSION: Global Burden of Disease Study 2015 found that mental and substance use disorders were leading contributors to disease burden in Australia. Despite several decades of national reform, the burden of mental and substance use disorders remained largely unchanged between 1990 and 2015. To reduce this burden, effective population-level preventions strategies are required in addition to effective interventions of sufficient duration and coverage.

Implementing cognitive remediation and social cognitive interaction training into standard psychosis care.

BACKGROUND: To evaluate the planned implementation of group based Cognitive Remediation therapy (CR) and Social Cognitive Interaction Training (SCIT) into routine psychosis care in a mental health service in Australia. METHOD: The study was conducted over 3 years in a mental health service in a metropolitan city in Australia. Participants were 22 program facilitators and 128 patients attending the programs. Implementation outcomes were assessed using administrative data, staff surveys and program audits. RESULTS: There was fidelity to the particular therapies at a program level. Programs were assessed as being feasible within the study setting with each hospital district developing a capacity to run CR and SCIT. The establishment of new programs improved the reach, but waiting lists indicate a need to expand capacity. There was a relatively high dropout and several factors impacted on completion of the programs - notably, acute exacerbation of psychosis. Once initiated the therapies were acceptable with no-one ceasing SCIT due to loss of interest and only 10% of participants ceasing CR due to loss of interest. Annual audits of programs found programs established were maintained and facilitators were retained. CONCLUSION: SCIT and CR programs were successfully implemented in three hospital districts. Several factors impeded participants receiving the recommended "dose" of the programs. The maintenance of the programs in the short term is encouraging in regards to organisational fit. Dissemination of cognitive rehabilitation programs to a service population takes planning. An implementation plan is essential for guiding development and maintenance of programs. These therapies are best suited to people in a stable phase of illness. Service user co-production is recommended to improve recruitment in future studies.

The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States.

Introduction: Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective: To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting: A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures: Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results: Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance: There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.

Identifying characteristics and practices of multidisciplinary team reviews for patients with severe mental illness: a systematic review.

OBJECTIVES: Multidisciplinary teams in mental health receive limited guidance, leading to inconsistent practices. We undertook a systematic review of the characteristics and practices of multidisciplinary team reviews for patients with severe mental illness or in relevant mental health service settings. METHODS: Sources published since 2000 were located via academic database and web searches. Results were synthesised narratively. RESULTS: A total of 14 sources were analysed. Important characteristics and practices identified included routine monitoring and evaluation, good communication, equality between team members, and clear documentation practices. Success factors included defined leadership and clear team goals. Four sources described considerations for patients with complex clinical needs, including allocating sufficient time for discussion, maintaining connections with community providers, and ensuring culturally sensitive practices. CONCLUSIONS: No single best practice model was found, due to variations in team caseload, casemix, and resourcing levels. However, key ingredients for success were proposed. Sources were mostly descriptive; there remains a lack of evidence-based guidance regarding multidisciplinary team review characteristics and practices.

The burden of mental, neurological, and substance use disorders in China and India: a systematic analysis of community representative epidemiological studies.

BACKGROUND: China and India jointly account for 38% of the world population, so understanding the burden attributed to mental, neurological, and substance use disorders within these two countries is essential. As part of the Lancet/Lancet Psychiatry China-India Mental Health Alliance Series, we aim to provide estimates of the burden of mental, neurological, and substance use disorders for China and India from the Global Burden of Disease Study 2013 (GBD 2013). METHODS: In this systematic analysis for community representative epidemiological studies, we conducted systematic reviews in line with PRISMA guidelines for community representative epidemiological studies. We extracted estimates of prevalence, incidence, remission and duration, and mortality along with associated uncertainty intervals from GBD 2013. Using these data as primary inputs, DisMod-MR 2.0, a Bayesian meta-regression instrument, used a log rate and incidence-prevalence-mortality mathematical model to develop internally consistent epidemiological models. Disability-adjusted life-year (DALY) changes between 1990 and 2013 were decomposed to quantify change attributable to population growth and ageing. We projected DALYs from 2013 to 2025 for mental, neurological, and substance use disorders using United Nations population data. FINDINGS: Around a third of global DALYs attributable to mental, neurological, and substance use disorders were found in China and India (66 million DALYs), a number greater than all developed countries combined (50 million DALYs). Disease burden profiles differed; India showed similarities with other developing countries (around 50% of DALYs attributable to non-communicable disease), whereas China more closely resembled developed countries (around 80% of DALYs attributable to non-communicable disease). The overall population growth in India explains a greater proportion of the increase in mental, neurological, and substance use disorder burden from 1990 to 2013 (44%) than in China (20%). The burden of mental, neurological, and substance use disorders is estimated to increase by 10% in China and 23% in India between 2013 and 2025. INTERPRETATION: The current and projected burden of mental, neurological, and substance use disorders in China and India warrants the urgent prioritisation of programmes focused on targeted prevention, early identification, and effective treatment. FUNDING: China Medical Board, Bill & Melinda Gates Foundation.

Addressing the burden of mental, neurological, and substance use disorders: key messages from Disease Control Priorities, 3rd edition.

The burden of mental, neurological, and substance use (MNS) disorders increased by 41% between 1990 and 2010 and now accounts for one in every 10 lost years of health globally. This sobering statistic does not take into account the substantial excess mortality associated with these disorders or the social and economic consequences of MNS disorders on affected persons, their caregivers, and society. A wide variety of effective interventions, including drugs, psychological treatments, and social interventions, can prevent and treat MNS disorders. At the population-level platform of service delivery, best practices include legislative measures to restrict access to means of self-harm or suicide and to reduce the availability of and demand for alcohol. At the community-level platform, best practices include life-skills training in schools to build social and emotional competencies. At the health-care-level platform, we identify three delivery channels. Two of these delivery channels are especially relevant from a public health perspective: self-management (eg, web-based psychological therapy for depression and anxiety disorders) and primary care and community outreach (eg, non-specialist health worker delivering psychological and pharmacological management of selected disorders). The third delivery channel, hospital care, which includes specialist services for MNS disorders and first-level hospitals providing other types of services (such as general medicine, HIV, or paediatric care), play an important part for a smaller proportion of cases with severe, refractory, or emergency presentations and for the integration of mental health care in other health-care channels, respectively. The costs of providing a significantly scaled up package of specified cost-effective interventions for prioritised MNS disorders in low-income and lower-middle-income countries is estimated at US$3-4 per head of population per year. Since a substantial proportion of MNS disorders run a chronic and disabling course and adversely affect household welfare, intervention costs should largely be met by government through increased resource allocation and financial protection measures (rather than leaving households to pay out-of-pocket). Moreover, a policy of moving towards universal public finance can also be expected to lead to a far more equitable allocation of public health resources across income groups. Despite this evidence, less than 1% of development assistance for health and government spending on health in low-income and middle-income countries is allocated to the care of people with these disorders. Achieving the health gains associated with prioritised interventions will require not just financial resources, but committed and sustained efforts to address a range of other barriers (such as paucity of human resources, weak governance, and stigma). Ultimately, the goal is to massively increase opportunities for people with MNS disorders to access services without the prospect of discrimination or impoverishment and with the hope of attaining optimal health and social outcomes.

Key factors that influence government policies and decision making about healthcare priorities: Lessons for the field of eating disorders.

Worldwide, the demand for healthcare exceeds what individuals and governments are able to afford. Priority setting is therefore inevitable, and mental health services have often been given low priority in the decision-making process. Drawing on established economic criteria, and specifically the work of Philip Musgrove, key factors which influence government decision-making about health priorities are reviewed. These factors include the size of the health burden, the availability of cost-effective interventions to reduce the burden, whether private markets can provide the necessary treatment efficiently, whether there are "catastrophic costs" incurred in accessing treatment, whether negative externalities arise from not providing care, and if the "rule of rescue" applies. Beyond setting priorities for resource allocation, governments also become involved where there is a need for regulation to maintain quality in the delivery of healthcare. By providing field-specific examples for each factor, we illustrate how advocates in the eating disorder field may use evidence to inform government policy about resource allocation and regulation in support of individuals with an eating disorder.