ABSTRACT
BACKGROUND: Quantifying diagnostic transitions across development is needed to estimate the long-term burden of mental illness. This study estimated patterns of diagnostic transitions from childhood to adolescence and from adolescence to early adulthood. METHODS: Patterns of diagnostic transitions were estimated using data from three prospective, longitudinal studies involving close to 20,000 observations of 3,722 participants followed across multiple developmental periods covering ages 9-30. Common DSM psychiatric disorders were assessed in childhood (ages 9-12; two samples), adolescence (ages 13-18; three samples), and early adulthood (ages 19 to age 32; three samples) with structured psychiatric interviews and questionnaires. RESULTS: Having a disorder at an early period was associated with at least a threefold increase in odds for having a disorder at a later period. Homotypic and heterotypic transitions were observed for every disorder category. The strongest evidence of continuity was seen for behavioral disorders (particularly ADHD) with less evidence for emotional disorders such as depression and anxiety. Limited evidence was found in adjusted models for behavioral disorders predicting later emotional disorders. Adult substance disorders were preceded by behavioral disorders, but not anxiety or depression. CONCLUSIONS: Having a disorder in childhood or adolescence is a potent risk factor for a range of psychiatric problems later in development. These findings provide further support for prevention and early life intervention efforts and suggest that treatment at younger ages, while justified in its own right, may also have potential to reduce the risk for disorders later in development.
Subject(s)
Mental Disorders/diagnosis , Mental Disorders/epidemiology , Adolescent , Adult , Age Factors , Anxiety Disorders/diagnosis , Anxiety Disorders/epidemiology , Anxiety Disorders/psychology , Attention Deficit Disorder with Hyperactivity/diagnosis , Attention Deficit Disorder with Hyperactivity/epidemiology , Attention Deficit Disorder with Hyperactivity/psychology , Child , Child Behavior Disorders/diagnosis , Child Behavior Disorders/epidemiology , Child Behavior Disorders/psychology , Cross-Sectional Studies , Depressive Disorder/diagnosis , Depressive Disorder/epidemiology , Depressive Disorder/psychology , Female , Health Surveys , Humans , Incidence , Interview, Psychological , Longitudinal Studies , Male , Mental Disorders/psychology , New Zealand , Odds Ratio , Prospective Studies , Risk Factors , Surveys and Questionnaires , Young AdultABSTRACT
OBJECTIVE: Prevalence estimates for mood and anxiety disorders in Canada are available, but various methodological approaches have produced inconsistent results. Simulation studies involve careful examination of available data by an expert modelling team working together with subject matter experts. Simulation can integrate datasets and literature-based estimates from various sources into a coherent mathematical representation of the underlying total population epidemiology. METHODS: Supported by the Mental Health Commission of Canada, a simulation modelling project for mental disorders in Canada was recently undertaken. The modelling was carried out by RiskAnalytica using their Life at Risk platform. Specification and calibration of the model occurred in consultation with national and international experts. RESULTS: To reconcile estimates of incidence and prevalence, recall bias needed to be represented in the model. This suggests that the population prevalence of mood and anxiety disorders has been underestimated by population surveys and may explain a discrepancy observed in the age-specific prevalence in population surveys as compared with studies using administrative data. The number of Canadians with mood and anxiety disorders is projected to increase in upcoming decades as a result of population growth, but, based on conservative assumptions, an increased prevalence proportion is not anticipated. CONCLUSIONS: Simulation models can act as a platform for economic analyses and epidemiologic projections and can support the rapid exploration of what-if scenarios, thereby informing policy decisions. This first national-level simulation provides a high level overview of mood and anxiety disorder epidemiology in Canada.
Subject(s)
Anxiety Disorders/epidemiology , Models, Statistical , Mood Disorders/epidemiology , Canada/epidemiology , Epidemiologic Methods , Humans , Incidence , PrevalenceABSTRACT
OBJECTIVE: To investigate the possibility of pediatric intensive care unit shortfalls, using pandemic models for a range of attack rates and durations. The emergence of the swine origin pH1N1 virus has led to concerns about shortfalls in our ability to provide pediatric ventilation and critical care support. DESIGN: Modeling of pediatric intensive care demand based on pH1N1 predictions using simulation techniques. SETTING: Simulation laboratory. PATIENTS: None. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data collected during the first wave of the pH1N1 in children in Canada were applied to several second wave pandemic models to explore potential pediatric intensive care unit ventilatory demands for Canada and to investigate the impact of vaccination upon these demands. In almost all cases studied, even for relatively low attack rates of 15%, significant pediatric intensive care unit shortages would be expected to occur. Vaccination strategies targeting 50% of the population significantly reduced demand, but shortages may still be expected. Although shortfalls can occur in all provinces, Ontario and British Columbia may experience the greatest supply-demand difference, even at low attack rates. CONCLUSION: Reducing the attack rate among children, whether through vaccination or additional measures, such as social distancing, will be critical to ensure sufficient pediatric intensive care unit capacity for continued pediatric care.
Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza, Human/epidemiology , Intensive Care Units, Pediatric/statistics & numerical data , Pandemics , Surge Capacity , Adolescent , Adult , Aged , Canada/epidemiology , Child , Child, Preschool , Health Services Needs and Demand/statistics & numerical data , Humans , Infant , Infant, Newborn , Middle Aged , Models, Statistical , Surge Capacity/statistics & numerical data , Vaccination , Young AdultABSTRACT
PURPOSE: To investigate the ability of Canadian intensive care units (ICUs) and ventilators to handle widespread re-emergence of the swine-origin H1N1 virus in the context of an aggressive strategy of vaccination. METHOD: Data collected during the first wave in Winnipeg, Manitoba, were applied to a variety of second wave pandemic models to determine potential ICU and ventilator demand. RESULTS: For attack rates greater than 20% to 25%, significant shortages in ventilators may be expected across Canada regardless of the duration of the pandemic if vaccination is not considered. The shortfall arises largely due to the extended durations that patients must remain on ventilation. From the Winnipeg study, 50% of patients required ventilation for more than two weeks. For larger attack rates of 35%, ventilator demand may exceed capacity for over five weeks, with a peak shortfall of 700 ventilators. Vaccination can significantly reduce the attack rates, and is expected to reduce ventilator demand to manageable levels CONCLUSION: Canada's health care system must be prepared for the possibility of a significant influx of ICU patients during the second wave of swine-origin H1N1. Efficient vaccination and other disease prevention measures can reduce the attack rate to manageable levels.
