Do community treatment orders for mental illness reduce readmission to hospital? - An epidemiological study

Background It has been suggested that community treatment orders (CTOs) will prevent readmission to hospital, but controlled studies have been inconclusive. We aimed to test the hypothesis that hospital discharges made subject to CTOs are associated with a reduced risk of readmission. The use of such a measure is likely to change after its introduction as clinicians acquire familiarity with it, and we also tested the hypothesis that the characteristics of patients subject to CTOs changed over time in the first decade of their use in Victoria, Australia. Method A database from Victoria, Australia (total population 4.8 million) was used. Cox proportional hazard models compared the hazard ratios of readmission to hospital before the end of the study period (1992-2000) for 16,216 discharges subject to a CTO and 112,211 not subject to a CTO. Results Community treatment orders used on discharge from a first admission to hospital were associated with a higher risk of readmission, but CTOs following subsequent admissions were associated with lower readmission risk. The risk also declined over the study period. Conclusions The effect of using a CTO depends on the patient's history. At a population level their introduction may not reduce readmission to hospital. Their impact may change over time.

The properties of the International Classification of the External Cause of Injury when used as an instrument for injury prevention research

Objective: To demonstrate properties of the International Classification of the External Cause of Injury (ICECI) as a tool for use in injury prevention research. Methods: The Childhood Injury Prevention Study (CHIPS) is a prospective longitudinal follow up study of a cohort of 871 children 5 - 12 years of age, with a nested case crossover component. The ICECI is the latest tool in the International Classification of Diseases (ICD) family and has been designed to improve the precision of coding injury events. The details of all injury events recorded in the study, as well as all measured injury related exposures, were coded using the ICECI. This paper reports a substudy on the utility and practicability of using the ICECI in the CHIPS to record exposures. Interrater reliability was quantified for a sample of injured participants using the Kappa statistic to measure concordance between codes independently coded by two research staff. Results: There were 767 diaries collected at baseline and event details from 563 injuries and exposure details from injury crossover periods. There were no event, location, or activity details which could not be coded using the ICECI. Kappa statistics for concordance between raters within each of the dimensions ranged from 0.31 to 0.93 for the injury events and 0.94 and 0.97 for activity and location in the control periods. Discussion: This study represents the first detailed account of the properties of the ICECI revealed by its use in a primary analytic epidemiological study of injury prevention. The results of this study provide considerable support for the ICECI and its further use.

A study of the lagged relationships among safety climate, safety motivation, safety behavior, and accidents at the individual and group levels

The authors measured perceptions of safety climate, motivation, and behavior at 2 time points and linked them to prior and subsequent levels of accidents over a 5-year period. A series of analyses examined the effects of top-down and bottom-up processes operating simultaneously over time. In terms of top-down effects, average levels of safety climate within groups at I point in time predicted subsequent changes in individual safety motivation. Individual safety motivation, in turn, was associated with subsequent changes in self-reported safety behavior. In terms of bottom-up effects, improvements in the average level of safety behavior within groups were associated with a subsequent reduction in accidents at the group level. The results contribute to an understanding of the factors influencing workplace safety and the levels and lags at which these effects operate.

Measuring the global burden of disease and epidemiological transitions: 2002-2030

Any planning process for health development ought to be based on a thorough understanding of the health needs of the population. This should be sufficiently comprehensive to include the causes of premature death and of disability, as well as the major risk factors that underlie disease and injury. To be truly useful to inform health-policy debates, such an assessment is needed across a large number of diseases, injuries and risk factors, in order to guide prioritization. The results of the original Global Burden of Disease Study and, particularly, those of its 2000-2002 update provide a conceptual and methodological framework to quantify and compare the health of populations using a summary measure of both mortality and disability: the disability-adjusted life-year (DALY). Globally, it appears that about 5 6 million deaths occur each year, 10. 5 million (almost all in poor countries) in children. Of the child deaths, about one-fifth result from perinatal causes such as birth asphyxia and birth trauma, and only slightly less from lower respiratory infections. Annually, diarrhoeal diseases kill over 1.5 million children, and malaria, measles and HIV/AIDS each claim between 500,000 and 800,000 children. HIV/AIDS is the fourth leading cause of death world-wide (2.9 million deaths) and the leading cause in Africa. The top three causes of death globally are ischaemic heart disease (7.2 million deaths), stroke (5.5 million) and lower respiratory diseases (3.9 million). Chronic obstructive lung diseases (COPD) cause almost as many deaths as HIV/AIDS (2.7 million). The leading causes of DALY, on the other hand, include causes that are common at young ages [perinatal conditions (7. 1 % of global DALY), lower respiratory infections (6.7%), and diarrhoeal diseases (4.7%)] as well as depression (4.1%). Ischaemic heart disease and stroke rank sixth and seventh, retrospectively, as causes of global disease burden, followed by road traffic accidents, malaria and tuberculosis. Projections to 2030 indicate that, although these major vascular diseases will remain leading causes of global disease burden, with HIV/AIDS the leading cause, diarrhoeal diseases and lower respiratory infections will be outranked by COPD, in part reflecting the projected increases in death and disability from tobacco use.

Multiple imputation for body mass index: lessons from the Australian Longitudinal Study on Women's Health

In large epidemiological studies missing data can be a problem, especially if information is sought on a sensitive topic or when a composite measure is calculated from several variables each affected by missing values. Multiple imputation is the method of choice for 'filling in' missing data based on associations among variables. Using an example about body mass index from the Australian Longitudinal Study on Women's Health, we identify a subset of variables that are particularly useful for imputing values for the target variables. Then we illustrate two uses of multiple imputation. The first is to examine and correct for bias when data are not missing completely at random. The second is to impute missing values for an important covariate; in this case omission from the imputation process of variables to be used in the analysis may introduce bias. We conclude with several recommendations for handling issues of missing data. Copyright (C) 2004 John Wiley Sons, Ltd.

Epidemiology of recreational exposure to freshwater cyanobacteria - an international prospective cohort study

Background: Case studies and anecdotal reports have documented a range of acute illnesses associated with exposure to cyanobacteria and their toxins in recreational waters. The epidemiological data to date are limited; we sought to improve on the design of some previously conducted studies in order to facilitate revision and refinement of guidelines for exposure to cyanobacteria in recreational waters. Methods: A prospective cohort study was conducted to investigate the incidence of acute symptoms in individuals exposed, through recreational activities, to low ( cell surface area < 2.4 mm(2)/mL), medium ( 2.4 - 12.0 mm(2)/mL) and high (> 12.0 mm(2)/mL) levels of cyanobacteria in lakes and rivers in southeast Queensland, the central coast area of New South Wales, and northeast and central Florida. Multivariable logistic regression analyses were employed; models adjusted for region, age, smoking, prior history of asthma, hay fever or skin disease ( eczema or dermatitis) and clustering by household. Results: Of individuals approached, 3,595 met the eligibility criteria, 3,193 (89%) agreed to participate and 1,331 (37%) completed both the questionnaire and follow-up interview. Respiratory symptoms were 2.1 (95% CI: 1.1 - 4.0) times more likely to be reported by subjects exposed to high levels of cyanobacteria than by those exposed to low levels. Similarly, when grouping all reported symptoms, individuals exposed to high levels of cyanobacteria were 1.7 ( 95% CI: 1.0 - 2.8) times more likely to report symptoms than their low-level cyanobacteria-exposed counterparts. Conclusion: A significant increase in reporting of minor self-limiting symptoms, particularly respiratory symptoms, was associated with exposure to higher levels of cyanobacteria of mixed genera. We suggest that exposure to cyanobacteria based on total cell surface area above 12 mm(2)/mL could result in increased incidence of symptoms. The potential for severe, life-threatening cyanobacteria-related illness is likely to be greater in recreational waters that have significant levels of cyanobacterial toxins, so future epidemiological investigations should be directed towards recreational exposure to cyanotoxins.

Using epidemiological models to estimate the health effects of diet behaviour change: the example of tailored fruit and vegetable promotion

Objective: To explore the use of epidemiological modelling for the estimation of health effects of behaviour change interventions, using the example of computer-tailored nutrition education aimed at fruit and vegetable consumption in The Netherlands. Design: The effects of the intervention on changes in consumption were obtained from an earlier evaluation study. The effect on health outcomes was estimated using an epidemiological multi-state life table model. input data for the model consisted of relative risk estimates for cardiovascular disease and cancers, data on disease occurrence and mortality, and survey data on the consumption of fruits and vegetables. Results: if the computer-tailored nutrition education reached the entire adult population and the effects were sustained, it could result in a mortality decrease of 0.4 to 0.7% and save 72 to 115 life-years per 100000 persons aged 25 years or older. Healthy life expectancy is estimated to increase by 32.7 days for men and 25.3 days for women. The true effect is likely to lie between this theoretical maximum and zero effect, depending mostly on durability of behaviour change and reach of the intervention. Conclusion: Epidemiological models can be used to estimate the health impact of health promotion interventions.