Ecological regression analysis of environmental benzene exposure and childhood leukaemia: sensitivity to data inaccuracies, geographical scale and ecological bias

Benzene is classified as a group 1 human carcinogen by the International Agency for Research on Cancer, and it is now accepted that occupational exposure is associated with an increased risk of various leukaemias. However, occupational exposure accounts for less than 1% of all benzene exposures, the major sources being cigarette smoking and vehicle exhaust emissions. Whether such low level exposures to environmental benzene are also associated with the risk of leukaemia is currently not known. In this study, we investigate the relationship between benzene emissions arising from outdoor sources (predominantly road traffic and petrol stations) and the incidence of childhood leukaemia in Greater London. An ecological design was used because of the rarity of the disease, the difficulty of obtaining individual level measurements of benzene exposure and the availability of data. However, some methodological difficulties were encountered, including problems of case registration errors, the choice of geographical areas for analysis, exposure measurement errors and ecological bias. We use a Bayesian hierarchical modelling framework to address these issues, and we investigate the sensitivity of our inference to various modelling assumptions.     

流行病疫情预测评估模型探讨

基于我国2003年新闻媒体公开发表的有关SARS确诊病例、疑似病例和死亡病例等的实际数据,建立有关流行病疫情严重程度、控制效果等方面的评估模型是本研究的目的。探讨了经典的流行病微分模型,建立了基于统计学的时序全局主成分分析模型。模型能比较好的与实际吻合,并能运用于与相类似于SARS的流行病的疫情预测评估。     

Perspectives on Incorporating Human Neurobehavioral End Points in Risk Assessments

Three topics are addressed: (1) measurement issues (e.g., the reliability and validity of neurobehavioral test scores), (2) general principles of assessment, including test selection, and (3) interpretation of scores. Psychological tests generally perform as well as medical tests in terms of reliability and validity. Test manuals, assessment textbooks, and psychologists are useful resources to the risk assessor. The variety of different tests employed in neurobehavioral studies complicates interstudy comparisons. In addition, tests that ostensibly assess the same general domain of function might assess somewhat different abilities within that domain. Although a uniform battery for use in all studies seems desirable, the battery appropriate for a specific study depends on study goals, knowledge about the mechanism(s) of neurotoxicity, nature of the study population, and pattern of exposure. Exposure-related neurobehavioral deficits are generally indicators of "altered function" rather than of "clinical disease." Limiting concern to end points corresponding to clinical disease might not be appropriate. Many neurobehavioral diagnoses are phenomenological and a neurotoxicant might cause a unique pattern of deficits for which no label has been created. The concern that a small shift in the central tendency of a distribution of test scores has no significance for the individual should be reexamined in light of the prevention paradox, formulated on the basis of epidemiologic studies of chronic disease. Poor performance on a neurobehavioral test does not necessarily map clearly onto underlying behavioral or neural substrate. The absence of such linkages, given current knowledge about brain-behavior relationships, should not reduce confidence in neurobehavioral end points. Use of neurobehavioral test scores involves considerations that differ little from those that the risk assessor routinely addresses in using end points commonly used in research on other topics in environmental epidemiology.     

Exposure-Response Functions for Health Effects of Air Pollutants Based on Epidemiological Findings

Quantitative knowledge about health damage due to air pollution is an important element in analyses of cost-effective abatement strategies, and is also essential for setting Air Quality Standards. Epidemiological studies, in spite of the numerous problems connected to them, provide a reasonable basis for exposure-response functions in this context. On the basis of a literature review, exposure-response functions that relate ambient air pollutant concentrations to the frequency of various health effects are recommended in this paper. The following end-points were examined: Acute and chronic respiratory symptoms in children and adults, crude mortality, and lung cancer incidence. The effects are attributed to one indicator component, which in most cases is particles. A calculation procedure is suggested which makes it possible to estimate excess annual symptom-days for short-term effects using the annual average concentration.     

The U.S. EPA Geographic Information System for Mapping Environmental Releases of Toxic Chemical Release Inventory (TRI) Chemicals

This study characterizes the environmental releases of toxic chemicals of the Toxic Chemical Release Inventory (TRI) in the southeastern United States by using the U.S. Environmental Protection Agency (EPA) Geographic Information System (GIS) to map them. These maps show that the largest quantities of TRI releases in the Southeast are usually near densely populated areas. This GIS mapping approach takes the first steps in defining those areas in the region which may be potential exposure zones and which could be strategic targets for future risk screening efforts in this geographic area.     

Unintentional injury: A major health problem for young children and youth

This article reviews data on childhood injury and explains how unintentional injuries have become the leading health problem for young children in the United States and a major health problem in teenage years. The article discusses the major types of childhood injuries, trends over time, and variations by location and social, behavioral, and familial risk factors. Results of epidemiological and sociobehavioral research on injury are followed by a discussion of policy considerations in the attempts to deal with childhood injury and its consequences. This includes a discussion of major ways to prevent injuries, a review of government activities, and recommendations for future efforts. Her research interests include child safety, preventive health behaviors, access to health care services, and health policy. She received her Ph.D. from Brown University in sociology in 1976. Her research interests include child safety, preventive health behavior, international health, and alternative health care models. She received her D.Sc. from Johns Hopkins University in 1985.     

Multilevel modelling of the geographical distributions of diseases

Multilevel modelling is used on problems arising from the analysis of spatially distributed health data. We use three applications to demonstrate the use of multilevel modelling in this area. The first concerns small area all-cause mortality rates from Glasgow where spatial autocorrelation between residuals is examined. The second analysis is of prostate cancer cases in Scottish counties where we use a range of models to examine whether the incidence is higher in more rural areas. The third develops a multiple-cause model in which deaths from cancer and cardiovascular disease in Glasgow are examined simultaneously in a spatial model. We discuss some of the issues surrounding the use of complex spatial models and the potential for future developments.     

“I Caught It at the Movies”: Reflections on Medical History,Movie Theaters,and the Cinema of Contagion

ABSTRACT

Undertaking an examination of the precarious places of the movies and movie theaters in queer lives in the 20th century, this article takes up a series of anecdotal episodes and feature-length films to consider how the space-related stakes of LGBT health have been best understood in literal cinema houses and the narrative cinema projections inside of them. The author argues for an appreciation of LGBT-themed motion pictures as oscillating between perpetuator of queer pathology and its potential solution.     

Study Design in Causal Models

The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing‐data mechanism together with the causal structure and allow the direct application of causal calculus in the estimation of the causal effects. The flow of the study is visualized by ordering the nodes of the causal diagram in two dimensions by their causal order and the time of the observation. Conclusions on whether a causal or observational relationship can be estimated from the collected incomplete data can be made directly from the graph. Causal models with design offer a systematic and unifying view to scientific inference and increase the clarity and speed of communication. Examples on the causal models for a case–control study, a nested case–control study, a clinical trial and a two‐stage case–cohort study are presented.