Epidemiologic Evidence for Chloroprene Carcinogenicity: Review of Study Quality and its Application to Risk Assessment

This article evaluates the quality and weight of evidence associated with epidemiologic studies of cancer among occupational cohorts exposed to chloroprene. The focus is on liver, lung, and lymphohematopoietic cancers, which had been increased in early studies. Literature searches identified eight morbidity/mortality studies covering seven chloroprene-exposed cohorts from six countries. These studies were summarized and their quality was assessed using the 10 criteria suggested by the U.S. Environmental Protection Agency. The limitations within this literature (primarily the early studies) included crude exposure assessment, incomplete follow-up, uncertain baseline rates, and uncontrolled confounding by factors such as smoking, drinking, and co-exposure to benzene and vinyl chloride. Four cohorts were studied by the same group of investigators, who reported no overall increased associations for any cancers. This four-cohort study was by far the most rigorous, having the most comprehensive exposure assessment and follow-up and the most detailed documentation. This study also contained the two largest cohorts, including an American cohort from Louisville, Kentucky, that ranked at or near the top for each of the 10 quality criteria. There was evidence of a strong healthy worker effect in the four-cohort study, which could have hidden small excess risks. Small increased risks were suggested by internal or company-specific analyses, but these were most likely caused by uncontrolled confounding and low baseline rates. Overall, the weight of evidence does not support any substantial link between chloroprene exposure and cancer, but inconsistencies and a lack of control for major confounders preclude drawing firmer conclusions.     

Some applications of lagrangian distributions in queueing theory and epidemiology

In this note we demonstrate that the Lagrangian distributions have applications in queueing theory and theory of epidemics. The Lagrangian distribution appears as the distribution describing the number of customers served in a busy period under certain conditions. Also, the Lagrangian distribution describes the distribution of number of persons infected by a certain infectious disease.     

A new approach to investigating spatial variations of disease

Summary.  For rare diseases the observed disease count may exhibit extra Poisson variability, particularly in areas with low or sparse populations. Hence the variance of the estimates of disease risk, the standardized mortality ratios, may be highly unstable. This overdispersion must be taken into account otherwise subsequent maps based on standardized mortality ratios will be misleading and, rather than displaying the true spatial pattern of disease risk, the most extreme values will be highlighted. Neighbouring areas tend to exhibit spatial correlation as they may share more similarities than non-neighbouring areas. The need to address overdispersion and spatial correlation has led to the proposal of Bayesian approaches for smoothing estimates of disease risk. We propose a new model for investigating the spatial variation of disease risks in conjunction with an alternative specification for estimates of disease risk in geographical areas—the multivariate Poisson–gamma model. The main advantages of this new model lie in its simplicity and ability to account naturally for overdispersion and spatial auto-correlation. Exact expressions for important quantities such as expectations, variances and covariances can be easily derived.     

Inclusion of Dietary Evaluation in Cardiovascular Disease Risk Prediction Models Increases Accuracy and Reduces Bias of the Estimations

In the past few years, the prediction of CVD risk has received special attention; however, some investigators assert that risk models have so far not been very successful. Thus, we examined whether the inclusion of dietary evaluation in a risk prediction model that already contained the classical CVD risk factors increases the accuracy and reduces the bias in estimating future CVD events. The database of the ATTICA study (which included information from 1,514 men and 1,528 women) was used. At baseline, the HellenicSCORE values (based on age, gender, smoking, systolic blood pressure, and total cholesterol) were calculated, while overall assessment of dietary habits was based on the Mediterranean diet score (MDS) that evaluates adherence to this traditional diet. In 2006, a five-year follow-up was performed in 2,101 participants and development of CVD (coronary heart disease, acute coronary syndromes, stroke, or other CVD) was defined according to WHO-ICD-10 criteria. The MDS and the HellenicSCORE were significant predictors of CVD events, even after adjusting for various potential confounders ( p < 0.05). However, estimating bias (i.e., misclassification of cases) of the model that included HellenicSCORE and other potential confounders was 8.7%. The MDS was associated with the estimating bias of the outcome ( p < 0.001) and explained 5.5% of this bias. Other baseline factors associated with bias were increased body mass index, low education status, and increased energy intake/BMR ratio. The inclusion of dietary evaluation, as well as other Sociodemographic and anthropometric characteristics, increases the accuracy and reduces estimating bias of CVD risk prediction models.     

Spatio‐temporal modelling of disease mapping of rates

This paper studies generalized linear mixed models (GLMMs) for the analysis of geographic and temporal variability of disease rates. This class of models adopts spatially correlated random effects and random temporal components. Spatio‐temporal models that use conditional autoregressive smoothing across the spatial dimension and autoregressive smoothing over the temporal dimension are developed. The model also accommodates the interaction between space and time. However, the effect of seasonal factors has not been previously addressed and in some applications (e.g., health conditions), these effects may not be negligible. The authors incorporate the seasonal effects of month and possibly year as part of the proposed model and estimate model parameters through generalized estimating equations. The model provides smoothed maps of disease risk and eliminates the instability of estimates in low‐population areas while maintaining geographic resolution. They illustrate the approach using a monthly data set of the number of asthma presentations made by children to Emergency Departments (EDs) in the province of Alberta, Canada, during the period 2001–2004. The Canadian Journal of Statistics 38: 698–715; 2010 © 2010 Statistical Society of Canada     

Cancer Dose-Response Modeling of Epidemiological Data on Worker Exposures to Aldrin and Dieldrin

The paper applies classical statistical principles to yield new tools for risk assessment and makes new use of epidemiological data for human risk assessment. An extensive clinical and epidemiological study of workers engaged in the manufacturing and formulation of aldrin and dieldrin provides occupational hygiene and biological monitoring data on individual exposures over the years of employment and provides unusually accurate measures of individual lifetime average daily doses. In the cancer dose-response modeling, each worker is treated as a separate experimental unit with his own unique dose. Maximum likelihood estimates of added cancer risk are calculated for multistage, multistage-Weibull, and proportional hazards models. Distributional characterizations of added cancer risk are based on bootstrap and relative likelihood techniques. The cancer mortality data on these male workers suggest that low-dose exposures to aldrin and dieldrin do not significantly increase human cancer risk and may even decrease the human hazard rate for all types of cancer combined at low doses (e.g., 1 g/kg/day). The apparent hormetic effect in the best fitting dose-response models for this data set is statistically significant. The decrease in cancer risk at low doses of aldrin and dieldrin is in sharp contrast to the U.S. Environmental Protection Agency's upper bound on cancer potency based on mouse liver tumors. The EPA's upper bound implies that lifetime average daily doses of 0.0000625 and 0.00625 g/kg body weight/day would correspond to increased cancer risks of 0.000001 and 0.0001, respectively. However, the best estimate from the Pernis epidemiological data is that there is no increase in cancer risk in these workers at these doses or even at doses as large as 2 g/kg/day.     

Gambling Participation and Social Support Among Older Adults: A Longitudinal Community Study

The purpose of this preliminary study was to examine associations between leaving home to engage in bingo or gambling activity and indices of physical and mental health and social support among a representative community cohort of 1016 elderly people. Cross-sectional and longitudinal data gathered from a prospective epidemiological study in a rural, low socio-economic status, area of Pennsylvania was employed. The cohort had a mean age of 78.8 (SD = 5.1) (range 71–97) and participated in three consecutive biennial waves of data collection. Nearly half (47.7) of the cohort reported gambling. To predict gambling, the independent variables included age, sex, education, employment, social support, depressive symptoms, self-rated health, alcohol use, cigarette use, and cognitive functioning. In cross-sectional, univariate analyses, gambling was associated with younger age, sex (male), fewer years of education, greater social support, lower depression scores, better self-rated health, alcohol use in the past year, and higher cognitive functioning. In a cross-sectional multiple regression model, younger age, greater social support, and alcohol use in the past year remain strongly and independently associated with gambling activity. Longitudinally, age, sex, social support, alcohol use, and gambling are predictive of future gambling activity. The results revealed that gambling may offer a forum of social support to older adults who are often isolated as they age.     

相关差别指标的区间估计方法比较

在公共疾病控制领域,重大稀有疾病的发病率非常低,符合逆抽样特征,量化分析重大稀有疾病的发病率并对其特点进行分析,为了研究在带有群内相关条件下的整群抽样问题,通过β-二项分布抽样对比流行病学中相关差别指标的六种渐近置信区间的构造方法,综合考虑实际覆盖率与区间长度对各种方法的优劣及适用情况并对比分析。研究表明,Wald型置信区间与对数变换的置信区间对发病率的估计表现因参数而定,而Bootstrap类方法不稳定。本研究找出了不同区间估计方法的适用场合,认为应合理看待置信区间这种评估方法在流行病学中的实际应用。     

相关差别指标的区间估计方法比较

在公共疾病控制领域,重大稀有疾病的发病率非常低,符合逆抽样特征,量化分析重大稀有疾病的发病率并对其特点进行分析。为了研究在带有群内相关条件下的整群抽样问题,通过二项分布抽样对比流行病学中相关差别指标的六种渐近置信区间的构造方法研究,综合考虑实际覆盖率与区间长度对各种方法的优劣及适用情况做出对比分析。研究表明,Wald型置信区间与对数变换的置信区间对发病率的估计表现因参数而定,而Bootstrap类方法不稳定。本研究找出了不同区间估计方法的适用场合,应合理看待置信区间这种评估方法在流行病学中的实际应用。     

Risk, Statistical Inference, and the Law of Evidence: The Use of Epidemiological Data in Toxic Tort Cases

Toxic torts are product liability cases dealing with alleged injuries due to chemical or biological hazards such as radiation, thalidomide, or Agent Orange. Toxic tort cases typically rely more heavily than other product liability cases on indirect or statistical proof of injury. There have been numerous theoretical analyses of statistical proof of injury in toxic tort cases. However, there have been only a handful of actual legal decisions regarding the use of such statistical evidence, and most of those decisions have been inconclusive. Recently, a major case from the Fifth Circuit, involving allegations that Benedectin (a morning sickness drug) caused birth defects, was decided entirely on the basis of statistical inference. This paper examines both the conceptual basis of that decision, and also the relationships among statistical inference, scientific evidence, and the rules of product liability in general.