Leukemia Attributable to Residential Magnetic Fields: Results from Analyses Allowing for Study Biases

Nearly every epidemiologic study of residential magnetic fields and childhood leukemia has exhibited a positive association. Nonetheless, because these studies suffer from various methodologic limitations and there is no known plausible mechanism of action, it remains uncertain as to how much, if any, of these associations are causal. Furthermore, because the observed associations are small and involve only the highest and most infrequent levels of exposure, it is believed that the public health impact of an effect would be small. We present some formal analyses of the impact of power-frequency residential magnetic-field exposure (as measured by attributable fractions), accounting for our uncertainties about study biases as well as uncertainties about exposure distribution. These analyses support the idea that the public health impact of residential fields is likely to be limited, but both no impact and a substantial impact remain possibilities in light of the available data.     

Umvu estimators for the population mean and variance based on random effects models for lognormal data

Cross-classified data are often obtained in controlled experimental situations and in epidemiologic studies. As an example of the latter, occupational health studies sometimes require personal exposure measurements on a random sample of workers from one or more job groups, in one or more plant locations, on several different sampling dates. Because the marginal distributions of exposure data from such studies are generally right-skewed and well-approximated as lognormal, researchers in this area often consider the use of ANOVA models after a logarithmic transformation. While it is then of interest to estimate original-scale population parameters (e.g., the overall mean and variance), standard candidates such as maximum likelihood estimators (MLEs) can be unstable and highly biased. Uniformly minimum variance unbiased (UMVU) cstiniators offer a viable alternative, and are adaptable to sampling schemes that are typiral of experimental or epidemiologic studies. In this paper, we provide UMVU estimators for the mean and variance under two random effects ANOVA models for logtransformed data. We illustrate substantial mean squared error gains relative to the MLE when estimating the mean under a one-way classification. We illustrate that the results can readily be extended to encompass a useful class of purely random effects models, provided that the study data are balanced.     

A likelihood ratio test for goodness‐of‐fit of recessive and dominant models for case–control studies

Testing goodness‐of‐fit of commonly used genetic models is of critical importance in many applications including association studies and testing for departure from Hardy–Weinberg equilibrium. Case–control design has become widely used in population genetics and genetic epidemiology, thus it is of interest to develop powerful goodness‐of‐fit tests for genetic models using case–control data. This paper develops a likelihood ratio test (LRT) for testing recessive and dominant models for case–control studies. The LRT statistic has a closed‐form formula with a simple $\chi^{2}(1)$ null asymptotic distribution, thus its implementation is easy even for genome‐wide association studies. Moreover, it has the same power and optimality as when the disease prevalence is known in the population. The Canadian Journal of Statistics 41: 341–352; 2013 © 2013 Statistical Society of Canada     

由日本动漫在中国的兴盛引发的思考

针对新形势下动物传染病学课程教学中存在的问题,以现代教育理念和现代人才培养模式为指导,结合现代畜牧业发展的趋势和本学科教学的实际情况,从教学内容的整合、教学方法的改革、强化实践教学以及严格教学管理等方面进行了动物传染病学的教学改革探索。     

流行病学思维在全科医学中的应用及重要性

流行病学与全科医学有共同的研究对象即以人群为基础和共同的研究目的即防治疾病、促进健康等.宏观(群体)、对比、概率统计、多病因论、分级预防及预防为主的流行病学思维方式与观点能够有力地指导全科医疗研究与实践.文章通过分析流行病学思维方式及其在全科医学中的应用及重要性,指出对于全科医学专业学生的流行病学教学首先应培养其流行病学思维方式,其次才是在思维方式指导下学习流行病学研究方法.     

About the contributors

The paper reports secondary analysis of data from the 2010 British Gambling Prevalence Survey, a household survey of a representative sample of the population aged 16 years and over (N = 7756). Responses to questions about frequency of gambling and average monthly spend on each of 15 forms of gambling, and responses to two different problem gambling screens (DSM-IV and PGSI), were used to derive estimates, for each form of gambling separately, of the percentage of (1) all days play (two estimates), and (2) all spend (four estimates), attributable to problem gamblers. Although these estimates must be treated as approximations only, they demonstrate that problem gamblers make a far greater contribution to total gambling attendances and losses than problem gambling prevalence figures would suggest. There are certain forms of British gambling to which problem gamblers may be contributing as much as 20–30% of all days play and spend, and moderate risk gamblers a possible further 10–20%.     

The role of acculturative stress and cultural backgrounds in migrants with pathological gambling

The objective of the present study was to differentiate specific migration-related factors that can account for an increased vulnerability to pathological gambling (PG) among migrants in Germany. One hundred and six gamblers (61 migrants, 45 Germans) with varying degrees of gambling problems participated in the study. We analysed (1) differences between migrants and Germans regarding gambling patterns, severity of gambling problems, motivation and craving; influence of (2) acculturative stress; (3) acceptance and popularity of gambling in the culture of origin on gambling problems; (4) differences between migrants and Germans regarding family gambling and peer gambling; and (5) differences in religiosity and its influence on gambling problems. Results suggest no differences between migrants and Germans regarding gambling patterns and the severity of gambling problems. However, findings indicate that migrants have higher motivation and craving to gamble. Findings further suggest that acculturative stress is associated with more severe gambling problems. In contrast, acceptance and popularity of gambling in the country of origin was not a significant predictor of gambling problems. At the same time, family gambling and peer gambling was significantly more prevalent among migrants, constituting an additional risk factor in the present sample. On the other hand, migrants in the sample benefit more often from a protective influence of religiosity.     

Risk Estimation and Value-of-Information Analysis for Three Proposed Genetic Screening Programs for Chronic Beryllium Disease Prevention

Genetic differences (polymorphisms) among members of a population are thought to influence susceptibility to various environmental exposures. In practice, however, this information is rarely incorporated into quantitative risk assessment and risk management. We describe an analytic framework for predicting the risk reduction and value-of-information (VOI) resulting from specific risk management applications of genetic biomarkers, and we apply the framework to the example of occupational chronic beryllium disease (CBD), an immune-mediated pulmonary granulomatous disease. One described Human Leukocyte Antigen gene variant, HLA-DP beta 1*0201, contains a substitution of glutamate for lysine at position 69 that appears to have high sensitivity (approximately 94%) but low specificity (approximately 70%) with respect to CBD among individuals occupationally exposed to respirable beryllium. The expected postintervention CBD prevalence rates for using the genetic variant (1) as a required job placement screen, (2) as a medical screen for semiannual in place of annual lymphocyte proliferation testing, or (3) as a voluntary job placement screen are 0.08%, 0.8%, and 0.6%, respectively, in a hypothetical cohort with 1% baseline CBD prevalence. VOI analysis is used to examine the reduction in total social cost, calculated as the net value of disease reduction and financial expenditures, expected for proposed CBD intervention programs based on the genetic susceptibility test. For the example cohort, the expected net VOI per beryllium worker for genetically based testing and intervention is $13,000, $1,800, and $5,100, respectively, based on a health valuation of $1.45 million per CBD case avoided. VOI results for alternative CBD evaluations are also presented. Despite large parameter uncertainty, probabilistic analysis predicts generally positive utility for each of the three evaluated programs when avoidance of a CBD case is valued at $1 million or higher. Although the utility of a proposed risk management program may be evaluated solely in terms of risk reduction and financial costs, decisions about genetic testing and program implementation must also consider serious social, legal, and ethical factors.     

Correlated linear models for the analysis of familial correlations

The problems of estimation and hypotheses testing on the parameters of two correlated linear models are discussed. Such models are known to have direct applications in epidemiologic research, particularly in the field of family studies. When the data are unbalanced, the maximum-likelihood estimation of the parameters is achieved by adopting a fairly simple numerical algorithm. The asymptotic variances and covariances of the estimators are derived, and the procedures are illustrated on arterial-blood-pressure data from the literature.