Effects of the analytical treatment of exposure data on associations of cancer and occupational magnetic field exposure

Epidemiological studies of cancer among workers exposed to magnetic fields have yielded inconsistent results. This variability may be partly explained by differences in study methods. To assess sensitivity to such methods, data from a previous study of brain cancer and leukemia among electric power company workers were reanalyzed using alternative models, which incorporated uncertainty about the intensity of historical exposures, alternative cut points for categorizing the exposure variable for analysis, and a range of lags for describing cancer latency. Mortality rate ratios for leukemia ranged from 0.8–1.5. For brain cancer, increasing cumulative magnetic field exposure was associated with increasing mortality in virtually all models, with rate ratios between 1.3–3.4 for the most exposed workers. These rate ratios are consistent with previous analyses suggesting a 1.5–3.0-fold increase in the risk of brain cancer but no association with leukemia, and confirm that the previous results are not dependent on arbitrary decisions in applying the exposure data. Am. J. Ind. Med. 34:49–56, 1998. © 1998 Wiley-Liss, Inc.     

Can exposure to electromagnetic radiation in diathermy operators be estimated from interview data?: A pilot study

As preparation for a case-control study dealing with possible teratogenic property of short waves, a pilot study was conducted in order to compare exposure assessment from different sources. In 11 physiotherapy clinics, exposure assessments based on interviews within 1 week among the exposed physiotherapists were compared with exposure assessments based on observations including measurements. It was possible to discriminate between recent high and low peak exposure. Furthermore, an interview index reflecting the duration of the exposure correlated to some extent with the corresponding measurements.     

Reporting of skin cancer risks in the house-building industry: alternative approaches to the analysis of categorical data

BACKGROUND: Increasing incidence of skin cancer is of concern to public health. Working predominantly outside, construction workers are at increased risk of sunburn and certain forms of skin cancer. The objective of this paper was to explore these concerns via use of alternative approaches to categorical data analysis by considering the relationship between the size of house-building companies, use of risk assessments and the system for reporting sunburn. METHODS: The survey population was speculative house-building companies. A self-administered questionnaire was sent to health and safety advisors in house-building companies. Questions related to the number of house units built, inclusion of adverse weather in the risk assessment, and the presence or absence of a system for reporting sunburn were analysed. Alternative approaches to conventional chi(2) tests were used in order to investigate a multiway data structure. A loglinear model was employed using Statistical Package for Social Sciences to explain data in three-way tables. RESULTS: The questionnaire achieved a response rate of 31% (n=94). A significant association identified in a two-way study of the mechanisms of reporting sunburn also appeared at the sublevels introduced by the inclusion of a third method of categorization. Finally, correspondence analysis was used to present a graphical insight into the study. CONCLUSIONS: In the two-way analysis, the size of house-building company had a significant impact on the presence of a system for reporting sunburn, although this was not translated into the three-way analysis. The establishment of systems within risk assessments to incorporate exposure of construction workers to ultraviolet radiation, and reporting of incidents of sunburn, is essential if this public health issue is to be addressed.     

Psychosocial work exposures of the job strain model and cardiovascular mortality in France: results from the STRESSJEM prospective study

Objectives:The study aims to explore the prospective associations of the psychosocial work exposures of the job strain model with cardiovascular mortality, including mortality for ischemic heart diseases (IHD) and stroke, using various time-varying exposure measures in the French working population of employees.Methods:The study was based on a cohort of 798 547 men and 697 785 women for which job history data from 1976 to 2002 were linked to mortality data and causes of death from the national death registry. Psychosocial work exposures from the validated job strain model questionnaire were assessed using a job-exposure matrix (JEM). Three time-varying measures of exposure were studied: current, cumulative, and recency-weighted cumulative exposure. Cox proportional hazards models were used to examine the associations between psychosocial work exposures and cardiovascular mortality.Results:Within the 1976–2002 period, there were 19 264 cardiovascular deaths among men and 6181 among women. Low decision latitude, low social support, job strain, iso-strain, passive job, and high strain were associated with cardiovascular mortality. Most of these associations were also observed for IHD and stroke mortality. The comparison between the different exposure measures suggested that current exposure may be more important than cumulative (or past) exposure. The population fractions of cardiovascular mortality attributable to job strain were 5.64% for men and 6.44% for women.Conclusions:Psychosocial work exposures of the job strain model may play a role in cardiovascular mortality. The estimated burden of cardiovascular mortality associated with these exposures underlines the need for preventive policies oriented toward the psychosocial work environment.     

Toward the integration of Omics data in epidemiological studies: still a “long and winding road”

Primary and secondary prevention can highly benefit a personalized medicine approach through the accurate discrimination of individuals at high risk of developing a specific disease from those at moderate and low risk. To this end precise risk prediction models need to be built. This endeavor requires a precise characterization of the individual exposome, genome, and phenome. Massive molecular omics data representing the different layers of the biological processes of the host and the nonhost will enable to build more accurate risk prediction models. Epidemiologists aim to integrate omics data along with important information coming from other sources (questionnaires, candidate markers) that has been proved to be relevant in the discrimination risk assessment of complex diseases. However, the integrative models in large‐scale epidemiologic research are still in their infancy and they face numerous challenges, some of them at the analytical stage. So far, there are a small number of studies that have integrated more than two omics data sets, and the inclusion of non‐omics data in the same models is still missing in most of studies. In this contribution, we aim at approaching the omics and non‐omics data integration from the epidemiology scope by considering the “massive” inclusion of variables in the risk assessment and predictive models. We also provide already available examples of integrative contributions in the field, propose analytical strategies that allow considering both omics and non‐omics data in the models, and finally review the challenges imbedding this type of research.     

Reducing classification errors in cohort studies: the approach and a practical application

Classification errors of dependent variables can distort the results of observational studies. To reduce misclassification from our multicentre observational study of abortion complications, we extended the methodology of Lawrence and Greenwald for use in situations of unequal sample sizes and implemented both an office review and a field review. We reabstracted 424 reported complications and a random sample of 364 reported non-serious cases from 12 institutions participating in our study. In total, 30 per cent of the reported serious complications turned out to be misclassified: the office review detected 74 per cent of the total number of misclassifications with the remainder found in the field review. Because, with our particular data base, we estimated expending only 15 per cent of the total resources with our office effort, this represented the most cost-efficient approach to reducing classification errors. By eliminating the false positives from our study, we forced the specificity to 1.00 which produced both an unbiased estimate of the relative risk and an increase of 4 per cent to 63 per cent in the power of our study.     

Occupational exposure to respirable dust from the coal-fired power generation process: sources,concentration, and health risk assessment

Abstract

To investigate the contamination levels of respirable dust released in the work environment and the induced workers’ health risk at a coal-fired power plant, we collected 405 dust samples from different dusty workstations by personal sampling during the coal-fired power generation process. Then, an inhalation risk assessment model from the USEPA was combined with the Monte Carlo simulation method to quantitatively evaluate the health risk caused by dust inhalation. Of 10 workstations researched, the dust concentration in the most workstations exceeded the prescribed occupational exposure limit. Workers engaged in ash removal suffered the highest health risk at 4.08?×?10^?6 ± 2.85?×?10^?6 (95% CI), closely followed by those involved in other job categories. The results can contribute to the formulation of targeted dust prevention measures and implementation of risk management for the coal-fired power sector.     

Selecting mixtures on the basis of dietary exposure and hazard data: application to pesticide exposure in the European population in relation to steatosis

Populations are exposed to mixtures of pesticides through their diet on a daily basis. The question of which substances should be assessed together remains a major challenge due to the complexity of the mixtures. In addition, the associated risk is difficult to characterise. The EuroMix project (European Test and Risk Assessment Strategies for Mixtures) has developed a strategy for mixture risk assessment. In particular, it has proposed a methodology that combines exposures and hazard information to identify relevant mixtures of chemicals belonging to any cumulative assessment group (CAG) to which the European population is exposed via food. For the purposes of this study, food consumption and pesticide residue data in food and drinking water were obtained from national surveys in nine European countries. Mixtures of pesticides were identified by a sparse non-negative matrix underestimation (SNMU) applied to the specific liver steatosis effect in children from 11 to 15 years of age, and in adults from 18 to 64 years of age in nine European countries. Exposures and mixtures of 144 pesticides were evaluated through four different scenarios: (1) chronic exposure with a merged concentration dataset in the adult population, (2) chronic exposure with country-specific concentration datasets in the adult population, (3) acute exposure with a merged concentration dataset in the adult population, and (4) chronic exposure with a merged concentration dataset in the paediatric population. The relative potency factors of each substance were calculated to express their potency relative to flusilazole, which was chosen as the reference compound. The selection of mixtures and the evaluation of exposures for each country were carried out using the Monte Carlo Risk Assessment (MCRA) software.Concerning chronic exposure, one mixture explained the largest proportion of the total variance for each country, while in acute exposure, several mixtures were often involved. The results showed that there were 15 main pesticides in the mixtures, with a high contribution of imazalil and dithiocarbamate. Since the concentrations provided by the different countries were merged in the scenario using merged concentration data, differences between countries result from differences in food consumption behaviours. These results support the approach that using merged concentration data to estimate exposures in Europe seems to be realistic, as foods are traded across European borders. The originality of the proposed approach was to start from a CAG and to integrate information from combined exposures to identify a refined list of mixtures with fewer components. As this approach was sensitive to the input data and required significant resources, efforts should continue regarding data collection and harmonisation among the different aspects within the pesticides regulatory framework, and to develop methods to group substances and mixtures to characterise the risk.     

Occupational respiratory cancer and exposure to asbestos: A case-control study in a cohort of workers in the electricity and gas industry

Cancers of the pleura, lung, and larynx between 1978 and 1989 among active male workers of Electricité de France-Gaz de France were studied in association with asbestos exposure using a case-control design nested within the cohort of workers of the company. The cohort included about 1,400,000 person-years, corresponding to a mean of 117,000 men per year. Exposure to asbestos and to some potential occupational confounders selected among agents from groups I, IIa, and IIb of the International Agency for Research on Cancer was assessed by a job-exposure matrix specific to the company. During the observation period, 12 cases of pleural cancer, 310 cases of lung cancer, and 116 cases of larynx cancer were registered in the cancer register of the company social security department. Four controls per case, matched for year of birth, were randomly selected among the cohort. Conditional logistic regression was used to estimate the odds ratios. A first analysis was conducted in order to assess the validity of the job-exposure matrix by investigating already known relationships between asbestos exposure and asbestosis. For asbestosis, a strong exposure-response relation was found with an odds ratio (OR) of 57.4 [95% confidence interval (CI): 17.0–194.0] in the highest exposure group. There was an elevated risk of pleural cancer (OR, 4.8, CI, 1.2–19.8). For lung cancer, significant ORs of 2.0 (CI, 1.3–3.2) and 1.9 (CI, 1.2–3.0) were found among the two highest cumulative exposure groups; adjustement for confounders slightly decreased the ORs. Squamous cell neoplasm of the lung was associated with asbestos exposure. The association between larynx cancer and asbestos exposure showed a tendency towards a nonsignificant increase in ORs in the highest cumulative exposure categories; this tendency disappeared when adjusting for occupational confounders. This study showed that occupational exposure to asbestos could increase the risk of pleural and lung cancer in a sector in which exposure levels are not considered to be high compared with other industrial settings.     

环境镉污染对生殖系统影响的研究进展

目的了解余姚市市售水产品镉含量水平,对居民水产品镉暴露风险进行初步评估,为镉暴露风险评估提供依据。方法2015—2017年采集各类市售水产品样品以石墨炉原子吸收光谱法测定镉含量。居民水产品消费量调查采用24 h膳食回顾法。以居民水产品镉平均暴露量结合每月摄入耐受量(PTMI)计算安全限值(MOS),以初步评估水产品镉暴露风险。结果水产品中海水蟹镉含量最高(0.465 mg/kg),其次分别为海水甲壳类(0.277 mg/kg)、淡水蟹(0.197 mg/kg)、海水软体类(0.172 mg/kg)。居民镉平均暴露量为每公斤体重0.004 mg,未超过PTMI限值规定。结论余姚市居民水产品镉暴露水平总体上安全,但应控制蟹类、甲壳类水产品的摄入。     

浅论病历资料在医疗纠纷诉讼证据中的证明能力和证明力

根据《中华人民共和国民事诉讼法》（以下简称《诉讼法》）中对证据种类的规定,病历资料属于书证的范畴;在医疗纠纷民事诉讼中,病历资料是非常重要的法律证据,是《诉讼法》中规定的七种证据的核心,因此,研究病历资料的证明能力和证明力就显得尤其的重要。     

Development and application of a fuzzy occupational health risk assessment model in the healthcare industry

Background:Hazards of the workplace and their impacts on the healthcare industry affect the quality of patient care and safety and impose high costs on the healthcare industry. Occupational health in this industry requires proper identification of hazards and managing the related risks. In this study, the researchers attempted to develop an easy-to-use and high applicability occupational health risk assessment model with a fuzzy approach to evaluate risks more precisely.Methods:In this study, a fuzzy inference system (FIS) was designed and applied to develop a risk assessment model.Conclusions:This study showed that the developed model could be applied as a practical model for evaluating occupational health risks. The weight of each risk criterion was used to calculate the risk level by adopting a fuzzy approach. The risk assessment results construed using the fuzzy set theory provided a broad picture of risks and could work adequately in the presence of inaccurate and insufficient data to calculate the risk. This model calculates risk levels and provides us with the dispersion and distribution of the calculated value of the risk number.