Increased suicide risk among workers following toxic metal exposure at the Paducah gaseous diffusion plant from 1952 to 2003: a cohort study.

BACKGROUND: Suicide is a problem worldwide and occupation is an important risk factor. In the last decade, 55 200 deaths in the US were attributed to occupational risk factors. OBJECTIVE: To determine if toxic metal exposure was associated with suicide risk among Paducah gaseous diffusion plant (PGDP) workers. METHODS: We assembled a cohort of 6820 nuclear industry workers employed from 1952 to 2003. A job-specific exposure matrix (JEM) was used to determine metal exposure likelihood. Uranium exposure was also assessed by urinalysis. All suicide/self-injury International Classification for Disease (ICD) codes were used to identify suicides. Standardized mortality ratios (SMR), odds ratios (OR), and hazard ratios (HR) were used to estimate suicide risk. RESULTS: PGDP suicide victims typically were younger white men. Within exposure likelihood categories, several suicide SMRs were typically elevated for several metals. Only beryllium exposure likelihood was associated with an increased HR. Uranium urine concentration was associated with an elevated suicide risk after stratification by urinalysis frequency. CONCLUSION: Suicide risk is associated with uranium exposure.

Multivariate logistic regression for predicting total culturable virus presence at the intake of a potable-water treatment plant: novel application of the atypical coliform/total coliform ratio.

Predicting the presence of enteric viruses in surface waters is a complex modeling problem. Multiple water quality parameters that indicate the presence of human fecal material, the load of fecal material, and the amount of time fecal material has been in the environment are needed. This paper presents the results of a multiyear study of raw-water quality at the inlet of a potable-water plant that related 17 physical, chemical, and biological indices to the presence of enteric viruses as indicated by cytopathic changes in cell cultures. It was found that several simple, multivariate logistic regression models that could reliably identify observations of the presence or absence of total culturable virus could be fitted. The best models developed combined a fecal age indicator (the atypical coliform [AC]/total coliform [TC] ratio), the detectable presence of a human-associated sterol (epicoprostanol) to indicate the fecal source, and one of several fecal load indicators (the levels of Giardia species cysts, coliform bacteria, and coprostanol). The best fit to the data was found when the AC/TC ratio, the presence of epicoprostanol, and the density of fecal coliform bacteria were input into a simple, multivariate logistic regression equation, resulting in 84.5% and 78.6% accuracies for the identification of the presence and absence of total culturable virus, respectively. The AC/TC ratio was the most influential input variable in all of the models generated, but producing the best prediction required additional input related to the fecal source and the fecal load. The potential for replacing microbial indicators of fecal load with levels of coprostanol was proposed and evaluated by multivariate logistic regression modeling for the presence and absence of virus.

Predictive input parameters for enteric virus presence at the inlet of a potable water supply.

Kentucky river water samples were collected at the input of a potable water supply weekly, for a period of two years. Eighteen parameters were analysed and/or recorded for each weekly observation. The variables were of a physical, chemical and biological nature. Enteric virus presence was detected by cell culture analysis from approximately 200 L samples of river water. A database of 108 observations was assembled. Of these only 100 complete observations were used for the modelling analysis. Model input parameters were selected solely based on their statistical significance in forward, backward and stepwise selection procedures. Multivariate logistic regression (MLR) was used to determine the relative significance of the input parameters for predicting the presence or absence of enteric virus. The final, best-fit MLR model that used log-transformed values for enterococci, the AC/TC ratio, faecal coliforms (FC) and temperature demonstrated 82.5 and 81.4% sensitivity and specificity, respectively.