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Environmental exposures cause substantial morbidity and mortality in the United States. A major goal of Centers for Disease Control and Prevention Environmental Public Health Tracking program is the development of a national network of health and environmental data with analytic tools for rapid evaluation of specific national or regional environmental health concerns. A six-state collaborative project in the northeast United States was established to assess the feasibility of such a system, assessing the possible association between ambient air quality and adverse birth outcomes. For this regional surveillance project, issues were discussed surrounding the design of a mutually acceptable protocol, obtaining human subjects' protection approvals, obtaining and organizing both the exposure and outcome data, analyzing the data both locally and regionally, and planning subsequent interventions to address identified public health concerns. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Case-control studies suggest hydrocarbons increase end-stage renal disease (ESRD) risk. No cohort studies have been conducted. METHODS: An occupational database was matched to the U.S. Renal Data System, and the outcome of all-cause ESRD was examined using multivariable Cox regression. Sixteen individual hydrocarbons were studied, although exposures were not mutually exclusive. RESULTS: For the 1973-2000 period, there was an approximate twofold increased risk of ESRD among workers exposed to trichloroethylene, 1,1,1-trichloroethane, and JP4 gasoline compared with unexposed subjects (all P < 0.05). Relative risk was greater than unity (P > 0.05) for several other hydrocarbons. Associations attenuated (all P > 0.05) when 2001-2002 data were included in the analyses. CONCLUSIONS: Certain hydrocarbons may increase all-cause ESRD risk. Uncertainty regarding the mechanism for increased risk and the observed attenuation in risk in 2001-2002, as well as the overlap of exposures, complicates interpretation. Additional research is needed. [ABSTRACT FROM AUTHOR]

Monte Carlo simulations are commonplace in quantitative risk assessments (QRAs). Designed to propagate the variability and uncertainty associated with each individual exposure input parameter in a quantitative risk assessment, Monte Carlo methods statistically combine the individual parameter distributions to yield a single, overall distribution. Critical to such an assessment is the representativeness of each individual input distribution. The authors performed a literature review to collect and compare the distributions used in published QRAs for the parameters of body weight, food consumption, soil ingestion rates, breathing rates, and fluid intake. To provide a basis for comparison, all estimated exposure parameter distributions were evaluated with respect to four properties: consistency, accuracy, precision, and specificity. The results varied depending on the exposure parameter. Even where extensive, well-collected data exist, investigators used a variety of different distributional shapes to approximate these data. Where such data do not exist, investigators have collected their own data, often leading to substantial disparity in parameter estimates and subsequent choice of distribution. The present findings indicate that more attention must be paid to the data underlying these distributional choices. More emphasis should be placed on sensitivity analyses, quantifying the impact of assumptions, and on discussion of sources of variation as part of the presentation of any risk assessment results. If such practices and disclosures are followed, it is believed that Monte Carlo simulations can greatly enhance the accuracy and appropriateness of specific risk assessments. Without such disclosures, researchers will be increasing the size of the risk assessment “black box,” a concern already raised by many critics of more traditional risk assessments. [ABSTRACT FROM AUTHOR]