The cohort is young, and because the number of deaths is small, the results though suggestive of increased risks for some causes, are inconclusive. However they indicate that this cohort is of interest, and that further follow-up might reveal a much clearer and consistent picture.

No abstract

The Environmental Public Health Tracking Network (EPHTN) proposes to link environmental hazards and exposures to health outcomes. Statistical methods used in case–control and cohort studies to link health outcomes to individual exposure estimates are well developed. However, reliable exposure estimates for many contaminants are not available at the individual level. In these cases, exposure/hazard data are often aggregated over a geographic area, and ecologic models are used to relate health outcome and exposure/hazard. Ecologic models are not without limitations in interpretation. EPHTN data are characteristic of much information currently being collected—they are multivariate, with many predictors and response variables, often aggregated over geographic regions (small and large) and correlated in space and/or time. The methods to model trends in space and time, handle correlation structures in the data, estimate effects, test hypotheses, and predict future outcomes are relatively new and without extensive application in environmental public health. In this article we outline a tiered approach to data analysis for EPHTN and review the use of standard methods for relating exposure/hazards, disease mapping and clustering techniques, Bayesian approaches, Markov chain Monte Carlo methods for estimation of posterior parameters, and geostatistical methods. The advantages and limitations of these methods are discussed.

We measured current serum hormone and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) concentrations in 37 men who sprayed 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) in the State of Victoria, Australia. TCDD levels were consistently significantly inversely related to prolactin levels in all analyses. In correlation analyses, TCDD levels were also inversely related to triiodothyronine (T3), thyroid-stimulating hormone (TSH), and testosterone levels, and positively associated with glucagon levels. The mean serum TCDD concentration in these sprayers was between 2.6 and 8.1 parts per trillion (ppt). Since such TCDD levels are commonly found in the general population in countries such as the US, the results could suggest that background levels of TCDD in the general population could have an effect on hormone levels. The findings are preliminary and need to be replicated in order to evaluate their full public health significance.

No abstract