Polychlorinated biphenyls, polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, pesticides, and diabetes in the Anniston Community Health Survey follow-up (ACHS II): single exposure and mixture analysis approaches.

Dioxins and dioxin-like compounds measurements were added to polychlorinated biphenyls (PCBs) and organochlorine pesticides to expand the exposure profile in a follow-up to the Anniston Community Health Survey (ACHS II, 2014) and to study diabetes associations. Participants of ACHS I (2005-2007) still living within the study area were eligible to participate in ACHS II. Diabetes status (type-2) was determined by a doctor's diagnosis, fasting glucose ≥125 mg/dL, or being on any glycemic control medication. Incident diabetes cases were identified in ACHS II among those who did not have diabetes in ACHS I, using the same criteria. Thirty-five ortho-substituted PCBs, 6 pesticides, 7 polychlorinated dibenzo-p-dioxins (PCDD), 10 furans (PCDF), and 3 non-ortho PCBs were measured in 338 ACHS II participants. Dioxin toxic equivalents (TEQs) were calculated for all dioxin-like compounds. Main analyses used logistic regression models to calculate odds ratios (OR) and 95 % confidence intervals (CI). In models adjusted for age, race, sex, BMI, total lipids, family history of diabetes, and taking lipid lowering medication, the highest ORs for diabetes were observed for PCDD TEQ: 3.61 (95 % CI: 1.04, 12.46), dichloro-diphenyl dichloroethylene (p,p'-DDE): 2.07 (95 % CI 1.08, 3.97), and trans-Nonachlor: 2.55 (95 % CI 0.93, 7.02). The OR for sum 35 PCBs was 1.22 (95 % CI: 0.58-2.57). To complement the main analyses, we used BKMR and g-computation models to evaluate 12 mixture components including 4 TEQs, 2 PCB subsets and 6 pesticides; suggestive positive associations for the joint effect of the mixture analyses resulted in ORs of 1.40 (95% CI: -1.13, 3.93) for BKMR and 1.32 (95% CI: -1.12, 3.76) for g-computation. The mixture analyses provide further support to previously observed associations of trans-Nonachlor, p,p'- DDE, PCDD TEQ and some PCB groups with diabetes.

A test of fluctuating asymmetry in Bluegills (Lepomis macrochirus Rafinesque) as a measure of pH-related stress.

Fluctuating asymmetry of bilateral anatomical characters, previously proposed as an indicator of stress induced by agents affecting the calcium metabolism of fishes, was measured in bluegills (Lepomis macrochirus) from eleven Wisconsin lakes. The fluctuating asymmetries of three meristic characters-numbers of pored lateral line scales, pectoral fin rays and gill rakers on the outer arch-were either unrelated or only marginally related to either lake pH or waterborne calcium concentration. The asymmetry variance of gill raker counts was negatively correlated with both lake pH and waterborne calcium concentration; however, the overall asymmetry mean of gill raker counts in bluegills from five low pH lakes only slightly exceeded that in bluegills from six lakes with circumneutral pH. Fluctuating asymmetry in adult fishes was judged to be insensitive as a potential measure of pH-related stress.

Assessing impacts of power plants on fish populations: A general strategy.

Environmental impact statements are often characterized by extraneous data collection, irrelevant statistical procedures, misapplied models and concomitant ambiguity in conclusions. Impact assessment is difficult but when explicit objectives are not stated and specific tasks are not linked to these objectives, assessment becomes impossible. We emphasize a flexible approach that can be adapted to site-specific requirements. The strategy consists of six steps: (1) Conceptualization of the ecosystem, (2) design and execution of pilot studies, (3) refinement of conceptualization, (4) design of a study plan, (5) execution of the study plan and (6) evaluation of impact. Development of a conceptual model leads to specification of testable hypotheses directly linked to the objectives of impact assessment. Deterministic and stochastic simulation modeling can be coupled effectively with traditional statistical methods to reduce the probability of decisions which impose unnecessary risks on the environment or costs to industry.