Presentation Time: 11:00 - 11:30

Objectives Carbon nanotubes (CNT) and carbon nanofibers (CNF) are among the first nanomaterials to reach commercial use in the US and are also showing evidence of serious health effects at occupationally relevant levels in toxicology studies. The objective of our work was to design an epidemiologic study of early possible health effects among US workers exposed to CNT and CNF, taking into account small workforce sizes, a global manufacturing and distribution system, uncertainty about which exposure metrics may best correlate with health effects, and short available latency.

Methods Initial exposure characterisation was conducted at 15 US manufacturers and users of CNT and CNF to determine the most specific and useful exposure metrics. Possible markers of early pulmonary, cardiovascular, and malignant health effects were identified from animal toxicology studies and epidemiologic research among populations exposed to ambient ultrafine particles. Power analyses were conducted to determine appropriate sample sizes.

Results A cross-sectional exposure assessment and epidemiology study was designed; it will include 100 workers from at least 10 US facilities making or using CNT or CNF. This study, now in progress, evaluates elemental mass and electron microscopy-based exposure metrics for each worker, along with early health outcomes including spirometry measures, blood pressure, and approximately 40 biomarkers of inflammation, oxidative stress, pulmonary fibrosis, cardiovascular disease, and cancer. The study will account for ambient ultrafine exposure using a combination of background sampling and non-specific direct-reading instruments that operate in the nanoscale range.

Conclusions Cross-sectional epidemiologic designs for nanomaterial exposures are feasible, but small workforce sizes and generally short latency limit power; cohort studies for outcomes such as malignant and nonmalignant respiratory and other disease may require international pooling. Researchers should collaborate to identify the most suitable exposure metrics and early health outcomes.