Follow-up study of chrysotile textile workers: cohort mortality and exposure-response
Occupational & Environmental Medicine. 2007 Apr 20; [Epub ahead of print] [Link]
Misty J Hein 1*, Leslie Stayner 2, Everett Lehman 1 and John M Dement 3
1 Centers for Disease Control and Prevention, United States
2 NIOSH, United States
3 Duke University Medical Center, United States
* To whom correspondence should be addressed. E-mail: zcr9@cdc.gov
Abstract
Objectives: This report provides an update of the mortality experience of a cohort of South Carolina asbestos textile workers.
Methods: A cohort of 3,072 workers exposed to chrysotile in a South Carolina asbestos textile plant (1916-1977) was followed up for mortality through 2001. Standardized mortality ratios (SMRs) were computed using U.S. and South Carolina mortality rates. A job exposure matrix provided calendar time dependent estimates of chrysotile exposure concentrations. Poisson regression models were fitted for lung cancer and asbestosis. Covariates considered included sex, race, age, calendar time, birth cohort, and time since first exposure. Cumulative exposure lags of 5 and 10 years were considered by disregarding exposure in the most recent 5 and 10 years, respectively.
Results: A majority of the cohort was deceased (64%) and 702 of the 1,961 deaths occurred since the previous update. Mortality was elevated based on U.S. referent rates for a priori causes of interest including all causes combined (SMR 1.33, 95% confidence interval (CI) 1.28-1.39); all cancers (SMR 1.27, 95% CI 1.16-1.39); esophageal cancer (SMR 1.87, 95% CI 1.09-2.99); lung cancer (SMR 1.95, 95% CI 1.68-2.24); ischemic heart disease (SMR 1.20, 95% CI 1.10-1.32); and pneumoconiosis and other respiratory diseases (SMR 4.81, 95% CI 3.84-5.94). Mortality remained elevated for these causes when South Carolina referent rates were used. Three cases of mesothelioma were observed among cohort members. Exposure-response modeling for lung cancer, using a linear relative risk model, produced a slope coefficient of 0.0198 (fiber-years/ml)-1 (standard error 0.00496), when cumulative exposure was lagged 10 years. Poisson regression modeling confirmed significant positive relationships between estimated chrysotile exposure and lung cancer and asbestosis mortality observed in previous updates of this cohort.
Conclusions: This study confirms the findings from previous investigations of excess mortality from lung cancer and asbestosis and a strong exposure-response relationship between estimated exposure to chrysotile and mortality from lung cancer and asbestosis.
