Rectal cancer and exposure to metalworking fluids in the automobile manufacturing industry

Elizabeth J. Malloy ¹, Katie L. Miller ¹ and Ellen A. Eisen ^1*

¹ Harvard School of Public Health, United States

^* To whom correspondence should be addressed. E-mail: eeisen{at}hsph.harvard.edu.

Accepted 4 August 2006

Abstract

Abstract Background: Rectal cancer has been previously associated with exposure to metalworking fluids in a cohort mortality study of autoworkers. The objective of this nested case-control analysis was to better specify the exposure-response relationship with straight metalworking fluids (mineral oils) by applying nonparametric regression methods that avoid linearity constraints and arbitrary exposure cut-points and by lagging exposure to account for cancer latency. Methods: In addition to the classical Poisson regression with categorical exposure, survival models with penalized splines were used to estimate the exposure-response relation between cumulative exposure to straight metalworking fluid and rectal cancer mortality. Exposures to water-based metalworking fluids were treated as potential confounders and all exposures were lagged by 5, 10, 15 and 20 years to account for cancer latency. Influence of the highest exposures was addressed by a log transformation and outlier removal. Sensitivity of the penalized splines to alternative criteria for model selection and to the placement of knots was also examined. Results: The hazard ratio for rectal cancer mortality increased essentially linearly with cumulative exposure to straight metalworking fluid (with narrow confidence bands) up to a maximum of 2.2 at the 99th percentile of exposure and then decreased (with wide confidence bands). Lagging exposure up to 15 years increased the initial steepness of the curve and raised the maximum hazard ratio to 3.2. Conclusions: Nonparametric smoothing of lagged exposures has revealed stronger evidence for a causal association between straight metalworking fluid and rectal cancer than was previously described using standard analytical methods. The present analysis suggests an exposure-response trend that is close to linear and statistically significant over most of the exposure range and that increases further with lagged exposures. Smoothing should be regularly applied to environmental studies with quantitative exposure estimates in order to refine characterization of the dose-response relationship.

Keywords: AIC, Cox regression, cross-validation, mineral oils, penalized splines

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