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0137 Exposure-lag-response in occupational epidemiology: application of distributed non-linear lag models in a cohort of diatomaceous earth workers exposed to crystalline silica
  1. Andreas Neophytou1,
  2. Sally Picciotto1,
  3. Daniel Brown1,
  4. Ellen Eisen1,
  5. Harvey Checkoway2,
  6. Sadie Costello1
  1. 1Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
  2. 2Department of Family and Preventive Medicine, University of California, San Diego, San Diego, CA, USA


Occupational exposures extending over a long working life can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Simple measures of cumulative, or average intensity of exposure typically considered in occupational studies may not fully capture these relationships. We applied distributed non-linear lag models to examine the association of crystalline silica exposures with mortality from lung cancer and non-malignant respiratory disease. We fitted Cox proportional hazard models for each cause of interest to data from a cohort study of 2342 California diatomaceous earth workers exposed to crystalline silica. Our models combined various functions for exposure-response and lag-response including linear, piece-wise constant and spline functions. Models with a spline function for exposure-response and a constant term for the lag-response appeared to have the best fit for lung cancer, while models with spline functions for both exposure-response and lag-response had the best fit for non-malignant respiratory disease. Hazard ratios (HR) from these best fitting models corresponding to average daily exposures of 275 µg/m3 during lag years 11–40 prior to the age of observed cases were 1.96 (95% confidence interval (CI) 0.95–4.06) and 2.01 (95% CI: 1.02–3.97) for the two outcomes respectively. HRs from simple models with linear exposure-response and constant lag-response terms for the same exposure scenario were 1.15 (95% CI: 0.88–1.49) and 1.21 (95% CI: 1.01–1.44) respectively. Occupational studies of longitudinal cohorts with detailed exposure histories could benefit from methods allowing for non-linearities and the disentanglement of intensity, duration and timing of exposure.

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