Modelling exposure in flour processing sectors in the Netherlands: a baseline measurement in the context of an
Tim Meijster1, Erik Tielemans, Nettie de Pater
1Business Unit Quality & Safety, TNO Quality of Life, Zeist, The Netherlands. tim.meijster@tno.nl
Introduction:
Recent studies have shown that even low exposure levels to flour dust and related allergens can cause severe respiratory symptoms. In The Netherlands the Dutch government and responsible branch organizations [from bakeries (traditional & industrial), flour mills and bakery ingredient producers] signed a covenant to reduce exposure to flour dust and decrease the prevalence of work-related occupational airway disease. This paper describes a sector wide survey to measure exposure to flour dust, wheat allergens and fungal alpha-amylase. The results are being used to underpin various elements of the covenant.
Methods:
A dataset containing 910 personal measurements was compiled from four field studies containing information on exposure and potential determinants. The dataset represents a baseline estimate of exposure for four major flour processing sectors in The Netherlands. Exposure models for all sectors and agents were generated, based on job, tasks and company size, taking into account worker and company as random effect components. Use of control measures and, where possible, their effect were evaluated.
Results:
Flour dust and enzyme exposures vary strongly between sectors. The job performed and specific tasks were identified as important determinants of exposure. The number of identified control measures during walk-through surveys, and their effectiveness in reduction of dust exposure was generally limited. The exposure models explained significant exposure variability between companies and workers but performed poorly in explaining day to day differences in exposure.
Discussion:
The dataset serves as a baseline estimate and will be compared with a post intervention survey in the near future. The information obtained on control measures can be used to optimize the intervention scenarios that will be implemented in the different sectors by external occupational hygienists. The predictive exposure models will provide a relevant measure of average personal exposure that will be used in the sector wide health surveillance system.
