Background: Swedish foundries have a long tradition of legally required surveys in the workplace that, from the late 1960s onwards, included measurements of quartz. The availability of exposure data spanning almost 40 years presents a unique opportunity to study trends over that time and to evaluate the validity of exposure models based on data from shorter time spans. The aims of this study were (i) to investigate long-term trends in quartz exposure over time, (ii) using routinely collected quartz exposure measurements to develop a mathematical model that could predict both historical and current exposure patterns, and (iii) to validate this exposure model with up-to-date measurements from a targeted survey of the industry.
Methods: Eleven foundries, representative of the Swedish iron foundry industry, were divided into three groups based on the size of the companies, i.e. the number of employees. A database containing 2333 quartz exposure measurements for 11 different job descriptions was used to create three models that covered time periods which reflected different work conditions and production processes: a historical model (1968-1989), a development model (1990-2004), and a validation model (2005-2006). A linear mixed model for repeated measurements was used to investigate trends over time. In all mixed models, time period, company size, and job title were included as fixed (categorical) determinants of exposure. The within- and between-worker variances were considered to be random effects. A linear regression analysis was performed to investigate agreement between the models. The average exposure was estimated for each combination of job title and company size.
Results: A large reduction in exposure (51%) was seen between 1968 and 1974 and between 1975 and 1979 (28%). In later periods, quartz exposure was reduced by 8% per 5 years at best. In the first period, employees at smaller companies experienced ~50% higher exposure levels than those at large companies, but these differences became much smaller in later years. The furnace and ladle repair job were associated with the highest exposure, with 3.9-8.0 times the average exposure compared to the lowest exposed group. Without adjusting for this autonomous trend over time, predicting early historical exposures using our development model resulted in a statistically significant regression coefficient of 2.42 (R(2) = 0.81), indicating an underestimation of historical exposure levels. Similar patterns were seen for other historical time periods. Comparing our development model with our validation model resulted in a statistically significant regression coefficient of 0.31, indicating an overestimation of current exposure levels.
Conclusion: To investigate long-term trends in quartz exposure over time, overall linear trends can be determined by using mixed model analysis. To create individual exposure measures to predict historical exposures, it is necessary to consider factors such as the time period, type of job, type of company, and company size. The mixed model analysis showed systematic changes in concentration levels, implying that extrapolation of exposure estimates outside the range of years covered by measurements may result in underestimation or overestimation of exposure.