Matgéné: a program to develop job-exposure matrices in the general population in France

Matgéné is a program to develop job-exposure matrices (JEMs) adapted to the general population in France for the period since 1950. The aim is to create retrospective exposure assessment tools for estimating the prevalence of occupational exposure to various agents that can then be correlated to health-related parameters.

JEMs were drawn up by a team of six industrial hygienists who based their assessments on available occupational measurement, economic and statistical data, and several thousand job descriptions from epidemiological studies performed in France since 1984. Each JEM is specific to one agent, assessing exposure for a set of homogeneous combinations (occupation × activity × period) according to two occupational classifications (ISCO 1968 and PCS 1994) and one economic activities classification (NAF 2000). The cells of the JEM carry an estimate of the probability and level of exposure. Level is estimated by the duration and intensity of exposure-linked tasks or by description of the tasks when exposure measurement data are lacking for the agent in question. The JEMs were applied to a representative sample of the French population in 2007, and prevalence for each exposure was estimated in various population groups. All documents and data are available on a dedicated website.

By the end of 2010, 18 JEMs have been developed and eight are under development, concerning a variety of chemical agents: organic and mineral dust, mineral fibers, and solvents. By implementation in the French population, exposure prevalences were calculated at different dates and for complete careers, and attributable risk fractions were estimated for certain pathologies. Some of these results were validated by comparison with those of other programs.

Initial Matgéné JEMs results are in agreement with the French and international literature, thus validating the methodology. Exposure estimates precision, however, vary between agents and according to the amount of exposure measurement data available. These JEMs are important epidemiological tools, and improving their quality will require investment in occupational health data harvesting, especially in the case of low-level exposures.