Development of an asthma specific job exposure matrix and its application in the epidemiological study of genetics and environment in asthma (EGEA)

Objectives-To develop a method suitable for estimating exposure risks in po pulation studies of asthma from job titles and international codes, by comb ining a new job exposure matrix (JEM) with the expert judgement approach. T he method was applied in the French epidemiological study of the genetics a nd environment in asthma (EGEA). Methods-The JEM contains 22 exposure groups including 18 high risk groups b ased on known risk factors for occupational asthma, divided into high molec ular weight agents, low molecular weight agents, and mixed environments. Af ter applying the JEM to job codes, exposure estimates for each subject were reevaluated by examining job title texts. Three high risk exposure estimat es for asthma were compared: firstly, applying the JEM to original codes (f rom different coders in each study centre); secondly, applying the JEM to r evised codes (from one experienced coder); and thirdly, after reviewing JEM exposure estimates in the light of job title texts. Results-The study comprised 173 cases with asthma and 285 controls (age 18- 65). Odds ratios (ORs) for asthma for high risk jobs were 1.0 (95% confiden ce interval (95% CI) 0.6 to 1.7), applying the JEM to original codes; 1.4 ( 95% CI 0.8 to 2.3), applying the JEM to revised codes; and 1.7 (95% CI 1.1 to 2.7), applying the JEM and subsequently re-evaluating exposure estimates from job title texts. Asthma ORs were 1.4 (95% CI 0.6 to 2.9) for high mol ecular weight agents, 2.3 (95% CI 1.2 to 4.4) for low molecular weight agen ts, and 2.1 (95% CI 0.9 to 5.2) for mixed environments. Conclusions-This asthma JEM, when enhanced by expert re-evaluation of expos ure estimates from job title texts, may be a useful tool in general populat ion studies of asthma. In this study, a 1.7-fold increase in prevalence odd s of high risk exposures was found among asthmatic workers compared with co ntrols, with risk magnitude varying for different classes of exposure.