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Using a representative sample of workers for constructing the SUMEX French general population based job-exposure matrix
  1. A Guéguen,
  2. M Goldberg,
  3. S Bonenfant,
  4. J C Martin
  1. INSERM Unité 88-IFR 69, Hôpital National de Saint-Maurice, 14, rue du Val d’Osne, 94415 Saint-Maurice Cedex, France
  1. Correspondence to:
 Prof. M Goldberg
 INSERM Unité 88-IFR 69, Hôpital National de Saint-Maurice, 14, rue du Val d’Osne, 94415 Saint-Maurice Cedex, France;


Background: Job-exposure matrices (JEMs) applicable to the general population are usually constructed by using only the expertise of specialists.

Aims: To construct a population based JEM for chemical agents from data based on a sample of French workers for surveillance purposes.

Methods: The SUMEX job-exposure matrix was constructed from data collected via a cross-sectional survey of a sample of French workers representative of the main economic sectors through the SUMER-94 survey: 1205 occupational physicians questioned 48 156 workers, and inventoried exposure to 102 chemicals. The companies’ economic activities and the workers’ occupations were coded according to the official French nomenclatures. A segmentation method was used to construct job groups that were homogeneous for exposure prevalence to chemical agents. The matrix was constructed in two stages: consolidation of occupations according to exposure prevalence; and establishment of exposure indices based on individual data from all the subjects in the sample.

Results: An agent specific matrix could be constructed for 80 of the chemicals. The quality of the classification obtained for each was variable: globally, the performance of the method was better for less specific and therefore more easy to assess agents, and for exposures specific to certain occupations.

Conclusions: Software has been developed to enable the SUMEX matrix to be used by occupational physicians and other prevention professionals responsible for surveillance of the health of the workforce in France.

  • CART, classification and regression tree
  • JEM, job-exposure matrix
  • NAF, Nomenclature d’Activités Française
  • PBB, polybrominated biphenyl
  • PCB, polychlorinated biphenyl
  • PCS, Nomenclature des Professions et Catégories Socioprofessionnelles
  • TLV, threshold limit value
  • chemicals
  • occupational exposure
  • segmentation methods

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