{
  "abstract": "Introduction Quantitative job-exposure matrices (JEMs) have been developed to assign exposure using International Standard Classification of Occupations (ISCO)-68 coded job information. For extended compatibility with the less detailed ISCO-88 coding, a quantitative JEM using the same underlying model was developed. We compared exposure-response relationships between cumulative respirable crystalline silica (RCS) and lung cancer risk using a quantitative JEM based on ISCO-88 (88-JEM) and ISCO-68 (68-JEM).Methods Based on a common set of approximately 15 000 RCS measurements, job-specific, region-specific and time-specific exposure levels were estimated for the 88-JEM and the 68-JEM and linked to participants’ job histories. Exposure-response relationships in an international lung cancer case-control study were analysed by logistic regression and generalised additive models.Results The 88-JEM and the 68-JEM yielded similar RCS-lung cancer associations, with elevated lung cancer risks across each cumulative exposure quartile. The 88-JEM exhibited a minor not statistically significant upward bend in the exposure-response curve at higher exposures.Conclusion To accurately detect associations between disease risk and occupational exposure, quantitative JEMs can be applied in community-based studies that provide job histories in either ISCO-88 or ISCO-68.",
  "authors": [
    {
      "affiliations": [
        "Utrecht University Institute for Risk Assessment Sciences, IRAS Utrecht University"
      ],
      "name": "Johan Ohlander"
    },
    {
      "affiliations": [
        "Utrecht University Institute for Risk Assessment Sciences, IRAS Utrecht University"
      ],
      "name": "Susan Peters"
    },
    {
      "affiliations": [
        "Utrecht University Institute for Risk Assessment Sciences, IRAS Utrecht University"
      ],
      "name": "Hans Kromhout"
    }
  ],
  "title": "8291794 A less detailed job axis in a quantitative job-exposure matrix results in a similar exposure-response association",
  "uid": "f479456c-1d1c-5ea4-b647-a3875e0abd21"
}