Development of a Crosswalk to Translate Italian Occupation Codes to ISCO-68 Codes.

In occupational epidemiology, job coding is an important-but time-consuming-step in assigning exposure. We implemented a tool (i.e. a crosswalk) to translate occupation codes from the Italian (ISTAT-CIP-91, n = 6319 five-digit job codes) to the International Standard Classification of Occupations (ISCO-68, n = 1881 five-digit job codes). The former is currently used in Italy for various purposes (e.g. in the National Mesothelioma Registry). The latter has been used in several studies on occupational cancers because it facilitates communication of results to the scientific community and, most importantly, because some job exposure matrices (JEMs) are based on international codes. Three authors created a table containing the crosswalk structure, providing an interpretation for each of the ISTAT-CIP-91 codes job descriptions and then manually recoding them according to ISCO-68. Two other authors independently revised it. The performance of the final version was assessed by comparison with results obtained by manual ISCO-68 coding performed in two previous case-control studies on asbestos and mesothelioma. More specifically, the automatically obtained ISCO-68 codes were merged with a JEM (DOM-JEM). The resulting individual asbestos exposure estimates (ever versus never exposed) were compared to those originally obtained (using the same DOM-JEM) from manual translation of ISTAT-CIP-91 to ISCO-68 (considered as the 'gold standard'). In the first study, among 159 peritoneal mesothelioma cases (400 job codes), Cohen's kappa was 0.91, sensitivity 0.95, and specificity 0.96. In the second study, among 716 pleural mesothelioma cases and controls (4400 job codes) kappa was 0.86, sensitivity 0.94, and specificity 0.91. Performance was better among in women. For men, performance was lower among cases than among controls (kappa 0.70, sensitivity 0.95, specificity 0.72 versus kappa 0.87, sensitivity 0.97, and specificity 0.92). In conclusion, the proposed tool allowed a rapid translation of thousands of job codes with good to excellent accuracy. The table containing ISTAT-CIP-91 codes and job descriptions and the corresponding ISCO-68 codes and job descriptions is made publicly available and can be freely used for epidemiological analyses in Italy and international collaborations.

Retrospective Exposure Assessment Methods Used in Occupational Human Health Risk Assessment: A Systematic Review.

As part of the assessment and management of chemical risk and occupational hygiene, retrospective exposure assessment (REA) to chemical agents can be defined as the estimate of exposure associated with a person's work history. The fundamental problem underlying the reconstruction of the exposure is that of transforming this type of information in quantitative terms to obtain an accurate estimate. REA can follow various approaches, some of which are technically complicated and both time and resource consuming. The aim of this systematic review is to present the techniques mainly used for occupational REA. In order to carry out this evaluation, a systematic review of the scientific literature was conducted. Forty-four studies were identified (published from 2010 to date) and analyzed. In exposure reconstruction studies, quantitative approaches should be preferable, especially when estimates will be used in the context of health impact assessment or epidemiology, although it is important to stress how, ideally, the experimental data available for the considered scenario should be used whenever possible as the main starting information base for further processing. To date, there is no single approach capable of providing an accurate estimate of exposure for each reasonably foreseeable condition and situation and the best approach generally depends on the level of information available for the specific case. The use of a combination of different reconstruction techniques can, therefore, represent a powerful tool for weighting and integrating data obtained through qualitative and quantitative approaches, in order to obtain the best possible estimate.