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Using Decision Rules to Assess Occupational Exposure in Population-Based Studies

  • Occupational Health (K Applebaum and M Friesen, Section Editors)
  • Published:
Current Environmental Health Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Population-based studies increasingly link task-based occupational questionnaire responses collected from subjects to exposure estimates via transparent, programmable decision rules. We reviewed recent applications and methodological developments of rule-based approaches.

Recent Findings

Agent-specific decision rules require interviews incorporating work-task-based questions. Some studies have developed rules before the interviews took place, while others developed rules after the interviews were completed. Agreement between rule-based estimates and exposures assigned using job-by-job expert review were generally moderate to good (Kappa = 0.4–0.8). Rules providing quantitative intensity levels using measurement data or that integrate multiple independent exposure sources for the same job represent further advances to improve the characterization of occupational exposures in population studies.

Summary

Decision rules have provided transparent and reproducible assessments, reduce job-by-job review, and facilitate sensitivity analyses in epidemiologic studies. Future studies should consider the development of decision rules concurrent with the questionnaire design to facilitate occupational exposure assessment efforts.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Fritschi L, Sadkowsky T, Benke GP, Thomson A, Glass DC. Triaging jobs in a community-based case–control study to increase efficiency of the expert occupational assessment method. Ann Occup Hyg. 2012;56(4):458–65. https://doi.org/10.1093/annhyg/mer117.

    Article  CAS  PubMed  Google Scholar 

  2. Teschke K, Olshan AF, Daniels JL, De Roos AJ, Parks CG, Schulz M, et al. Occupational exposure assessment in case-control studies: opportunities for improvement. Occup Environ Med. 2002;59(9):575–94. https://doi.org/10.1136/oem.59.9.575.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. • Ge CB, Friesen MC, Kromhout H, Peters S, Rothman N, Lan Q, et al. Use and reliability of exposure assessment methods in occupational case-control studies in the general population: past, present, and future. Ann Work Expo Health. 2018;62(9):1047–63. https://doi.org/10.1093/annweh/wxy080 This paper provides a comprehensive review of retrospective exposure assessment methods used in population studies over the last 40 years.

    Article  PubMed  Google Scholar 

  4. Friesen M, Lavoué J, Teschke K, Van Tongeren M. Occupational exposure assessment in industry- and population-based epidemiological studies. In: Nieuwenhuijsen MJ, editor. Exposure Assessment in Environmental Epidemiology, 2nd edition. Oxford: Oxford University Press; 2015. p. 139–62.

    Chapter  Google Scholar 

  5. Siemiatycki J. Exposure assessment in community-based studies of occupational cancer. Occup Hyg. 1996;3(1):41–58.

    CAS  Google Scholar 

  6. Kromhout H. Commentary. Occup Environ Med. 2002;59(9):594.

    Google Scholar 

  7. • Fritschi L, Friesen MC, Glass D, Benke G, Girschik J, Sadkowsky T. OccIDEAS: retrospective occupational exposure assessment in community-based studies made easier. J Environ Public Health. 2009;2009(957023):5. https://doi.org/10.1155/2009/957023 This study describes the theoretical framework and the development of decision rules and job-specific modules of the OccIDEAS approach.

    Article  CAS  Google Scholar 

  8. •• Pronk A, Stewart PA, Coble JB, Katki HA, Wheeler DC, Colt JS, et al. Comparison of two expert-based assessments of diesel exhaust exposure in a case–control study: programmable decision rules versus expert review of individual jobs. Occup Environ Med. 2012;69(10):752–8. https://doi.org/10.1136/oemed-2011-100524 This study contains the earliest published rules used to assess retrospective occupational exposures for an existing study. It describes the development of exposure scenarios and decision rules to estimate exposure to diesel engine exhaust, and includes a comparison with job-by-job expert review.

    Article  PubMed  PubMed Central  Google Scholar 

  9. • Friesen MC, Wheeler DC, Vermeulen R, Locke SJ, Zaebst DD, Koutros S, et al. Combining decision rules from classification tree models and expert assessment to estimate occupational exposure to diesel exhaust for a case-control study. Ann Occup Hyg. 2016;60(4):467–78. https://doi.org/10.1093/annhyg/mev095 This study describes the transposition of decision rules between countries (United States and Spain) and the use of reliability assessment to prioritize jobs requiring additional expert review.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Fidler AT, Baker EL, Letz RE. Estimation of long term exposure to mixed solvents from questionnaire data: a tool for epidemiological investigations. Br J Ind Med. 1987;44(2):133–41.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Peters S, Glass DC, Reid A, de Klerk N, Armstrong BK, Kellie S, et al. Parental occupational exposure to engine exhausts and childhood brain tumors. Int J Cancer. 2013;132(12):2975–9. https://doi.org/10.1002/ijc.27972.

    Article  CAS  PubMed  Google Scholar 

  12. Rai R, Glass DC, Heyworth JS, Saunders C, Fritschi L. Occupational exposures to engine exhausts and other PAHs and breast cancer risk: a population-based case-control study. Am J Ind Med. 2016;59(6):437–44. https://doi.org/10.1002/ajim.22592.

    Article  PubMed  Google Scholar 

  13. Greenop KR, Peters S, Bailey HD, Fritschi L, Attia J, Scott RJ, et al. Exposure to pesticides and the risk of childhood brain tumors. Cancer Causes Control. 2013;24(7):1269–78. https://doi.org/10.1007/s10552-013-0205-1.

    Article  PubMed  Google Scholar 

  14. Buitenhuis W, Fritschi L, Thomson A, Glass D, Heyworth J, Peters S. Occupational exposure to ionizing radiation and risk of breast cancer in Western Australia. J Occup Environ Med. 2013;55(12):1431–5. https://doi.org/10.1097/JOM.0b013e3182a7e692.

    Article  CAS  PubMed  Google Scholar 

  15. Fritschi L, Erren TC, Glass DC, Girschik J, Thomson AK, Saunders C, et al. The association between different night shiftwork factors and breast cancer: a case–control study. Br J Cancer. 2013;109(9):2472–80. https://doi.org/10.1038/bjc.2013.544.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Fritschi L, Behrens T, Mester B. Sharing JEMS in occupational cohort studies: what if measurement data are not available? Occup Environ Med. 2012;69(10):770–77770. https://doi.org/10.1136/oemed-2012-100908.

    Article  PubMed  Google Scholar 

  17. Peters S, Glass DC, Greenop KR, Armstrong BK, Kirby M, Milne E, et al. Childhood brain tumours: associations with parental occupational exposure to solvents. Br J Cancer. 2014;111(5):998–1003. https://doi.org/10.1038/bjc.2014.358.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Glass DC, Heyworth J, Thomson AK, Peters S, Saunders C, Fritschi L. Occupational exposure to solvents and risk of breast cancer. Am J Ind Med. 2015;58(9):915–22. https://doi.org/10.1002/ajim.22478.

    Article  CAS  PubMed  Google Scholar 

  19. • Peters S, Glass DC, Milne E, Fritschi L. Aus-ALL consortium. Rule-based exposure assessment versus case-by-case expert assessment using the same information in a community-based study. Occup Environ Med. 2014;71(3):215–9. https://doi.org/10.1136/oemed-2013-101699 This study compares exposures assigned using decision rule to those from job-by-job review for solvents, pesticides, and diesel exhaust. It found higher agreement for lifetime cumulative exposure than for individual jobs and for jobs with interview data.

    Article  PubMed  Google Scholar 

  20. Dopart PJ, Locke SJ, Cocco P, Bassig BA, Josse PR, Stewart PA et al. Estimation of source-specific occupational benzene exposure in a population-based case control study of non-Hodgkin lymphoma. Ann Work Exp Health. In press.

  21. Friesen MC, Pronk A, Wheeler DC, Chen Y-C, Locke SJ, Zaebst DD, et al. Comparison of algorithm-based estimates of occupational diesel exhaust exposure to those of multiple independent raters in a population-based case–control study. Ann Occup Hyg. 2013;57(4):470–81. https://doi.org/10.1093/annhyg/mes082.

    Article  CAS  PubMed  Google Scholar 

  22. • Wheeler DC, Burstyn I, Vermeulen R, Yu K, Shortreed SM, Pronk A, et al. Inside the black box: starting to uncover the underlying decision rules used in a one-by-one expert assessment of occupational exposure in case-control studies. Occup Environ Med. 2013;70(3):203–10. https://doi.org/10.1136/oemed-2012-100918 This study describes the application of classification and regression tree models to job-by-job expert assessment data to reconstruct the internal decision rules of experts.

    Article  PubMed  Google Scholar 

  23. Wheeler DC, Archer KJ, Burstyn I, Yu K, Stewart PA, Colt JS, et al. Comparison of ordinal and nominal classification trees to predict ordinal expert-based occupational exposure estimates in a case–control study. Ann Occup Hyg. 2015;59(3):324–35. https://doi.org/10.1093/annhyg/meu098.

    Article  PubMed  Google Scholar 

  24. •• Callahan CL, Locke SJ, Dopart PJ, Stewart PA, Schwartz K, Ruterbusch JJ, et al. Decision rule approach applied to estimate occupational lead exposure in a case-control study of kidney cancer. Am J Ind Med. 2018;61(11):901–10. https://doi.org/10.1002/ajim.22912 This is the first population-based study to describe the development of source-specific decision rules to assign retrospective occupational exposures.

    Article  PubMed  Google Scholar 

  25. Park D-U, Colt JS, Baris D, Schwenn M, Karagas MR, Armenti KR, et al. Estimation of the probability of exposure to machining fluids in a population-based case-control study. J Occup Environ Hyg. 2014;11(11):757–70. https://doi.org/10.1080/15459624.2014.918984.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Friesen MC, Park D-U, Colt JS, Baris D, Schwenn M, Karagas MR, et al. Developing estimates of frequency and intensity of exposure to three types of metalworking fluids in a population-based case–control study of bladder cancer. Am J Ind Med. 2014;57(8):915–27. https://doi.org/10.1002/ajim.22328.

    Article  PubMed  PubMed Central  Google Scholar 

  27. • Bourgkard E, Wild P, Gonzalez M, Févotte J, Penven E, Paris C. Comparison of exposure assessment methods in a lung cancer case-control study: performance of a lifelong task-based questionnaire for asbestos and PAHs. Occup Environ Med. 2013;70(12):884–91. https://doi.org/10.1136/oemed-2013-101467 This is the only population-based study comparing the exposures assigned using several assessment approaches that included task-based decision rules.

    Article  CAS  PubMed  Google Scholar 

  28. Wild P, Schill W, Bourgkard E, Drescher K, Gonzalez M, Paris C. The 2-phase case–control design: an efficient way to use expert-time. Scand J Work Environ Health. 2016;42(2):162–9. https://doi.org/10.5271/sjweh.3547.

  29. • Dopart PJ, Friesen MC. New opportunities in exposure assessment of occupational epidemiology: use of measurements to aid exposure reconstruction in population-based studies. Curr Environ Health Rep. 2017;4(3):355–63. https://doi.org/10.1007/s40572-017-0153-0 This paper reviews sources of workplace measurement data and their applications in exposure assessment for population-based studies, including for the development of decision rules.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Koh D-H, Locke SJ, Chen Y-C, Purdue MP, Friesen MC. Lead exposure in US worksites: a literature review and development of an occupational lead exposure database from the published literature. Am J Ind Med. 2015;58(6):605–16. https://doi.org/10.1002/ajim.22448.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Locke SJ, Deziel NC, Koh D-H, Graubard BI, Purdue MP, Friesen MC. Evaluating predictors of lead exposure for activities disturbing materials painted with or containing lead using historic published data from U.S. workplaces. Am J Ind Med. 2017;60(2):189–97. https://doi.org/10.1002/ajim.22679.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Friesen MC, Locke SJ, Tornow C, Chen Y-C, Koh D-H, Stewart PA, et al. Systematically extracting metal- and solvent-related occupational information from free-text responses to lifetime occupational history questionnaires. Ann Occup Hyg. 2014;58(5):612–24. https://doi.org/10.1093/annhyg/meu012.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Friesen MC, Shortreed SM, Wheeler DC, Burstyn I, Vermeulen R, Pronk A, et al. Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies. Ann Occup Hyg. 2015;59(4):455–66. https://doi.org/10.1093/annhyg/meu101.

    Article  PubMed  Google Scholar 

  34. Siemiatycki J. Risk factors for cancer in the workplace. Boca Raton: CRC Press; 1991.

    Google Scholar 

  35. Stewart PA, Stewart WF, Heineman EF, Dosemeci M, Linet M, Inskip PD. A novel approach to data collection in a case-control study of cancer and occupational exposures. Int J Epidemiol. 1996;25(4):744–52. https://doi.org/10.1093/ije/25.4.744.

    Article  CAS  PubMed  Google Scholar 

  36. Behrens T, Mester B, Fritschi L. Sharing the knowledge gained from occupational cohort studies: a call for action. Occup Environ Med. 2012;69(6):444–8. https://doi.org/10.1136/oemed-2011-100305.

    Article  PubMed  Google Scholar 

  37. Macfarlane E, Benke G, Sim MR, Fritschi L. OccIDEAS: an innovative tool to assess past Asbestos exposure in the Australian mesothelioma registry. Saf Health Work. 2012;3(1):71–6. https://doi.org/10.5491/SHAW.2012.3.1.71.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Fernandez RC, Peters S, Carey RN, Davies MJ, Fritschi L. Assessment of exposure to shiftwork mechanisms in the general population: the development of a new job-exposure matrix. Occup Environ Med. 2014;71(10):723–9. https://doi.org/10.1136/oemed-2014-102101.

    Article  PubMed  Google Scholar 

  39. Walasa WM, Carey RN, Si S, Fritschi L, Heyworth JS, Fernandez RC, et al. Association between shiftwork and the risk of colorectal cancer in females: a population-based case–control study. Occup Environ Med. 2018;75(5):344–50. https://doi.org/10.1136/oemed-2017-104657.

    Article  PubMed  Google Scholar 

  40. Friesen MC, Lan Q, Ge C, Locke SJ, Hosgood D, Fritschi L, et al. Evaluation of automatically assigned job-specific interview modules. Ann Occup Hyg. 2016;60(7):885–99. https://doi.org/10.1093/annhyg/mew029.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Carey RN, Driscoll TR, Peters S, Glass DC, Reid A, Benke G, et al. Estimated prevalence of exposure to occupational carcinogens in Australia (2011–2012). Occup Environ Med. 2014;71(1):55–62. https://doi.org/10.1136/oemed-2013-101651.

    Article  PubMed  Google Scholar 

  42. Carey RN, Hutchings SJ, Rushton L, Driscoll TR, Reid A, Glass DC, et al. The future excess fraction of occupational cancer among those exposed to carcinogens at work in Australia in 2012. Cancer Epidemiol. 2017;47:1–6. https://doi.org/10.1016/j.canep.2016.12.009.

    Article  PubMed  Google Scholar 

  43. Soeberg MJ, Leigh J, van Zandwijk N. Malignant mesothelioma in Australia 2015: current incidence and asbestos exposure trends. J Toxicol Environ Health Part B. 2016;19(5–6):173–89. https://doi.org/10.1080/10937404.2016.1194254.

    Article  CAS  Google Scholar 

  44. Fritschi L, Crewe J, Darcey E, Reid A, Glass DC, Benke GP, et al. The estimated prevalence of exposure to asthmagens in the Australian workforce, 2014. BMC Pulm Med. 2016;16(1):48. https://doi.org/10.1186/s12890-016-0212-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. El-Zaemey S, Carey RN, Darcey E, Reid A, Glass DC, Benke GP, et al. Prevalence of occupational exposure to asthmagens derived from animals, fish and/or shellfish among Australian workers. Occup Environ Med. 2018;75(4):310–6. https://doi.org/10.1136/oemed-2017-104459.

    Article  PubMed  Google Scholar 

  46. El-Zaemey S, Carey RN, Darcey E, Reid A, Glass DC, Driscoll TR, et al. The prevalence of exposure to high molecular weight asthmagens derived from plants among workers in Australia. Am J Ind Med. 2018;61(10):824–30. https://doi.org/10.1002/ajim.22903.

    Article  CAS  PubMed  Google Scholar 

  47. El-Zaemey S, Glass D, Fritschi L, Darcey E, Carey R, Driscoll T, et al. Isocyanates in Australia: current exposure to an old hazard. J Occup Environ Hyg. 2018;15(7):527–30. https://doi.org/10.1080/15459624.2018.1461221.

    Article  CAS  PubMed  Google Scholar 

  48. Lewkowski K, Heyworth JS, Li IW, Williams W, McCausland K, Gray C, et al. Exposure to noise and ototoxic chemicals in the Australian workforce. Occup Environ Med. 2019;76(5):341–8. https://doi.org/10.1136/oemed-2018-105471.

    Article  PubMed  Google Scholar 

  49. •• Lewkowski K, McCausland K, Heyworth JS, Li IW, Williams W, Fritschi L. Questionnaire-based algorithm for assessing occupational noise exposure of construction workers. Occup Environ Med. 2018;75(3):237–42. https://doi.org/10.1136/oemed-2017-104381 This study represents the first validation of exposures assigned by decision rules. Using a subset of recent construction jobs for which noise dosimetry measurements were collected, the sensitivity and specificity of OccIDEAS to identify jobs exposed above the Australian noise exposure limit was 83% and 69%, respectively.

    Article  PubMed  Google Scholar 

  50. • Florath I, Glass DC, Rhazi MS, Parent ME, Fritschi L. Inter-rater agreement between exposure assessment using automatic algorithms and using experts. Ann Work Exp Health. 2018;63(1):45–53. https://doi.org/10.1093/annweh/wxy084 This study compared exposures assigned using decision rules to those assigned by two experts, with one expert involved in developing the rules, and the other expert being independent. It also showed higher agreement using the consensus rating of the two experts.

    Article  Google Scholar 

  51. Abbas Virji M, Woskie SR, Pepper LD. Task-based lead exposures and work site characteristics of bridge surface preparation and painting contractors. J Occup Environ Hyg. 2009;6(2):99–112. https://doi.org/10.1080/15459620802615772.

    Article  CAS  PubMed  Google Scholar 

  52. Susi P, Goldberg M, Barnes P, Stafford E. The use of a task-based exposure assessment model (T-BEAM) for assessment of metal fume exposures during welding and thermal cutting. Appl Occup Environ Hyg. 2000;15(1):26–38.

    Article  CAS  PubMed  Google Scholar 

  53. Seixas NS, Sheppard L, Neitzel R. Comparison of task-based estimates with full-shift measurements of noise exposure. AIHA J. 2003;64(6):823–9. https://doi.org/10.1080/15428110308984878.

    Article  Google Scholar 

  54. Su F-C, Friesen MC, Stefaniak AB, Henneberger PK, LeBouf RF, Stanton ML, et al. Exposures to volatile organic compounds among healthcare workers: modeling the effects of cleaning tasks and product use. Ann Work Exp Health. 2018;62(7):852–70. https://doi.org/10.1093/annweh/wxy055.

    Article  CAS  Google Scholar 

  55. Quinot C, Dumas O, Henneberger P, Varraso R, Wiley A, Speizer F, et al. Development of a job-task-exposure matrix to assess occupational exposure to disinfectants among US nurses. Occup Environ Med. 2017;74(2):130–7. https://doi.org/10.1136/oemed-2016-103606.

    Article  CAS  PubMed  Google Scholar 

  56. Benke G, Sim M, Fritschi L, Aldred G. Beyond the job exposure matrix (JEM): the task exposure matrix (TEM). Ann Occup Hyg. 2000;44(6):475–82. https://doi.org/10.1093/annhyg/44.6.475.

    Article  CAS  PubMed  Google Scholar 

  57. Hyland RA, Yates DH, Benke G, Sim M, Johnson AR. Occupational exposure to asbestos in New South Wales, Australia (1970–1989): development of an asbestos task exposure matrix. Occup Environ Med. 2010;67(3):201–6. https://doi.org/10.1136/oem.2008.039347.

    Article  CAS  PubMed  Google Scholar 

  58. Dick FD, Semple SE, van Tongeren M, Miller BG, Ritchie P, Sherriff D, et al. Development of a task-exposure matrix (TEM) for pesticide use (TEMPEST). Ann Occup Hyg. 2010;54(4):443–52. https://doi.org/10.1093/annhyg/meq014.

    Article  CAS  PubMed  Google Scholar 

  59. Carles C, Bouvier G, Lebailly P, Baldi I. Use of job-exposure matrices to estimate occupational exposure to pesticides: a review. J Expo Sci Environ Epidemiol. 2017;27(2):125–40. https://doi.org/10.1038/jes.2016.25.

    Article  CAS  PubMed  Google Scholar 

  60. van der Mark M, Vermeulen R, Nijssen PCG, Mulleners WM, Sas AMG, van Laar T, et al. Occupational exposure to pesticides and endotoxin and Parkinson disease in the Netherlands. Occup Environ Med. 2014;71(11):757–64. https://doi.org/10.1136/oemed-2014-102170.

    Article  PubMed  Google Scholar 

  61. Vila J, Turner MC, Gracia-Lavedan E, Figuerola J, Bowman JD, Kincl L, et al. Occupational exposure to high-frequency electromagnetic fields and brain tumor risk in the INTEROCC study: an individualized assessment approach. Environ Int. 2018;119:353–65. https://doi.org/10.1016/j.envint.2018.06.038.

    Article  PubMed  Google Scholar 

  62. Gérin M, Fletcher AC, Gray C, Winkelmann R, Boffetta P, Simonato L. Development and use of a welding process exposure matrix in a historical prospective study of lung cancer risk in European welders. Int J Epidemiol. 1993;22(Suppl 2):S22–8.

    Article  PubMed  Google Scholar 

  63. Lillienberg L, Zock JP, Kromhout H, Plana E, Jarvis D, Torén K, et al. A population-based study on welding exposures at work and respiratory symptoms. Ann Occup Hyg. 2008;52(2):107–15. https://doi.org/10.1093/annhyg/mem063.

    Article  CAS  PubMed  Google Scholar 

  64. Semple SE, Dick F, Cherrie JW. Exposure assessment for a population-based case-control study combining a job-exposure matrix with interview data. Scand J Work Environ Health. 2004;30(3):241–8. https://doi.org/10.2307/40968782.

    Article  PubMed  Google Scholar 

  65. Purdue MP, Stewart PA, Friesen MC, Colt JS, Locke SJ, Hein MJ, et al. Occupational exposure to chlorinated solvents and kidney cancer: a case–control study. Occup Environ Med. 2017;74(4):268–74. https://doi.org/10.1136/oemed-2016-103849.

    Article  PubMed  Google Scholar 

  66. Callahan CL, Stewart PA, Friesen MC, Locke S, De Roos AJ, Cerhan JR, et al. Case-control investigation of occupational exposure to chlorinated solvents and non-Hodgkin’s lymphoma. Occup Environ Med. 2018;75(6):415–20. https://doi.org/10.1136/oemed-2017-104890.

    Article  PubMed  Google Scholar 

  67. Sauvé J-F, Lavoué J, Nadon L, Lakhani R, Senhaji Rhazi M, Bourbonnais R, et al. A hybrid expert approach for retrospective assessment of occupational exposures in a population-based case-control study of cancer. Environ Health. 2019;18(1):14. https://doi.org/10.1186/s12940-019-0451-0.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Black J, Benke G, Smith K, Fritschi L. Artificial neural networks and job-specific modules to assess occupational exposure. Ann Occup Hyg. 2004;48(7):595–600. https://doi.org/10.1093/annhyg/meh064.

    Article  PubMed  Google Scholar 

  69. García AM, González-Galarzo MC, Kauppinen T, Delclos GL, Benavides FG. A job-exposure matrix for research and surveillance of occupational health and safety in Spanish workers: MatEmESp. Am J Ind Med. 2013;56(10):1226–38. https://doi.org/10.1002/ajim.22213.

    Article  PubMed  Google Scholar 

  70. Fritschi L, Nadon L, Benke G, Lakhani R, Latreille B, Parent M-É, et al. Validation of expert assessment of occupational exposures. Am J Ind Med. 2003;43(5):519–22. https://doi.org/10.1002/ajim.10208.

    Article  PubMed  Google Scholar 

  71. Chen YC, Coble JB, Deziel NC, Ji BT, Xue S, Lu W, et al. Reliability and validity of expert assessment based on airborne and urinary measures of nickel and chromium exposure in the electroplating industry. J Expo Sci Environ Epidemiol. 2014;24(6):622–8. https://doi.org/10.1038/jes.2014.22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. DellaValle CT, Purdue MP, Ward MH, Locke SJ, Stewart PA, De Roos AJ, et al. Validity of expert assigned retrospective estimates of occupational polychlorinated biphenyl exposure. Ann Occup Hyg. 2015;59(5):609–15. https://doi.org/10.1093/annhyg/mev001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Sauvé J, Ramsay J, Locke S, Dopart P, Josse P, Zaebst D et al. Validity of retrospective occupational exposure estimates of lead and manganese in a case-control study. Occup Environ Med. https://doi.org/10.1136/oemed-2019-105744.

  74. Callahan CL, Friesen MC, Locke SJ, Dopart PJ, Stewart PA, Schwartz K, et al. Case-control investigation of occupational lead exposure and kidney cancer. Occup Environ Med. 2019;76:433–40. https://doi.org/10.1136/oemed-2018-105327.

    Article  PubMed  Google Scholar 

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Funding

This work was supported by the Intramural Research Programs of the Division of Cancer Epidemiology and Genetics, National Cancer Institute.

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  1. Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, 20850, USA

    Jean-François Sauvé & Melissa C. Friesen

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  1. Jean-François Sauvé
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Correspondence to Jean-François Sauvé.

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Sauvé, JF., Friesen, M.C. Using Decision Rules to Assess Occupational Exposure in Population-Based Studies. Curr Envir Health Rpt 6, 148–159 (2019). https://doi.org/10.1007/s40572-019-00240-w

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