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

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. 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.

Keywords: Decision rules; Occupational exposure assessment; Population-based studies.

Figure 1.

Example of decision rules applied to estimate the probability of exposure to diesel engine exhaust from a questionnaire for jobs in the heavy construction industry, based on work location and proximity to heavy equipment (HE). The terminal nodes at the bottom indicate the rule-assigned probability (P; 0: unexposed; 1: low; 2: medium; 3: high) and intensity (I; 1: 0.25 to <5; 2: 5 to <20; 3: ≥20 μg/m³ respirable elemental carbon). The asterisk denotes time period-specific probability: low for <1940, medium for 1940–1949, and high for ≥1950.