Heat stress is a major occupational health risk, particularly in hot regions such as Iran, where workers in labor-intensive industries. Comprehensive assessment requires both physiological and perceptual indicators to consider objective and subjective responses to heat exposure. This study aimed to identify and prioritize these indicators using fuzzy-based decision-making methods within the context of Iranian labor-intensive industries. A non-systematic literature review initially identified 38 potential heat stress indicators. The Fuzzy Delphi Method (FDM) was applied in three iterative rounds with 25 Iranian experts in occupational health, ergonomics, and heat stress assessment to obtain a consensus on the most relevant indicators, yielding 19 indicators (12 physiological and 7 perceptual). The Fuzzy Analytic Hierarchy Process (FAHP) was then used to prioritize these indicators through pairwise comparisons and Chang’s extent analysis approach. Sensitivity analysis (± 10% perturbation) was conducted to examine the robustness of the model results. The most influential physiological indicators were core body temperature (CBT; normalized weight = 0.164) and heart rate (HR; 0.143), while the top perceptual indicators were thermal sensation (TS; 0.256) and perceived exertion (PE; 0.218). Physiological indicators collectively accounted for 61% of the total weight compared with 39% for perceptual indicators. Sensitivity analysis confirmed the robustness of the rankings, with minimal variation (1.5–2.0%) under parameter perturbations. The integrated FDM–FAHP framework effectively handles uncertainty in expert judgments and provides a reliable tool for occupational heat stress assessment. The prioritized indicators can be incorporated into wearable monitoring technologies and workplace safety programs to reduce heat-related incidents and improve worker health protection in Iranian labor-intensive industries, with clear applicability to other workplaces at the world.
Mousavi et al. (Fri,) studied this question.
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