No Single Heat Stress Index Fits Every Climate, Landmark Iranian Study Finds

As heat waves grow longer, hotter, and more frequent across the globe, the tools scientists use to measure how much the heat actually burdens the human body have quietly become a problem of their own. A new study published in Environmental and Sustainability Indicators by Seyed Mahdi Mousavi, Habibollah Dehghan, and Saeid Yazdanirad of Isfahan University of Medical Sciences delivers one of the most systematic answers yet to a deceptively simple question: which heat stress index should a city trust? The researchers built a climate-sensitive decision-support framework and tested it in three Iranian cities with sharply different climates, and their conclusion is striking. There is no universal champion. The best index for a humid Gulf port is not the best index for a dry mountain plateau, and choosing the wrong one can systematically misjudge the danger that heat poses to urban residents and outdoor workers.

The stakes are far from academic. Global mean air temperature has already risen by roughly 1.1 degrees Celsius, and urban areas suffer additional warming from the urban heat island effect, in which asphalt, concrete, and dense building fabric trap heat long after sunset. Epidemiological investigations in Paris, Chicago, and Shanghai have documented substantial spikes in heat-related mortality during extreme heat events, and global assessments estimate that around three billion people now experience heat stress conditions exceeding safe physiological thresholds. Against this backdrop, dozens of indices have been developed to translate raw meteorological variables such as air temperature, humidity, wind speed, and radiation into a single integrated value of human thermal load. They fall into four broad families: empirical indices like the Heat Index and Humidex, bioclimatic indices such as the Wet Bulb Globe Temperature, rational heat-balance indices like the Physiological Equivalent Temperature and the Universal Thermal Climate Index, and physiological strain indices such as Predicted Heat Strain.

The trouble, as comparative studies have repeatedly shown, is that these indices disagree. Work in humid Hong Kong, Singapore, and Guangzhou found that humidity-sensitive indices such as UTCI and the Heat Index best captured perceived thermal stress, while studies in arid Tehran, Phoenix, and Riyadh concluded that solar radiation and wind speed dominate thermal strain, favoring PET and WBGT. The same weather conditions can therefore land in different heat stress categories depending on which index is applied. Yet most urban climate and occupational health studies never justify their choice of index at all, defaulting to whatever is conventional in their region or discipline. Middle Eastern researchers tend to lean on WBGT because it is embedded in occupational guidelines, while European investigators often champion PET and UTCI. The new study set out to replace this habit with a transparent, reproducible method.

The framework unfolded in four stages across three carefully chosen cities: Abadan, a hot-humid city near the Persian Gulf; Isfahan, a hot-dry city at 1,570 meters altitude; and Gorgan, a temperate-humid city near the Caspian Sea. First, the team compiled a pool of twenty candidate indices through a systematic search of Scopus, Web of Science, PubMed, and Google Scholar. Second, they applied the Fuzzy Delphi Method, a structured consensus technique in which twenty-six experts with at least five years of experience in heat stress, thermal comfort, occupational health, or climatology rated each index on a five-point linguistic scale. The verbal judgments were converted into triangular fuzzy numbers, aggregated, and defuzzified using the center-of-gravity method. Only indices achieving a defuzzified score of at least 0.70 and sufficient expert consensus survived; exactly ten did, led by WBGT with 96.2 percent consensus, followed by PHS, UTCI, and PET, all above 88 percent. Simpler empirical indices clustered near the bottom of the accepted list.

Third, the researchers used the Fuzzy Analytic Hierarchy Process to rank the ten surviving indices against five evaluation criteria: physiological relevance, climatic sensitivity, outdoor applicability, data requirements, and scientific validation support. The expert panel judged physiological relevance the most important criterion, with a normalized weight of 0.370, followed by scientific validation support at 0.229 and climatic sensitivity at 0.210. Pairwise comparisons were performed separately for each city, yielding climate-specific global weights and rankings. The results were unambiguous. In steamy Abadan, WBGT took first place with a final weight of 0.178, followed by PHS and UTCI. In arid Isfahan, UTCI led at 0.171, ahead of PET and mPET. In temperate Gorgan, PET ranked first at 0.166, with UTCI and SET close behind. Across all three climates, the simplest empirical indices, the Heat Index and Humidex, languished near the bottom of the table.

Crucially, the team did not stop at expert opinion. They subjected the rankings to a one-at-a-time sensitivity analysis, perturbing each criterion weight by plus or minus 10, 20, and 30 percent while rescaling the remaining weights. The top-ranked index in every city survived every perturbation, and Spearman rank correlations between baseline and perturbed rankings ranged from 0.88 to 0.97, indicating that the climate-specific hierarchies are structurally embedded in the decision framework rather than artifacts of particular expert judgments. All pairwise comparison matrices also met the standard consistency threshold, with consistency ratios below 0.10, reinforcing confidence in the aggregated expert judgments.

The fourth and most novel stage brought real human bodies into the equation. Between April and September 2025, the researchers surveyed 300 adults, one hundred per city, recruited through stratified convenience sampling to represent walking, standing, and light work in streets, parks, and commercial areas. Calibrated instruments measured air temperature, humidity, wind speed, black globe temperature, and WBGT at roughly 1.1 meters above ground, the center of gravity of a standing adult, synchronized with each participant’s Thermal Sensation Vote on the standardized ASHRAE seven-point scale from minus three, cold, to plus three, hot. Perceived heat differed dramatically across the cities: the mean TSV was plus 2.10 in Abadan, where 68 percent of respondents reported feeling hot or very hot, compared with plus 1.52 in Isfahan and just plus 0.84 in Gorgan, where only 27 percent reached the hot end of the scale.

When the continuous index values were correlated against these field votes, the climate dependence of index performance became vivid. In Abadan, WBGT showed the strongest agreement with thermal sensation, a Spearman coefficient of 0.79, with PHS close behind at 0.74. In Isfahan, UTCI peaked at 0.76 and PET at 0.73. In Gorgan, PET led at 0.72, followed by UTCI at 0.69 and SET at 0.67. Grouped by category, physiological indices achieved a mean correlation of 0.70 and thermal comfort indices 0.68, while empirical indices trailed at 0.49. Most tellingly, when the expert-derived FAHP rankings were compared with rankings built purely from the perception data, the agreement was strong in all three cities, with Spearman coefficients of 0.82 in Abadan, 0.79 in Isfahan, and 0.81 in Gorgan, and the top three indices were identical in both rankings everywhere. The mean values of the top-ranked indices also rose monotonically across successive thermal sensation categories, showing they can discriminate progressive levels of perceived strain, an essential property for heat-warning systems.

The physiological logic behind these patterns is coherent. In humid climates, high moisture content of the air suppresses evaporative heat loss, so indices that explicitly track humidity-driven heat storage and sweat evaporation, like WBGT and PHS, track real strain best. In arid environments, intense solar radiation and wind dominate the energy balance, which is precisely what the radiation-sensitive, heat-balance indices UTCI and PET capture. In milder temperate-humid settings, severe physiological strain is less dominant and cumulative discomfort and behavioral adaptation matter more, favoring comfort-oriented indices that integrate energy balance with perceptual dimensions. The authors acknowledge limitations, including a predominantly Iranian expert panel, convenience sampling, a warm-season-only data window, and the omission of micro-scale urban morphology variables such as sky-view factor and vegetation shading. They call for extending the framework across seasons, adding urban form parameters, and testing dynamic indices under projected climate-change scenarios.

The practical message for city planners, public health authorities, and occupational safety bodies is direct: stop assuming one standard indicator fits everywhere. A heat-health warning system in a humid coastal city that relies on a dry-climate comfort index may understate danger precisely when evaporative cooling fails, while an arid inland city using a humidity-centric index may miss the dominant role of radiant heat. By fusing fuzzy expert consensus, multi-criteria weighting, sensitivity testing, and ground-truth human perception into a single transferable methodology, the study offers a template any city can adapt. As global warming pushes more urban populations past safe physiological thresholds, knowing which thermometer of human strain to trust may prove as important as the measurements themselves.

Subject of Research: Climate-sensitive prioritization of human heat stress indices in urban environments

Article Title: A climate-sensitive decision-support framework for prioritizing human heat stress indices: Integrating fuzzy Delphi, FAHP, and thermal perception in Abadan, Isfahan, and Gorgan, Iran

Article References: Mousavi, S. M., Dehghan, H., & Yazdanirad, S. (2026). A climate-sensitive decision-support framework for prioritizing human heat stress indices: Integrating fuzzy Delphi, FAHP, and thermal perception in Abadan, Isfahan, and Gorgan, Iran. Environmental and Sustainability Indicators, 32, Article 101529. https://doi.org/10.1016/j.indic.2026.101529

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101529

Keywords: heat stress, thermal comfort, WBGT, UTCI, PET, urban climate, Fuzzy Delphi, FAHP, thermal sensation, climate change, Iran, decision support