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Objective: In a previous study, the author used a Cox proportional hazards regression model to analyze the relationships between emergency transport data for heatstroke cases in Tokyo in 2025, meteorological factors, and urban aerosols, thereby identifying factors that alter the risk of heatstroke in an urban environment. While the analysis suggested a positive correlation between PM2.5 concentrations and the risk of heatstroke, this association was not statistically significant. The present study reports the results of an analysis that integrates data from 2023, 2024, and 2025. Method: Analysis was performed using a Cox proportional hazards regression model in which ambient temperature was incorporated as a parameter of the baseline hazard function. Result and Discussion: The results of the Cox proportional hazards regression analysis identified atmospheric pressure and relative humidity as positive predictors. Furthermore, an increase in PM2.5 levels was found to be statistically significantly associated with an elevated risk of heatstroke. Conversely, duration of sunshine, PM10 levels, and the cumulative number of days since June 1st were identified as negative predictors. PM2.5 contains numerous substances derived from combustion, which generate free radicals that are harmful to the human cardiopulmonary system. Consequently, it is thought that PM2.5 may increase the risk of heatstroke. In the present study, which integrated data from 2023, 2024, and 2025, PM2.5 concentration was identified as a statistically significant positive modifying factor. It should be noted, however, that while this study demonstrates an association, it does not establish a causal relationship. Conclusion: Further research was conducted on the relationship between PM2.5 and the risk of heatstroke, utilizing a larger number of cases. PM2.5 showed a positive correlation with the risk of heatstroke, and this association was statistically significant.
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Shigeru Suna (2026) studied this question.
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