Impact of Maximum Air Temperature on Ambulance Transports Owing to Heat Stroke During Spring and Summer in Tottori Prefecture, Japan: A Time-stratified Case-crossover Analysis.

BACKGROUND: The frequency and intensity of hot weather have increased. In Japan, there have been many studies of the relationship between ambulance transports owing to heat stroke (ATHS) and high air temperature in the summer season. However, there have been very few reports focusing on ATHS in spring. Therefore, we investigated the effect of the maximum air temperature on ATHS not only in summer but also in spring, to help with development of effective measures to prevent heat stroke. METHODS: We obtained daily ATHS and meteorological data from April to September in 2017 in Tottori Prefecture. We used a time-stratified case-crossover method for data analysis. RESULTS: A total 382 cases of ATHS were identified from April to September in 2017 in Tottori. The number of cases was highest in July, followed by August and May. Maximum air temperature was significantly linked to ATHS. The risk of ATHS was increased 1.13 times when maximum air temperature rose by 1°C. In summer, the risk on extremely hot days (maximum air temperature ≥ 35°C) increased by 5.55 times or more compared with that on days below 30 °C (< 30°C). The risk was approximately four times greater on hot days (≥ 30°C and < 35°C) than that on relatively cooler days (< 30°C) during the spring months of April through May. CONCLUSION: Maximum air temperature was significantly linked to ATHS. It is necessary to pay particular attention to heat stroke prevention not only on extremely hot days in summer but also on hot days in the spring.

Prediction of health effects of cross-border atmospheric pollutants using an aerosol forecast model.

Health effects of cross-border air pollutants and Asian dust are of significant concern in Japan. Currently, models predicting the arrival of aerosols have not investigated the association between arrival predictions and health effects. We investigated the association between subjective health symptoms and unreleased aerosol data from the Model of Aerosol Species in the Global Atmosphere (MASINGAR) acquired from the Japan Meteorological Agency, with the objective of ascertaining if these data could be applied to predicting health effects. Subjective symptom scores were collected via self-administered questionnaires and, along with modeled surface aerosol concentration data, were used to conduct a risk evaluation using generalized estimating equations between October and November 2011. Altogether, 29 individuals provided 1670 responses. Spearman's correlation coefficients were determined for the relationship between the proportion of the participants reporting the maximum score of two or more for each symptom and the surface concentrations for each considered aerosol species calculated using MASINGAR; the coefficients showed significant intermediate correlations between surface sulfate aerosol concentration and respiratory, throat, and fever symptoms (R = 0.557, 0.454, and 0.470, respectively; p < 0.01). In the general estimation equation (logit link) analyses, a significant linear association of surface sulfate aerosol concentration, with an endpoint determined by reported respiratory symptom scores of two or more, was observed (P trend = 0.001, odds ratio [OR] of the highest quartile [Q4] vs. the lowest [Q1] = 5.31, 95% CI = 2.18 to 12.96), with adjustment for potential confounding. The surface sulfate aerosol concentration was also associated with throat and fever symptoms. In conclusion, our findings suggest that modeled data are potentially useful for predicting health risks of cross-border aerosol arrivals.