Table 1.
List of symbols and notations used in this work.
Fig 1.
Association between daily temperature measures and number of HST from year 2013 to 2018.
Fig 2.
Association between daily WBGT estimates and number of HST from year 2013 to 2018.
Fig 3.
Flowchart of the research methodology.
Table 2.
The descriptive statistics of the daily number of HST in Fukuoka from 2013 to 2018.
Table 3.
Descriptive statistics and approximate correlations with response variable accompanied by the p-values.
Table 4.
Results of four different NB regression models with main covariates.
Table 5.
Correlations between the main covariates and modified weather-related factors.
Table 6.
Results of eight different NB regression models with main covariates and modified weather-related factors.
Fig 4.
Decomposition of the daily HST counts per 1,000 residents of Fukuoka City by age and gender.
Table 7.
Results of NB regression model for different age groups with daily mean and maximum temperatures.
Table 8.
Results of NB regression model for different age groups with daily mean and maximum WBGT estimates.
Fig 5.
Comparison between the predicted mean number of HST per 10,000 residents of Fukuoka City among different age groups.
Fig 6.
Percentage distribution for the time of heatstroke occurrence for overall patients and vulnerable group.
Fig 7.
Percentage distribution for the place of heatstroke occurrence for the varying aged patients.
Fig 8.
Percentage distribution for varying level of heatstroke occurrence among patients of different age and gender.
Table 9.
Results of NB regression models with main covariates and modified weather-related factors for patients aged ≥70 years.
Table 10.
Results of the best models encountered with significant effect of working day.