Table 4 Results of binary logistic regression models for knowledge on heatstroke symptoms displaying estimated coefficients (\(\:\widehat{\beta\:}\)) along with p-values, standard errors (SE) and odds ratios (OR) along with their 95% confidence intervals (CI).
From: Survey reveals heatstroke awareness and prevention in Fukuoka City, Japan
Variables | \(\:\widehat{\beta\:}\) | SE | OR | 95% CI |
|---|---|---|---|---|
Intercept | 1.409 | 0.830 | 4.093 | [0.805, 20.826] |
Past experience of HS Not experienced (RC) Experienced | - 0.129 | - 0.245 | - 1.138 | - [0.704, 1.840] |
HS preventive measures Less prevention Moderate prevention (RC) High prevention | -0.953** - 0.712** | 0.327 - 0.236 | 0.386 - 2.038 | [0.203, 0.731] - [1.285, 3.235] |
Checking weather forecasts No (RC) Yes | - 1.231* | - 0.598 | - 3.423 | - [1.061, 11.044] |
Occupation Employed (RC) Unemployed Students | - -0.242 1.037 | - 0.260 0.821 | - 0.785 2.420 | - [0.472, 1.306] [0.564, 14.102] |
Type of living house Owned house (RC) Others | - -0.025 | - 0.231 | - 0.976 | - [0.620, 1.536] |
Year of survey 2020 (RC) 2022 | - -0.574** | - 0.219 | - 0.563 | - [0.367, 0.865] |
Age-sex composite variable Young males (RC) Young females Middle-aged males Middle-aged females Old males Old females | - 0.162 -0.312 -0.088 -1.004 -0.553 | - 0.653 0.522 0.548 0.552 0.579 | - 1.176 0.732 0.916 0.366 0.575 | - [0.327, 4.232] [0.263, 2.039] [0.313, 2.679] [0.124, 1.081] [0.185, 1.789] |
