Table 4.
Odds Ratios of Average Daily Mean and Extreme Heat Indicator as Predictors for Work‐Related Hyperthermia Emergency Department Visits, by State
| No strata | ||||
|---|---|---|---|---|
| All 5 states | 1.136 (1.115, 1.158) | <0.0001 | 1.536 (1.384, 1.705) | <0.0001 |
| Florida | 1.143 (1.087, 1.201) | <0.0001 | 1.135 (0.920, 1.401) | 0.2363 |
| Georgia | 1.098 (1.047, 1.152) | <0.0001 | 1.723 (1.372, 2.163) | <0.0001 |
| Kentucky | 1.160 (1.114, 1.209) | <0.0001 | 2.164 (1.567, 2.988) | <0.0001 |
| Louisiana | 1.117 (1.071, 1.165) | <0.0001 | 1.847 (1.449, 2.353) | <0.0001 |
| Tennessee | 1.143 (1.103, 1.184) | <0.0001 | 1.453 (1.172, 1.802) | <0.0001 |
Average daily mean temperature (°F) was modeled as a 1‐degree change. The Average Tmean variable is calculated as an average of temperatures observed on the day of ED visit and three preceding days for the county where the ED visit occurred. EHE indicator is a binary indicator and is set to “1” if the day of the ED visit or three preceding days were part of an extreme heat event. All estimates of odds ratios include both “Average Tmean” and “EHE Indicator” as independent variables in the logistic regression models.