Graduation Year

2024

Document Type

Thesis

Degree

M.S.

Degree Name

Master of Science (M.S.)

Degree Granting Department

Public Health

Major Professor

Thomas E. Bernard, Ph.D.

Committee Member

René Salazar, Ph.D.

Committee Member

Luis Pieretti, Ph.D.

Keywords

heat exposure, heat stress, WBGT, radiant heat

Abstract

Occupational heat stress significantly affects outdoor workers who face challenges due to increased heat exposure. Because of the prevalence of heat illness, it is important to measure heat stress for outdoor workers. Monitoring occupational heat stress most often relies on the Wet Bulb Globe Temperature (WBGT) measure. Heat Index (HI) is a widely used measure to account for air temperature and humidity. Adjusted Temperature (Tadj) considers air temperature, humidity and estimates radiant heat. There is interest in predicting WBGT from HI and HI from WBGT. This study builds on previous USF research by Bernard and Iheanacho and Irvin to evaluate the interrelationships between WBGT, HI, and Tadj. The purpose of this study was to analyze seven propositions for prediction of: WBGT from HI, HI from WBGT, and WBGT from Tadj based on local conditions. Besides the temperature measurements, the data included on observations - Surface Type, Direct Sun, Cloud Cover, and Beaufort Wind Force. One dataset of 128 observations was collected as part of this thesis. Another dataset of 127 observations was created by Pofahl for her thesis. The Bernard & Iheanacho model, the Irvin model, and multiple linear regression were used to examine the seven propositions. For all seven propositions, Bland-Altman plots were created. The mean and the difference of the observed and predicted values was computed, and the differences were plotted against the means to create the data for the Bland-Altman plots. Calculating HI from WBGT using the Bernard & Iheanacho and Irvin models resulted in differing levels of bias and precision that indicated that they were not suitable. The strongest results were calculating HI from WBGT based on local conditions using a multiple linear regression that proved to be accurate and precise. Calculating WBGT from HI using the Bernard & Iheanacho and Irvin models resulted in unacceptable accuracy and weak precision. Calculating WBGT from HI based on local conditions using a multiple linear regression resulted in a model that can approximate WBGT. Predicting WBGT using Tadj showed an acceptable bias, but a weak precision with a study effect. The seven alternative propositions were not very promising and showed unacceptable implications for practice.

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