Accuracy of an estimated core temperature algorithm for agricultural workers

There is a substantial burden of occupational health effects from heat exposure. We sought to assess the accuracy of estimated core body temperature (CBTest) derived from an algorithm that uses sequential heart rate and initializing CBT,(1) compared with gastrointestinal temperature measured using more invasive ingestible sensors (CBT,(gi)), among outdoor agricultural workers. We analyzed CBTest and CBTgi data from Washington State, USA, pear and apple harvesters collected across one work shift in 2015 (13,413 observations, 35 participants) using Bland Altman methods. The mean (standard deviation, range) CBTgi was 37.7 (0.4, 36.5-39.4)degrees C. Overall CBT bias (limits of agreement) was -0.14 (+/- 0.76)degrees C. Biases ranged from -0.006 to -0.75 degrees C. The algorithm, which does not require the use of ingestible sensors, may be a practical tool in research among groups of workers for evaluating the effectiveness of interventions to prevent adverse occupational heat health effects.

Automated summary

This study assessed the accuracy of estimating core body temperature using an algorithm compared to gastrointestinal temperature measured with ingestible sensors among outdoor agricultural workers. The findings suggest that the algorithm can be a practical tool for evaluating the effectiveness of interventions to prevent adverse occupational heat health effects without the need for ingestible sensors.