Abstract
Objectives
Fevers have been used as a marker of disease for hundreds of years and are frequently used for disease screening. However, body temperature varies over the course of a day and across individual characteristics; such variation may limit the detection of febrile episodes complicating the diagnostic process. Our objective was to describe individual variation in diurnal temperature patterns during episodes of febrile activity using millions of recorded temperatures and evaluate the probability of recording a fever by sex and for different age groups.
Methods
We use timestamped deidentified temperature readings from thermometers across the US to construct illness episodes where continuous periods of activity in a single user included a febrile reading. We model the mean temperature recorded and probability of registering a fever across the course of a day using sinusoidal regression models while accounting for user age and sex. We then estimate the probability of recording a fever by time of day for children, working-age adults, and older adults.
Results
We find wide variation in body temperatures over the course of a day and across individual characteristics. The diurnal temperature pattern differed between men and women, and average temperatures declined for older age groups. The likelihood of detecting a fever varied widely by the time of day and by an individual’s age or sex.
Conclusions
Time of day and demographics should be considered when using body temperatures for diagnostic or screening purposes. Our results demonstrate the importance of follow-up thermometry readings if infectious diseases are suspected.
Funding source: Agency for Healthcare Research and Quality (AHRQ)
Award Identifier / Grant number: R01HS027375
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Research ethics: The University of Iowa Institutional Review Board designates this study exempt from review.
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Informed consent: Not applicable.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. ACM and PMP conceived of the study question and study design. ACM and SHK managed the data. ACM, SHK and JEK oversaw the statistical analysis. MS and PMP provided clinical guidance on the research question. All authors contributed in writing and revising the final manuscript.
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Competing interests: The authors state no conflict of interest.
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Research funding: This work was supported by a grant (R01HS027375) from by the Agency for Healthcare Research and Quality (AHRQ).
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Data availability: The data used for this data are proprietary data from Kinsa Inc. The data may only be obtained with permission from Kinsa Inc.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/dx-2023-0074).
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