Women Produce Skin Temperature Data That Are Just as Predictable as Men

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Cyclic females (blue), acyclic females (teal), and males (red) when compared to a single static mean for 7 days (A) and 28 days (B) and 60 days (C) with cycling females either unaligned (natural cyclic phase distribution; C or aligned by cyclic phase (D)

The team chose to track skin temperature because it’s essentially a way to monitor the state of a person’s endocrine system, said Ben Smarr, the paper’s corresponding author and a professor in the Shu Chien Gene Lay Department of Bioengineering and the Halicioglu Data Science Institute at the University of California San Diego. Temperature has been tied to hormonal changes, daily rhythms and women’s health states by previous research. 

“In this study, the difference between two men is bigger than the difference between the average man and the average woman,” said Lauryn Keeler Bruce, the paper’s first author and a Ph.D. student in the Biomedical Informatics and Systems Biology program at UC San Diego. “In addition, the variability between men and women is not statistically significant.”

Smarr and colleagues used the ŌURA ring, a smart wearable produced by Finland-based company Oura Ring to track skin temperature in the study. The device can also track heart rate, activity, and provides sleep tracking. The ŌURA Ring has become a go-to research tool because it’s easy to use and delivers high-quality data. It has been used in recent publications about medical device adherence, predicting pregnancy outcomes, and tracking COVID-19. 

Through statistical analysis the team developed, they found, in women who cycled, a pattern of variation in nightly maximum skin temperature over a roughly 28-day period, consistent with menstrual cycles. This was not unexpected, as temperature monitoring has been used as a tool to track fertility across many cultures. If anything, the pattern made variations easier to predict for the subjects that experienced it. The data for these females was more predictable than for all the other subjects in the study. 

“This analysis confirms that ovarian rhythms do affect temperature,” the researchers write. “This analysis does not suggest that these rhythms make any given measurement more prone to error.” 

Researchers also pointed out that none of their female subjects constantly had a 28-day cycle. “No one was a textbook example,” Keeler Bruce said.

Researchers hope that other teams will adopt their methodology. Being able to continuously monitor physiological signals, such as temperature, is crucial in capturing a more accurate picture of a person’s health, Smarr said. “In order to know what disturbs a pattern, you need to know what the pattern is in the first place,” he said. 

The team plans to examine data from pregnant people throughout pregnancy next. They also plan to examine the differences in activity patterns between male and female subjects. 

Funders include the  Medical Technology Enterprise Consortium (MTEC), the Start Small foundation, and Oura Health. 

Variability of temperature measurements recorded by a wearable device by biological sex 


UC San Diego

Department of Biomedical Informatics: Lauryn Keeler Bruce

Shu Chien-Gene Lay Department of Bioengineering: Patrick Kasl and Benjamin L. Smarr 

Bioinformatics and Systems Biology: Severine Soltani 

Department of Electrical and Computer Engineering: Varun K. Viswanath

Halicioglu Data Science Institute: Iklay Altintas, Amaranath Gupta and Benjamin L. Smarr 

San Diego Supercomputer Center: Saubhasis Dasgupta, Iklay Altintas and Amaranath Gupta 

UC San Francisco Osher Center for Integrative Health: Wendy Hartogensis, Frederick M. Hecht, Anoushka Chowdhary, Claudine Anglo, Keena Pandya and Ashley Mason  

City University New York, Baruch College: Stephan Dilchert

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