California [US], November 9 (ANI): When it comes to skin temperature, women produce physiological data that is just as predictable as males. This may seem obvious, yet fluctuations in bodily signals caused by menstrual cycles, such as temperature, have been used to keep women out of clinical research for decades.
The data for the discovery came from a wearable device that continuously monitored the skin temperature of 600 participants, half of whom were female and half of whom were male, over a six-month period.
The researchers discovered that there were more differences between any two people in the study, male or female, than between the sexes.
Women provide physiological data that is equally as predictable as men when it comes to skin temperature. Although this may appear obvious, variations in body signals induced by menstrual cycles, such as temperature, have been utilised for decades to keep women out of clinical studies.
The data for the discovery came from a wearable device that continuously recorded the skin temperature of 600 volunteers over a six-month period, half of whom were female and half of whom were male.
The researchers revealed that there were greater differences between male and female participants in the study than between the sexes.
Despite guidelines from the National Institutes of Health that require studies to include females and minorities in clinical studies, women are still disproportionately excluded from research, particularly in drug trials. This is due in part to concerns that menstrual cycles would introduce too many variables in the data.
And despite the harm to women that results from using medicines designed for men, including higher overdose and side effect rates, no one had yet looked at continuous physiology signals across large groups of men and women to see if women’s cycles really did make the data harder to analyze-until now. The study didn’t find any statistically significant differences, showing that concern is not warranted.
The team included researchers from the San Diego Supercomputer Center, the Halicioglu Data Science Institute and the Jacobs School of Engineering at the University of California San Diego as well as the UC San Francisco Osher Center for Integrative Health.
The UC San Diego team has been working with the UC San Francisco team, led by co-senior author Dr. Ashley E. Mason, since 2020 to gather wearable data from around the world and develop tools for detecting disease outbreaks. “If the point is that we can now use wearables to track health over big groups of people, then it makes no sense to exclude whole groups of people from the research” said Mason, a sleep clinician and principal investigator of the broader TemPredict project from which this study grew.
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 PhD 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 OURA 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, and activity, and provides sleep tracking. The OURA 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. (ANI)
