Understanding wrist skin temperature changes to hormone variations across the menstrual cycle

Area of Science:

• Physiology
• Endocrinology
• Wearable Technology

Background:

• Consumer devices are increasingly used for peripheral body temperature (PBT) monitoring, particularly for menstrual cycle tracking.
• The relationship between peripheral body temperature and hormonal fluctuations during the menstrual cycle is not fully understood.
• Wrist skin temperature (WST) is a commonly measured PBT metric in wearable devices.

Purpose of the Study:

• To investigate the relationship between nightly wrist skin temperature (WST) and key hormone levels (estrogen metabolite E3G, luteinizing hormone LH) during the menstrual cycle.
• To assess the potential impact of demographic factors and self-reported stress on this relationship.
• To inform the development of algorithms for wearable devices used in menstrual cycle and hormonal tracking.

Main Methods:

• Fifty participants collected physiological data including nightly WST, daily step counts, and glucose levels.
• Hormone levels (E3G, LH) were measured, alongside self-reported diary entries and stress levels.
• Statistical analysis was performed to correlate WST with hormone levels, controlling for confounding variables.

Main Results:

• A significant negative correlation was observed between WST and hormone levels (E3G, LH) when these hormones were below their average values.
• This correlation remained robust despite variations in demographics and self-reported stress.
• Greater variability was noted between mid-cycle hormonal peaks and WST fluctuations, potentially due to differences between WST and basal body temperature (BBT).

Conclusions:

• Wrist skin temperature (WST) exhibits a complex relationship with hormonal changes during the menstrual cycle.
• The observed variance suggests that WST may not directly mirror core body temperature changes typically used in basal body temperature (BBT) tracking.
• Algorithms for wearable menstrual cycle tracking should consider the increased variance in WST trends to improve accuracy and reliability.