Abstract
For most women of reproductive age, assessing menstrual health and fertility usually involves regular visits to a gynecologist or another clinician. While these exams provide critical information on an individual’s reproductive health status, they typically rely on personal memory, and the results are rarely, if ever, assessed at the population level. In recent years, mobile apps for menstrual tracking have become very popular, allowing us to evaluate the accuracy, reliability and tracking frequency of millions of self-observations, thereby providing an unparalleled view, both in detail and scale, on menstrual health and its evolution. We acquired self-observation data from two mobile apps dedicated to the application of the sympto-thermal fertility awareness method, resulting in a dataset of more than 30 million days of observations from over 2.7 million cycles, where up to 40% of the cycles in which users were seeking pregnancy had recordings every single day. We used a statistical and modeling approach to describe the collected data and investigate ovulation timing. We found that only 24% of ovulations occur at days 14 to 15, that ~20% of luteal phases last for only 10 days or shorter, and that pre-menstrual light bleeding is associated with earlier temperature drop in the late luteal phase. The digital epidemiology approach presented here can help to lead to a better understanding of menstrual health and its connection to women’s health overall, which has historically been severely understudied.
Significance statement Over 200 million women track their menstrual cycles using mobile phone apps, but it is unclear if these digitally reported data can inform on menstrual health or fertility at the population level. Here we acquired and presented self-observation data of over 2.7 million cycles from two fertility awareness apps. We used a statistical and modeling approach to evaluate the accuracy, reliability and tracking frequency of millions of self-observations. As up to 40% of the cycles in which users were seeking pregnancy had recordings every single day, mobile self-tracking provides a high resolution and long-term view on individual women’s patterns, with a strong potential for improved clinical decision making.