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Women's health is so neglected that, in my experience, most people forget it could be different. Medical literature doesn't have a granular definition for what menopause is, or how it differs from person to person, or why. There is no standard definition for pregnancy onset, or way to monitor physiological trajectories across pregnancy and development. We don't know how hormonal contraception affects health, and most drugs are specifically not tested in pregnancy, so side effects can only be discovered once they hit someone who was given no warnings and no protections. We don't even know how regular "normal" 28 day cycles are, though data now show differences by demographic, supporting the clear need for much attention to women's health than has historically been given.
With such a low bar for progress, opportunities abound. The timing is perfect for supporting large, collaborative efforts driven by participants, and enabled by apps and wearables to capture their experience and their physiology for others to learn from.
We recently published the first high-resolution maps of physiology across pregnancy.
Most pregnancies get short, surface-level check ups at best every few weeks. Many people do not even know they are pregnant for the first couple months. Wearable devices can fill in the gaps between visits, provide early detection of changes to menstrual cycle pattern (left of the green line in this image) such as pregnancy onset, and allow for the comparison of these patterns across people. These comparisons in turn let us figure out what looks safe or worrisome for whom. For example, not everyone above 35 looks physiologically different from someone at 20, but some might do.
Much of this work is inspired by the women who come forward with their personal data stories. It is my priviledge to try and make those stories more visible, and documented in the scientific and medical literature. It's long past due that women's health is modernized.
Women's health is not a niche to do with reproduction. It is medicine for those people who make up half the population. Historically, women have been excluded not only as scientists and doctors, but also as research subjects. The result is that most modern medicine assumes that white men in their 30s and 40s is the "normal" against which everyone should be compared. We therefore strive to make use of the emerging abundance of personal data from apps and wearables to fill in those knowledge gaps. This includes work on statistics showing that including women does not weaken study power. It also includes work with complex mathematical models developing "digital twin networks" and then testing how often sex segregrates networks. What we tend to find is that there are many real sex differences, but also many places where something else about someone's physiology is more important in defining their health (as in chronotype, diabetes and inflammation, sleep structure, etc.). With so much more than just a binary variable defining our lives, it should not be surprising that there is a lot of work to do helping science be more equitable, and a lot more stories to hear and learn from.
I made the above image from the life-long menstrual period chart a woman provided to me out of general interest. She said she was always irregular, and kept the dates hoping a pattern would emerge, but that she never saw one. The two orange valleys are child birth, and the decline at the end is menopause. Interestingly, her cycles became regular in menopause, around 28 days long , where for most women the opposite experience is reported. Then there seems to be a log decay.
How many other women show similar patterns? What are they correlated to, and how can knowing more help? I've never met another women with a complete life-long journal of menstrual cycles, but these days, sensors and apps are capturing data like these across millions of people. What will we find in those mountains of new observations?
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