Summary
The idea of an "average" menstrual cycle is a myth that often hurts more than it helps. For a long time, medical systems and society have tried to fit everyone into a single mold, ignoring the huge differences in how people actually experience their periods. This "one size fits all" approach is becoming even more dangerous as we rely more on apps and artificial intelligence to track health. By focusing only on what is common, we risk ignoring the millions of people whose bodies do not fit the standard model.
Main Impact
The biggest problem with focusing on an "average" body is that it makes anyone who is different feel invisible. When doctors, apps, and schools design everything for a "normal" cycle, they exclude trans men, non-binary people, and those with severe health issues like endometriosis. This leads to people doubting their own pain and missing out on the care they need. If a system is built only for the majority, the people at the edges are left to suffer in silence, often believing that their struggle is their own fault rather than a failure of the system.
Key Details
What Happened
For decades, science has used averages to make data easier to handle. While this helps in some areas, it fails in menstruation because every person’s cycle is different. Some people have very light periods, while others face intense pain that stops them from working or going to school. Furthermore, the conversation around periods has traditionally been limited to women. This ignores trans men and non-binary individuals who also menstruate but face extra challenges, such as using gendered washrooms or buying products marketed only to women.
Important Numbers and Facts
Most health apps and medical studies look for patterns that fit the majority. For example, an app might claim to be 95% accurate. While that sounds good, it means that 5% of users are getting incorrect or unhelpful information. When you consider that millions of people use these apps, that 5% represents millions of individuals whose health needs are being ignored. Additionally, data collection is often too simple. Apps usually ask if a flow is "light, medium, or heavy," which cannot capture the complex reality of physical pain or emotional distress.
Background and Context
The reason we rely on averages is that they are easy to measure and put into spreadsheets. In the past, medical research often left out the specific details of individual lives to create general rules. However, health is not a general rule. In menstruation, what is "normal" for one person might be a sign of a medical emergency for another. By trying to make everything fit into a neat box, society has created a world where people are expected to just "deal with" pain because they are told it is a normal part of life.
Public or Industry Reaction
There is a growing movement to change how we talk about and track periods. Many people are calling for more inclusive language, such as using the term "people who menstruate" instead of only "women." This change helps trans and non-binary people feel seen and safe. In the tech world, there is also a push for "inclusive design." This means building apps and tools that account for the "outliers"—the people who don't fit the standard pattern. Instead of seeing these people as errors in the data, experts are starting to realize they are a vital part of the human experience.
What This Means Going Forward
As artificial intelligence becomes a bigger part of healthcare, we must be careful. AI learns from the data we give it. If we only give it data about "average" cycles, the AI will continue to ignore anyone who is different. To fix this, we need to collect better, more descriptive data. We need to move away from simple checkboxes and allow people to describe their experiences in their own words. Technology should be a guide, not the final authority. People should be encouraged to trust their own bodies over what an app tells them.
Final Take
A system that only works for the average person is a system that is broken. True progress in health and technology means building tools that are big enough to include everyone, regardless of their gender identity or how their body functions. We must stop asking people to shrink themselves to fit into a model and instead start building models that reflect the real, messy, and diverse world we live in. No one should have to feel invisible just because their experience doesn't match a statistic.
Frequently Asked Questions
Why is the "average" menstrual cycle considered a myth?
It is considered a myth because very few people actually fit the perfect 28-day cycle with standard symptoms. Real cycles vary greatly in length, pain levels, and flow from month to month and person to person.
How does AI affect period tracking?
AI looks for common patterns to make predictions. This means it often ignores "outliers," such as people with irregular cycles or trans individuals on hormone therapy, treating their real experiences as errors or "noise" in the data.
Why is inclusive language important in menstrual health?
Inclusive language, like "people who menstruate," ensures that trans men and non-binary people are recognized and can access healthcare and products without feeling excluded or unsafe in gendered environments.
