The Equinox Women’s Health Advisory Board member answers your FAQs.
Discussions surrounding women’s health rarely get the care they deserve. Social media is flooded with long-disproved myths and baseless hacks meant to go viral. Meanwhile, artificial intelligence chatbots — which roughly one third of adults use for health information and advice — offer tips that can be inaccurate or, worse, put your health at risk.
It’s time to cut through the noise. Each month, the Equinox Women’s Health Advisory Board is opening up its inbox and addressing your most pressing wellness questions. Consider this your direct line to a group of leading women’s health experts across specialties.
In this installment, Advisory Board Member Stephanie Kuku, M.D., an ob-gyn and surgical oncologist who focuses on reproductive healthspan and the future of fertility, answers your FAQs.
Have a wellness question for the Women's Health Advisory Board? Submit your query here.
Many women are feeling “wellness overwhelm.” What do you think is the simplest, most effective first step to support health?
Dr. Kuku: Walk outside daily.
I know it sounds almost disappointingly simple in an industry built on complexity, but it’s the intervention I’d recommend first to almost any woman, at almost any stage of life. A daily walk in natural light regulates your circadian rhythm, which improves your sleep. It snowballs from there: better sleep helps modulate your hormone secretion, regulate your appetite, and boost your mood, which can improve your capacity to make every other decision about your health. It’s the quiet keystone habit underneath all the louder ones.
It costs nothing and requires no app, no subscription, no protocol. It gives you something the wellness industry can’t sell you: time to think, to notice your body, to be a person rather than a project.
How do you think women can use wearables as tools to improve their sleep?
Dr. Kuku: A wearable can show you what’s happening, but it doesn’t change you. What does is the decision you make in response to its data.
The first step is to shift how you read the data. Nightly scores create anxiety; weekly and monthly trends create insight. Stop asking: “What was my score last night?” Start asking: “What does my last month look like, and what was different with my routine during the good weeks?” Patterns are where behavior lives.
The second step is choosing one variable to change, not ten. Sleep responds reliably to a small number of levers: a consistent schedule, morning light, a cooler bedroom, and a real boundary around alcohol and nighttime screen use. Pick one. Run it for three weeks. Watch the data move.
The third is pairing the objective with the subjective. How did you actually feel? How is your energy, mood, hunger, focus, or libido? These are the outcomes that matter.
How do you envision AI changing the way women approach health?
Dr. Kuku: Continuous glucose data alone is interesting. Cycle-phase data alone is interesting. So is a full hormonal or micronutrient panel, a gut microbiome evaluation, or a look at sleep architecture or training load. But in isolation, it’s just noise.
What excites me is the synthesis of these individual data points with AI. With this technology, we’re moving from “eat more protein” to “here’s what your body specifically needs this week, in this phase, at this training volume, given your iron and vitamin D status.”
For example, Oura has launched its first proprietary large language model designed to deliver personalized women’s health guidance. It’s built on wearable biometric data and clinician-reviewed medical research, covering menstrual cycles, pregnancy, and menopause. When you ask the Oura Advisor a question, the system draws on curated research while simultaneously analyzing your own sleep, activity, cycle, pregnancy, and stress data. The response is contextualized to your personal trends, not generic advice.
Still, from a scientific credibility perspective, I’d encourage women to be curious and not credulous. When receiving AI insights, ask yourself what has been validated. Ask who’s interpreting the data. Ask whether the recommendation would change a doctor’s mind in a clinic.
Editor’s note: Responses have been lightly edited for length, clarity, and accuracy. The views expressed are those of the speaker and do not necessarily reflect the views or positions of any entities they represent.