For the first time in history, ovarian biological age can be measured, and I became the first woman in the world to take the test. Until now, women have had no real way to understand how their ovaries are aging beyond rough estimates like AMH. But this new machine-learning algorithm, trained on over 40,000 real women across different life stages, analyzes hormone biomarkers, body composition, and reproductive history to estimate ovarian age relative to chronological age. This is a massive step forward in female longevity science. In this episode, I walk through what the test measures, how the algorithm works, and what becoming the first data point actually means, not just for me, but for women collectively. We also explore what may be driving ovarian aging in the first place. I also share how I’m now testing specific interventions in isolation, including hyperbaric oxygen therapy, to determine whether we can meaningfully influence ovarian aging over time. Ovarian lifespan is significantly shorter than overall lifespan and once we can measure it, we can begin to understand it. This is only the first step in redefining female longevity. Join the most comprehensive *female-specific community for health and longevity optimization.* After over a decade dedicated to human performance and women’s health, I created this space to share everything you need to know to optimize health and lifespan. Inside, you’ll get access to exclusive protocols, live Q&As, the latest female longevity science, and a private, supportive community of like-minded women. Chris Masterjohn: https://www.youtube.com/watch?v=z3quYW_pCDU 00:10:48 Study About Ovarian Stiffness Increase https://pmc.ncbi.nlm.nih.gov/articles/PMC7681059/#acel13259-sec-0002 00:16:22 Study For Increased PFAS https://pubmed.ncbi.nlm.nih.gov/41620147/ 00:17:56 Red Light Therapy Study: https://www.sciencedirect.com/science/article/abs/pii/S1011134424001842?via=ihub