Welcome to the PCOS episode, part of Science Savvy with Carmen. In this episode, I explore the science behind Polycystic Ovarian Syndrome, a complex hormonal and metabolic condition that affects millions of women worldwide. With my background in pharmacology and biomedical engineering, I break down the mechanisms behind PCOS and unpack how it shows up in your daily life.

This episode features a conversation with Dr. Basma Faris, a board-certified OB/GYN and certified culinary medicine specialist. We discuss why PCOS is not just about cystic ovaries, how insulin resistance contributes to hormonal imbalance, and the ways diet, sleep, and stress management play a role in symptom control. We also talk through the myths, the science, and the danger of wellness misinformation. Whether you're navigating a diagnosis or simply curious about how hormones, metabolism, and lifestyle connect, this episode offers clear and engaging insights grounded in real research.

Science Savvy helps you understand the systems shaping your thoughts, health, and behavior. If you're ready to explore your body and brain with a little more clarity, you're in the right place.

Further reading and references:

St-Onge, M. P., et al. (2023). The interrelationship between sleep, diet, and glucose metabolism. Sleep Medicine Reviews, 69, 101788. https://doi.org/10.3390/medicina60010061
Ehrhardt, N., & Al Zaghal, E. (2018). Behavior modification in prediabetes and diabetes: Potential use of real-time continuous glucose monitoring. Journal of Diabetes Science and Technology, 13(2), 271–275. https://doi.org/10.1177/1932296818790994
Hanefeld, M., et al. (2014). Differences in glycemic variability between normoglycemic and prediabetic subjects. Journal of Diabetes Science and Technology, 8(2), 286–290. https://doi.org/10.1177/1932296814522739
Dmitrovic, R., et al. (2011). Continuous glucose monitoring during pregnancy in women with polycystic ovary syndrome. Obstetrics & Gynecology, 118(4), 878–885. https://doi.org/10.1097/AOG.0b013e31822c887f
Tao, M., et al. (2011). Continuous glucose monitoring reveals abnormal features of postprandial glycemic excursions in women with PCOS. Postgraduate Medicine, 123(2), 185–190. https://doi.org/10.3810/pgm.2011.03.2277
Merino, J., et al. (2022). Validity of continuous glucose monitoring for categorizing glycemic responses to diet. American Journal of Clinical Nutrition, 115(6), 1569–1576. https://doi.org/10.1093/ajcn/nqac026
Wyatt, P., et al. (2021). Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nature Metabolism, 3(4), 523–529. https://doi.org/10.1038/s42255-021-00383-x
Zahalka, S. J., et al. (2024). Continuous glucose monitoring for prediabetes: What are the best metrics? Journal of Diabetes Science and Technology, 18(4), 835–846. https://doi.org/10.1177/19322968241242487
Basiri, R., & Cheskin, L. J. (2024). Personalized nutrition therapy without weight loss counseling produces weight loss in individuals with prediabetes. Nutrients, 16(14). https://doi.org/10.3390/nu16142218
Joseph, J. I., et al. (2018). Glucose sensing in the subcutaneous tissue: Correlation with immune response and CGM accuracy. Diabetes Technology & Therapeutics, 20(5), 321–324. https://doi.org/10.1089/dia.2018.0106
Jospe, M. R., et al. (2024). Leveraging continuous glucose monitoring as a catalyst for behaviour change. International Journal of Behavioral Nutrition and Physical Activity, 21(1), 74. https://doi.org/10.1186/s12966-024-01622-6
Zhu, J. P., et al. (2013). Increased mean glucose levels in patients with PCOS and hyperandrogenemia as determined by CGM. Acta Obstetricia et Gynecologica Scandinavica, 92(2), 165–171. https://doi.org/10.1111/aogs.12031
Rizos, E. C., et al. (2024). Difference on glucose profile from CGM in people with prediabetes vs. normoglycemic individuals. Journal of Diabetes Science and Technology, 18(2), 414–422. https://doi.org/10.1177/19322968221123530