Episodes

  • Stanford's Aging Fish, Tracking Wishlist, Placebo Blueberries & Measuring Body Composition - Q1’26 Updates (Fit For Science Episode 15)

    Stanford's Aging Fish, Tracking Wishlist, Placebo Blueberries & Measuring Body Composition - Q1’26 Updates (Fit For Science Episode 15)
    Apr 27 2026
    In this episode, Rob and Stephan explore the intersection of lifespan research, the exposome, and daily health tracking, tackling everything from aging fish and AI stool analysis to passive exercise tracking and body composition scales.📝SummaryIn episode 15 of Fit For Science, Rob and Stephan explore the intersection of lifespan research, the exposome, and daily health tracking, tackling everything from fish behavior to body composition. The hosts, both biological data scientists, dive into a recent Stanford study published in Science that tracked the lifetime behavior of short-lived fish to uncover insights into aging, connecting these methods to human wearable technology and exposome tracking. They transition into discussing the potential benefits and practical hurdles of tracking daily bowel movements using AI and the Bristol stool chart compared to infrequent microbiome testing. The conversation also highlights wishlist features for wearables, specifically the ability to quantify passive exercises like saunas and cold plunges. A personal anecdote about a sudden burst of energy and reduced sleep need following the consumption of freeze-dried blueberries sparks a debate on whether this was due to antioxidants reducing neuroinflammation or simply project-induced excitement. Finally, they compare at-home bioelectrical impedance smart scales to clinical measurements, detailing the nuances between lean mass, visceral fat, and the importance of long-term trend averaging.⏳Chapters00:00:00 Fish Aging Study: Discussing a Stanford study connecting fish with wearables00:04:13 The Exposome: Exploring how environmental exposures are tracked00:12:05 Stool Tracking vs. Microbiome Analysis00:19:33 Quantifying Passive Exercise: A wishlist discussion00:25:30 The Blueberry Effect and Sleep: Stephan's placebo experience00:34:30 Body Composition and Smart Scales00:43:03 Advanced Body Composition Measurement Techniques00:46:07 Lean Mass vs. Visceral Fat00:51:22 Data Averages and Trends📚ResourcesLinkedIn post about Stanford's aging fish study Watching a lifetime in motion reveals the architecture of aging Youthful antics predict lifespan — at least for these fish Paper: Lifelong behavioral screen reveals an architecture of vertebrate aging Amazon's failed body composition app: The science behind the Halo Body feature Academic publishing: Open Access vs Paywalls Actigraphy An atlas of exposome–phenome associations in health and disease risk Exposome Snyder Lab - Exposome A Network-Based Framework for Assessing the Pathobiological Impact of Environmental Exposures on Human Development & Health - Salvo D LombardoCeMM - Research Center for Molecular Medicine (where we work) Massive biomolecular shifts occur in our 40s and 60s Microbiome Bristol Stool Chart: Types & What They Mean Zettelkasten system (Stephan uses his email inbox)Body Scan | Withings Europe The 10 Best Ways to Measure Your Body Fat Percentage The Evaluation of a Mass Media Campaign Aimed at Weight Gain Prevention Among Young Dutch Adults Sustained visceral fat loss is associated with attenuated brain atrophy and improved cognitive function in late midlife…There is more: complete show notes here🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise and enable everyone to become their best N-of-1.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon MusicCollection of all show notes⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    56 mins
  • The Silicon Valley Peptide Craze: Trust the Science, Not the Influencer (+ Hierarchy of Evidence) (Fit For Science Episode 14)

    The Silicon Valley Peptide Craze: Trust the Science, Not the Influencer (+ Hierarchy of Evidence) (Fit For Science Episode 14)
    Apr 21 2026
    In this episode of Fit for Science, Rob and Stephan use the recent Silicon Valley "peptide craze" as a case study to explore how to critically evaluate health claims and navigate the scientific hierarchy of evidence.📝SummaryIn episode 14 of the Fit for Science podcast, biological data scientists Rob and Stephan delve into the growing trend of Silicon Valley tech elites self-injecting unregulated peptides, using this phenomenon as a launchpad to discuss how to critically assess health and lifestyle claims. They begin by demystifying what peptides actually are, providing examples ranging from life-saving insulin and GLP-1 agonists to harmful spider venom, while warning against the dangers of untested, gray-market substances. The core of the episode breaks down the hierarchy of scientific evidence, guiding listeners from the weakest forms, such as second-hand anecdotes and social media influencers, up through epidemiological observational studies, prospective studies, and rigorous randomized controlled trials, finally culminating at the pinnacle: meta-analyses. Furthermore, they offer practical advice on safely running personal health experiments using wearables, emphasizing the importance of systematic testing, understanding biological mechanisms versus actual tested outcomes, and relying on high-quality institutional guidelines over viral internet trends.⏳Chapters00:00:00 Unpacking the Silicon Valley peptide craze00:04:50 Defining Peptides: Understanding small proteins00:17:18 The Hierarchy of Evidence: Why anecdotes and personal experiences sit at the bottom00:26:59 Epidemiological Studies: The value and limitations of observational data00:32:45 Prospective Studies: Planning health research and utilizing wearable data00:35:08 Randomized Controlled Trials: The gold standard for testing interventions and eliminating bias00:43:24 Meta-Analyses: Combining data to form medical consensus and guidelines00:46:29 Evaluating Sources: Disentangling the message from the messenger00:52:17 AI in Health Research: Tips and pitfalls when using frontier models for scientific inquiries00:58:10 Community Q&A: How to safely use wearables to run systematic self-experiments01:07:11 Final thoughts on evaluating risks and a recap of the evidence hierarchy📚Resources‘Chinese Peptides’ Are the Latest Biohacking Trend in the Tech World - The New York TimesSilicon Valley's new miracle drugEric Topol - The Peptide Craze - Ground Truths Economist - Want to hack your body with peptides? If only the science agreed ‘People are turning themselves into lab rats’: the injectable peptides craze sweeping the US | The GuardianProPublica - A Las Vegas Festival Promised Ways to Cheat Death. Two Attendees Left Fighting for Their Lives. Hierarchy of evidence Survivorship bias (incl. airplane bullet holes anecdote) UK Biobank NHANES - National Health and Nutrition Examination Survey | CDC Meta-analysis - Examine VIP medicine aka VIP syndrome aka VIP effect Edison Platform for science-based AI researchPerplexity AI for research (you can select academic papers) Eddy Burback - ChatGPT made me delusional Principles from the episodeProteins are the smallest functional unit of life and peptides are just small proteins.…There is more: complete show notes here🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise and enable everyone to become their best N-of-1.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon MusicCollection of all show notes⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 10 mins
  • The $100 Genome: Genetic Risk Scores & Sequencing Babies (Fit For Science Episode 13)

    The $100 Genome: Genetic Risk Scores & Sequencing Babies (Fit For Science Episode 13)
    Mar 19 2026
    Rob and Stephan explore the new reality of $100 whole genome sequencing, the actionable value of polygenic risk scores, and the ethical future of personalized genomic medicine.📝SummaryBiological data scientists Rob and Stephan discuss the implications of the newly achieved $100 whole genome sequencing milestone, comparing unbiased whole genome reads to popular genotyping consumer products like 23andMe. They delve into the mechanics of genome-wide association studies and polygenic risk scores, examining how genetics interact with lifestyle and environmental factors to influence disease probability. The hosts share their personal experiences with services like Nebula Genomics, 23andMe and Dante Labs, revealing how insights, such as a high genetic predisposition for elevated ApoB levels, can drive actionable dietary changes like reducing saturated fats. Finally, they explore the psychological barriers, data privacy concerns, and ethical considerations of integrating genomic sequencing into standard medical practice and newborn screening to create a proactive, Bayesian model of preventative healthcare.⏳Chapters00:00:00 The $100 Genome: Cost breakthroughs and historical perspective00:07:41 Defining Sequencing: Genotyping consumer products vs. Whole Genome Sequencing00:16:19 Polygenic Risk Scores: Predicting complex diseases using multiple genes00:20:44 Nature vs. Nurture: How lifestyle pulls the trigger on genetic predispositions00:23:17 Medical Implementation: Psychological anxiety and the actionability of genetic data00:33:03 Personal Experiences: Reviews of Nebula Genomics, 23andMe, and Dante Labs00:44:23 Actionable Insights: Modifying saturated fat intake based on ApoB percentiles00:54:55 A Bayesian Healthcare Model: Combining genetics, demographics, and lifestyle01:06:20 Ethical Explorations: The future of sequencing newborns and preventative screening📚ResourcesHuman Genome Project cost ~$3 Billion and took ~13 years (1990-2003)How to sequence the human genome - TED-Ed Video Genetic disorder (monogenic i.e., single-gene cause) Scrappy San Diego startup goes toe-to-toe with gene-sequencing giant IlluminaElement BiosciencesEric Topol's X post about $100 Gneom The cost of sequencing human genome has fallen from $100M to under $100 in approximately 25 years The $100 Genome: Where’s the Limit? Genome-wide association study (GWAS)Polygenic score (PRS)What are Polygenic Risk Scores (PRS) and how can they be used in healthcare? Systematic comparison of family history and polygenic risk across 24 common diseases > “In most diseases, including coronary artery disease, glaucoma, and type 2 diabetes, a positive family history with a high PRS was associated with a considerably elevated risk, whereas a low PRS compensated completely for the risk implied by positive family history.”> “In addition to capturing shared DNA, FH [family history] measures non-genetic exposures and behaviors shared by families”Nebula Genomics now DNA Complete with subscription modelGeorge Church (geneticist) 23andMeDante LabsPromethease for DNA reportingReference genome Personalized genomics Apolipoprotein B (ApoB) The ‘thousand-dollar genome’: an ethical exploration | European Journal of Human Genetics (2013!)…There is more: complete show notes here🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise and enable everyone to become their best N-of-1.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon MusicCollection of all show notes⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 3 mins
  • How We Think About Supplements: What We Take, What We Ditched & Our Daily Protocols (Fit For Science Episode 12)

    How We Think About Supplements: What We Take, What We Ditched & Our Daily Protocols (Fit For Science Episode 12)
    Mar 2 2026
    Rob and Stephan unpack their personal supplement protocols, discussing everything from creatine and omega-3s to the reasons they both ditched popular green powders like AG1.📝SummaryIn this episode, biological data scientists Rob and Stephan explore the rationale, logistics, and science behind their personal supplementation protocols, emphasizing that supplements can never replace foundational habits like sleep, nutrition, and activity. The hosts dissect their differing approaches, with Rob detailing why he stripped his stack down to just creatine and whey protein after experiencing adverse effects like vivid dreams from L-theanine, while Stephan breaks down his extensive daily routine organized by morning, noon, and evening doses. They critically evaluate the utility and safety of compounds ranging from vitamin D3, K2, and magnesium bisglycinate to more experimental interventions like lion's mane and exogenous ketones. The conversation also covers the economics of tracking health, the potential heavy metal risks associated with popular green powders like AG1, downsides of complex blends, and the immunological implications of high protein diets.⏳Chapters00:00:00 Defining Supplements: Deficiencies versus performance optimization00:04:11 The Fundamentals: Why pills cannot replace sleep and nutrition00:09:26 Simplifying the Stack: Why Rob stopped taking pre-formulated mixes00:15:16 Safety First: Water-soluble vitamins versus fat-soluble accumulation00:18:23 The Morning Routine: Collagen, Vitamin C, and Electrolytes00:26:38 The Top Three: Vitamin D3, K2, and Creatine Monohydrate00:34:29 The Noon Routine: Lion's mane, selenium, and dark chocolate polyphenols00:40:23 The Evening Routine: Magnesium bisglycinate, Omega-3s, and Glycine00:46:03 The Cost of Supplementation: Budgeting for the quantified self00:48:55 On-Demand Tools: Nicotine as a stimulant and wheat germ for spermidine00:52:45 Protein Targets: Muscle maintenance, mTOR, and cardiovascular risk00:58:50 Ditched Supplements: Why we stopped taking AG101:03:28 Future Experiments: Exploring exogenous ketones for metabolic flexibility📚ResourcesStephan's supplement stack & schedule Creatine benefits, dosage, and side effects Creatine: What It Does, Benefits, Supplements & Safety What Every Vegan Should Know About Vitamin B12 Clarification: The avid listener might notice a contradiction: B vitamins are water-soluble, yet B12 is stored for years. Both can be true because it is continuously recycled in the liver, tightly bound to proteins, and too large for the kidneys to flush out.Iodine: Its Role in Thyroid Hormone Biosynthesis and Beyond What is the effect of combining L-theanine with caffeine? Vitamin D Lion’s Mane Mushroom (Hericium erinaceus): A Neuroprotective Fungus with Antioxidant, Anti-Inflammatory, and Antimicrobial Potential The Master Antioxidant: Glutathione Magnesium Bisglycinate vs. Other Forms: Which Is Best? Omega-3 Fatty Acids benefits, dosage, and side effects How Much Spermidine Is in a Tablespoon of Wheat Germ? High-protein diets increase cardiovascular risk by activating macrophage mTOR to suppress mitophagy Fruits, Veggies, and Other Greens Supplements Review (Including Spirulina and Chlorella) …There is more: complete show notes here🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise and enable everyone to become their best N-of-1.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon MusicCollection of all show notes⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 6 mins
  • Can and Should We Live Forever? Blue Zone Myths, Longevity Drugs & The 50/50 Genetics-Lifestyle Split (Fit For Science Episode 11)

    Can and Should We Live Forever? Blue Zone Myths, Longevity Drugs & The 50/50 Genetics-Lifestyle Split (Fit For Science Episode 11)
    Feb 17 2026
    Rob and Stephan dissect the "Nature vs. Nurture" debate in longevity, debunk Blue Zone myths, and evaluate the potential of anti-aging interventions like calorie restriction and Rapamycin.📝SummaryIn this episode, biological data scientists Rob and Stephan explore the realistic limits of human lifespan, starting with the outlier case of supercentenarian Jeanne Calment. They tackle the age-old "nature vs. nurture" debate, discussing recent research that suggests a near-even split in agency compared to previous estimates, while also highlighting the "Ig Nobel" findings that attribute many Blue Zone claims to poor record-keeping or fraud rather than biological superiority. The conversation moves through the biology of aging, touching on genome-wide association studies (GWAS) and specific genes like APOE and FOXO3, before transitioning to lifestyle interventions such as calorie restriction and the concept of hormetic stress. Finally, the hosts critically evaluate the current landscape of longevity pharmacology, including Metformin, GLP-1 agonists, and Rapamycin, ultimately concluding that while living forever remains scifi, maximizing healthspan through foundational lifestyle habits remains the most effective strategy.⏳Chapters00:00:00 Introduction: Limits of lifespan and the "Don't Die" philosophy00:00:40 The Maximum Lifespan: Jeanne Calment and winning the genetic lottery00:02:46 Blue Zones Debunked: The Ig Nobel Prize for bad record-keeping00:04:22 Nature vs. Nurture: Genetics, epigenetics, and the blueprint of life00:07:49 Genome Wide Association Studies (GWAS): How we link genes to traits00:12:23 Longevity Genes: APOE and FOXO3 mechanisms00:15:44 The 50/50 Split: Recent evidence on genetic vs. lifestyle influence00:23:36 Calorie Restriction: Mouse models, immune suppression, and hormesis00:34:16 The Vices: Smoking, obesity, alcohol, and the hygiene hypothesis00:39:54 Longevity Drugs: Metformin and the risk of blunting exercise gains00:44:46 Weight Loss Drugs: GLP-1 agonists, muscle loss, and heart rate effects00:47:11 Rapamycin: Inhibiting mTOR and the balance of anabolism vs. catabolism00:51:00 Senolytics: Clearing "zombie cells" with Quercetin and Dasatinib00:56:37 Life Expectancy: Realistic predictions and the definition of a good life📚ResourcesJeanne CalmentBryan JohnsonIg Nobel Prize for Blue Zone debunkingNature versus nurtureHuntington's diseaseCorrection: life expectancy is 15-25 years after the onset of symptoms, often occurring in the 20s/30sGenome-wide association study (GWAS)CentenarianMultifaceted roles of APOE in Alzheimer diseaseFOXO3Central dogma of molecular biology (DNA -> RNA -> protein)Heritability of intrinsic human life span is about 50% when confounding factors are addressed (2026)Estimates of the Heritability of Human Longevity Are Substantially Inflated due to Assortative Mating (Calico 2018)CRISPR gene editingGermlineStem cellFDA Approves First Gene Therapies to Treat Patients with Sickle Cell Disease (2023) Do ‘blue zones,’ supposed havens of longevity, rest on shaky science? Sleep, Nutrition, Activity, Purpose (SNAP framework)Calorie restrictionHormesisSupercompensation Progressive overload 2-year calorie restriction study (CALERIE) …There is more: complete show notes here🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise and enable everyone to become their best N-of-1.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon MusicCollection of all show notes⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 9 mins
  • How to Actually Read Your Sleep Data (Beyond Accuracy) + 7 Scientific "Cumulative Biomarkers" for Longevity (Fit For Science Episode 10)

    How to Actually Read Your Sleep Data (Beyond Accuracy) + 7 Scientific "Cumulative Biomarkers" for Longevity (Fit For Science Episode 10)
    Feb 9 2026
    Rob and Stephan discuss why sleep stage trends matter more than absolute accuracy, review Oura's latest metrics, and define seven essential cumulative biomarkers for long-term health.📝SummaryIn this episode, biological data scientists Rob and Stephan challenge the standard approach to sleep tracking validation, proposing that detecting deviations from an individual's baseline is often more valuable for the user than absolute agreement with polysomnography. The hosts shortly brainstorm the creation of an independent, crowd-funded wearable testing institute to provide unbiased data for the quantified self community and research. Then they analyze the utility of Oura’s new Sleep Debt and Cumulative Stress features, discussing how these metrics align with subjective experiences of recovery after social events like the Viennese ball season. The conversation expands into a deep dive on "cumulative biomarkers," where Stephan outlines a suite of stable, long-term health indicators, including HbA1c, VO2 max, Grip Strength, and the Omega-3 Index, that serve as superior proxies for longevity compared to transient measurements.⏳Chapters00:00:00 Sleep Study Analysis: User centric comparisons00:10:39 Testing Philosophy: Why "more or less than usual" matters most00:16:13 The Vision: A crowd-funded independent wearable testing lab00:24:37 Oura's Trend Features: Analyzing Sleep Debt and recovery timelines00:34:43 Cumulative Stress: Physiological stress vs “Distress” vs "Eustress"00:41:51 Hardware Woes: The decline of Fitbit and device longevity00:45:15 Feature Disparity: Oura Health Panels and US vs. EU regulations00:51:22 Cumulative Biomarkers: Stable markers vs. transient snapshots00:52:23 Metabolic Health: Why HbA1c trumps fasting glucose00:57:55 Fitness Markers: VO2 Max and the utility of Grip Strength01:01:31 Nutritional Status: The Omega-3 Index and cell membrane saturation01:05:22 Organ Health: Cystatin C for kidney function and DXA for body composition01:09:47 Cardiovascular Risk: The Coronary Artery Calcium (CAC) score01:12:25 Smart Scales: Bio-impedance limitations and the need for handles📚ResourcesIn the episode we call the discussed biomarkers “integrative”, but “cumulative” better captures the intended meaning.Rob's sleep studyPolysomnography Cohen's Kappa (Statistic)Sensitivity and specificity Oura's Sleep Debt FeatureOura's Cumulative Stress FeatureOura's Resilience FeatureOura's Daytime (Physiological) Stress featureDistress vs EustressElectrodermal activity as proxy for stressFitBit Sense 2 (with cEDA sensor) Oura's Health Panel featureRed blood cellGlycated hemoglobin (HbA1c) HbA1c > 6.5% is used for diabetes diagnosisVO2 max Grip strength as a mortality predictorOmega-3 Index (Dr. Rhonda Patrick)Cystatin C (Kidney Function)DXA Scan Radiation comparison (DXA ~0.001mSv, US coast-to-coast round-trip flight ~0.03mSv)Coronary Artery Calcium (CAC) ScoreThe limits of coronary calcium Visceral FatPreprint introducing "Peakspan"Nature Medicine paper "Shared and specific blood biomarkers for multimorbidity"🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise in the health and fitness industry.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon MusicCollection of all show notes⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 18 mins
  • The “Dark Side” of Tracking & VO2 Max as Longevity Predictor: Testing, Training & Our Results (Fit For Science Episode 9)

    The “Dark Side” of Tracking & VO2 Max as Longevity Predictor: Testing, Training & Our Results (Fit For Science Episode 9)
    Feb 2 2026
    In this episode, Rob and Stephan explore the psychological risks of self-quantification, the science of aerobic capacity, and the physiological nuances of lactate thresholds.📝SummaryBiological data scientists Rob and Stephan discuss the "dark side" of the quantified self, specifically focusing on orthosomnia, a condition where sleep tracking leads to increased anxiety and worsened sleep quality. They reflect on the importance of using technology as a tool for a specific purpose rather than making the tracking itself the goal. The conversation transitions into a deep dive on VO2 max, explaining its critical role as a longevity predictor and the varying results obtained from different exercise modalities like cycling and running. Finally, the hosts break down the science of lactate thresholds, explaining how the body's metabolic shift from aerobic to anaerobic states serves as a vital biomarker for training optimization.⏳Chapters00:00:00 Introduction: The dark side of tracking and VO2 max00:00:55 Orthosomnia: When sleep tracking causes insomnia00:05:09 The psychological impact of metrics and obsession00:13:13 Tracking with purpose: Avoiding the identity trap00:25:59 Oura Ring experiences: “Injuries” and data accuracy00:30:50 Strength training and basal metabolic rate00:36:47 VO2 Max: The ultimate longevity marker?00:38:26 Hazard Ratios: Comparing fitness to smoking00:44:39 The U-shaped curve of exercise volume00:49:37 Gold Standard: VO2 max lab testing protocols01:04:25 Training for capacity: The Norwegian 4x4 protocol01:07:51 Lactate thresholds and metabolic switching01:16:09 Wearable estimations: Garmin vs. Apple vs. Oura01:21:47 VO2 Max Records: Oskar Svendsen (97.5) and Tadej Pogačar (96)01:23:42 Teaser: Biological age and integrative biomarkers📚ResourcesOrthosomniaThe Molecular Precision Medicine Master’s Programme at Medical University of Vienna (where Rob and Stephan teach)Quote for purposeful tracking: "I shall not waste my days in trying to prolong them" - Jack LondonNatural language processing (NLP)Semantic analysisDevelopment of a scale for measuring orthosomnia: the Bergen Orthosomnia Scale (BOS)Sleep tracker use nears 50%, AASM survey findsPrevalence of Orthosomnia in a General Population Sample Dark triad (Personality Traits)Basal metabolic rate (BMR)BMR Calculator Lean body mass was found to be the single predictor of BMRPhelps supposedly consumed 8,000-10,000 kcal per training day before the Olympic GamesVO2 maxHazard ratioHow does VO2 max correlate with longevity? - Peter Attia Physical activity types, variety, and mortality: results from two prospective cohort studies Peak oxygen uptake was strongly correlated to total heart volumeRob's VO2 max results: 58 for cycling, 54 for runningStephan's VO2 max results: 42 for cycling, 49 for runningVO2 max percentile calculatorVO2 Max ChartAerobic high-intensity intervals improve VO2max more than moderate training (Norwegian 4x4) How to Improve Your Cardio Capacity (VO2 Max)Lactate threshold for aerobic to anaerobic switch at 2mmol/litreLactate shuttle hypothesis Maximum heart rate formula: 220 - age in yearsCooper test for VO2max estimationWalking test for VO2max estimation🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise in the health and fitness industry.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon Music⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 25 mins
  • AI is Changing Wearables in 2026(?) and Predicts 130 Diseases from Sleep! (Fit For Science Episode 8)

    AI is Changing Wearables in 2026(?) and Predicts 130 Diseases from Sleep! (Fit For Science Episode 8)
    Jan 26 2026
    Rob and Stephan evaluate current AI features in wearables, break down a revolutionary paper predicting diseases from a single night of sleep, and discuss the future of medical integration into wearables.📝SummaryIn this episode, biological data scientists Rob and Stephan critically assess the current use of AI in the wearable market, ranging from the practical limitations of Oura and Whoop coaches to the potential of Google’s Gemini and Withings’ biomarker-tracking devices. The central scientific discussion focuses on "SleepFM," a groundbreaking foundation model published in Nature Medicine that utilizes self-supervised learning on polysomnography data to predict over 130 diseases, biological age, and mortality risk from a single night of sleep with unprecedented accuracy. The hosts speculate on how this technology could bridge the gap between clinical sleep labs and consumer wearables, potentially transforming preventive medicine through longitudinal tracking and non-invasive sensors.⏳Chapters00:00:00 AI in wearables and their current capabilities00:01:21 AI Coaches: Testing the limits of Oura, Whoop, and Garmin 00:12:24 The Smart Toilet: Withings U-Scan and the value of waste biomarkers 00:23:00 Environmental Health: PVC off-gassing and vinyl records 00:28:15 Generative AI: ChatGPT Health and Claude for Life Sciences 00:37:17 SleepFM: A multimodal sleep foundation model for disease prediction 00:43:00 Self-Supervised Learning: How foundation models learn from sleep data 00:51:00 Disease Prediction: Predicting 130 conditions with unseen accuracy00:59:46 The Future: Translating clinical models to consumer wearables 01:19:25 Community Feedback📚ResourcesIntroducing Oura Advisor (not Coach)WHOOP Coach Powered by OpenAIActive Intelligence With Garmin Connect+U-Scan NutrioNews: Withings latest smart scale (‘longevity station’)Withings IntelligenceBody ScanKetone bodiesKetosis: Definition, Benefits & Side EffectsKeto Breath (“dragon breath”)Air Quality Measurement DeviceVINYL: Maybe it's time we had an intervention.Introducing ChatGPT HealthSegment about AI in health(care)Claude in healthcare and the life sciencesClarification: Anthropic's product is called Claude with three differently sized models named Haiku, Sonnet, and Opus.ICD-10 and ICD-11 Codes: International Classification of Diseases (ICD)Understanding ICD-10 | Johns Hopkins MedicineHealthcare Spending - Our World in DataFederated learningSwarm LearningSleepFM - Nature Medicine paperCodeStanford Sleep Bench v1.0Foundation modelAttention Is All You Need (Transformers)Self-supervised learningImageNetFine-tuningReinforcement learning from human feedback (RLHF)PolysomnographyRecurrent neural network (LSTM)Long short-term memory (RNN)C-index: Evaluating Survival ModelsBest Wearables for Sleep: Scientific Rankings (2024-05)Best Wearables for Sleep: Scientific Rankings (2025-10)Philips Somnolyzer 24x7 for automated sleep stagingWhoop listened(?) and is looking for a VP for Foundation AIAUROC of blood pressure to predict ASCVD ~0.80Podcast Recommendation: Drug Story Atorvastatin (Lipitor)Life expectancy: Netherlands (82.2) vs Austria (82.0)Diagnostic and Statistical Manual of Mental Illnesses (DSM-5)Mechanism does not imply outcome. Outcome implies mechanism. - Layne NortonNo Biological Free Lunches🎙️AboutFit For Science is a deep-dive podcast hosted by two biological data scientists, Rob and Stephan, exploring the intersection of research, health tech, and data-driven lifestyle design. The hosts provide evidence-based systems, layered with practical "N=2" personal experimentation, to cut through the noise in the health and fitness industry.Learn more and subscribe on your favorite platforms:YouTubeSpotifyApple PodcastsAmazon Music⚠️Disclaimer: This podcast represents our own opinions and is for informational purposes only. It does not constitute medical or financial advice or a professional relationship.
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    1 hr and 25 mins