Can exercise actually be bad for you if you don’t get enough sleep? A widely shared claim says yes—that working out while sleep deprived may speed up aging. In this episode, we put that claim under the microscope. We examine the study behind it, unpack how sleep and aging were measured, and explore key statistical ideas like interaction effects and flexible models that can “dance” to the data. With the help of a $400,000 handbag and a man with seven boats, we also break down what it really takes to show that one variable changes the effect of another. What we find: some clear study bloopers, inconsistent modeling results, and interpretations that are flat-out wrong. 

Statistical topics

• Measurement error 
• Model specification
• Piecewise linear regression
• Regression models
• Residual confounding
• Splines
• Statistical interactions
• Survey design

Methodological morals

• “Before you believe something shocking, ask what had to go wrong to make it true.”
• “If slight modeling changes flip the story, there wasn't much story to begin with.”
• “Unethical Life Pro Tip: If you do not want your analysis critiqued, then just make it impossible to understand.”

Kristin’s Biological Age Calculator

References

• Original Viral Tweet: Ng D. "People who slept under 6 hours and exercised actually aged faster." X. March 9, 2026.
• Holmer B. Does exercise “age you faster” if you don’t sleep enough? Medium. March 16, 2026.
• You Y. Chen Y. Liu R., et al. Inverted U-shaped relationship between sleep duration and phenotypic age in US adults: a population-based study. Sci Rep. 2024;14:6247. 
• Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging. 2018;10:573-591. 

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Introduction
• (04:05) - What is NHANES?
• (06:38) - The Sleep Duration Results
• (12:50) - The 2015 Sleep Mystery
• (17:10) - Measuring Biological Aging
• (22:32) - The Penalized Cox Regression
• (29:13) - Sleep and Aging Results
• (31:00) - Cubic Splines and Dancing
• (38:08) - Adding Exercise to the Mix
• (42:16) - Boats, Handbags, and Interaction Effects
• (49:39) - The Cubic Spline Exercise Analysis
• (52:40) - The Opposite Result
• (57:13) - Academic Writing Gone Wrong
• (59:46) - The Writing Makeover
• (01:02:31) - Rating the Claim with Gatorinis

Are young people really having less sex? Headlines about a “sex recession” suggest a dramatic decline—but what do the data actually show? In this episode, we trace that claim back to the research behind it—and find a story that’s far more nuanced than the headlines suggest. We examine large national surveys, including the General Social Survey and the National Survey of Sexual Health and Behavior, and uncover how small analytical choices can completely change the story. Along the way, we tackle ordinal versus quantitative data, why averages can mislead, how logistic regression reframes the question, and what happens when researchers try to time-travel with statistics. Plus: the surprising role of extreme values, why “eight fewer sexual encounters per year” may not mean what you think, and whether young men and women are really following the same trends.

Statistical topics

• Average vs distribution
• Binary variables
• Effect size vs statistical significance
• Logistic regression
• Measurement / operationalization
• Ordinal variables
• Outliers / extreme values
• Self-reported datagoog
• Social desirability bias
• Variable coding / transformation

Methodological morals

• “You shouldn't use data from people in their 80s to guess what they were doing in their 20s unless your data come with a time machine.”
• “When extreme values drive the average, the average stops describing most people.”

References

• Julian K. Why are young people having so little sex? The Atlantic. December 2018. Accessed April 19, 2026. https://www.theatlantic.com/magazine/archive/2018/12/the-sex-recession/573949/
• Skwarecki B. Nearly half of Gen Z adults have never had sex: report. Newsweek. January 7, 2025. Accessed April 19, 2026. https://www.newsweek.com/nearly-half-of-gen-z-adults-have-never-had-sexreport-11052178
• Virginity survey. DatingAdvice.com. Accessed April 19, 2026. https://www.datingadvice.com/studies/virginity-survey
• Twenge JM, Sherman RA, Wells BE. Declines in sexual frequency among American adults, 1989-2014. Arch Sex Behav. 2017;46(8):2389-2401.
• Ueda P, Mercer CH, Ghaznavi C, Herbenick D. Trends in frequency of sexual activity and number of sexual partners among adults aged 18 to 44 years in the US, 2000-2018. JAMA Netw Open. 2020;3(6):e203833.
• Herbenick D, Rosenberg M, Golzarri-Arroyo L, et al. Changes in penile-vaginal intercourse frequency and sexual repertoire from 2009 to 2018: findings from the National Survey of Sexual Health and Behavior. Arch Sex Behav. 2022;51(3):1419-1433.
• Wellings K, Palmer MJ, Machiyama K, Slaymaker E. Changes in, and factors associated with, frequency of sex in Britain: evidence from three National Surveys of Sexual Attitudes and Lifestyles (Natsal). BMJ. 2019;365:l1525. Published 2019 May 7. doi:10.1136/bmj.l1525
• Burghardt J, Beutel ME, Hasenburg A, Schmutzer G, Brähler E. Declining Sexual Activity and Desire in Women: Findings from Representative German Surveys 2005 and 2016. Arch Sex Behav. 2020 Apr;49(3):919-925. doi: 10.1007/s10508-019-01525-9. Epub 2019 Dec 4. Erratum in: Arch Sex Behav. 2020 Apr;49(3):927. doi: 10.1007/s10508-019-01622-9. PMID: 31802290.
• Twenge JM. Possible Reasons US Adults Are Not Having Sex as Much as They Used To. JAMA Netw Open. 2020;3(6):e203889. Published 2020 Jun 1. doi:10.1001/jamanetworkopen.2020.3889

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Introduction
• (04:04) - Fact-Checking the Headlines
• (07:37) - The Twenge Study and the GSS
• (16:02) - The Hill-Shaped Trend
• (19:23) - The Ordinal Variable Problem
• (24:59) - The Married vs. Never-Married Paradox
• (28:39) - Time-Traveling to the 1920s
• (32:35) - The Ueda Study: A Better Approach
• (36:22) - The Two Classrooms
• (43:39) - What Counts as Sex?
• (50:49) - Historical Sex Terms
• (54:32) - The Sexual Repertoire Results
• (57:50) - Why Is This Happening?
• (01:04:09) - Rating the Claim

Diagnostic testing: what do those statistics actually tell you? Sensitivity, specificity, positive predictive value . . . you’ve probably seen these terms before. Maybe you memorized them for a test. But do you actually know what they mean? In this episode, we take a closer look at how diagnostic tests are evaluated—and how they’re often misinterpreted. From a genetic test for cellulite to a blood test for autism, we explore how “statistically significant” findings can turn into tests that don’t actually help anyone. Along the way we meet the freckle gene, the wanderlust gene, and infidelity gene.

Statistical topics

• Base Rate
• Bayes Rule
• Case-Control Study
• Matching
• Conditional Probability
• Sensitivity
• Specificity
• Positive Predictive Value
• Prevalence
• Negative Predictive Value
• False Positives and Negatives
• True Positives and Negatives

Methodological morals

• “A biomarker paper is not the same thing as a biomarker test.”
• “If your sample doesn't match the real world, then for all of your positive predictive value needs, call on Bayes' theorem.”

Detailed Show Notes with calculations

References

• Emanuele E, Bertona M, Geroldi D. A multilocus candidate approach identifies ACE and HIF1A as susceptibility genes for cellulite. Journal of the European Academy of Dermatology and Venereology; 2010. 24: 930-35. 
• https://genomelink.io/traits/cellulite
• https://www.genexdiagnostics.com/ 
• Ebstein RP, Novick O, Umansky R, et al. Dopamine D4 receptor (D4DR) exon III polymorphism associated with the human personality trait of Novelty Seeking. Nat Genet. 1996;12:78-80. 
• Kluger AN, Siegfried Z, Ebstein RP. A meta-analysis of the association between DRD4 polymorphism and novelty seeking. Mol Psychiatry. 2002;7:712-7.
• He Y, Martin N, Zhu G, Liu Y. Candidate genes for novelty-seeking: a meta-analysis of association studies of DRD4 exon III and COMT Val158Met. Psychiatr Genet. 2018 Dec;28(6):97-109. 
• Smith AM, King JJ, West PR, et al. Amino Acid Dysregulation Metabotypes: Potential Biomarkers for Diagnosis and Individualized Treatment for Subtypes of Autism Spectrum Disorder. Biol Psychiatry. 2019;85:345-54.
• Sainani K, Goodman S. Lack of Diagnostic Utility of “Amino Acid Dysregulation Metabotypes.”
  Biol Psychiatry. 2018; 85: e41-e42.

Kristin and Regina’s online courses

• Demystifying Data: A Modern Approach to Statistical Understanding  
• Clinical Trials: Design, Strategy, and Analysis 
• Medical Statistics Certificate Program  
• Writing in the Sciences 
• Epidemiology and Clinical Research Graduate Certificate Program 
• Programs that we teach in:
• Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Introduction
• (02:24) - The Cellulite Test
• (06:41) - Understanding Sensitivity and Specificity
• (12:50) - Enter Positive Predictive Value
• (18:40) - Why Base Rates Matter
• (24:06) - More Ridiculous Tests
• (33:30) - The Wanderlust Gene Deep Dive
• (41:27) - The NeuroPoint Autism Test
• (53:34) - Trying to Set the Record Straight
• (01:02:39) - Personal Stories
• (01:05:54) - Wrap-up

Epidurals are widely used and widely trusted for pain relief during labor. So when a 2020 study reported that they might be linked to autism, it raised a troubling question: could a routine medical decision have long-term consequences? We follow that claim from headline to evidence—and watch what happens when other scientists take a closer look. We dig into the original study, a wave of replication studies from around the world, and a meta-analysis that tries to make sense of it all. Along the way, we unpack hazard ratios, Cox regression, inverse probability weighting, and sibling analyses—and why even sophisticated statistical adjustment can’t eliminate confounding. Plus: why bigger datasets don’t solve everything, what happens when results shrink after adjustment, and how a controversial study turned into a case study in science working as it should. Bonus: our first guest journalist interview!

Statistical topics

• Confounding
• Cox regression
• Hazard ratios
• Inverse probability weighting (IPTW)
• Multivariable adjustment
• Observational studies
• Residual confounding
• Retrospective cohort studies
• Sibling analysis
• Statistical adjustment
• Statistical significance vs practical significance
• Survival analysis

Methodological morals

• “Every time you adjust the model and the effect gets smaller, that's the universe whispering, maybe don't build a causal story out of this.”
• “Consistency across studies is gold.”
• “There's more to the story than the statistics.”

References

• Dattaro, Laura. A questionable study linked autism to epidurals. Then what? Spectrum. April 18, 2023. 
• Dattaro, Laura. How to find baby sharks. Nautilus. September 9. 2024.
• Laura Dattaro’s home page.
• Phil Kearney’s blog post about the SMART framework.
• Qiu C, Lin JC, Shi JM, et al. Association Between Epidural Analgesia During Labor and Risk of Autism Spectrum Disorders in Offspring. JAMA Pediatr. 2020;174:1168-1175. 
• Joint Statement. Labor Epidurals Do Not Cause Autism; Safe for Mothers and Infants, say Anesthesiology, Obstetrics, and Pediatric Medical Societies. American Society of Anesthesiologists. October 12, 2020.
• Wall-Wieler E, Bateman BT, Hanlon-Dearman A, Roos LL, Butwick AJ. Association of Epidural Labor Analgesia With Offspring Risk of Autism Spectrum Disorders. JAMA Pediatr. 2021;175:698-705. 
• Christakis DA. More on epidurals and autism. JAMA Pediatrics. 2021; 175: 705.
• Mikkelsen AP, Greiber IK, Scheller NM, Lidegaard Ø. Association of Labor Epidural Analgesia With Autism Spectrum Disorder in Children. JAMA. 2021;326:1170–1177. 
• Hanley GE, Bickford C, Ip A, et al. Association of Epidural Analgesia During Labor and Delivery With Autism Spectrum Disorder in Offspring. JAMA. 2021;326:1178-1185. 
• Hegvik TA, Klungsøyr K, Kuja-Halkola R, et al. Labor epidural analgesia and subsequent risk of offspring autism spectrum disorder and attention-deficit/hyperactivity disorder: a cross-national cohort study of 4.5 million individuals and their siblings. Am J Obstet Gynecol. 2023;228:233.e1-233.e12. Epub 2022 Aug 13. Hu X, Wang B, Chen J, Han D, Wu J. 
• Association Between Epidural Labor Analgesia and Autism Spectrum Disorder in Offspring: A Systematic Review and Meta-Analysis. J Pain Res;17:227-240. 

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Intro
• (01:40) - Why autism is hard to study
• (05:18) - The original 2020 study
• (11:38) - Results & hazard ratios
• (15:24) - Confounding & adjustment
• (27:29) - Criticism & plausibility
• (35:08) - Replications begin
• (45:57) - Converging evidence & meta-analysis
• (52:07) - What does it mean?
• (54:57) - Guest & wrap-up

Every year we spring forward and lose an hour of sleep. But do we also lose a few heart cells? Some headlines claim that heart attacks spike by 24% after daylight saving time begins. In this episode we trace that number back to the research behind it—and what we find is more complicated than the headlines suggest. We examine a famous New England Journal of Medicine letter, a large international meta-analysis, and a massive modern U.S. registry study. Along the way we talk about incidence ratios, relative versus absolute risk, negative controls, and a haunting concept called harvesting. Plus: why bar charts are not for numerical data, why journalists love dramatic numbers, and how a bug collector helped invent daylight saving time.

Statistical topics

• Incidence ratios / incidence rates
• Meta-analysis
• Negative controls
• Relative risk vs absolute risk
• Statistical vs practical significance
• Statistical Sleuthing

Methodological morals

• “A bump in time isn’t always a bump in total.” 
• “If you already know the story you want to tell, you can always find a number to tell it.”  

References

• Bourke, India. “An obsessed insect hunter: The creepy-crawly origins of daylight saving.” BBC Future, March 31, 2024. https://www.bbc.com/future/article/20240308-how-first-suggestions-of-daylight-savings-time-was-inspired-by-insects
• Fox-Skelly, Jasmin. “How Daylight Saving Time Affects Your Health.” BBC Future, October 25, 2025. https://www.bbc.com/future/article/20251024-how-daylight-saving-time-affects-our-health
• Hurst A, Morfeld P, Lewis P, Erren TC. Daylight Saving Time Transitions and Risk of Heart Attack. Dtsch Arztebl Int. 2024;121(15):490-496. doi:10.3238/arztebl.m2024.0078
• Janszky I, Ljung R. Shifts to and from daylight saving time and incidence of myocardial infarction. N Engl J Med. 2008;359(18):1966-1968. doi:10.1056/NEJMc0807104
• Jiddou MR, Pica M, Boura J, Qu L, Franklin BA. Incidence of myocardial infarction with shifts to and from daylight savings time. Am J Cardiol. 2013;111(5):631-635. doi:10.1016/j.amjcard.2012.11.010
• Mellour, Richard. “The builder who changed how the world keeps time.” BBC Future, March 11, 2016. https://www.bbc.com/future/article/20160310-the-builder-who-changed-how-the-world-keeps-time
• Rymer JA, Li S, Chiswell K, et al. Daylight Savings Time and Acute Myocardial Infarction. JAMA Netw Open. 2025;8(9):e2530442. Published 2025 Sep 2. doi:10.1001/jamanetworkopen.2025.30442
• https://graph2table.com/

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Intro
• (05:03) - Strange history of daylight saving time
• (16:06) - Swedish NEJM study
• (19:14) - Incidence ratios explained
• (22:13) - What the Swedish study actually found
• (31:11) - Absolute vs relative risk
• (34:27) - Harvesting effect
• (40:10) - 2024 Meta-analysis
• (45:37) - Large modern US study
• (55:23) - Where the “24% increase” came from
• (59:16) - Wrap-up

How many carbs do you need to run your best marathon? Recent headlines suggest that 120 grams per hour is the magic number. But what’s the science behind that claim? To find out, we dug into the study fueling the hype — and were surprised by what we found. In this episode, we uncover numbers that mysteriously shift after peer review, figures that don’t match the text, and p-values that refuse to line up with their confidence intervals. Along the way, we swap bonking stories, revisit repeated-measures ANOVA, renew our antipathy for spreadsheets, and follow a trail of statistical termites to a surprisingly happy scientific ending.

Statistical topics

• Article in press vs final publication
• Data management and workflow
• Multiple testing
• P-values and confidence intervals
• Repeated Measures ANOVA
• Statistical sleuthing
• Version control in research
• Within-person study design

Methodological morals

• “Everyone makes statistical mistakes, not everyone fixes them.”
• “If the numbers aren't consistent, Excel is often part of the story.”
• “If a p-value doesn't survive the trip from text to figure, there's a problem.”

Statistical Sleuthing Extended Notes

References

• Ravikanti S, Silang KG, Martyn HJ, et al. 13C-labelled glucose–fructose show greater exogenous and whole-body CHO oxidation and lower O2 cost of running at 120 versus 60 and 90 g·h−1 in elite male marathoners. J Appl Physiol. 2025;139:1581–95. (final version)
• Article in Press of J Appl Physiol. 2025;139:1581–95. 
• graph2table AI data extraction from figures. Use the discount code normalcurves20 for 20% off!
• Bob Kempainen gutting out the win at the 1996 U.S. Olympic Marathon Trials.
• N=7 is a Dinner Party LinkedIn Post
• WebPlotDigitizer
• Holmer B. The new high-carb study that’s rocking the running world. Marathon Handbook. Dec 5, 2025.
• Ivy JL, Miller W, Dover V, et al. Endurance improved by ingestion of a glucose polymer supplement. Med Sci Sports Exerc. 1983; 15:466–471.
• Coyle EF, Coggan AR, Hemmert MK, et al. Muscle glycogen utilization during prolonged strenuous exercise when fed carbohydrate. J Appl Physiol. 1986; 61:165–172.
• Coggan AR, Coyle EF. Reversal of fatigue during prolonged exercise by carbohydrate infusion or ingestion. J Appl Physiol. 1987; 63:2388–2395.
• Below PR, Mora-Rodríguez R, González-Alonso J, et al. Fluid and carbohydrate ingestion independently improve performance during 1 h of intense exercise. Med Sci Sports Exerc. 1995; 27:200–210.
• American College of Sports Medicine. Position stand: Nutrition and athletic performance. Med Sci Sports Exerc. 1996.
• Jeukendrup AE, Jentjens R. Oxidation of carbohydrate feedings during prolonged exercise: current thoughts, guidelines and directions for future research. Sports Med. 2000; 29:407–424.
• Currell K, Jeukendrup AE. Superior endurance performance with ingestion of multiple transportable carbohydrates. Med Sci Sports Exerc. 2008; 40:275–281.
• American Dietetic Association, Dietitians of Canada, American College of Sports Medicine, et al. Nutrition and athletic performance. Med Sci Sports Exerc. 2009; 41:709–731.
• Triplett D, Doyle JA, Rupp JC, et al. An isocaloric glucose–fructose beverage's effect on simulated 100-km cycling performance compared with a glucose-only beverage. Int J Sport Nutr Exerc Metab. 2010; 20:122–131.
• Stellingwerff T, Cox GR. Systematic review: carbohydrate supplementation on exercise performance or capacity of varying durations. Appl Physiol Nutr Metab. 2014; 39:998–1011.
• Thomas DT, Erdman KA, Burke LM. Position of the Academy of Nutrition and Dietetics, Dietitians of Canada, and the American College of Sports Medicine: Nutrition and athletic performance. Med Sci Sports Exerc. 2016.
• King AJ, O’Hara JP, Morrison DJ, et al. Carbohydrate dose influences liver and muscle glycogen oxidation and performance during prolonged exercise. Physiol Rep. 2018; 6:e13555.
• Urdampilleta A, Mielgo-Ayuso J, Martínez-Sanz JM, et al. Effects of 120 vs 90 g·h⁻¹ carbohydrate intake during a mountain marathon on neuromuscular function and high-intensity run capacity recovery. Nutrients. 2020; 12:2099.
• Podlogar T, Bescós R, Wallis GA, et al. Increased exogenous but unaltered endogenous carbohydrate oxidation with 120 vs 90 g·h⁻¹ carbohydrate ingestion during prolonged endurance exercise. Front Nutr. 2022; 9:936691.
• Smith JW, Pascoe DD, Passe DH, et al. Curvilinear dose-response relationship of carbohydrate (0–120 g·h⁻¹) and performance. Med Sci Sports Exerc. 2013; 45:336–341.
• Lukasiewicz C, Vandiver KJ, Albert ED, et al. Assessing exogenous carbohydrate intake needed to optimize human endurance performance across sex: insights from modeling runners pursuing a sub-2-hour marathon. J Appl Physiol. 2024.

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Can a list of questions really make two strangers fall in love? In 2015, a viral New York Times Modern Love column claimed psychologists had discovered a formula for love: 36 increasingly personal questions, plus four minutes of eye contact. Millions of people tried it. There was even an app. But when we followed the citation trail back to the science, the story started to unravel. In this episode, we crack open the 1997 study behind the “36 Questions,” unearth a forgotten pilot study with a different (and sexier) protocol, and track down the real origin of the eye-gazing task. Along the way, we break down why control groups matter, why scale midpoints mislead, and why group averages aren’t people. We also try the questions on each other—purely for science, of course—and ask the nerdiest Valentine’s Day question of all: can a list of questions really make anyone fall in love?

Statistical topics

• Control groups
• Correlated observations
• Group averages vs individual inference
• Pilot studies
• Reference distributions
• Scale interpretation
• Units of observation

Methodological morals

• “Before you repeat a scientific claim, follow it back to the original study and read it carefully.”
• “You can slice the data into subgroups all you want, but that doesn't magically give you a control group. It gives you meaningless results.”

Our version of the “40 Questions” app!

References

• Aron, A., Aron, E.N., Melinat, E. and Vallone, R., 1991. Experimentally induced closeness, ego identity, and the opportunity to say no. In Conference of the International Network on Personal Relationships, Normal, IL.
• Aron, A., Melinat, E., Aron, E.N., Vallone, R.D. and Bator, R.J., 1997. The experimental generation of interpersonal closeness: A procedure and some preliminary findings. Personality and social psychology bulletin, 23(4), pp.363-377.
• Catron, Mandy L. To fall in love with anyone, do this. New York Times. January 11, 2015. https://www.nytimes.com/2015/01/11/style/modern-love-to-fall-in-love-with-anyone-do-this.html
• Catron, M.L., 2017. How to fall in love with anyone: a memoir in essays. Simon and Schuster.
• Jones, Daniel. The 36 Questions That Lead to Love. New York Times. January 9, 2015. https://www.nytimes.com/2015/01/09/style/no-37-big-wedding-or-small.html
• Kashdan, T.B. and Wenzel, A., 2005. A transactional approach to social anxiety and the genesis of interpersonal closeness: Self, partner, and social context. Behavior Therapy, 36(4), pp.335-346.
• Lee, Anna G. Long After ‘36 Questions,’ Finally Asking a Bigger One. New York Times. May 16, 2025. https://www.nytimes.com/2015/01/09/style/no-37-big-wedding-or-small.html
• Sprecher, S., 2021. Closeness and other affiliative outcomes generated from the Fast Friends procedure: A comparison with a small-talk task and unstructured self-disclosure and the moderating role of mode of communication. Journal of Social and Personal Relationships, 38(5), pp.1452-1471.
• Vacharkulksemsuk T, Fredrickson BL. Strangers in sync: Achieving embodied rapport through shared movements. J Exp Soc Psychol. 2012;48(1):399-402. doi:10.1016/j.jesp.2011.07.015
• Mandy Len Catron’s TEDx talk: https://www.youtube.com/watch?v=v8Yo-PXN7UA
• Ivan Vendrov’s Twitter/X post about his exchange with Arthur Aron: https://x.com/IvanVendrov/status/1611809736823013377/photo/1
• https://www.scientificamerican.com/podcast/episode/love-and-the-brain-part-1-the-36-questions-revisited/
• Our version of the “40 Questions” app: https://www.normalcurves.com/questions-to-fall-in-love/

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Intro
• (04:42) - Viral NYT Modern Love essay’s cultural influence
• (09:32) - Science behind the 36 questions
• (15:07) - The 1997 paper myth busting
• (19:49) - Sleuthing the pilot study
• (30:41) - What did the 1997 paper actually show
• (42:21) - Discussion section
• (51:55) - Did it replicate
• (58:44) - Wrap up

While we’re on a short break between seasons, we’re revisiting some of our favorite episodes from Season 1. This week, we’re re-releasing our debut episode on pheromones and sexy sweat, with some added commentary up front..

Sweaty t-shirt dating parties, sex pheromone dating sites, choosing your dating partner by sniffing them up — wacko fringe fads or evidence-based mating strategies? And what does your armpit stain have to do with your kids’ immune systems, or hormonal contraceptive pills, or divorce rates? 

In this episode, we reach back into the 1990s and revisit the scientific paper that started it all: The Sweaty T-Shirt Study. They bring a sharp eye and open mind, critically examining the study and following the line of research to today. Along the way, they encounter interesting statistical topics – including correlated observations, within-person study design, and bar chart blasphemy – with a short, surprising detour into Neanderthal sex. 

Statistical topics

• Bar charts 
• Correlated observations
• Cherry-picking
• Data and methodological transparency
• Multiple testing
• Post-hoc analyses
• Unit of observation / unit of anaysis
• Within-person study design

Methodological morals

“Repeat after me: Bar charts are not for numerical data.”

“Those who ignore dependencies in their data are destined for flawed conclusions.”

References

• Nuzzo, R. Ah, Love at first whiff. Los Angeles Times. May 19, 2008.
• Papamarko, S. Pheromone parties attempt to match singles by scent. Yahoo!life. April 12, 2012.
• Sainani, K. Stone Age Gene Swap. Stanford Magazine. November/December 2011.
• Aldhous, P. Darling, You Smell Wonderfully Different. New Scientist. 6 May 1995.
• Wedekind C, Seebeck T, Bettens F, Paepke AJ. MHC-dependent mate preferences in humans. Proc Biol Sci. 1995; 260(1359):245-249. doi:10.1098/rspb.1995.0087
• Hedrick P, Loeschcke V. MHC and mate selection in humans?. Trends Ecol Evol. 1996;11(1):24. doi:10.1016/0169-5347(96)80237-0
• Wedekind C, Seebeck T. Reply from C. Wedekind and T. Seebeck. Trends Ecol Evol. 1996;11(1):24-25. doi:10.1016/0169-5347(96)81061-5
• Wedekind C, Füri S. Body odour preferences in men and women: do they aim for specific MHC combinations or simply heterozygosity?. Proc Biol Sci. 1997;264(1387):1471-1479. doi:10.1098/rspb.1997.0204
• Havlíček J, Winternitz J, Roberts SC. Major histocompatibility complex-associated odour preferences and human mate choice: near and far horizons. Philos Trans R Soc Lond B Biol Sci. 2020;375(1800):20190260. doi:10.1098/rstb.2019.0260

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Introduction
• (06:09) - Conclusion
• (06:16) - Breaking Down the Original Sweaty T-Shirt Study
• (06:16) - Study Design Flaws and Data Transparency Issues
• (06:17) - Media Reactions and the Study’s Public Impact
• (06:26) - The Pill's Influence on Scent Preferences
• (06:30) - Analyzing the Study's Questionable Results
• (06:30) - Other Studies and their results
• (06:34) - Overstated Conclusions and Wandering Discussions
• (06:35) - Pheromone Dating Parties
• (06:39) - Statistical Flaws: Correlated Observations Explained
• (06:55) - The Science of HLA Genes and Mate Selection
• (07:05) - Pheromone Dating Sites and Genetic Matching

While we’re on a short break between seasons, we’re revisiting some of our favorite episodes from Season 1. This week, we’re re-releasing our exploration of how your diet can affect your skin – now with added commentary!

Wrinkles and sagging skin—just normal aging, or can you blame your sweet tooth? We dive into “sugar sag,” exploring how sugar, processed foods, and even your crispy breakfast toast might be making you look older than if you’d said no to chocolate cake and yes to broccoli. Along the way, we encounter statistical adjustment, training and test data sets, what we call “references to nowhere,” plus some cadavers and collagen. Ever heard of an AGE reader? Find out how this tool might offer a sneak peek at your date’s age—and maybe even a clue about his… um… “performance.”

Statistical topics 

• Confounding
• Correlation vs causation
• Measurement error / proxy variables
• Overfitting 
• Plagiarism
• Proper citing practices
• References to nowhere
• Statistical adjustment
• Training and test sets

Methodologic morals

• “When you plagiarize, you steal the errors too.”
• “Overdone statistical adjustment is like overdone photo filters–at a certain point it’s just laughable.”

Citations

Collagen turnover: 

• Verzijl N, DeGroot J, Thorpe SR, et al.Effect of Collagen Turnover on the Accumulation of Advanced Glycation End Products. JBC. 2000;275:39027-31.

Cadaver study:

• Hamlin CR, Kohn RR, Luschin JH. Apparent Accelerated Aging of Human Collagen in Diabetes Mellitus. Diabetes. 1975; 24: 902–904.

AGE Reader

Studies of AGEs and diabetes and health:

• Monnier VM, Cerami A. Nonenzymatic browning in vivo: possible process for aging of long-lived proteins. Science. 1981;211:491-3. 
• Brownlee M, Vlassara H, Cerami A. Nonenzymatic glycosylation and the pathogenesis of diabetic complications. Ann Intern Med. 1984;101:527-37. 
• Monnier VM, Vishwanath V, Frank KE, et al. Relation between Complications of Type I Diabetes Mellitus and Collagen-Linked Fluorescence. N Engl J Med. 1986;314:403-408.
• Monnier VM, Sell DR, Abdul-Karim FW, et al. Collagen browning and cross-linking are increased in chronic experimental hyperglycemia. Relevance to diabetes and aging. Diabetes. 1988;37:867-72. 
• Monnier VM, Bautista O, Kenny D, et al. Skin collagen glycation, glycoxidation, and crosslinking are lower in subjects with long-term intensive versus conventional therapy of type 1 diabetes: relevance of glycated collagen products versus HbA1c as markers of diabetic complications. Diabetes 1999; 48: 870–80.
• Genuth S, Sun W, Cleary P, et al. Glycation and carboxymethyllysine levels in skin collagen predict the risk of future 10-year progression of diabetic retinopathy and nephropathy in the diabetes control and complications trial and epidemiology of diabetes interventions and complications participants with type 1 diabetes. Diabetes. 2005;54:3103-11. 
• van Waateringe RP, Slagter SN, van Beek AP, et al. Skin autofluorescence, a non-invasive biomarker for advanced glycation end products, is associated with the metabolic syndrome and its individual components. Diabetol Metab Syndr. 2017;9:42. 
• Kouidrat Y, Zaitouni A, Amad A, et al. Skin autofluorescence (a marker for advanced glycation end products) and erectile dysfunction in diabetes. J Diabetes Complications. 2017;3:108-113. 
• Fujita N, Ishida M, Iwane T, et al. Association between Advanced Glycation End-Products, Carotenoids, and Severe Erectile Dysfunction. World J Mens Health. 2023;41:701-11. 
• Uruska A, Gandecka A, Araszkiewicz A, et al. Accumulation of advanced glycation end products in the skin is accelerated in relation to insulin resistance in people with Type 1 diabetes mellitus. Diabet Med. 2019;36:620-625. 
• Boersma HE, Smit AJ, Paterson AD, et al. Skin autofluorescence and cause-specific mortality in a population-based cohort. Sci Rep 2024;14:19967.

Review article with conflicts of interest: 

• Draelos ZD. Sugar Sag: What Is Skin Glycation and How Do You Combat It? J Drugs Dermatol. 2024; 23:s5-10.

Clinical study on AGE interrupter cream:

• Draelos ZD, Yatskayer M, Raab S, Oresajo C. An evaluation of the effect of a topical product containing C-xyloside and blueberry extract on the appearance of type II diabetic skin. J Cosmet Dermatol. 2009;8:147-51. 

Our citation trail:

• 2023 review article: Zgutka K, Tkacz M, Tomasiak, et al. A Role for Advanced Glycation End Products in Molecular Ageing. Int J Mol Sci. 2023; 24: 9881. Sentence: “Interestingly, strict control of blood sugar for 4 months reduced the production of glycosylated collagen by 25%, and low-sugar food prepared by boiling could also reduce the production of AGEs [152].”
• Reference 152 is a review article: Cao C, Xiao Z, Wu Y, et al. Diet and Skin Aging-From the Perspective of Food Nutrition. Nutrients. 2020;12:870. Sentence: “However, strict control of blood sugar for four months can reduce the production of glycosylated collagen by 25%, and low-sugar food prepared by boiling can also reduce the production of AGEs [93–95].”
• Reference 93 is a review article: Nguyen HP, Katta R. Sugar sag: Glycation and the role of diet in aging skin. Skin Ther Lett. 2015; 20: 1–5. Sentence: “Tight glycemic control over a 4-month period can result in a reduction of glycated collagen formation by 25%.37,38”
• Reference 94 and 38 is a review article: Draelos ZD. Aging skin: the role of diet: facts and controversies. Clin Dermatol. 2013;31:701-6. Sentence: “Tighter glycemic control can reduce glycated collagen by 25% in 4 months.” No citation given....

While we’re on a short break between seasons, we’re revisiting some of our favorite episodes from Season 1. This week, we’re re-releasing our deep dive into vitamin D and the origins of the so-called deficiency epidemic, with added commentary.

Is America really facing an epidemic of vitamin D deficiency? While this claim is widely believed, the story behind it is packed with twists, turns, and some pesky statistical cockroaches. In this episode, we’ll dive into a study on Hawaiian surfers, expose how shifting goalposts can create an epidemic, tackle dueling medical guidelines, and flex our statistical sleuthing skills. By the end, you might wonder if the real deficiency lies in the data.

Statistical topics

• conflicts of interest
• cut points and thresholds
• dichotomization
• incentives in science
• measurement and classification
• normal distribution 
• researcher biases
• standard deviation
• statistical sleuthing

Methodologic morals

• “Arbitrary thresholds make for arbitrary diseases.”
• “Statistical errors are like cockroaches: Where there’s one, there’s many.”

Note that all blood vitamin D levels discussed in the podcast are 25-hydroxyvitamin D levels given in units of ng/ml. To convert from ng/ml to nmol/L, use the formula: nmol/L=2.5*ng/ml. For example, a vitamin D level of 30 ng/mL corresponds to 75 nmol/L.

Citations
Dr. Rhonda Patrick: Micronutrients for Health & Longevity. Huberman Lab Podcast. May 1, 2022

Noh CK, Lee MJ, Kim BK, et al. A Case of Nutritional Osteomalacia in Young Adult Male. J Bone Metab. 2013; 20:51-55.

Binkley N, Novotny R, Krueger D, et al. Low vitamin D status despite abundant sun exposure. J Clin Endocrinol Metab. 2007;92:2130-5. 

Malabanan A, Veronikis IE, Holick MF. Redefining Vitamin D Insufficiency. Lancet. 1998;351:805-6. 

Dawson-Hughes B, Heaney RP, Holick MF, et al. Estimates of optimal vitamin D status. Osteoporos Int. 2005;16:713-6.

Holick MF. Vitamin D deficiency. N Engl J Med. 2007;357:266-81.

Cui A, Xiao P, Ma Y, et al. Prevalence, trend, and predictor analyses of vitamin D deficiency in the US population, 2001-2018. Front Nutr. 2022;9:965376. 

Ross AC, Manson JE, Abrams SA, et al. The 2011 report on dietary reference intakes for calcium and vitamin D from the Institute of Medicine: what clinicians need to know. J Clin Endocrinol Metab. 2011;96:53-8. 

Holick MF, Binkley NC, Bischoff-Ferrari HA, et al. Evaluation, Treatment, and Prevention of Vitamin D Deficiency: an Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2011;96:1911-30. 

Manson JE, Brannon PM, Rosen CJ, et al. Vitamin D deficiency-is there really a pandemic. N Engl J Med. 2016;375:1817-20. 

Conti G, Chirico V, Lacquaniti A, et al. Vitamin D intoxication in two brothers: be careful with dietary supplements. J Pediatr Endocrinol Metab. 2014;27:763-7.

Holick, Michael, et al. The UV Advantage. Ibooks, 2004.

Holick, Michael F. The Vitamin D Solution: A 3-Step Strategy to Cure Our Most Common Health Problems. Penguin Publishing Group, 2011.

Szabo, Liz. Vitamin D, the Sunshine Supplement, Has Shadowy Money Behind It. The New York Times. August 18, 2018.

Lee JM, Smith JR, Philipp BL, Chen TC, Mathieu J, Holick MF. Vitamin D deficiency in a healthy group of mothers and newborn infants. Clin Pediatr. 2007;46:42-4. 

Holick MF. Vitamin D deficiency: what a pain it is. Mayo Clin Proc. 2003;78:1457-9.

Passeri G, Pini G, Troiano L, et al. Low Vitamin D Status, High Bone Turnover, and Bone Fractures in Centenarians. J Clin Endocrinol Metab. 2003;88:5109-15. 

Armstrong, David. The Child Abuse Contrarian. ProPublica. September 16, 2018.

Irwig MS, Kyinn M, Shefa MC. Financial Conflicts of Interest Among Authors of Endocrine Society Clinical Practice Guidelines. J Clin Endocrinol Metab. 2018;103:4333-38. 

Demay MB, Pittas AG, Bikle DD, et al. Vitamin D for the Prevention of Disease: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2024;109:1907-47.

McCartney CR, McDonnell ME, Corrigan MD, et al. Vitamin D Insufficiency and Epistemic Humility: An Endocrine Society Guideline Communication. J Clin Endocrinol Metab. 2024; 109:1948–54.

See our detailed notes here

Kristin and Regina’s online courses
Demystifying Data: A Modern Approach to Statistical Understanding 

Clinical Trials: Design, Strategy, and Analysis

Medical Statistics Certificate Program 

Writing in the Sciences

Epidemiology and Clinical Research Graduate Certificate Program

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn...

Description

Nobody expects Batman—but when he shows up in a crowded subway car, are people suddenly more likely to help a passenger in need? This week on Normal Curves, we unpack a recent quasi-experimental field study involving a caped superhero costume, a prosthetic pregnancy belly, and some puzzled Italian commuters. Along the way, we demystify three common ways of describing effects for binary outcomes—risk differences, risk ratios, and odds ratios—and explain what they actually mean in plain language. We also do some statistical sleuthing, uncover a major problem hiding in the paper’s numbers, and debate what really counts as an effective Batman outfit.

Statistical topics

• absolute vs relative effects
• binary outcomes
• coding errors
• data errors and quality control
• effect size interpretation
• field experiments
• odds
• odds ratios
• percentage differences
• quasi-experimental studies
• risk differences
• risk ratios
• statistical sleuthing

Methodological morals

• “We love an uncluttered paper, but when it's missing the basics, it's like an empty fridge. Clean, yes, but dinner is not happening.”
• “Before you make a fancy model, make sure the numbers in the table in the text match.”

References

• Pagnini F, Grosso F, Cavalera C, et al. Unexpected events and prosocial behavior: the Batman effect. Npj Ment Health Res. 2025;4(1):57. Published 2025 Nov 3. doi:10.1038/s44184-025-00171-5
• PubPeer. Comments on “Unexpected events and prosocial behavior: the Batman effect.” Accessed December 2025.
• Sainani KL. Understanding odds ratios. PM R. 2011;3(3):263-267. doi:10.1016/j.pmrj.2011.01.009
• Nuzzo RL. Communicating measures of relative risk in plain English. PM R. 2022;14(2):283-287. doi:10.1002/pmrj.12761
• Sainani KL. How statistics can mislead. Am J Public Health. 2012;102:e3-4.

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin -  LinkedIn & Twitter/X

Regina - LinkedIn & ReginaNuzzo.com

• (00:00) - Intro
• (03:42) - Why would Batman make people nicer?
• (07:33) - How they ran the experiment
• (17:50) - Did Batman save the day? Different ways to answer that
• (23:00) - What are odds and odds ratios?
• (30:00) - Where people get it wrong
• (34:52) - The plot twist: big numerical errors
• (41:20) - Did men or women give up their seat more often?
• (43:49) - Wrap-up and methodological morals