Normal Curves: Sexy Science, Serious Statistics

Are we all secretly ageist when it comes to dating? We put the stereotype that older men prefer younger women under the microscope using data from thousands of blind dates. What we found surprised us: the “age penalty” was real but microscopic, women wanted younger partners too, and hard age cutoffs weren’t so hard after all. Along the way, we unpack statistical significance versus practical importance, play with the infamous “half your age plus seven” rule, and imagine what it would take for love to die out… somewhere around age 628.Statistical topicsDiscontinuous regressionEffect sizesExtrapolation pitfallsLinear regressionLogistic regressionOdds ratiosOpen dataStatistical significance vs. practical significanceMethodological morals“Do not be swept off your feet by statistical significance. Tiny effects in bed are still tiny.”“Fancy units sound smart, but plain English wins hearts.”Show Notes Technical Appendix (with step-by-step explanations)ReferencesEastwick PW, Finkel EJ, Meza EM, Ammerman K. No gender differences in attraction to young partners: A study of 4500 blind dates. Proc Natl Acad Sci U S A. 2025 Feb 4;122(5):e2416984122. Matchmaking Dataset and Code on Open Science Framework: https://osf.io/rkm2d/?view_only=a0fe91dae0464077af7772e6890a8151Nuzzo RL. Communicating measures of relative risk in plain English. PM&R. 2022 Feb;14(2):283-7.O'Rell, Max. Her Royal Highness, Woman: And His Majesty--Cupid. Abbey Press, 1901.Sainani KL. Logistic regression. PM&R. 2014 Dec;6(12):1157-62.Sainani KL. Understanding odds ratios. PM&R. 2011 Mar;3:263-7. Sainani KL. Clinical versus statistical significance. PM&R. 2012 Jun;4:442-5.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/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Intro (04:01) - Half-your-age-plus-seven rule (09:15) - Matchmaking service for the study (17:59) - Blind dates as natural experiments (22:49) - Regression results part 1: Age penalties? (29:32) - Wait, how big of an effect was that? (35:03) - Odds ratio of a second date (38:55) - Surprising age pair-ups (41:47) - Regression results part 2: Deal-breaking age limits? (45:21) - Why the patterns may or may not be true (47:24) - Wrap-up, ratings, and methodological morals

ChatGPT is melting our brainpower, killing creativity, and making us soulless — or so the headlines imply. We dig into the study behind the claims, starting with quirky bar charts and mysterious sample sizes, then winding through hairball-like brain diagrams and tens of thousands of statistical tests. Our statistical sleuthing leaves us with questions, not just about the results, but about whether this was science’s version of a first date that looked better on paper.Statistical topicsANOVABar graphsData visualization False Discovery Rate correctionMultiple testingPreprintsStatistical SleuthingMethodological morals"Treat your preprints like your blind dates. Show up showered and with teeth brushed.""Always check your N. Then check it again.""Never make a bar graph that just shows p-values. Ever."Link to paperKristin 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 ProgramPrograms that we teach in:Epidemiology and Clinical Research Graduate Certificate Program Find us on:Kristin -  LinkedIn & Twitter/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Intro (03:46) - Media coverage of the study (08:35) - The experiment (12:09) - Sample size issues (13:11) - Bar chart sleuthing (19:15) - Blind date analogy (23:51) - Interview results (30:01) - Simple text analysis results (34:01) - Natural language processing results (40:57) - N-gram and ontology analysis results (45:52) - Teacher evaluation results (52:27) - Neuroimaging analysis (01:00:29) - Multiple testing and connectivity issues (01:06:07) - Brain adaptation results (01:09:44) - Wrap-up, rating, and methodological morals

Can correcting misinformation make it worse? The “backfire effect” claims that debunking myths can actually make false beliefs stronger. We dig into the evidence — from ghost studies to headline-making experiments — to see if this psychological plot twist really holds up. Along the way, we unpack interaction effects, randomization red flags, and what happens when bad citations take on a life of their own. Plus: dirty talk analogies, statistical sleuthing, and why “familiarity” might be your brain’s sneakiest trick.Statistical topicsComputational replicationReplicationBlock randomizationProblems in randomizationBad citingInteractions in regressionUnpublished "Ghost Paper"PDF retrieved from the Wayback MachineCitationsNyhan B, Reifler J. When corrections fail: The persistence of political misperceptions. Political Behavior. 2010;32:303–330.Skurnik I, Yoon C, Schwarz N. “Myths & Facts” about the flu: Health education campaigns can reduce vaccination intentions. Unpublished manuscript, PDF posted separately.Schwarz N, Sanna LJ, Skurnik I, et al. Metacognitive experiences and the intricacies of setting people straight: Implications for debiasing and public information campaigns. Advances in Experimental Social Psychology. 2007;39:127–61.Lewandowsky S, Ecker UKH, Seifert CM, et al. Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest. 2012;13:106–131.Pluviano S, Watt C, Della Sala S. Misinformation lingers in memory: Failure of three pro-vaccination strategies. PLOS ONE. 2017;12:e0181640.Pluviano S, Watt C, Ragazzini G, et al. Parents’ beliefs in misinformation about vaccines are strengthened by pro‑vaccine campaigns. Cognitive Processing. 2019;20:325–31.Wood T, Porter E. The elusive backfire effect: Mass attitudes’ steadfast factual adherence. Political Behavior. 2019;41:135–63.Nyhan B, Porter E, Reifler J, Wood TJ. Taking fact-checks literally but not seriously? The effects of journalistic fact-checking on factual beliefs and candidate favorability. Political Behavior. 2020;42:939–60.Ecker UKH, Hogan JL, Lewandowsky S. Reminders and repetition of misinformation: Helping or hindering its retraction? Journal of Applied Research in Memory and Cognition. 2017;6:185–92.Swire B, Ecker UKH, Lewandowsky S. The role of familiarity in correcting inaccurate information. Journal of Experimental Psychology: Learning, Memory, and Cognition. 2017;43:1948–61.Ecker UKH, O’Donnell M, Ang LC, et al. The effectiveness of short- and long-format retractions on misinformation belief and recall. British Journal of Psychology. 2020;111:36–54.Ecker UKH, Sharkey CXM, Swire-Thompson B. Correcting vaccine misinformation: A failure to replicate familiarity or fear-driven backfire effects. PLOS ONE. 2023;18:e0281140.Cook J, Lewandowsky S. The Debunking Handbook. University of Queensland. 2011.Lewandowsky S, Cook J, Ecker UKH, et al. The Debunking Handbook 2020. Available at https://sks.to/db2020. Swire‑Thompson B, DeGutis J, Lazer D. Searching for the backfire effect: Measurement and design considerations. Journal of Applied Research in Memory and Cognition. 2020;9:286–99.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/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - (00:00) - Intro (02:05) - What is the backfire effect? (03:55) - The 2010 paper that panicked fact-checkers (06:25) - The ghost paper what it really said (12:35) - Study design of the 2010 paper (19:19) - Results of the 2010 paper (20:49) - Crossover interactions, regression models, and intimate talk (26:18) - Missing data and cleaning your bedroom analogy (29:05) - Fact-checking the fact-checking paper (34:01) - Replication and pushing the data to the limit (37:53) - The purported backfire effect spreads (42:00) - The 2017 paper that got a lot of attention (45:19) - Statistical sleuthing the 2017 paper (49:45) - Will researchers double down on their earlier conclusions? (55:40) - A review paper sums it all up (56:54) - Wrap up, rating, and methodological morals

Loyal, funny, hot — you’ve probably got a wish list for your dream partner. But does checking all your boxes actually lead to happily ever after? In this episode, we dive into a massive global study that put the “ideal partner” hypothesis to the test. Do people really know what they want, and does getting it actually make them happier? We explore surprising statistical insights from over 10,000 romantics in 43 countries, from mean-centering and interaction effects to the good-catch confounder. Along the way, we dig into dessert metaphors, partner boat-count regression models, and the one trait that people say doesn’t matter — but secretly makes them happiest.Statistical topicsRegressionRandom Slopes and Intercepts (Random Effects) in RegressionStandardized Beta Coefficients in RegressionInteraction Effects in RegressionMean CenteringExploratory AnalysesMethodological morals“Good science bares it all.”“When the world isn't one size fits all, don't fit just one line; use random slopes and intercepts.”ReferencesEastwick PW, Sparks J, Finkel EJ, Meza EM, Adamkovič M, Adu P, Ai T, Akintola AA, Al-Shawaf L, Apriliawati D, Arriaga P, Aubert-Teillaud B, Baník G, Barzykowski K, Batres C, Baucom KJ, Beaulieu EZ, Behnke M, Butcher N, Charles DY, Chen JM, Cheon JE, Chittham P, Chwiłkowska P, Cong CW, Copping LT, Corral-Frias NS, Ćubela Adorić V, Dizon M, Du H, Ehinmowo MI, Escribano DA, Espinosa NM, Expósito F, Feldman G, Freitag R, Frias Armenta M, Gallyamova A, Gillath O, Gjoneska B, Gkinopoulos T, Grafe F, Grigoryev D, Groyecka-Bernard A, Gunaydin G, Ilustrisimo R, Impett E, Kačmár P, Kim YH, Kocur M, Kowal M, Krishna M, Labor PD, Lu JG, Lucas MY, Małecki WP, Malinakova K, Meißner S, Meier Z, Misiak M, Muise A, Novak L, O J, Özdoğru AA, Park HG, Paruzel M, Pavlović Z, Püski M, Ribeiro G, Roberts SC, Röer JP, Ropovik I, Ross RM, Sakman E, Salvador CE, Selcuk E, Skakoon-Sparling S, Sorokowska A, Sorokowski P, Spasovski O, Stanton SCE, Stewart SLK, Swami V, Szaszi B, Takashima K, Tavel P, Tejada J, Tu E, Tuominen J, Vaidis D, Vally Z, Vaughn LA, Villanueva-Moya L, Wisnuwardhani D, Yamada Y, Yonemitsu F, Žídková R, Živná K, Coles NA. A worldwide test of the predictive validity of ideal partner preference matching. J Pers Soc Psychol. 2025 Jan;128(1):123-146. doi: 10.1037/pspp0000524Love Factually Podcast: https://www.lovefactuallypod.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/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - (00:00) - Intro (04:57) - Actual dating profile wishlists vs study wishlists (09:12) - Juicy paper details (18:31) - What the study actually asked – wishlist, partner resume, relationship satisfaction (25:04) - Linear regression illustrated through number of boats your partner has (31:31) - Standardized regression coefficients illustrated through spouse height concordance (35:46) - Good catch confounder: We all just want the same high-quality ice cream / mate (40:40) - Does your personalized wishlist matter? Results (42:55) - Wishlist regression interaction effects: like chocolate and peanut butter (46:45) - Partner traits result in happiness bonus points (50:45) - What do we say we want – and what really makes us happy? Surprise (55:04) - Gender stereotypes and whether they held up (57:45) - Random effects models and boats again (01:00:24) - Other cool things they did (01:01:35) - One-minute paper summary (01:03:17) - Wrap-up, rate the claim, methodological morals

It’s our first stats reunion! In this special review episode, we revisit favorite concepts from past episodes—p-values, multiple testing, regression adjustment—and give them fresh personalities as characters. Meet the seductive false positive, the clingy post hoc ex, and Charlotte, the well-meaning but overfitting idealist.Statistical topicsBar charts vs Box plotsBonferroni correctionConfoundingFalse positives Multiple testingMultivariable regressionOutcome switchingOver-adjustmentPost hoc analysisPre-registrationResidual confoundingStatistical adjustment using regressionSubgroup analysis Unmeasured confoundingReview SheetReferencesNuzzo RL. The Box Plots Alternative for Visualizing Quantitative Data. PM R. 2016 Mar;8(3):268-72. doi: 10.1016/j.pmrj.2016.02.001. Epub 2016 Feb 15. PMID: 26892802.Sainani KL. The problem of multiple testing. PM R. 2009 Dec;1(12):1098-103. doi: 10.1016/j.pmrj.2009.10.004. PMID: 20006317.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/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Intro (02:26) - Mailbag (06:42) - P-values (12:43) - Multiple Testing Guy (16:05) - Bonferroni solution (17:11) - Post hoc analysis ex (22:22) - Subgroup analysis person (30:28) - Statistical adjustment idealist (43:54) - Unmeasured confounding (45:19) - Residual confounding (49:25) - Over-adjustment (54:42) - Wrap-up

Could a preteen vaccine wipe out a global cancer? In this episode, we examine the bold claim that cervical cancer could be eradicated in much of the world by the end of the century—thanks to the highly effective HPV vaccine. We unpack statistical modeling, microsimulations, and how Markov chains make good date-night conversation. We also explore why vaccine uptake has been uneven, how a splash of vinegar is helping screen for cancer in low-resource countries, and why HPV isn’t just a women’s issue—it now causes more cancer in men than in women. Plus: dangerously tight corsets, allegedly breast-squeezing nuns, and the Cosmo quote we wish we’d written ourselves.Statistical topics:Cancer surveillanceMarkov modelsMicrosimulation modelsSensitivity analysesPassive surveillanceBackground ratesCase reports and case seriesMethodologic morals:“When reality is too complex to test, let microsimulations do the rest.”“Case reports are medicine's equivalent to see something, say something. They call for hard data, not hysteria.”Citations:No cervical cancer cases detected in vaccinated women following HPV immunisation. University of Strathclyde, January 22, 2024.Palmer TJ, Kavanagh K, Cuschieri K, et al. Invasive cervical cancer incidence following bivalent human papillomavirus vaccination: a population-based observational study of age at immunization, dose, and deprivation. J Natl Cancer Inst. 2024;116:857-65.Rigoni-Stern. Statistical facts about cancers on which Doctor Rigoni-Stern based his contribution to the Surgeons' Subgroup of the IV Congress of the Italian Scientists on 23 September 1842. (translation). Stat Med. 1987;6:881-4.Gordan JA, Lenkei SC. Cleanliness, Continence, Constancy, and Cervical Carcinoma. Can Med Assoc J. 1964;90:1132.zur Hausen H. Condylomata acuminata and human genital cancer. Cancer Res. 1976;36:794.Walboomers JM, Jacobs MV, Manos MM, et al. Human papillomavirus is a necessary cause of invasive cervical cancer worldwide. J Pathol. 1999;189:12-9.Chesson HW, Dunne EF, Hariri S, et al. The estimated lifetime probability of acquiring human papillomavirus in the United States. Sex Transm Dis. 2014;41:660-4.Sullivan, Morgan. Let’s Have a Little Chat About the HPV Vaccine. Cosmopolitan. March 19, 2025.Burger EA, Kim JJ, Sy S, et al. Age of Acquiring Causal Human Papillomavirus (HPV) Infections: Leveraging Simulation Models to Explore the Natural History of HPV-induced Cervical Cancer. Clin Infect Dis. 2017;65:893-99.Canfell K. Towards the global elimination of cervical cancer. Papillomavirus Res. 2019;8:100170.World Health Organization. Global strategy to accelerate the elimination of cervical cancer as a public health problem. November 17, 2020.Hall MT, Simms KT, Lew JB, et al. The projected timeframe until cervical cancer elimination in Australia: a modelling study. Lancet Public Health. 2019;4:e19-e27.Burger EA, Smith MA, Killen J, et al. Projected time to elimination of cervical cancer in the USA: a comparative modelling study. Lancet Public Health. 2020 Apr;5(4):e213-e222.Brisson M, Kim JJ, Canfell K, et al. Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries. Lancet. 2020;395:575-90.Escabí-Wojna E, Alvelo-Fernández PM, Suárez E, et al. Sex differences in parental reasons for lack of intent to initiate HPV vaccination among adolescents ages 13-17 years: National Immunization Survey - Teen 2019-2021. Vaccine. 2025;44:126584. (see supplement) Szilagyi PG, Albertin CS, Gurfinkel D, et al. Prevalence and characteristics of HPV vaccine hesitancy among parents of adolescents across the US. Vaccine. 2020;38:6027-6037.LaPook, Jonathan. Is the HPV Vaccine Safe? CBS Evening News. August 18, 2009.Slade BA, Leidel L, Vellozzi C, et al. Postlicensure safety surveillance for quadrivalent human papillomavirus recombinant vaccine. JAMA. 2009;302:750-7.Kharabsheh S, Al-Otoum H, Clements J, et al. Mass psychogenic illness following tetanus-diphtheria toxoid vaccination in Jordan. Bull World Health Organ. 2001;79:764-70.Jones TF, Craig AS, Hoy D, et al. Mass psychogenic illness attributed to toxic exposure at a high school. N Engl J Med. 2000;342:96-100.Buttery JP, Madin S, Crawford NW, et al. Mass psychogenic response to human papillomavirus vaccination. Med J Aust. 2008;189:261-2.Clements CJ. Gardasil and mass psychogenic illness. Aust N Z J Public Health. 2007;31:387.Simas C, Munoz N, Arregoces L, et al. HPV vaccine confidence and cases of mass psychogenic illness following immunization in Carmen de Bolivar, Colombia. Hum Vaccin Immunother. 2019;15:163-66.Larson HJ. Japan's HPV vaccine crisis: act now to avert cervical cancer cases and deaths. Lancet Public Health. 2020;5:e184-e185.Brinth LS, Pors K, Theibel AC, Mehlsen J. Orthostatic intolerance and postural tachycardia syndrome as suspected adverse effects of vaccination against human papilloma virus. Vaccine. 2015;33:2602-5.Large well-done studies following up on case reports and passive surveillance:Phillips A, Hickie M, Totterdell J, Brotherton J, Dey A, Hill R, Snelling T, Macartney K. Adverse events following HPV vaccination: 11 years of surveillance in Australia. Vaccine. 2020;38:6038-46.Arnheim-Dahlström L, Pasternak B, Svanström H, et al.

Today’s deep dive: the surprisingly serious science of penis size. Using self-report surveys, objective measurements, and a healthy dose of old-school statistics, we ask: How do you get clean data on gentlemen’s goods?Along the way, we explore social desirability bias, survey design tricks, and what happens when science meets insecurity. You’ll never look at a Starbucks cup the same way again.Statistical topicsSocial desirability biasSelection biasVolunteer BiasDescriptive StatisticsRight-Skewed DistributionsStrategies to improve accuracy in self-report dataMethodological morals“When answers aim to please, truth takes its leave.”“Without descriptive statistics, you'll never know if you measure up.”ReferencesCROWNE DP, MARLOWE D. A new scale of social desirability independent of psychopathology. J Consult Psychol. 1960;24:349-354. doi:10.1037/h0047358Gebhard, P.H. and Johnson, A.B., 1998. The Kinsey data: Marginal tabulations of the 1938-1963 interviews conducted by the Institute for Sex Research. Indiana University Press.Herbenick D, Reece M, Schick V, Sanders SA. Erect penile length and circumference dimensions of 1,661 sexually active men in the United States. J Sex Med. 2014;11(1):93-101. doi:10.1111/jsm.12244Johnston, L., McLellan, T., & McKinlay, A. (2014). (Perceived) size really does matter: Male dissatisfaction with penis size. Psychology of Men & Masculinity, 15(2), 225–228. https://doi.org/10.1037/a0033264King BM. The Influence of Social Desirability on Sexual Behavior Surveys: A Review. Arch Sex Behav. 2022;51(3):1495-1501. doi:10.1007/s10508-021-02197-0King BM. Average-Size Erect Penis: Fiction, Fact, and the Need for Counseling. J Sex Marital Ther. 2021;47(1):80-89. doi:10.1080/0092623X.2020.1787279King BM, Duncan LM, Clinkenbeard KM, Rutland MB, Ryan KM. Social Desirability and Young Men's Self-Reports of Penis Size. J Sex Marital Ther. 2019;45(5):452-455. doi:10.1080/0092623X.2018.1533905Larson, R.B., 2019. Controlling social desirability bias. International Journal of Market Research, 61(5), pp.534-547.Stodel, M. (2015). But What Will People Think?: Getting beyond Social Desirability Bias by Increasing Cognitive Load. International Journal of Market Research, 57(2), 313-322. https://doi.org/10.2501/IJMR-2015-024   (Original work published 2015)Spreadsheet with Penis Length DataOur online courses and programs: 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 Find us on social:Kristin -  LinkedIn & Twitter/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Introduction (02:33) - Starbucks metric and episode themes (07:17) - Men and women’s sampling frames (09:24) - Kinsey and his studies (14:59) - Statistics quiz on Kinsey penis data (22:10) - Social desirability bias (29:17) - Cognitive tricks to elicit honest survey answers (35:10) - Condoms, honest penis lengths, and another stats quiz (41:30) - Objective penis appraisers, measurement error, and reliability (46:42) - Whose penises? Volunteer and selection bias (50:27) - Mini-meta-analysis and the “answer” (52:06) - Wrap-up and methodological morals

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 Training and test setsStatistical adjustmentOverfitting PlagiarismProper citing practicesReferences to nowhereMethodologic 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.”CitationsCollagen 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 ReaderStudies 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. The 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.Reference 95 and 37 is a review article: Danby FW. Nutrition and aging skin: Sugar and glycation. Clin. Dermatol. 2010;28: 409–11. Sentence: “...tight glycemic control can drop glycated collagen formation by 25% in 4 months.” No citation given.The origi...

What if you could treat your prediabetes with . . . worms? Regina and Kristin dive into a surprising early-phase clinical trial on hookworm therapy—that’s right, intentionally infecting yourself with parasitic worms—to treat metabolic conditions. They dig into the biological rationale (inflammation, abdominal fat, and gut immunology), the clever study design (hello, Tabasco sauce!), and the statistical chops behind this phase 1B trial (block randomization, missing data, and nonparametric hypothesis tests).  Along the way, expect self-experimenting scientists, worm sex, poop analysis, and the world’s nerdiest aphrodisiac: a well-documented protocol. Statistical topicsRandomized controlled trial (RCT)Primary and secondary outcomesPlacebos, placebo effect, and nocebo effectBlock randomizationSample sizeDouble-blindingMissing data protocolsReproducible researchNonparametric hypothesis testingKruskal-Wallis testMethodological morals“Walk before you can run. Invest in simple but high-quality Phase I clinical trials.”“When faced with small samples, you better rank and sum, baby.”ReferencesPierce DR, McDonald M, Merone L, et al. Effect of experimental hookworm infection on insulin resistance in people at risk of type 2 diabetes. Nat Commun. 2023;14(1):4503. doi:10.1038/s41467-023-40263-4Nuzzo, R. What Happens When Scientists Experiment on Themselves? Reader’s Digest. Updated April 16, 2016.Ethics of self-experimentation Helminthic Therapy Wiki Pritchard D. Worming your way to good health [video online]. TEDx Talks. Published November 19, 2013. https://www.youtube.com/watch?v=sm5DcdZbnGAChapman PR, Giacomin P, Loukas A, McCarthy JS. Experimental human hookworm infection: a narrative historical review. PLoS Negl Trop Dis. 2021;15(12):e0009908. doi:10.1371/journal.pntd.0009908Sobotková K, Parker W, Levá J, Růžková J, Lukeš J, Jirků Pomajbíková K. Helminth Therapy - From the Parasite Perspective. Trends Parasitol. 2019;35(7):501-515. doi:10.1016/j.pt.2019.04.009Zatterale F, Longo M, Naderi J, et al. Chronic Adipose Tissue Inflammation Linking Obesity to Insulin Resistance and Type 2 Diabetes. Front Physiol. 2020;10:1607. Published 2020 Jan 29. doi:10.3389/fphys.2019.01607Kristin and Regina’s online coursesDemystifying 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 Program we teach in:Epidemiology and Clinical Research Graduate Certificate Program Find us on:Kristin -  LinkedIn & Twitter/XRegina - LinkedIn & ReginaNuzzo.com(02:44) - What happens when scientists experiment on themselves (06:56) - Mail-order DIY helminthic therapy (09:26) - Hookworm biology (15:53) - Inflammation, abdominal fat, immune system, and hookworms (22:23) - Hookworm therapy clinical trial design (26:54) - Clinical trial phases deep dive (32:18) - Interesting placebos (sham surgeries and psychedelics) (38:27) - Excitement over hookworm trial open data and data protocols (45:39) - Hookworm trial results (49:42) - Mood and well-being with hookworms (54:20) - Effects of hookworms on weight (57:03) - Nonparametric tests and how they work (01:03:50) - What the participants did after the study (01:05:47) - Wrap-up

Does a daily glass of wine really keep the cardiologist away? It’s a claim we’ve all heard: light to moderate drinking is good for your heart. But is it science or just a convenient excuse for happy hour? In this episode, we dive into the history behind this claim, discuss the challenges of observational studies and statistical adjustment, and explore attempts at randomized trials and natural experiments to get to the bottom of this boozy debate. Grab your drink—or maybe don’t—and join us! Statistical topicsStatistical AdjustmentRegressionResidual and Unmeasured ConfoundingRandomized TrialsMultiple TestingOutcome SwitchingMendelian Randomization Methodological morals“Statistical adjustment cannot erase all confounding.”“When you can’t experiment on people, let Nature experiment on people.”CitationsAlcohol and Drinking. Gallup Poll. 2024. Canada’s Guidance on Alcohol and Health. Canadian Centre on Substance Use and Addiction. 2023.  U.S. Department of Agriculture and U.S. Department of Health and Human Services. 2020 – 2025 Dietary Guidelines for Americans. 2020.U.S. Department of Agriculture and U.S. Department of Health and Human Services. Alcohol and Cancer Risk: The US Surgeon General's Advisory. 2025.Mezue K, Osborne MT, Abohashem S, et al. Reduced stress-related neural network activity mediates the effect of alcohol on cardiovascular risk. JACC. 2023;81:2315-25.McPhillips D, Goodman B. Small amounts of alcohol may turn down stress in the brain, benefiting the heart, new study finds. CNN. June 12, 2023.Friedman GD, Klatsky AL. Is alcohol good for your health? NEJM. 1993;329:1882-3.Sainani K. Alcohol and Weight. Allure. July 14, 2010.Wang LU, Lee IM, Manson JE, et al. Alcohol consumption, weight gain, and risk of becoming overweight in middle-aged and older women. Arch Intern Med. 2010;170:453-61.Sainani K. Drinking and Weight. Allure. Oct 31, 2008.Tolstrup JS, Halkjær J, Heitmann BL, et al. Alcohol drinking frequency in relation to subsequent changes in waist circumference. Am J Clin Nutr. 2008;87:957-63.Rabin RC. Major Study on Drinking Will be Shut Down. New York Times. June 15, 2018.Mitchell G, Lesch M, McCambridge J. Alcohol industry involvement in the moderate alcohol and cardiovascular health trial. AJPH. 2020;110:485-8.Gepner Y, Golan R, Harman-Boehm I, et al. Effects of Initiating Moderate Alcohol Intake on Cardiometabolic Risk in Adults With Type 2 Diabetes: A 2-Year Randomized, Controlled Trial. Ann Intern Med. 2015;163:569-79.Slade E, Drysdale H, Goldacre B, et al. Discrepancies between prespecified and reported outcomes. Ann Intern Med. 2016;164:374.Biddinger KJ, Emdin CA, Haas ME, et al. Association of habitual alcohol intake with risk of cardiovascular disease. JAMA Netw Open. 2022;5:e223849.Page with more details on the CASCADE trial 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 Program that we teach in:Epidemiology and Clinical Research Graduate Certificate Program Find us on:Kristin -  LinkedIn & Twitter/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Introduction (03:00) - Drinking habits in America (04:13) - New Canadian drinking guidelines (07:51) - Definition of light-to-moderate drinking (08:43) - Risks and benefits of light-to-moderate drinking (11:37) - History of the heart health claim (18:34) - Problems with observational studies (23:34) - Statistical adjustment (26:33) - Residual and unmeasured confounding (32:13) - Overconfidence in observational studies (36:10) - Randomized trials of alcohol (37:26) - Canceled NIH randomized trial of alcohol (42:36) - The CASCADE randomized trial of wine (44:12) - The problem of multiple testing (48:50) - Outcome switching (50:26) - Mendelian randomization (59:58) - Mendelian randomization studies of alcohol and heart disease (01:04:03) - Wrap-up