Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Daily, weekly, seasonal and menstrual cycles in women’s mood, behaviour and vital signs

Nature Human Behaviour volume 5, pages 716–725 (2021)Cite this article

Subjects

Abstract

Dimensions of human mood, behaviour and vital signs cycle over multiple timescales. However, it remains unclear which dimensions are most cyclical, and how daily, weekly, seasonal and menstrual cycles compare in magnitude. The menstrual cycle remains particularly understudied because, not being synchronized across the population, it will be averaged out unless menstrual cycles can be aligned before analysis. Here, we analyse 241 million observations from 3.3 million women across 109 countries, tracking 15 dimensions of mood, behaviour and vital signs using a women’s health mobile app. Out of the daily, weekly, seasonal and menstrual cycles, the menstrual cycle had the greatest magnitude for most of the measured dimensions of mood, behaviour and vital signs. Mood, vital signs and sexual behaviour vary most substantially over the course of the menstrual cycle, while sleep and exercise behaviour remain more constant. Menstrual cycle effects are directionally consistent across countries.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Overview of the dataset.
Fig. 2: Decomposition of women’s mood, behaviour and vital signs into daily, weekly, seasonal and menstrual cycles.
Fig. 3: Premenstrual mood effects are directionally consistent across countries.
Fig. 4: Premenstrual effects change with age for happy–sad mood, RHR, BBT and weight.

Data availability

Data that support the findings of this study are available from the corresponding author (J.L.) with appropriate permission from Clue. The data are not publicly available to preserve the privacy of Clue users.

Code availability

Code to reproduce the findings of this study is available at https://github.com/epierson9/four-cycles.

References

  1. Van Dongen, H. P. & Dinges, D. F. Circadian rhythms in fatigue, alertness, and performance. Princ. Pract. Sleep. Med. 20, 391–399 (2000).

    Google Scholar 

  2. Roenneberg, T., Allebrandt, K. V., Merrow, M. & Vetter, C. Social jetlag and obesity. Curr. Biol. 22, 939–943 (2012).

    Article  CAS  PubMed  Google Scholar 

  3. Partonen, T. & Lönnqvist, J. Seasonal affective disorder. CNS Drugs 9, 203–212 (1998).

    Article  CAS  Google Scholar 

  4. Wilcox, A. J., Dunson, D. & Baird, D. D. The timing of the ‘fertile window’ in the menstrual cycle: day specific estimates from a prospective study. BMJ 321, 1259–1262 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Bergemann, N., Parzer, P., Runnebaum, B., Resch, F. & Mundt, C. Estrogen, menstrual cycle phases, and psychopathology in women suffering from schizophrenia. Psychol. Med. 37, 1427–1436 (2007).

    Article  PubMed  Google Scholar 

  6. Badwe, R. et al. Timing of surgery during menstrual cycle and survival of premenopausal women with operable breast cancer. Lancet 337, 1261–1264 (1991).

    Article  CAS  PubMed  Google Scholar 

  7. Golder, S. A. & Macy, M. W. Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science 333, 1878–1881 (2011).

    Article  CAS  PubMed  Google Scholar 

  8. Murray, G., Allen, N. B. & Trinder, J. A longitudinal investigation of seasonal variation in mood. Chronobiol. Int. 18, 875–891 (2001).

    Article  CAS  PubMed  Google Scholar 

  9. Romans, S., Clarkson, R., Einstein, G., Petrovic, M. & Stewart, D. Mood and the menstrual cycle: a review of prospective data studies. Gend. Med. 9, 361–384 (2012).

    Article  PubMed  Google Scholar 

  10. Lorenz, T. K., Gesselman, A. N. & Vitzthum, V. J. Variance in mood symptoms across menstrual cycles: implications for premenstrual dysphoric disorder. Women’s Reprod. Health 4, 77–88 (2017).

    Article  Google Scholar 

  11. Bosman, R. C., Albers, C. J., de Jong, J., Batalas, N. & aan het Rot, M. No menstrual cyclicity in mood and interpersonal behaviour in nine women with self-reported premenstrual syndrome. Psychopathology 51, 290–294 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hengartner, M. P. et al. Negative affect is unrelated to fluctuations in hormone levels across the menstrual cycle: evidence from a multisite observational study across two successive cycles. J. Psychosom. Res. 99, 21–27 (2017).

    Article  PubMed  Google Scholar 

  13. Hartlage, S. A., Breaux, C. A. & Yonkers, K. A. Addressing concerns about the inclusion of premenstrual dysphoric disorder in DSM-5. J. Clin. Psychiatry 75, 70–76 (2014).

    Article  PubMed  Google Scholar 

  14. Chakradhar, S. Discovery cycle. Nat. Med. 24, 1082–1085 (2018).

    Article  CAS  PubMed  Google Scholar 

  15. Elford, K. & Spence, J. The forgotten female: pediatric and adolescent gynecological concerns and their reproductive consequences. J. Pediatr. Adolesc. Gynecol. 15, 65–77 (2002).

    Article  CAS  PubMed  Google Scholar 

  16. Johnston-Robledo, I. & Chrisler, J. C. The menstrual mark: menstruation as social stigma. Sex. Roles 68, 9–18 (2013).

    Article  Google Scholar 

  17. Hillard, P. J. A. Menstruation in adolescents: what do we know? and what do we do with the information? J. Pediatr. Adolesc. Gynecol. 27, 309–319 (2014).

    Article  Google Scholar 

  18. Park, M., Thom, J., Mennicken, S., Cramer, H. & Macy, M. Global music streaming data reveal diurnal and seasonal patterns of affective preference. Nat. Hum. Behav. 3, 230–236 (2019).

  19. Hillard, P. J. A. & Vlajic Wheeler, M. Data from a menstrual cycle tracking app informs our knowledge of the menstrual cycle in adolescents and young adults. J. Pediatr. Adolesc. Gynecol. 30, 269–270 (2017).

    Article  Google Scholar 

  20. Pierson, E., Althoff, T. & Leskovec, J. in WWW: Proceedings of the 2018 World Wide Web Conference, 107–116 (2018).

  21. Alvergne, A., Vlajic Wheeler, M. & Högqvist Tabor, V. Do sexually transmitted infections exacerbate negative premenstrual symptoms? Insights from digital health. Evol. Med. Public Health 2018, 138–150 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Liu, B. et al. in WWW: Proceedings of the 2019 World Wide Web Conference (2019).

  23. Johansson, E., Larsson-Cohn, U. & Gemzell, C. Monophasic basal body temperature in ovulatory menstrual cycles. Am. J. Obstet. Gynecol. 113, 933–937 (1972).

    Article  CAS  PubMed  Google Scholar 

  24. Tudor-Locke, C. et al. Descriptive epidemiology of pedometer-determined physical activity. Med. Sci. Sports Exerc. 36, 1567–1573 (2004).

    Article  PubMed  Google Scholar 

  25. Shephard, R. J. & Aoyagi, Y. Seasonal variations in physical activity and implications for human health. Eur. J. Appl. Physiol. 107, 251–271 (2009).

    Article  PubMed  Google Scholar 

  26. Caruso, S. et al. Do hormones influence women’s sex? Sexual activity over the menstrual cycle. J. Sex. Med. 11, 211–221 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Quer, G., Gouda, P., Galarnyk, M., Topol, E. J. & Steinhubl, S. R. Inter- and intraindividual variability in daily resting heart rate and its associations with age, sex, sleep, BMI, and time of year: retrospective, longitudinal cohort study of 92,457 adults. PLoS ONE 15, e0227709 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ma, Y. et al. Seasonal variation in food intake, physical activity, and body weight in a predominantly overweight population. Eur. J. Clin. Nutr. 60, 519–528 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Dunson, D. B., Colombo, B. & Baird, D. D. Changes with age in the level and duration of fertility in the menstrual cycle. Hum. Reprod. 17, 1399–1403 (2002).

    Article  PubMed  Google Scholar 

  30. Batista, M. C. et al. Effects of aging on menstrual cycle hormones and endometrial maturation. Fertil. Steril. 64, 492–499 (1995).

    Article  CAS  PubMed  Google Scholar 

  31. Soules, M. R. et al. Executive summary: stages of reproductive aging workshop (STRAW). Climacteric 4, 267–272 (2001).

    Article  CAS  PubMed  Google Scholar 

  32. Metcalf, M. G. & Mackenzie, J. A. Incidence of ovulation in young women. J. Biosoc. Sci. 12, 345–352 (1980).

    Article  CAS  PubMed  Google Scholar 

  33. Committee on Adolescence, American College of Obstetricians and Gynecologists, Committee on Adolescent Health Care, AmericanAcademyofPediatrics Menstruation in girls and adolescents: using the menstrual cycle as a vital sign. Pediatrics 118, 2245 (2006).

    Article  Google Scholar 

  34. Epstein, D. A. et al. in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 6876–6888 (ACM, 2017).

  35. Bramwell, R. & Zeb, R. Attitudes towards and experience of the menstrual cycle across different cultural and religious groups. J. Reprod. Infant Psychol. 24, 314–322 (2006).

    Article  Google Scholar 

  36. Hoerster, K. D., Chrisler, J. C. & Rose, J. G. Attitudes toward and experience with menstruation in the US and India. Women Health 38, 77–95 (2003).

    Article  PubMed  Google Scholar 

  37. Uskul, A. K. Women’s menarche stories from a multicultural sample. Soc. Sci. Med. 59, 667–679 (2004).

    Article  PubMed  Google Scholar 

  38. Chandra, P. S. & Chaturvedi, S. K. Cultural variations in attitudes toward menstruation. Can. J. Psychiatry 37, 196–198 (1992).

    Article  CAS  PubMed  Google Scholar 

  39. Li, K. et al. Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile-health data. NPJ Digit. Med. 3, 1–13 (2020).

    Article  Google Scholar 

  40. Shansky, R. M. Are hormones a ‘female problem’ for animal research? Science 364, 825–826 (2019).

    Article  CAS  PubMed  Google Scholar 

  41. Johansson, C. et al. Circadian clock-related polymorphisms in seasonal affective disorder and their relevance to diurnal preference. Neuropsychopharmacology 28, 734 (2003).

    Article  CAS  PubMed  Google Scholar 

  42. Saad, G. & Stenstrom, E. Calories, beauty, and ovulation: the effects of the menstrual cycle on food and appearance-related consumption. J. Consum. Psychol. 22, 102–113 (2012).

    Article  Google Scholar 

  43. Rosato, D. What your period tracker app knows about you. Consumer Reports (28 January 2020).

  44. Sommer, M. Menarche: a missing indicator in population health from low-income countries. Public Health Rep. 128, 399–401 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Lerner, S. Over 5 years later, Fitbit finally adds menstrual cycle and text response features. Tech Times https://www.techtimes.com/articles/227079/20180507/over-5-years-later-fitbit-finally-adds-menstrual-cycle-and-text-response-features.htm (7 May 2018).

  46. 23 new iOS tracking categories and a more accurate algorithm. Clue by BioWink GmbH http://helloclue.com/articles/about-clue/23-new-ios-tracking-categories-more-accurate-algorithm (2015).

  47. Plutchik, R. The nature of emotions. Am. Sci. 89, 344–350 (2001).

    Article  Google Scholar 

  48. Plutchik, R. Outlines of a new theory of emotion. Trans. N. Y. Acad. Sci. 20, 394–403 (1958).

    Article  CAS  PubMed  Google Scholar 

  49. How many hours of sleep are enough for good health? The Mayo Clinic https://www.mayoclinic.org/healthy-lifestyle/adult-health/expert-answers/how-many-hours-of-sleep-are-enough/faq-20057898 (2018).

  50. Moran, V. H., Leathard, H. L. & Coley, J. Cardiovascular functioning during the menstrual cycle. Clin. Physiol. 20, 496–504 (2000).

    Article  CAS  PubMed  Google Scholar 

  51. Yonkers, K. A., O’Brien, P. S. & Eriksson, E. Premenstrual syndrome. Lancet 371, 1200–1210 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Chiazze, L., Brayer, F. T., Macisco, J. J., Parker, M. P. & Duffy, B. J. The length and variability of the human menstrual cycle. JAMA 203, 377–380 (1968).

    Article  PubMed  Google Scholar 

  53. Jebb, A. T., Tay, L., Diener, E. & Oishi, S. Happiness, income satiation and turning points around the world. Nat. Hum. Behav. 2, 33 (2018).

    Article  PubMed  Google Scholar 

  54. World Health Organization Global Health Observatory (GHO). Prevalence of overweight among adults, BMI ≥ 25 (age-standardized estimate), age group: 18+ years, Sex: Female (2016).

  55. World Health Organization Global Health Observatory (GHO). Prevalence of obesity among adults, BMI ≥ 30 (age-standardized estimate), age group: 18+ years, Sex: Female (2016).

  56. Walpole, S. C. et al. The weight of nations: an estimation of adult human biomass. BMC Public Health 12, 439 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Durain, D. Primary dysmenorrhea: assessment and management update. J. Midwifery Women’s Health 49, 520–528 (2004).

    Article  Google Scholar 

  58. Mannix, L. K. Menstrual-related pain conditions: dysmenorrhea and migraine. J. Women’s Health 17, 879–891 (2008).

    Article  Google Scholar 

  59. Salzman, B., Fleegle, S. & Tully, A. S. Common breast problems. Am. Fam. Phys. 86, 343–349 (2012).

    Google Scholar 

  60. Won, H. R. & Abbott, J. Optimal management of chronic cyclical pelvic pain: an evidence-based and pragmatic approach. Int. J. Women’s Health 2, 263 (2010).

    Google Scholar 

  61. Haines, P. S., Hama, M. Y., Guilkey, D. K. & Popkin, B. M. Weekend eating in the United States is linked with greater energy, fat, and alcohol intake. Obes. Res. 11, 945–949 (2003).

    Article  PubMed  Google Scholar 

  62. Finlay, A. K., Ram, N., Maggs, J. L. & Caldwell, L. L. Leisure activities, the social weekend, and alcohol use: evidence from a daily study of first-year college students. J. Stud. Alcohol Drugs 73, 250–259 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Seasonal allergies: nip them in the bud. The Mayo Clinic https://www.mayoclinic.org/diseases-conditions/hay-fever/in-depth/seasonal-allergies/art-20048343 (2019).

  64. Lebowitz, M. D., Collins, L. & Holberg, C. J. Time series analyses of respiratory responses to indoor and outdoor environmental phenomena. Environ. Res. 43, 332–341 (1987).

    Article  CAS  PubMed  Google Scholar 

  65. Andersen, T. B. A model to predict the beginning of the pollen season. Grana 30, 269–275 (1991).

    Article  Google Scholar 

  66. Finkelman, B. S. et al. Global patterns in seasonal activity of influenza A/H3N2, A/H1N1, and B from 1997 to 2005: viral coexistence and latitudinal gradients. PloS ONE 2, e1296 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  67. The flu season. Centers for Disease Control and Protection https://www.cdc.gov/flu/about/season/flu-season.htm (2018)

  68. Baum T. & Lundtorp S. (eds) Seasonality in Tourism (Elsevier, 2001).

  69. Cheng, J., Bernstein, M., Danescu-Niculescu-Mizil, C. & Leskovec, J. in CSCW: Proceedings of the Conference on Computer-Supported Cooperative Work, vol. 2017, 1217 (NIH Public Access, 2017).

  70. Symul, L., Wac, K., Hillard, P. & Salathe, M. Assessment of menstrual health status and evolution through mobile apps for fertility awareness. NPJ Digit. Med. 2, 64 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Pliner, P. & Fleming, A. S. Food intake, body weight, and sweetness preferences over the menstrual cycle in humans. Physiol. Behav. 30, 663–666 (1983).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank D. Jurafsky, P. Wei Koh, S. Li, A. Mastrioanni, M. Mateen, L. Pierson, R. Pierson, N. Roth, C. Ruiz, R. Sosic, P. Thaker, C. Yau, M. Zitnik and J. Zou for helpful comments. For financial support, they thank the Hertz and NDSEG Fellowships; the SAP Stanford Graduate Fellowship; NIH grant U54 EB020405; the Bill & Melinda Gates Foundation (INV-004841); the Stanford Data Science Initiative; NSF Grants IIS-1901386; OAC-1835598 (CINES), OAC-1934578 (HDR), CCF-1918940 (Expeditions) and IIS-2030477 (RAPID); Wu Tsai Neurosciences Institute; and the Chan Zuckerberg Biohub. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. J.L. is a Chan Zuckerberg Biohub investigator.

Author information

Authors and Affiliations

  1. Department of Computer Science, Stanford University, Stanford, CA, USA

    Emma Pierson & Jure Leskovec

  2. Microsoft Research New England, Cambridge, MA, USA

    Emma Pierson

  3. Paul G. Allen School of Computer Science & Engineering, University of Washington, Washington, WA, USA

    Tim Althoff

  4. Clue by BioWink GmbH, Berlin, Germany

    Daniel Thomas

  5. Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA

    Paula Hillard

  6. Chan Zuckerberg Biohub, San Francisco, CA, USA

    Jure Leskovec

Authors
  1. Emma Pierson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tim Althoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daniel Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Paula Hillard
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jure Leskovec
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.P. performed the statistical analysis. E.P., T.A., D.T., P.H. and J.L. jointly analysed the results and wrote the paper.

Corresponding author

Correspondence to Jure Leskovec.

Ethics declarations

Competing interests

E.P. is employed by Microsoft Research. D.T. is employed by Clue by BioWink GmbH. P.H. is on the medical advisory board of Clue by BioWink GmbH. All other authors declare no competing interests.

Additional information

Peer review information Primary Handling Editor: Jamie Horder

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pierson, E., Althoff, T., Thomas, D. et al. Daily, weekly, seasonal and menstrual cycles in women’s mood, behaviour and vital signs. Nat Hum Behav 5, 716–725 (2021). https://doi.org/10.1038/s41562-020-01046-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-020-01046-9

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing