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RecruitingNCT07037082C-HEALTHUpdated Jun 22, 2026

Understanding Cycles to Improve Women's Health

An observational study in Woman of Reproductive Age and Socioeconomic Factors, sponsored by University Hospital, Montpellier. Recruiting at 1 site in France. Open to female participants aged 18 Years to 39 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-06-22.

Sponsored by University Hospital, Montpellier · Observational

From the registry’s dates

  • Started Sep 2025; still recruiting 1 year 1 month later.
Study type
Observational
Model
Ecologic or community
Time perspective
Prospective
Enrollment
320
Ages
18 Years to 39 Years
Sex
Female
01

Study summary

Introduction:

The C-HEALTH study investigates how environmental and socio-economic conditions affect women's menstrual cycles and reproductive health.

Aim:

To compare progesterone levels during the luteal phase among women from different socio-economic backgrounds living in rural and urban areas in southern France.

Methods:

This is a prospective observational study involving 320 healthy women of reproductive age.

  • Hormones (progesterone, estradiol) will be measured daily in saliva.
  • Inflammation (Protéine C Réactive: CRP) will be measured five times per cycle via blood drops.
  • Participants will wear a smart ring to monitor body temperature and activity.
  • Daily symptoms and lifestyle data will be collected.
  • Environmental exposures (pollution, stress, living conditions) will be assessed and linked to menstrual health outcomes.
Read the detailed description

Introduction:

Menstrual health is an important indicator of women's overall health, but the biological and environmental factors influencing the menstrual cycle are still poorly understood. The C-HEALTH study explores how social and ecological conditions - such as pollution, stress, socio-economic status, and living environment - affect hormonal patterns and menstrual health in women living in the Occitanie region (France).

Aim:

The primary objective is to compare luteal phase progesterone levels among women from different socio-economic backgrounds living in either rural or urban areas in the Occitanie region.

The secondary objectives are:

  • To compare, according to the women's environment: levels of sex hormones (progesterone and estradiol) throughout a menstrual cycle, levels of an inflammation marker (C-reactive protein) throughout a menstrual cycle, and the description of the menstrual cycle (characteristics, possible abnormalities such as pain, abnormal bleeding, etc.).
  • To identify environmental factors associated with potential biological and menstrual cycle abnormalities.

Methods:

To meet the objectives of this research, 80 women aged 18-45 living in Occitanie (France) will be enrolled in each socioeconomic group at each location (4 groups: low-income urban, high-income urban, low-income rural, high-income rural; total n=320).

After the inclusion visit (visit 1) and the training visit for self-sampling (visit 2), participants will collect their biological samples and data during one observed menstrual cycle, with a follow-up visit on day 7 of the cycle (visit 3), and will complete their participation with the collection of biological samples at home (visit 4).

Biological samples (saliva and dried blood spots) will be collected no later than 30 days after the end of the collection period.

The exposome matrix will be inferred using postcode and will include data from an air pollution database (Environment Data Management System - EDMS) linked primarily to traffic, industry, stationary fuel burners, forest fires and solid fuel combustion, comfort parameters (temperature, humidity), UV, pollen count, green, grey and blue spaces, vegetation, Shannon biodiversity index, noise, water quality (pesticides, heavy metals)

At the end of this study:

  • Saliva samples will be analyzed using ELISA tests to measure steroid levels.
  • Dried blood spot samples will be analyzed using immunoenzymatic assays to measure CRP levels, using the ELISA technique.
  • The exposome will be analyzed using classical statistics, clustering/PCA (Principal Component Analysis) to assess exposure profiles, and EnWAS will be used to untangle independent associations between exposure variables and menstrual cycle parameters. A series of minimally adjusted univariate analyses will be performed and exposures significant at the false discovery rate will be retained in the cluster analysis. Within each cluster, a multivariable analysis will be performed to reduce the number of variables of interest. This will allow us to identify exposome factors independently associated with menstrual health.
02

Conditions studied

  • Woman of Reproductive Age
  • Socioeconomic Factors

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Keywords

  • Menstrual Cycle
  • Exposome
  • Hormones
  • Inflammation
  • Rural/Urban
  • Socioeconomic status
  • Pollution
  • Ovulation
03

In context

Inflammation

3,438 studies on the registry are indexed under Inflammation; 629 are open to participants now.

This study's planned enrollment of 320 is above the median of 95 across 895 observational studies indexed under Inflammation.

Browse Inflammation studies →

Lead sponsor

University Hospital, Montpellier is the lead sponsor of 1,244 studies on the registry; 225 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 39 Years
Sexes eligible
Female
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

Women were initially recruted from medical and paramedical practices, hospitals, clinics, pharmacies and medical advisors from the different environments studied in Occitanie, then in a second time via social networks (Facebook and Snapchat) and local newspapers (e.g. Midi Libre) in the event of recruitment difficulties.

Inclusion criteria

  • Woman of childbearing age (18-39 years)
  • Woman not using hormonal contraception for at least 6 months
  • Woman with semi-regular menstrual cycles between 21 and 45 days inclusive
  • Woman with no known history of infertility
  • Woman working in the same environment (urban/rural) as her place of residence
  • Knowledge of the dates of periods over the last 3 cycles
  • Woman who has a freezer at -20°C

Exclusion criteria

Exclusion Criteria:

  • Diagnosis by a physician of one or more of the following comorbidities: Polycystic ovarian syndrome (PCOS), Endometriosis, Adenomyosis, Diabetes or thyroid disease, Hormone-dependent gynecological cancers (breast, endometrium, ovaries), Coagulation diseases (von Willebrand), Chronic liver failure, chronic renal failure, heart disease, autoimmune disease, Autism, Diagnosis and/or treatment for a psychiatric illness
  • Chronic exposure to cocaine, amphetamine/methamphetamine, morphine or ecstasy within 30 days prior to inclusion
  • Chronic exposure to THC within 7 days prior to inclusion.
  • Person who is not comfortable with self-sampling (hematophobia or other)
  • No access to a smartphone
  • No possibility of wearing a connected ring for at least 60 days 22h/24h
  • Pregnant or breastfeeding woman
  • Woman who gave birth or breastfed in the 2 months before the study
  • Person who moved less than 2 years before the study (does not concern participants who moved in the same environment (rural or urban, less than 20 km)
  • Person unable to read French
  • Failure to obtain informed consent
  • Person not benefiting from a national health insurance scheme
  • Person under legal protection, guardianship or curatorship
  • Person participating in other research involving the human person
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Study design

Observational model
Ecologic or community
Time perspective
Prospective
Enrollment
320 participants (estimated)
Patient registry
No
Biospecimen retention
Samples without dna

Groups and cohorts

  • Environment 1a

    Women with low socio-economic status in rural areas

    Other: Self-saliva sampling · Other: Self-collection of dried blood spots · Other: Wearing the connected ring · Other: Ovulation test

  • Environment 1b

    Women with high socio-economic status in rural areas

    Other: Self-saliva sampling · Other: Self-collection of dried blood spots · Other: Wearing the connected ring · Other: Ovulation test

  • Environment 2a

    Women with low socio-economic status in urban areas

    Other: Self-saliva sampling · Other: Self-collection of dried blood spots · Other: Wearing the connected ring · Other: Ovulation test

  • Environment 2b

    Women with high socio-economic status in urban areas

    Other: Self-saliva sampling · Other: Self-collection of dried blood spots · Other: Wearing the connected ring · Other: Ovulation test

Interventions

  • OtherSelf-saliva sampling

    Self-saliva samples are taken every day from D1 inclusive over 1 consecutive cycle, to measure progesterone (P4) and estradiol (E2) concentrations.

  • OtherSelf-collection of dried blood spots

    Self-blood sampling is done 5 times during the cycle to measure protéine C-Réactive (CRP) concentrations.

  • OtherWearing the connected ring

    A connected ring is worn every day of the observed cycle, while maintaining lifestyle habits, to measure daily body temperature, assess heart rate variability and resting heart rate, evaluate physical activity and energy expenditure, assess stress level, and evaluate sleep quality.

  • OtherOvulation test

    An ovulation test (Ovulatest®) is carried out from day 7 until a test is positive, or until day 39 if ovulation is not detected

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What researchers measure

Primary outcomes

  1. Mean Luteal Phase Salivary Progesterone

    Mean salivary progesterone concentration (pg/mL) measured during the luteal phase - from the day after ovulation (Day of Ovulation, Jov) to the end of the menstrual cycle, or from day 32 to 45 if ovulation is not detected. The outcome is used to compare hormonal levels between women of low vs. high socioeconomic status living in rural (Environment 1) or urban (Environment 2) areas in the Occitanie region

    Time frame: One menstrual cycle (up to 45 days)

Secondary outcomes

  1. Progesterone levels

    Progesterone levels (pg/ml) will be measured in saliva every day of the observed cycle. Averages will be calculated over 7 periods of the cycle: * Follicular Average * Follicular Peak Average * Luteal Average * Luteal Peak Average * Preovulatory Average\* * Periovulatory Average\* * Postovulatory Week 1 Average\* * Postovulatory Week 2 Average\* * Postovulatory Week 3 Average\* (\* for ovulatory cycles only)

    Time frame: One menstrual cycle (up to 45 days)

  2. Estradiol levels

    Estradiol levels (pg/ml) will be measured in saliva every day of the observed cycle. Averages will be calculated during 7 periods of the cycle: * Follicular Average * Follicular Peak Average * Luteal Average * Luteal Peak Average * Preovulatory Average\* * Periovulatory Average\* * Postovulatory Week 1 Average\* * Postovulatory Week 2 Average\* * Postovulatory Week 3 Average\* (\* for ovulatory cycles only)

    Time frame: One menstrual cycle (up to 45 days)

  3. Protéine C Réactive (CRP) levels

    CRP levels (mg/L) will be measured in the blood at 5 points during the observed cycle: * Day 2 (D2) * Day 7 (D7) * Day of ovulation (Dov) or Day 32 (D32=D45-13) if ovulation is not detected * at the Luteal Peak on Dov+7 or Day 39 (D39=D45-6) if ovulation is not detected * in the premenstrual phase on Dov+12 or Day 44 (D44=D45-1) if ovulation is not detected * Difference in CRP will be measured between D2 and Dov+7, or between D2 and D39 if ovulation is not detected

    Time frame: Day 2, Day 7, Day of ovulation (or Day 32 if ovulation is not detected), 7 days after ovulation (or Day 39 if ovulation is not detected), 12 days after ovulation (or Day 44 if ovulation is not detected)

  4. The length of cycles

    The length (in days) of the 3 cycles preceding the observed cycle

    Time frame: Day 0

  5. Period frequency

    Period frequency in the observed cycle (calculated as the length of a cycle: Duration between the first day of the observed cycle (D0) and the day before the first day of the next cycle). * Amenorrhea: no bleeding * Infrequent: \> 38 days * Normal: 24 to 38 days * Frequent: \< 24 days

    Time frame: Day 0 and the day before the next cycle

  6. Cycle regularity

    Cycle regularity over the observed cycle and the three previous cycles: Difference (in days) between the longest and shortest cycle over four continuous cycles. * Normal or regular: difference ≤ 7-9 days) * Irregular: difference ≥ 10 days)

    Time frame: Day 0 and the day before the first day of the next cycle

  7. Duration of the period

    The duration of the period in the observed cycle (in days). * Amenorrhea: 0 days * Normal: ≤ 8 days * Prolonged: \> 8 days

    Time frame: Day 0 and the last day of menstruation (up to 45 days)

  8. Flow abundance

    Flow abundance (heavy/light) Heavy periods are defined as the need to change a sanitary napkin or tampon every 1 or 2 hours.

    Time frame: Day 0 and the last day of menstruation (up to 45 days)

  9. Score Higham

    Score Higham is an objective assessment of menstrual blood loss based on the number of sanitary pads used and clots passed, to classify periods are light, normal or heavy. Score interpretation: * 100 points: blood loss of at least 80 mL, indicating menorrhagia. * 150 points: potential indication for surgical intervention in menometrorrhagia.

    Time frame: Day 0 and the last day of menstruation (up to Day 45)

  10. Ovulation test

    Ovulatest® ovulation test performed from Day 7 until a positive test is obtained, or until Day 39 (D39=Day 45-6) if ovulation is not detected. Ovulation is considered the day following the positive test.

    Time frame: Day 7 to positive test (up to Day 45) or until Day 39 if ovulation is not detected

  11. Body temperature

    Body temperature will be recorded on a smart ring throughout the observed cycle. Ovulation will be detected by an increase of at least 0.3°C by the smart ring.

    Time frame: One menstrual cycle (up to 45 days)

  12. Length of the luteal phase

    Length of the luteal phase (in days), defined as the number of days between Dov (inclusive, measured by the first positive Ovulatest®) and the last day of the cycle. * ≤ 10 days: short luteal phase * \> 10 days: normal luteal phase (Practice Committees of the American Society for Reproductive Medicine and the Society for Reproductive Endocrinology and Infertility, 2021)

    Time frame: First Day of ovulation and the day before the first day of the following cycle (up to Day 45), only if ovulation is detected

  13. Intermenstrual bleeding

    Presence of intermenstrual bleeding in the observed cycle (yes/no, and if yes, specify cycle day/date)

    Time frame: One menstrual cycle (up to 45 days)

  14. Premenstrual symptoms Intensity

    Premenstrual symptoms intensity will be assessed over the observed cycle: * On Day 12 for the period between Days 6 and 12 (mid-follicular phase), * On Day 12 (Days 6 to 12) or Day 44 (Days 38 to 44) if ovulation is not detected. 16 symptoms (sweet cravings, increased appetite, mood swings/anxiety, fatigue, breast tenderness, weight gain, bloating, constipation or diarrhea, abdominal pain, headaches, sleep problems, inattention/distraction, hot flashes, decreased libido, oily hair, skin irritation) will be rated on a Likert scale from 1 to 5 (1=No symptoms; 2=Mild symptoms; 3=Moderate symptoms; 4=Severe symptoms; 5=Very severe symptoms).

    Time frame: Day 12 and 12 days after ovulation (or Day 44 if ovulation is not detected)

  15. Pain during menstruation

    Pain during menstruation will be assessed on Day 2 of the observed cycle using a visual numeric scale (VNS) from 0 to 10.

    Time frame: Day 2

07

Study locations

1 of 1 sites recruiting
  • Institute of Evolutionary Science of Montpellier
    Montpellier, 34090, France
    • Alexandra ALVERGNE, PhD · Contact · alexandra.alvergne@umontpellier.fr · +33467144966
    • Charlotte FAURIE, MD · Principal investigator
    • Alexandra ALVERGNE, pHD · Sub investigator
    • Valérie DURAND, AE · Sub investigator
    Recruiting
08

References and documents

Publications

  • American Academy of Pediatrics Committee on Adolescence; American College of Obstetricians and Gynecologists Committee on Adolescent Health Care; Diaz A, Laufer MR, Breech LL. Menstruation in girls and adolescents: using the menstrual cycle as a vital sign. Pediatrics. 2006 Nov;118(5):2245-50. doi: 10.1542/peds.2006-2481. PubMed 17079600 ↗
  • Male V. COVID-19 vaccination and menstruation. Science. 2022 Nov 18;378(6621):704-706. doi: 10.1126/science.ade1051. Epub 2022 Nov 17. PubMed 36395209 ↗
  • Wang YX, Arvizu M, Rich-Edwards JW, Stuart JJ, Manson JE, Missmer SA, Pan A, Chavarro JE. Menstrual cycle regularity and length across the reproductive lifespan and risk of premature mortality: prospective cohort study. BMJ. 2020 Sep 30;371:m3464. doi: 10.1136/bmj.m3464. PubMed 32998909 ↗
  • Jasienska G, Bribiescas RG, Furberg AS, Helle S, Nunez-de la Mora A. Human reproduction and health: an evolutionary perspective. Lancet. 2017 Jul 29;390(10093):510-520. doi: 10.1016/S0140-6736(17)30573-1. Epub 2017 Jul 27. PubMed 28792413 ↗
  • Merklinger-Gruchala A, Jasienska G, Kapiszewska M. Effect of Air Pollution on Menstrual Cycle Length-A Prognostic Factor of Women's Reproductive Health. Int J Environ Res Public Health. 2017 Jul 20;14(7):816. doi: 10.3390/ijerph14070816. PubMed 28726748 ↗
  • Vitzthum VJ. The ecology and evolutionary endocrinology of reproduction in the human female. Am J Phys Anthropol. 2009;140 Suppl 49:95-136. doi: 10.1002/ajpa.21195. PubMed 19890865 ↗
  • Jasienska G, Ellison PT. Energetic factors and seasonal changes in ovarian function in women from rural Poland. Am J Hum Biol. 2004 Sep-Oct;16(5):563-80. doi: 10.1002/ajhb.20063. PubMed 15368604 ↗
  • Lorenz TK, Heiman JR, Demas GE. Testosterone and immune-reproductive tradeoffs in healthy women. Horm Behav. 2017 Feb;88:122-130. doi: 10.1016/j.yhbeh.2016.11.009. Epub 2016 Nov 17. PubMed 27865788 ↗
  • Lorenz TK, Demas GE, Heiman JR. Interaction of menstrual cycle phase and sexual activity predicts mucosal and systemic humoral immunity in healthy women. Physiol Behav. 2015 Dec 1;152(Pt A):92-8. doi: 10.1016/j.physbeh.2015.09.018. Epub 2015 Sep 21. PubMed 26394125 ↗
  • Alvergne A, Hogqvist Tabor V. Is Female Health Cyclical? Evolutionary Perspectives on Menstruation. Trends Ecol Evol. 2018 Jun;33(6):399-414. doi: 10.1016/j.tree.2018.03.006. Epub 2018 May 16. PubMed 29778270 ↗
  • Munro MG, Critchley HOD, Fraser IS; FIGO Menstrual Disorders Committee. Corrigendum to "The two FIGO systems for normal and abnormal uterine bleeding symptoms and classification of causes of abnormal uterine bleeding in the reproductive years: 2018 revisions" [Int J Gynecol Obstet 143(2018) 393-408.]. Int J Gynaecol Obstet. 2019 Feb;144(2):237. doi: 10.1002/ijgo.12709. Epub 2018 Nov 27. No abstract available. PubMed 30609040 ↗
  • Vitzthum VJ. Field methods and strategies for assessing female reproductive functioning. Am J Hum Biol. 2021 Sep;33(5):e23513. doi: 10.1002/ajhb.23513. Epub 2020 Oct 6. PubMed 33022128 ↗
  • Gregory S, Denham SG, Lee P, Simpson JP, Homer NZM. Using LC-MS/MS to Determine Salivary Steroid Reference Intervals in a European Older Adult Population. Metabolites. 2023 Feb 13;13(2):265. doi: 10.3390/metabo13020265. PubMed 36837884 ↗
  • McDade TW, Burhop J, Dohnal J. High-sensitivity enzyme immunoassay for C-reactive protein in dried blood spots. Clin Chem. 2004 Mar;50(3):652-4. doi: 10.1373/clinchem.2003.029488. No abstract available. PubMed 14981035 ↗
  • McDade TW, Williams S, Snodgrass JJ. What a drop can do: dried blood spots as a minimally invasive method for integrating biomarkers into population-based research. Demography. 2007 Nov;44(4):899-925. doi: 10.1353/dem.2007.0038. PubMed 18232218 ↗
  • McDade TW. Development and validation of assay protocols for use with dried blood spot samples. Am J Hum Biol. 2014 Jan-Feb;26(1):1-9. doi: 10.1002/ajhb.22463. Epub 2013 Oct 15. PubMed 24130128 ↗
  • Fontana R, Della Torre S. The Deep Correlation between Energy Metabolism and Reproduction: A View on the Effects of Nutrition for Women Fertility. Nutrients. 2016 Feb 11;8(2):87. doi: 10.3390/nu8020087. PubMed 26875986 ↗
  • Vitzthum VJ, Bentley GR, Spielvogel H, Caceres E, Thornburg J, Jones L, Shore S, Hodges KR, Chatterton RT. Salivary progesterone levels and rate of ovulation are significantly lower in poorer than in better-off urban-dwelling Bolivian women. Hum Reprod. 2002 Jul;17(7):1906-13. doi: 10.1093/humrep/17.7.1906. PubMed 12093859 ↗
  • Tshomo T, Gurung MS, Shah S, Gil-Cuesta J, Maes P, Wangdi R, Tobden J. Menstrual Hygiene Management-Knowledge, Attitudes, and Practices Among Female College Students in Bhutan. Front Reprod Health. 2021 Aug 27;3:703978. doi: 10.3389/frph.2021.703978. eCollection 2021. PubMed 36303967 ↗
  • Li K, Urteaga I, Wiggins CH, Druet A, Shea A, Vitzthum VJ, Elhadad N. Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile-health data. NPJ Digit Med. 2020 May 26;3:79. doi: 10.1038/s41746-020-0269-8. eCollection 2020. PubMed 32509976 ↗
  • Lenton EA, Landgren BM, Sexton L, Harper R. Normal variation in the length of the follicular phase of the menstrual cycle: effect of chronological age. Br J Obstet Gynaecol. 1984 Jul;91(7):681-4. doi: 10.1111/j.1471-0528.1984.tb04830.x. PubMed 6743609 ↗
  • Windham GC, Elkin EP, Swan SH, Waller KO, Fenster L. Cigarette smoking and effects on menstrual function. Obstet Gynecol. 1999 Jan;93(1):59-65. doi: 10.1016/s0029-7844(98)00317-2. PubMed 9916957 ↗
  • Jukic AM, Weinberg CR, Baird DD, Wilcox AJ. Lifestyle and reproductive factors associated with follicular phase length. J Womens Health (Larchmt). 2007 Nov;16(9):1340-7. doi: 10.1089/jwh.2007.0354. PubMed 18001191 ↗
  • Kato I, Toniolo P, Koenig KL, Shore RE, Zeleniuch-Jacquotte A, Akhmedkhanov A, Riboli E. Epidemiologic correlates with menstrual cycle length in middle aged women. Eur J Epidemiol. 1999 Oct;15(9):809-14. doi: 10.1023/a:1007669430686. PubMed 10608360 ↗
  • Fenster L, Quale C, Waller K, Windham GC, Elkin EP, Benowitz N, Swan SH. Caffeine consumption and menstrual function. Am J Epidemiol. 1999 Mar 15;149(6):550-7. doi: 10.1093/oxfordjournals.aje.a009851. PubMed 10084244 ↗
  • Cole SK, Billewicz WZ, Thomson AM. Sources of variation in menstrual blood loss. J Obstet Gynaecol Br Commonw. 1971 Oct;78(10):933-9. doi: 10.1111/j.1471-0528.1971.tb00208.x. No abstract available. PubMed 5111902 ↗

Individual participant data

Plan to share: Yes — De-identified individual participant data (IPD) will be made available to other researchers upon reasonable request, following publication of the main study results. Data sharing will be subject to approval by the study steering committee and may require a data-sharing agreement to ensure compliance with GDPR and ethical guidelines

Supporting information: Study protocol, Sap, Icf, Analytic code

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jun 22, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07037082
Lead sponsor
University Hospital, Montpellier
Collaborators
National Research Agency, France, Institut National de la Santé Et de la Recherche Médicale, France, Centre National de la Recherche Scientifique, France, Institute of Evolutionary Science of Montpellier, Université Montpellier
Responsible party
Sponsor
First posted
Jun 25, 2025
Start date
Sep 1, 2025
Primary completion
Jul 1, 2029 (estimated)
Completion
Jul 1, 2029 (estimated)
Last update
Jun 22, 2026

Study contacts

Alexandra ALVERGNE, PhD
Contact
alexandra.alvergne@umontpellier.fr
+33467144966
Charlotte FAURIE, MD
Contact
charlotte.faurie@umontpellier.fr
Alexandra ALVERGNE, PhD
study director · Institute of Evolutionary Science of Montpellier (ISEM)
Noémie RANISAVLJEVIC, MD
study chair · University Montpellier hospital

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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