Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Women's Health Reviews
  4. Volume 21, Issue 2
  5. Article
Volume 21, Issue 2
  • ISSN: 1573-4048
  • E-ISSN: 1875-6581

Abstract

Though population explosion is a major problem of the world today, infertility also exists and needs attention. Understanding reproductive health, menstrual cycle, and adopting natural methods by couples can manage both fertility as well as infertility. During the preparation of the present review article, several search engines, such as Research Gate, Google Scholar, shodhganga, Scopus, emerging source citation index, chemical abstract services, academic journals database, open access medical journals, scirus, journal informatics, and various referred and non-referred journals were used for the extraction of scientific information. Hence, this article has been prepared meticulously, which would help married couples in adopting an effective life plan for managing their reproductive activities. It explains about means of avoiding unwanted pregnancies using some naturally proven methods available. It also addresses issues related to infertility. Understanding ovulation symptoms and the fertile window is the key to determine the right time for intercourse in order to avoid or plan pregnancy. The ovulation technique uses the indicators of ovulation to determine the fertile window. A rise in body temperature and changes in cervical mucus (wet, clear, slippery) are the best indicators of ovulation. Understanding the concept of the fertile window enables women to strategically plan the timing of intercourse in order to either facilitate conception or prevent it.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cwhr/10.2174/0115734048282403240101112918
2024-01-11
2025-01-11

  • From This Site

    /content/journals/cwhr/10.2174/0115734048282403240101112918
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. AbmaJ.C. MartinezG.M. CopenC.E. Teenagers in the United States: sexual activity, contraceptive use, and childbearing, national survey of family growth 2006-2008.Vital Health Stat. 2320103014721548441
     [Google Scholar]
  2. CornerG. Our knowledge of the menstrual cycle, 1910-1950.Lancet1951257666191992310.1016/S0140‑6736(51)92447‑614825858
     [Google Scholar]
  3. VoD.X. PateO.L. ZhaoH. SiuP. GinsburgK.R. Voices of asian american youth: Important characteristics of clinicians and clinical sites.Pediatrics20071206e1481e149310.1542/peds.2007‑035117984213
     [Google Scholar]
  4. WilcoxA.J. WeinbergC.R. BairdD.D. Timing of sexual intercourse in relation to ovulation. Effects on the probability of conception, survival of the pregnancy, and sex of the baby.N. Engl. J. Med.1995333231517152110.1056/NEJM1995120733323017477165
     [Google Scholar]
  5. ColeL.A. LadnerD.G. ByrnF.W. The normal variabilities of the menstrual cycle.Fertil. Steril.200991252252710.1016/j.fertnstert.2007.11.07318433748
     [Google Scholar]
  6. SuH.W. YiY.C. WeiT.Y. ChangT.C. ChengC.M. Detection of ovulation, a review of currently available methods.Bioeng. Transl. Med.20172323824610.1002/btm2.1005829313033
     [Google Scholar]
  7. SusannahF. DugganM. Mobile health.2012Available from: https://www. pewinternet.org/2012/11/08/mobile-health-2012/ (Accessed June 2019).
  8. FawcettT. Mining the quantified self: Personal knowledge discovery as a challenge for data science.Big Data20153424926610.1089/big.2015.004927441406
     [Google Scholar]
  9. WiseL.A. RothmanK.J. MikkelsenE.M. StanfordJ.B. WesselinkA.K. McKinnonC. GruschowS.M. HorganC.E. WileyA.S. HahnK.A. SørensenH.T. HatchE.E. Design and conduct of an Internet-based preconception cohort study in North America: Pregnancy study online.Paediatr. Perinat. Epidemiol.201529436037110.1111/ppe.1220126111445
     [Google Scholar]
  10. ChenetteP. MartinezC. Synchronization of women’s cycles: A big data and crowdsourcing approach to menstrual cycle analysis.Fertil. Steril.20141023e25010.1016/j.fertnstert.2014.07.853
     [Google Scholar]
  11. LangeA. YehJ. MesserlianC. HauserR. ChavarroJ.E. GaskinsA.J. TothT.L. Smartphone fertility app use among couples of reproductive age: Potential use of big data to improve fertility care and advance reproductive health research.Fertil. Steril.20161063e11110.1016/j.fertnstert.2016.07.318
     [Google Scholar]
  12. LanhamM. ChristensenM.A. Fertility-related smartphone application use among patients seeking treatment for infertility.Fertil. Steril.20151043e35410.1016/j.fertnstert.2015.07.1102
     [Google Scholar]
  13. MartinezC. Monthly fecundity and the benefits of ovulation tracking in the United States. What big data tells us about the true nature of fertility.Fertil. Steril.20151043e30410.1016/j.fertnstert.2015.07.951
     [Google Scholar]
  14. SmallC.M. ManatungaA.K. KleinM. FeigelsonH.S. DominguezC.E. McChesneyR. MarcusM. Menstrual cycle characteristics: Associations with fertility and spontaneous abortion.Epidemiology2006171526010.1097/01.ede.0000190540.95748.e616357595
     [Google Scholar]
  15. WilcoxA.J. DunsonD. BairdD.D. The timing of the “fertile window” in the menstrual cycle: Day specific estimates from a prospective study.BMJ200032172711259126210.1136/bmj.321.7271.125911082086
     [Google Scholar]
  16. EcochardR. BoehringerH. RabilloudM. MarretH. Chronological aspects of ultrasonic, hormonal, and other indirect indices of ovulation.BJOG2001108882282910.1111/j.1471‑0528.2001.00194.x11510707
     [Google Scholar]
  17. GuermandiE. VegettiW. BianchiM.M. UgliettiA. RagniG. CrosignaniP. Reliability of ovulation tests in infertile women.Obstet. Gynecol.2001971929611152915
     [Google Scholar]
  18. DireitoA. BaillyS. MarianiA. EcochardR. Relationships between the luteinizing hormone surge and other characteristics of the menstrual cycle in normally ovulating women.Fertil. Steril.2013991279285.e310.1016/j.fertnstert.2012.08.04722999798
     [Google Scholar]
  19. PfeiferS. ButtsS. FossumG. GraciaC. La BarberaA. MersereauJ. OdemR. PaulsonR. PenziasA. PisarskaM. RebarR. ReindollarR. RosenM. SandlowJ. VernonM. Optimizing natural fertility: A committee opinion.Fertil. Steril.20171071525810.1016/j.fertnstert.2016.09.02928228319
     [Google Scholar]
  20. GnothC. Frank-HerrmannP. SchmollA. GodehardtE. FreundlG. Cycle characteristics after discontinuation of oral contraceptives.Gynecol. Endocrinol.200216430731710.1080/gye.16.4.307.31712396560
     [Google Scholar]
  21. NassarallaC.L. StanfordJ.B. DalyK.D. SchneiderM. SchliepK.C. FehringR.J. Characteristics of the menstrual cycle after discontinuation of oral contraceptives.J. Womens Health201120216917710.1089/jwh.2010.200121219248
     [Google Scholar]
  22. DunsonD.B. StanfordJ.B. Bayesian inferences on predictors of conception probabilities.Biometrics200561112613310.1111/j.0006‑341X.2005.031231.x15737085
     [Google Scholar]
  23. DarneyP. PatelA. RosenK. ShapiroL.S. KaunitzA.M. Safety and efficacy of a single-rod etonogestrel implant (Implanon): Results from 11 international clinical trials.Fertil. Steril.20099151646165310.1016/j.fertnstert.2008.02.14018423453
     [Google Scholar]
  24. YarkoniT. WestfallJ. Bambi: A simple interface for fitting Bayesian mixed effects models.Available from : https://osf.io/preprints/osf/rv7sn (Accessed June 2019).10.31219/osf.io/rv7sn
  25. SalvatierJ. WieckiT.V. FonnesbeckC. Probabilistic programming in Python using PyMC3.PeerJ Comput. Sci.20162e5510.7717/peerj‑cs.55
     [Google Scholar]
  26. WestfallJ. Statistical details of the default priors in the Bambi library.Available from : https://arxiv.org/abs/1702.01201
  27. WeschlerT. Taking charge of your fertility.New YorkHarperCollins2006
     [Google Scholar]
  28. Evans-HoekerE. PritchardD.A. LongD.L. HerringA.H. StanfordJ.B. SteinerA.Z. Cervical mucus monitoring prevalence and associated fecundability in women trying to conceive.Fertil. Steril.2013100410331038.e110.1016/j.fertnstert.2013.06.00223850303
     [Google Scholar]
  29. FidanU. KeskinU. UlubayM. ÖztürkM. BodurS. Value of vaginal cervical position in estimating uterine anatomy.Clin. Anat.201730340440810.1002/ca.2285428192868
     [Google Scholar]
  30. EnglishA. FordC.A. The HIPAA privacy rule and adolescents: legal questions and clinical challenges.Perspect. Sex. Reprod. Health2004362808610.1363/360800415136211
     [Google Scholar]
  31. National Library of MedicinePelvic pain.Available from: https://medlineplus.gov/pelvicpain.html (Accessed August 16 2018).
     [Google Scholar]
  32. CanobbioM.M. Contraception for the adolescent and young adult with congenital heart disease.Nurs. Clin. North Am.200439476978510.1016/j.cnur.2004.08.00115561159
     [Google Scholar]
  33. WoodsN. (a) Premenstrual symptoms: another look. Public Health Rep 1987; 102:106. (b) Gavin L, Moskosky S, Carter M, Curtis K, Glass E, Godfrey E, Marcell A, Mautone-Smith N, Pazol K, Tepper N, Zapata L. Providing quality family planning services: recommendations of CDC and the US Office of Population Affairs. Morbidity and Mortality Weekly Report.Recomm Rep2014634154
     [Google Scholar]
  34. StachowskaA KicińskaAM WierzbaTH The history of fertility awareness methods.Kwartalnik Naukowy Fides et Ratio202251310.34766/fetr.v3i51.1093
     [Google Scholar]
  35. GrimesDA GalloMF HalpernV NandaK SchulzKF LopezLM Fertility awareness-based methods for contraception.Cochrane Database Syst Rev2004410.1002/14651858.CD004860.pub2
     [Google Scholar]
  36. SymulL. WacK. HillardP. SalathéM. Assessment of menstrual health status and evolution through mobile apps for fertility awareness.NPJ Digit. Med.2019216410.1038/s41746‑019‑0139‑431341953
     [Google Scholar]
  37. OpSC Promoting Men’s involvement in family planning: Its’ implication for social work practice in nigeria.methods2016621
     [Google Scholar]
  38. JudákováZ. The role of information technologies in natural family planning.InFamily Planning and Reproductive HealthIntechOpen.2020120
     [Google Scholar]
  39. UrrutiaR.P. PolisC.B. Fertility awareness based methods for pregnancy prevention.BMJ2019366l424510.1136/bmj.l424531296535
     [Google Scholar]
  40. Frank-HerrmannP. HeilJ. GnothC. ToledoE. BaurS. PyperC. JenetzkyE. StrowitzkiT. FreundlG. The effectiveness of a fertility awareness based method to avoid pregnancy in relation to a couple’s sexual behaviour during the fertile time: a prospective longitudinal study.Hum. Reprod.20072251310131910.1093/humrep/dem00317314078
     [Google Scholar]
  41. TrivaxB. AzzizR. Diagnosis of polycystic ovary syndrome.Clin. Obstet. Gynecol.200750116817710.1097/GRF.0b013e31802f351b17304034
     [Google Scholar]
  42. HallA.M. KutlerB.A. Intrauterine contraception in nulliparous women: A prospective survey.J. Fam. Plann. Reprod. Health Care2016421364210.1136/jfprhc‑2014‑10104625854550
     [Google Scholar]
  43. BatesonD. HarveyC. TrinhL. StewartM. BlackK.I. User characteristics, experiences and continuation rates of copper intrauterine device use in a cohort of Australian women.Aust. N. Z. J. Obstet. Gynaecol.201656665566110.1111/ajo.1253427704541
     [Google Scholar]
  44. JonesR.K. LindbergL.D. HigginsJ.A. Pull and pray or extra protection? Contraceptive strategies involving withdrawal among US adult women.Contraception201490441642110.1016/j.contraception.2014.04.01624909635
     [Google Scholar]
  45. Peragallo UrrutiaR. PolisC.B. JensenE.T. GreeneM.E. KennedyE. StanfordJ.B. Effectiveness of fertility awareness-based methods for pregnancy prevention: A systematic review.Obstet. Gynecol.2018132359160410.1097/AOG.000000000000278430095777
     [Google Scholar]
  46. JohnsonS. MarriottL. ZinamanM. Can apps and calendar methods predict ovulation with accuracy?Curr. Med. Res. Opin.20183491587159410.1080/03007995.2018.147534829749274
     [Google Scholar]
  47. GuzmanL. CaalS. PetersonK. RamosM. HickmanS. The use of fertility awareness methods (FAM) among young adult Latina and black women: what do they know and how well do they use it? Use of FAM among Latina and black women in the United States.Contraception201388223223810.1016/j.contraception.2013.05.01523845211
     [Google Scholar]
  48. DuaneM. ContrerasA. JensenE.T. WhiteA. The performance of fertility awareness-based method apps marketed to avoid pregnancy.J. Am. Board Fam. Med.201629450851110.3122/jabfm.2016.04.16002227390383
     [Google Scholar]
  49. HarmonA. TowegoodmanN. FortunatoC. GrangerD. Differences in saliva collection location and disparities in baseline and diurnal rhythms of alpha-amylase: A preliminary note of caution.Horm. Behav.200854559259610.1016/j.yhbeh.2008.05.01918640119
     [Google Scholar]
  50. U.S. Food and Drug AdministrationDevice software functions including mobile medical applications.2019
     [Google Scholar]
  51. PolisC.B. Published analysis of contraceptive effectiveness of Daysy and DaysyView app is fatally flawed.Reprod. Health201815111310.1186/s12978‑018‑0560‑129940983
     [Google Scholar]
  52. TherapeuticsM.D. Prescribing information Annovera (segesterone acetate and ethinyl estradiol vaginal system).Boca Raton, FL2018https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/209627s000lbl.pdf
     [Google Scholar]
  53. KohnJ.E. SimonsH.R. Della BadiaL. DraperE. MorfesisJ. TalmontE. BeasleyA. McDonaldM. WesthoffC.L. Increased 1-year continuation of DMPA among women randomized to self-administration: results from a randomized controlled trial at Planned Parenthood.Contraception201897319820410.1016/j.contraception.2017.11.00929246818
     [Google Scholar]
  54. PalombaS. DaolioJ. RomeoS. BattagliaF.A. MarciR. La SalaG.B. Lifestyle and fertility: The influence of stress and quality of life on female fertility.Reprod. Biol. Endocrinol.201816111310.1186/s12958‑018‑0434‑y30501641
     [Google Scholar]
  55. RothmanK.J. WiseL.A. SørensenH.T. RiisA.H. MikkelsenE.M. HatchE.E. Volitional determinants and age-related decline in fecundability: A general population prospective cohort study in Denmark.Fertil. Steril.20139971958196410.1016/j.fertnstert.2013.02.04023517858
     [Google Scholar]
  56. WellingLL BurrissRP Investigating the ovulatory cycle.InThe Oxford handbook of evolutionary psychology and behavioral endocrinologyOxford University Press.201910910.1093/oxfordhb/9780190649739.013.6
     [Google Scholar]
  57. VandenbrouckeJ.P. RosingJ. BloemenkampK.W.M. MiddeldorpS. HelmerhorstF.M. BoumaB.N. RosendaalF.R. Oral contraceptives and the risk of venous thrombosis.N. Engl. J. Med.2001344201527153510.1056/NEJM20010517344200711357157
     [Google Scholar]
  58. MishraG.D. PandeyaN. DobsonA.J. ChungH.F. AndersonD. KuhD. SandinS. GilesG.G. BruinsmaF. HayashiK. LeeJ.S. MizunumaH. CadeJ.E. BurleyV. GreenwoodD.C. GoodmanA. SimonsenM.K. AdamiH.O. DemakakosP. WeiderpassE. Early menarche, nulliparity and the risk for premature and early natural menopause.Hum. Reprod.201732367968610.1093/humrep/dew35028119483
     [Google Scholar]
  59. TakaiN. YamaguchiM. AragakiT. EtoK. UchihashiK. NishikawaY. Effect of psychological stress on the salivary cortisol and amylase levels in healthy young adults.Arch. Oral Biol.2004491296396810.1016/j.archoralbio.2004.06.00715485637
     [Google Scholar]
  60. NaterU.M. RohlederN. GaabJ. BergerS. JudA. KirschbaumC. EhlertU. Human salivary alpha-amylase reactivity in a psychosocial stress paradigm.Int. J. Psychophysiol.200555333334210.1016/j.ijpsycho.2004.09.00915708646
     [Google Scholar]
  61. RaffH. HomarP.J. SkonerD.P. New enzyme immunoassay for salivary cortisol.Clin. Chem.200349120320410.1373/49.1.20312507989
     [Google Scholar]
  62. GrangerD.A. KivlighanK.T. El-SheikhM. GordisE.B. StroudL.R. Salivary alpha-amylase in biobehavioral research: Recent developments and applications.Ann. N. Y. Acad. Sci.20071098112214410.1196/annals.1384.00817332070
     [Google Scholar]
  63. PalloneS.R. BergusG.R. Fertility awareness-based methods: Another option for family planning.J. Am. Board Fam. Med.200922214715710.3122/jabfm.2009.02.08003819264938
     [Google Scholar]
  64. TakahashiT. FujimoriC. HagiwaraA. OgiwaraK. Recent advances in the understanding of teleost medaka ovulation: The roles of proteases and prostaglandins.Zool. Sci.201330423924710.2108/zsj.30.23923537233
     [Google Scholar]
  65. LaliveR. ZweimüllerJ. How does parental leave affect fertility and return to work? Evidence from two natural experiments.Q. J. Econ.200912431363140210.1162/qjec.2009.124.3.1363
     [Google Scholar]
  66. ShilaihM. GoodaleB.M. FalcoL. KüblerF. De ClerckV. LeenersB. Modern fertility awareness methods: wrist wearables capture the changes in temperature associated with the menstrual cycle.Biosci. Rep.2018386BSR2017127910.1042/BSR2017127929175999
     [Google Scholar]
  67. LobmaierJ.S. BachofnerL.M. Timing is crucial: Some critical thoughts on using LH tests to determine women’s current fertility.Horm. Behav.2018106A2A310.1016/j.yhbeh.2018.07.00530092174
     [Google Scholar]
  68. LavenJ.S.E. MuldersA.G.M.G.J. VisserJ.A. ThemmenA.P. de JongF.H. FauserB.C.J.M. Anti-Müllerian hormone serum concentrations in normoovulatory and anovulatory women of reproductive age.J. Clin. Endocrinol. Metab.200489131832310.1210/jc.2003‑03093214715867
     [Google Scholar]
  69. PiltonenT. Morin-PapunenL. KoivunenR. PerheentupaA. RuokonenA. TapanainenJ.S. Serum anti-Müllerian hormone levels remain high until late reproductive age and decrease during metformin therapy in women with polycystic ovary syndrome.Hum. Reprod.20052071820182610.1093/humrep/deh85015802325
     [Google Scholar]
  70. VillarroelC. MerinoP.M. LópezP. EyzaguirreF.C. Van VelzenA. IñiguezG. CodnerE. Polycystic ovarian morphology in adolescents with regular menstrual cycles is associated with elevated anti-Mullerian hormone.Hum. Reprod.201126102861286810.1093/humrep/der22321784736
     [Google Scholar]
  71. EilertsenT.B. VankyE. CarlsenS.M. Anti-Mullerian hormone in the diagnosis of polycystic ovary syndrome: Can morphologic description be replaced?Hum. Reprod.20122782494250210.1093/humrep/des21322693172
     [Google Scholar]
  72. RobinG. GalloC. Catteau-JonardS. Lefebvre-MaunouryC. PignyP. DuhamelA. DewaillyD. Polycystic Ovary-Like Abnormalities (PCO-L) in women with functional hypothalamic amenorrhea.J. Clin. Endocrinol. Metab.201297114236424310.1210/jc.2012‑183622948766
     [Google Scholar]
  73. PignyP. GorisseE. GhulamA. RobinG. Catteau-JonardS. DuhamelA. DewaillyD. Comparative assessment of five serum antimüllerian hormone assays for the diagnosis of polycystic ovary syndrome.Fertil. Steril.2016105410631069.e310.1016/j.fertnstert.2015.12.02326769302
     [Google Scholar]
  74. VillarroelC. LópezP. MerinoP.M. IñiguezG. Sir-PetermannT. CodnerE. Hirsutism and oligomenorrhea are appropriate screening criteria for polycystic ovary syndrome in adolescents.Gynecol. Endocrinol.201531862562910.3109/09513590.2015.102538026190534
     [Google Scholar]
  75. Ramlau-HansenC.H. ThulstrupA.M. NohrE.A. BondeJ.P. SørensenT.I.A. OlsenJ. Subfecundity in overweight and obese couples.Hum. Reprod.20072261634163710.1093/humrep/dem03517344224
     [Google Scholar]
  76. AxmonA. RylanderL. AlbinM. HagmarL. Factors affecting time to pregnancy.Hum. Reprod.20062151279128410.1093/humrep/dei46916410331
     [Google Scholar]
  77. StarlingM.S. KandelZ. HaileL. SimmonsR.G. User profile and preferences in fertility apps for preventing pregnancy: An exploratory pilot study.mHealth201842110.21037/mhealth.2018.06.0230050917
     [Google Scholar]
  78. Berglund ScherwitzlE. LundbergO. Kopp KallnerH. Gemzell DanielssonK. TrussellJ. ScherwitzlR. Perfect-use and typical-use Pearl Index of a contraceptive mobile app.Contraception201796642042510.1016/j.contraception.2017.08.01428882680
     [Google Scholar]
  79. JenningsV. HaileL.T. SimmonsR.G. SpielerJ. ShattuckD. Perfect- and typical-use effectiveness of the Dot fertility app over 13 cycles: Results from a prospective contraceptive effectiveness trial.Eur. J. Contracept. Reprod. Health Care201924214815310.1080/13625187.2019.158116430880509
     [Google Scholar]
  80. GrimesD.A. GalloM.F. GrigorievaV. NandaK. SchulzK.F. Fertility awareness-based methods for contraception.Cochrane Database Syst. Rev.200420044CD00486015495128
     [Google Scholar]
  81. World Health OrganizationFact Sheet: Family Planning/ContraceptionAvailable from : https://www.who.int/news-room/fact-sheets/detail/family-planning-contraception 2018
     [Google Scholar]
  82. ArévaloM. JenningsV. SinaiI. Efficacy of a new method of family planning: The standard days method.Contraception200265533333810.1016/S0010‑7824(02)00288‑312057784
     [Google Scholar]
  83. MurphyN. YoungP.C. Sexuality in children and adolescents with disabilities.Dev. Med. Child Neurol.200547964064410.1111/j.1469‑8749.2005.tb01220.x16138674
     [Google Scholar]
  84. Berglund ScherwitzlE. Lindén HirschbergA. ScherwitzlR. Identification and prediction of the fertile window using NaturalCycles.Eur. J. Contracept. Reprod. Health Care201520540340810.3109/13625187.2014.98821025592280
     [Google Scholar]
  85. GalloM.F. LopezL.M. GrimesD.A. SchulzK.F. HelmerhorstF.M. Combination contraceptives: Effects on weight.Cochrane Database Syst. Rev.20084CD00398718843652
     [Google Scholar]
  86. BehreH.M. KuhlageJ. GaβnerC. SonntagB. SchemC. SchneiderH.P.G. NieschlagE. Prediction of ovulation by urinary hormone measurements with the home use ClearPlan® Fertility Monitor: Comparison with transvaginal ultrasound scans and serum hormone measurements.Hum. Reprod.200015122478248210.1093/humrep/15.12.247811098014
     [Google Scholar]
  87. RielyC. Contraception and pregnancy after liver transplantation.Liver Transpl.2001711Suppl. 1S74S7610.1053/jlts.2001.2864411689779
     [Google Scholar]
  88. DunsonD.B. BairdD.D. WilcoxA.J. WeinbergC.R. Day-specific probabilities of clinical pregnancy based on two studies with imperfect measures of ovulation.Hum. Reprod.19991471835183910.1093/humrep/14.7.183510402400
     [Google Scholar]
  89. BullJ.R. RowlandS.P. ScherwitzlE.B. ScherwitzlR. DanielssonK.G. HarperJ. Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles.NPJ Digit. Med.2019218310.1038/s41746‑019‑0152‑731482137
     [Google Scholar]
  90. SucatoG.S. LandS.R. MurrayP.J. CecchiniR. GoldM.A. Adolescents’ experiences using the contraceptive patch versus pills.J. Pediatr. Adolesc. Gynecol.201124419720310.1016/j.jpag.2011.02.00121454110
     [Google Scholar]
  91. TrussellJ. AikenA.R.A. MicksE. Efficacy, safety, and per-sonal considerations.Contraceptive technology.21st ed HatcherR.A. NelsonA.L. TrussellJ. New York, NYAyer Company Publishers201895128
     [Google Scholar]
  92. ButlerW.R. Inhibition of ovulation in the postpartum cow and the lactating sow.Livest. Prod. Sci.2005981-251210.1016/j.livprodsci.2005.10.007
     [Google Scholar]
  93. PuS. WangM. WangJ. ZhangQ. MaX. WangR. YuS. WangL. PanY. Metagenomic analysis reveals a dynamic microbiome with diversified adaptive functions that respond to ovulation regulation in the mouse endometrium.BMC Genomics202324161510.1186/s12864‑023‑09712‑837833670
     [Google Scholar]
  94. SeliE. DulebaA.J. Optimizing ovulation induction in women with polycystic ovary syndrome.Curr. Opin. Obstet. Gynecol.200214324525410.1097/00001703‑200206000‑0000212032379
     [Google Scholar]
/content/journals/cwhr/10.2174/0115734048282403240101112918
Loading
Understanding Fertile Window: A Key to Pregnancy as well as Contraception
Current Women's Health Reviews 21, E110124225540 (2025); https://doi.org/10.2174/0115734048282403240101112918
/content/journals/cwhr/10.2174/0115734048282403240101112918
/content/journals/cwhr/10.2174/0115734048282403240101112918
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): body temperature; cervical mucus; Fertile window; infertility; ovulation; pregnancy

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test