Assess quantitatively the impact of nocturnal light pollution on the menstrual cycle.
Design
Cross-sectional observational study.
Setting
Single French institute from November 2017 to March 2018.
Participants
Nineteen ostensibly healthy menstruating women aged 19 to 45, inclusive. Intervention(s): None.
Main Outcome Measures
Assessment of nocturnal light pollution (questionnaire and lux meter) and 22 clinical signs of ovulation disorder. Wilcoxon tests were used to quantify the abilities of nocturnal light pollution factors to predict clinical signs of ovulation disorders.
Results
Nearly half of the 94 daily observations made by questionnaire and measurements made by lux meter indicated light pollution due to light flooding into the bedroom from indoor or outdoor sources. Nearly more than half of the 56 menstrual cycles presented at least mild abnormalities. The data showed that some clinical signs of ovulation disorders may be significantly predicted by factors of light pollution but a lack of power prevented reaching Bonferroni criterion.
Conclusions
The indications of negative impact of dim light at night on some menstrual cycle characteristics call for a randomized study to quantify improvements of menstrual cycle characteristics brought by suppressing nocturnal light pollution. This will pave the way for new therapeutic perspectives for some difficult cases of ovulation disorders.
The hypothalamic-pituitary-ovarian (HPO) axis is a tightly regulated system controlling female reproduction. HPO axis dysfunction leading to ovulation disorders can be classified into three categories defined by the World Health Organization (WHO). Group I ovulation disorders involve hypothalamic failure characterized as hypogonadotropic hypogonadism. Group II disorders display a eugonadal state commonly associated with a wide range of endocrinopathies. Finally, group III constitutes hypergonadotropic hypogonadism secondary to depleted ovarian function. Optimal evaluation and management of these disorders is based on a careful analysis tailored to each patient. This article reviews ovulation disorders based on pathophysiologic mechanisms, evaluation principles, and currently available management options.
Hilgers TW, 2004·The Medical and Surgical Practice of NaProTECHNOLOGY·
The sonographic ovulation classification is validated against targeted hormone profiles -- estradiol, LH, and serial post-Peak progesterone (P+3 through P+11) -- drawn at CrMS Peak-anchored time points rather than fixed calendar days. Hormone patterns corresponding to each sonographic category (e.g., absent LH surge in anovulation, progesterone rise without follicle rupture in LUF) confirm that ultrasound morphology reliably reflects the underlying endocrine disorder, establishing the biochemical legitimacy of the classification for clinical diagnosis.
To characterize how the menstrual cycle pattern relates to fertility regardless of potential biases caused by inappropriate coital timing during the menstrual cycle or early embryonal loss. Prospective follow-up study. Healthy couples recruited throughout Denmark. PATIENT(S): Two hundred ninety-five couples who were planning their first pregnancy were followed up from the discontinuation of birth control until a pregnancy was recognized within six menstrual cycles. Early embryonal losses were detected by changes in urinary hCG levels. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): The probability of pregnancy occurring within one menstrual cycle (fecundity). RESULT(S): In women who had a cycle length that differed by >10 days from the usual cycle length, fecundity was approximately 25% that of women who had no variation (odds ratio 0.25, 95% confidence interval 0.09-0.68). When the combined effect of cycle variation and cycle length was assessed, cycle variation was a persistent strong predictor of fecundity. CONCLUSION(S): The mechanisms of the present findings probably are female functional disturbances in ovulation, conception, implantation, or sustained pregnancy, linked with variable menstrual cycle length. Thus, identification of medical and environmental causes of abnormal menstrual cycle patterns may provide clues to the causes of infertility. Moreover, the menstrual cycle pattern also should be taken into consideration in the clinical decision-making process.
A significant portion of human infertility is presumably due to defective ovulation, including patients who fail to conceive despite medical induction of ovulation, those who fail despite repeated timely donor inseminations, and those with "infertility of unknown etiology". All point out the inadequacy of standard criteria for normal ovulation. This investigation correlates preovulatory serum estradiol and gonadotropin concentrations with dominant follicle growth measured ultrasonographically and serum progesterone levels. The data indicate a 35% incidence of cycles with significantly abnormal serum estradiol levels, decreased dominant follicle size, and abnormal progesterone levels despite biphasic basal body temperature curves and normal cycle length. If these cycles represent inadequate or abnormal ovulation, they can be distinguished from adequate cycles prior to follicle rupture and may benefit the treatment of human infertility.