Age-Dependent and Seasonal Changes in Menstrual Cycle Length and Body Temperature Based on Big Data

Menstrual Cycle Characteristics of U. S. Adolescents According to Gynecologic Age and Age at Menarche

STUDY OBJECTIVE

To characterize typical menstrual cycle characteristics in adolescents and determine how these differ with age at menarche or years since menarche (gynecologic age).

METHODS

We surveyed 13 to 18-year-old U.S. users of the Clue app (N = 6,486) and linked their responses to app-recorded cycle data (N=38,916 cycles). We analyzed cycle characteristics including cycle length, cycle variability, period length, experience of heavy flow, and dysmenorrhea in relation to gynecologic age and menarcheal age using mixed effects models.

RESULTS

With increasing gynecologic age, we observed dose-dependent associations of lower odds of cycle irregularity (defined as cycles that were highly variable, short, or long) and higher odds of reporting ≥1 day of heavy flow. Individuals <1 year post-menarche had lower odds of heavy flow (Odds Ratio (OR) = 0.3; 95% confidence interval (CI): 0.1, 0.6), and increased odds of having a highly variable cycle (OR = 2.6; 95% CI: 1.3, 5.2) or short cycles (OR = 5.0; 95% CI: 2.3, 11.0) compared to those who were 6+ years post-menarche. We also found associations with early and late age at menarche. Compared to menarcheal age of 14+ years, menarcheal age ≤10 years was associated with shorter cycle length (β = -1.63 days; 95% CI: -2.51, -0.75), increased odds of dysmenorrhea (OR = 3.2; 95% CI: 2.3, 4.6), and decreased odds of high cycle variability (OR = 0.8; 95% CI: 0.6, 1.0).

CONCLUSION

Cycle characteristics in adolescence are associated with menarcheal age and gynecologic age. Notably, highly variable cycles are common, especially among those with younger gynecologic age or older menarcheal age.

Menstrual cycle patterns and their relationship with measures of well-being and perceived performance metrics in competitive and recreational resistance-trained athletes

BACKGROUND

There is mixed evidence on how the menstrual cycle (MC) affects sports performance, with many studies showing variations in performance during different phases of the MC, while other evidence shows that the MC's effects on performance may be trivial. Therefore, this exploratory longitudinal monitoring study was designed to investigate MC characteristics and symptoms in a resistance-trained (RT) population to look for associations between measures of well-being and perceived performance metrics across the MC.

METHODS

RT females reported their workout habits, perceived performance metrics, and measures of well-being while tracking their MC with detailed methods via daily check-ins in an app.

RESULTS

Most MC characteristics and symptoms in the present RT population aligned with previous research on the general population. However, the frequency of irregular cycles was higher than in previous research on the general population. The amount of individual variation and within-subject cycle-to-cycle variation in MC characteristics and MC symptoms was also high. All measures of well-being were significantly associated with specific days of the MC, demonstrating a change in well-being based on the timing of the MC. Several perceived performance metrics were significantly associated with changes across the MC, while others were not.

CONCLUSIONS

Overall, with the current evidence as it stands, a highly individualized approach should be taken for any training or performance considerations surrounding the MC due to the high levels of individual variation.

Coronary artery culprit lesions progression and ambient temperature exposure - personalised analysis

Introduction

Global warming is claimed to be an important cardiovascular disease risk factor. The air pollution and ambient temperatures are believed to have a significant influence on increased morbidity and premature deaths.

Aim

To point out possible causative factors for coronary angiography progression in patients presenting with chronic coronary syndrome.

Material and methods

There were 66 patients (41 [62%] men and 25 [38%] women) with a median age of 71.5 (62-76) years, who underwent repeated coronary angiographies due to chronic coronary syndrome within a median time interval of 145 (96-296) days. In 18 (27%) patients coronary artery lesion progression was observed despite optimal pharmacotherapy. The demographical, clinical, and personalised epidemiological factors including air pollution particles and ambient temperature exposure were taken into account in the analysis.

Results

In the multivariate logistic regression model with backward stepwise elimination method, tropical nights (p = 0.047) and mean daily temperatures (p = 0.043) were revealed as predictors of coronary lesion progression > 30%. The analysis of seasonal temperature changes showed significant differences related to minimal winter temperatures between both groups (p = 0.018).

Conclusions

Coronary artery lesion progression can be related to either high values of daily temperatures or to low ambient temperature. The dichotomous characteristics of temperature exposure to atherosclerosis progression suggest a detrimental role of environmental extremities on human health.

Prolongation of the Menstrual Cycle After Receipt of the Primary Series and Booster Doses of mRNA Coronavirus Disease 2019 (COVID-19) Vaccination

OBJECTIVE

To quantitatively evaluate the effect of a booster vaccination dose against coronavirus disease 2019 (COVID-19) on menstrual cycle in a large-scale retrospective cohort study using a menstrual cycle tracking smartphone application (app).

METHODS

Prospectively or retrospectively recorded data, including the start and finish dates of menstrual cycles, were collected with the app. Detailed data on vaccinations, side effects, and participants' characteristics were retrospectively collected from a questionnaire on the app. For each COVID-19 vaccination shot (first, second, and third), within-individual changes in menstrual cycle length up to the fourth postvaccination cycle were evaluated.

RESULTS

Among the 7,376 and 6,873 participants who had the first and second COVID-19 vaccine doses in different menstrual cycles, respectively, menstrual cycles immediately after the vaccination (first postvaccination cycles) were an average of 0.22 days (95% CI, 0.06-0.39) and 0.37 days (95% CI, 0.20-0.54) longer than the prevaccination cycle. In contrast, among the 1,672 participants who received the first and second doses in the same cycle, the first postvaccination cycle was an average of 4.21 days (95% CI, 3.69-4.72) longer. The second to fourth postvaccination cycles returned to the level of the prevaccination cycle. However, among the 4,768 participants who had the third COVID-19 vaccine dose, the menstrual cycle immediately after the vaccination was an average of 1.20 days (95% CI, 1.00-1.40) longer, with prolongation of cycles of 0.27 days (95% CI, 0.10-0.44) to 0.41 days (95% CI, 0.22-0.59) persisting from the second to the fourth postvaccination cycle.

CONCLUSION

The booster shot against COVID-19 may have a greater and longer-lasting effect on menstrual cycles than the primary-series shots. Although the effect size was small, evidence on the side effects of immunization on menstruation should be accumulated.

The menstrual cycle is influenced by weekly and lunar rhythms

OBJECTIVE

To study whether the menstrual cycle has a circaseptan (7 days) rhythm and whether it is associated with the lunar cycle (also defined as the synodic month, it is the cycle of the phases of the Moon as seen from Earth, averaging 29.5 days in length).

DESIGN

Cross-sectional study.

SUBJECTS

A total of 35,940 European and North American women aged 18-40 years.

EXPOSURE

Data were collected in real-life conditions.

INTERVENTION

No intervention was performed.

MAIN OUTCOME MEASURE

The onset of menstruation was assessed in prospectively measured menstrual cycles (311,064 cycles) over 3 full years (2019-2021). Associations were calculated between the onset of menstruation and the day of the week, and between the onset of menstruation and the lunar phase.

RESULTS

In this large data set, a circaseptan (7-day) rhythmicity of menstruation was observed, with a peak (acrophase) of menstrual onset on Thursdays and Fridays. This circaseptan rhythm was observed in every age group, in every phase of the lunar cycle, and in all seasons. This feature was most pronounced for cycle durations between 27 and 29 days. In winter, the circaseptan rhythm was found in cycles of 27-29 days, but not in other cycle lengths. A circalunar rhythm was also statistically significant, but not as clearly defined as the circaseptan rhythm. The peak (acrophase) of the circalunar rhythm of menstrual onset varied according to the season. In addition, there was a small but statistically significant interaction between the circaseptan rhythm and the lunar cycle.

CONCLUSION

Although relatively small in amplitude, the weekly rhythm of menstruation was statistically significant. Menstruation occurs more often on Thursdays and Fridays than on other days of the week. This is particularly true for women whose cycles last between 27 and 29 days. Circalunar rhythmicity was also statistically significant. However, it is less pronounced than the weekly rhythm.

A molecular staging model for accurately dating the endometrial biopsy

Natural variability in menstrual cycle length, coupled with rapid changes in endometrial gene expression, makes it difficult to accurately define and compare different stages of the endometrial cycle. Here we develop and validate a method for precisely determining endometrial cycle stage based on global gene expression. Our 'molecular staging model' reveals significant and remarkably synchronised daily changes in expression for over 3400 endometrial genes throughout the cycle, with the most dramatic changes occurring during the secretory phase. Our study significantly extends existing data on the endometrial transcriptome, and for the first time enables identification of differentially expressed endometrial genes with increasing age and different ethnicities. It also allows reinterpretation of all endometrial RNA-seq and array data that has been published to date. Our molecular staging model will significantly advance understanding of endometrial-related disorders that affect nearly all women at some stage of their lives, such as heavy menstrual bleeding, endometriosis, adenomyosis, and recurrent implantation failure.

Defining Usual Oral Temperature Ranges in Outpatients Using an Unsupervised Learning Algorithm

Importance

Although oral temperature is commonly assessed in medical examinations, the range of usual or "normal" temperature is poorly defined.

Objective

To determine normal oral temperature ranges by age, sex, height, weight, and time of day.

Design, Setting, and Participants

This cross-sectional study used clinical visit information from the divisions of Internal Medicine and Family Medicine in a single large medical care system. All adult outpatient encounters that included temperature measurements from April 28, 2008, through June 4, 2017, were eligible for inclusion. The LIMIT (Laboratory Information Mining for Individualized Thresholds) filtering algorithm was applied to iteratively remove encounters with primary diagnoses overrepresented in the tails of the temperature distribution, leaving only those diagnoses unrelated to temperature. Mixed-effects modeling was applied to the remaining temperature measurements to identify independent factors associated with normal oral temperature and to generate individualized normal temperature ranges. Data were analyzed from July 5, 2017, to June 23, 2023.

Exposures

Primary diagnoses and medications, age, sex, height, weight, time of day, and month, abstracted from each outpatient encounter.

Main Outcomes and Measures

Normal temperature ranges by age, sex, height, weight, and time of day.

Results

Of 618 306 patient encounters, 35.92% were removed by LIMIT because they included diagnoses or medications that fell disproportionately in the tails of the temperature distribution. The encounters removed due to overrepresentation in the upper tail were primarily linked to infectious diseases (76.81% of all removed encounters); type 2 diabetes was the only diagnosis removed for overrepresentation in the lower tail (15.71% of all removed encounters). The 396 195 encounters included in the analysis set consisted of 126 705 patients (57.35% women; mean [SD] age, 52.7 [15.9] years). Prior to running LIMIT, the mean (SD) overall oral temperature was 36.71 °C (0.43 °C); following LIMIT, the mean (SD) temperature was 36.64 °C (0.35 °C). Using mixed-effects modeling, age, sex, height, weight, and time of day accounted for 6.86% (overall) and up to 25.52% (per patient) of the observed variability in temperature. Mean normal oral temperature did not reach 37 °C for any subgroup; the upper 99th percentile ranged from 36.81 °C (a tall man with underweight aged 80 years at 8:00 am) to 37.88 °C (a short woman with obesity aged 20 years at 2:00 pm).

Conclusions and Relevance

The findings of this cross-sectional study suggest that normal oral temperature varies in an expected manner based on sex, age, height, weight, and time of day, allowing individualized normal temperature ranges to be established. The clinical significance of a value outside of the usual range is an area for future study.

Using Hormone Data and Age to Pinpoint Cycle Day within the Menstrual Cycle

Background and Objectives: Menstrual cycle tracking is essential for reproductive health and overall well-being. However, there is still an over-reliance on estimations that standard cycles are 28 days long, divided evenly between the follicular and luteal phases. Due to the variability of cycle length and cycle phase lengths, common methods of identifying where an individual is in their cycle are often inaccurate. This study used daily hormone monitoring obtained through a remote hormone-monitoring platform to evaluate hormone levels across a menstrual cycle to identify nuances in the follicular and luteal phases in individuals of different age groups. Materials and Methods: This study used a remote fertility testing system that quantitatively tracks luteinizing hormone (LH) and pregnanediol-3-glucuronide (PdG) through urine tests read by an AI-powered smartphone app. The study analyzed cycle data from 1233 users with a total of 4123 evaluated cycles. Daily levels for LH and PdG were monitored across multiple cycles. Results: This study determined that calculated cycle lengths tended to be shorter than user-reported cycle lengths. Significant differences were observed in cycle phase lengths between age groups, indicating that follicular phase length declines with age while luteal phase length increases. Finally, the study found that if an individual's age, first cycle day, and current hormone levels are known, population-level hormone data can be used to pinpoint which cycle phase and cycle day they are in with 95% confidence. Conclusions: At-home hormone monitoring technologies can allow patients and clinicians to track their cycles with greater precision than when relying on textbook estimations. The study's findings have implications for fertility planning, clinical management, and general health monitoring. Prior to this study, no standard existed for pinpointing where a person was in their cycle through only one measure of LH and PdG. These findings have the potential to fill significant gaps within reproductive healthcare and beyond.

Climate change and pregnancy complications: From hormones to the immune response

Pregnant women are highly vulnerable to adverse environments. Accumulating evidence highlights that increasing temperatures associated with the ongoing climate change pose a threat to successful reproduction. Heat stress caused by an increased ambient temperature can result in adverse pregnancy outcomes, e.g., preterm birth, stillbirth and low fetal weight. The pathomechanisms through which heat stress interferes with pregnancy maintenance still remain vague, but emerging evidence underscores that the endocrine system is severely affected. It is well known that the endocrine system pivotally contributes to the physiological progression of pregnancy. We review – sometimes speculate - how heat stress can offset hormonal dysregulations and subsequently derail other systems which interact with hormones, such as the immune response. This may account for the heat-stress related threat to successful pregnancy progression, fetal development and long-term children’s health.

Distribution of the follicular and luteal phase lengths and their age-dependent changes in Japanese women: A large population study

Purpose

The current definition of menstrual cycle length in a Japanese woman is different from those of WHO definition, and the original data are outdated. We aimed to calculate the distribution of follicular and luteal phases length in modern Japanese women with various menstrual cycles.

Methods

This study determined the lengths of the follicular and luteal phases of Japanese women using basal body temperature data collected via a smartphone application from 2015 to 2019, and the data were analyzed using the Sensiplan method. Over 9 million temperature readings from more than 80 000 participants were analyzed.

Results

The mean duration of the low-temperature (follicular) phase averaged 17.1 days and was shorter among participants aged 40-49 years. The mean duration of the high-temperature (luteal) phase was 11.8 days. The variance and maximum-minimum difference of the length of the low temperature period were significant in women under 35 years old than women aged more than 35 years.

Conclusions

The shortening of the follicular phase in women aged 40-49 years implied a relationship with the rapid decline of ovarian reserve in these women, and the age 35 years old was turning point of ovulatory function.

Tracking of menstrual cycles and prediction of the fertile window via measurements of basal body temperature and heart rate as well as machine-learning algorithms

BACKGROUND

Fertility awareness and menses prediction are important for improving fecundability and health management. Previous studies have used physiological parameters, such as basal body temperature (BBT) and heart rate (HR), to predict the fertile window and menses. However, their accuracy is far from satisfactory. Additionally, few researchers have examined irregular menstruators. Thus, we aimed to develop fertile window and menstruation prediction algorithms for both regular and irregular menstruators.

METHODS

This was a prospective observational cohort study conducted at the International Peace Maternity and Child Health Hospital in Shanghai, China. Participants were recruited from August 2020 to November 2020 and followed up for at least four menstrual cycles. Participants used an ear thermometer to assess BBT and wore the Huawei Band 5 to record HR. Ovarian ultrasound and serum hormone levels were used to determine the ovulation day. Menstruation was self-reported by women. We used linear mixed models to assess changes in physiological parameters and developed probability function estimation models to predict the fertile window and menses with machine learning.

RESULTS

We included data from 305 and 77 qualified cycles with confirmed ovulations from 89 regular menstruators and 25 irregular menstruators, respectively. For regular menstruators, BBT and HR were significantly higher during fertile phase than follicular phase and peaked in the luteal phase (all P < 0.001). The physiological parameters of irregular menstruators followed a similar trend. Based on BBT and HR, we developed algorithms that predicted the fertile window with an accuracy of 87.46%, sensitivity of 69.30%, specificity of 92.00%, and AUC of 0.8993 and menses with an accuracy of 89.60%, sensitivity of 70.70%, and specificity of 94.30%, and AUC of 0.7849 among regular menstruators. For irregular menstruators, the accuracy, sensitivity, specificity and AUC were 72.51%, 21.00%, 82.90%, and 0.5808 respectively, for fertile window prediction and 75.90%, 36.30%, 84.40%, and 0.6759 for menses prediction.

CONCLUSIONS

By combining BBT and HR recorded by the Huawei Band 5, our algorithms achieved relatively ideal performance for predicting the fertile window and menses among regular menstruators. For irregular menstruators, the algorithms showed potential feasibility but still need further investigation.

TRIAL REGISTRATION

ChiCTR2000036556. Registered 24 August 2020.

Cognitive function evaluation in premenstrual syndrome during the follicular and luteal phases using near-infrared spectroscopy

Background

Many adult females experience periodic mental and physical symptoms associated with premenstrual syndrome (PMS). Diagnosis of PMS is generally based on self-reported symptoms over several menstrual cycles, but there are concerns about its accuracy and duration. It is well known that decreased cognitive function is one of the symptoms of PMS. Near-infrared spectroscopy (NIRS) is one of the methods for imaging brain activity, similar to magnetic resonance imaging (MRI), electroencephalography (EEG), and positron emission tomography (PET). NIRS has been used to assess cognitive function decline demonstrated by decline in brain activity. However, to the best of our knowledge, there have been no report characterizing brain activity pattern in females with PMS during the luteal and follicular phases separately.

Objective

We aimed to characterize the cognitive function of females with PMS during the follicular and luteal phases using NIRS.

Methods

The level of brain activity in the prefrontal cortex was detected with NIRS while PMS women were performing cognitive tasks. NIRS detected brain activity by measuring the oxy-hemoglobin and deoxy-hemoglobin levels. Participants were females between the ages of 20 and 25 with PMS (n = 11) and without PMS (n = 11). During the participants’ follicular and luteal phases, the participants were asked to perform the cognitive task; an N-back task (0-, 1-, and 2-back tasks), which is widely used for assessing cognitive function. We also calculated the oxyhemoglobin integral value during the N-back task using the NIRS signal; this value represented the total amount of change in cerebral oxyhemoglobin and the brain activation level.

Results

The correct response rate on the 2-back task was significantly lower during both the follicular and luteal phases in females with PMS compared to that in females without PMS (P = 0.01; P = 0.02, during the follicular and luteal phases, respectively). During the luteal phase, brain activation was significantly lower in participants with PMS than in that in females without PMS (P = 0.04). In addition, during the luteal phase, the participants with PMS also had higher negative mood than those without PMS.

Conclusion

The cognitive decline during the luteal phase in participants with PMS was detected by NIRS with significant differences from participants without PMS. The difference was observed only during the luteal phase, not in the follicular phase and were related to the increase in negative mood. These results may provide an objective method for diagnosing PMS based on brain activity. We believe that the use of instruments (e.g., NIRS, MRI, EEG … etc.) to detect cognitive function decline will lead to rapid and reliable diagnosis of PMS and premenstrual dysphoric disorder.

Impact of the Hormonal Status in Women on Intraoperative Hypothermia during Laparoscopic Gynecologic Surgery when Considering the Fresh Gas Flow Rate: A Retrospective Study

Previous studies reported the impact of intrinsic and extrinsic factors on intraoperative hypothermia. However, no clinical study to date has considered the effects of both the phase of the menstrual cycle (an intrinsic factor) and the fresh gas flow rate (FGF) during anesthesia (an extrinsic factor) on the core body temperature and intraoperative hypothermia. This study is aimed at investigatig the effect of the menstrual cycle phase on intraoperative hypothermia when considering the FGF in patients who underwent laparoscopic gynecologic surgery. This study included 667 women aged 19-65 years with menstruation cycles and menopause. The patients were divided into the follicular, luteal, and menopause groups. The primary outcome was the correlations of hormonal status with intraoperative hypothermia. Secondary outcomes included the incidence of intraoperative hypothermia, time to onset of hypothermia, incidence of shivering after anesthesia, and frequency of antishivering drug use in the three groups and risk factors for hypothermia. Overall, the hypothermia incidence was the lowest and the time to onset of hypothermia was the longest in the luteal phase group. At a high FGF, the incidence of hypothermia in the luteal phase group was lower than that in the other two groups (P < 0.05). At a low FGF, the time to onset of hypothermia in the luteal phase group was longer than that in the other two groups (P < 0.05). The female hormonal status had weak positive correlations with hypothermia at low and high FGF rates. A high FGF in univariate and multivariate analyses, follicular phase and menopause in multivariate analysis, and estradiol and progesterone levels in univariate analysis were risk factors for hypothermia. When considering the FGF, the luteal phase is associated with better outcomes concerning intraoperative hypothermia.

The global pandemic and changes in women's reproductive health: an observational study

OBJECTIVE

The COVID-19 global pandemic has led to the death of millions around the world and impacted the overall health of many people. In this article we aim to compare reproductive health indicators in the first 6 months of 2020 to the prior year, as well as explore stress and quality of life during this time.

METHODS

This retrospective observational study examined the menstrual cycles of 1159 women who were using a fertility tracking device to record their menstrual cycle and BBT data. We utilised a supplemental mobile application to administer a supplemental survey to collect data on stress and quality of life. Descriptive analyses were conducted with t-tests for two-group comparisons.

RESULTS

Study participants from 15 countries contributed to a total of 13,194 cycles. 23.1% (268/1159) responded to the survey focussed on assessing psychosocial distress. 44.4% (119/268) of the study participants reported that they had noticed a change in their menstrual cycle, temperature curve, or menstruation in the past 12 months. Cycle analysis found the average cycle length and pre-ovulation phase length was longer in the first 6 months of 2019, while the average days of menstruation was slightly longer in 2020.

DISCUSSION

Our findings indicate that menstrual cycle indicators changed only slightly in the first 6 months of 2020 but were still statistically significant. We were also able to understand that these study participants had some level of awareness of changes to their menstrual health.

Intracellular thermometry uncovers spontaneous thermogenesis and associated thermal signaling

Conventional thermal biology has elucidated the physiological function of temperature homeostasis through spontaneous thermogenesis and responses to variations in environmental temperature in organisms. In addition to research on individual physiological phenomena, the molecular mechanisms of fever and physiological events such as temperature-dependent sex determination have been intensively addressed. Thermosensitive biomacromolecules such as heat shock proteins (HSPs) and transient receptor potential (TRP) channels were systematically identified, and their sophisticated functions were clarified. Complementarily, recent progress in intracellular thermometry has opened new research fields in thermal biology. High-resolution intracellular temperature mapping has uncovered thermogenic organelles, and the thermogenic functions of brown adipocytes were ascertained by the combination of intracellular thermometry and classic molecular biology. In addition, intracellular thermometry has introduced a new concept, "thermal signaling", in which temperature variation within biological cells acts as a signal in a cascade of intriguing biological events.

Menstrual cycle length and modern living: a review

PURPOSE OF REVIEW

The aim of this review is to evaluate biological, life history, environmental, and lifestyle factors and exposures that cause variability in menstrual cycle length (MCL).

RECENT FINDINGS

Recent literature has detailed a number of factors that influence MCL, with particular emphasis placed on novel environmental exposures, such as air pollution and endocrine disrupting chemicals.

SUMMARY

MCL varies widely in response to intrinsic and extrinsic inputs and is a useful predictor of reproductive health and fecundability.

VIDEO ABSTRACT

http://links.lww.com/COE/A28.

Smartphone application improves fertility treatment-related literacy in a large-scale virtual randomized controlled trial in Japan

People of reproductive age have unmet needs related to deficiencies in fertility literacy. Here, we aimed to investigate whether providing fertility-related information via a smartphone application could improve fertility treatment-related literacy in participants. We performed a randomized control-group pretest posttest study and recruited participants between June 18 and 25, 2020. Participants’ fertility treatment-related literacy was assessed with a pretest that comprised of 28 questions and participants were allocated with stratified randomization to either intervention group or control group. The intervention comprised a one-week smartphone application-based provision of information on fertility-related information and the control group received general information about women’s healthcare. Effectiveness of intervention was assessed using a posttest. A total of 4137 participants were administered the questionnaire and pretest, among which 3765 participants (91.0 %) responded and were randomly allocated into either the intervention group (N = 1883) or the control group (N = 1882). A significantly higher posttest mean score was observed for the intervention group compared to the control group (P = 0.0017). We also observed that posttest scores were significantly improved compared to pretest scores in both the intervention and control group (P < 0.001). When examining by specific test question, the proportion answering correctly increased at posttest compared to pretest for both intervention and control groups (P < 0.001). Furthermore, the intervention group showed a greater mean difference between posttest and pretest scores than the control group (P < 0.001). In conclusion, educational intervention using a smartphone application contributed to enhancing fertility treatment-related literacy.

Seasonal reproduction and gonadal function: A focus on humans starting from animal studies

Photoperiod impacts reproduction in many species of mammals. Mating occurs at specific seasons to achieve reproductive advantages, such as optimization of offspring survival. Light is the main regulator of these changes during the photoperiod. Seasonally breeding mammals detect and transduce light signals through extraocular photoreceptor, regulating downstream melatonin-dependent peripheral circadian events. In rodents, hormonal reduction and gonadal atrophy occur quickly, and consensually with short-day periods. It remains unclear whether photoperiod influences human reproduction. Seasonal fluctuations of sex hormones have been described in humans, although they seem to not imply adaptative seasonal pattern in human gonads. This review discusses current knowledge about seasonal changes in the gonadal function of vertebrates, including humans. The photoperiod-dependent regulation of hypothalamic-pituitary-gonadal axis, as well as morphological and functional changes of the gonads are evaluated herein. Endocrine and morphological variations of reproductive functions, in response to photoperiod, are of interest as they may reflect the nature of past population selection for adaptative mechanisms that occurred during evolution.