The correlation between menstrual characteristics and fertility in women of reproductive age: a systematic review and meta-analysis.

IMPORTANCE: Menstruation serves as an indicator of women's reproductive well-being and plays a pivotal role in their fertility; nevertheless, there remains an ongoing debate regarding the epidemiological evidence linking menstrual characteristics as well as fertility. OBJECTIVE: To explore the correlation between menstrual characteristics and fertility in women of reproductive age. DATA SOURCES: A comprehensive literature search was conducted using PubMed, Embase, Web of Science, and Cochrane libraries to identify research articles published up until February 9, 2024. STUDY SELECTION AND SYNTHESIS: We included all studies in which the relationship between menstrual characteristics and pregnancy rates among women of reproductive age was investigated. We excluded studies involving the administration of oral contraceptives, the application of assisted reproductive technologies, and individuals with a documented history of infertility or partners with a known history of infertility. MAIN OUTCOME MEASURE(S): Clinical pregnancy and miscarriage. RESULT(S): This meta-analysis was composed of nine studies involving a total of 399,966 women, and the evidential quality derived from these studies was deemed to be high with a low risk of bias. Compared with a normal menstrual cycle length (25-32 days), the impact of a short (<25 days) or long (>32 days) menstrual cycle on a woman's pregnancy was relatively insignificant ([odds ratio {OR}, 0.81; 95% confidence interval {CI}, 0.65-1.01; I2, 68%]; [OR, 0.89; 95% CI, 0.75-1.06; I2, 60%], respectively); however, a change in cycle length may increase the risk of miscarriage ([relative risk, 1.87; 95% CI, 1.11-3.15; I2, 0]; [relative risk, 1.66; 95% CI, 1.07, 2.57; I2, 43%], respectively). In comparison to women experiencing menarche at a typical age (12-14 years), those with a late age at menarche (>14 years) exhibited a decreased likelihood of pregnancy (OR, 0.92; 95% CI, 0.91-0.93; I2, 0%); and compared with women experiencing a normal duration of menstrual bleeding (4-7 days), those with a short duration of menstrual bleeding (<4 days) exhibited reduced fertility potential (OR, 0.86; 95% CI, 0.84-0.88; I2, 29%). CONCLUSION(S): Short and long menstrual cycle lengths may elevate women's susceptibility to spontaneous abortion, whereas late age at menarche as well as short duration of menstrual bleeding appear to be linked to diminished fertility among women of reproductive age. CLINICAL TRIAL REGISTRATION: PROSPERO CRD42023487458 (9 December 2023).

New AMH cutoff values for warning of decreased ovarian response based on MCL characteristics in young women: a retrospective study using a propensity score-matching analysis.

BACKGROUND: Menstrual cycle length (MCL) and ovarian response varies widely among women of childbearing age. They are provided with anti-Mu¨llerian hormone (AMH) cutoffs for "normal" and "weakened" ovarian responses, which give an early warning of the onset of decreased ovarian response. METHODS: This was a retrospective study in women aged 21 to 35 years with MCLs of 21-35 days receiving in vitro fertilization (IVF) treatment at Center for Reproductive Medicine from October 2018 to October 2021. Intergroup variables were balanced using propensity score matching based on age and BMI, and each case patient (patients with MCLs of 21-25 days) was matched with three control patients (patients with MCLs of 26-35 days). A receiver operating characteristic curve was used to calculate the AMH cutoff values. RESULTS: We included 135 patients with MCLs of 21-25 days and 405 matched control patients with MCLs of 26-35 days who received IVF treatment. The case group had significantly fewer retrieved oocytes, lower AMH values and higher initial and total Gonadotropin (Gn) levels during controlled ovarian hyperstimulation than the control group. The ovarian response began to decrease when AMH was < 3.5 ng/ml in the case group and < 2.7 ng/ml in the control group. CONCLUSION: In young women with MCLs of 21-35 days, short MCL was negatively correlated with AMH values and the number of oocytes retrieved. In patients with MCLs of 21-25 days and 26-35 days, the AMH cutoff values corresponding to the onset of decreased ovarian response were 3.5 ng/ml and 2.7 ng/ml, respectively.

A prospective study of the association between SARS-CoV-2 infection and COVID-19 vaccination with changes in usual menstrual cycle characteristics.

BACKGROUND: Despite anecdotal reports, the impacts of SARS-CoV-2 infection or COVID-19 vaccination on menstrual health have not been systemically investigated. OBJECTIVE: This study aimed to examine the associations of SARS-CoV-2 infection and COVID-19 vaccination with menstrual cycle characteristics. STUDY DESIGN: This study prospectively observed 3858 premenopausal women in the Nurses' Health Study 3 living in the United States or Canada who received biannual follow-up questionnaires between January 2011 and December 2021 and completed additional monthly and quarterly surveys related to the COVID-19 pandemic between April 2020 and November 2021. History of positive SARS-CoV-2 test, COVID-19 vaccination status, and vaccine type were self-reported in surveys conducted in 2020 and 2021. Current menstrual cycle length and regularity "before COVID-19" were reported at baseline between 2011 and 2016, and current menstrual cycle length and regularity "after COVID-19" were reported in late 2021. Pre- to post-COVID change in menstrual cycle length and regularity was calculated between reports. Logistic or multinomial logistic regression models were used to assess the associations between SARS-CoV-2 infection and COVID-19 vaccination and change in menstrual cycle characteristics. RESULTS: The median age at baseline and the median age at end of follow-up were 33 years (range, 21-51) and 42 years (range, 27-56), respectively, with a median follow-up time of 9.2 years. This study documented 421 SARS-CoV-2 infections (10.9%) and 3527 vaccinations (91.4%) during follow-up. Vaccinated women had a higher risk of increased cycle length than unvaccinated women (odds ratio, 1.48; 95% confidence interval, 1.00-2.19), after adjusting for sociodemographic and behavioral factors. These associations were similar after in addition accounting for pandemic-related stress. COVID-19 vaccination was only associated with change to longer cycles in the first 6 months after vaccination (0-6 months: odds ratio, 1.67 [95% confidence interval, 1.05-2.64]; 7-9 months: odds ratio, 1.43 [95% confidence interval, 0.96-2.14]; >9 months: odds ratio, 1.41 [95% confidence interval, 0.91-2.18]) and among women whose cycles were short, long, or irregular before vaccination (odds ratio, 2.82 [95% confidence interval, 1.51-5.27]; odds ratio, 1.10 [95% confidence interval, 0.68-1.77] for women with normal length, regular cycles before vaccination). Messenger RNA and adenovirus-vectored vaccines were both associated with this change. SARS-CoV-2 infection was not associated with changes in usual menstrual cycle characteristics. CONCLUSION: COVID-19 vaccination may be associated with short-term changes in usual menstrual cycle length, particularly among women whose cycles were short, long, or irregular before vaccination. The results underscored the importance of monitoring menstrual health in vaccine clinical trials. Future work should examine the potential biological mechanisms.

A Model for Predicting Polycystic Ovary Syndrome Using Serum AMH, Menstrual Cycle Length, Body Mass Index and Serum Androstenedione in Chinese Reproductive Aged Population: A Retrospective Cohort Study.

Background: A clinical diagnosis of polycystic ovary syndrome (PCOS) can be tedious with many different required tests and examinations. Furthermore, women with PCOS have increased risks for several metabolic complications, which need long-term health management. Therefore, we attempted to establish an easily applicable model to identify such women at an early stage. Objective: To develop an easy-to-use tool for screening PCOS based on medical records from a large assisted reproductive technology (ART) center in China. Materials and Methods: A retrospective observational cohort from Peking University Third Hospital was used in the study. Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 10-fold cross-validation was applied to construct the model. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity values were used to evaluate and compare the models. Design Setting and Participants: This retrospective cohort study included 21,219 ovarian stimulation cycle records from January to December 2019 in Peking University Third Hospital. Main Outcomes and Measures: The main outcome was whether there was a clinical diagnosis of PCOS. The independent variables included were age, body mass index (BMI), upper limit of menstrual cycle length (UML), basal serum levels of anti-Müllerian hormone (AMH), testosterone androstenedione, antral follicle counts et al. Results: We have established a new mathematical model for diagnosing PCOS using serum AMH and androstenedione levels, UML, and BMI, with AUC values of 0.855 (0.838-0.870), 0.848 (0.791-0.891), 0.846 (0.812-0.875) in the training, validation, and testing sets, respectively. The contribution of each predictor to this model were: AMH 41.2%; UML 35.2%; BMI 4.3%; and androstenedione 3.7%. The top 10 groups of women most predicted to develop PCOS were demonstrated. An online tool (http://121.43.113.123:8888/) has been developed to assist Chinese ART clinics. Conclusions: The models and online tool we established here might be helpful for screening and identifying women with undiagnosed PCOS in Asian populations and could assist in the long-term management of related metabolic disorders.

Menstrual cycle length and adverse pregnancy outcomes among women in Project Viva.

BACKGROUND: Retrospective studies suggest that menstrual cycle length may be a risk marker of adverse pregnancy outcomes, but this evidence is susceptible to recall bias. OBJECTIVE: To evaluate the prospective association between menstrual cycle length and the risk of adverse pregnancy outcomes. METHODS: Secondary analysis of 2046 women enrolled in Project Viva at ~10 weeks of gestation and followed through delivery. The exposure was menstrual cycle length. The outcomes included gestational glucose tolerance (gestational diabetes/impaired glucose tolerance [GDM/IGT] and isolated hyperglycaemia), hypertensive disorders of pregnancy (gestational hypertension/preeclampsia), gestational weight gain, birthweight-for-gestational age z-scores (BWZ) categorised in tertiles, preterm birth and birth outcome (live birth and pregnancy loss). We used modified Poisson and multinomial logistic regression adjusted for age, race/ethnicity, parity, age at menarche and pre-pregnancy body mass index. RESULTS: Mean (SD) age at enrolment was 32.1 (4.9) years. Most women (74.3%) had a cycle length of 26-34 days (reference group), 16.2% reported short cycles (≤25 days), and 9.5% reported long/irregular cycles (≥35 days/too irregular to estimate). Compared with the reference group, women with short cycles had lower odds of GDM/IGT (odds ratio [OR] 0.50, 95% confidence interval [CI] 0.28, 0.89), whereas women with long/irregular cycles had higher odds (OR 1.72, 95% CI 1.04, 2.83). Additionally, women with short cycles had higher odds of having a newborn in the lowest tertile of BWZ (OR 1.45, 95% CI 1.06, 1.98). There was a U-shaped relation between cycle length and preterm birth with both short (relative risk [RR] 1.49, 95% CI 0.98, 2.27) and long/irregular (RR 2.04, 95% CI 1.30, 3.20) cycles, associated with a higher risk. CONCLUSIONS: Variation in menstrual cycle length may be a risk marker of GDM/IGT, lower birth size and preterm birth and flag women who may benefit from targeted monitoring and care before and during pregnancy.

Ovarian Reserve Biomarkers and Menstrual Cycle Length in a Prospective Cohort Study.

CONTEXT: While age-related changes in menstrual cycle length are well known, it is unclear whether anti-Müllerian (AMH) or other ovarian reserve biomarkers have a direct association with cycle length. OBJECTIVE: To determine the association between biomarkers of ovarian reserve and menstrual cycle length. METHODS: Secondary analysis using data from time to conceive (TTC), a prospective time to pregnancy cohort study. The age-independent association between cycle length and biomarkers of ovarian reserve was analyzed using linear mixed and marginal models. Study participants were TTC-enrolled women aged 30-44 years with no history of infertility who were attempting to conceive for <3 months were enrolled. Serum AMH, follicle-stimulating hormone, and inhibin B levels were measured on cycle day 2, 3, or 4. Participants recorded daily menstrual cycle data for ≤4 months. The primary outcome was menstrual cycle length; follicular and luteal phase lengths were secondary outcomes. RESULTS: Multivariable analysis included 1880 cycles from 632 women. Compared with AMH levels of 1.6 to 3.4 ng/mL, women with AMH <1.6 ng/mL had cycles and follicular phases that were 0.98 (95% CI -1.46, -0.50) and 1.58 days shorter (95% CI -2.53, -0.63), respectively, while women with AMH >8 ng/mL had cycles that were 2.15 days longer (95% CI 1.46, 2.83), follicular phases that were 2 days longer (95% CI 0.77, 3.24), and luteal phases that were 1.80 days longer (95% CI 0.71, 2.88). CONCLUSION: Increasing AMH levels are associated with longer menstrual cycles due to both a lengthening of the follicular and the luteal phase independent of age.

Low-dose aspirin in reproductive health: effects on menstrual cycle characteristics.

OBJECTIVE: To estimate the effect of daily 81 mg low-dose aspirin (LDA) on menstrual cycle length and hormone profiles. DESIGN: Secondary analysis of a trial evaluating the effect of daily LDA or placebo on live birth among women with one or two previous pregnancy losses. SETTING: University medical centers. PATIENT(S): A total of 915 regularly menstruating women who had at least one menstrual cycle (3,190 total cycles) in which pregnancy did not occur. INTERVENTION(S): Randomized allocation to LDA versus placebo. MAIN OUTCOME MEASURE(S): Menstrual cycle length and follicular and luteal phases were measured. Urinary pregnanediol glucuronide, follicle-stimulating hormone, luteinizing hormone, and estrone-3-glucuronide were assessed up to six times during the first two cycles. Generalized estimating equations estimated relative risk of short (<25th percentile: <27 days) and long (>75th percentile: ≥32 days) versus normal cycle length. Linear mixed models estimated mean hormone level differences with weights used to account for multiple cycles contributed per participant. RESULT(S): There were no significant differences in total menstrual cycle, follicular phase, or luteal phase length between LDA and placebo groups. LDA posed no greater risk of having a short versus normal-length or long versus normal-length follicular phase, or having a short versus normal-length or long versus normal-length luteal phase. There were no significant differences in hormone levels across the menstrual cycle between the LDA and placebo groups. CONCLUSION(S): Daily LDA use did not result in any changes to menstrual cycle, follicular phase, or luteal phase length or hormone levels across the menstrual cycle compared with placebo. CLINICAL TRIAL REGISTRATION NUMBER: NCT00467363.

Does an association exist between menstrual cycle length within the normal range and ovarian reserve biomarkers during the reproductive years? A systematic review and meta-analysis.

BACKGROUND: Regular menstrual cycling during the reproductive years is an indicator of spontaneous ovulation but sometimes falsely perceived as an indicator of preserved fertility. In contrast, menstrual cycle shortening, a physiologic occurrence preceding the menopausal transition, is not usually perceived as an indicator of decreased ovarian reserve in the general population. OBJECTIVE AND RATIONALE: The individual decrease in menstrual cycle length (MCL) might represent a sensitive biomarker of diminishing ovarian reserve. The aim of this systematic review and meta-analysis is to examine the possible association between MCL in regularly cycling women (21-35 days) and ovarian reserve tests (ORT), fecundability in natural cycles and IVF outcomes. SEARCH METHODS: An electronic database search employing PubMed, Web of Science, Trip, EBSCO, ClinicalTrials.gov and the Cochrane library was performed to identify research articles, only on human, published between January 1978 and August 2019. Search terms were pregnancy OR fertility OR fecundity OR fecundability, anti-Müllerian hormone OR AMH OR antral follicle count OR AFC OR ovarian reserve OR ovarian reserve test, in vitro fertilization OR ART OR assisted reproductive therapy OR assisted reproductive treatment OR assisted reproductive technology OR IVF OR ICSI, menstrual cycle length OR menstrual cycle characteristics. We combined these terms to complete the search. All prospective and retrospective studies exploring an association between MCL and proxies of ovarian reserve were included. The exclusions included studies of PCOS, ovarian failure, oral contraception treatment, prior chemotherapy and/or radiotherapy or ovarian surgery. The Newcastle-Ottawa scale was used to assess the quality of studies that were eligible for meta-analysis. OUTCOMES: Eleven studies were eligible for meta-analysis, including 12 031 women. The included studies had a low risk of bias. Short MCL (21-27 days) was associated with lower ORT values as compared to normal (28-31 days), long (32-35 days) and all other (28-35 days) MCL sets. The estimated weighted mean difference (WMD) of AMH level was -1.3 ng/mL (95% CI: -1.75 to -0.86, P < 0.001) between the short and normal MCL sets. The estimated WMD of AFC values was -5.17 (95% CI: -5.96 to -4.37, P < 0.001) between the short and normal MCL sets. The weighted overall odds ratio (OR) of fecundability in natural cycles between women with short versus normal MCL sets was statistically significant (overall OR 0.81; 95% CI 0.72-0.91, P < 0.001). In the IVF setting, fewer oocytes were retrieved in short MCL in comparison to normal, long and all other MCL sets, with an estimated WMD of -1.8 oocytes (95% CI: -2.5 to -1.1, P < 0.001) in the short versus normal MCL sets. The weighted overall OR of clinical pregnancy rate between women with short versus all other MCL sets was statistically significant (overall OR 0.76; 95% CI: 0.60 to 0.96, P = 0.02). Low levels of heterogeneity were found in most meta-analyses of MCL and qualitative ovarian reserve biomarkers, while heterogeneity was high in meta-analyses performed for quantitative measures. WIDER IMPLICATIONS: MCL in regularly cycling women is closely related to ovarian reserve biomarkers during the reproductive years. A short MCL, as compared to normal, is significantly associated with lower ORT values, reduced fecundability and inferior IVF outcomes, independent of age. The results imply that short MCL may be a sign of ovarian aging, combining the quantitative and qualitative facets of ovarian reserve. Educational efforts ought to be designed to guide women with short MCL at a young age, who desire children in the future, to seek professional counselling.

Real-life insights on menstrual cycles and ovulation using big data.

STUDY QUESTION: What variations underlie the menstrual cycle length and ovulation day of women trying to conceive? SUMMARY ANSWER: Big data from a connected ovulation test revealed the extent of variation in menstrual cycle length and ovulation day in women trying to conceive. WHAT IS KNOWN ALREADY: Timing intercourse to coincide with the fertile period of a woman maximises the chances of conception. The day of ovulation varies on an inter- and intra-individual level. STUDY DESIGN SIZE DURATION: A total of 32 595 women who had purchased a connected ovulation test system contributed 75 981 cycles for analysis. Day of ovulation was determined from the fertility test results. The connected home ovulation test system enables users to identify their fertile phase. The app benefits users by enabling them to understand their personal fertility information. During each menstrual cycle, users input their perceived cycle length into an accessory application, and data on hormone levels from the tests are uploaded to the application and stored in an anonymised cloud database. This study compared users' perceived cycle characteristics with actual cycle characteristics. The perceived and actual cycle length information was analysed to provide population ranges. PARTICIPANTS/MATERIALS SETTING METHODS: This study analysed data from the at-home use of a commercially available connected home ovulation test by women across the USA and UK. MAIN RESULTS AND THE ROLE OF CHANCE: Overall, 25.3% of users selected a 28-day cycle as their perceived cycle length; however, only 12.4% of users actually had a 28-day cycle. Most women (87%) had actual menstrual cycle lengths between 23 and 35 days, with a normal distribution centred on day 28, and over half of the users (52%) had cycles that varied by 5 days or more. There was a 10-day spread of observed ovulation days for a 28-day cycle, with the most common day of ovulation being Day 15. Similar variation was observed for all cycle lengths examined. For users who conducted a test on every day requested by the app, a luteinising hormone (LH) surge was detected in 97.9% of cycles. LIMITATIONS REASONS FOR CAUTION: Data were from a self-selected population of women who were prepared to purchase a commercially available product to aid conception and so may not fully represent the wider population. No corresponding demographic data were collected with the cycle information. WIDER IMPLICATIONS OF THE FINDINGS: Using big data has provided more personalised insights into women's fertility; this could enable women trying to conceive to better time intercourse, increasing the likelihood of conception. STUDY FUNDING/COMPETING INTERESTS: The study was funded by SPD Development Company Ltd (Bedford, UK), a fully owned subsidiary of SPD Swiss Precision Diagnostics GmbH (Geneva, Switzerland). I.S., B.G. and S.J. are employees of the SPD Development Company Ltd.

A self-excited threshold autoregressive state-space model for menstrual cycles: Forecasting menstruation and identifying within-cycle stages based on basal body temperature.

The menstrual cycle is divided into hypothermic and hyperthermic phases based on the periodic shift in the basal body temperature (BBT), reflecting events occurring in the ovary. In the present study, we proposed a state-space model that explicitly incorporates the biphasic nature of the menstrual cycle, in which the probability density distributions for the advancement of the menstrual phase and that for the BBT switch depending on a latent state variable. Our model derives the predictive distribution of the day of the next menstruation onset that is adaptively adjusted by accommodating new observations of the BBT sequentially. It also enables us to obtain conditional probabilities of the woman being in the early or late stages of the cycle, which can be used to identify the duration of hypothermic and hyperthermic phases, possibly as well as the day of ovulation. By applying the model to real BBT and menstruation data, we show that the proposed model can properly capture the biphasic characteristics of menstrual cycles, providing a good prediction of the menstruation onset in a wide range of age groups. The application of the proposed model to a large data set containing 25 622 cycles provided by 3533 women further highlighted the between-age differences in the population characteristics of menstrual cycles, suggesting its wide applicability.

Cardiovascular risk factors among women with self-reported infertility.

BACKGROUND: Amongst women with certain types of ovulatory disorder infertility, the studies are conflicting whether there is an increased risk of long-term cardiovascular disease risk. This paper evaluates the associations of several CVD risk factors among Framingham women with self-reported infertility. METHODS: Women who completed the Framingham Heart Study Third Generation and Omni Cohort 2 Exam 2 (2008-2011), and reported on past history of infertility and current cardiovascular disease status were included in this cross-sectional study. Directly measured CVD risk factors were: resting blood pressure, fasting lipid levels, fasting blood glucose, waist circumference, and body mass index (BMI). Multivariable models adjusted for age, smoking, physical activity, and cohort. Generalized estimating equations adjusted for family correlations. We performed sensitivity analyses to determine whether the association between infertility and CVD risk factors is modified by menopausal status and menstrual cycle length. RESULTS: Comparing women who self-reported infertility to those who did not, there was an average increase in BMI (ß = 1.03 kg/m2, 95% CI: 0.18, 1.89), waist circumference (ß = 3.08 in., 95% CI: 1.06, 5.09), triglycerides (ß = 4.47 mg/dl, 95% CI:-1.54, 10.49), and a decrease in HDL cholesterol (ß = -1.60 mg/dl, 95% CI: -3.76, 0.56). We estimated that infertile premenopausal women have an increased odds of obesity (BMI ≥ 30 kg/m2) (OR = 1.56, 95% CI: 1.11, 4.49) and diabetes (OR = 1.96, 95% CI: 0.86, 4.49). CONCLUSIONS: BMI and waist circumference were the most strongly correlated CVD risk factors amongst women reporting a history of infertility.

The forecasting of menstruation based on a state-space modeling of basal body temperature time series.

Women's basal body temperature (BBT) shows a periodic pattern that associates with menstrual cycle. Although this fact suggests a possibility that daily BBT time series can be useful for estimating the underlying phase state as well as for predicting the length of current menstrual cycle, little attention has been paid to model BBT time series. In this study, we propose a state-space model that involves the menstrual phase as a latent state variable to explain the daily fluctuation of BBT and the menstruation cycle length. Conditional distributions of the phase are obtained by using sequential Bayesian filtering techniques. A predictive distribution of the next menstruation day can be derived based on this conditional distribution and the model, leading to a novel statistical framework that provides a sequentially updated prediction for upcoming menstruation day. We applied this framework to a real data set of women's BBT and menstruation days and compared prediction accuracy of the proposed method with that of previous methods, showing that the proposed method generally provides a better prediction. Because BBT can be obtained with relatively small cost and effort, the proposed method can be useful for women's health management. Potential extensions of this framework as the basis of modeling and predicting events that are associated with the menstrual cycles are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The influence of age at menarche, menstrual cycle length and bleeding duration on time to pregnancy: a large prospective cohort study among rural Chinese women.

OBJECTIVE: To investigate the relations among age at menarche (AAM), menstrual cycle length, menstrual bleeding duration and time to pregnancy in a large cohort of rural Chinese women. DESIGN: A prospective cohort study. SETTING: Local family-planning service agencies and maternal/child care service centres. POPULATION: A total of 391 320 rural women of reproductive age who participated in the National Free Pre-pregnancy Checkups and were planning to conceive were enrolled. METHODS: Menstrual characteristics were collected via face-to-face interviews. The Cox proportional hazards model were used to estimate the fecundability ratios (FRs) and 95% confidence intervals for each measure relative to its reference category. MAIN OUTCOME MEASURES: Time to pregnancy. RESULTS: Women with an AAM later than 14 years of age were less likely become pregnant compared with women with AAM at 13-14 years of age (FR 0.93, 95% CI 0.92-0.94). Those with menstrual cycle lengths >29 days were less likely to come pregnant (FR 0.91, 95% CI 0.90-0.92) compared with the reference cycle length of 27-29 days. Women with bleeding durations of <4 (FR 0.88; 95% CI 0.86-0.91) or >5 days (FR 0.91; 95% CI 0.90-0.91) showed lower FRs compared with those reporting 4-5 days of bleeding. The associations were independent of maternal age, ethnicity, education level, occupation, tobacco use, alcohol use and body mass index. CONCLUSION: A later onset of menarche, longer menstrual cycle length, both shorter (<4 days) and longer (>5 days) bleeding duration were associated with a lower FR and longer time to pregnancy in rural Chinese women. TWEETABLE ABSTRACT: A later menarche, longer cycle, shorter or longer bleeding duration were associated with lower fecundity.

A joint modeling approach for multivariate survival data with random length.

In many biomedical studies that involve correlated data, an outcome is often repeatedly measured for each individual subject along with the number of these measurements, which is also treated as an observed outcome. This type of data has been referred as multivariate random length data by Barnhart and Sampson (1995). A common approach to handling such type of data is to jointly model the multiple measurements and the random length. In previous literature, a key assumption is the multivariate normality for the multiple measurements. Motivated by a reproductive study, we propose a new copula-based joint model which relaxes the normality assumption. Specifically, we adopt the Clayton-Oakes model for multiple measurements with flexible marginal distributions specified as semi-parametric transformation models. The random length is modeled via a generalized linear model. We develop an approximate EM algorithm to derive parameter estimators and standard errors of the estimators are obtained through bootstrapping procedures and the finite-sample performance of the proposed method is investigated using simulation studies. We apply our method to the Mount Sinai Study of Women Office Workers (MSSWOW), where women were prospectively followed for 1 year for studying fertility.

Influence of fixed orthodontic treatment on the menstrual cycle of adult females: A prospective longitudinal study.

OBJECTIVE: To investigate the influence of fixed orthodontic treatment on the menstrual cycle, including menstrual cycle length (MCL) and duration of menstrual bleeding (DMB), in adult female patients. MATERIALS AND METHODS: This was a prospective longitudinal study conducted in Chengdu, China. A total of 164 adult women with normal menstrual cycles were recruited in the study, with 79 patients undergoing orthodontic treatment and 85 serving as controls. Data of MCL, DMB, and accompanying symptoms were collected over six consecutive menstrual cycles in each participant. Student's t test, Chi-square test, Moses extreme reaction test, and repeated measures analysis of variance were used for statistical analysis. RESULTS: The MCL of the first menstrual cycle (T1) was significantly elongated by 2.1 ± 0.5 days compared with baseline (P  =  .003, 95% CI [-3.7, -0.5]). Variability of MCL of the orthodontic group at T1 was also significantly greater (range, 15-46 days) than that of the control group (range, 24-36 days) (P < .05). No significant difference in MCL was found in the subsequent five menstrual cycles (T2-T6) compared with baseline, and no significant differences in DMB or other accompanying symptoms were observed throughout the study. CONCLUSION: Fixed orthodontic treatment may influence the MCL of adult females in the first month after bonding, but showed no effect on DMB or subsequent MCL through the follow-ups.

Comparing four ovarian reserve markers--associations with ovarian response and live births after assisted reproduction.

INTRODUCTION: We compared the ability of four different ovarian reserve tests (ORTs) to predict live births per started in vitro fertilization-intracytoplasmic sperm injection (IVF-ICSI) cycle, and poor and excessive response to controlled ovarian hyperstimulation. MATERIAL AND METHODS: This was a cohort study in a private infertility center in collaboration with Uppsala University, comprising 1230 IVF-ICSI cycles in 892 consecutive women between April 2008 and June 2011. Anti-Müllerian hormone (AMH) levels, antral follicle counts (AFC), combinations of basal levels of follicle-stimulating hormone and luteinizing hormone, and menstrual cycle lengths were analyzed for correlation and treatment outcome prediction in age-adjusted statistical models. Stepwise multivariable generalized estimating equation analyses were carried out in a sub-group with complete data on all four ORTs (620 cycles in 443 women). Odds ratios and c-statistics were calculated in the largest available set of data for each significant variable. Primary outcomes were live birth rate per started cycle and poor and excessive ovarian response to controlled ovarian hyper-stimulation (defined by the ovarian sensitivity index). RESULTS: All ORTs correlated significantly with each other, with the strongest correlation between AFC and AMH (r = 0.71, p < 0.0001). Univariately, AMH and age equivalently predicted live birth (c-statistic 0.61), and together they provided a significantly better model (c-statistic 0.64). For prediction of poor and excessive response the best model included AMH, AFC and age (c-statistic 0.89). CONCLUSIONS: AMH improves the ability to estimate live birth rates after assisted reproduction compared with female age alone. AMH, AFC and age together constituted the best model for prediction of ovarian response.

Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length.

Prospective pregnancy studies are a valuable source of longitudinal data on menstrual cycle length. However, care is needed when making inferences of such renewal processes. For example, accounting for the sampling plan is necessary for unbiased estimation of the menstrual cycle length distribution for the study population. If couples can enroll when they learn of the study as opposed to waiting for the start of a new menstrual cycle, then due to length-bias, the enrollment cycle will be stochastically larger than the general run of cycles, a typical property of prevalent cohort studies. Furthermore, the probability of enrollment can depend on the length of time since a woman's last menstrual period (a backward recurrence time), resulting in selection effects. We focus on accounting for length-bias and selection effects in the likelihood for enrollment menstrual cycle length, using a recursive two-stage approach wherein we first estimate the probability of enrollment as a function of the backward recurrence time and then use it in a likelihood with sampling weights that account for length-bias and selection effects. To broaden the applicability of our methods, we augment our model to incorporate a couple-specific random effect and time-independent covariate. A simulation study quantifies performance for two scenarios of enrollment probability when proper account is taken of sampling plan features. In addition, we estimate the probability of enrollment and the distribution of menstrual cycle length for the study population of the Longitudinal Investigation of Fertility and the Environment Study.

Predictive factors of successful pregnancy after assisted reproductive technology in women aged 40 years and older.

PURPOSE: This study aimed to investigate the factors that predict successful pregnancy (live birth) in assisted reproductive technology (ART) for infertile women aged 40 and older. METHODS: Patients who underwent first ART treatments at the age of 40 and older at our institution were enrolled. Several factors which can be evaluated before the first treatments were retrospectively compared among those patients who did and did not achieve live birth. RESULTS: Nineteen of 119 patients delivered healthy babies. There was no significant difference of live-birth rate among age groups of 40, 41 and 42. No women who underwent the first treatment at age 43 or older achieved live birth. In the successful group, significantly more women held FSH levels under 12 mIU/ml and had regular menstrual cycles (26-32 days) than unsuccessful women of the same age group. In addition, significantly fewer women in the successful group had prior ovarian surgery. CONCLUSIONS: Our results show that low FSH levels, regular menstrual cycles and absence of prior ovarian surgery were related to high live-birth rates and they are good prognostic factors in patients between 40 and 42 years of age. On the other hand, none of these parameters were correlated with success in women aged 43 and older.