Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length.
ABSTRACT: 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.
Project description:Perfluoroalkyl substances have been associated with changes in menstrual cycle characteristics and fecundity, when modeled separately. However, these outcomes are biologically related, and we evaluate their joint association with exposure to perfluoroalkyl substances.We recruited 501 couples from Michigan and Texas in 2005-2009 upon their discontinuing contraception and followed them until pregnancy or 12 months of trying. Female partners provided a serum sample on enrollment and completed daily journals on menstruation, intercourse, and pregnancy test results. We measured seven perfluoroalkyl substances in serum using liquid chromatography-tandem mass spectrometry. We assessed the association between perfluoroalkyl substances and menstrual cycle length using accelerated failure time models and between perfluoroalkyl substances and fecundity using a Bayesian joint modeling approach to incorporate cycle length.Menstrual cycles were 3% longer comparing women in the second versus first tertile of perfluorodecanoate (PFDeA; acceleration factor [AF] = 1.03, 95% credible interval [CrI] = [1.00, 1.05]), but 2% shorter for women in the highest versus lowest tertile of perfluorooctanoic acid (PFOA; AF = 0.98, 95% CrI = [0.96, 1.00]). When accounting for cycle length, relevant covariates, and remaining perfluoroalkyl substances, the probability of pregnancy was lower for women in second versus first tertile of perfluorononanoate (PFNA; odds ratio [OR] = 0.6, 95% CrI = [0.4, 1.0]) although not when comparing the highest versus lowest (OR = 0.7, 95% CrI = [0.3, 1.1]) tertile.In this prospective cohort study, we observed associations between two perfluoroalkyl substances and menstrual cycle length changes, and between select perfluoroalkyl substances and diminished fecundity at some (but not all) concentrations. See video abstract at, http://links.lww.com/EDE/B136.
Project description:Menstrual cycle length (MCL) has been shown to play an important role in couple fecundity, which is the biologic capacity for reproduction irrespective of pregnancy intentions. However, a comprehensive assessment of its role requires a fecundity model that accounts for male and female attributes and the couple's intercourse pattern relative to the ovulation day. To this end, we employ a Bayesian joint model for MCL and pregnancy. MCLs follow a scale multiplied (accelerated) mixture model with Gaussian and Gumbel components; the pregnancy model includes MCL as a covariate and computes the cycle-specific probability of pregnancy in a menstrual cycle conditional on the pattern of intercourse and no previous fertilization. Day-specific fertilization probability is modeled using natural, cubic splines. We analyze data from the Longitudinal Investigation of Fertility and the Environment Study (the LIFE Study), a couple based prospective pregnancy study, and find a statistically significant quadratic relation between fecundity and menstrual cycle length, after adjustment for intercourse pattern and other attributes, including male semen quality, both partner's age, and active smoking status (determined by baseline cotinine level 100 ng/mL). We compare results to those produced by a more basic model and show the advantages of a more comprehensive approach.
Project description:Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape.
Project description:BACKGROUND:There is increasing information characterizing menstrual cycle length in women, but less information is available on the potential differences across lifestyle variables. OBJECTIVE:This study aimed to describe differences in menstrual cycle length, variability, and menstrual phase across women of different ages and BMI among a global cohort of Flo app users. We have also reported on demographic and lifestyle characteristics across median cycle lengths. METHODS:The analysis was run based on the aggregated anonymized dataset from a menstrual cycle tracker and ovulation calendar that covers all phases of the reproductive cycle. Self-reported information is documented, including demographics, menstrual flow and cycle length, ovulation information, and reproductive health and diseases. Data from women aged ?18 years and who had logged at least three cycles (ie, 2 completed cycles and 1 current cycle) in the Flo app were included (1,579,819 women). RESULTS:Of the 1.5 million users, approximately half (638,683/1,579,819, 40.42%) were aged between 18 and 24 years. Just over half of those reporting BMIs were in the normal range (18.5-24.9 kg/m2; 202,420/356,598, 56.76%) and one-third were overweight or obese (>25 kg/m2; 120,983/356,598, 33.93%). A total of 16.32% (257,889/1,579,819) of women had a 28-day median cycle length. There was a higher percentage of women aged ?40 years who had a 27-day median cycle length than those aged between 18 and 24 years (22,294/120,612, 18.48% vs 60,870/637,601, 9.55%), but a lower percentage with a 29-day median cycle length (10,572/120,612, 8.77% vs 79,626/637,601, 12.49%). There were a higher number of cycles with short luteal phases in younger women, whereas women aged ?40 years had a higher number of cycles with longer luteal phases. Median menstrual cycle length and the length of the follicular and luteal phases were not remarkably different with increasing BMI, except for the heaviest women at a BMI of ?50 kg/m2. CONCLUSIONS:On a global scale, we have provided extensive evidence on the characteristics of women and their menstrual cycle length and patterns across different age and BMI groups. This information is necessary to support updates of current clinical guidelines around menstrual cycle length and patterns for clinical use in fertility programs.
Project description:The normal menstrual cycle requires a delicate interplay between the hypothalamus, pituitary and ovary. Therefore, its length is an important indicator of female reproductive health. Menstrual cycle length has been shown to be partially controlled by genetic factors, especially in the follicle-stimulating hormone beta-subunit (FSHB) locus. A genome-wide association study meta-analysis of menstrual cycle length in 44 871 women of European ancestry confirmed the previously observed association with the FSHB locus and identified four additional novel signals in, or near, the GNRH1, PGR, NR5A2 and INS-IGF2 genes. These findings not only confirm the role of the hypothalamic-pituitary-gonadal axis in the genetic regulation of menstrual cycle length but also highlight potential novel local regulatory mechanisms, such as those mediated by IGF2.
Project description:Air pollution can influence women's reproductive health, specifically menstrual cycle characteristics, oocyte quality, and risk of miscarriage. The aim of the study was to assess whether air pollution can affect the length of the overall menstrual cycle and the length of its phases (follicular and luteal). Municipal ecological monitoring data was used to assess the air pollution exposure during the monitored menstrual cycle of each of 133 woman of reproductive age. Principal component analyses were used to group pollutants (PM10, SO₂, CO, and NOx) to represent a source-related mixture. PM10 and SO₂ assessed separately negatively affected the length of the luteal phase after standardization (b = -0.02; p = 0.03; b = -0.06; p = 0.02, respectively). Representing a fossil fuel combustion emission, they were also associated with luteal phase shortening (b = -0.32; p = 0.02). These pollutants did not affect the follicular phase length and overall cycle length, neither in single- nor in multi-pollutant models. CO and NOx assessed either separately or together as a traffic emission were not associated with overall cycle length or the length of cycle phases. Luteal phase shortening, a possible manifestation of luteal phase deficiency, can result from fossil fuel combustion. This suggests that air pollution may contribute to fertility problems in women.
Project description:Ovulatory menstrual cycles are essential for women's fertility and needed to prevent bone loss. There is a medical/cultural expectation that clinically normal menstrual cycles are inevitably ovulatory. Currently within the general population it is unknown the proportion of regular, normal-length menstrual cycles that are ovulatory. Thus, the objective of this study was to determine the population point prevalence of ovulation in premenopausal, normally menstruating women. The null hypothesis was that such cycles are ovulatory.This is a single-cycle, cross-sectional, population-based study-a sub-study of the HUNT3 health study in the semi-rural county (Nord Trøndelag) in mid-Norway. Participants included >3,700 spontaneously (no hormonal contraception) menstruating women, primarily Caucasian, ages 20-49.9 from that county. Participation rate was 51.9%. All reported the date previous flow started. A single, random serum progesterone level was considered ovulatory if ?9.54 nmol/L on cycle days 14 to -3 days before usual cycle length (CL).Ovulation was assessed in 3,168 women mean age 41.7 (interquartile range, [IQR] 36.8 to 45.5), cycle length 28 days (d) (IQR 28 to 28) and body mass index (BMI) 26.3 kg/m2 (95% CI 26.1 to 26.4). Parity was 95.6%, 30% smoked, 61.3% exercised regularly and 18% were obese. 1,545 women with a serum progesterone level on cycle days 14 to -3 were presumed to be in the luteal phase. Of these, 63.3% of women had an ovulatory cycle (n = 978) and 37% (n = 567) were anovulatory. Women with/ without ovulation did not differ in age, BMI, cycle day, menarche age, cigarette use, physical activity, % obesity or self-reported health. There were minimal differences in parity (96.7% vs. 94.5%, P = 0.04) and major differences in progesterone level (24.5 vs. 3.8 nmol/L, P = 0.001).Anovulation in a random population occurs in over a third of clinically normal menstrual cycles.
Project description:To evaluate the impact of the 2006 Massachusetts health reform, the model for the Affordable Care Act, on short-term enrollment and utilization in the unsubsidized individual health insurance market.Seven years of administrative and claims data from Harvard Pilgrim Health Care.We employed pre-post survival analysis and an interrupted time series design to examine changes in enrollment length, utilization patterns, and use of elective procedures (discretionary inpatient surgeries and infertility treatment) among nonelderly adult enrollees before (n = 6,912) and after (n = 29,207) the MA reform.The probability of short-term enrollment dropped immediately after the reform. Rates of inpatient encounters (HR = 0.83, 95 percent CI: 0.74, 0.93), emergency department encounters (HR = 0.85, 95 percent CI: 0.80, 0.91), and discretionary inpatient surgeries (HR = 0.66 95 percent CI: 0.45, 0.97) were lower in the postreform period, whereas the rate of ambulatory visits was somewhat higher (HR = 1.04, 95 percent CI: 1.00, 1.07). The rate of infertility treatment was higher after the reform (HR = 1.61, 95 percent CI: 1.33, 1.97), driven by women in individual (vs. family) plans. The reform was not associated with increased utilization among short-term enrollees.MA health reform was associated with a decrease in short-term enrollment and changes in utilization patterns indicative of reduced adverse selection in the unsubsidized individual market. Adverse selection may be a problem for specific, high-cost treatments.
Project description:OBJECTIVE:To evaluate whether irregular or long menstrual cycles throughout the life course are associated with all cause and cause specific premature mortality (age <70 years). DESIGN:Prospective cohort study. SETTING:Nurses' Health Study II (1993-2017). PARTICIPANTS:79?505 premenopausal women without a history of cardiovascular disease, cancer, or diabetes and who reported the usual length and regularity of their menstrual cycles at ages 14-17 years, 18-22 years, and 29-46 years. MAIN OUTCOME MEASURES:Hazard ratios and 95% confidence intervals for all cause and cause specific premature mortality (death before age 70 years) were estimated from multivariable Cox proportional hazards models. RESULTS:During 24 years of follow-up, 1975 premature deaths were documented, including 894 from cancer and 172 from cardiovascular disease. Women who reported always having irregular menstrual cycles experienced higher mortality rates during follow-up than women who reported very regular cycles in the same age ranges. The crude mortality rate per 1000 person years of follow-up for women reporting very regular cycles and women reporting always irregular cycles were 1.05 and 1.23 for cycle characteristics at ages 14-17 years, 1.00 and 1.37 for cycle characteristics at ages 18-22 years, and 1.00 and 1.68 for cycle characteristics at ages 29-46 years. The corresponding multivariable adjusted hazard ratios for premature death during follow-up were 1.18 (95% confidence interval 1.02 to 1.37), 1.37 (1.09 to 1.73), and 1.39 (1.14 to 1.70), respectively. Similarly, women who reported that their usual cycle length was 40 days or more at ages 18-22 years and 29-46 years were more likely to die prematurely than women who reported a usual cycle length of 26-31 days in the same age ranges (1.34, 1.06 to 1.69; and 1.40, 1.17 to 1.68, respectively). These relations were strongest for deaths related to cardiovascular disease. The higher mortality associated with long and irregular menstrual cycles was slightly stronger among current smokers. CONCLUSIONS:Irregular and long menstrual cycles in adolescence and adulthood are associated with a greater risk of premature mortality (age <70 years). This relation is slightly stronger among women who smoke.
Project description:Age at menarche and menstrual cycle characteristics are indicators of endocrine function and may be risk factors for diseases such as reproductive cancers. The progesterone receptor gene (PGR) has been identified as a candidate gene for age at menarche and menstrual function.Women office workers ages 19-41 self-reported age at menarche and participated in a prospective study of menstrual function and fertility. First-morning urine was used as the DNA source. 444 women were genotyped for a functional variant in PGR, rs1042838 (Val660Leu), and 264 women were also genotyped for 29 other SNPs across the extended gene region.Genetic variation across PGR was associated with age at menarche using a global score statistic (p = 0.03 among non-Hispanic whites). Women carrying two copies of the Val660Leu variant experienced menarche 1 year later than women carrying one or no copies of the variant (13.6 ± 0.5 vs. 12.6 ± 0.1; p = 0.03). The Val660Leu variant was also associated with decreased odds of short menstrual cycles (17-24 days) (OR, 95% CI: 0.54 [0.36, 0.80]; p = 0.002).Genetic variation in PGR was associated with age at menarche and menstrual cycle length in this population. Further investigation of these associations in a replication dataset is warranted.